SPORTS AND ATHLETICS PREPARATION, PERFORMANCE, AND PSYCHOLOGY
COACHING AND MANAGEMENT TECHNIQUES IN ATHLETICS
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SPORTS AND ATHLETICS PREPARATION, PERFORMANCE, AND PSYCHOLOGY
COACHING AND MANAGEMENT TECHNIQUES IN ATHLETICS
JASON A. MORELLI AND
OSCAR D. VELEZ EDITORS
Nova Science Publishers, Inc. New York
Copyright © 2011 by Nova Science Publishers, Inc. All rights reserved. No part of this book may be reproduced, stored in a retrieval system or transmitted in any form or by any means: electronic, electrostatic, magnetic, tape, mechanical photocopying, recording or otherwise without the written permission of the Publisher. For permission to use material from this book please contact us: Telephone 631-231-7269; Fax 631-231-8175 Web Site: http://www.novapublishers.com
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LIBRARY OF CONGRESS CATALOGING-IN-PUBLICATION DATA Coaching and management techniques in athletics / editors, Jason A. Morelli and Oscar D. Velez. p. cm. -- (Sports and athletics preparation, performance, and psychology) Includes bibliographical references and index. ISBN 978-1-62100-119-5 (eBook)_ 1. Coaching (Athletics)--United States. I. Morelli, Jason A. II. Velez, Oscar D. GV711.C587 2011 796.07'7--dc22 2010044710
Published by Nova Science Publishers, Inc. † New York
CONTENTS Preface Chapter 1
Chapter 2
Chapter 3
Chapter 4
Chapter 5
vii A Description and Comparison of Duties and Responsibilities of NCAA Division II Head Baseball and Football Coaches Randy Nichols Fundraising Responsibilities and Expectations of NCAA Division II Head Baseball and Football Coaches Randy Nichols and Carl Bahneman For Love of the Game: The Mediating Potential of Job Satisfaction of College Coaches upon Career Satisfaction Aaron W. Clopton, Tim D. Ryan and Michael Sagas Stress Factors in the Profession of Coaching: Assessing Their Nature, Scope and Impact Deborah A. Yow, James H. Humphrey and William W. Bowden Are Female Coaches Held to a Higher Standard of Athletics Compliance? The Theory of Planned Behavior and NCAA Division I (FBS) Major Recruiting Infractions Robert S. Clark and Paul J. Batista
1
13
25
43
59
vi Chapter 6
Chapter 7
Chapter 8
Chapter 9
Chapter 10
Index
Contents The Coaching Belief Triad: Placing Philosophy Within the Coaching Process Steven C. Barnson and Doris L. Watson
71
Burnout in High School Basketball Coaches from a Reversal Theory Perspective Ryan K. Zapalac, Jay T. Lee and Dale G. Pease
87
Coaching Behavior: Leadership Preferences of Rookie and Veteran College Athletes Christopher M. Keshock and Shelley Bradford In Demand? Examining Sport Management Faculty Openings and Hires Edward (Ted) M. Kian, Paul M. Pedersen and John Vincent An Empirical Examination of the Presence of Minority Managers in Minor League Baseball Braden Holcomb, Kurt A. Stahura and James Busser
107
125
135
153
PREFACE The process of coaching has been conceptualized, studied, and analyzed in a wide variety of ways. The most common theoretical perspective used by researchers has been to view coaching as a decision-making process. Successful coaching has been described as the practice of making correct decisions within the constraints of a highly complex social and dynamic environment. In a general sense, coaches articulate a purpose and establish unique mechanisms for achieving success. This book examines the role of a coach or manager in sports and athletics. Chapter 1 – The purpose of this study was to: (1) describe the duties and responsibilities of NCAA Division II head football and baseball coaches. The data were collected via a survey. Instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree, the majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the role responsibilities of the head coaches outside of coaching varies from teaching, coaching, admissions, residence life and financial aid. The data also revealed that head baseball coaches have more responsibilities outside of coaching than football coaches. Chapter 2 – The purpose of this study was to: (1) describe the fundraising responsibilities and expectations of NCAA Division II head baseball and football coaches. The data were collected via a survey instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II
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head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree. Data indicated that a majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the most successful fund-raising activities for baseball programs are fund-raising events, while football programs raise a higher percentage through solicitation of alumni and individuals with athletic interest. Money raised by these programs was used in somewhat different manners with baseball programs using a majority of the money raised for travel and equipment, while football programs used these funds for equipment, capital improvements and recruiting. Data analysis also revealed that head baseball coaches are expected as part of their contract to raise a higher percentage of operating costs than are football coaches. Chapter 3 – As demands on today‘s coach escalates, the role and presence of job satisfaction increases in significance, as well. Past research has analyzed job satisfaction in both sport and business literature (e.g. Wright, 2006); and linked with diversity (Pastore, 1993; Sagas et al., 2005) and supervisor satisfaction (Chelladurai, 2003). This investigation examined the relationship of supervisor satisfaction with career satisfaction for the coaching sample, a relationship presented in previous research (e.g. Sagas and Cunningham, 2004). Results indicated significant correlations between supervisor, career, and job satisfaction levels (p < .01). An initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches‘ career satisfaction (β = .31, p < .001). A further regression analysis revealed significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence signified the mediating potential of job satisfaction on the relationship between supervisor satisfaction and career satisfaction. Chapter 4 – The coaching profession is most appropriately characterized by the profound uniqueness of its nature. A coach is at once a teacher, a psychologist, a father/mother figure and other roles which he or she finds it expedient or necessary to assume at a given time. Clearly, the college athletic coach labors in a distinctly stressful environment. It is a volatile and often unpredictable profession involving numerous and concurrent pressures. These include the need to continuously interact personally and effectively with his or her student athletes regarding myriads of training, competitive, academic and personal issues. There is also the continuous pressure to recruit and develop a winning team and the need for the coach and players to handle defeat. Add to this relational element with student athletes the human relations which must be maintained with his or her sports supervisor (athletic director, assistant athletic director or associate
Preface
ix
athletic director), the parents of student athletes, individuals in the media, high school coaches, boosters/fans, assistant coaches, athletic department support staff, and myriads of others, then it is seen that the compelling matrix of human relations which must be attended to by the coach (not to mention the personal and family relations which are often challenging to maintain because of the considerable demands and pressure of the profession). Chapter 5 – In this study, NCAA Division I (FBS) recruiting violations were collected from the NCAA Legislative Services Database for the Internet (LSDBi) and analyzed based upon the type of sport, the gender of the studentathletes participating in the sport, and the gender of the head coach from 19872007. The theory of planned behavior (Ajzen, 1991) was used to guide the findings that major recruiting violations are more prevalent among male coaches within revenue sports, which may lead to a higher standard of athletics compliance for female sports and coaches. Chapter 6 – Successful coaching has been described as the practice of making correct decisions within the constraints of a highly complex social and dynamic environment (Abraham and Collins, 1998). Coaches articulate a purpose and establish unique mechanisms for achieving success. However, the specific function a coach‘s belief system plays in the overall coaching process has received limited and fragmented theoretical treatment. Therefore, this paper presents a conceptual framework that coaching professionals can use as a tool to analyze the process of coaching. The framework consists of two key elements: a) a general model of the coaching process, describing coaching as an integrated and dynamic whole and specifying major factors coaches must consider in order to maintain an effective alignment within their sport context; and b) a coaching typology, which describes different patterns of philosophical beliefs used by coaches. This typology, referred to as a Coaching Belief Triad, is introduced to elaborate on the elements of a coaching philosophy. Chapter 7 – Attributes related to burnout potential in high school varsity basketball coaches were investigated using Reversal Theory as a theoretical base (e.g., Apter, 2001). Four hundred coaches, controlled for school size and gender, were randomly selected and mailed a questionnaire which included the Apter Motivational Style Profile (AMSP) (Apter, 1999), Maslach Burnout Inventory (MBI) (Maslach, Jackson, and Leiter, 1996), and a demographic information sheet. Coaches (N= 126) returned usable questionnaires that showed no significant gender or school size differences. It was hypothesized that coaches exhibiting dominances high in telic and conformist dominances would have greater susceptibility to burnout than coaches who are more paratelic and negativistic dominant. This hypothesis was not supported. In
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total, fifteen percent of coaches demonstrated high potential for burnout. Autic sympathy (a transactional pair) had the strongest association with burnout accounting for almost 30% of the total variance. Coaches who exhibited autic sympathy dominance had increased feelings of depersonalization and emotional exhaustion and reduced feelings of personal accomplishment. Chapter 8 – Of all the managerial responsibilities, leadership, which is inextricably intertwined with all the functions a head coach performs, is considered by Chelladurai and Saleh (1980) to be the most significant task executed by a coach. Studies in the area of sports leadership behavior have shown individual athlete effectiveness is largely attributed to the leadership behavior exercised by a coach (Amorose and Horn, 2000; Beam, Serwatka, and Wilson, 2004; Sherman, Fuller, and Speed, 2000; Zhang, Jensen, and Mann, 1997). Using the Leadership Scale for Sports (Chelladurai and Saleh, 1980) the present study revealed certain preferences for coaching behaviors between rookie and veteran athletes competing at the intercollegiate level. Implications drawn from the study suggest college coaches to emphasize certain dimensions of leadership according to the preferences existing amongst rookie and veteran players on a team. Chapter 9 – Over the past 25-30 years, sport management has been among the fastest growing academic disciplines in higher education within the United States. However, the few universities producing sport management doctoral graduates have seemingly been unable to meet the demands for qualified individuals to teach at the university level. This study analyzed each of the 124 professorial advertisements for sport management/administration placed by U.S. universities over a one-year period, encompassing the 2005-06 academic year. The majority of the openings were in the Southeast, Northeast, and Midwest, with few listings in the Southwest or West. Nearly half of all listings were at institutions offering sport management only at the undergraduate level. A phone survey revealed only 69% of advertised positions were filled, with 53% of schools with failed searches citing a lack of desired applicants. A majority of schools that did not hire planned to re-post their positions the following academic year. Chapter 10 – This article attempts to offer some insights relative into: (1) the ratio of minority coaches to minority players within 40 teams of the AAA, AA, and A levels within professional baseball (2) whether minority coaches would be relegated to the less prestigious coaching positions receiving token status within the hierarchical structure of minor league baseball. The data was analyzed using the Chi Square test, the results indicate there are more black
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coaches and fewer Latino coaches than expected based on the number of players within the hierarchical structure of professional baseball. Versions of these chapters were also published in Journal of Contemporary Athletics, Volume 3, Numbers 1, 2, and 4, and Volume 4, Number 1, 2, and 3, edited by Dan Drane, published by Nova Science Publishers, Inc. They were submitted for appropriate modifications in an effort to encourage wider dissemination of research.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 1
A DESCRIPTION AND COMPARISON OF DUTIES AND RESPONSIBILITIES OF NCAA DIVISION II HEAD BASEBALL AND FOOTBALL COACHES Randy Nichols Slippery Rock University and Carl Bahneman West Virginia University, USA
ABSTRACT The purpose of this study was to: (1) describe the duties and responsibilities of NCAA Division II head football and baseball coaches. The data were collected via a survey. Instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree, the majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the role responsibilities of the head coaches outside of coaching varies from teaching, coaching, admissions, residence life and financial aid. The data also revealed that head baseball coaches have more responsibilities outside of coaching than football coaches.
Today‘s coaches are under many pressures (Lyle, 1999). They try to win games, recruit and retain athletes, prepare facilities, raise money, travel to contests
2
Randy Nichols
and perform a variety of other duties assigned by the athletic director (Judd, Kelley, and Pastore, 1993). Many Division II coaches are asked to perform other duties or functions at their institutions, including teaching, student affairs and admissions duties (NCAA, 2003b). As the number of programs expand along with the level of competition, so does the amount of administrative duties performed by the athletic director required for each program. To this end, responsibilities that often were handled by an athletic administrator have now been shifted to head coaches (Jones, 2001). In making this shift, the head coach must accept greater responsibility and accountability for his or her program (Swank, 1995). With little or no administrative, or management experience, the head coach is now expected to complete administrative duties (Protrac, Brewer, Jones, and Hoff, 2000). The role of the coach becomes even more complex when you add teaching or other administrative type activities to his or her coaching assignment. Division II coaches are responsible for teaching, class preparation, advising students, committee work, scholarly activities and all other duties associated with faculty positions and the tenure process as well as all of the administrative duties that go along with coaching. Dual role positions can cause stress because of role ambiguity due to the lack of clear job descriptions and the expectations that go along with both teaching and coaching, along with carrying out policy and raising money (Chu, Segrave, and Becker, 1985).
PROCEDURES Selection of the Participants All of the institutions (n= 122) that offer both baseball and football at the NCAA Division II level were asked by letter to participate in the study.
Selection of the Instrument The questionnaire was designed to assess the demographic framework, including institutional standing, institutional size, and the number of sponsored intercollegiate athletic programs. This information provided the researcher with a brief, yet informative, profile of the participants and the institution. The primary areas examined included the current role responsibilities of the head baseball and football coaches at these institutions. The questionnaire was developed with the help of a panel of coaches from Slippery Rock University. Their comments and
A Description and Comparison of Duties and Responsibilities of NCAA…
3
recommendations were solicited in order that the questionnaire could be refined and develop content validity. The panel received the list of research questions developed by the researcher, and sample survey questions. The panel was asked to develop what they judged to be relevant questions. The questionnaire was then examined for face validity by faculty members of the Slippery Rock University Sport Management Department. Questionnaires were sent to these individuals and they were asked to rate the questions within the instrument using a four point rating system. A four on the rating system indicated that a question was excellent and that it should be retained on the survey. A rating of three indicated a good question and that it could be retained on the survey. A rating of two indicated an average question that could possibly be retained if revised. A rating of one indicated a poor question that should be completely revised or removed from the questionnaire. The samples were returned and examined and the questionnaire was revised according to their comments. The questionnaire is comprised of 40 questions related to demographic information, and the role responsibilities of the head coaches in these programs. Content validity was established by conducting a pilot study using one coach from each of the eight NCAA Division II regions. The coaches who were selected for the pilot study were asked to complete the survey and return it to the researcher within two weeks.
Data Collection A cover letter requesting completion of the survey was sent to the head baseball and football coaches of the NCAA Division II institutions. A thorough explanation of the nature and purpose of the study was provided in the letter along with a self-addressed, stamped envelope. Respondents were assured that all responses would be kept confidential. A two-week deadline was established from the date of the initial mailing and a second letter, along with an additional questionnaire, was sent as a reminder to all participants following the two-week deadline. The data were collected and analyzed by the researcher. In turn, the participants were asked to answer each question thoroughly and accurately, and when necessary, talk about the specific fundraising practices utilized by the baseball and football programs. All respondents were given the opportunity to receive results.
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Randy Nichols
RESULTS Survey Return Rate The participants for this study were head coaches of NCAA Division II baseball and football programs. One hundred and twenty two institutions sponsor baseball and football at the NCAA Division II level. Of the 122 that were mailed to both head baseball and head football coaches, 41 were returned by head baseball coaches for a return rate of 33.6% and a total of 38 were returned by head football coaches for a return rate of 31.1%.
Head Baseball and Football Coaches Demographics Survey questions 1 through 4 provided information regarding head coaches‘ demographics. These items included questions pertaining to the sport coached, ethnic background, age and level of education. Among the coaches who responded, the sport coached distribution was nearly equal with 51.9% (n= 41) head baseball coaches and 48.1% (n=38) head football coaches. Table 1 depicts the sport coached of the head coaches who responded to the survey. Table 1. Sports Coached by Respondents
Baseball Football Total
Frequency 41 38 79
Percent 51.9% 48.1% 100%
Survey responses to ethnic background revealed that the most prevalent ethnicity was Caucasian with 79.7% (n=63). African American was next with 11% (n=11). Table 2 shows the overall composition of the ethnic background among the respondents. Table 3 shows the age ranges of the head coaches who responded to the survey. Results showed that the responses fell into mostly two categories with 49.3% (n=39) in the 25 to 44 age range and 41.7% (n=33) in the 45 to 64 age range.
A Description and Comparison of Duties and Responsibilities of NCAA…
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Table 2. Ethnic Backgrounds of Respondents
Asian African American Caucasian Hispanic Other Total
Frequency 2 11 63 2 1 79
Percent 2.5% 13.9% 79.8% 2.5% 1.3% 100%
Table 3. Age of Respondents Frequency 1 39 33 6 79
18 to 24 25 to 44 45 to 64 64 or older Total
Percent 1.3% 49.4% 41.8% 7.5% 100%
Results about the level of education revealed that 72.2% (n=57) of the coaches who responded had earned a master‘s degree as their highest level of education, while 20.3 % (n=16) had earned a bachelors degree. Table 4 displays the level of education. Table 4. Level of Education of Respondents
Some College Undergraduate Degree Master‘s Degree Doctorate Total
Frequency 1 16 57 5 79
Percent 1.3% 20.3% 72.2% 6.2% 100%
The last demographic item dealt with the winning percentage of respondents. Results from the baseball coaches showed that 53.6% (n=22) had a winning percent of .500 or better, while the results from the football coaches showed a percent of 47.4% (n=18) had a winning percent of .500 or better. Table 5 represents the winning percentage of coaches who responded.
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Randy Nichols Table 5. Winning Percentage of Respondents’ Teams
Baseball Coaches Football Coaches
.000-.300 2
.301-.500 17
.501-.700 19
.701-.900 3
.901-1.000 0
Total 41
3
17
10
8
0
38
College and University Demographics Survey questions 5, 6 and 7 provided information regarding demographics of the colleges and universities in which the coaches were employed. These questions included information on category (private or public), location and enrollment. Results showed that 65.9% (n=27) of the responding baseball coaches are employed at public institutions, and 34.1% (n=14) are employed at private institutions. Results also show that 60.5% (n=23) of the football coaches who responded are employed at public colleges and universities, while 39.5% (n=15) are employed at private institutions. Table 6 depicts these results. Table 6. Public or Private Institutions of Respondents
Baseball Coaches Football Coaches
Public 27 23
Percent 65.9% 60.5%
Private 14 15
Percent 34.1% 39.5%
Survey responses to institution location revealed that 53.7% (n=22) of the baseball coaches are employed at urban institutions, while 36.8% (n=14) of the football coaches are employed at urban institutions. Table 7 represents these findings. Table 7. Institution Location of Respondents
Baseball Coaches Football Coaches Total
Rural 8 10 18
Percent 19.5% 26.3%
Suburban 11 14 25
Percent 26.8% 36.8%
Urban 22 14 36
Percent 53.7% 36.8%
A Description and Comparison of Duties and Responsibilities of NCAA…
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Reponses to institution size show that a high percent of both baseball coaches (34.1%) and football coaches (28.9%) are employed at institutions with student enrollment between 4001 and 6000 students. Table 8 displays the current enrollment status of the institutions where the coaches who responded are employed. Table 8. College and University Enrollment of Respondents
Less than 2,000 2,001 to 4,000 4,001 to 6,000 6,001 to 8,000 8,001 to 10,000 Greater than 10,000 Total
Baseball Coaches 5 6 14 7 4 5 41
Percent 12.2% 14.6% 34.1% 17.1% 9.8% 12.2% 100%
Football Coaches 9 7 11 8 1 2 38
Percent 23.7% 18.4% 28.9% 21.1% 2.6% 5.3% 100%
An analysis of Table 9 reveals that 41.5 % (n=17) of baseball coaches who responded hold faculty rank, while 36.8% (n=14) of football coaches who responded hold faculty rank. Table 9. Head Coaches who Hold Faculty Rank - Baseball and Football Coaches
Baseball Coaches Football Coaches
Frequency 17 14
Percent 41.5% 36.8%
Tables 10 and 11 represent the analysis of the coaching/teaching duties for those baseball and football coaches who responded. An analysis of these results show that a higher percentage of baseball coaches have some teaching responsibilities as part of their contract 31.7% (N=13) when compared to football coaches 26.3% (N=10). Table 12 represents an analysis of coaches who are assigned other duties outside of coaching and/or teaching.
8
Randy Nichols Table 10. Coaching/Teaching Duties - Baseball Coaches
Teach full-time with no release time for coaching Teach full-time with release time for coaching Have no teaching responsibilities Omitted Total
Frequency 2 11 18 10 41
Percent 4.9% 26.8% 44 % 24.4% 100%
Table 11. Coaching/Teaching Duties - Football Coaches
Teach full-time with no release time for coaching Teach full-time with release time for coaching Have no teaching responsibilities Omitted Total
Frequency 0 10 22 6 38
Percent 0.0% 26.3% 57.9% 15.8% 100%
Table 12. Coaches with Other Assigned Duties - Baseball and Football Coaches
Baseball Coaches Football Coaches
Frequency 33 10
Percent 80.5% 26.3%
Table 13 represents the results of the areas in which coaches were assigned additional duties/responsibilities? Coaches‘ response choices were admissions, financial aid, residence life, athletics, intramurals/campus recreation and other. An analysis of Table 18 reveals that 34.1% (n=14) of baseball coaches who responded have additional duties within the athletic department. Table 14 reveals that 15.8% (n=6) of football coaches who responded have additional duties within the athletic department. Coaches were asked if they were required to participate in scholarly activities, (publications and presentations). The response choices were yes or no. Table 15 reveals that 29.3 % (n=12) of the baseball coaches who responded and 23.7% (n=9) of the football coaches who responded are expected to be involved in scholarly activities.
A Description and Comparison of Duties and Responsibilities of NCAA…
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Table 13. Additional Duties - Baseball Coaches Frequency 3 3 5 14 2 4 10 41
Admissions Financial aid Residence life Athletics Intramurals Other Omitted Total
Percent 7.3% 7.3% 12.2% 34.1% 4.9% 9.8% 24.4% 100%
Table 14. Additional Duties - Football Coaches
Admissions Financial aid Residence life Athletics Intramurals Other Omitted Total
Frequency 3 0 1 6 0 0 28 38
Percent 7.9% 0.0% 2.6% 15.8% 0.0% 0.0% 73.7% 100%
Table 15. Involvement in Scholarly Activities - Baseball and Football Coaches
Baseball coaches Football coaches
Frequency 12 9
Percent 29.3% 23.7%
Additionally coaches were asked if they were required to conduct academic advisement for students other than their athletes. The response choices were yes or no. Table 16 reveals that 14.6 % (n=6) of the baseball coaches who responded and 15.8% (n=6) of the football coaches who responded are expected to be involved in academic advisement. Finally, coaches were asked wether or not they advise any student groups (club/organizations) other than their own athletes?
10
Randy Nichols Table 16. Involvement in Academic Advisement – Baseball and Football Coaches
Baseball coaches Football coaches
Frequency 6 6
Percent 14.6% 15.8%
Table 17. Advisement of Student Groups (Clubs/Organizations) – Baseball and Football Coaches
Baseball coaches Football coaches
Frequency 3 1
Percent 7.3% 2.6%
The response choices were yes or no. Table 17 reveals that 7.3% (n=3) of the baseball coaches who responded and 2.6% (n=1) of the football coaches who responded are involved with advising student clubs or organizations.
DISCUSSION An analysis of Table 30 reveals that 41.5 % (n=17) of baseball coaches hold faculty rank, while 36.8% (n=14) of football coaches hold faculty rank, and 31% of the baseball coaches teach full-time with release time for coaching and 26.3% of football coaches teach full-time with release time for coaching. Survey question 31 asked coaches if they had other assigned duties. Results showed that 80.5% (n=33) of baseball coaches had other assigned duties, while only 26.3% (n=10) of football coaches had other assigned duties outside of coaching. These additional duties can be expected to takeaway from time spent on developing a competitive program or enhancing fund-raising endeavors. In reviewing the results, one can see that 34.1% (n=14) of baseball coaches who have additional duties are assigned to those duties within the athletic department. The results also reveal that 15.8% (n=6) of football coaches who have additional duties are assigned within the athletic department; however, 73.7% (n=28) of the football coaches left this question blank, which leads one to believe that most of these coaches are not assigned additional duties. Scholarly activities are usually expected of full-time university faculty, and the results showed that 29.3 % (n=12) of the baseball coaches and 23.7% (n=9) of
A Description and Comparison of Duties and Responsibilities of NCAA… 11 the football coaches are expected to be involved in scholarly activities. These results are considered typical when you look at the fact that 31% (n=13) and 26.3% (n=10) of the baseball coaches and football coaches were considered fulltime faculty. These results represent a workload expectation of coaches in some programs that goes beyond coaching. These additional responsibilities can result in putting coaches in positions with expectations that are in conflict with the time and energy it takes to manage and oversee a NCAA Division II athletic program.
REFERENCES Chu, D., Segrave, J.,and Becker, B.J. (1985). Sport and higher education. Winning and giving. Human Kinetics, Champaign, Il. 114-125. Jones, R.L. (2001) Applying empowerment in coaching. In Developing decision makers: An empowerment approach to coaching (pp.83-94). Innovative Communications. Judd, M., Kelley, B. and Pastore, D. (1993). Reduce and prevent coaching burnout. Strategies, 15-16. Lyle, J. (1999) The coaching process. Oxford, England: Butterworth Heinemann. 272. NCAA. (2003) NCAA division II operating manual. Indianapolis, IN. Potrac, P., Brewer, C., Jones, R. and Hoff, J. (2000). Toward a holistic understanding of the coaching process. Quest, 52, 186-199. Swank, M. (1995). Athletic directors sharing thoughts and actions. Athletic Administration, 21, 26-27.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 2
FUNDRAISING RESPONSIBILITIES AND EXPECTATIONS OF NCAA DIVISION II HEAD BASEBALL AND FOOTBALL COACHES Randy Nichols1 and Carl Bahneman2 1
Slippery Rock University, USA West Virginia University, USA
2
ABSTRACT The purpose of this study was to: (1) describe the fundraising responsibilities and expectations of NCAA Division II head baseball and football coaches. The data were collected via a survey instrument returned by 41 of 122 head baseball coaches and 38 of 122 football coaches surveyed. Demographic data indicated the following: the majority of NCAA Division II head baseball and football coaches are Caucasian between the ages of 25 and 64 and have a master's degree. Data indicated that a majority of head baseball coaches are responsible for coordinating their programs fund-raising efforts while fewer head football coaches have this responsibility, the most successful fund-raising activities for baseball programs are fund-raising events, while football programs raise a higher percentage through solicitation of alumni and individuals with athletic interest. Money raised by these programs was used in somewhat different manners with baseball programs using a majority of the money raised for travel and equipment, while football programs used these funds for equipment, capital improvements and recruiting. Data analysis also revealed that head baseball coaches are expected as part of their contract to raise a higher percentage of operating costs than are football coaches.
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Randy Nichols and Carl Bahneman
Today‘s coaches are under many pressures. They are trying to win games, recruit and retain athletes, prepare facilities, raise money, travel to contests and perform a variety of other duties assigned by the athletic director (Protrac, Brewer, Jones, and Hoff, 2000). Many Division II coaches are asked to perform other duties or functions at their institutions, including teaching, student affairs and admissions duties (NCAA, 2003b). As the number of programs expand along with the level of competition, so does the amount of administrative duties performed by the athletic director required for each program. To this end, responsibilities that often were handled by an athletic administrator including fundraising have now been shifted to head coaches (Jones, 2001). In making this shift, the head coach must accept greater responsibility and accountability for his or her program which includes funding the program sometimes at a substantial level.
PROCEDURES Selection of the Participants All of the institutions (n= 122) that offer both baseball and football at the NCAA Division II level were asked by letter to participate in the study.
Selection of the Instrument The questionnaire was designed to assess the demographic framework, including institutional standing, institutional size, and the number of sponsored intercollegiate athletic programs. This information provided the researcher with a brief, yet informative, profile of the participants and the institution. The primary areas examined included the current fundraising responsibilities and expectations of the head baseball and football coaches at these institutions. The questionnaire was developed with the help of a panel of coaches from Slippery Rock University. Their comments and recommendations were solicited in order that the questionnaire could be refined and develop content validity. The panel received the list of research questions developed by the researcher, and sample survey questions. The panel was asked to develop what they judged to be relevant questions. The questionnaire was then examined for face validity by faculty members of the Slippery Rock University Sport Management Department. Questionnaires
Fundraising Responsibilities and Expectations of NCAA Division II…
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were sent to these individuals and they were asked to rate the questions within the instrument using a four point rating system. A four on the rating system indicated that a question was excellent and that it should be retained on the survey. A rating of three indicated a good question and that it could be retained on the survey. A rating of two indicated an average question that could possibly be retained if revised. A rating of one indicated a poor question that should be completely revised or removed from the questionnaire. The samples were returned and examined and the questionnaire was revised according to their comments. The questionnaire is comprised of 40 questions related to demographic information, and the role responsibilities of the head coaches in these programs. Content validity was established by conducting a pilot study using one coach from each of the eight NCAA Division II regions. The coaches who were selected for the pilot study were asked to complete the survey and return it to the researcher within two weeks.
Data Collection A cover letter requesting completion of the survey was sent to the head baseball and football coaches of the NCAA Division II institutions. A thorough explanation of the nature and purpose of the study was provided in the letter along with a self-addressed, stamped envelope. Respondents were assured that all responses would be kept confidential. A two-week deadline was established from the date of the initial mailing and a second letter, along with an additional questionnaire, was sent as a reminder to all participants following the two-week deadline. The data were collected and analyzed by the researcher. In turn, the participants were asked to answer each question thoroughly and accurately, and when necessary, talk about the specific fundraising practices utilized by the baseball and football programs. All respondents were given the opportunity to receive results.
RESULTS Survey Return Rate The participants for this study were head coaches of NCAA Division II baseball and football programs. One hundred and twenty two institutions sponsor baseball and football at the NCAA Division II level. Of the 122 that were mailed
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to both head baseball and head football coaches, 41 were returned by head baseball coaches for a return rate of 33.6% and a total of 38 were returned by head football coaches for a return rate of 31.1%.
Head Baseball and Football Coaches Demographics Survey questions 1 through 4 provided information regarding head coaches‘ demographics. These items included questions pertaining to the sport coached, ethnic background, age and level of education. Among the coaches who responded, the sport coached distribution was nearly equal with 51.9% (n= 41) head baseball coaches and 48.1% (n=38) head football coaches. Table 1 depicts the sport coached of the head coaches who responded to the survey. Table 1. Sports Coached by Respondents
Baseball Football Total
Frequency 41 38 79
Percent 51.9% 48.1% 100%
Table 2. Individual Responsible for Coordinating Fund-Raising Activities Baseball Coaches
Head Coach Assistant Coach Graduate Assistant Student Assistant Athletic Department Rep. Total
Frequency 33 3 0 0 5 41
Percent 80.5% 7.3% 0.0% 0.0% 12.2% 100%
Responses show that 80.5% (n=33) of baseball coaches are responsible for fund-raising activities for their program, while 55.3% (n=21) of football coaches are responsible for fund-raising for their programs. Baseball coaches responded with 70.7 % (n=29) having fiscal control of money raised, while 81.6 percent (n=31) of football coaches reported having fiscal control.
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Table 3. Individual Responsible for Coordinating Fund-Raising Activities Football Coaches
Head Coach Assistant Coach Graduate Assistant Student Assistant Athletic Department Rep. Total
Frequency 21 6 0 0 11 38
Percent 55.3% 15.8% 0.0% 0.0% 28.9% 100%
Table 4. Fiscal Control of Money Raised
Baseball Coaches Football Coaches
Frequency 29 31
Percent 70.7% 81.6%
Of those coaches who responded, 78% (n= 32) of baseball coaches are expected as part of their contract to raise money, while 60.5% (n=23) of football coaches are expected to raise money. Those coaches who are expected to raise money varied by the amount expected to be raised. Baseball coaches range from 0% to 60%, while football coaches range from 0% to 40%. Tables 5 and 6 report these findings. Table 5. Percentage of Budget that Baseball Coaches are Expected to Raise
0% 10% 15% 20% 25% 30% 40% 50% 55% 60% Total
Frequency 10 3 2 7 4 7 2 3 1 2 41
Percent 24.4% 7.3% 4.9% 17.1% 9.8% 17.1% 4.9% 7.3% 2.3% 4.9% 100%
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The coaches were given nine different events and asked to rank in order their top three events based on success of the event, which was defined as raising at least five percent of their operating budget. These event choices included auction, baseball tournament, golf tournament, raffle, banquet, camps/clinics, food sales, thons (hit, dance, walk/run, etc.), facility rental, and other. Results are based on the number of coaches who completed these items. Table 7 lists the fund-raising events in order of success for baseball programs based on the mean score calculated from the baseball responses of their most successful events. Table 6. Percentage of Budget that Football Coaches are Expected to Raise Frequency 20 4 4 1 3 5 1 38
0% 5% 10% 15% 20% 30% 40% Total
Percent 52.6% 10.5% 10.5% 2.6% 7.8% 13.3% 2.6% 100%
Table 7. Successful Fund-Raising Events - Baseball Coaches Frequency Camp/Clinic Raffle Golf Tournament Thon (marathon game/ Hit-a-thon) Facility Rental Auction Baseball Tournament Banquet Food Sale Other
26 21 20 15
Ranked Order of Success (Mean) 1.7 1.9 2.5 3.8
9 4 3 1 1 0
4.5 0
Table 8 lists the fund-raising events in order of success for football programs based on the mean score calculated from the football responses of their most successful events.
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An analysis of the data indicated fund-raising events were the category used to raise the highest amounts of funds for baseball programs with over 60.9% (n=25) raising over 20% of there operating budget, 10.5 % (n= 4) of the football programs raised over 20% of their budget through fund raising events. Table 8. Successful Fund-Raising Events - Football Coaches
Other (game fee) Other (media guide) Golf Tournament Camp/Clinic Raffle Auction Banquet
Frequency 19 25 24 20 13 6 3
Ranked Order of Success (Mean) 1.4 1.8 2.4 2.6 -
Table 9. Percentage of Operating Budget Raised Through Fund-Raising Events – Baseball
0-10% 11-20% 21-30% 31-40% 41-50% 51-60% Total
Frequency 4 12 8 11 4 2 41
Percent 9.7% 29.3% 19.6% 26.8% 9.8% 4.8% 100%
Table 10. Percentage of Operating Budget Raised Through Fund-Raising Events – Football
0-10% 11-20% 21-30% Total
Frequency 26 8 4 38
Percent 68.4% 21.1% 10.5% 100%
An analysis of the data from question number 23 indicates football programs raised a higher percentage of their operating budget through solicitation of alumni and representatives with athletic interest with 18.4 % (n=7) raising more than 20%
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of their operating budget through this method. Results also showed that 14.6% (n=6) of baseball programs raised 20% or more of their operating budget through solicitation of alumni and representatives with athletic interest. Tables 11 and 12 depict the results from survey question 23. Table 11. Percentage of Operating Budget Raised Through Solicitation of Alumni and Representatives with Athletic Interest – Baseball
0-10% 11-20% 21-30% 31-40% Total
Frequency 29 6 4 2 41
Percent 70.9% 14.8% 9.7% 4.8% 100%
Table 12. Percentage of Operating Budget Raised Through Solicitation of Alumni and Representatives with Athletic Interest – Football
0-10% 11-20% 21-30% Total
Frequency 22 9 7 38
Percent 57.9% 23.6% 18.5% 100%
Table 13. Allocated Budget and Expenses - Baseball and Football
Baseball Football
Allocated Budget (mean) $64,487 $378,736
Expenses (mean) $92,817 $392,789
Percent Difference 32% 4%
Results showed that of those who responded, football programs had a higher allocated budget (mean=$378,736) than did baseball programs (mean=$64,487), which would be expected due to the greater number of players involved with football programs. Results also showed that football programs spent more (mean= $392,789) than did baseball (mean = $92,817). Finally, results show that baseball programs have a higher deficit when the operating budget is compared to the amount spent for both programs, showing that baseball programs on average had
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to fund 32% of the their expenses, while football programs had to fund 4% of their expenses. Table 13 displays these results. Response choices for questions 19, 24 and 27 included athletic scholarships, capital improvements, coaching staff salaries, team travel, equipment, recruitment and other. An analysis of the data indicated that coaches used the money raised in somewhat different manners. Tables 14 and 15 display the use of money raised through fund-raising events. Table 14. Use of Money Raised Through Fund-Raising Events – Baseball
Scholarships Capital Improvements Salaries Travel Equipment Recruiting Other
Frequency 10 10 4 33 30 9 0
Percent 24.3% 24.3% 9.7% 80.4% 73.1% 21.9% 0.0%
Baseball coaches responding to question 19 used money raised through fundraising events primarily for travel 80.4% (n=33) and equipment 73.1% (n=30), while football coaches used money raised through fund-raising events for equipment 57.8% (n=22), capital improvements 39.4% (n=15) and recruiting 31.5% (n=12). It should be noted that respondents could choose more than one category. Table 15. Use of Money Raised Through Fund-Raising Events – Football
Scholarships Capital Improvements Salaries Travel Equipment Recruiting Other
Frequency 11 15 3 14 22 12 0
Percent 28.9% 39.4% 7.8% 36.8% 57.8% 31.5% 0.0%
Baseball coaches responding to question 24 used money raised through solicitation of alumni and individuals with athletic interest primarily for travel
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58.5% (n=24), equipment 58.5% (n=24) and scholarships 36.6% (n=15), while football coaches used money raised through solicitation of alumni and individuals with athletic interest for equipment 52.6% (n=20), capital improvements 31.5% (n=12) and travel 28.9% (n=11). Tables 16 and 17 display the use of money raised through solicitation of alumni and individuals with athletic interest. Table 16. Use of Money Raised Through Solicitation of Alumni and Individuals with Athletic Interest –Baseball
Scholarships Capital Improvement Salaries Travel Equipment Recruiting Other
Frequency 15 9 2 24 24 4 0
Percent 36.6% 22.0% 4.9% 58.5% 58.5% 9.8% 0.0%
Table 17. Use of Money Raised Through Solicitation of Alumni and Individuals with Athletic Interest – Football
Scholarships Capital Improvement Salaries Travel Equipment Recruiting Other
Frequency 11 12 3 11 20 12 0
Percent 28.9% 31.5% 7.9% 28.9% 52.6% 31.6% 0.0%
Table 18. Percentage of Operating Budget Expected to Raise
Baseball Football
Mean + standard deviation 21.88 + 17.9 * 9.06 + 12.6 *
Range (low and high) 0-60 0-40
* Indicates significant difference between groups p<.05.
t value 3.421 3.421
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The mean amount expected to be raised for baseball coaches who responded was 21.88% (sd=17.9), and the mean amount expected to be raised for football coaches who responded was 9.1% (sd=12.6). Analysis of the data shows that responses varied greatly with extreme levels of high and low fund-raising expectations for both baseball and football coaches, which accounts for the high standard deviation levels. The difference in the percentage of the operating budget expected to be raised between baseball coaches and football coaches was statistically significant at the .001 level. Table 18 represents these results.
DISCUSSION The results of this study show that baseball coaches are being expected as part of the job to raise a higher percentage of operating budget and 80.5% (n=33) of baseball coaches are responsible for fund-raising activities for their program while 55.3% (n=21) of football coaches are responsible for fund-raising for their program. 70.7 % (n=29) of baseball coaches who responded have fiscal control of money raised, while 81.6 percent (n=31) of football coaches reported having fiscal control. One can conclude from these findings that baseball coaches are expected to raise a higher percentage of their operating costs, funds raised are used more for essential needs within baseball programs when compared to football programs, baseball coaches have less control of how money raised is used and finally baseball coaches are directly responsible for doing so along with the other duties that are associated with being a head coach and any other duties that may be assigned to them.
REFERENCES Jones, R.L. (2001) Applying empowerment in coaching. In Developing decision makers: An empowerment approach to coaching (pp.83-94). Innovative Communications. NCAA. (2003) NCAA division II operating manual. Indianapolis, IN. Potrac, P., Brewer, C., Jones, R. and Hoff, J. (2000). Toward a holistic understanding of the coaching process. Quest, 52, 186-199.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 3
FOR LOVE OF THE GAME: THE MEDIATING POTENTIAL OF JOB SATISFACTION OF COLLEGE COACHES UPON CAREER SATISFACTION Aaron W. Clopton1, Tim D. Ryan2 and Michael Sagas3 1
Marshall University, USA University of Memphis, USA 3 Texas AandM University, USA 2
ABSTRACT As demands on today‘s coach escalates, the role and presence of job satisfaction increases in significance, as well. Past research has analyzed job satisfaction in both sport and business literature (e.g. Wright, 2006); and linked with diversity (Pastore, 1993; Sagas et al., 2005) and supervisor satisfaction (Chelladurai, 2003). This investigation examined the relationship of supervisor satisfaction with career satisfaction for the coaching sample, a relationship presented in previous research (e.g. Sagas and Cunningham, 2004). Results indicated significant correlations between supervisor, career, and job satisfaction levels (p < .01). An initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches‘ career satisfaction (β = .31, p < .001). A further regression analysis revealed
Correspondence: Aaron W. Clopton, Ph.D. Marshall University, Division of Exercise Science, Sport, and Recreation, One John Marshall Drive, Huntington, WV 25755-2450. E-mail:
[email protected]. (304) 696 – 5405
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence signified the mediating potential of job satisfaction on the relationship between supervisor satisfaction and career satisfaction.
INTRODUCTION The daily experience of a worker‘s employment environment has, not surprisingly, been found throughout past research to significantly impact many affective outcomes that can influence the landscape of the larger profession. Outcomes of a worker‘s experience, including such aspects as job and career satisfaction (e.g. Abraham, 1999; Cotton and Tuttle, 1986; Igbaria and Greenhaus, 1992; Michaels and Spector, 1982), organizational commitment (Davy, Kinicki, and Scheck, 1991; Williams and Hazer, 1986), and turnover intentions (Ding and Lin, 2006; Michaels and Spector, 1982) are a few of the many components that have been significantly linked with such work environmental factors as supervisor support (Durham et al., 1997), teamwork (Griffin, Patterson, and West, 2001), work performance (Bauer and Green, 1996; Vroom, 1964) and workplace accidents (Porac et al., 1983). Protruding most fervently out of the organizational literature is impact of the supervisor, most likely due to the pertinence of their impact upon the structuring of the work environment and their ability to provide information and feedback back to their employees (Griffin et al., 2001). For this reason, the supervisor behavior has been found to significantly impact the affective reactions of team members under them (Durham et al., 1997). Not surprisingly, then, the role of the supervisor has often been penned as a major contributor to job and career satisfaction of the subordinate (e.g. Gerstner and Day, 1997; Greenhaus, Parasuraman, and Wormely, 1990), thus, possessing the ability to shape not only the existence of one‘s department or company, but of the overall profession due to the supervisor‘s ability to directly influence both the professional and organizational commitment (Wakabayashi, Graen, Graen, and Graen, 1988) and the turnover intentions (Abraham, 1999; Greenhaus et al., 1990).
Supervisor Satisfaction Operationally defined here as the relationship between a subordinate worker and his or her supervisor and the perception of the subordinate that the
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relationship positively contributes to his or her career development (Kram, 1985); supervisor satisfaction maintains a consistent influence over many work outcomes. In fact, a tight web connects the aforementioned factors and outcomes such that significant, positive relationships exist between supervisor support/ satisfaction and job and career satisfaction (i.e. Greenhaus et al., 1990) and organizational commitment (Ding and Lin, 2006; Kanter, 1979), while significant negative relationships exist between turnover intentions and supervisor support/satisfaction (Greenhaus, 1987). Further depicting the meticulous relationship is both the mediating (Griffin et al., 2001) and moderating (Erdogan and Enders, 2007) ability of supervisor support upon job satisfaction and working relationships, as well as the mediating role that organization commitment plays between job satisfaction and turnover intentions (Lin and Ma, 2004; Lin and Chen, 2004).
Career Satisfaction On a much broader scope than job satisfaction, career satisfaction besets the all the jobs that an individual has worked (Williamson, Pemberton, and Lounsbury, 2005), or about 100,000 hours for a typical American (Career Strategists, 2006). Thus, career satisfaction includes a wide array of feelings and emotions on all of the experiences related to one‘s career (Lounsbury, Moffitt, Gibson, Drost, and Stevens, 2007). Because of this positive orientation towards one‘s career, then, career satisfaction has often been significantly linked with such outcomes as commitment and turnover (Gupta, Guimaraes, and Raghunathan, 1992; Igbaria, Greenhaus, and Parasuraman, 1991). This same relationship has matriculated through in the coaching profession, as well, with satisfaction with the coaching profession and one‘s career being connected with turnover intention (e.g. Chelladurai, 2003). Notably, coaches have been found to possess moderately-high career satisfaction (e.g. Sagas and Cunningham, 2004) as well as moderately-high or high job satisfaction (Sagas and Cunningham, 2004; Sagas, Paetzold, and Cunningham, 2005).
Job Satisfaction Additionally, job satisfaction has been shown to play a significant secondary role in many relationships in the organization literature. Cogently defined as the extent to which a worker feels positively or negatively about his or her job
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas
(Odom, Boxx, and Dunn, 1990), job satisfaction was discovered to mediate the influences of role conflict and role ambiguity on various facets of organization commitment including affective, continuance, and normative commitment (Yousef, 2002). Todd and Kent (2006) found, using employees from a sporting goods manufacturer, that job satisfaction partially mediated the effect of intrinsically-satisfying tasks on helping behavior, as well as partially mediating the influence of task significance on helping behavior. The same research also established job satisfaction as full mediator upon the relationship between task autonomy and sportsmanship (Todd and Kent, 2006). Other literature in organizational theory have shown job satisfaction to mediate the relations between self-leadership behavioral-focused strategies and team performance (Politis, 2005), positive affectivity and turnover intention (Chiu and Francesco, 2002), as well as moderating the existence between hesitation and self-management performance (Diefendorf, Richard, and Gosserand, 2006). Therefore, any research endeavor into one of the aforementioned job elements, such as satisfaction or role of supervisor, must be prepared to elucidate the roles and position of each element in the relationship. While research in the sport management literature has included the elements of job and career satisfaction and supervisor support (e.g. Clopton, Sagas, and Sosa, 2006), little depth exists that clearly explicates the mediating roles of each work-outcome, specifically for the work environment of intercollegiate athletic coaches. Sagas and Ashley (2000) did, however, discover a differential existence in gender and satisfaction where male coaches exhibited significantly higher levels of job satisfaction than female coaches, something that led to significantly lower levels of turnover intention for the male coaches. Thus, as the ―primary employees of intercollegiate athletics‖ (Chelladurai and Ogasawara, 2003, p. 62), many socio-cultural issues have arisen within the profession college coaching, including gross inequities in gender (Acosta and Carpenter, 2006) and race (Sagas and Cunningham, 2004; Cunningham and Sagas, 2005). Thus, perhaps, further investigation into the work environment of college coaches might illuminate some of the current tribulations of the coaching landscape. The purpose of the current research, then, was to explore the impact of a coach‘s satisfaction with his or her supervisor upon the coach‘s career satisfaction and the extent to which job satisfaction mediated the aforementioned impact.
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THEORETICAL FRAMEWORK Leader-Member Exchange Theory (LMX) The conceptualization for this study was drawn from both the leader-member exchange theory (LMX theory, or LMX; Graen, 1976), and the career satisfaction research model (Jiang and Klein, 2000). One of the earliest leadership theories based upon relationships, LMX suggests that the quality of interaction between both leader and subordinate significantly shapes the work experience and, thus, appropriate work outcomes (Graen, 1976; Graen and Cashman, 1975). When LMX relationships are of high quality, leaders and subordinates share mutual trust, respect, and obligation (Graen, 1976; Graen and Schieman, 1978), and positive support, common bonds, and shared loyalty (Dienesch and Liden, 1986; Graen and Uhl-Bien, 1995). Originating from what organizational literature terms Vertical Dyad Linkages (VDL), LMX theory has focused on the specific connection that leaders form individually with their subordinates (Dansereau,, Graen, and Haga, 1975). The individual dyadic linkage, or relationship, is defined, then, by the exchanges between leader and follower. Inevitably through these relationships, in-groups and out-groups emerge dependent upon the quality with which the leader-subordinate dyads operate (Dansereau et al., 1975; Northouse, 2001). Leaders develop only a select number of followers as their in-group members to function within the work setting, as each leader is constrained by his or her personal resources as a leader (Graen and Uhl-Bien, 1995). With this in-group selection comes a high degree of mutual trust, respect, obligation, and loyalty, to name a few (Dienesch and Liden, 1986). As the ―trusted assistants,‖ in-group members receive more information, influence, and confidence from their leader (Zalensky and Graen, 1987), thus, shaping a much different work experience. It is within this in-group that previous literature has determined potential sources behind the gender and racial inequities in collegiate coaching, including homologous reproduction (Stangl and Kane, 1991) and the similarity-attraction paradigm (Sagas et al., 2005), to list a couple. Regardless, the impetus for most coaching environment research involves, albeit towards a varied extent, some relationship and exchange with a coach and his or her supervisor, or leader. Because of the aforementioned significant relationship between the leader-member exchange and a positive work experience, leaders and supervisors play a direct role in the matriculation of the future work force, thus, possessing the ability to actively shape the potential demography of the profession. What has not been established, though, is to what extent the inherent
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas
satisfaction one derives from the performing their job is able to override the impact that their leader-member exchange has upon their overall satisfaction with their career. Applying the LMX theory of leadership towards today‘s landscape of college coaches, we offer the following initial hypothesis: Hypothesis 1: A significant, positive relationship will exist between the coaches‘ satisfaction with their supervisor and their career satisfaction. LMX has been significantly linked to job satisfaction as a strong, direct relationship (Stringer, 2006) and, indirectly, through perceptions of the degree of empowerment (Sparrowe, 1994), trust in leader (Dirks and Ferrin, 2001), and positive feelings about their work context (Wayne et al., 1997). Notably, job satisfaction has been found to moderate the effects of initial low LMX (Scandura and Graen, 1984), thus further contributing to the satisfaction triumvirate of supervisor, job, and career.
Career Satisfaction Research Model This satisfaction triumvirate has been copiously arranged within the conceptual framework by the career satisfaction research model (Jiang and Klein, 2000). The relationship between the three measures of satisfaction within the model is triplicate, with supervisor support directly influencing the outcome of career satisfaction, a path in accord with LMX. The alternate routes to career satisfaction extend from the supervisor position into, and through, both external career opportunities and internal career anchors (Jiang and Klein, 2000). Here, internal career anchors are defined by the needs, values, and talents that deemed necessary for one‘s career existence. Examples of internal career anchors include autonomy, identity, and security (Delong, 1982; Schein, 1975). A subordinate‘s internal career anchors allow one to envision his or her perceptions of the future, career orientation, impact of work experiences, and more. External career opportunities, then, become defined by an organization‘s ability to bolster the internal career anchors of the individual employee (Jiang and Klein, 2000). Thus, external career opportunities exist within the environment created by the organization. Organizational effectiveness in supporting the internal career anchors of employees, of which supervisors are a part, lies within the organization‘s ability to adjust its structure to meet the needs and desires of its employees (Igbaria and Baroudi, 1993). Accordingly, then, the second path into
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career satisfaction originates from the supervisor and is shaped directly by a subordinate‘s perceptions of external career opportunities. Most notably, though, is mediating influence provided by the third path into career satisfaction. Also originating from the supervisor, a subordinate experiences are shaped by the relationship between one‘s perceived external career opportunities and the extant internal career anchors. It is afterward that the resulting experience defines one‘s career satisfaction (Jiang and Klein, 2000). Using this tertiary path, then, we can deductively operationalize job satisfaction as the extent to which an employee has established quality internal career anchors and by the magnitude to which an employee‘s organization is meeting said anchors by opportunities. Further, because of the significant existence between the ubiquitous job satisfaction measure and both supervisor satisfaction and career satisfaction, job satisfaction will now be expected to supersede the relationship between the coaches‘ supervisor satisfaction and their satisfaction with their career, in accordance with the career satisfaction research model (Jiang and Klein, 2000). Moreover, the intercollegiate athletic coaching profession is a unique profession in that many demands upon personal and family time, personal resources, and more are enacted upon each coach. While a small percentage of today‘s college coach receives overwhelming financial rewards, the vast majority of coaches are drawn to the profession for the love and enjoyment of competing and performing the intricacies of the very job of coaching itself (Chelladurai, 2003). Thus, the following hypothesis is included: Hypothesis 2: Job satisfaction will mediate the relationship between supervisor satisfaction and career satisfaction.
METHODOLOGY Participants As part of a larger study, data were collected through a mailed questionnaire as part of larger study assessing the quality of employment in college coaching. A stratified simple random sample of 800 head coaches were selected to participate in the study (400 men‘s team coaches; 400 women‘s team coaches), and represented coaches from all three NCAA divisions. A total of 261 usable responses were collected after one round of data collection and a mailing to nonrespondents resulted in another 83 responses (N = 344, 43.1% response rate). To assess potential response bias, we tested differences between early and late
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas
responders. No significant mean differences were noted between the early and late respondents on any of the main study variables. The three NCAA divisions were represented in the usable sample in a proportion similar to that of the general population (Division I = 123; Division II = 76; Division III = 145, see DeHass, 2003). The age of the responding coaches ranged from 23 to 73, and the male coaches were older (M = 44.41, SD = 11.35) than female coaches (M = 36.56, SD = 8.85). In addition to the amount of organization tenure, male coaches in the sample possessed more years as a college coach (M = 13.75, SD = 9.00) than the women in the sample (M = 12.01, SD = 8.09). Finally distinguishing the two genders of the respondents, males were more likely to be married, with 74.8% of the male respondents reporting to be married where a mere 34% of female respondents were married. Further, the sampling of head coaches had been at their current college or university over nine years (M = 9.42; SD = 8.28) and in their current supervisor-head coach dyad for five years (SD = 4.60). Moreover, 71.2% of the male head coaches were in gender-similar dyads (N = 178) while only 37.2% of the female head coaches worked under a female supervisor (N = 35). It should be noted that no differences were found in gender or NCAA division echoing the sentiments of past literature (Pastore, 1993).
Survey Instrumentation The survey instrument contained a series of questions assessing numerous outcomes related to the quality of employment as an intercollegiate coach in the NCAA. The supervisor satisfaction, job satisfaction, and career satisfaction measures were embedded within the larger survey instrument. The concept of supervisor satisfaction was measured with a four-item scale exploring the perceptions each head coach held on his or her supervisor (Spector, 1985). The questions included such items as ―My supervisor is quite competent in doing his/her job‖ and ―My supervisor is unfair to me,‖ and provided a highly-reliable estimate (α=.93). To establish the presence of job satisfaction, the three-item Overall Job Satisfaction Questionnaire was used (Cammann et al., 1983). The job satisfaction variable was also determined to be highly-reliable (α = .91). The Overall Job Satisfaction Questionnaire included items like ―In general, I am satisfied with my job.‖ Finally, the career satisfaction variable was determined by the five-item Career Satisfaction Scale (Greenhaus et al., 1990), such items as ―I am satisfied with the success I have achieved in my career.‖ The career satisfaction measure was also established with acceptable reliability (α=.81).
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Data Analyses Initially, descriptive statistics were ran to obtain demographical information on the respondents regarding age, education level, gender, marital status, and coaching experience. The research question then explored, using linear regression, the relationship of perceived supervisor satisfaction and the resultant career satisfaction of the coaches. To investigate the mediating potential of job satisfaction on the predictability of supervisor satisfaction upon career satisfaction, Pearson correlations were obtained between the dependent variable (career satisfaction), the independent variable (supervisor satisfaction) and the potential mediator (job satisfaction). Results were calculated via Sobel‘s test to determine possible mediation (Baron and Kenny, 1986; Preacher and Hayes, 2004; Sobel, 1982).
RESULTS Results indicated significant bivariate correlations between supervisor, career, and job satisfaction levels (p < .01), and are given in Table 1. In the testing of the first hypothesis, an initial regression analysis displayed a significant presence of supervisor satisfaction in predicting coaches' career satisfaction (β= .31, p < .001, R2 = .10). This supported the first hypothesis. In examining the mediating effects of job satisfaction on the relationship of supervisor support to career satisfaction of college coaches, as predicted in the second hypothesis, four separate conditions needed to be satisfied, as suggested by Baron and Kenny (1986). The first two steps were to find significant relationships between the predictor variable and the outcome variable, and the predictor variable and the mediator. Again, Table 1 shows these significant relationships. Additionally, the first step was also satisfied by the first regression analysis used to test Hypothesis 1. The next step is to include the mediating variable, job satisfaction, along with the predictor variable, supervisor support, in the linear regression to predict the outcome, career satisfaction. This analysis revealed significant predictability of job satisfaction when added to the model (β = .50, p < .05). This presence negated the significant presence of supervisor satisfaction in the relationship, thus, suggesting the mediating potential of job satisfaction on the relationship between supervisor satisfaction and career satisfaction (R2 = .27). Confirming hypothesis 2 that job satisfaction mediated the relationship between supervisor support and career satisfaction.
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas
Table 1. Descriptive Statistics, Correlations, and Reliability Estimates of All Variables Used in Analysis (N= 344)
Notes. * p< .01. Reliability estimates given in diagonal.
Table 2. Results of Regression Analysis
Notes. *p < .05. ** p< .01.
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DISCUSSION The aims of this study were to explore the impact of a coach‘s satisfaction with his or her supervisor upon the coach‘s career satisfaction, and to specifically examine the extent to which job satisfaction mediated the aforementioned impact. As was expected through the initial hypothesis, the satisfaction with supervisor by the responding coaches significantly impacted the coaches‘ career satisfaction. This finding concurred with both the LMX and the career satisfaction research models, in addition to previous organizational literature (e.g. Gerstner and Day, 1997; Greenhaus, Parasuraman, and Wormely, 1990). More importantly, though, the supervisor satisfaction-career satisfaction relationship, as predicted in hypothesis 2, was superseded by the by mediating influence of the coaches‘ job satisfaction. This finding adds to the widely-established mediating ability of job satisfaction in organizational literature (e.g. Politis, 2005; Todd and Kent, 2006).
Implications Because of the connection between career satisfaction and turnover intention, a greater impetus for control of the coaching landscape is placed within the control of today‘s intercollegiate athletics administrator. Not only does the administration impact career satisfaction through support, but by shaping the job description of the coach, thus, impacting the amount of satisfaction the coach has with his or her specific coaching position. Further responsibility might be distributed, as well, into the hands of national coaching associations i.e. NABC, AFCA, NFCA, etc. Here, the national coaching associations are charged with enhancing their respective coaching professions through support and education. Perhaps, now aware of the ability of job satisfaction to mediate relationships with career satisfaction, thus influencing rates of turnover intention and impacting the coaching profession, a more profound examination into the factors that influence job satisfaction will ensue. This examination should, potentially, rank higher than other items on a coaching association‘s agenda, such as sport structure, playing rules, or sport promotion. Findings from this article might also provide additional insight into perpetual inequities in the intercollegiate coaching profession (e.g. Acosta and Carpenter, 2006). It should be noted that satisfaction levels were fairly high and that there were no significant differences in levels of satisfaction between the male and female coaches. This finding is both refuted in past literature (Sagas and Ashley, 2000) and supported (Pastore, 2003; Sagas et al., 2005). Sagas and Ashley (2000)
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Aaron W. Clopton, Tim D. Ryan and Michael Sagas
discovered that male coaches recorded significantly higher levels of job satisfaction than their female counterparts, and displayed significantly lower levels of occupational turnover intention. While no significant gender differences existed here, the inevasible discrepancy between male and female coaching numbers does (see Acosta and Carpenter, 2006). While it was beyond the scope of the current study, future research should examine more thoroughly the multifaceted construction of job satisfaction for male and female coaches. A similar approach would be merited for race in the coaching profession, as well.
Limitations and Future Directions The use of the sample of head coaches exists as a potential limit upon the external validity of the findings. The mean organizational tenure of the respondents was nearly nine years, indicating at least a moderate level of job satisfaction. Utilizing a sample with graduate assistants and assistant coaches might offer more diverse results, particularly if the coaches had shorter organizational or professional tenures. In the same vein, the head-coach sample limited the results as we were unable to reach out towards those coaches that had either left the profession due to lack of job or career satisfaction. For further exploration, the internal career anchors of the career satisfaction research model (Jiang and Klein, 2000) should be more fully-integrated and applied towards the coaching profession. Ideas of identity, autonomy, and more are imperative towards the individual in the coaching profession and, therein, might contain potential gender and racial differences for which past sport management literature has searched. A larger sampling of intercollegiate coaches would also make possible the ability to disaggregate the sample of respondents by level NCAA affiliation. Potential differences in perceived gender discrimination or perceived promotional opportunities between the three broad NCAA divisions (I, II, and III) would be able to illuminate the culture of athletics at each level that might contribute to such differential outcomes. Additionally, care needs to be taken when interpreting any questionnaire results, especially those cross-sectional in nature. In an attempt to control for common method variance, several questions were reversed scored. Additionally, care needs to be used when interpreting the results. While the results suggest satisfaction with supervisor may lead to career satisfaction through job satisfaction, alternative interpretations are possible. One possibility may be that those who are satisfied with their career choice may find their work environment
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more pleasant. This could lead to higher rating of satisfaction with coworkers, including a supervisor. While the sample involved college coaches, we would suggest that the findings would generalize past college coaches, but also to high school and professional coaches. At the high school level, this may be of significance to athletic directors and school administration as a reduction in coaching migration may reduce general turnover for teachers (Ryan and Sagas, 2006). It is further suggested here as the results in this study reinforce Jiang and Klein‘s (2000) findings for information technology professionals that the findings are generalizable to much of the working population. Future work, both within sport and outside sport, should continue examining internal and external career anchors through the testing of the Career Satisfaction Research Model (Jiang and Klein, 2000). Additionally, as mentioned above, potential difference in career anchors for those from different race, gender, backgrounds, etc., should be examined. While this study examined the effect of satisfaction with supervisor, further work needs to be done on how the different needs and backgrounds of workers affect their perceived satisfaction with a supervisor. Finally, the general quality of work life for coaches needs to continually be explored through a variety of methods. It is suggested that qualitative work be used to deepen the understanding of the specific ways that supervisory support effects satisfaction with the supervisor. Moreover, examine specific factors within athletic departments and schools that lead to dissatisfaction which may affect career satisfaction. It is suggested that quantitative methods be used to examine the broadness of phenomena discovered through qualitative exploration.
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Gupta, Y.P., Guimaraes, T, and Raghunathan, T.S. (1992). Attitude and intentions of information center personnel. Information Management, 22, 151-160. Igbaria, M. and Baroudi, J.J. (1993). A short form measure of career orientations: A psychometric evaluation. Journal of Management Information Systems, 10(2), 131-154. Igbaria, M., Greenhaus, J.J., and Parasuraman, S. (1991). Career orientations of mis employees: An empirical analysis. MIS Quarterly, 15(2), 151-169. Jiang, J.J. and Klein, G. (2000). Supervisor support and career anchor impact on the career satisfaction of the entry-level information systems professional. Journal of Management Information Systems, 16(3), 219-240. Kanter, R.M. (1979). Differential access to opportunity and power. In Alvarez, R. (Ed.) Discrimination in Organizations. San Francisco: Jossey-Bass. 52-68. Kram, K.E. (1985). Mentoring at work: Developmental relationships in organizational life. Glenview, IL: Scott Foresman. Liden, R.C., Wayne, S.J., and Stilwell, D. (1993). A longitudinal study on the early development of leader-member exchanges. Journal of Applied Psychology, 78(4), 662-674. Lin, C.P. and Chen, M.F. (2004). Career commitment as a moderator of the relationships among procedural justice, perceived organizational support, organizational commitment, and turnover intentions. Asia Pacific Management Review, 8, 71-98. Lin, C.P. and Ma, H.C. (2004). Effects of leader-member exchange, job satisfaction, and organizational commitment on diagnosing employee job performance using career stage as a moderator. Asia Pacific Management Review, 9, 79-99. Lounsbury, J.W., Moffitt, L., Gibson, L.W., Drost, A.W., and Stevens, M. (2007). An investigation of personality traits in relation to job and career satisfaction of information technology professionals. Journal of Information Technology, 22, 174-183. Michaels, C.E. and Spector, P.E. (1982). Causes of employee turnover: A test of the Mobley, Griffeth, Hand, and Meglino Model. Journal of Applied Psychology, 67, 53-59. Northouse, P.G. (2001). Leadership theory and practices (2nd ed) Thousand Oaks, CA: Sage. Odom, R.Y., Boxx, W.R., and Dunn, M.G. (1990). Organizational culture, commitment, satisfaction, and cohesion. Public Productivity and Management Review, 14(2), 157-168. Ogasawara, E., and P. Chelladurai. (1998, June). Gender Differences in Job Satisfaction and Commitment Among NCAA Coaches. Paper Presented at the
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Annual Meeting of the North American Society for Sport Management, Buffalo, NY. Pastore, D.L. (1993). Job satisfaction and female college coaches. Physical Educator, 50(4), 216-222. Politis, J.D. (2006). Self-leadership behavioral-focused strategies and team performance: The mediating influence of job satisfaction. Leadership and Organizational Development Journal, 27(3), 203-216. Porac, J.F., Ferris, G.R. and Fedor, D.B. (1983). Job satisfaction and performance. Academy of Management Journal, 26, 285-296. Preacher, K. J., and Hayes, A. F. (2004). SPSS and SAS procedures for estimating indirect effects in simple mediation models. Behavior Research Methods, Instruments, and Computers, 36(4), 717-731. Sagas, M. and Ashley, F. B. (2001). Gender differences in the intent to leave coaching: The role of personal, external, and work-related variables. International Journal of Sport Management, 2, 297-314. Sagas, M., Cunningham, G.B., and Ashley, F.A. (2000). Examining the women‘s coaching deficit through the perspective of assistant coaches. International Journal of Sport Management, 1, 267-282. Sagas, M. and Cunningham, G.B. (2004). The impact of supervisor support on perceived career outcomes of the senior woman administrator. International Journal of Sport Management. 5(3), 229-242. Sagas, M., Paetzold, R., and Cunningham, G.B. (2005). Effects of dyad demographic diversity on the job satisfaction experienced by assistant coaches. International Journal of Sport Management, 7, 141-159. Scandura, T. and Graen, G.B. (1984). Moderating effects of initial leadermember exchange status on the effects of a leadership intervention. Journal of Applied Psychology, 69, 428-436. Schein, V. E. (1975). The relationship between sex role stereotypes and requisite management characteristics among female managers. Journal of Applied Psychology, 60, 340-344. Snyder, C.J. (1990). The effects of leader behavior and organizational climate on intercollegiate coaches‘ job satisfaction. Journal of Sport Management, 4, 5970. Sobel, M.E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. In Leinhardt, S. (Ed.), Sociological Methodology 1982, Washington, D.C.: American Sociological Association. 290-312. Sparrowe, R.T. (1994). Empowerment in the hospital industry: An exploration of antecedents and outcomes. Hospitality Research Journal, 17, 51-73.
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Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 4
STRESS FACTORS IN THE PROFESSION OF COACHING: ASSESSING THEIR NATURE, SCOPE AND IMPACT Deborah A. Yow1, James H. Humphrey1 and William W. Bowden2 1
2
University of Maryland, USA Strategic Management Associates, USA
ABSTRACT The coaching profession is most appropriately characterized by the profound uniqueness of its nature. A coach is at once a teacher, a psychologist, a father/mother figure and other roles which he or she finds it expedient or necessary to assume at a given time. Clearly, the college athletic coach labors in a distinctly stressful environment. It is a volatile and often unpredictable profession involving numerous and concurrent pressures. These include the need to continuously interact personally and effectively with his or her student athletes regarding myriads of training, competitive, academic and personal issues. There is also the continuous pressure to recruit and develop a winning team and the need for the coach and players to handle defeat. Add to this relational element with student athletes the human relations which must be maintained with his or her sports supervisor (athletic director, assistant athletic director or associate athletic director), the parents of student athletes, individuals in the media, high school coaches, boosters/fans, assistant coaches, athletic department support staff, and myriads of others, then we see the compelling
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Deborah A. Yow, James H. Humphrey and William W. Bowden matrix of human relations which must be attended to by the coach (not to mention the personal and family relations which are often challenging to maintain because of the considerable demands and pressure of the profession).
THE ESSENCE OF COACHING The essence of coaching is the balance between being caring, motivational, supportive, and approachable, while maintaining the firm discipline, strategic drive and uncompormising determination to require of student athletes the academic and competitive excellence which also characterize the work of outstanding college coaches. Again, effective human relations are as important to a coach‘s long term success and respect as his or her command of the game itself. Clearly, coaching intercollegiate sports demands many more competencies than just being able to teach a specific skill. It is possible that some coaches might be unable to physically and psychologically cope with the stress resulting from the human demands on their energy, emotions and time. At the same time, however, it is clear that coaching as a profession can be as enjoyable and fulfilling as it can be frustrating and difficult. Successful coaches accept the rigors of their profession while they also recognize their own strengths and weaknesses. Although they are constantly striving for improvement and development, they maintain a healthy level of self-affirmation. As a result, they remain psychologically well adjusted and successful a majority of the period of their coaching careers, while also experiencing the inevitable sense of vulnerability from time to time. Indeed, most coaches admit to the fact that their jobs can be fraught with a variety of mild to quite serious stress inducing factors. In order to assess the scope and impact of these and other stress inducing factors, the authors conducted a comprehensive survey of stress among collegiate coaches and in the college athletic environment. The results are discussed extensively in the book by the authors entitled, Stress In College Athletics: Causes, Consequences and Coping (along with a thorough examination of stress among athletic administrators and student athletes, published by Haworth Press). Here, we will examine the causes and consequences of stress among collegiate coaches and then discuss a variety of their attempts to cope with this stress.
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CAUSES OF STRESS We obtained firsthand from coaches themselves those factors which induced the most stress, their consequences and how they attempt to cope with them. This was accomplished by simply requesting that they identify those factors connected with their jobs that were most stressful for them, how this stress affected them, and how they attempted to cope with this stress. Obviously, this resulted in a large mass of data. It was helpful to sort out the stressors and place them into a number of kinds or classifications. The difficulty encountered in attempting to devise a seamless system for classification of the coaches‘ stressors was the fact that it is sometimes not possible to fit an identified stressor in one exclusive classification because it may touch upon or overlap another kind of stressor. However, an attempt was made to do so and the results indicate that the classifications are representative of the kinds of responses received from collegiate coaches. The following predominant classifications of coaches‘ stressors were identified: Players; Performance/ Results; Outside Influences; Time; Associates; Public Relations; Finance.
Student Athletes/Players There is no question that those who participate on an athletic team are its most important asset. Anyone knows that without the proper material (adequate player personnel) coaches would not be able to consistently produce competitively successful teams. But many coaches are in the profession because of the personal satisfaction they derive from dealing with the young men and women with whom they are associated, whatever their skill level. It is not uncommon for coaches to refer to team members and others closely associated with them as a ―family.‖ And, even though in most families the members love and respect each other, at the same time they can be stressful to one another. So it is not surprising that players are frequently a significant stressinducing factor for coaches. Indeed, in this stress classification (players), 85 percent of the coaches reported sources of stress. These stressors are identified in the following list of subclassifications, with the descriptors of this and each of the other areas stated in the words of the coaches. 1. Player Behavior and Attitude. This was a serious stressor for coaches as evidenced by the fact that 38 percent of the player stressors were in this category. The things that stressed coaches the most in regard to player behavior and attitude were the following:
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Deborah A. Yow, James H. Humphrey and William W. Bowden • • • • • • • • • •
Apathy and indifference of players. Social problems such as the need for drug testing. Players behaving improperly or unlawfully on campus and in the local community. Insubordination of players. Dissensions among players. Selfishness of players. Any kind of team conflict. Players not accepting responsibility for their own actions. Lack of maturity of players. Players who do not have the best interest of the team.
2. Recruiting. It is not surprising that 22 percent of player stressors are found in this category. Coaches were not only stressed by the general aspect of recruiting, but specific aspects were stated as follows: • • • •
Failing to sign the top athletes. Not getting your quota of recruits. The last two days of recruiting are especially stressful. Rejecting people who expect to be recruited.
3. Academic Performance of Players. Seventeen percent of the player stressors were in this category. It is well known that numerous troubling and even scandalous incidents in college athletics have been related to academic issues. Among the stressors for coaches were: • • • •
Players not interested in graduating. The stress of keeping players eligible to participate. Players failing to progress academically. Cheating on examinations or otherwise receiving fraudulent grades.
4. Player Performance. Coaches are concerned about how their players perform and 15 percent of the stressors were in this category. Among the most important were: • • •
Players not performing to their potential. Not getting the best effort or attitude from players. Difficulty in motivating players to perform.
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• Excuses of players for not performing well. • Lack of dedication and commitment of players. 5. Injuries. Coaches worry about injuries to players–both in regard to the success of the team and their feelings and concern for their players. Eight percent of the stressors were in this category and as might be expected the majority of concerns regarding injury were among football coaches.
Finally, it should be mentioned that the player-coach stress factor is a natural phenomenon. This is to say that in most instances the same sort of relationship prevails among most caretakers or custodians with persons who are in their charge. Studies show that physicians and nurses are stressed by patients, teachers are stressed by students, prison guards are stressed by inmates, and further that conditions precipitating long-term stress are essentially the same for all of these groups.
Performance/Results This category of stressors pertains to the performance of the coach himself or herself. In this classification a notable 74 percent of the coaches reported sources of stress. This classification overlaps to some extent with performance of players, but for the most part involved the coach‘s own feeling about his or her ability and performance. No attempt was made to make subclassification because of the difficulty in doing so. Coaches stated these examples of performance-related stressors: • • • • • • • • •
Inability to produce consistently winning teams. The frustration of not having practices which get us ready for what must be done in games. Game day performance. Losing games that should have been won. Not winning the big game. Losing games on chance factors or circumstances that were perceived as beyond the control of the coach. Waiting for the kickoff before a game. High expectations not met. Game day participation/performance of coach.
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Deborah A. Yow, James H. Humphrey and William W. Bowden
Outside Influences Included here is any individual who is outside the immediate group of team members, coaches and others who have a close working relationship with the team such as trainers, managers, chaplains, and team physicians. A remarkable 56 percent of the coaches reported stressors in this classification. Included among such stressors stated were: • • • • • • • • • •
Reactions of alumni and other fans. Not being able to please administrators. Officiating. Hate mail. NCAA rules and policies. Dealing with unqualified people trying to run my job. Things that are controlled by others. Criticism that is unwarranted. Outside influences on athletes such as drugs, alcohol and agents. Faculty members who do not accept the value of athletics in the total university program.
Time In most studies of occupational stress well over one-fourth of the respondents cite factors related to time as serious causes of stress. One half of this number say there is insufficient time for planning and about one-third of them say there is not enough time in the day to do the job expected of them. Notably, 38 percent of the coaches reported stressors in this classification. Such stressors included in their statements were: • • • • • •
Not having enough time for family. Not enough time to get everything done. Time and priority allocations. Abundance of time-consuming travel required. Meeting deadlines. Not enough time for players‘ needs.
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Associates Success in any endeavor, coaching included, depends upon the cooperation of group members. In the present context associates are identified as the assistants to the head coach. It was surprising to find that 32 percent of the coaches reported this classification as a cause of stress. Most coaches maintain firm control and good relationships in dealing with staff members, but according to our findings this is clearly not always the case. In fact, one coach made this statement: ―Much stress is created by groups within the staff itself. Selfishness is a key to stressful situations. The less selfishness within the staff, the less stressful situations are seen.‖ The following were stated most stressful in this category: • • • • • • • •
Getting personalties of the program to work together. Unpleasant interpersonal relationships with staff. Treating conflicts among staff members. Lack of communication with staff. Staff placing their recruits ahead of needs of the team. Motives of associates. Motivating staff. Hiring and maintaining a stable staff.
Public Relations Twenty-one percent of the coaches reported some aspect of public relations as being stressful. The stressors were related to the areas identified by these coaches in their following statements: • • • • • • •
Misunderstanding by the media and public. Lack of media understanding and printing the truth. Media innuendo. Dealing with time demands of the media. Dealing with time demands of the public. Being in public after losing a game. Boosters, alumni and fans who don‘t have a clue.
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Deborah A. Yow, James H. Humphrey and William W. Bowden
Finances A majority of coaches feel that the financing of athletic programs is mainly the responsibility of others and only 12 percent of them reported this classification as a source of stress. A few coaches indicated that they felt stress due to the lack of money for their programs and others said they were under stress to win in order to finance other sports. The preceding discussion of the data on stress-inducing factors was presented as an aggregate to include all coaches who provided responses. At this point it seems appropriate to cite these comparative data for female coaches and male coaches. The information in Table I is provided for this purpose. Table I. Comparison of Stressors for Female and Male Coaches Stress Classification
Percent for Females
Percent for Males
Players
90
83
Performance
90
67
Outside Influences
50
58
Time
50
33
Associates
20
38
Public Relations
6
29
Finances
10
13
It would be speculative at best to offer reasons for the differences between female and male coaches. Each reader will interpret the results individually. However, we would comment on the significant difference in the stressor classification of Public Relations. We have discussed this with selected female coaches who feel that they generally do not have enough media attention nor sufficiently pervasive or vigorous public interest for these sources to create significant stress. (It is possible that indeed this lack of attention for their sport could be a potential stressor for a number of females. Again, however, this would be speculation since the study did not focus on this issue.)
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CONSEQUENCES OF STRESS The effect that stress has on coaches can be classified into the following two broad areas: (a) impact on physical health, and (b) impact on mental/emotional health. Forty seven percent of the coaches perceived an impact on their physical health while more than half of them said that stress impacted their mental/emotional health. The following statements by coaches indicate how it affected them physically. • • •
It affects me physically with loss of sleep. Stress will have an influence on my eating habits and sleeping. Very often stress causes me to have an upset stomach.
Regarding its effect on mental/emotional health a number of coaches commented as follows. • • •
Sometimes I have an emotional outburst against the team and I hate myself for it after it is over. I get terribly frustrated when I lose and it takes me too long to get over it. It causes me to get angry with no really good reason for it.
Only about 10 percent of the coaches said that stress did not bother them. They made such comments as the following. • • •
Stress in coaching can be handled with a systematic daily routine of spiritual nourishment; therefore it does not bother me. Stress is greatly overrated. If you are organized and have a plan you should not be stressed. I never feel any stress in coaching; however, maybe I experience it but don‘t know that I‘m experiencing it.
COPING WITH STRESS We learned that the coping techniques of coaches fell into what can be called coping behaviors and coping techniques.
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Deborah A. Yow, James H. Humphrey and William W. Bowden
Coping Behaviors Regarding the coping behaviors inherent in the basic principles of living, the following results of the study were apparent.
Principle #1: Practicing Good Personal Health Habits The imposing work load of a coach may cause him or her to neglect the basic requirements that are essential for the human being to maintain an adequate functional health level. (Recall how stress had an effect on the physical health of some coaches.) Fifty-six percent of the coaches said they abided by this principle in attempting to cope with the stress of their profession. This leaves almost half of them who are neglectful of some aspect of their personal health. Principle #2: Learnt to Recognize and Value Your Own Accomplishments Sometimes coaches do not accept or assume enough credit for their own performance and achievements. (See previous comment under performance as a cause of stress for coaches.) Twenty-six percent of the coaches said that they practiced this principle of valuing their own achievements as a means of coping with stress. Principle #3: Learn to Take One Thing at a Time Some coaches are likely to put things off, especially unpleasant things, and as a consequence frustrations can build as tasks pile up. An important solution to this for coaches is the practice of taking one task or problem at a time. We are all familiar with coaches who also talk about ―taking one game at a time.‖ Budgeting of time can also help eliminate serious worries related to time urgency and the feeling of ―too much to do in too short a time.‖ Sixty-one percent of the coaches indicated that they practiced this principle in order to diminish the stress under which they were functioning. Principle #4: Learn to Take Things Less Seriously Often a coach will take the loss of a game too seriously. It is important to remember this single truism: A game that has been lost can never be won no matter how much a coach may fret or agonize over it. Those coaches who are able to keep the challenges of their profession and specific losses in perspective and to see the humorous side of various situations tend to look at a potentially stressful situation more objectively. Clearly, this can assist in keeping stress levels lower. Forty-seven percent of the coaches said they attempt to abide by this principle.
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Principle #5: Do Things for Others It can be stated unequivocally that most coaches try to do a considerable amount on behalf of their players. That in itself, as well as other acts of assisting individuals in some way, can help to relieve coaches from stress. Generally, this is a principle of human nature. Fifty-three percent of the coaches said that they practiced this principle in order to relieve stress. Principle #6: Talk Things Over with Others One coach commented that it could be a good idea for coaches to get together in order to have a dialogue about the stressful conditions of the profession. It is important to keep in mind that such discussion should best be positive and objective lest it degenerate into idle gossip. Of course there is value sometimes in simply venting frustrations or fears regarding challenges, problems, and issues. Three-fourths of the coaches said they practiced this principle and in most instances they talked issues over with family members or close friends. These were the prevailing six life principles practiced by coaches in coping with stress.
Coping Techniques Coaches were asked to identify those techniques they used in attempting to deal with stress. These techniques involved the following methods. Three techniques which are specifically used for inducing a relaxation response–muscle relaxation, meditation, and biofeedback; they also used the techniques of physical exercise, recreational activities, resorting to divine guidance, and consumption of alcoholic beverages. The three techniques for inducing a relaxation response were as follows: 17 percent used muscle relaxation, 3 percent used meditation, and less than 1 percent used biofeedback. Eighty-six percent of the coaches engaged in physical exercise as a means of reducing stress. However, the majority said that this was done more or less sporadically. Half of the respondents said they engaged in recreational activities, including such activities as reading, card games and listening to music. Slightly more than half of the coaches resorted to divine guidance and the following are representative statements in this regard. •
In dealing with stress, I put my faith in God.
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Deborah A. Yow, James H. Humphrey and William W. Bowden • •
A personal commitment to Christ is my central theme, and the only way I have been able to lessen stress. When I feel stressed I personally draw peace and strength from my relationship with the Lord.
Ten percent of the coaches said they used alcohol with some regularity in order to cope with the stress of their work. Simply stated, individuals dealing with the problems of stress differ, techniques for dealing with stress differ, and what might be successful for one person might not be necessarily so for another. Finally, the information presented in Tables II and III is intended to make comparisons of female and male coaches in terms of the procedures they use to cope with stress. Table II reflects a comparison of the ―application of principles of living,‖ and Table III presents ―specific coping techniques.‖ Again, the reader is left to his or her own judgment regarding the reasons for the differences. It is not entirely clear which of the genders in the coaching profession is more sensitive to or susceptible to stress reactivity, or which of the interventions are most useful. In the absence of completely objective evaluative criteria, such questions will remain difficult to answer. Table II. Comparison of Female and Male Coaches in the Application of Principles of Living to Avoid Stress Principle
Percent for Female
Percent fo Male
45
60
27
40
Taking One Thing at a Time
67
60
Taking Things Less Seriously
45
48
Doing Things for Others
45
36
Talk Things Over With Others
78
72
Observation of Personal Health Practices Recognizing Your Own Accomplishments
Stress Factors in the Profession of Coaching
55
Table III. Comparison of Female and Male Coaches for Specific Stress-Reducing Techniques TechniquePhysical Exercise Recreational Activities
Percent for Female
Percent fo Male
Physical Exercise
91
84
Recreational Activities
36
56
Muscle Relaxation
18
16
Meditation
0
4
Biofeedback
0.2
0.4
Divine Guidance
55
56
Use of Alcohol
8
12
What is very clear is that coaches function under considerable stress and that among a significant percentage of college coaches this stress is pervasive and almost unrelenting. In February 1999 the Iowa State Legislature presented the University of Iowa‘s retiring head football coach, Hayden Fry, with a ceremony and Resolution of Appreciation for his 18 years of service to the institution and the state. Coach Fry‘s final season had ended several weeks before, but one of his compelling statements at the ceremony was, ―I‘m trying to learn how to relax." Coaches across the profession would understand his statement–after his 18 excellent years at Iowa, following his successful years at Southern Methodist University and previous experiences. Clearly, it was only after he was out from under the unrelenting stress of the coaching profession that he was at last finding an opportunity ―...to relax.‖ Coaches, in general, will understand the full dimension of that statement.
ACCOUNTABILITY FOR STUDENT ATHLETE WELFARE One notable current movement in the NCAA is the viable and pervasive emphasis on student athlete welfare. Among the several emphases of this movement are the physical, academic and personal welfare of the college athlete. This trend represents an important recognition of the accountability that the athletic department, the institution and the coaching staff must accept to assure
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that in every way possible each athlete will be viewed as a person of value and importance beyond the court and playing field–that they are worthy of everyone‘s best effort to see that they develop and succeed as an individual and as a student. But authentically great coaches have for decades accepted this role and this accountability. In July 1954 coach Brutus Hamilton, respected track coach at the University of California at Berkeley, wrote a recruiting letter to an outstanding high school runner named Don Bowden. It reflected his commitment to the welfare and total development of the student athlete and his commitment to ―coaching the whole person.‖ ―There is not much I can add to what I told you when you last visited the campus. You know pretty well what kind of a coach I am, since we have visited together and since you heard me speak at your meeting there in San Jose. You know our facilities, our schedule, and you know the prestige of the university as an educational institution. There can be no degree more coveted than one earned here. I think you know, too, that we have a healthy attitude toward sports here at Berkeley. We want our boys to win; we want them to maximize their potentialities in sports, but we don’t want them doing so at the expense of the more serious phases of college life [italics added]. Your principal purpose in going to college, of course, is to get an education in your field of study which will probably be medicine. If you can break the world‘s record in the half-mile, which seems quite likely to me, while doing this, well and good. The main thing, however, is to be graduated a capable, self-reliant young man which your parents and friends want you to be. I can assure you that we here in the Athletic Department will do everything possible to see that your goals are achieved.‖
Don Bowden enrolled at the University of California at Berkeley, was a successful student and became the first American to run the mile in under 4 minutes (on June 1, 1957). Likewise, in 1999 the highly conscientious head football coach at the University of Maryland expressed his commitment to the welfare of his student athletes when he said, ―I measure my success not solely by our wins on the field, but also by our young men winning in the classroom and in life. That is our firm and uncompromising goal and we will not settle for less.‖ (Coach Ron Vanderlinden, College Park, Maryland, February 1999.) The kind of accountability embraced by these and many other college coaches clearly adds to the scope of responsibility and the stress of the profession, but they indicate that it also presents an opportunity for the job of coaching to take on a more meaningful and personal dimension.
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57
We have discussed in some depth the stressors which challenge college coaches, the results or consequences of these stressing factors, and the ways in which coaches attempt to cope with stress in their professional experience. The findings are interesting and compelling – and indicate the prevalence of mild to very serious stress among collegiate coaches. The results of this study will also be quite helpful to athletics administrators who interface with coaches and, of course, to coaches themselves.
ABOUT THE AUTHORS Deborah A. Yow, Director of Athletics at the University of Maryland, has authored numerous articles and books and is a nationally respected leader and athletics administrator. Dr. Yow has served as a member of the NCAA Management Council and other prestigious athletics and educational agencies and commissions. She has served as President of the National Association of Collegiate Directors of Athletics and currently serves as President of the Division IA Athletic Directors Association. James H. Humphrey, Professor Emeritus at the University of Maryland has authored or coauthored more than a dozen books about stress, including Stress in Coaching. His articles and research reports have appeared in more than 20 national and international journals and magazines. Considered a pioneer in stress education, he is the founder and editor of Human Stress: Current Selected Research and editor of the 16-book series on Stress in Modern Society. William W. Bowden is President of Strategic Management Associates, an education and business consulting firm which has worked with dozens of colleges, universities, corporations and the NCAA in their athletics interests and their management challenges. He served previously as a university administrator and is the author of more than 40 research reports, articles and books.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 5
ARE FEMALE COACHES HELD TO A HIGHER STANDARD OF ATHLETICS COMPLIANCE? THE THEORY OF PLANNED BEHAVIOR AND NCAA DIVISION I (FBS) MAJOR RECRUITING INFRACTIONS Robert S. Clark and Paul J. Batista Texas A&M University, Texas, United States of America
ABSTRACT In this study, NCAA Division I (FBS) recruiting violations were collected from the NCAA Legislative Services Database for the Internet (LSDBi) and analyzed based upon the type of sport, the gender of the student-athletes participating in the sport, and the gender of the head coach from 1987-2007. The theory of planned behavior (Ajzen, 1991) was used to guide the findings that major recruiting violations are more prevalent among male coaches within revenue sports, which may lead to a higher standard of athletics compliance for female sports and coaches.
INTRODUCTION In an introductory press conference for former Indiana men‘s basketball coach Kelvin Sampson, the University President stated that Sampson ―will
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comply fully with NCAA regulations" (ESPN, 2008). A few years prior to this press conference, the NCAA Infractions Committee wrote that they were ―troubled by [Sampson‘s] conscious decision to violate NCAA recruiting legislation‖ while previously coaching at Oklahoma (LSDBi 1, 2008). Although he was not fired after his first commission of major recruiting infractions, Sampson and his assistants once again violated multiple NCAA recruiting bylaws at Indiana which led to his subsequent termination from Indiana. Months later, both the Athletic Director and the Director of Athletics Compliance at Indiana resigned after the NCAA deemed that the university failed to monitor the actions of its basketball program. In the same conference four years earlier, Minnesota head women‘s basketball coach Cheryl Littlejohn was fired days after an institutional investigation of committing NCAA major recruiting infractions (LSDBi 1, 2008). This particular incident was different than Sampson‘s because this was her first major recruiting infraction, she is female, and was immediately fired upon investigation of the infraction, unlike Sampson who was not immediately fired. Could gender be a factor for Coach Sampson retaining his employment longer than Coach Littlejohn? This study examines the nature of major recruiting violations in relation to gender, sport, and behavioral controls in NCAA Division I Football Bowl Subdivision (FBS) athletics programs. Table 1.Major recruiting violations by sport and gender Sport
Football Basketball Baseball/Softball Tennis Track Soccer Cross Country Gymnastics Lacrosse / Field Hockey Wrestling Rifle Swimming
% all violations
% of male violations
% of female violations
% with male coach
% with female coach
% with female coach within women‘s sport
27.27 32.58 3.03 4.54 17.42 3.03 2.27 2.27
33.96 32.09 3.77 4.72 13.20 1.89 0.94 0.94
X 34.62 0 3.85 34.61 7.69 7.69 7.69
100 90.70 100 100 100 100 100 100
0 9.30 0 0 0 0 0 0
X 44.44 X 0 0 0 0 0
% female coach fired or resigned after violation X 75 X X X X X X
0.77 4.54 0.77 1.51
0.94 5.66 X 1.89
0 X 3.85 0
100 100 100 100
0 0 0 0
X X 0 X
X X X X
Are Female Coaches Held to a Higher Standard of Athletics Compliance? 61 In order to address the issue of gender and NCAA recruiting violations, it is important to analyze the organizational behaviors that lead to access and treatment discrimination within intercollegiate sports organizations as well as the set of beliefs that lead to researchers interpreting these behaviors through a theoretical lens. The theory of planned behavior (Ajzen, 1991) is used to predict and clarify human behavior (Sagas, Cunningham, & Pastore, 2006). There are three key components that comprise this theory: a) attitude toward a particular behavior, b) subjective norms experienced by social pressure to perform a function, and c) perceived behavioral control with regard to the execution of a particular behavior or function (Ajzen, 1991). It is through these three components that the connection between gender, types of sports, and NCAA recruiting infractions can be elucidated. First, attitude toward recruiting rules greatly influences perception of gender roles in NCAA recruiting. In 2001, the Knight Commission stated that over half of Division I programs were placed on NCAA sanctions or probation leading to a reduction of scholarships, television coverage, or limiting participation in the post-season. According to this evidence, violating NCAA legislation seems to be normal behavior comparative to obedience to these laws (Knight Commission, 2001; Mahony, Fink, & Pastore, 1999). Despite NCAA Article 13, which stipulates what recruiting actions are permissible, many universities have adopted a ―win-at-all-costs‖ attitude and neglect to follow the provisions of NCAA recruiting legislation (Langlett, 2003). Gender deviance research has further stratified the difference between male and female recruiting violations as Rhodes & Fischer (1993) found that males engage in more serious delinquent behaviors than female counterparts. In addition, athletic directors perceive that men‘s revenue sports, like football, have higher needs due to high operating costs (Patrick, Mahony, & Petrosko, 2008). These attitudes of men and women in Division I (FBS) sports lead to differing expectations where women‘s sports must be compliant with NCAA legislation and men‘s revenue generating sports perceive the rules more like suggestions. Second, a major difference between men‘s revenue sports (i.e. football and men‘s basketball) and all other sports are the subjective norms experienced by social pressure to win games. Researchers of unethical behavior in higher education assert that external pressures of university employees encourage ethical lapses (Goodstein, 2002; Howe & Moses, 1999; Kelley & Chang, 2007). Humphreys & Ruseski (2006) found that there is financial incentive to violate NCAA legislation. While recruiting infractions bring sanctions that limit scholarships of athletic programs, winning games help increase revenues for entire athletic departments and simultaneously benefit the universities
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(Humphreys & Ruseski, 2006). Winning programs often fill stadiums with money-paying ticket holders and increase applications to universities, which then can then increase the prestige of the university‘s athletic program by increasing the talent of student-athletes that attend the institution (Humphreys & Ruseski, 2006; Chressanthis & Grimes, 1993). There is also greater incentive for universities not winning championships to violate NCAA legislation than consistent winning programs, as the aforementioned financial benefits exceed the NCAA sanctions (Fleisher, Shughart, Tollison, & Goff, 1988). Although coaches may excel in other areas of higher education like increasing application rates, ultimately if the coach does not have a winning team he or she will be fired (Bruening & Lee, 2002). This pressure prompts the expectations that a coach will do what it takes to get a ―competitive edge‖ on opposing teams and the belief that everyone else is doing the same. Unfortunately, this competitive edge can lead to the violation of NCAA Article 13. The third aspect of planned behavior in recruiting is perceived behavioral control with regard to the execution of recruiting violations. Hegarty and Sims (1978) found that by increasing the severity of NCAA enforcement penalties, the number of violations will decrease. However, since the inception of the Bowl Championship Series, a typical sanction of the NCAA is scholarship limitations placed upon the infracting university (Sutter and Winkler, 2003). NCAA Bylaw 19.01.1 states that the purpose of NCAA sanctions is to ensure the compliance of its member institutions with the associated legislation and to eliminate NCAA violations (NCAA, 2008). However, if the punishments for rules violations are not sufficiently severe for the offending party, there is no deterrent to prevent future violations from occurring. As a matter of fact, Depken & Wilson (2004) found that the greatest financial impact of NCAA sanctions in football violations cases was felt by non-football sports, thus inciting a greater desire for compliance in sports that are not football and providing little incentive to football programs in executing compliant recruiting policies.
DATA COLLECTION The NCAA has compiled a database of all NCAA infractions which is known as the Legislative Services Database for the Internet (LSDBi). The LSDBi contains the written decisions of all major infractions of NCAA legislation from 1954 to the present and lists the institution responsible for the violation, the date of infraction, and the nature of the infraction. By utilizing the information from the LSDBi, all major recruiting violations of Article 13 from 1987-2007 were
Are Female Coaches Held to a Higher Standard of Athletics Compliance? 63 collected. Then, data was categorized by sport, the gender of the student-athletes participating in the sport, and the gender of the head coach.
ANALYSIS Violations By Sport While football and basketball generate over 70% of most athletics departments‘ annual revenue (Humphreys & Ruseski, 2006), they also account for over half of all major recruiting infractions. Men‘s and women‘s basketball combined for 32.58% of all major recruiting violations, whereas football accounted for 27.27%. Men‘s basketball and football are considered the ―revenue generating sports‖ (Mahony & Hums, 2005), but are not the only sports that where major recruiting infractions are committed. Indoor and outdoor track and field accounted for 17.42% of major recruiting violations. The remainder of the sports were each responsible for 4.54% or less of the total major recruiting violations. In terms of sport classification, there are three distinct groups that commit major recruiting violations from the least-compliant (football and basketball) to somewhat-compliant (track and field) to mostly-compliant (tennis, baseball, softball, soccer, cross country, gymnastics, lacrosse, wrestling, swimming, and rifle).
Male Recruiting Violations From 1987-2007, over 80% of all major recruiting violations were committed by individuals within men‘s sports. Much like the overall trend in Division I (FBS) major recruiting infractions, there are three distinct groups of rules violators in men‘s sports. First, football and men‘s basketball account over 66% of all major recruiting infractions in male sports. The second group consists of track and field, which was associated with 13.2% of all men‘s major recruiting violations. The final group consists of tennis, baseball, softball, soccer, cross country, gymnastics, lacrosse, wrestling, and swimming. Each sport had a percentage below 6%. Other NCAA Division I (FBS) sponsored men‘s sports such as archery, badminton, bowling, equestrian, fencing, ice hockey, skiing, and water polo were not associated with major recruiting violations. Accordingly, in men‘s sports, the major recruiting violations were mostly committed within the revenue generating sports of football and men‘s basketball. Clearly, many male
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coaches of revenue sports have established an attitude of noncompliance with NCAA Article 13 compared to non-revenue sports.
Female Recruiting Violations Individuals associated with women‘s sports committed about 20% of all major recruiting violations from 1987-2007. Of these violations, there were also three groups of sports. First, women‘s basketball and track accounted for over 69% of all women‘s major recruiting violations. The second group, soccer, cross country, and gymnastics, each committed 7.69% of all female major recruiting infractions. Finally, of the total women‘s major recruiting violations, tennis and rifle each committed 3.85%. In women‘s sports, the major recruiting infractions were mostly committed by basketball and track coaches.
Gender of Coach and Recruiting Violations Men coached 97% of the teams that committed major recruiting infractions from 1987-2007. Since most of the major recruiting violations were committed by men‘s teams, it is not astonishing that the majority of coaches are male. Only women‘s basketball had some female head and assistant coaches that committed major recruiting infractions. In women‘s tennis, rifle, gymnastics, cross country, soccer, and track, all of the violating coaches were males. In basketball, 90.7% of all of the coaches of a team with a major recruiting infraction from 1987-2007 were men and 9.3% were women. Approximately 44.4% of women‘s basketball coaches involved in a major recruiting infraction were female. Furthermore, one year after committing each of these violations, 75% of all female women‘s basketball coaches involved had been fired or resigned (Fink, 2003; Associated Press, 2008; Voepel, 2006). Not only are female coaches in the minority of those that commit major recruiting violations, an automatic sanction for a major recruiting infraction by a female coach is termination of employment or forcible resignation. While several male coaches were also fired following major recruiting infractions, an astounding majority of female coaches were either fired or forcibly resigned. Accordingly, there are clearly different expectations for male coaches, in terms of compliance with NCAA Article 13, than there are for female coaches.
Are Female Coaches Held to a Higher Standard of Athletics Compliance? 65
IMPLICATIONS A dichotomy of recruiting legislation compliance has been established from 1987- 2007 based on gender. In the theory of planned behavior, this execution of compliance or noncompliance relies heavily upon the attitudes and expectations surrounding recruiting infractions. These expectations and attitudes are different for revenue sports (e.g. football and men‘s basketball), than non-revenue sports (e.g. women‘s basketball, softball, soccer, track, etc.). Since over 59% of all major recruiting violations are committed by men‘s basketball and football, and over 70% of the athletics department revenue is generated by these sports (Humphreys & Ruseski, 2006), the expectation for these two sports is to win. Winning games increases ticket sales and tangential attendance revenues, and increases conference distributions from NCAA Tournament games and bowl revenue. This financial expectation of winning has put coaches in a position to ―win-at-all-costs,‖ thus providing justification for non-compliant recruiting practices. The pressure to win in non-revenue sports like women‘s tennis or men‘s lacrosse does not have the same financial implications as winning in basketball and football; therefore, the expectations and attitude of administrators and coaches is total compliance to recruiting bylaws in NCAA Article 13. It is not realistic to recommend lower expectations of winning for men‘s basketball and football programs. However, there are substantial implications of this research to compliance directors in Division I (FBS) athletics departments. Huston and Sakkab (2006) stated that an innovative organization will know what to look for in order to best serve its constituents. Following this model, compliance directors need to search for recruiting violations first in football, basketball and track, then focus upon the other sports. In terms of coaches, athletics directors should demand compliance of all coaches, but be aware that male coaches are responsible for 97% of all major recruiting violations. Another implication of this research is the effectiveness of NCAA sanctions for major recruiting violations. Although previous research has indicated that severe penalties have decreased future violations (Hegarty & Sims, 1978), the current method of scholarship reduction may not be the proper punishment. Future research should address this issue using the data from LSDBi. Also, coaches are currently able to change jobs after committing major recruiting violations with little repercussion. Coach Sampson committed major recruiting violations at Oklahoma prior to his major violations at Indiana. As a result of his actions, he switched jobs twice, was given a $750,000 buyout of his Indiana contract, and became the assistant head coach for the NBA‘s Milwaukee Bucks (ESPN, 2008). Thus, the minimal repercussion of coaches‘ disregard for recruiting legislation
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demonstrates that the NCAA expects universities to bear the brunt of the sanctions instead of the individuals involved. Pursuant to NCAA Bylaw 19.02.1, coaches and universities attempting to hire coaches with a background of infractions can be given a ―show-cause order‖ by the NCAA. Here, the institution must demonstrate why recruiting limitations should not be placed the coach. Thus, the burden of compliance rests upon the institution and the ―win at all costs‖ mentality is further promulgated because revenue sports‘ coaches are not held accountable for their violations of recruiting rules.
CONCLUSION Because recruiting violations are prevalent among male coaches within revenue sports, expectations or attitudes toward the behavior of recruiting violations based upon gender vary. In the revenue sports‘ ―win-at-all-costs‖ mantra, these recruiting violations are almost considered normative behavior (Knight Commission, 2001; Mahony et al, 1999). This study confirms that female coaches are held to a higher standard for athletics compliance in recruiting. Furthermore, an increased social pressure with this higher standard enhances the subjective norms of female coaches to be compliant. Thus, the perceived behavioral control is established where women coaches that cause a major recruiting infraction are more likely to have their employment terminated immediately following a violation, much like Coach Littlejohn. On the other hand, female and non-revenue sports mostly follow the rules due to respect or fear of the repercussions of violating NCAA recruiting legislation. Therefore, the execution of compliant recruiting tactics follows the attitudes and expectations that female and non-revenue sports must be compliant. Although women‘s basketball and track are more prone to have alternative attitudes toward compliance to recruiting in comparison to other female sports, women‘s basketball and track often follow the planned behavior of female and non-revenue sports. Thus, this research can assist athletic administrators in making ethical decisions based upon situations where recruiting violations incite a dilemma of gender equitable treatment in intercollegiate sports administration. Huston and Sakkab (2006) suggest several other potential actions that innovative organizations that could take in ethical decision making. Once athletic directors know where to look for recruiting violations, they need to leverage their networks, distribute and screen ideas for coaches, and promote openness to external ideas (Huston & Sakkab, 2006). Networks could include compliance directors from other universities inside or outside of the member conference. By
Are Female Coaches Held to a Higher Standard of Athletics Compliance? 67 establishing networks, compliance directors can ask colleagues questions regarding recruiting legislation encountered by others that could assist compliance directors in their pursuit of ethical athletic conduct. This practice promotes openness to external ideas throughout the NCAA member institutions. Compliance directors can also proactively seek to understand the perspectives of male and female coaches to garner support and find practical solutions to curtail future major recruiting infractions. These ideas can shape positive attitudes toward athletic compliance, establish the expectations of the social environment in the athletic department regarding recruiting practices, and offer suggestions to ease the enactment of ethical recruiting practices among both male and female coaches. Thus, an implementation of the theory of planned behavior in recruiting policies and procedures for athletic departments could influence coaches‘ behavior and possibly curtail future recruiting violations.
Figure 1.Theory of planned behavior in recruiting
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REFERENCES Agle, B. R., & Kelley, P. C. (2001). Ensuring validity in the measurement of corporate social performance: Lessons from corporate United Way and PAC campaigns. Journal of Business Ethics, 31, 271–284. Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50, 179-211. Associated Press news services (February 13, 2008). Ex-Fresno State accepts reduced discrimination award. Retrieved on February 7, 2009 from http://sports.espn.go.com /ncw/news/story?id=3244177. Bruening, J.E. & Lee, M.Y. (2007). The university of Notre Dame: An examination of the impact and evaluation of brand equity in NCAA division I-A football. Sport Marketing Quarterly, 16, 38-48. Chressanthis, G.A. & Grimes, P.W. (1993). Intercollegiate sports success and first-year student enrollment demand. Sociology of Sport Journal, 10, 286300. Depken, C.A. & Wilson, D.P. (2004). ―The cost of probation in Division IA college football.‖ in Economics of College Sports, eds. J. Fitzel and R. Fort. Arlington, TX. ESPN.com new services (February 15, 2008) NCAA lists 5 major violations; IU AD 'profoundly disappointed‘. Retreived on May 3, 2008 from http://sports.espn.go.com/ncb /news/story?id=3243793 ESPN.com news services (May 2, 2008). Sampson set to sign as Milwaukee assistant. Retrieved on May 3, 2008 from http://sports.espn.go.com/nba /news/story?id=3378617 Fink, A. (2003, September 4). Chicago State hoops fires ex-gophers coach Littlejohn. Minnesota Daily. Retrieved from http://old.mndaily.com/articl es/2003/09/04/46374. Fleisher, A.A., Shughart, W.F., Tollison, R.D., & Goff, B.L. (1988). Journal of Economic Behavior and Organization, 10, 433-451. Hegarty, W. H., and Sims, H. P., Jr. (1978). "Some determinants of unethical decision behavior: An experiment." Journal of Applied Psychology, 63, p. 451-457. Howe, K. R., & Moses, M. S. (1999). Ethics in educational research. Review of Researchin Education, 24, 21–60.
Are Female Coaches Held to a Higher Standard of Athletics Compliance? 69 Humphreys, B.R. & Ruseski, J.E. (2006). Financing intercollegiate athletics: The role of monitoring and enforcing NCAA recruiting regulations. International Journal of Sport Finance, 1,151-161. Huston, L. & Sakkab, N. (2006). Connect and develop: inside Procter & Gamble‘s new model for innovation. Harvard Business Review, 3, 1-10. Kelley, P.C. & Chang, P.L. (2007). A typology of university ethical lapses:types, levels of seriousness, and originating location. The Journal of Higher Education, 78(4), 402-429. Knight Foundation-Commission Intercollegiate Athletics (2001). A call to action: Reconnecting college sports and higher education. Charlotte, NC. Langlett, George (2003). The relationship between recruiting and team performance in Division IA College Football. Journal of Sports Economics, 4(3), 240-245. Legislative Services Database for the Internet by the National Collegiate Athletic Association (2007). Major Infractions Cases. Retrieved on January 4, 2008 from https://goomer.ncaa.org/wdbctx/LSDBi/LSDBI.home Legislative Services Database for the Internet by the National Collegiate Athletic Association (2007). Secondary Infractions Cases. Retrieved on January 4, 2008 from https://goomer.ncaa.org/wdbctx/LSDBi/LSDBI.home Mahony, D. F., Fink, J., & Pastore, D. (1999). Ethics in intercollegiate athletics: Anexamination of NCAA violations and penalties-1952-1997. Professional Ethics, 7(2), 53-74. Mahony, D.F. & Hums, M.A. (2005). Bases for determining need: Perspectives of intercollegiate athletic directors and athletic board chairs. Journal of Sports Management, 19, 170-192. Morgan, B. L., Korschgen, A., & Gardner, J. (2001, Fall). The ethics of faculty behavior:Students‘ and professors‘ views. College Student Journal, 418–422. National Collegiate Athletic Association (2007). Secondary Infractions SelfReporting. Retrieved on October 20, 2007 from, http://www2.ncaa.org/portal/ legislation_ and_governance/compliance/secondary_infractions_self_reporting.html National Collegiate Athletic Association Division I Manual (2008). Indianapolis , IN.Patrick, I.S.C., Mahony, D.F., Petrosko, J.M. (2008). Distributive justice in intercollegiate athletics: An examination of equality, revenue production, and need. Journal of Sport Management, 22 (2), 165-183. Rhodes, J.E. & Fischer, K. (1993) Spanning the gender gap: Gender differences in delinquency among inner-city adolescents. Adolescence, 28(112), 879-885.
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Sagas, Cunningham, & Pastore, (2006). Predicting head coaching intentions of male and female assistant coaches: An application of the theory of planned behavior within sport organizations. Sex Roles, 54, 695-705. Sutter, D. & Winkler, S. (2003). NCAA scholarship limits and competitive balance in college football. Journal of Sports Economics, 4(1), 3-18. Voepel, M. (November 12, 2006). Geralds, Lawless lead Purdue into 2006-07. Retrieved on February 6, 2009 from http://sports.espn.go.com/ncw/ preview2006/columns/story? columnist=voepel_mechelle&id=2653712.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 6
THE COACHING BELIEF TRIAD: PLACING PHILOSOPHY WITHIN THE COACHING PROCESS Steven C. Barnson and Doris L. Watson University of Nevada, Las Vegas, NV, USA
ABSTRACT Successful coaching has been described as the practice of making correct decisions within the constraints of a highly complex social and dynamic environment (Abraham and Collins, 1998). Coaches articulate a purpose and establish unique mechanisms for achieving success. However, the specific function a coach‘s belief system plays in the overall coaching process has received limited and fragmented theoretical treatment. Therefore, this paper presents a conceptual framework that coaching professionals can use as a tool to analyze the process of coaching. The framework consists of two key elements: a) a general model of the coaching process, describing coaching as an integrated and dynamic whole and specifying major factors coaches must consider in order to maintain an effective alignment within their sport context; and b) a coaching typology, which describes different patterns of philosophical beliefs used by coaches. This typology, referred to as a Coaching Belief Triad, is introduced to elaborate on the elements of a coaching philosophy.
The process of coaching has been conceptualized, studied, and analyzed in a wide variety of ways. The most common theoretical perspective used by
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researchers has been to view coaching as a decision-making process. Successful coaching has been described as the practice of making correct decisions within the constraints of a highly complex social and dynamic environment (Abraham and Collins, 1998; Cratty, 1970; Lyle, 2002). In a general sense, coaches articulate a purpose and establish unique mechanisms for achieving success. The foundational premise behind the theoretical model presented in this paper follows that effective coaching is a decision-making process in which coaches attempt to direct goal attainment within a sporting context, and accomplish effectiveness through a congruent intentional philosophical approach; a trueness to one‘s beliefs. Coaching may be regarded not as a behavior to be copied but rather as a cognitive skill to be developed (Abraham and Collins, 1998). The identification and utilization of a coaching philosophy, also referred to as a belief system, has long been mentioned as one of the essential skill sets coaches must incorporate into their position as a leader (Cratty, 1970; Horn, 2008). Despite this recognition, the specific function a coach‘s belief system plays in the overall coaching process has received limited and fragmented theoretical treatment. Successful coaches engage in an ongoing process of evaluating their intent – reflecting, verifying, and redefining the manner of interaction they have with their environment (Gilbert and Trudel, 2001, 2006). Effective coaches are continually modifying and refining the strategies they use to achieve their purposes. Whereas, ineffective coaches struggle to develop and maintain the strategies that create a congruent connection between them and their players, their specific sport situation, and their true self. In his multidimensional model of leadership, Chelladurai (1990) describes this congruent connection, or lack of, as a function of three interacting features of leader behavior: actual, preferred, and required behavior. For most coaches the dynamic process of adjustment, attempting to maintain an effective alignment within the environment while maintaining a congruent purpose, is enormously complex. Numerous authors have described the countless number of decisions and behaviors a coach must consider in the process of coaching (Abraham, Collins, and Martindale, 2006; Cushion, Armour, and Jones, 2006; Lyle, 2002; Nash and Collins, 2006). Some researchers are questioning if it is even possible to correctly capture the complexities of the coaching process (Cushion, 2007). But, the complexity of the coaching process can be penetrated. By searching for patterns in the behaviors of coaches, one can describe and eventually predict the process of effective coaching. This paper presents a conceptual framework that coaching practitioners and coaching education students can use as a tool to analyze the process of coaching. Specifically, the framework has two major elements: a) a general model of the coaching process, describing
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coaching as an integrated and dynamic whole and specifying major factors coaches must consider in order to maintain an effective alignment within their sport context. This general model also helps explain where a coaching philosophy fits into the overall process; and b) a coaching typology, which describes different patterns of philosophical beliefs used by coaches. This typology will be referred to as a Coaching Belief Triad, and is introduced as a means of elaborating on the elements of a coaching philosophy.
A GENERAL MODEL OF THE COACHING PROCESS Criticisms of previous attempts to model the coaching process as an integrated whole have come from two extremes (Abraham and Collins, 1998; Cushion, Armour, and Jones, 2006; Lyle, 2002). Either, models have been described as being too multifaceted to be useful in portraying the complexity of coaching, or models are described as too simplistic to fully capture the complexity of coaching. What seems to have been lost during these critical evaluations is, ―why‖ is the coaching process complex? We return to our foundational premise in arguing that the complexity involved in the coaching process stems from the notion, effectiveness requires a congruent intentional philosophical approach; a trueness to one‘s beliefs. Accomplishing "trueness" is not an easy endeavor; in order to accomplish a sense of congruence coaches must connect the specifics from the past to the uncertainties of the future. In other words, coaches are attempting to connect their tacit knowledge, experiences, personal characteristics (including personality), and sense of duty -- to the uncertainties involved in any sporting context which include the explicit behaviors athletes ultimately display while playing the game or practice. An example of how other fields of study have dealt with a similar dilemma can be seen in organizational theory (Slack and Parent, 2006). Miles, Snow, Meyer, and Coleman (1978) introduced the notion of a leading and lagging variable as a way of connecting two seemingly opposing requirements within a process. In describing the process of organizational adaptation researchers used a construct they referred to as an administrative system to act as a bridging mechanism, this bridge allowed an organization to both monitor past activities and at the same time have the freedom necessary to recognize future innovations the organizational environment may require. We use a similar idea to contend that a coaching philosophy acts as both a leading and lagging variable within the process of coaching. A philosophy is a unique configuration of broad theories which in a general manner explain how
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success is achieved (Nespor, 1987; Pajares, 1992). This is not a one-size fits all approach to success, but rather a belief system constructed by each individual coach to explain their path to future goal attainment. The presence of a coaching belief system as part of the overall coaching process is stated in numerous conceptual and empirical research studies (Abraham and Collins, 1998; Cushion, Armour, and Jones, 2003; Horn, 2002; Vallee and Bloom, 2005). To date, very few attempts have been made to more fully explain the source, elements, or impact of a coach‘s philosophy. As a leading variable, a coaching philosophy ties together elements of the coaching process that are retro-active in nature. Shown in figure 1 these constructs include: Socio-Environmental Factors, Efficacy, and Role Tasks. What is meant by ―retro-active‖ is the notion that particular aspects of a coach‘s socio/psychological profile are influenced by past appraisals, actions, or fixed variables. These concepts have been investigated in great detail by other researchers, and were collectively referred to as antecedents by Horn (2002, 2008) when she explained how coaches‘ behavior does not occur in a vacuum. Antecedents are defined as the, ―cognitions, thoughts, beliefs and or perceptions that coaches have prior to, or during, practice or competitive events, and how such cognitions or thoughts are used to guide their actions or behaviors in actual field situations‖ (Horn, 2008, p. 8). The Socio-Environmental Factors construct shown in figure 1 represents elements which relate to a coach's sociocultural background (e.g., gender, race/ethnicity), organizational environment (e.g., age of athletes, level of competition), and coaches‘ personal characteristics (e.g., sports background, demeanor, personality). All of these elements are pre-established characteristics a coach, in essence, brings to each new decision-making opportunity. A large amount of research is represented within this construct. Areas of inquiry include; sport sociology (Donnelly and Young, 1988; Ewing, Forrest, Knoppers, and Meyer, 1993; Nash and Collins, 2006), competitive/program climate (Cumming, Smoll, Smith, and Grossbard, 2007; Olympiou, Jowett, and Duda, 2008), and motivational style (Frederick and Morrison, 1999; Jowett, 2008). The construct Efficacy is meant to represent the theory of self-efficacy introduced by Albert Bandura (1977, 1986, 1997), which has been one of the most studied antecedent constructs in the physical domain literature over the past twenty years. Efficacy in the broadest sense is defined as, the judgment in one‘s ability based on retro-active appraisals to execute a specific task successfully (Wood, Bandura, and Bailey, 1990). When Feltz, Chase, Moritz, and Sullivan (1999) introduced the construct of coaching efficacy, they based their framework
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on Bandura‘s Social Cognitive Theory along with the model of teacher efficacy developed by Denham and Michael (1981).
Figure 1. A General Model of the Coaching Process.
Coaching efficacy is defined as the extent to which coaches believe, based in large part on past perceptions of success, if they have the capacity to affect the future learning and performance of their athletes. As presented in figure 1, Coaching Philosophy also acts as a leading variable for the antecedent construct referred to as Role Tasks. This construct is much broader than the title implies, encompassing ideas that help explain how coaches perceive and define their responsibility as a leader. The notion of a coaching role frame was first introduced to the coaching literature by Gilbert and Trudel (2004) and describes how coaches create a dynamic set of duties they hold themselves responsible for accomplishing. Much of the research into how coaches set personal goals (Sousa, Smith, and Cruz, 2008; Thelwell, Weston, Greenlees, and Hutchings, 2008), and locus of control (Smoll and Smith, 1989) would also fall within the Role Tasks construct. As a lagging variable, a coaching philosophy must facilitate a coach's decision-making future. By evoking a general theory of sport success, a philosophy supports a coach's need to focus and simplify the myriad of possible problems they face at any given moment. Because a coaching philosophy is derived from the specifics of a coach's past, as mentioned before, it becomes a unique configuration of beliefs best understood by that coach. This quality also allows a coach to interpret, reinforce, and articulate the path he/she believe will lead to future success to the athletes they are charged with leading.
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A coaching philosophy acts as a bridge from elements at a more tacit level of consciences to elements that are more explicit and observable. The first of these explicit constructs is shown in figure 1 as Problem Identification. The process involved in identifying a problem is most systematically explained in the Gilbert and Trudel (2001, 2006) conceptualization of reflection. In essence, Gilbert and Trudel's research describes how coaches learn through experience, and how they choose what behaviors will be incorporated into their personal sport situation. Central to their work, Gilbert and Trudel (2001) found evidence that coaches go through a reflective conversation when faced with an issue. A reflective conversation is made up of four components: (1) issue setting, (2) strategy generation, (3) experimentation, and (4) evaluation. When a coach is faced with an issue that requires action on his/her part, the latter three components of the reflective conversation often cycle through a number of times in an effort to uncover a congruent decision to the coaches‘ belief system, hence, creating a straight line of thought and action. For example, a coach hired to take over a university basketball program is faced with the immediate issue, what problem to tackle first. Placed in this situation a coach may anticipate the difficulties of implementing the unique type of offense she plans to bring to the new program, and begins putting her playbook together. Another coach in the same situation may choose to evaluate the skills of her players, and decides to spend time recruiting athletes that fill a specific talent deficit. Yet another coach may decide to spend significant time talking with players in an effort to discover the values her athletes currently hold, and determines "loyalty" is not a common value among team members and sets up mechanisms to change that. The above example can continue indefinitely, both the problems available for a coach to focus on and the actions a coach can choose to solve the problems are seemingly endless. The point is, in order to achieve an effective degree of congruence within the process coaches require a guiding belief system that is both large enough to handle the complexity of sport and narrowed enough to allow for consistency. Consistency is related to congruence in that athletes must ultimately interpret a coach's actions (as shown in figure 1) and the more consistent a coach is throughout the process the easier it will be for the athletes to make that interpretation. Consistency in this context does not necessarily mean following a strict repetition of previous coaching actions, even if those actions produced success in the past. Most sporting environments are too variable to consider this an option. The notion follows more closely with the idea of a coach staying true to his/her general philosophy of success. The notion of consistency is highlighted in Smoll and Smith's (1989) cognitive-mediational model, and Chelladurai's (1990)
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multidimensional model of leadership, as well as more recent empirical studies such as Becker and Solomon (2005). In these perspectives, effective coaching was described by the direct and indirect influences a coach‘s behavior had on team performance and the behavior of athletes. The more consistent coaching decisions were, in association with other complex variables, the more likely positive outcomes were experienced. In summary, we return to the purpose of placing philosophy within the coaching process. Coaching issues, the impetus to a reflective conversation, do not simply present themselves to coaches but are constructed by coaches (Gilbert and Trudel, 2006). The fact that different coaches choose to tackle different problems at different times even when placed in similar sporting context provides evidence that a link, in the form of a coaching philosophy, does exist between antecedent constructs and the more explicit elements of the coaching process.
THE COACHING BELIEF TRIAD If one accepts the general model of coaching presented in the previous section as plausible, the question becomes: How do coaches arrange their coaching philosophy to act as a bridge between the antecedent elements and the future decision-making the process requires? Our research and interpretation of the literature show there are essentially three belief types coaches arrange into a personal coaching philosophy. The three orientations coaches use to create their own coaching philosophy include: team development, individual-talent development, and scheme development. The three success orientations when arranged collectively into a Coaching Belief Triad help to explain: a) how a coach relates his/her past success/failure to their future desires; b) what problems within the coaching environment he/she will focus his/her attention; c) why an individual coach will demonstrate a particular behavior or coaching style; and d) ultimately what behaviors the coach hopes to see from his/her athletes. The following sections outline the individual dimensions believed to make up the coaches‘ belief triad. Contained within each description are examples supported by empirically based studies investigating various aspects of the coaching process; it should not be implied these studies were investigations into the coaches‘ belief triad.
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Team Development Coaches with team development as their primary belief perspective will be referred to as conductors. A conductor is a coach who believes he/she is skilled at guiding, directing, and/or influencing the behavior of a group. These coaches attempt to discover what is universal among group members and capitalize on that collective quality in order to bring the individuals closer to a common goal. Team development coaches believe that building cohesiveness and playing together as a team will lead to victory. Team development can most easily be described as the ―we‖ approach to coaching. While discussing organizational skills, and more specifically team selection, a coach in the Vallee and Bloom (2005) study expressed the personal belief, ―I was very good at recruiting a team, not recruiting 12 individuals‖ (p. 189). The sports cliché a conductor coach would most likely identify with is; united we stand, divided we fall. Conductors feel they have a responsibility to inspire and direct an attitude of common purpose among team members. This may be accomplished by taking a more thematic approach to coaching. A female coach in the Gilbert and Trudel (2004) study articulated the theme of fairness in her responses. At one point she stated, ―My understanding and it is also part of my belief, that at this age the concept of being part of the team is more important than assigning one captain for the entire year‖ (p. 34). The themes that a conductor coach chooses to emphasize are meant to create a standard of behavior among the athletes. Other themes conductors could center their approach around include, but are not limited to: communication, appearance, demeanor, and expectations. A parallel can be drawn between this type of coach and the conductor of a musical orchestra. One of the most important responsibilities for the leader of an orchestra is to interpret and inspire a common theme of the music so that each individual musician approaches the concert from the same state. Likewise, a coach as conductor will also strive to inspire his/her athletes to recognize the common goals and importance inherent to functioning as a team toward achieving success.
Individual-Talent Development A second belief among coaches is related to developing the individual athlete and highlighting the unique talents among the members of a group. An individualtalent approach can be described as the ―he/she‖ approach. Similar to leadership models described in a business context this coaching philosophy attempts to find the right person for the right job, in essence, getting the right people on the bus,
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the wrong people off, and everyone in the correct seats (Collins, 2001). For that reason this type of coach will be referred to as a manager. Managers strive to discover the value and uniqueness of each individual in the group and integrate the eccentricities each member brings to the sport situation for the betterment of both individual and group objectives. By increasing individual skills and establishing an atmosphere where athletes strive for personal best, the coach hopes to build upon individual achievements and compound those into greater program success. Managers are likely to ascribe to the ideal that you cannot succeed without talent, believing it is their responsibility to identify and deploy the differences among the group members and challenge them to excel in their own way. Found within Abraham et al.‘s (2006) qualitative review of the coaching process, the following quote best illustrates a coach‘s individual-talent approach in how objectives for his team are set, ―I try to think, and most of my colleagues try to think that it, the program, is centered around the athlete because if the athletes don‘t win medals, we have got no program and we are out of a job. We try to satisfy the athlete‘s needs, it‘s like an athlete-centered approach‖ (p. 555). Managers often see the key to success not only in increasing the skills of athletes but in surrounding the athletes with others who have unique and specialized talents. A coach in the Kellett (1999) study, while discussing his method of empowerment noted, ―I delegate to assistant coaches, reserve coaches, fitness coordinators, ruck coaches, rehabilitation coaches different roles. The head coach oversees it all…he has got these specialist people‖ (p. 162). Thus, a coach within this philosophy very much functions as a ―guide on the side‖; recruiting the best and creating situations by which each athlete can achieve his/her best.
Scheme Development The third belief philosophy is concerned with creating a uniqueness of technique, strategy, or organization with the hope that by developing the scheme it will provide a competitive edge over opponents. These coaches could be called innovators. They believe that the execution of the game plan is the key to success. Innovators strive for creativity, method improvement, and order within their unique system of play, with the belief these characteristics will lead to success both individually and collectively. In essence, innovators seek success through manipulating the X‘s and O‘s of the game. Like an inventor, these coaches strive to build a better mouse trap.
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By focusing on the ―it‖ of their particular sport, innovators guide the development of unique systems of play, and believe this creativity will transfer into a better chance to reach higher levels of success. One of the youth hockey coaches within the Gilbert and Trudel (2004) role frame study stated, ―We try, and I stress, we try to win at all cost, but within a structured scenario, and [if] we can do that, great‖ (p. 37). This sense of control and uniqueness is not only seen during in-game strategies, but this perspective is also evident in the type and character of drills done during practice time. While discussing ways of making practices enjoyable and effective, a coach referring to his creative use of video sessions said, ―I think I made them more game smart: I show them what they did and why it worked or why it did not work. I think they were able to analyze the game better and carry that over into helping them prepare for the next opponent‖ (Vallee and Bloom, 2005, p. 188). In addition, a coach in a study by Bloom, Stevens, and Wickwire, (2003) represents the notion of system order, when he described practice planning saying, ―They know from day one to the last practice of the year what type of workout they‘ll be doing and the objectives of the day, of the week, of the month‖ (p. 136). Thus, innovators seek to weave a tapestry from the possibly more mundane aspects of coaching into a unique and potentially successful result.
BUILDING THE COACHING PHILOSOPHY As mentioned in the General Model section of this paper, coaches configure their own unique coaching philosophy by orientating the three belief types. In effect, through a tacit interpretation of the antecedent factors which make up every coach's socio/psychological profile, a coach will arrange the three beliefs into a complete belief system; coaches utilize each belief type to a certain extent as a way of building wholeness to the system. While similar typologies of various aspects of coaching behavior are available (Chelladurai, 1990; Feltz et al., 1999; Smoll and Smith, 1989), our model specifies a relationship among individuals, group, talent, and strategy to the point where the process of coaching can be viewed as an integrated whole functioning within a dynamic environment. Any typology is unlikely to encompass every form of behavior (Miles et al., 1978). The world of coaching and coaches are much too changeable and complex to permit such a claim. Nevertheless, every coach we have observed appears to have a predominant belief that guides their belief system. This primary belief is thought to work in concert with the other two beliefs to create a sort of comprehensiveness. Essentially, the belief system can be arranged into a primary,
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secondary, and third order configuration, as shown in the general model (figure 1). The success orientation a coach adopts at any given moment is an either/or choice among beliefs. Thus, the coaching belief triad is more paradoxical in nature, each perspective working independently in time but needing the other perspectives to provide wholeness to the particular context. Similar to the gears of a machine, force can be applied to any of the gears independently which in turn provides the synergy to move the other elements of the motor. For example, when trying to ready his/her team for an upcoming game a coach can choose to address the group, the individual players, or the strategy. No matter which perspective the coach ultimately decides to focus his attention on, the others will be affected to some degree. Because the belief triad is believed to act as the driving mechanism for subsequent elements of the coaching process, the framework is depicted as a set of three gears, as noted in figure 1. Although there is high confidence in the usefulness of the framework to increase the self awareness of coaching students/practitioners, the framework is not meant to be viewed as a complete and sufficient grasp of all that is known about the coaching process. Taking the lead from Cushion (2007), the model and typologies presented in this paper may best be viewed as instruments of analysis, rather than the object of analysis. One appropriate example may be to investigate how often successful coaches display behaviors not congruent with their primary belief. It could be hypothesized that coaches with primarily a team development orientation who spend a significant amount of time focused on scheme or talent issues will be less likely to achieve success than coaches who focus on issues more in line with their primary belief.
BENEFITS OF A COACHING BELIEF TRIAD As the field of coaching science has grown, the awareness that coaching is a central element to athlete development and athletic program success has increased (Abraham and Collins, 1998; Horn, 2002, 2008; Jones and Turner, 2006). One need only take a cursory look at the field of coaching science to realize that athletic coach education (ACE) is also growing (Demers, Woodburn, and Savard, 2006; Gilbert, Cote, and Mallett, 2006; McCullick, Belcher, and Schempp, 2005; Trudel and Gilbert, 2006). The purpose of ACE has always been to help both novice and experienced coaches translate the information, strategies, and insights gained through scientific inquiries into behaviors useful in their quest for success. We agree with Lyle (2002), if the growth in ACE is to continue attention must
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turn to providing tools in the form of frameworks that will help educators translate the vast amounts of knowledge coaching science has revealed. The irony of the current situation is that although coaching practitioners/students are seeking opportunities to become more educated, ACE researchers are questioning if it is even possible to correctly capture the complexities of the coaching process (Cushion, 2007). Recently some have taken a critical view of coaching research, making the argument the field lacks a sound conceptual base (Abraham, Collins, and Martindale, 2006; Cushion, 2007; Cushion, Armour, and Jones, 2006). This critical judgment is best expressed by Abraham et al. (2006), who describes the field as lacking integrated conceptual models of the coaching process. ―In contrast to the current situation in coaching, research examining practice and development in similar but more established paradigms such as teaching reveal simple conceptual models that characterize the qualities required in an effective schematic‖ (Abraham et al., 2006, p. 550). For many coaches, disconnect between coaching education and actual coaching practice is related to this lack of tools that allow students/practitioners to reflect on their own experiences and situations. However, it is only as a function of focusing on exploring the processes of coaching, e.g., antecedents, cognition, decision making, knowledge, that coaching science and ACE will gain the insight into establishing useful models of effective coaching practices. The critical implication for ACE, and the focus of this theoretical article, has been the creation of a framework that attempts to square the paradoxical dilemma concerning providing simple comprehensive knowledge about the process of coaching that also, incorporates and displays the complexity inherent in sport. Coaching science can use the commonalities among coaches to bring a sense of clarity to the field. Although no two coaches are exactly alike, all coaches have commonly occurring attributes that allow researchers to classify and compare them. By identifying common attributes eventually we can classify coaches into effective and ineffective typologies that will allow student/practitioners to better reflect on their own unique situations. Mills and Margulies (1980, p. 255) explain, ―Typologies play an important role in theory development because valid typologies provide a general set of principles for scientifically classifying things or events.‖ These classifications will also make it possible for researchers to design studies, models, and theories that will continue to push coaching science toward deeper understanding of the coaching process. Without the continued establishment of viable and intuitively appealing typologies the field of coaching science, and arguably ACE, is not likely to emerge with appropriate theories and principles in the future. Therefore,
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disconnect between coaching theory and coaching practice will remain for many coaches both novice and experienced.
CONCLUSION Although the conceptual framework put forth in this paper was based on empirical research from many different domains, there is much more work to be done. This paper is an initial step in bridging the space between theory and practice in our field. Multiple research opportunities were highlighted throughout this paper. Chief among those research opportunities is the empirical confirmation of the coaching belief triad. If coaching researchers choose to concentrate on the overt behaviors of coaches without delving deeper into the internal mechanisms that drive the behaviors, the field reduces the practice of coaching to a trial and error endeavor. Some coaches, the lucky ones, will experience the success and joy of authentic leadership, while many will simply continue to feel the frustration of failure. Providing knowledge concerning the processes of coaching in a simple and comprehensive manner that also fully displays the complexity inherent in sport is a paradoxical dilemma, but should forever remain the goal of sport science research. It is the hope this paper has contributed at least a small piece of understanding to the puzzle we call coaching.
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Nash, C., and Collins, D. (2006). Tacit knowledge in expert coaching: Science or art? Quest, 58(4), 465-478. Nespor, J. (1987). The role of beliefs in the practice of teaching. Journal of Curriculum Studies, 19, 317-328. Olympiou, A., Jowett, S., and Duda, J.L. (2008). The psychological interface between the coach created motivational climate and the coach-athlete relationship in team sports. Sport Psychologist, 22(4), 423-439. Pajares, M.F. (1992). Teachers‘ beliefs and educational research: Cleaning up a messy construct. Review of Educational Research, 62(3), 307-332. Slack, T., and Parent, M. M. (2006). Understanding sport organizations: The application of organization theory. Champaign, Il: Human Kinetics. Smoll, F.L., and Smith, R.E. (1989). Leadership behavior in sport: A theoretical model and research paradigm. Journal of Applied Social Psychology, 19, 1522-1551. Sousa, C., Smith, R.E., and Cruz, J. (2008). An individualized behavioral goalsetting program for coaches. Journal of Clinical Sport Psychology, 2(3), 258278. Thelwell, R.C., Weston, N. J., Greenlees, I.A., and Hutchings, N.V. (2008). A qualitative exploration of psychological-skills use in coaches. Sport Psychologist, 22(1), 38-54. Trudel, P., and Gilbert, W. (2006). Coaching and coach education. In D. Kirk, M. O‘Sullivan, and D. McDonald (Eds.), Handbook of Physical Education (p. 516- 539). London: Sage. Vallee, C.N., and Bloom, G.A. (2005). Building a successful university program: Key and common elements of expert coaches. Journal of Applied Sport Psychology, 17, 179-196. Wood, R., Bandura, A., and Bailey, T. (1990). Mechanisms Governing Organizational performance in complex decision-making environments. Organizational Behavior and Human Decision Processes, 46, 181-201.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 7
BURNOUT IN HIGH SCHOOL BASKETBALL COACHES FROM A REVERSAL THEORY PERSPECTIVE Ryan K. Zapalac1,1, Jay T. Lee2 and Dale G. Pease3 1
Sam Houston State University, TX, USA 2 Ft. Bliss, Texas, TX, USA 3 University of Houston, TX, USA
ABSTRACT Attributes related to burnout potential in high school varsity basketball coaches were investigated using Reversal Theory as a theoretical base (e.g., Apter, 2001). Four hundred coaches, controlled for school size and gender, were randomly selected and mailed a questionnaire which included the Apter Motivational Style Profile (AMSP) (Apter, 1999), Maslach Burnout Inventory (MBI) (Maslach, Jackson, and Leiter, 1996), and a demographic information sheet. Coaches (N= 126) returned usable questionnaires that showed no significant gender or school size differences. It was hypothesized that coaches exhibiting dominances high in telic and conformist dominances would have greater susceptibility to burnout than coaches who are more paratelic and negativistic dominant. This hypothesis was not supported. In total, fifteen percent of coaches demonstrated high potential for burnout. Autic sympathy (a transactional pair) had the strongest association with burnout accounting for almost 30% of the total variance. Coaches who 1
Contact Information: Ryan K. Zapalac, Ph.D. Dept. of Health and Kinesiology, Sam Houston State University, Box 2176, Huntsville, TX 77341, (936)294-4575 – direct, Email:
[email protected]
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Ryan K. Zapalac, Jay T. Lee and Dale G. Pease exhibited autic sympathy dominance had increased feelings of depersonalization and emotional exhaustion and reduced feelings of personal accomplishment.
Keywords: Psychological burnout, coaching, basketball, Maslach Burnout Inventory, Reversal Theory
INTRODUCTION Burnout has been defined as a syndrome of emotional exhaustion, depersonalization, and reduced personal accomplishment (Maslach, Jackson, and Leiter, 1996). Raedeke (1997) added the factors of physical exhaustion and sport devaluation in his burnout research on young athletes. While research on burnout has been primarily focused on human services professionals who have excessive contact with their clients (Drake and Yadama, 1995; Maslach, et al., 1996) there is increasing research showing burnout to be a potential problem for coaches and athletes. Research involving coaches and burnout has sought relations among factors such as job conditions (Pastore and Judd, 1993), personal/situational factors (e.g., Kelley and Gill, 1993; Vealey, Udry, Zimmerman, and Soliday, 1992), level of coaching (e.g., Pastore and Judd, 1993), coach/player interaction (Price and Weiss, 2000), gender differences (e.g., Kelley, 1994; Pastore and Judd, 1993), feelings of entrapment (Raedeke, Granzyk, and Warren, 2000), and coaching style (e.g.,Vealey, Armstrong, Comar, and Greenleaf, 1998). A recent review reported four general psychological correlates related to coach burnout: perceived stress, commitment, social support and leadership behavior (Goodger, Gorely, Lavaliee, and Harwood, 2007). Theory-based research focused on specific associated psychological factors is limited. Therefore, the purpose of this study was to develop a profile using the dominances and states proposed by Reversal Theory (e.g., Apter, 2001) to better understand the potential for burnout in Texas high school varsity basketball coaches. Previous studies involving burnout in the coaching profession have linked a number of factors to the development of burnout or potential for burnout. Using Smith‘s (1986) cognitive-affective model of burnout, Vealey et al. (1992) found trait anxiety to be the best predictor of burnout for both male and female coaches. Significant relations were also established between burnout and factors such as overload of demands, low perceived control, low professional support, and lack of professional accomplishments. For collegiate head basketball coaches, Kelley and
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Gill (1993) reported coaching issues and role conflict were related to higher levels of burnout. Also female coaches were found to have higher levels of perceived stress relating to burnout than males coaches. In a follow-up study using collegiate baseball and softball coaches, Kelley (1994) reported that the coaches were experiencing moderate to high levels of emotional exhaustion and low to moderate levels of depersonalization and personal accomplishment. When compared with male coaches, female coaches‘ experienced higher levels of being emotionally depleted, frustrated, and ‗at the end of one‘s rope‘. Further analysis showed coaching issues (e.g., pressures of winning, lack of time, budgets, role model/conflict, etc.) to be significant burnout predictors for females while these factors were somewhat less of a predictor of burnout for male coaches. Other studies have investigated the role of coaching level (i.e., two year colleges in relation to four year) and the coach/player interaction as these variables relate to coach burnout. Assuming that higher athlete turnover occurred at two year colleges, and that these institutions promoted certain types of coaching styles, Pastore and Judd (1993) reported that female coaches experienced higher levels of emotional exhaustion than male coaches. This was attributed to the social aspect of athlete turnover and the style of coaching promoted by the institution. In investigating the coach/player dyad in relation to burnout, Price and Weiss (2000) found coaches high in burnout indices, especially emotional exhaustion, were perceived to be providing their athletes less training instruction and social support (coaching styles). This suggested that coaches were depersonalizing more and emphasizing personal accomplishment less. They further suggested that a democratic leadership style signified an increased possibility for coach burnout. Therefore, it has been established that those involved in the sport world, and more specifically, the coaches who have direct contact with the athletes, are susceptible to burnout. The pressures, both internally and externally imposed (i.e., pressure to win, the time demands, the support services, role conflicts, etc.), have been found to contribute to burnout. In the studies involving coaches, only trait anxiety (Vealey et al. 1992) and hardiness (Kelley, 1994) have been reported as specific psychological variables associated with burnout. Is there a more complete psychological profile that would result in a better understanding of innate factors that may contribute to the susceptibility of burnout in coaches?
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REVERSAL THEORY To establish a theoretical base to investigate coaches‘ burnout, Reversal Theory (RT) was selected because it is a general psychological theory that includes motivation, emotion and personality (Apter, 2001; Frey, 1997), all of which have been associated with burnout. RT, often presented as an activation theory, has been used to research such topics as enjoyment of humor, stress in the work place, adolescent rebellion, sport preference, sexual dysfunction, addictions, and other psychological phenomena (see Apter 2001 for a complete review). In relation to burnout from an RT perspective, Braman (2001) has ―…postulated burnout as being due to the satiation of sets of generalized goal-directed behaviors organized around the ‗telic-conformity state‘‖ (p.137). This is based on his prediction that burnout occurs with highly motivated people where the rewards encourage them to overwork. In addition, these individuals often do not take time off for rest and fail to switch to other behaviors periodically. Table 1. Characteristics of the Eight States in Reversal Theory State
Core Value
Motivational Style
Emotional Dimension
Telic
Achievement
Serious
Arousal
Paratelic
Enjoyment
Playful
Arousal
Conformist
Duty
Obedient
Arousal
Negativistic
Freedom
Rebellious
Arousal
Mastery
Power
Competitive
Transactional outcome
Sympathy
Love
Affectionate
Transactional outcome
Autic
Individuality
Self-oriented
Transactional outcome
Alloic
Transcendence
Other-oriented
Transactional outcome
Note. From Reversal Theory: The dynamics of motivation, emotion, and personality (p. 227), by M.J. Apter, 2007, Oxford: Oneworld. Copyright 2007 by Michael J. Apter. Adapted with permission.
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In a more general review of RT, Apter, Fontana, and Murgatroyd (1985) describe RT as being structural phenomenological in nature. They state that the way a person experiences his/her world is clearly structured in various ways. This explains the importance of one‘s experiences and the systematic interpretations of these experiences by the individual (phenomenological). RT is more concerned with the subjective experience than the objective observable behavior. Behavior is not deemed as unimportant, but rather RT emphasizes a need to explore the motivation that underlies behavior. Apter (2001) describes this as an ‗inside-out approach‘, where one starts with motivation and experience and then interprets the behavior. However, RT assumes that the interpretation of the experience and the resulting motives and emotions are based on a fixed set of eight metamotivational states and the relationships among those states (structure). The dynamic nature of this structural phenomenology lies in the reversal process and the articulation of states over time (Frey, 1997). The eight metamotivational states are paired into four domains of experience (telic/paratelic and conformist/negativistic, which are referred to as the somatic pairs since they relate to felt arousal; and mastery/sympathy and alloic/autic, which are referred to as the transactional pairs since they relate to personal interaction). For further description of the RT states, please see Table 1. In the RT literature focused on burnout, the somatic pairs have received the most attention, specifically the telic–conformist states. Braman (2001) focuses on the burnout phenomenon and its relation to the somatic states. ‗Telic‘ means goal directed while ‗conformist‘ means to be guided by the perception of other people‘s requirements. Therefore, as the satiation of this behavioral set (i.e., telic – conformist) builds up, Braman proposes that involuntary reversals to a purposeless, negativistic state occur. As a result, these individuals can no longer behave in ways that previously provided them with desired rewards. He states that burnout is the product of rewarded behavior carried to an extreme. In addition, burnout can be linked to the removal of rewards, and thus people will often abandon what they are doing. Kerr (1997) has also focused on the somatic pairs, especially ‗telic tension– stress‘ in addressing contributors to burnout from an RT perspective. Tension stress occurs when there is a discrepancy between the preferred and actual level of some salient motivational variable (Apter and Svebak, 1989). If one is in the telic state, with an accompanying preference for low arousal, and the arousal level is high, tension stress would occur. Turning to the transactional states it is proposed that if one is in the mastery mode, and cannot achieve the feeling of power desired for this state, tension stress will occur. From a coaching perspective, if the coach is very goal directed and cannot achieve the desired success, high tension–stress
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could be expected. If this experienced stress is chronic in nature it could result in increased potential for burnout. In RT, a second type of stress is referred to as effort-stress. It is the expenditure of effort to reduce, tolerate, or master a stressor. Apter (2001) suggests that this is often referred to as coping. While effort-stress is often associated with tension-stress, it can occur in the absence of tension-stress. The example Apter provides is the case where a person has many work responsibilities, expends a great deal of effort to avoid failure, and experiences the resulting feelings of tension and anxiety. A coach may work long hours and expend high levels of effort, to avoid situations perceived as failure. Consequently, that coach may encounter a great deal of tension-stress. If failure does occur, there is the combination of both tension and effort stress acting on the motivational variables (telic and mastery states) that would seem to increase the possibility of burnout. As shown, Braman (2001) and Kerr (1997) have focused more on the telicconformist states which are the somatic pairs. However, one might argue that burnout could be associated with the transactional pairs (i.e., autic/alloic and mastery/sympathy), especially the alloic state. The alloic state is described as having concerns primarily with others, looking to identify with others, unselfish and valuing transcendence beyond oneself. The alloic state is also described as preferring high felt identification with another person or identity (Apter, 2001). Since coaches often take on great responsibility for their players, maybe too much focusing on the ‗other‘ at times, they can experience the same reactions reported by those involved in the health service profession who experienced burnout (Drake and Yadama, 1995; Maslach, Jackson, and Leiter, 1996). The other transactional pair, mastery/sympathy, also could be playing a role in the occurrence of burnout. Coaches high in mastery dominance would be described as needing or preferring high felt toughness, or feelings of being tough, hardy, and being resilient. This would seem to describe hardiness which was reported as an important variable in studying burnout by Kelley (1994). Further, coaches high in sympathy would be found to have greater sensitivity, and the need for kindness and caring which may be difficult for a coach to receive when losing. Therefore, the alloic/sympathy pairing could be associated with high rates of burnout. It has been shown that RT‘s proposed four dominances and/or eight states could contribute to the potential for burnout in basketball coaches. Therefore, the major purpose of this study was to develop a profile using the RT theoretical base of proposed dominances and states to directly examine the potential for burnout in basketball coaches. Following the lead of Braman (2001) and Kerr (1997), it was expected that coaches whose profiles were high in telic and conformists
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dominances would have greater susceptibility to burnout. The rationale being that the coaches who were more goal driven (telic) and rule following (conformists), within the somatic pairs, would be at greater risk of burnout. Of the transactional pairs, it was expected that the alloic/sympathy dominance would have a stronger influence on burnout potential, which would be more similar to the health profession literature. Based on the research of Kelley and Gill (1993) and Kelley (1994) it was expected that the potential for burnout profiles of male and female coaches would differ. Since most of the burnout research using RT has focused on the relations among the individual states, it was believed to be important to compare the eight state profiles with the resulting four dominance profiles. This comparison could provide new insights into RT concepts and their future application in the research setting.
METHODS Participants Four hundred varsity basketball coaches were randomly selected, after controlling for school size and gender of coach, from the listings published in the Texas State Coaching Directory. School size was limited to 5A (largest public schools in the state), 4A (large to medium size), and 3A (medium size schools). Coaches from the smallest schools (2A and 1A) were not included in the study. Basketball was chosen since it provided potential gender differences. A total of 126 coaches, 90 male coaches and 36 female coaches, returned completed and usable questionnaires for a return rate of 31%. See Table 2.
Instrumentation Apter Motivational Style Profile (AMSP). The AMSP is a comprehensive multidimensional measure consisting of 40 items that measures eight subscales and the dominance and salience of each of the four pairs of metamotivational styles. The eight subscales are 1) telic, 2) paratelic, 3) conformist, 4) negativistic, 5) mastery, 6) sympathy, 7) autocentric and 8) allocentric which when analyzed individually represent motivational styles. A profile of the four dominances can be obtained by combining the telic/paratelic, conforming/negativistic, mastery/ sympathy, and the autic/alloic (Apter, 2001). The internal reliability for the eight subscales has been estimated by means of Cronbach‘s alpha ranging from .54 to
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.84 for American undergraduates (N=450), from .68 to .89 for a sample of United Kingdom subjects (N= 365) (Apter, Mallows, and Williams, 1998), and from .61 to .86 for an Australian sample (N=413) (Power, Findlay, and Heskin, 1995). (Cited in Apter, 1999). Using test-retest correlations from over a 12-week period, the external reliability was found to range from .61 to .92 for the eight styles (Apter, Mallows, and Williams, 1998). These reliability coefficients obtained from several studies suggest that the instrument is a reliable measure. Validation of the AMSP was based on the previous work from its predecessor the Motivational Styles Profile (MSP) (Apter, 2001). Discriminant validity was determined by comparing the MSP to instruments such as the Beck Depression Inventory (Beck, Ward, Mendelson, Mock, and Erbaugh, 1961), the Booklet Category Test (DeFillippis and McCampbell, 1979), the Beck Hopelessness Scale (Beck, 1978), and the Group Embedded Figures Test (Oltman, Raskin, and Witkin, 1971). The comparisons produced low correlations in the predicted directions. See Apter (2001) for further information on the development of the AMSP from the MSP. Maslach Burnout Inventory – Educators Survey (MBI). This widely used instrument to measure burnout was modified with copyright permission for use with this specific population. The term ‗coaching‘ was substituted for ‗work‘ and ‗players‘ for ‗students‘ in an effort to increase logical validity. The MBI‘s 22 item survey contains three subscales assessing Emotional Exhaustion (tired and fatigued feelings), Depersonalization (displaying indifferent and negative attitudes toward their athletes), and Personal Accomplishment (lack of contributing to athletes‘ development, and/or the coach being disappointed in their own professional development). The response set range is from 0 (never) to 6 (everyday) based on HOW OFTEN one experiences the emotions and cognitive feelings stated in the items. Reported Cronbach alpha estimates for reliability range from .90 to .72 (Iwanicki and Schwab, 1981; Gold, 1984). For a coaching and athlete population, Kelley (1994) reported alpha reliability coefficients ranging from .71 to .92 for the three subscales.
Demographics Data The information form attached to the front of the questionnaire sought the following information from each coach included in the sample: gender, age, size of school, gender of team coached, years in coaching basketball at current school, and total years in coaching, previous season won/loss record, career basketball
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coaching won/loss record, estimate of average hours per week worked during season, and future expectations related to the coaching profession.
Procedures Following the random selection of four hundred coaches, controlling for school size and coaches‘ gender, coaches were mailed a packet containing the human subjects consent form from the University‘s Human Subjects Committee, the information form, the AMSP and the MBI with a stamp-addressed return envelope. The mailing occurred within one week of the end of the high school basketball season with the request that the questionnaire be completed and returned within two weeks. Two weeks after the first mailing, a reminder was sent to all coaches requesting those who had not completed the questionnaire at that time do so within the next week. No further follow-up reminders were sent. In order to produce profiles combining the RT data with the MBI data, factor analysis was employed treating the subscale scores as first order factors. In the first analysis, the MBI subscale scores were entered with the RT subscale scores to produce a profile examining the relationships among the three burnout instrument variables and the individual subscales of the AMSP. The second analysis was focused on the relationship among the dominances and the MBI subscales. Gorsuch (1983) and Cattell (1966) described the approach of using factor analytic techniques to examine the relationships among second-order factors revealed through the resulting profiles. It is well known that factor analysis can yield factors present in data and is thus psychometrically useful for producing subscales and developing instruments. However, in this study the factor analysis of the existing subscales of both the MBI and the AMSP allows more options to investigate the unknown (Royce, 1967) structural relationships between these two instruments contributing to a greater understanding of the data.
RESULTS There were a total of 126 participants who returned usable questionnaires for a 31% response return. Of those, 36 were female and 90 were male. Twenty–four (19%) participants reported coaching at a 3A school (medium size school), 53 (42.1%) coached at a 4A school (medium to large size school), and 49 (38.9%) at a 5A school (largest size school). The average age was approximately 42 years (SD= 8.8) with an average number of years of coaching being 16.3 (SD= 8.3).
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Using the win/loss percentage rate as a success measure, this sample reported a 53% (SD = 15%) winning rate and reported a commitment of approximately 39 hours a week dedicated to basketball during the season. Gender differences were not significant with men reporting to be slightly older, having more years of experience, and working slightly more hours per week. Females in this sample reported a slightly higher winning percentage. However, there were no significant differences (p > .05) between male and female coaches on the major variables. Thus, for further analysis, gender was considered as one factor. Table 2 presents the descriptive statistics for the study‘s participants. Table 3 presents the means, standard deviations, and coefficient alpha for the MBI and AMSP scales. Table 4 includes the means and standard deviations for the dominance (i.e., combined state) scores from the AMSP (Apter, 1999). Table 5 reports the means and standard deviations for the MBI subscales and also utilizes the published MBI scores for risk of burnout as published by Maslach, Jackson, and Leiter (1996). Table 6 reports the correlations between the AMSP states and dominances and the MBI. As evidenced by the results, no potential multicollinearity existed within the sample. Table 2. Participant Descriptive Results
Age (years) Male Female Coaching (years) Male Female Winning (percentage) Male Female Work (hours/week) Male Female
M 41.8 43.1 38.3 16.3 17.2 13.9 .53 .52 .55 38.8 39.8 36.1
SD 8.8 8.7 8.2 8.3 8.2 8.2 .15 .14 .17 16.5 17.2 14.2
SE .79 .92 1.4 .74 .87 1.3 .01 .01 .03 1.5 1.8 2.5
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Table 3. Mean, Standard Deviation, and Coefficient Alpha for the MBI and the AMSP State Subscales
MBI
Emotional Exhaustion Depersonalization Personal Accomplishment AMSP States Telic Paratelic Conformist Negativistic Autic mastery Autic sympathy Alloic mastery Alloic sympathy
M
SD
α
20.42 7.49 37.00
10.89 5.38 5.88
.89 .73 .73
25.35 19.29 22.13 9.47 23.06 18.40 26.14 25.29
6.84 12.30 7.26 8.59 9.20 23.74 8.15 7.12
.57 .65 .33 .65 .53 .81 .84 .55
Table 4. Means And Standard Deviations For The AMSP Dominances AMSP Dominances Telic Conformist Mastery Autocentric
M 6.13 12.91 2.82 -4.96
SD 4.12 4.12 3.13 4.00
Table 5. Means and Standard Deviations for the MBI Subscale Scores MBI Subscale Emotional exhaustion Males Females Depersonalization Males
Risk for Burnout Low* ≤16 M(SD) 9.35 (4.32) 9.81 (5.17) ≤8 M(SD) 4.83 (2.39)
Moderate* 17-26 M(SD) 21.15 (3.08) 21.57 (2.56) 9-13 M(SD) 10.78 (1.47)
High* ≥27 M(SD) 33.81 (6.02) 34.27 (6.51) ≥14 M(SD) 16.36 (2.46)
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Ryan K. Zapalac, Jay T. Lee and Dale G. Pease Table 5(Continued).
Females Personal accomplishment Males Females
3.24 (2.83) ≥37
10.83 (1.83) 31-36
19.4 (4.03) ≤30
M(SD) 41.67 (3.27) 42.50 (1.32)
M(SD) 33.40 (1.65) 33.80 (1.98)
M(SD) 28.31 (1.70) 29.50 (0.97)
*Note. Each categorical classification was sourced from Maslach, Jackson, and Leiter (1996).
Table 6. Correlation Among the AMSP State and Dominance Subscales
AMSP States Telic Paratelic Conformist Negativistic Autic mastery Autic sympathy Alloic mastery Alloic sympathy Dominances Telic Conformist Mastery Autocentric
MBI subscale Emotional Exhaustion
Depersonalization
Personal accomplishment
-.047 -.154 .108 -.064 .112 .219* -.178* -.096
-.071 -.005 .036 .120 .182* .239* -.225* -.220*
-.147 -.136 -.027 .079 .050 .157 -.422* -.158
.086 .080 -.173 * .266
-.089 -.173 * -.112 .409
-.008 .101 .148 -.323
* p < .05.
The first factor analysis entered the three MBI subscales, emotional exhaustion, depersonalization, and personal accomplishment, and the AMSP state subscales: 1) telic, 2) paratelic, 3) conformist, and 4) negativistic, 5) autic mastery, 6) autic sympathy, 7) alloic mastery, and 8) alloic sympathy. Kaiser– Meyer–Olkin measure of sampling adequacy was .601. Bartlett‘s test of sphericity was 2 = 326.84 (p < .000001). Factors were extracted with a principal components method and subjected to a varimax rotation. As shown in Table 7,
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this resulted in a 4–factor solution aligned with 67.1% of the total variance and is the MBI and RT state burnout profile. Table 7. Summary of Items and Factor Loadings for Varimax Orthogonal Three–Factor Solution for the MBI and the AMSP Metamotivational State Scores Subscale MBI
Emotional exhaustion Depersonalization Personal accomplishment AMSP states Telic Paratelic Conformist Negativistic Autic mastery Autic sympathy Alloic mastery Alloic sympathy Eigenvalues % of variance
1
2
3
4
Communality
.765
.62
.792 -.586
.66 .45 .481 .818
.568 -.446 -.311 2.69 24.5
.313 .332 .739 2.02 18.4
.816 .856
.645
.808 .614
1.56 14.3
1.09 9.9
.67 .73 .73 .77 .80 .52 .69 .70
*Note. Factor loadings less than .3 were suppressed for clarity.
The second factor analysis entered the three MBI subscales, emotional exhaustion, depersonalization, and personal accomplishment, and the AMSP dominance subscales: 1) telic, 2) conformist, 3) mastery, and 4) autocentrism to produce an MBI and RT dominance profile. Kaiser–Meyer–Olkin measure of sampling adequacy was .585. Bartlett‘s test of sphericity was 2= 168.14 (df = 21, p < .0001). The factors were extracted with a principal components method and subjected to a varimax rotation. This 3 factor solution shown in Table 8, aligned with 69.97% of the variance.
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Table 8. Summary of Items and Factor Loadings for Varimax Orthogonal Three–Factor Solution for the MBI and the AMSP Metamotivational Dominance Scores Subscale MBI
Emotional exhaustion Depersonalization Personal accomplishment AMSP Dominance Telic Conformist Mastery Autocentric Eigenvalues % of variance
Factor loading 1 2 3
Communality
.816 .870 -.618
.700 .777 .412 .859 .886
.502 2.07 29.65
1.59 22.78
.929 -.538 1.22 17.54
.772 .814 .866 .557
*Note. Factor loadings less than .3 were suppressed for clarity.
In summary, utilizing factor analysis to develop a potential for burnout profile based on RT constructs, feelings of greater depersonalization and emotional exhaustion and lower feelings of personal accomplishment were significantly linked to the autic sympathy states. When examining the dominance profiles, coaches exhibiting an autocentric dominance were at greater risk for burnout. The somatic pairs (telic/paratelic and conformist/negativistic) were not found to be significantly associated with the burnout factors.
DISCUSSION Burnout has been shown to influence the careers of sport coaches (e.g., Kelley and Gill, 1993; Pastore and Judd, 1993). However, most studies have investigated the environmental factors (e.g., job demands, level of coaching, gender differences, etc.) suspected to be associated with burnout. This study, using a theoretical position proposed by Reversal Theory (Apter, 2001; Apter, Fontana, and Murgatroyed, 1985), investigated personal and motivation factors that may be associated with sport coach burnout. The sample included high school varsity basketball coaches from middle size schools to the largest size schools in the state of Texas. The average age of the sample was 42 years old with coaches possessing an average of 16 years of coaching experience. The average winning
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percentage was 53% winning suggesting the sample included coaches with both winning and losing records. Thus, the professional characteristics of the coaches included in this sample represented a wide variety of ages, experience, and success. The average number of hours per week dedicated to coaching basketball during the season was reported to be 39 hours. In all cases, the coaches reported having other school assignments such as teaching or administrative duties, but were not asked to report hours spent on other assignments. Of interest was the fact that less than half of these coaches reported expecting to be coaching basketball 10 years in the future. An analysis of the MBI scores of the coaches showed this sample to be lower in emotional exhaustion and depersonalization and higher in personal accomplishment than norms for teachers published by Maslach, Jackson, and Leiter (1996). It was found that 25 of the 126 coaches (20%) were in the high range for emotional exhaustion while 12 of the 126 (10%) were in the high range for depersonalization. Twenty six (21%) of the coaches reported low levels of personal accomplishment. Therefore, it is assumed that approximately 15% of the current sample is at high risk for burnout. Further comparison of the mean scores showed coaches in this sample were more closely identified with MBI norms established for social service workers than those in the teaching professions (Maslach, Jackson, and Leiter, 1996). This represents a potentially significant finding as it may highlight the importance of the beneficial psychological effects associated with enhanced interpersonal relationships between the coach and his or her athletes. The fact that the coaches in this sample are reporting significantly less depersonalization (M = 7.49, SD = 5.38) than those involved in the traditional teaching settings (M = 11.00, SD = 6.19) (Maslach, Jackson, and Leiter, 1996) could help support this notion, but additional confirmation is necessary. The major aim of this study was to examine the role of the somatic and transactional pairs to the potential for burnout. Both Kerr (1997) and Braman (2001) had focused on the somatic pairs, with Braman suggesting that a satiation effect occurs resulting in meaningless reversals. These meaningless reversals can cause an individual to become distraught, which are often precursors to burnout (i.e., emotional exhaustion). Braman goes on to state that when athletes are telicconformist dominant they become extremely involved in their sport building up a response satiation and are at greater risk for burnout. Kerr has suggested that burnout is related to a tension-stress effect caused by these pairs. It would seem that what they have suggested would apply to coaches. Coaches with a telicconformist dominance would be goal directed knowing the future of their coaching career is related to their success (win/loss records). Therefore, as
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Braman has suggested, burnout may be the result of finding nothing else satisfying, only the performance of their teams. Contrary to expectations, the first factor of the analysis accounting for 29.65% of the variance (Table 8), suggested that coaches who exhibited an autocentric dominance (i.e., transactional pairs) had increased feelings of depersonalization and emotional exhaustion, and reduced feelings of personal accomplishment. Autocentrism is focused on being an individual and what happens to oneself is what matters most while sympathy dominance is one of desired sensitivity and tenderness. Coaches with this dominance profile are seeking power and sympathy (recognition) from others. When this is not occurring, there are depersonalized feelings toward others and emotional exhaustion from not achieving desired personal accomplishment. Autocentrism deals with low felt identification which is ―the degree to which the individual experiences himself/herself to be associated with or part of another person or identity‖ (Apter, 2001, p. 41). This is similar to the construct of depersonalization on the MBI scale. The sympathy dominance is associated with felt toughness that is the result of behaving in a tough and hardy way. The coaches in this sample exhibit a low degree of felt toughness. The mastery dominance would exhibit high felt toughness. Therefore, the coaches who appeared to be identifying less with their teams, and had low feelings of toughness, were potential candidates for burnout. This was the only significant RT dominance factor associated with the MBI factors. It is also of interest to further explore the contribution of the somatic and transactional states to the potential for burnout. Similar to the results presented in Table 7, the first factor (24.5% of the variance) included the MBI subscales and the AMSP autic sympathy state subscale. In addition, both of the AMSP alloic state combinations were also negatively loaded with the MBI subscales on the first factor. These directional findings appear to support the results presented in Table 8, albeit at a more rudimentary level. Thus, the association of the alloic states with less depersonalization is consistent with RT tenets since the alloic state is often associated with high felt identification with other(s). To further explore the implications of the above findings, one should consider the possibility that while some of these coaches may be dominated by one state in each of the pairs, they must function in the opposing nondominant state due to the demands and expectations of the job. It is this dynamic nature of human behavior that distinguishes RT from psychological trait theory (Apter, 2001). For example, a coach who is paratelic dominant may be forced by circumstances to be locked-in to the telic state due to job pressures to win. Studies on athletes by Weinberg (1998) and Young (1998) (cited in Apter, 2001) found that athletes were often
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competing in metamotivational (i.e., situational dominance) states different from their dominant state array. This discrepancy between the preferred level of relevant variables and the actual level can result in tension-stress (Svebak, 1991). Further, this notion of inconsistency between one‘s preferred dominance and being locked-in to an opposing state would seem to have some support in Braman‘s (2001) interpretation of burnout based on RT concepts. The possibility of incongruence between one‘s dominance and the state of functioning and the relation of this imbalance to burnout presents future research possibilities. Social networks have been deemed to be very influential on the reduction of psychological burnout (Garrett and McDaniel, 2001). The lower amount of depersonalization in this sample suggests that the relationships that coaches develop with their players could serve the purpose of a social network for the coach, thus reducing symptoms of burnout. Ivancevich and Matteson (1996) also note that those most susceptible to burnout are those individuals that are most committed to their work. Given the fact that coaches in this sample report a significant amount of time is committed to coaching each week (almost 39 hours per week), researchers must focus on identifying methods coaches use to reduce symptoms of burnout. For example, future studies could focus on examining the nature of the coach-athlete dyad and whether its effects are influential in the reduction of reported burnout indicators. There are several limitations embedded in this study. First, the results reflect a return rate of approximately 31% which is somewhat consistent with the return rate of mail-out surveys (Borg and Gall, 1989). Some coaches had successful seasons while other coaches reported unsuccessful seasons based on win-loss records. However, we did not have a significant number of coaches in our sample with extreme records, especially on the loss side. This eliminated the possibility of using an extreme scores model for statistical analysis. The assumption that coaches with losing seasons would be at greater risk for burnout due to the reward systems involved in coaching may be challenged. It might be suggested that coaches with extremely successful records may be candidates for burnout due to the continuing high expectations for success. Therefore, a larger sample with greater variability in win/loss records would greatly strengthen the study and its application to this population. A second limitation of concern is the reliability of the AMSP where four scales have alphas well below Nunnally‘s (1978) suggested acceptance level. The conformist state scale (.33) is of greatest concern. In four previous studies, Apter (1999) reports alphas ranging from .54 to .70 for this scale. The telic, autic mastery, and autic sympathy scale scores were slightly below those reported by Apter in four studies involving three hundred or more subjects. One explanation
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may be that the coaching sample was very homogeneous, thus restricting variance. This was especially true of the conformist subscale as every coach in the sample reported a conformist dominance. The lack of variance in our sample may have influenced the reliability of the scales (Thorndike, 1967). A second explanation may be that the AMSP was designed to be a more practical version of the MSP and for use in counseling, workshops, and other applied situations. It may need further development for use as a research instrument. In summary, in the RT literature on burnout, it is the somatic pairs that have received the most attention. Intuitively, and supported by this research, the transactional pairs must be considered in burnout research since they deal with human interaction. In conducting this research on such populations, better sampling and data collection procedures must be used. As shown, negativistic coaches, if such exist, did not respond to this research effort.
REFERENCES Apter, M. J. (1999). Users manual for the Apter Motivational Style Profile (AMSP). Rutland, England: Apter International Ltd Apter, M. J. (2001). Motivational styles in everyday life: A guide to Reversal Theory. Washington, DC: American Psychological Association. Apter, M.J. (2007). Reversal Theory: The dynamics of motivation, emotion, and personality. Oxford: Oneworld. Apter, M. J., Fontana, D., and Murgatroyed, S. (1985). Reversal Theory: Applications and developments. Cardiff, Wales: University College Cardiff Press. Apter, M. J., and Svebak, S. (1989). Stress from a Reversal Theory perspective. In C. D. Spielberger and J. Strelau (Eds.), Stress and anxiety (Vol. 12, pp. 3952). New York: Hemisphere. Apter, M. J., Mallows, R., and Williams, S. (1998). The development of the Motivational Style Profile. Personality and Individual Differences, 24, 7-18. Beck, A. (1978). Beck Hopeless Scale, Philadelphia, Pennsylvania: Center for cognitive Therapy. Beck, A., Ward, C. H., Mendelson, M., Mock, J., and Erbaugh, J. K. (1961). An inventory of measuring depression. Archives of General Psychiatry, 4, 561571. Borg, W. R. and Gall, M. D. (1989). Educational Research. White Plains, NY: Longman.
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Braman, O. R. (2001). The role of response satiation in overtraining and burnout in sports. In J.H. Kerr, Counseling Athletes applying Reversal Theory (pp. 129-143). New York: Routledge. Cattell, R. B. (1966). Higher order factor structures and reticular vs. hierarchical formulae for their interpretation. In C. Banks and P. L. Broadhurst (Eds.). Studies in psychology. London: University of London Press. Ltd. DeFillippis, N. A., and McCampbell, E. (1979). The Booklet Category Test, Vol. 1, Subtests I-IV, Odessa, Florida: Psychological Assessment Resources. Drake, B., and Yadama, G. N. (1995). Confirmatory factor analysis of the Maslach burnout inventory. Social Work Research, 19 (3), 184-193. Frey, K. P. (1997). About Reversal Theory. In S. Svebak and M.J. Apter (Eds.), Stress and health: A Reversal Theory perspective (pp. 3-19). Washington, DC: Taylor and Francis. Garrett, D. K., and McDaniel, A. M. (2001). A new look at nurse burnout. Journal of Nursing Administration, 31(2), 91-96. Gold, Y. (1984). The factorial validity of the Maslach Burnout Inventory in a sample of California elementary and junior high school classroom teachers. Educational and Psychological Measurement, 44, 1009-1016 Goodger, K., Gorely, T., Levaliee, D., and Harwood, C. (2007). Burnout in sport: A systematic review. The Sport Psychologist, 21, 127-151. Gorsuch, R.L. (1983). Factor Analysis, Hillsdale, NJ: Lawrence Erlbaum. Ivancevich, J. M. and Matteson, M. T. (1996). Organizational behavior and management. New York: McGraw-Hill. Iwanicki, E. F., and Schwab, R. L. (1981). A cross-validational study of the Maslach Burnout Inventory. Educational and Psychological Measurement, 41, 1167-1174. Kelley, B. C. (1994). A model of stress and burnout in collegiate coaches: Effects of gender and time of season. Research Quarterly for Exercise and Sport, 65, 48-58. Kelley, B. C., and Gill, D. L. (1993). An examination of personal/situational variables, stress appraisal, and burnout in collegiate teacher-coaches. Research Quarterly for Exercise and Sport, 64, 94-102. Kerr, J. H. (1997). Motivation and emotion in sport: Reversal Theory. Hove, England: Psychology Press. Maslach, C., Jackson, S. E., and Leiter, M. P. (1996). Maslach burnout inventory manual (3rd ed.). Palo Alto, CA: Consulting Psychologists. Nunnally, J. (1978). Psychometric theory (2nd ed.). New York: McGraw-Hill. Oltman, P. K., Raskin, E., and Witkin, H. A. (1971). Group embedded Figures Test. Palo Alto, California: Consulting Psychologists Press.
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Pastore, D. L., and Judd, M. R. (1993). Gender differences in burnout among coaches of women‘s athletic teams at 2-year colleges. Sociology of Sport Journal, 10, 205-212. Power, V., Findlay, B. and Heskin, K. (1998). Australian validation of the Personal Orientation Profile. Paper presented at the seventh International Conference on Reversal Theory, Swinburne University, Melbourne, Australia, 1995. Price, M. S., and Weiss, M. R. (2000). Relationships among coach burnout, coach behaviors, and athletes‘ psychological responses. The Sport Psychologist, 14, 391-417. Raedeke, T. D. (1997). Is athlete burnout more than just stress? A sport commitment perspective. Journal of Sport and Exercise Psychology, 19, 391410. Raedeke, T. D., Granzyk, T. L., and Warren, A. (2000). Why coaches experience burnout: A commitment perspective. Journal of Sport and Exercise Psychology, 22, 85-105. Royce, J. R. (1967). Factors as theoretical constructs. In D.N. Jackson and S. Messick (Eds.), Problems in human assessment (pp 318-325). New York: McGraw-Hill. Smith, R. E. (1996). Toward a cognitive-affective model of athletic burnout. Journal of Sport Psychology, 8, 36-50. Svebak, S. (1991). The role of effort in stress and emotion. In Z. Kulcsar, G. L. Van Heck, and C. Spielberger (Eds.) Stress and emotion: Anger, anxiety, and curiosity (Vol. 14, pp.121-133). New York: Hemisphere. Thorndike, R. L. (1967). Reliability. In D. N. Jackson and S. Messick (Eds.), Problems in Human Assessment (pp. 217-240). New York: McGraw-Hill. Vealey, R. S., Armstrong, L., Comar, W., and Greenleaf, C. A. (1998). Influence of perceived coaching behaviors on burnout and competitive anxiety in female college athletes. Journal of Applied Sport Psychology, 10, 297-318. Vealey, R. S., Udry, E. M., Zimmerman, V., and Soliday, J. (1992). Intrapersonal and situational predictors of coaching burnout. Journal of Sport and Exercise Psychology, 14, 40-58. Weinberg, G. (1998). Motivation in ultra distance runners: A Reversal Theory approach to optimal experience. Unpublished doctoral dissertation. Fielding Institute, Santa Barbara, CA. Young, J. A. (1998). Professional tennis players in flow: Flow Theory and Reversal Theory perspectives. Unpublished doctoral dissertation. Faculty of Science, Monash University, Melbourne, Australia.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 8
COACHING BEHAVIOR: LEADERSHIP PREFERENCES OF ROOKIE AND VETERAN COLLEGE ATHLETES Christopher M. Keshock and Shelley Bradford University of South Alabama, U.S.A.
ABSTRACT Of all the managerial responsibilities, leadership, which is inextricably intertwined with all the functions a head coach performs, is considered by Chelladurai and Saleh (1980) to be the most significant task executed by a coach. Studies in the area of sports leadership behavior have shown individual athlete effectiveness is largely attributed to the leadership behavior exercised by a coach (Amorose and Horn, 2000; Beam, Serwatka, and Wilson, 2004; Sherman, Fuller, and Speed, 2000; Zhang, Jensen, and Mann, 1997). Using the Leadership Scale for Sports (Chelladurai and Saleh, 1980) the present study revealed certain preferences for coaching behaviors between rookie and veteran athletes competing at the intercollegiate level. Implications drawn from the study suggest college coaches to emphasize certain dimensions of leadership according to the preferences existing amongst rookie and veteran players on a team.
Contact Information: Dr. Chris Keshock, University of South Alabama. HPELS Department, Mobile, Alabama 36688. (251) 461-1613. E-mial:
[email protected]
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From the time when competitive team sports became an enjoyable dimension in the lives of people, leadership issues have intrigued those directing programs in many different historical eras. Initially, studies designed in the behavioral sciences to investigate leadership styles and motivational tendencies of groups within organizational systems provided findings that were extrapolated or revised to apply to sports related environments (Halpin and Winery, 1957; House, 1971; Katz, Maccoby, and Morse, 1950; Stogdill, 1948). Subsequently, a body of literature relevant to actual sports environments has been developed for possible use by coaches, athletic trainers, administrators, and other professionals involved in sports endeavors (Beam, Serwatka, and Wilson, 2004; Chelladurai, 1990; Horn, 2002; Smoll and Smith, 2001; Zhang, Jensen, and Mann, 1997). These studies and reviews have led to an awakening of interest in the relationship of sport and leadership as sports teams have sought to gain prominence in international, professional, interscholastic, and youth sports competition (LeUnes and Nation, 1996; Weinberg and Gould, 2007). Research in the area of preferred sport leadership behavior (Chelladurai and Reimer, 1998; Horn, 2002; Sherman, Fuller, and Speed, 2000; Zhang, et al., 1997) has demonstrated that an athlete‘s effectiveness can be attributed in large measure to the leadership behaviors evidenced by one‘s coach. How these behaviors are perceived by the respective athletes on an athletic team, which may lead to the attainment of individual performance goals, is a key element worthy of systematic, empirical investigation in the area of sport leadership. However, despite previous efforts aimed at sport leadership, researchers and consultants have observed a gap between the scientific understanding of leadership coaching behaviors preferred by athletes and the value of this knowledge as a carryover into practical situations (Slack and Parent, 2006; Weinberg and Gould, 2007). This may be attributable to a lack of a clear scientific examination of leadership preferences athletes have for coaches and valid instrumentation to assess such relationships. Therefore, Taylor and Wilson (2005) suggest research that advances knowledge and understanding of coach-athlete relationships at both scientific and practical levels is necessary to bridge this gap. One area that has not been fully investigated to date that would add to the growing body of knowledge is the differences and similarities amongst college players and their preferred leadership style based upon team participation status (rookies and veterans). It stands to reason older returning players on a college team or veterans would have more overall experience at their school and in general sports as a whole then those younger players new to a intercollegiate sports environment commonly classified as rookies who are high school graduates moving on to play in college or those transferring in from another institution.
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Additionally, one may posit incoming high school recruits and junior college transfers new to participating at a higher competition level as college rookies may not be as developed when it comes to skill mastery or knowledge of a sport; which in turn would suggest different preferences toward how they want to be coached and ultimately led. In an effort to expand past literature, especially literature involving college athletes, the present study examined the preferred leadership behaviors of rookie and veteran college athletes. Since it appears the study of sport leadership is an evolving enterprise, empirical measures to investigate the coach/athlete leadership dynamic based upon whether a player is a rookie or classified as a veteran may provide further support to ultimately help an intercollegiate coach determine how college student athletes prefer to be led.
LITERATURE REVIEW In assessing the managerial functions of a coach/leader, many different roles are often executed. These include planning activities, recruitment of student athletes, budgeting, scheduling, networking, organizing the promotion of athletic events, counseling of players (to the extent that professional skills permit this), and, most importantly, applying leadership principles to the practice of coaching. While some of these functions may be assigned to other staff members in a department of athletics, clearly defined leadership activities are primarily within the realm of the individual athletic coach and to be implemented as he or she sees fit. Yukl and Van Fleet (1992) have provided a working definition of leadership to include the shaping of organizational objectives, maintaining the groups‘ culture, and influencing the implementation of winning strategies. In this approach, the main focus is on ―what the leader does rather than what the leader is‖ (p. 149). Chelladurai (1999), in explaining the dynamic interaction between a coach and players, describes leadership principles as part of a behavioral process, interpersonal in nature, and aimed at influencing and motivating individuals toward group or organizational goals within athletic competition. However, Slack and Parent (2006) suggest caution should be used in the application of these leadership definitions concerning how situational variables- task structure, characteristics of the environment, or subordinate‘s characteristics- impact leadership effectiveness. Therefore, in order to more fully understand these sports leadership research has focused on the feedback given by sports participants concerning the behaviors of their coaches in different situations.
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Coaching Feedback The work of Black and Weiss (1992); Sherman, et al. (2000); and Wang, Chen, and Ji (2004) implied that the type of feedback athletes perceive as being given by a coach during practices and competitive events has a significant impact upon the athlete‘s own perceptions of their abilities and motivation. Of equal importance in these studies were the findings that athletes preferred their coaches to exhibit consistent behavioral patterns in terms of the leadership role which, in turn, enhanced their own attainment of well-developed competencies leading to eventual success. Studies such as this suggest that a coach striving to be an effective leader capable of motivating athletes would do well to recognize his or her own behavioral tendencies as perceived by team members- a self analysis potentially contributing to greater fulfillment and success in the field. Self-analysis was recommended by ancient philosophers thousands of years ago as part of the personal adjustment principle or admonition to ―Know Thyself‖. Attempts to enhance one‘s knowledge of self, to include behavioral tendencies, has been developed as the use of psychological and educational instrumentation grounded in empirical data gathering to assess athletes‘ preferences for certain coaching behaviors related to effective leadership. In this evaluative process, it is projected that the relationships between athletes and coaches will be heightened as more is known about their unique interaction (Taylor and Wilson, 2005).
Multidimensional Model of Leadership in Coaching In order for effective coaching to transpire certain conditions relating to the satisfaction of athletes must fall into place. These are described in the multidimensional model of leadership in coaching applied by Salminen and Liukkonen (1996) evolving from the works of Chelladurai (1978); Chelladurai and Saleh (1980); Chelladurai and Carron (1983) in which three major areas of effective leadership behavior are stressed: Required Behavior, Actual Behavior, and Preferred Behavior. These dimensions of the coach/athlete dynamic must be established in order for athletes to experience satisfaction and subsequently perform well (Chelladurai, 1984; Chelladurai and Saleh, 1980, Horn and Carron, 1985; Wang, et al., 2004). In the multidimensional model, required leader behavior consists of antecedent variables (size, technology, and structure) described as task-oriented and conducive to the realization of group objectives or behavior expected of the leader on a more formal basis such as organizational demands (LeUnes and
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Nation, 1996). Actual leader behavior consists of two determinants: the breadth of technical skills and conceptual abilities possessed by the coach and athlete or behavior that is engaged in irrespective of norms or subordinate preferences (Taylor and Wilson, 2005). Additionally, preferred leader behavior relates to the preferences of participants for specific leader behaviors stemming from situational characteristics and the characteristics of the team members themselves or the behavior subordinates would like to see in the leader (Chelladurai, 1986). In this complex arrangement, the presence of these three dimensions of leadership in a sports environment promises to do much in fostering personal satisfaction for both the coach and athletes while improving performances (Chelladurai, 1999: Sherman, et al., 2000). Weiss and Friedrichs (1986) supported the evolving multidimensional model of sports leadership, as contrasted to conceptualizations of leadership in other fields. Their conclusion stated, ―it is the only leadership model that utilizes research findings from the field of sports in its formulization‖ (p. 334). While this model seeks to synthesize the various forms of leadership theories to be found in the larger culture, it is designed primarily to relate to sport environments or apply to sport leadership behaviors that suggest important practical implications (Holmes, McNeil, Adorna, and Procaccino, 2008; Sherman, et al., 2000). In retrieving and interpreting data related to the preferences athletes have towards different coaching behaviors (multidimensional model paradigm), a self report inventory was developed by Chelladurai and Saleh (1980). Prior to that time, a number of instruments had been created to measure leadership behavior in industrial settings (Halpin, 1957; Fleishman, Harris, and Burtt, 1957); however, instrumentation concomitant to the field of sports was relatively rare. Reasons cited for this paucity of measurement information included the following: Athletes spend a disproportionate amount of time training for competition in contrast to much shorter training periods in the business sector. Winning is always accompanied by losing which is not always the case in organizational settings. And members of athletic teams are only assembled for a short period of time while in the business sector the time frame is much longer (Chelladurai and Saleh, 1980, p. 36).
Leadership Scale for Sport The Leadership Scale for Sport (LSS) was developed in order to provide insights concerning the leadership behaviors preferred by athletes and to provide
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data of some importance in assessing the multidimensional model of sports leadership. As described by Amorose and Horn (2000), it is comprised of forty items representing five distinct dimensions of leader behavior. Of the five subscales of the LSS, two measure the coach‘s decision-making style (democratic or autocratic), two measure the coach‘s motivational tendencies (social support and positive feedback), and one measures the coach‘s instructional behavior (training and instruction) (p. 68). Further descriptions of the five dimensions of leader behavior, as cited in Singer, Murphy, and Tennant (1999) are included in Table 1. Because it is one of the few instruments designed to effectively assess athletes‘ preferences for specific coaching behaviors, the LSS has been utilized in a variety of situations or environments. Table 1. Dimensions of Leader Behavior in Sport Dimension
Description
Training and Instruction
Coaching behavior aimed at improving the athletes‘ performance by emphasizing and facilitating hard and strenuous training, instructing them in the skills, techniques, and tactics of sport; clarifying the relationship among members; and structuring and coordinating the members‘ activities
Social Support
Coaching behavior characterized by a concern for the welfare of individual athletes, positive group atmosphere, and warm interpersonal relations with members
Positive Feedback
Coaching behavior that reinforces an athlete by recognizing and rewarding good performance Coaching behavior that allows greater participation by athletes in decisions pertaining to group goals, practice methods, and game tactics and strategies Coaching behavior that involves independent decision making and that stresses personal authority
Democratic Behavior
Autocratic Behavior
Source: Chelladurai and Saleh (1980).
It has been administered to youth athletes (Martin, Jackson, Richardson, and Weiller, 1999); male and female college students receiving athletic scholarships in the United States (Amorose and Horn, 2000); French Canadian hockey players (Lacoste and Laurencelle, 1989); Indian athletes (Chelladurai, 1986); Australian
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football, netball, and basketball participants (Sherman, et al., 2000); and Korean university athletes (Kim, Lee, and Lee, 1990) as part of making cross cultural comparisons. The varied findings have been attributed to personal characteristics of the athlete subjects such as age, gender, and ethnicity as well as situational variables to include collegiate, high school, and youth sport competition. This has raised caveats for sport professionals seeking to better identify specific leadership dimensions as preferred by athletes. Zhang, Jensen, and Mann (1997) revised the LSS but advised that the use of the revised LSS makes no difference from the original scale. Further, the various versions of the LSS which have been translated into several languages (Isberg and Chelladurai, 1990; Kim, et al., 1990) can be used alone or together for different investigations that are related to the examination, prescription, selection and/or training of coaching leadership behaviors. In any event, as indicated by Weinberg and Gould (2007), the LSS has received extensive testing and psychometric support in recent years; and, despite any limitations Holmes, et al., (2008); LeUnes and Nation (1996); Sherman, et al., (2000); and Shields, Gardner, Bredemeier, and Bostro (1997) support it as a viable mechanism for sport scientists to conduct leadership research now and in the future.
Situational Characteristics and Leadership Preferences An underlying tenet of situational leadership is that different types of leadership behavior are more appropriate than others in particular situations (Slack and Parent, 2006). The need to assess situations and choose an appropriate leadership response is inherent within the Multi-Dimensional Model of Leadership suggesting team member preferences for certain forms of leader behavior will reflect the influences of the situation (Chelladurai, 2005). Fundamentally then, situational characteristics such as sport type, size of team, level of competition, structure, organizational goals, and social norms ostensibly become antecedents to the type of behavior players would like to see in their coach (Gillentine and Crow, 2005). Furthermore, Jowett and Lavelle (2007) suggest that culture, team vs. individual sport, and the competitive nature of participants are other possible situational variables that affect preferred leadership behavior. For instance, sports teams participating at a higher level of competition are presumed to possess greater skills and ability than those competing at lower
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levels. As a result Chelladurai and Carron (1983) claimed advanced competition athletes may prefer a relationship oriented approach (supportive behaviors) more readily than other forms of coaching leadership behavior. Within this parameter an assumption can be made that teams benefit from leadership that meshes with the stage of development of the particular group. This draws attention to ways leaders can work with subordinates to build up confidence levels (Slack and Parent, 2006). To a certain extent then the situational approach to leadership is based upon the premise that different situations require different types of leadership; and, subsequently successful leaders are able to discern when to emphasize certain behaviors over others to improve group effectiveness (Jensen and Overman, 2003).
Athlete Characteristics and Leadership Preferences Drawing further upon the multidimensional model of sport coaching, a major factor in team members‘ preferences for specific leader behaviors would be that of the individual characteristics of group members or players (Singer, et al., 1999). It was reported that the needs for achievement (Nach), affiliation, cognitive security, and competence in a task influence a player‘s preferences for coaching and guidance, social support, and feedback. Other factors affecting team member preferences, as described in Hershey and Blanchard‘s (1977) leadership theory, suggest that leaders should vary their behaviors according to subordinates‘ readiness which was defined as a combination of the members‘ education, experience, achievement motivation, and willingness to take on responsibilities. This eclectic stance was a derivative of House‘s (1971) Path-goal theory where subordinates‘ are led down the most effective paths to reach organizational and personal goals according to their relevant ability. For example, one player may already have a firm understanding of how to carry out sport related tasks and therefore has the ability to do so requiring less guidance from a coach. However, another player who has not yet been exposed to the ways in which to develop skills to perform tasks may be led differently. Subsequently, a rookie player or new transfer to a team may prefer a coach to spend more time with them clarifying goals and giving instruction, ultimately guiding the player down a different path since the player is new to a program. Compounding interpretation difficulties is the common problem confronting coaches in regards to whether or not certain types of athletes have consistent preferences as to the ways they want to be coached; for example, differences
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between younger and older players. Neil and Kirby (1985) suggested less experienced athletes have different coaching preferences than more-experienced athletes. In contrast, the work of Martin, et al., (1999) involving early verses late adolescent athletes suggested that there were similarities for both groups in terms of preferences for coaching behaviors. In the light of some contradictory findings such as these involving athletic maturity and past sport experience, the present investigation sought to explore differences in preferences for coaching behavior between returning players of intercollegiate athletic teams or veterans (experience of one year or more of athletic competition at a four-year institution) and those considered to be first year players or rookies (less experienced players with no previous college history at the same four-year school).
METHODOLOGY Sample In order to ascertain the differences in coaching preferences of intercollegiate athletes as a function of their levels of experience at the institution, the Leadership Scale for Sport (LSS) was administered to male and female athletic teams from a southeastern United States National Collegiate Athletic Association (NCAA) Division II member institution. Of the university‘s eleven athletic teams, four agreed to participate in the study: women‘s volleyball (WVB), men‘s baseball (MBSB), women‘s basketball (WBSK), and women‘s softball (WSB).
Procedures Permission to conduct this study was granted by obtaining Institutional Review Board (IRB) approval from the investigators institution. Further, permission was granted by the athletic department where the study was held, and then from the respective head coaches of the teams involved in the study. The principle investigator administered the questionnaire to each team before practice. At each administration, a verbal explanation of the study was given to each participant. Reference to the description of the demographics section and preferred coaching behavior sections were clarified. Athletes were informed of their voluntary and anonymous participation in the completion of the study, and participants were told they could stop at any time without any benefits being
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forfeited. Further, athletes were given as much time as they needed to complete the survey and were told that their answers would remain confidential.
Measures Each participant was given the questionnaire which included five demographic questions in the first section to obtain information relating to the team type, academic rank, athletic eligibility rank, years of experience at the school and the type of school that was attended the previous year. Subjects were then asked to complete the LSS section of the questionnaire designed by Chelladuria and Saleh (1980). Participants responded to each item in the LSS (training and instruction-TI, democratic behavior-DB, autocratic behavior-AB, social support-SS and positive feedback-PF) by selecting one of the response categories on a 5-point Likert-type scale (always-5, often-4, occasionally-3, seldom-2, or never-1). Response categories were anchored at 100%, 75%, 50%, 25%, and 0% of the time respectively. Further, respondents were told to preface each item with the words, ―I prefer my coach to…‖ In a previous study Chelladauri and Saleh (1980) reported that the test-retest reliability estimates from the repeated responses of 53 physical education majors after a four week interval on the LSS were 0.72 for training and instruction, 0.82 for democratic behavior, 0.76 for autocratic behavior, 0.71 for social support, and 0.79 for positive feedback. These values are adequate and comparable to those reported in the literature for similar scores (Sherman, et al., 2000; Shields, et al., 1997).
RESULTS There were 66 athletes who participated in this study and this represented a 94.2% response rate. Twelve participants (18.2%) were from the women‘s volleyball team, twenty-three (34.8%) from the men‘s basketball team, sixteen (24.2%) from the women‘s basketball team and fifteen (22.7%) from the women‘s softball team. Of the 66 participants, there were 36 first year players which represented 54.5 % of the sample and included eight junior college transfers, two players transferred from other four-year institutions, and 26 players who played at the high school level the previous year. The 30 returning players represented 45.5 % of the sample and included one red-shirt freshman (member of his/her team last
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year but did not participate in contests), nine sophomores, 12 juniors, seven seniors and one fifth-year senior (4 years with his/her team with one of those years being a red-shirt year). Overall, the returning players had a mean of 1.96 years of experience. In applying the multidimensional model of sport coaching to a group of Division II student-athletes, it became apparent that their preferences for specific leader behaviors were driven by individual characteristics as well as situational factors unique to a significant historical period. Following are the results of the LSS administration to a sample of 66 collegiate competitors:
DISCUSSION Once the data were compiled, copies of the results were shared with the respective coaches who agreed to cooperate in the investigation of preferred leadership behaviors. For the most part coaches were receptive to the information provided indicating that it would be utilized informally initially and more systematically as their coaching careers progressed. In particular, decision-making procedures were described as amenable to review as part of the executive functions coaches have long carried out in working with young men and women competing in the challenging field of sports. An appraisal of the mean (x) scores from Table 2 indicates that Training and Instruction, in terms of preferred leader behavior, was deemed to be the most important aspect of a leader‘s (coaching) involvement with undergraduate athletes. As described in the LSS manual, this includes coaching behavior aimed at improving an athlete‘s performance by emphasizing hard and strenuous training; instruction in the skills, clarifying relationships among members; and structuring and coordinating members‘ activities. The other elevated scaled score of Positive Feedback (coaching behavior which reinforces an athlete by recognizing and rewarding good performance) more nearly describes the accepted or traditional aspects interpreted by many theoreticians or practitioners as good leadership. The rookie competitors and veterans had similar, elevated perceptions of this coaching behavior in effect valuing the efforts of a leader to energize efforts with praise rather than ridicule and to ―catch them being good‖ in the manner of positive reinforcement as used in behavioral training. Social support mean scores in the moderate range (occasionally or 50% of the time) were similar across the rookie and veteran competitors categories. Still another set of scaled scores, Democratic Behavior, was evidenced in the moderate
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range for both groups of athletes with rookies having a slightly higher mean (x=3.33) than veteran competitors (x=3.18). This pattern appears to support Chelladurai‘s (1999) observation that individuals favoring a democratic leadership style need to feel a sense of ownership in the groups endeavors, get feedback about how decisions are made, and to become more knowledgeable about common challenges or problems. As rookie players learn more about decisionmaking in particular, it is projected that their feelings of self-worth will be enhanced. Veteran players on the other hand, being familiar with a coach‘s management practices in the collegiate environment, have less of a need in this area. Table 2. Descriptive Statistics of the Leadership Scale for Sports First year athletes
Returning athletes
Subscales
x
x
Training and Instruction
4.28
4.33
Democratic Behavior Autocratic Behavior
3.33 2.15
3.18 2.47
Social Support Positive Feedback
3.73 4.08
3.20 4.33
Note: N= 36 for first year athletes and N= 30 for returning athletes.
As might be expected, the lowest LSS scores were produced in the Autocratic Behavior scale, indicating coaching behavior involving independent decisionmaking which stresses the personal authority of a leader. The slightly higher mean score (x=2.47) for veteran athletes as contrasted with a mean score of 2.15 for rookies may be due to a number of factors operating in an athletic environment. Returning athletes with advanced knowledge of a coach‘s ability to make decisions under pressure-oriented conditions would tend to draw upon his/her history of past successes and consequently avoid conflict-ridden situations. Both samples, however, reflected their disdain for this style of leadership which should not be considered unusual or atypical in a democratic society. Determining what makes effective sport leadership is clearly not a simple process since it is influenced by a variety of personal and situational factors (Weinberg and Gould, 2007). Previous studies have attempted to assess players‘ preferred leadership behaviors of coaches based upon antecedents such as gender (Martin, et al., 1999); nationality (Lacoste and Laurencelle, 1989); type of sport (Chelladurai and Reimer, 1998); and age and maturity (Chelladurai and Carron,
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1983). In the case of the later, sport is often seen as a mechanism for fostering maturity, however Chelladurai and Carron (1983) posit sport is largely an autocratic enterprise that may run counter to the development of maturity. ―As people get older and mature athletically (reach college age), they increasingly prefer coaches who are more autocratic and socially supportive‖ (Weinberg and Gould, 2007, p. 218). On the other hand younger adolescents (high school) preferred democratic coaches who gave positive feedback and much training and instruction (Martin, et al., 1999). Taking the works of others a step further this study attempted to define the maturity characteristic beyond common classification schemes such as the level of competition into years playing experience at a college institution. Every year college coaches are faced with varying proportions of both incoming rookie athletes in addition to veteran players returning to complete their four or five years of eligibility on the same team at the same school. This presents a different picture in comparison to evaluating preferred leadership styles according to a player‘s maturity level using age as numerical descriptors. It is quite possible some rookies on a college team may be older, as incoming transfer students or junior college recruits when juxtaposed with team veterans (sophomores, juniors, and seniors) who have taken the traditional route of signing out of high school and remaining at the same school for consecutive years until graduation. One highlight derived from this study in comparison to other maturity driven leadership studies (high school verses college athletes and numerical age) was that veteran players on college sports teams preferred more autocratic coaches then rookies. Therefore, coaches operating at the college level may want to consider giving rookies more decision making opportunities in comparison to veteran players since incoming players prefer the democratic support system more. This is not to say that rookies on a college team are looking for a coach to make decisions on his or her own to get things done, only that rookie players prefer coaches who engage players in participative decision making in the areas of group goals, practice methods, game tactics and strategies. Interestingly, this inference counters one of the assumed attributes often generalized from sports participation, in that it builds maturity in players. College veteran athletes surveyed in the present study preferred less responsibility, empowerment, and opportunities to voice their opinion which are normally considered values inherent in mature persons. One other noticeable presumption drawn from the study results was the effect of rookie players preferring coaching behavior characterized by concern for the welfare of athletes, a positive group atmosphere, and warm interpersonal relations with members on a team to exhibit more social support in comparison to the way
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veteran players preferred this leadership style. Again, as seen with the autocratic/democratic preferred leadership characteristics it is a matter of what should be emphasized. When it comes to social support behavior coaches may be wise to emphasize this leadership dimension more with their rookie athletes in relation to the social support given to veteran players.
CONCLUSION The present study depicted the preferences and in some categories the differences regarding preferred coaching behaviors for rookie and veteran athletes at a Division II university. The Leadership Scale for Sports (LSS), a self-report inventory in the manner of a Likert-type scale, when administered to athletes on a voluntary, anonymous basis, yielded promising results. In this university sample, preferences were evidenced in the areas of Training and Instruction and Positive Feedback while Social Support, Democratic Behavior, and Autocratic Behavior were less preferred aspects of coaching behaviors from both rookie and veteran players at a NCAA DII school. Of note were result differences between veterans and rookies in the areas of autocratic, democratic and social support dimensions which would suggest to college coaches that more or less emphasis should be placed in these leadership behaviors according to whether a player is classified as a rookie or veteran participant. Further research involving athletes that participate in other sports than those selected for this study may be able to confirm the results. More specifically, would the sports that have a higher inclination for contact (football, field hockey) or lower levels of game tactics (cross-country) affect the outcome of preferred coaching behavior? Fortunately, there have been some studies that have begun to classify players and their preferences of coaching behaviors. Another area that could be examined is leadership preferences and how it relates to gender in rookie vs. veteran athletes. That is, do male rookies and veteran athletes have the same leadership preferences as female rookies and veteran athletes? Additional investigations in this area may surface and possibly validate the groupings of athletes so that coaches can effectively lead their teams towards positive results.
Limitations It is important to note several design limitations exist with the present study. The small sample of athletes (n=66) from a NCAA DII affiliated institution
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situate this study as a case study of one college team in the larger area of intercollegiate athletics. It is cautioned that as a case study the results were highly based on the organizational components surrounding athletes competing at the DII level and may not be readily generalized to other college environments. Nevertheless, it has been demonstrated that there are some similarities between what was found in this study and the principles developed in previous research on preferred sport leadership. This study is one of a few that have focused on experience and maturity levels of sports participants and knowingly the only one to date which has used rookie and veteran classifications at the college level to examine preferred coaching leadership behavior. In this sense the study provides insight toward how student-athletes prefer to be led, and at the very least what has been demonstrated in this case lends itself to being put to consideration by college coaches. The current study supported the future use of the LSS as an important part of the self analysis that successful coaches and other leaders undertake on a consistent basis. This is especially important in the field of sport as young athletes become more aware of the importance of decision-making practices at the collegiate level and as the public in general scrutinizes the leadership practices of coaches as described by the media and the athletes.
REFERENCES Amorose, A. J., and Horn, T. S. (2000). Intrinsic motivation: Relationship with college athletes‘ gender, scholarship status, and perceptions of their coach‘s behavior. Journal of Sport and Exercise Psychology, 22, 63-87. Beam, J. W., Serwatka, T. S., and Wilson, W. J. (2004). Preferred leadership of NCAA division I and II intercollegiate student-athletes. Journal of Sport Behavior, 27 (1), 1-17. Black, J. S., and Weiss, M. R. (1992). The relationship among perceived coaching behaviors, perceptions of ability, and motivation in competitive age groups swimmers. Journal of Sport and Exercise Psychology, 14(3), 309-325. Chelladurai, P. (1978). A contingency model of leadership in athletics. Unpublished doctoral dissertation, University of Waterloo, Canada. Chelladurai, P. (1984). Discrepancy between preferences and perceptions of leadership behavior and satisfaction of athletes in varying sports. Journal of Sport Psychology, 6, 27-41.
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Chelladurai, P. (1986). Applicability of the Leadership Scale for Sports to the Indian context. In J. Watkins, T. Riley, and L. Burwitz (Eds.), Sport science (pp. 291-296). New York: E. and F. N. Spon Ltd. Chelladurai, P. (1990). Leadership in sports: A review. International Journal of Sport Psychology, 21, 328-354. Chelladurai, P. (1999). Human resource management in sport and recreation. Champagne, IL: Human Kinetics. Chelladurai, P. (2005). Managing organizations for sport and physical activity. Scottsdale, AZ: Holcomb Hathaway Publishers. Chelladurai, P., and Carron, A. V. (1983). Athletic maturity and preferred leadership. Journal of Sport Psychology, 5, 371-380. Chelladurai, P. and Reimer, H. (1998). Measurement of leadership in sport. In J. Duda (Ed.), Advances in sport and exercise psychology measurement (pp. 227-256). Morgantown, WV : Fitness Information Technology. Chelladurai, P. and Saleh, S. D. (1980). Dimensions of leader behavior in sport: Development of a leadership scale. Journal of Sport Psychology, 2, 34-45. Fleishman, E. A., Harris, E. F., and Burtt, H. E. (1957). Leadership and supervision in industry. Columbus: Ohio State University, Bureau of Business Research. Gillentine, A. and Crow, R. B. (2005). Foundations of sport management. Morgantown, WV: Fitness Information Technology. Halpin, A. W. (1957). The observed behavior and ideal leader behavior of aircraft commanders and school superintendents. In R. M. Stodgill and A. E. Coons (eds). Leader behavior: Its description and measurement, 65-68. Columbus: Ohio State University, Bureau of Business Research. Halpin, A. W. and Winery, B. J. (1957). A factorial study of leader behavior descriptions. In R. M. Stodgill and A. E. Coons (Eds.), Leader behavior: Its description and measurement, 39-51, Columbus: Ohio State University, Bureau of Business Research. Hershey. P and Blanchard, H. K. (1977). Management of organizational behavior (3rd ed.), Englewood Cliffs, NJ: Prentice-Hall. Holmes, R. M., McNeil, M., Adorna, P., and Procaccino, J. K. (2008). Collegiate student athletes‘ preferences and perceptions regarding peer relationships. Journal of Sport Behavior, 31(4), 338-351. Horn, T., and Carron, A. V. (1985). Compatibility in coach-athlete relationships. Journal of Sport Psychology, 7, 137-149. Horn, T. S. (2002). Coaching effectiveness in the sport domain. In T. Horn (Ed.), Advances in sport psychology (2nd ed., pp. 309-365). Champaign, IL: Human Kinetics.
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House, R. J. (1971). A path goal theory of leader effectiveness. Administrative Science Quarterly, 16, 321-338. Isberg, L. and Chelladurai, P. (1990). The leadership scale for sports: its applicability to the Swedish context. Unpublished manuscript, University College of Falun/Borlange, Sweden. Jensen, C. R., and Overman, S. J. (2003). Administration and management of physical education and athletic programs. Prospect Heights, IL: Waveland Press. Jowett, S. and Lavelle, D. (2007). Social psychology in sport. Champaign, IL: Human Kinetics. Katz, D., Maccoby, N., and Morse, N. (1950). Productivity, supervision and morale in office situations. Ann Arbor, MI: University of Michigan. Kim, B. H., Lee, H. K., and Lee, J. Y. (1990). A study on the coaches’ leader behavior in sports. Unpublished manuscript, Korean Sport Science Institute. Lacoste, P. L. and Laurencelle, L. (1989). The French validation of the leadership scale for sports. Unpublished abstract, University of Quebec, Canada. LeUnes, A. D., and Nation, J. R. (1996). Sport psychology. Chicago, IL: NelsonHall. Martin, S. B., Jackson, A. W., Richardson, P. A., and Weiller, K. H. (1999). Coaching preferences of adolescent youths and their parents. Journal of Applied Sport Psychology, 11, 247-262. Neil, G. I., and Kirby, S L. (1985). Coaching styles and preferred leadership among rowers and paddlers. Journal of Sport Behavior, 8, 3–17. Salminen, S., and Liukkonen, J. (1996). Coach-athlete relationships and coaching behaviorin training sessions. International Journal of Sport Psychology, 27, 5967. Sherman, C. A., Fuller, R., and Speed, H. D. (2000). Gender comparisons of preferred coaching behaviors in Australian sports. Journal of Sport Behavior, 23(4), 389-406. Shields, D. L., Gardner, D. E., Bredemeier, B. J., and Bostro, A. (1997). The relationship between leadership behaviors and group cohesion in team sports. The Journal of Psychology, 131(2), 196-210. Singer, R. N., Murphy, M., and Tennant, L. K. (1999). Handbook of research on sport psychology, pp. 647-671. New York: Macmillan. Slack, T., and Parent, M. M. (2006). Understanding sport organizations: The application of organization theory. Champaign, IL: Human Kinetics. Smoll, F. L., and Smith, R. E. (2001). Conducting sport psychology training programs for coaches: Cognitive-behavioral principles and techniques. In J.
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M. Williams (Ed.), Applied sport psychology: Personal growth to peak performance (4th ed., pp. 378-400). Mountain View, CA: Mayfield. Stogdill, R. M. (1948). Personal factors associated with leadership: Survey of literature. Journal of Psychology, 25, 35-71. Taylor, J., and Wilson, G. S. (2005). Applying sport psychology: Four perspectives. Champaign, IL: Human Kinetics. Wang, J., Chen, L., and Ji, J. C. (2004). Athletes‘ perceptions on coaches‘ behaviors and competitive situations at collegiate level. International Sports Journal, 8(2), 1-14. Weiss, M. R., and Friedrichs, W. D. (1986). The influence of leader behaviors, coach attributes, and institutional variables on performance and satisfaction of collegiate basketball teams. Journal of Sport Psychology, 8, 342-348. Weinberg, R. S., and Gould, D. (2007). Foundations of sport and exercise psychology. Champaign, IL: Human Kinetics. Yukl, G. A. and Van Fleet, D. D. (1992). Theory and research on leadership in organizations. In M. D. Dunnette and L. M. Hough (Eds.), Handbook of industrial and organizational psychology (2nd ed., pp. 147-197). Chicago: Rand McNally. Zhang, J., Jensen, B. E., and Mann, B. L. (1997). Modification and revision of the leadership scale for sports. Journal of Sport Behavior, 20(1), 105-122.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 9
IN DEMAND? EXAMINING SPORT MANAGEMENT FACULTY OPENINGS AND HIRES Edward (Ted) M. Kian1, Paul M. Pedersen2 and John Vincent3 1
University of Central Florida, USA Indiana University – Bloomington 3 University of Alabama, USA
2
ABSTRACT Over the past 25-30 years, sport management has been among the fastest growing academic disciplines in higher education within the United States. However, the few universities producing sport management doctoral graduates have seemingly been unable to meet the demands for qualified individuals to teach at the university level. This study analyzed each of the 124 professorial advertisements for sport management/administration placed by U.S. universities over a one-year period, encompassing the 2005-06 academic year. The majority of the openings were in the Southeast, Northeast, and Midwest, with few listings in the Southwest or West. Nearly half of all listings were at institutions offering sport management only at the undergraduate level.
Please send all correspondence to: Edward (Ted) M. Kian, Ph.D. Sport Leadership – Graduate Program Coordinator. University of Central Florida, PO Box 161250. Orlando, FL 32816-1250. Email:
[email protected]. Office: 407-823-4631. Cell: 407-927-5403. Fax: 407-823-3859
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Edward (Ted) M. Kian, Paul M. Pedersen and John Vincent A phone survey revealed only 69% of advertised positions were filled, with 53% of schools with failed searches citing a lack of desired applicants. A majority of schools that did not hire planned to re-post their positions the following academic year.
Keywords: Academic Positions, Faculty Jobs, Announcements, Hires. The exponential growth of the academic field of sport management/sport administration over the last 25-30 years has been well-documented (e.g., Cuneen, 2004; Mahony, Mondello, Hums, & Judd, 2006). Parkhouse and Pitts (2001) noted the number of sport management programs offered at universities and colleges in North America grew from 20 in 1980 to more than 200 in 2000. While there is no exact figure for the number of institutions currently offering sport management degrees, Cuneen (2006) noted there were more than 300 sport management or related programs at universities throughout the world. The discipline is most popular with students seeking employment in the sport industry and intercollegiate athletes (Crockett, 2005). Possibly due to the rapid rise of sport management as an academic discipline, university graduate programs appear to be having difficulty producing enough qualified future professors to teach within these sport management programs (Costa, 2005; Mahony, Mondello, Hums, & Judd, 2004). Several authors have noted a lack of qualified professors to teach sport management courses, leading to universities facing supply-and-demand difficulties in hiring and retaining sport management faculty (e.g., Cuneen, 2004; Mahony et al., 2006; Mondello, Mahony, Hums, & Moorman, 2002; Mondello, Mahony, Judd, & Hums, 2006; Stier, 2001; Weese, 2002). Jisha and Pitts (2004) found only eight North American universities that either issued doctoral degrees in sport management or a closely related field, or offered concentrations for doctoral degrees in those areas. Related to this shortage of Ph.D. programs, Mahony et al. (2004) found sport management programs collectively produced only 15 doctoral graduates per year. However, several universities have since implemented Ph.D. programs in sport management/administration. In 2007, the North American Society for Sport Management (NASSM) Web site listed 22 North American universities or colleges that advertised doctoral programs in sport management/administration, with 19 of those schools based in the United States. Several authors have examined sport management academic job openings. In general, this research has shown the number of openings seems to be increasing annually. Mahoney et al. (2004) found there was an average of 75 sport management faculty openings per academic year from 1996-97 through 2000-01,
In Demand? Examining Sport Management Faculty Openings and Hires 127 which included an increase each year from a low of 48 positions in 1996-97 to a high of 112 openings in 2000-01. Pedersen and Schneider (2003) found 128 international sport management faculty/teaching positions that were advertised during the 2000-01 academic year, while Pedersen, Whisenant, and Schneider (2005) found a slight increase to 131 openings the following academic year. In the most comprehensive study of sport management academic job openings to date, Pedersen, Fielding, and Vincent (2007) examined sport management /administration faculty position announcements from 2001-02 through 2005-06 at colleges and universities in 12 countries. The authors found a total of 655 total openings over that five-year period, with 594 of those either fulltime sport management teaching or research jobs, or sport management teaching positions that included other duties. The number of postings increased from 131 in the 2001-02 academic year to a five-year high of 158 in 2005-06. Overall, 594 (91%) of the 655 openings were at schools based in the U.S. Therefore, the increasing popularity of this academic field appears to be centered predominately within the U.S., and thus examinations of job opportunities in this discipline should focus on the U.S. The work of Pedersen and Schneider (2003) is the only published article that attempted to determine how many posted sport management academic positions were actually filled. Using a written questionnaire and telephone calls, the authors received a 91% response rate for the 128 posted positions during the 2000-01 academic year, 117 (91%) of which were located in the U.S. They found only 62% of those positions were actually filled to begin employment during the following academic year. The majority of those hires (65%) were at the assistant professor level, with 10% hired at the associate professor level, and 7% as lecturers. No other researchers have attempted a similar study since. While the number of open positions has increased since Pedersen and Schneider‘s (2003) examination of the 2000-01 openings, so have the number of programs offering doctoral degrees in sport management/sport administration. Seemingly, those schools should be able to produce more students with doctoral degrees to provide a broader applicant pool to potentially fill faculty positions. Therefore, new data is needed to determine if sport management in U.S. academia remains a ―buyers‘ market‖ for doctoral students, as well as current faculty considering positions at other schools.
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METHOD This study consisted of two parts. First, a content analysis was employed to locate posted job openings from universities within the United States and then to determine which of these jobs should be classified as sport management/sport administration academic positions. Second, a phone survey was conducted to see how many of those positions were actually filled. Two researchers, working independently of each other, searched from August 1, 2005, through July 31, 2006, for any academic postings in sport-related fields from three sources: The Chronicle of Higher Education Internet site, HigherEdJobs.com, and the Sport Management Listserv e-mail service. Areas searched for potential listings included sport(s) management, fitness management, sport(s) administration, athletic(s) administration, sport(s) leadership, sport(s) marketing, sport(s) studies, physical education, and recreation management. All listings for department chairs, associate or assistant professors, instructors, lecturers, and full-time adjunct professors were included for potential examination. Jobs that stated primary teaching and/or research responsibilities in sport or fitness management, sport or athletics administration, or sport leadership were automatically included in the study. Other listings were only included if it was determined by the researchers that 50% or more of the duties were in sport management-related areas. For example, a job posting for a professor in a school of business that listed sport marketing as one of several potential teaching areas was not included in this study if no other sport courses were listed as teaching areas. In contrast, an advertisement that listed primary teaching duties in both physical education and sport management was included. Sport studies positions were included if the job listings entailed teaching or research duties in any sport management core areas as set by NASSM (i.e., budget and finance in sport, communication in sport, economics in sport, governance in sport, legal aspects of sport, management and leadership in sport, marketing in sport). However, three sport studies positions that specifically stated primary teaching/research responsibilities in the sport social sciences (e.g., history, sociology) were not included for examination. One researcher compiled an initial list of 140 openings that could be included in the study, including multiple job positions at some universities. The second researcher‘s initial list included 120 openings, including three that were not on the first researcher‘s list. Thus, the initial intercorder agreement in this study was 83.6% between independent researchers. Through further analysis of the posted listings, discussions between the two primary researchers, and phone calls to
In Demand? Examining Sport Management Faculty Openings and Hires 129 selected universities in question, a final list of 125 different job postings from 111 universities were determined to fall within the parameters of this study and thus be classified as sport management/sport administration academic job openings at U.S. universities or colleges. A brief phone survey was formulated. Respondents were first asked if a hire was made for the stated position. If so, respondents were asked if the hired candidate was on a tenured or tenure-track line, employed full-time, and the incoming rank or title of the individual hired. If the respondents answered that a hire was not made, they were then asked if the line was scheduled to or had been re-listed, if the lack of hiring was due to financial considerations and/or a lack of desired applicants, and if the position had been offered to at least one person. From September 25, 2006, through, November 14, 2006, a representative who was able to answer each of these questions was reached from all 111 colleges or universities that posted advertisements, resulting in a 100% response rate. Depending on the size of the school and program, and the availability to reach someone via phone, respondents included deans of colleges, department chairs, program heads, associate and assistant professors in the same department, and program administrators. It should be noted the decision to re-list a position may have changed in either direction after respondents were reached. In addition, two different representatives from one school on the list for the 125 job postings said they never had an opening that could be classified under sport management/administration and no new hires in their department were made. Finally, 16 additional postings were advertised through these three outlets that may have fallen within the study‘s parameters of a sport management opening but were offered by universities located outside of the United States. These listings were for positions in Australia (5), Canada (3), Great Britain (4), New Zealand (1), Singapore (1), South Korea (1), and Turkey (1).
RESULTS Content Analysis The content analysis revealed a final total of 124 sport management openings at U.S. universities posted on at least one of three sources used to locate positions. Overall, 56 (45%) of those job openings were at private institutions, while 68 (55%) were at public universities or colleges. A total of 57 positions (46%) were at schools that offer only an undergraduate degree, major, emphasis, or
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specialization in sport management or a related area. A single position at one school offered only an undergraduate minor in sport management. A total of 43 job postings (35%) were at colleges or universities that offer both undergraduate and master‘s degrees, majors, specializations, or an emphasis in sport management. Institutions that field only master‘s programs accounted for 11 openings (9%), while nine job postings (7%) were at universities that offer sport management degrees at all three levels: undergraduate, master‘s, doctorate. Only two openings (2%) were at schools that offer both master‘s and doctoral degrees but not one at the undergraduate level. One opening was at an institution that had no sport management program at any level. However, a representative from that particular college said the school plans to add such a program in the near future. The majority of the 124 postings were colleges or universities located in the Southeast (n=44, or 35%), Northeast (n=40, or 32%), and Midwest (n=23, or 19 %). There were fewer job postings for openings in the Southwest (n=10, or 8%) or West (n=7, or 6%). Institutions in New York had the most openings of any state with 14 (11%), followed by Florida with 12 (10%), and Pennsylvania with 10 (8%). No other state had more than six openings. Schools from 41 different states had at least one opening, while 22 states had multiple job postings.
Phone Survey Of the 124 job postings, the phone survey revealed 86 (69%) of those were filled. All 86 hires were for full-time employment, and 65 (76%) of those positions were filled by an individual who was hired on a tenure line. The 86 hires included 60 (70%) at the assistant professor level, 14 (16%) associate professors, three (3%) visiting lecturers, two instructors (2%), two lecturers (2%), and one each with the titles of adjunct professor, assistant athletic director, clinical assistant professor, department chair, and program director. Among the 68 job postings from public colleges or universities, approximately 46 (68%) were filled. Private colleges filled 40 (71%) of their 56 openings. Hires were made for 34 (77%) of the 44 posted positions at schools in the Southeast. Colleges or universities in the Northeast made 25 hires (63%) from their 40 posted positions. Schools in the Midwest filled 17 (74%) of 23 openings. There were approximately six hires (60%) for the 10 posted positions in the Southwest and four position fillings (57%) among the seven openings in the West. Colleges or universities that offered sport management/sport administration programs only at the undergraduate level filled 37 (65%) of 57 posted positions. Schools with programs only at the master‘s level made eight hires (73%) for 11
In Demand? Examining Sport Management Faculty Openings and Hires 131 posted positions. Colleges or universities that fielded programs at both the undergraduate and master‘s level made 34 hires (79%) for 43 posted positions. Approximately six hires (67%) were made for the nine positions posted from universities or colleges that fielded programs at all three levels. One hire (50%) was made among the two postings at schools which offered programs at the master‘s and doctorate levels only. No hires were made at the school that only offered a sport management undergraduate minor, or at the school that fielded no programs but has plans to do so in the future. Of the 38 positions not filled, school representatives at 29 (76%) of those colleges or universities said they planned to or had already re-posted the same position during the 2006-07 academic calendar year, with a position starting date of January, 2007, in three cases, or for the start of the 2007-08 academic year for the remaining 26 positions. Representatives from seven schools (18%) among the 38 that did not hire said they would not re-list the position the following year, while two (5%) more program reps were unsure if their positions would be relisted the following year. Representatives from six (16%) of the 38 positions that were not filled said inadequate finances played a part in not hiring anyone, while financial issues were not cited as a factor for the other 32 schools (84%) that did not hire. Finally, 20 representatives (53%) of schools that did not fill their respective vacancies said that a lack of desired applicants factored into departments‘ decision not to hire anyone for the posted position.
CONCLUSIONS AND DISCUSSION The data from the content analysis revealed there continues to be a high demand for qualified candidates applying for sport management/sport administration academic openings. This study found 124 advertisements for academic positions in sport management at U.S. colleges or universities posted during the 2005-06 academic year. Pedersen et al. (2007) found an average of 119 sport management/sport administration academic job openings per year from their examination of job listings from 12 countries over five years of academic calendars. Therefore, the number of sport management academic positions in the U.S. appears to still be on the rise as had been noted by previous researchers (Mahony et al., 2004; Pedersen et al., 2007). The majority of job postings in 2005-06 were at academic institutions that offer only an undergraduate degree in sport management or related field (n=57, or 46%), or at schools that offered both an undergraduate and a master‘s degree in sport management (n=43, or 35%).This reinforces the notion of sport management
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as a practitioner-based academic discipline, while recognizing the scarcity of schools that offer doctoral programs in this area (Jisha and Pitts, 2004; Mahony et al., 2004; Mondello et al., 2002). This project was the second known study that attempted to determine how many sport management academic job postings were filled in an academic calendar year. Just 69% of the 124 openings posted during the 2005-06 academic year resulted in hires. This marked an improvement from the 62% of hires Pedersen and Schneider (2003) found in their analysis of jobs posted during the 2000-01 academic year. However, there appears to still be a shortage of quality candidates to fill these positions. Only six (16%) of the 38 failed or cancelled searches were attributed in part due to financial reasons. More disturbing for deans, department chairs, and search committee chairs who are attempting to hire sport management faculty, at least 29 (76%) of the openings that resulted in failed searches were slated to be re-posted during the 2006-07 academic year. Moreover, 53% of the schools that did not fill their positions advertised during the 2005-06 academic year were not satisfied with their applicant pool. Based on the results of this phone survey, it appears the lack of programs producing doctoral students cited by previous researchers has resulted in a shortage of quality candidates (Mahony et al., 2006; Weese, 2002). It remains a fruitful market for recent sport management doctoral graduates and current sport management faculty considering relocation to another school. In contrast, universities seeking to hire faculty in this area may need to offer more incentives to entice qualified candidates, who will likely be sought by other universities as well. Failed searches likely diminish the quality of specific sport management programs, possibly resulting in a shortage of quality teachers and researchers in specific areas, enrollment caps, and larger classes (Pedersen & Schneider, 2003; Stier, 2001). This research did not attempt to find out how many of the 86 hires were gainfully employed at other universities before accepting these positions. However, it is plausible several schools that lost faculty members to other universities during this period may have waited until the following year to post their vacancies. Amazingly, this implies sport management academics may be even more in demand than the one-sided statistics discovered in this study. A high number of positions (n=57, or 46%) were at schools offering a sport management degree at only the undergraduate level, so it was not surprising the vast majority of hires (n=69, or 80%) were as assistant professors, lecturers, instructors, or fulltime adjunct professors. This could also be in part due to the relative newness of sport management, resulting in a lack of experienced job applicants.
In Demand? Examining Sport Management Faculty Openings and Hires 133 Overall, the results of this study re-affirmed previous research, which found that sport management academia remains a viable market for doctoral graduates and faculty who are open to considering positions at other universities (Mahony et al., 2006; Mondello et al., 2006; Pedersen & Schneider, 2003). It is clear there still remains a need for sport management doctoral programs to produce more qualified graduates to fill these vacant positions.
REFERENCES Crockett, S. S. (2005). Why undergraduate students choose sport management as a major: Factors influencing college choice decisions. Unpublished master‘s thesis. Florida State University. Costa, C.A. (2005). The status and future of sport management: A Delphi study. Journal of Sport Management, 19(2), 117-142. Cuneen, J. (2006). From the editor. Sport Marketing Quarterly, 15(3), 1. Cuneen, J. (2004). Managing program excellence during our transition from potential to merit. Journal of Sport Management, 18(1), 1-12. Jisha, A., and Pitts, B. (2004). Program choice factors of sport management doctoral students in North America. Sport Management and Related Topics Journal, 1(1), 2-14. Mahony, D.F., Mondello, M., Hums, M.A., and Judd, M. (2006). Recruiting and retaining sport management faculty: Factors affecting job choice. Journal of Sport Management, 20(3), 414-430. Mahony, D.F., Mondello, M., Hums, M.A., and Judd, M.R. (2004). Are sport management doctoral programs meeting the needs of the faculty job market? Observations for today and the future. Journal of Sport Management, 18(2), 91-110. Mondello, M., Mahony, D.F., Hums, M.A., and Moorman, A.M. (2002). A survey of search committee chairpersons: Candidate qualifications preferred for entry-level sport management faculty positions. International Journal of Sport Management, 3(4), 262-281. Mondello, M.J., Mahony, D., Judd, M., and Hums, M. (2006). Sport management doctoral students in North America: Perceptions of their graduate training. International Journal of Sport Management, 7(2), 160-173. Parkhouse, B. L., and Pitts, B. G. (2001). Definition, evolution, and curriculum. In B.L. Parkhouse (Ed.), The management of sport: Its foundation and application (3rd ed., pp. 2-14). New York: McGraw-Hill.
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Pedersen, P.M., Fielding, L., and Vincent, J. (2007). A five-year content analysis of academic positions in sport management: Professorial announcements and advertisements from 2001-02 through 2005-06. International Journal of Sport Management, 8(4), 447-461. Pedersen, P.M., and Schneider, R.G. (2003). Investigating the academic openings in sport management: An analysis of the field‘s professorial position announcements and hires. International Sports Journal, 7(1), 35-47. Pedersen, P.M., Whisenant, W.A., and Schneider, R.G. (2005). Analyzing the 2001-02 sport management faculty openings. International Journal of Sport Management, 6(2), 154-164. Stier, W.F. (2001). The current status of sport management and athletic (sport) administration programs in the 21st century at the undergraduate and graduate levels. International Journal of Sport Management, 2(1), 60-97. Weese, W.J. (2002). Opportunities and headaches: Dichotomous perspectives on the current and future hiring realities in the sport management academy. Journal of Sport Management, 15(1), 1-17.
Coaching and Management Techniques in Athletics ISBN: 978-1-61122-825-0 Editors: J.A. Morelli and O.D. Velez © 2011 Nova Science Publishers, Inc.
Chapter 10
AN EMPIRICAL EXAMINATION OF THE PRESENCE OF MINORITY MANAGERS IN MINOR LEAGUE BASEBALL Braden Holcomb, Kurt A. Stahura* and James Busser University of Nevada Las Vegas, United States of America
ABSTRACT This article attempts to offer some insights relative into: (1) the ratio of minority coaches to minority players within 40 teams of the AAA, AA, and A levels within professional baseball (2) whether minority coaches would be relegated to the less prestigious coaching positions receiving token status within the hierarchical structure of minor league baseball. The data was analyzed using the Chi Square test, the results indicate there are more black coaches and fewer Latino coaches than expected based on the number of players within the hierarchical structure of professional baseball.
Key Words: minority coaches, race, occupational employment patterns
*
Correspondence: Dr. Kurt A. Stahura Department of Recreation and Sport Management William F. College of Hotel Administration 4505 Maryland Parkway – Box 453035 Las Vegas, Nevada 89154-3035 Phone: (702) 895-1265 E-Mail:
[email protected]
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INTRODUCTION As stated by Stahura and Greenwood (2001), ―sport has been viewed by minorities, as a way to facilitate upward socioeconomic mobility‖ (p. 85). It would appear that the world of sports is be a great equalizer for African Americans, but the fact remains that minorities who have gained wealth, prestige, and advancement through sports are the exception to the rule. Woodward (2004) has claimed that ―whites still dominate most sports at the collegiate and high school level, as well as holding most management positions in professional sports‖ (p. 356). It is interesting to note that African Americans dominate certain sports from a population standpoint, such as football and basketball, and Latinos have made significant strides within the sport of baseball yet are still in the minority when it comes to head coaching, ownership, and senior level management positions (Cunningham, Bruening, & Straub, 2006; Doherty & Chelladurai, 1999; Fennel & Miller, 2007; Long, Robinson, & Spracklen, 2005; Stahura & Greenwood, 2001; Holcomb, et.al, 2009). This analysis attempts to tease out managerial representation within the structure of minor league baseball.
Stacking Stacking exists when minority athletes are overrepresented at some playing positions and underrepresented in others. Loy (1970) introduced the concept of stacking to the intellectual community, at least with respect to the field of sport, back in the late 1960‘s. The theoretical construct that has evolved to what we now know to be stacking finds its roots in Grusky's (1963) theory on the formal structure of organizations and Blalocks (1962) theoretical ideologies surrounding occupational discrimination. Loy and McElvogue (1970) suggested in their famous study found that those in the center of the organizational structure through which information was flowing possessed the traits most would associate with leadership qualities. Stacking, as introduced by Loy, has been applied to a variety of sports and within a broad range of contexts (Ball, 1993; Eitzen & Furst, 1989; Malcom, 1997; Melnick & Thompson, 1996; Schneider & Eitzen, 1979). Loy and McElvogue analyzed African-American versus white representation within the leadership positions of the NFL, NBA and Major League Baseball. Woodward (2002) suggested that the factor of centrality itself is significant only in so far as greater outcome control and leadership responsibilities are typically vested in centrally located positions since actors holding these positions have a better
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perspective on the nuances and dynamics within context of the sport. Woodward (2004) in a later article claimed that this ideology has manifested itself in patterns whereby whites still dominate most sports with respect to representation at the collegiate and high school level, as well as holding most management positions in professional sports. This pattern does not appear to hold true for minorities who hold a majority of the positions at the professional level particularly in baseball. It is interesting to note that African Americans dominate certain sports from a population standpoint, such as football and basketball, yet are still in the minority when it comes to head coaching, ownership, and senior level management positions (Cunningham, Bruening, & Straub, 2006; Doherty & Chelladurai, 1999; Fennel & Miller, 2007; Long, Robinson, & Spracklen, 2005; Stahura & Greenwood, 2001). It is suggested that certain leadership positions on the field provide leadership skills that are conducive to training for future managers. The ―leadership‖ aspect of central positions appears to facilitate entry into coaching or managerial positions for players who wish to continue their professional baseball opportunities after their playing career is over (Grusky, 1963; Loy and McElvogue, 1970). From a playing perspective, quarterback and middle linebacker in football (offense and defense), point guard and center in basketball and the pitcher and catcher in baseball are the central positions that scholars would suggest that by virtue of their special positioning are most likely to be associated with the aforementioned leadership proclivities. Scully (1974) studied the relationship between stacking relative to managerial structures in professional baseball. Johnson (1988) applied stacking to youth baseball and high school football. Gonzales (1996) introduced the notion of stacking relative to the Latino population in baseball and found a positive relationship between the centrality of position and the occupancy of team leadership roles such as captain and co-captain. High interactive positions may cultivate personal traits and leadership attributes which increase the likelihood of managerial recruitment and selection in baseball (Leonard, Ostrosky, and Hutchendorf, 1990). A noticeable feature of professional baseball is the absence of minority members serving in managerial positions. It has been argued that minority players did not occupy the playing positions from which managers gain leadership qualities to maintain a coaching position (Fabianic, 1984). Linear logic would suggest that the underrepresentation of minorities occupying positions within the infield, because of stacking, is a factor in keeping minority athletes away from the center of decision-making positions whereby players appear to develop the managerial skills needed for career advancement.
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Managers are recruited most heavily from the central or high interactive positions, positions in which minorities predominately do not maintain (Leonard, Ostrosky, and Huchendorf, 1990). Minority managers tend to be outfielders, a position defined as low interaction or peripheral, in which they are overrepresented but a position that has produced a limited number of managers (Rimer, 1996; Holcomb et. al 2009). It has also been determined that minority managers at the Major League level are underrepresented based on the ratio of minority managers to minority players (Fabianic, 1984). In addition to playing at the professional level, managing at the minor league level is often considered a prerequisite for obtaining a major league managerial job (Rimer, 1996). The fewer the number of minority managers in Minor League Baseball in turn results in a fewer the number of minority managers at Major League Baseball. The trickle down affect involving position and opportunity may be affecting minority managerial opportunities. This study will also offer insights into whether minority representation has created a bunching affect within the lower tiers of the hierarchal structure of minor league baseball (A versus AAA) creating a ―glass ceiling‖ not unlike that faced by women and minorities in other work settings (Sack, Singh, & Theil, 2005).
Marginalization and Tokenism Although minorities are overrepresented as players, they continue to be underrepresented as coaches, general managers, and other positions of leadership (Holcolm, et. al, 2009). However, unlike players, managers are not evaluated based on their athletic traits or skills. The manager‘s win-loss record is the only quantitative measurement or objective analysis that can be used to evaluate a manager‘s effectiveness. All other forms of analysis are clearly subjective as one views prospective managers for the major league ranks (Wilkerson, 1996). According to the uncertainty hypothesis, discrimination of any kind can be hidden under ―the rubric of subjective qualities; this is particularly the case in coaching, where no quantitative formula or objective criteria are believed reliable indicators of who should fill the role‖ (Wilkerson, 1996, p. 423). Relying on intangible criteria, unattainable goals and the failure to give credibility of measurable goals leaves great latitude to those hiring coaches. Thus, assessing the potential and ability of candidates for the coaching position becomes subjective and in accordance with the uncertainty hypotheses, is more apt to be discriminatory (Wilkerson, 1996). Wilkerson, through the uncertainty hypothesis, suggests that one way to mask overt discrimination is to deny the importance of
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quantifiable criteria and rely on subjective credentials. In a more subtle way sport has reinforced stereotypical ideologies surrounding leadership patterns, genetic superiority with intellectual limitations resulting in positional and managerial marginalization, (Loy, 1970; Stahura & Greenwood, 2001; Holcomb et. al., 2009). In other words, the patterns that played out on the field that were uncovered by Loy in the early 1970‘s have left the field and the pervading ideology associated with positional marginalization has infiltrated the hierarchal structure of the front office including managerial positions. Lovett and Lowry (1994) suggested that the ‗good old boys clubs‘ were and still are alive and well at the administrative levels within the field of sport and the hiring practices of these individuals is greatly affected by such relationships. Although these hiring patterns were originally framed in relation to gender within intercollegiate athletic programs, these deep rooted relationships, which utilize old-fashioned contacts and networking, have perhaps prevented minorities from entering the field of coaching entirely. Kanter (1977) describes the process of selecting, nurturing and elevating "the right kind of person." ―Those who run (things) often rely on outward manifestations to determine who is ‗the right sort of person‘. Managers tend to carefully guard power and privilege for those that fit in, for those they see as ‗their kind‘ ‖ (Kanter, 1977, p. 48). In essence, the dominant group reproduces itself in its own image. What is quite apparent from this perception is that white males often end up in managerial positions because the person doing the hiring (i.e., General Manager, President) is a white male. This may be one explanation for why minorities are so dramatically underrepresented, even in minor league baseball by virtue of the trickle down theory. When a dominant group sits atop a profession and allows a limited number of minorities into the organization the dominant group maintains its positions of power and prestige. The other less prestigious, marginalized positions within the hierarchical structure are then made available to those within the minority. Judith Laws (1975) spoke of tokenism as it exists in its present form. She suggested that within a profession some groups were ―permitted entrance but not full participation.‖ The sociological literature has even suggested that minorities are ―hired, admitted, or appointed to a group because of their difference from other members, perhaps to serve as proof that the group does not discriminate against such people‖ (Zimmer, 1988, p.65). Sport organizations as corporations themselves, quite aware of their image, may be hiring minorities to occupy certain positions but those positions deny opportunity for upward mobility. Sports are often assumed to be ―the ultimate meritocracy,‖ as level a playing field as perhaps exists throughout society (Early, 1998). Though it is generally assumed that sport provides greater opportunities for upward mobility for
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minorities, when examined from a global perspective, results often indicate that sport only reproduces similar social circumstances of the larger society, thereby becoming merely a microcosm of society (Long et. al., 2005). This is particularly true within the administrative hierarchy of the NFL, NBA, and MLB (Stahura & Greenwood, 2001). Occupational patterns need to be analyzed within the entire hierarchical structure of sport in order to shed light on the future patterns that are likely to occur. Employment patterns within minor league baseball prepare potential candidates for major league baseball which is of course the highest, most visible level within the sport. On the surface it would appear as if minorities are making tremendous strides in sport as players and coaches as portrayed by the popular media. Because of the enormous exposure sport generates, influential scholars have even suggested that the insitution ―remains the one national plane where people of color and whites seem to have the greatest opportunity to set a national example for the rest of the country‖ (Lapchick, 1998, p. 2). Most of the scholarship, for obvious reasons, has analyzed sport at the highest level including the National Football League (NFL), National Basketball Association (NBA), National Hockey League (NHL) and Major League Baseball (MLB). As previously suggested, minor league sports are not only worthy of scholarly inquiry but must be analyzed due to the fact that the minor league system is a proving ground for future major leaguers both as players and managers.
METHODS The Sample Subjects for the study were coaches and players from 40 of the 120 total AAA (the highest level of minor league baseball), AA (the second highest level of minor league baseball), and A (the third highest level of minor league baseball) Minor League Baseball teams for the 2006 season. This is a replication and extension of work done by Gonzalez (1996). For the purposes of this study the number of Minor League Baseball teams was limited to 40 of the total 120 teams. In order to receive a random sample of teams, each team was numbered within their respective division (AAA, AA, or A) and a random number generator was used to determine which team was selected. A random sample of 10 teams was selected from a population of 30 AAA teams. Also, a random sample of 10 teams was selected from a population of 30 AA teams. Finally, a random sample of 20 teams was selected from a population of 60
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A teams. A larger number of teams were randomly selected for the A league to ensure that each league had the same percentage of team representation.
Sample Characteristics For the purposes of the study, three racial categories were established: White, or ―having origins in any of the original peoples of Europe, the Middle East, or North Africa‖ (Office of Management and Budget, 1997); Black, or ―having origins in any of the Black racial groups or Africa‖ (Office of Management and Budget, 1997); and Latino, or ―a person of Cuban, Mexican, Puerto Rican, South or Central American, or other Spanish culture or origin, regardless of race‖(Office of Management and Budget, 1997). Any subjects that did not fit into one of the three racial categories were excluded from the study due to their limited representation (3%) in the study‘s overall population. The coaching positions were also categorized into one of three different positions: head coach ―the manager of a baseball team‖ (Enlexica, 2007); pitching coach or ―a coach who specializes in helping pitchers‖ (Enlexica, 2007); and hitting coach, or ―a member of a baseball team that works with players to improve batting results‖(Enlexica, 2007). The sample characteristics replicated the work done by Gonzales (1996).
Data Collection Team media guides and team websites were used for each of the 40 randomly selected teams comprising A, AA, and AAA Minor League Baseball. The team websites were initially used to identify the race of the players and coaches. If the team websites were unable to produce the data set the teams were contacted for a media guide for data collection. If both the website and team media guide were unable to produce the data another number was randomly generated and a new team was used in the method. This replacement method was utilized only twice and it was done at the A level which greatly outnumbered the other levels. The name, picture, and biographical information in the team media guides and websites were the determining factors in the placement of the players and coaches into their respective racial group. Again, the sample was chosen based on the number of teams at each level. The number of A teams far outnumbered the number of AA and AAA teams and the sample reflected this difference. The following research questions were subjected to statistical testing:
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Braden Holcolm, Kurt A. Stahura and James Busser 1. Will the ratio of minority coaches to minority players be equal within the 40 teams of AAA, AA, and A? All players and coaches on the 40 AAA, AA and A teams were coded for one of the three racial categories using information given in the team‘s media guide or website. The players were compared to the coaches to determine what the ratio between minority coaches and minority players was during the 2006 season. 1A. Will the ratio of minority coaches to minority players be equal within the 20 ―A‖ Minor League Baseball teams? All players and coaches on the 20 ―A‖ teams were coded for one of the three racial categories using information given in the team‘s media guide or website. The players were compared to the coaches to determine what the ratio between minority coaches and minority players was during the 2006 season. 1B. Will the ratio of minority coaches to minority players be equal within the 10 AA Minor League Baseball teams? All players and coaches on the 10 AA teams were coded for one of the three racial categories using information given in the team‘s media guide or website. The players were compared to the coaches to determine what the ratio between minority coaches and minority players was during the 2006 season. 1C. Will the ratio of minority coaches to minority players be equal within the 10 AAA Minor League Baseball teams? All players and coaches on the 10 AAA teams were coded for one of the three racial categories using information given in the team‘s media guide or website. The players were compared to the coaches to determine what the ratio between minority coaches and minority players was during the 2006 season. 2. Will there be a disproportionate number of minorities at any of the three coaching positions in Minor League Baseball? All of the coaches were grouped into one of the three racial categories (White, Latino, African-American) and then classified into one of the three coaching categories (Head Coach, Pitching Coach, Hitting Coach) to see if a relationship between the two exists.
Analysis of Data The data was analyzed using the Chi Square test. This data analysis practice was utilized in previous stacking studies which have attempted to detect significant patterns in the levels of differences between observed and expected levels of representation in race and/or positional categories (Gonzales, 1996). A
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statement of acceptance or rejection for any of the questions was based on a .05 rejection level.
RESULTS The initial sample selection of 40 teams produced a response rate of 80% (32/40). Both the AAA and AA teams initial sample produced a 90% (9/10) initial response rate and the single A teams produced a 70% (14/20) initial response rate. The first replacement sampling response rate was 75% (6/8), followed by a second replacement response rate of 100% (2/2). This is the one instance in which a team had to be replaced due to insufficient media resources. Of the initial 40 teams selected 28 of the 32 responses were via team websites; team media guides were used for the remaining 4 teams. Of the 8 teams randomly selected in the second replacement sampling team websites were used in all 8. The following research questions will statistically identify any underrepresentation of minority coaches in Minor League Baseball.
Testing the Research Questions Will the Ratio of Minority Coaches to Minority Players Be Equal Within the 40 Teams of AAA, AA, And A? The research question addressed whether minority coaches were being equally represented based on the number of minority players at the AAA, AA, and A level. For the 120 coaches and 997 players, as shown in table 1, using two degrees of freedom, a χ² value of 25.74 was calculated, with a p < .001, thereby indicating an unequal ratio of minority coaches to minority players at the Minor League level. The results indicated that there are more black coaches than expected based on the number of black players. The results indicate that there are fewer Latino coaches than expected based on the number of Latino players. Table 1. Chi-Square Results of All Coaches and Players by Race White Observed Expected Black Observed
Coaches 91 83 20
Players 668 676 71
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Expected Latino Observed
Expected
10
81
9
238
27
220
χ² (2, N=1,117) = 25.74, p < .001
Will the Ratio of Minority Coaches to Minority Players be Equal Within the 20 Single a Minor League Baseball Teams? The question asked whether minority coaches are being equally represented based on the number of minority players at the single A level. For the 60 coaches and 501 players, as shown in table 2, using two degrees of freedom, a χ² value of 19.32 was calculated and statistically significant (p < .001), thereby indicating an unequal ratio of minority coaches to minority players at the A level. The results indicate that there are more black coaches and fewer white and Latino coaches than expected based on the number of players in each group. This is the only level where white coaches are underrepresented in Minor League Baseball. This reinforces the notion that minorities are getting opportunities at the entry level within the hierarchical structure of minor league baseball or perhaps white managers are even starting at higher levels (AA, AAA). Table 2. Chi-Square Results of Single A Coaches and Players by Race White Observed Expected Black Observed Expected Latino Observed Expected
Coaches 43 41
Players 337 339
11 4
31 38
6 15
133 124
χ² (2, N = 561) = 19.32, p < .001
Will the Ratio of Minority Coaches to Minority Players be Equal Within the 10 AA Minor League Baseball Teams? The question addressed whether minority coaches are being equally represented based on the number of minority players at the AA level. For the 30 coaches and 252 players, as shown in table 3, using two degrees of freedom, a χ² value of 6.32 was calculated and statistically significant (p < .05), thereby
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indicating an unequal ratio of minority coaches to minority players at the AA level. The results indicate there are more black coaches and fewer Latino coaches than expected based on the number of players in each group. Table 3. Chi-Square Results of AA Coaches and Players by Race White Observed Expected Black Observed Expected Latino Observed Expected
Coaches 23 21
Players 174 176
5 3
19 21
2 6
59 54
χ² (2, N = 282) = 6.32, p < .05
Will the Ratio of Minority Coaches to Minority Players be Equal Within the 10 AAA Minor League Baseball Teams? The question isolates whether minority coaches are being fairly represented based on the number of minority players at the AAA level. For the 30 coaches and 224 players, as shown in table 4, using two degrees of freedom, a χ² value of 5.25 was calculated and statistically significant (p < .10), thereby indicating no statistical difference between minority coaches and minority players at the AAA level. The results indicate no significant differences in representation observed within the ratio of minority coaches to minority players at the AAA. In essence, the ratio between minority coaches and players was not statistically significant. Table 4. Chi-Square Results of AAA Coaches and Players by Race White Observed Expected Black Observed Expected Latino Observed Expected χ² (2, N = 251) = 5.25, p = .10
Coaches 26 22
Players 157 161
3 3
21 21
1 6
46 41
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The chi-square results may not have been statistically significant but the numbers do seem to show a misrepresentation, especially with the Latino coaches. An additional chi-square test was conducted using only the Whites and Latinos. For the 27 coaches and 203 players, as shown in table 5, using one degree of freedom, a χ² value of 5.27 was calculated and statistically significant (p ≤ .025), thereby indicating a statistical difference between minority coaches and minority players at the AAA level. Table 5. Chi-Square Results of AAA White and Latino Coaches and Players by Race White Observed Expected Latino Observed Expected
Coaches 26 21 1 6
Players 157 162 46 41
χ² (1, N = 230) = 5.27, p ≤ .025
Will there be a Disproportionate Number of Minorities at Any of the Three Coaching Positions in Minor League Baseball? The question addressed whether minority coaches are underrepresented or overrepresented at any of the three coaching positions (manager, pitching coach, and hitting coach) in Minor League Baseball. For the 120 coaches, as shown in table 6, using four degrees of freedom, a χ² value of 15.63 was calculated and statistically significant (p < .001), thereby indicating there is a disproportionate number of minorities at the three coaching positions in Minor League Baseball. Table 6. Chi-Square Results of Coaches by Current Position and Race White Observed Expected Black Observed Expected Latino Observed Expected
Manager 32 31
Hitting Coach 24 31
Pitching Coach 36 31
3 6
13 6
3 6
5 3
3 3
1 3
χ² (4, N = 120) = 15.63, p < .001
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The black coaches are the only group to be misrepresented. There were fewer black managers than expected, more black hitting coaches than expected, and fewer black pitching coaches than expected.
DISCUSSION During the last century minorities have fought for racial equality in all facets of life. No place is this more evident than in the field of sports. While many people would argue that minority players are given equal rights and equal opportunities the same cannot be said of minority managers and coaches who continue to be underrepresented in professional sports (Gonzales, 1996; Rimer 1996). The purpose of this study was to address two main issues 1) the ratio of minority players to minority coaches, 2) the current coaching position and the race of the coaches, Fabianic‘s (1984) work showed that minority managers were not proportionally represented based on the number of minority players at the Major League level. This study was a replication and extension of Fabianic‘s work performed at the Minor League level. The data collected in this study identifies the same conclusion. Minority managers, specifically Latino coaches, are not proportionally represented based on the number of Latino players at the Minor League level during the 2006 season. Two studies, performed by Medoff (1986) and Gonzales (1996), sampling African-Americans and Latinos, respectively, found evidence of stacking, or segregation into positions by race, at the player level. Medoff (1986) suggests that blacks are generally isolated from positions requiring interpersonal collaboration and decision-making because white management views interracial relationships as potentially problematic. Gonzales (1994) suggests that management segregates black players from positions which are characterized by leadership and control. This study was an extension of Medoff and Gonzales‘ work at the Minor League level. While not as poignant as the previous studies, particularly with respect to sample size, the data collected did identify representation discrepancies at the coaching level on the basis of race and can make a worthwhile contribution to the literature
Ratio of Coaches to Players Latino coaches were statistically underrepresented based on the number of Latino players in A, AA, AAA – when compared to white coaches. Also, black
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coaches were overrepresented based on the number of black players in A and AA. Based on the data collected for this study, Latino coaches are underrepresented based on the number of Latino players in Minor League Baseball. One explanation for this underrepresentation of Latino coaches could be because of the rapid increase in Latino players in the last decade and the pool for Latino coaches has not caught up to the large influx of Latino players. The data in this research shows African-American coaches are equally represented based on the number of African-American players. Compared with previous studies done in Major League Baseball, which showed an underrepresentation of African-American coaches to the ratio of African-American players, progress seems to have been made in professional baseball.
Current Coaching Position and Race The data collected uncovered that there were fewer black managers than expected, more black hitting coaches than expected, and fewer black pitching coaches than expected. The data also found fewer white hitting coaches than expected. By referring to previous stacking studies done on players at the Major League level, African-American players were found to be underrepresented at central (high interaction) positions and overrepresented at peripheral (low interaction) positions (Curtis & Loy, 1978; Medoff, 1986; Phillips, 1991). Because of this it is easy to identify why African-American coaches would be underrepresented at the manager and pitching coach (predominate central orientation) positions and overrepresented at the hitting coach (predominate peripheral orientation). The largest concern with this research seems to lie with the representation of the Latino population in professional baseball. The rise of Latino‘s in the United States‘ overall population as well as in Minor League Baseball brings questions to the representation of Latino head coaches, hitting coaches, and pitching coaches in professional baseball, relative to the number of Latino baseball players. This study attempts to respond to a void in the research by examining the population of Minor League Baseball during the 2006 season for evidence of underrepresentation and stacking within positional categories and by addressing whites, blacks, and Latinos as distinct racial groups. The results of the present study indicate that patterns in minority underrepresentation occur in Minor League Baseball at the coaching level. The main purpose of the current study was to determine the racial structure of Minor League Baseball at the coaching level. Obviously, one study does not have
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the power to completely understand the complexities of the situation. This study was a snapshot of one year for the racial breakdown; this is not sufficient to make any concrete cases towards the dynamic nature of Minor League Baseball. While forty teams may be sufficient to make statistical claims an additional study of all teams could do a better job of identifying any significant differences. Also, identification of minority players based their picture and name may have led to an error in placing them into a racial category. Lavoie and Leonard (1994) have postulated yet another reason for stacking in professional sports. Their research into professional baseball caused them to determine that there was another way of describing stacking not seen in previous literature. They called this the uncertainty thesis of discrimination, which claimed that positional segregation is due to a form of racial discrimination that becomes effective when it is difficult to measure performance. According to this
hypothesis, the more difficult it is to accurately and objectively measure performance, the higher the probability that subjective and less relevant factor will be taken into account. Among those subjective and less relevant factors, or even irrelevant factors, that may be taken into account are the "old boys network," gender, family status, religion, mother tongue, and skin color (Lavoie & Leonard 1994). The researchers soon discovered that the uncertainty hypothesis could be a good explanation for racial stacking if it is combined with the pressure coaches put on African Americans to accept peripheral positions on the field (Woodward 2004). As previously stated, understanding the racial structure of Minor League Baseball is important to understanding the racial structure of Major League Baseball. The coaches in Minor League Baseball are simply a large candidate pool for coaching positions in Major League Baseball. If patterns surrounding tokenism are being established within Minor League Baseball, then the opportunity for minorities to coach in Major League Baseball is severely limited. It can be noted that after discussing the different explanations of why racial stacking might exist in any level of professional sport, it cannot be reduced to one fact but rather a combination of historical as well as sociological dynamics. Coakley (1998) maintained that racial stacking was based on a number of different factors, including: historical traditions related to ethnic relations in society, the history of a minority group‘s involvement in a particular sport, the proportion of minority-majority group members in a sport, the ethnic backgrounds of a team‘s coaches, general managers, and player scouts, the degree to which different positions in a sport involve different skills and responsibilities, the ways that positions are defined, and the perspectives used by those who identify and assess player skills and recruit players for teams (Woodward 2002).
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Future research needs to investigate minor league sports simply because it is from this pool that future major league managers are to be drawn. Minor League Baseball, especially at coaching and administrative levels, for a more precise understanding of the racial representation needs to be empirically dissected. In order to get a better understanding of hiring practices, a longitudinal data-oriented study should be performed. Perhaps then additional explanations can be put forth and a more complete mosaic can be derived creating blocks from which others can build. Addition information relative to the aspirations of minor league managers would in determining the patterns that have unveiled themselves within this profession. Although their analysis was confined to Division I intercollegiate football, Cunningham, Sagas, and Ashley (2006) suggest that African Americans do not aspire to occupy the head position within the coaching hierarchy. This may be due to the fact that upward mobility is not seen as an option or that appropriate mentoring that would support upward mobility is not present. Both themes merit additional investigation.
REFERENCES Blalock, H. (1962). Occupational discrimination: Some theoretical propositions. Social Problems, 9, 240-247. Cousens, L. & Slack, T. (2005). Field-level change: The case of North American major league professional sport. Journal of Sport Management, 19, 13-42. Cunningham, G.B., Bruening, J.E., & Straub, T. (2006). The underrepresentation of African Americans in NCAA Division I-A head coaching positions. Journal of Sport Management, 20, 387-413. Curtis, J., & Loy, J. (1978). Race/ethnicity and relative centrality of playingpositions in team sports. In Hutton (Ed.), Exercise and Sports Sciences review, 285-313. Early, G. (1998). Performance and reality: race, sports, and the modern world.The Nation, August 10-17, 11-20. Eitzen, D.S., & Yetman, N.R. (1977). Immune from racism? Civil Rights Digest, 9, 3-13. Enlexica: the language of baseball. An online dictionary and thesaurus. Retrieved March 15, 2005, from http://www.enlexica.com/sp/bb/ Fabianic, D. (1984). Minority managers in professional baseball. Sociology of Sport Journal, 2, 163-171.
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Fennel, M., & Miller, S.D. (2007). Follow the ―Rooney rule‖ for leadership succession. Retrieved November 3,2007, from http://www.university business.com/ViewArticle.aspx? articleid=855 Fabianic, D. Organizational effectiveness and managerial succession: An update of an old problem. Journal of Sport Behavior, 7(4) 139-152. Gonzales, G. (1996). The stacking of Latinos in Major League Baseball. Journal of Sport and Social Issues, 22, 134-160. Goss, B.D. (1996). Not as simple as black and white: An investigation of alleged stacking practices and the rise of the Latino population within Major League Baseball's positional categories, 1993—1997. Unpublished doctoral dissertation, University of Southern Mississippi. Grusky, O. (1963). The effects of formal structure on managerial recruitment: a study of baseball organizations. Sociometry, 26, 345-353. Holcomb, B., Stahura, K. & Busser, J (2009). An analysis of minority managers in minor league baseball: The relationship between past playing postion and future leadership positions. Applied Research in Coaching and Athletics Annual, 24, 1-23. Kooistra, P., Mahoney, J., & Bridges, L. (1993). The unequal opportunity for equal ability hypothesis: Racism in the National Football League? Sociology of Sport Journal, 10, 241-255. Lapchick, R. (1998). Racial Report Card. [On-line] Available: http://www.spor tinsociety.org/rgrc98.html Lavoie, M., & Leonard, W. M. (1994). In search of an alternative explanation of stackingin baseball: The uncertainty hypothesis. Sociology of Sport Journal, 11, 140-154. Leonard, W., Ostrosky, T., & Hutchendorf, S. (1990). Centrality of positionand managerial recruitment: the case of Major League Baseball. Sociology of Sport Journal, 7, 294-301. Loy, J. & McElvogue, J. (1970). Racial discrimination in American sport. International Review of Sport Sociology, 5, 5-24. Medoff, M.H. (1986). Positional segregation and the economic hypothesis. Sociology of Sport Journal, 3, 297-304. Office of Management and Budget (1997). Revisions to the standards for the classification of federal data on race and ethnicity. Retrieved March 15, 2005 from http://www.whitehouse.gov/omb/fedreg/ombdir15.html Phillips, J.C. (1991). The integration of central positions in baseball: The black shortstop. Sociology of Sport Journal, 8, 161-167.
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Rimer, E. (1996). Discrimination in major league baseball: Hiring standards for standards for major league managers, 1975-1994. Journal of Sport &Social Issues, 22, 118-133. Sack, A., Singh, P., Theil, R. (2005). Occupational segregation on the playing field: The case of Major League Baseball. Journal of Sport Management, 19, 34-51. Sagas, M., Paetzold, R., & Cunningham, G.B. (2006). Effects of supervisorsubordinate demographic diversity on the job satisfaction experienced by assistant coaches. International Journal of Sport Management, 7, 141-159. Scully, G.W (1989). The business of Major League Baseball. Chicago: University ofChicago Press. Stahura, K. & Greenwood, M. (2001). The effects of the ―black mystique‖ andstereotyping on African-American representation within the hierarchyof the NBA and NFL. International Sports Journal, 84-100. Wilkerson, M. (1996). Explaining the presence of men coaches in women's sports: The uncertainty hypothesis. Journal of Sport and Social Issues, 20, 411-426. Woodward, J. R. (2002). An examination of a National Football League draft publication:Do racial stereotypes still exist in football? Sociology of Sport Online Journal, 5(2): November/December. Woodward, J. R. (2004). Professional football scouts: An investigation of racial stacking.Sociology of Sport Journal, 21, 356-375.
INDEX 2 21st century, 134
A AA, x, 135, 140, 141, 142, 143, 144, 145, 147 AAA, x, 135, 138, 140, 141, 142, 143, 144, 145, 146, 147 Abraham, ix, 26, 37, 71, 72, 73, 74, 79, 81, 82, 83 academic, 9 Academic Performance of Players, 46 Academic Positions, 126 access, 40, 61 accidents, 26 accountability, 2, 14, 55, 56 accounting, x, 87, 102 adaptation, 73 adjustment, 72, 110 administration, 35, 37, 66 administrative, 2, 139, 140, 150 administrators, 44, 48, 57, 65, 66, 108, 129 adolescents, 69, 119 advancement, 136, 137 advertisements, x, 125, 129, 131, 134 affective reactions, 26 Africa, 141 African American, 4, 5, 136, 137, 149, 150 African Americans, 136, 137, 149, 150 African-American, 136, 142, 147, 148, 152
age, 4, 16, 32, 33, 74, 78, 94, 95, 100, 113, 118, 119, 121 alternative, 36, 66, 151 AM, 38 ambiguity, 2, 28 American Psychological Association, 104 Announcements, 126 antecedent variables, 110 antecedents, 41 anxiety, 88, 89, 92, 104, 106 application, 62, 70 appraisals, 74 Apter Motivational Style Profile (AMSP), ix, 87, 93, 104 assessment, 106 assignment, 2 associations, 35 athletes, viii, ix, x, 1, 9, 14, 43, 44, 46, 48, 56, 59, 62, 63, 73, 74, 75, 76, 77, 78, 79, 85, 88, 89, 94, 101, 102, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 116, 117, 118, 119, 120, 121, 122, 126, 136, 137 atmosphere, 79, 112, 119 attitudes, 38, 61, 65, 66 authority, 112, 118 Autic sympathy, x, 87, 97, 98, 99 autonomy, 28, 30, 36 awareness, 81
Index
154
B badminton, 63 base, ix, 82, 87, 90, 92 baseball coaches, vii, 1, 4, 5, 6, 7, 8, 9, 10, 13, 16, 17, 23 basketball, 59, 61, 63, 64, 65, 66, 136, 137 Beck Depression Inventory, 94 behavior, ix, 26, 28, 41, 59, 61, 62, 65, 66, 67, 68, 69, 70 behavioral change, 83 behavioral sciences, 108 behaviors, x, 42, 51, 52, 61, 72, 73, 74, 76, 77, 81, 83, 90, 106, 107, 108, 109, 110, 111, 112, 113, 114, 115, 117, 118, 120, 121, 123, 124 beliefs, 61 benefits, 62, 115 biofeedback, 53 boys, 139, 149 breakdown, 149 Britain, 129 Brooklyn, 37 burnout, ix, 11, 87, 88, 89, 90, 91, 92, 94, 95, 96, 99, 100, 101, 102, 103, 104, 105, 106 burnout potential, ix, 87, 93 business, viii, 25 buyers, 127
C campaigns, 68 candidates, 102, 103, 131, 132, 138, 140 career development, 27 career satisfaction, viii, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 40 case study, 121 category a, 47 Caucasian, vii, 1, 4, 5 CE, 42 Central America, 141 certification, 85 challenges, 52, 53, 57, 118 Chicago, 39, 68, 123, 124, 152
citizenship, 42 Civil Rights, 150 clarity, 82, 99, 100 classes, 132 classification, 45, 47, 48, 49, 50, 63, 98, 119, 151 classroom, 56, 105 classroom teacher, 105 classroom teachers, 105 clients, 88 climate, 41, 74, 84, 86 Coaching Belief Triad, vi, ix, 71, 73, 77, 81 coaching efficacy, 74, 84 coaching process, ix, 11, 23, 71, 72, 73, 74, 77, 79, 81, 82, 84 coaching profession, viii, ix, 27, 31, 35, 36, 43, 54, 55, 71, 88, 95 coaching typology, ix, 71, 73 collaboration, 147 college athletic coach, viii, 43 college students, 112 colleges, 6, 57, 89, 106, 126, 127, 129, 130, 131 color, iv, 140, 149 communication, 49, 78, 128 community, 46, 136 competition, 2, 14, 74, 108, 109, 111, 113, 115, 119 competitors, 117 complex organizations, 39 complexity, 72, 73, 76, 82, 83, 84 compliance, ix, 59, 62, 64, 65, 66, 69 components, 26, 61 conceptual model, 82, 84 conceptualization, 29, 37, 76 conference, 59, 65, 66 confidence, 29, 41 confidence interval, 41 confidence intervals, 41 configuration, 73, 75, 81 conflict, 11, 28, 46, 89, 118 congruence, 73, 76 consensus, 83 consent, 95 constituents, 65
Index construction, 36, 84 consulting, 57 consumption, 53 content analysis, 128, 129, 131, 134 contingency, 121 control, 35, 36, 61, 62, 66, 136, 147 corporations, 139 correlations, viii, 25, 33, 94, 96 cost, 68, 80 costs, 61, 65, 66 counseling, 104, 109 creativity, 79, 80 credentials, 139 credibility, 138 cross-sectional, 36 cross-validation, 105 cultural, 28, 42 cultural perspective, 42 culture, 36, 40, 109, 111, 113, 141 curriculum, 133
D data analysis, 142 data collection, 31, 104, 141 data gathering, 110 data set, 141 database, 62 decision makers, 11, 23 decision making, 66 decision-making process, vii, 72 decisions, 62, 66 defense, 137 deficit, 20, 41, 76 degenerate, 53 degree, vii, 1, 5, 29, 30 degrees of freedom, 143, 144, 145, 146 delinquency, 69 delinquent behavior, 61 demand, 65, 68 demographic, 2, 3, 5, 41 demographics, 4, 6, 38 demography, 29, 38 dependent variable, 33
155
depersonalization, x, 88, 89, 98, 99, 100, 101, 102, 103 depression, 104 devaluation, 88 deviation, 22, 23 dichotomy, 65 directors, 11, 37, 61, 65, 66, 69 discrimination, 36, 38, 61, 68, 136, 138, 149, 150, 151 discriminatory, 138 dissatisfaction, 37 distribution, 4, 16 diversity, viii, 25, 41, 152 division, 11, 32, 68, 140 dominance, x, 88, 92, 93, 96, 99, 100, 101, 102, 103, 104 draft, 152 drug testing, 46 drugs, 48 duties, vii, 1, 2, 7, 8, 10
E education, x, 4, 5, 11, 16, 33, 35, 56, 57, 61, 69, 72, 81, 82, 84, 86, 114, 116, 123, 125, 128 Education, 5, 68, 69 educational research, 68, 86 educators, 82 efficacy, 39 election, 143 e-mail, 128 emotion, 90, 104, 105, 106 emotional exhaustion, x, 88, 89, 98, 99, 100, 101, 102 emotional health, 51 emotions, 27 empirical studies, 77 employees, 26, 28, 30, 39, 40, 61 employment, 26, 31, 32, 60, 64, 66, 126, 127, 130, 135 empowerment, 11, 23, 30, 79, 119 energy, 11, 44 enforcement, 62 England, 11, 104, 105
Index
156
enrollment, 6, 7, 68, 132 entrapment, 88 envelope, 3 environment, vii, viii, ix, 26, 28, 29, 30, 36, 43, 44, 67, 71, 72, 73, 74, 77, 80, 108, 109, 111, 118 environmental factors, 26, 100 equality, 69, 147 equipment, viii, 13, 21, 22 ethnic background, 4, 16, 149 ethnicity, 4, 74, 113, 150, 151 Europe, 141 everyday life, 104 evidence, 61, 76, 77, 147, 148 evolution, 133 examinations, 46, 127 execution, 61, 62, 65, 66, 79 executive function, 117 executive functions, 117 exercise, 53, 83, 122, 124 exposure, 140 external validity, 36
F face validity, 3, 14 factor analysis, 95, 98, 99, 100, 105 Faculty Jobs, 126 faculty positions, 2, 127, 133 families, 45 family, 31, 149 family members, 53 February, 68, 70 feedback, 26 feelings, x, 27, 30, 47, 88, 92, 94, 100, 102, 118 fencing, 63 financial, vii, 1, 8, 31, 61, 62, 65, 129, 131, 132 financial aid, vii, 1, 8 football, vii, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 47, 55, 56, 61, 62, 63, 65, 68, 70, 113, 120, 136, 137, 150, 152
Football, v, 1, 4, 6, 7, 8, 9, 10, 13, 16, 17, 18, 19, 20, 21, 22, 60, 69, 140, 151, 152 force, 29, 81 formula, 138 France, 28, 38 freedom, 73, 143, 144, 145, 146 funding, 14 fundraising, vii, 3, 13, 14, 15 fund-raising efforts, vii, viii, 1, 13 fundraising responsibilities, vii, 13, 14 funds, viii, 13, 19, 23
G games, 1, 61, 65 gender, ix, 28, 29, 32, 33, 36, 37, 59, 60, 61, 63, 65, 66, 69, 139, 149 gender differences, 36, 88, 93, 100 gender gap, 69 gender role, 61 general model of the coaching process, ix, 71, 72 Germany, 42 glass, 138 glass ceiling, 138 goal attainment, 72, 74 goal-directed behavior, 90 goals, 138 goal-setting, 86 governance, 69, 128 graduate program, 126 Great Britain, 129 groups, 29, 63, 64, 139, 141, 148 growth, 81, 124, 126 guidance, 53, 114 gymnastics, 63, 64
H hands, 35 Harvard, 69 head, vii, 1, 2, 3, 4, 31, 32, 36, 38 head football coaches, vii, viii, 1, 4, 13, 16 health, 51, 52, 92, 93, 105
Index helping behavior, 28 high school, ix, 37, 43, 56, 87, 88, 95, 100, 105, 108, 113, 116, 119, 136, 137 higher education, x, 11, 61, 69, 125 Hires, vi, 125, 126, 130 hiring, 126, 129, 131, 134, 138, 139, 150 Hispanic, 5 history, 115, 118, 128, 149 hospital, 39, 41 House, 108, 114, 123 human, viii, 42, 43, 44, 52, 53, 61, 88, 95, 102, 104, 106 human behavior, 61, 102 Human Kinetics, 11 human nature, 53 human subjects, 95 hypothesis, ix, 30, 31, 33, 35, 87, 138, 149, 151, 152
I ideal, 79, 122 identification, 72, 92, 102, 149 identity, 30, 36, 84, 92, 102 ideology, 137, 139 image, 139 implementation, 67 improvements, viii, 13, 21, 22 incentive, 61, 62 independent variable, 33 Indiana, 59, 65 indicators, 138 indirect effect, 41, 42 individual character, 114, 117 individual characteristics, 114, 117 individuals, viii, ix, x, 3, 13, 15, 21, 22, 43, 53, 54, 63, 66, 78, 80, 90, 91, 103, 109, 118, 125, 139 industrial, 39 industry, 41, 122, 126 Information System, 40 information systems, 40 information technology, 37, 40 Information Technology, 40 innovation, 69
157
insight, 35 institutions, x, 2, 3, 4, 6, 7, 14, 15, 38, 62, 67, 89, 116, 125, 126, 129, 131 intangible, 138 integration, 151 intelligence, 37 intentions, 26, 27, 39, 40, 70 interaction, 29, 138, 148 intercollegiate athletics, 28, 35, 38, 69, 121 intercollegiate level, x, 107 interface, 57, 86 internal mechanisms, 83 Internet, ix, 59, 62, 69 interpersonal relations, 49, 101, 112, 119 interpersonal relationships, 49, 101 intervention, 41 Iowa, 55 irony, 82 issues, viii, 28, 39, 43, 46, 53, 77, 81, 89, 108, 131, 147
J January, 69 Japanese, 38, 42 job performance, 39, 40 job position, 128 job satisfaction, viii, 25, 27, 28, 30, 31, 32, 33, 35, 36, 38, 40, 41, 42, 152 jobs, 27, 65 junior high school, 105 justice, 69 justification, 65
K Korea, 129
L landscape, 26, 28, 30, 35 language, 150 languages, 113
Index
158
Latino, xi, 135, 137, 141, 142, 143, 144, 145, 146, 147, 148, 151 Latinos, 136, 146, 147, 148, 151 lead, ix, 36, 37, 59, 61, 62, 70, 75, 78, 79, 81, 92, 108, 120 Leader-Member Exchange Theory (LMX), 29 leadership, x, 28, 29, 30, 38, 39, 41, 42, 72, 77, 78, 83, 85, 88, 89, 107, 108, 109, 110, 111, 113, 114, 117, 118, 119, 120, 121, 122, 123, 124, 128, 136, 137, 138, 139, 147, 151 leadership characteristics, 120 Leadership Scale for Sports, x, 107, 118, 120, 122 leadership style, 89, 108, 118, 119, 120 learning, 75, 84 legislation, 60, 61, 62, 65, 66, 67, 69 level of education, 4, 5, 16 light, 115, 140 likelihood, 137 limitations, 62, 66, 139 linear regression, 33 linkage, 29, 38, 39 literature, viii, 25, 26, 27, 28, 29, 32, 35, 36 local community, 46 longitudinal study, 37, 40
M magazines, 57 magnitude, 31 Major League Baseball, 136, 138, 140, 148, 149, 151, 152 majority, vii, x, 1, 13, 31, 44, 47, 50, 53, 64, 125, 126, 127, 130, 131, 132, 137, 149 majority group, 149 males, 32, 61, 64, 139 man, 56, 66 management, iv, x, 2, 28, 36, 41, 42, 57, 85, 105, 118, 122, 123, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134, 136, 137, 147 managerial responsibilities, x, 107 manufacturer, 28 marginalization, 139 marital status, 33
marketing, 128 Maryland, 43, 56, 57, 135 mask, 138 Maslach Burnout Inventory (MBI), ix, 87 matter, iv, 52, 62, 81, 120 MBI, ix, 87, 94, 95, 96, 97, 98, 99, 100, 101, 102 measurement, 68, 111, 122, 138 measures, 30, 32 media, ix, 19, 43, 49, 50, 121, 140, 141, 142, 143 mediation, 33, 41 medicine, 56 men, 31, 61, 64, 152 mentoring, 150 meritocracy, 139 meta-analysis, 38 Mexican, 141 microcosm, 140 Middle East, 141 migration, 37 Minnesota, 60, 68 minorities, 136, 137, 138, 139, 140, 142, 144, 146, 147, 149 minority, x, 64, 135, 136, 137, 138, 139, 142, 143, 144, 145, 146, 147, 148, 149, 151 minority coaches, x, 135, 142, 143, 144, 145, 146, 147 minority players, x, 135, 137, 138, 142, 143, 144, 145, 146, 147, 149 Mississippi, 151 mobility, 136, 139, 150 models, 35, 41, 42, 73, 78, 82 moderators, 39 modifications, xi money, 1, 2, 62 morale, 123 mosaic, 150 Moses, 61, 68 mother tongue, 149 motivation, 42, 90, 91, 100, 104, 110, 114, 121 multidimensional, 72, 77, 93, 110, 111, 112, 114, 117 muscle relaxation, 53
Index music, 53, 78
N national, 35, 140 National Basketball Association, 140 National Collegiate Athletic Association, 38, 69 National Football League, 140, 151, 152 National Football League (NFL), 140 nationality, 118 NBA, 136, 140, 152 NC, 69 NCAA, vii, ix, 1, 2, 3, 4, 11, 31, 32, 36, 38, 40, 59, 60, 61, 62, 63, 64, 65, 66, 67, 68, 69, 70, 150 NCAA Division I (FBS) recruiting violations, ix, 59 NCAA Legislative Services Database for the Internet (LSDBi), ix, 59 negative attitudes, 94 negative relation, 27 Negativistic, 90, 97, 98, 99 neglect, 52, 61 network, 149 networking, 109, 139 Nevada, 135 New York, 37, 38, 42 New Zealand, 129 NFL, 136, 140, 152 NHL, 140 normal, 61 normative behavior, 66 norms, 61, 66 North Africa, 141 North America, 41, 42, 126, 133, 150 Notre Dame, 68 nurses, 47
O obedience, 61 objective criteria, 138 obligation, 29
159
observable behavior, 91 observed behavior, 122 occupational, 36, 135, 136 Office of Management and Budget, 141, 151 OH, 39 Oklahoma, 60, 65 old-fashioned, 139 operating costs, viii, 13, 23, 61 opportunities, 30, 36, 82, 83, 119, 127, 137, 138, 139, 144, 147 organization, 27, 30, 32, 65, 139 organizational behavior, 61, 122 organizational citizenship behaviors, 42 organizational tenure, 36 organizations, 9, 10, 37, 38, 39, 61, 66, 70, 136, 139, 151 orientation, 27, 30, 148 overlap, 45 overtraining, 105 ownership, 118, 136, 137
P Pacific, 40 parallel, 78 Paratelic, 90, 97, 98, 99 parents, ix, 43, 56, 123 participants, 2, 3, 4, 14, 15, 85, 95, 96, 109, 111, 113, 115, 116, 121 peace, 54 Pearson correlations, 33 peer relationship, 122 penalties, 62, 65, 69 perceived control, 88 perception, 26, 61, 139 perceptions, 30, 32, 38 performance, 26, 28, 39, 41, 69, 149 permission, iv, 90, 94, 115 permit, 80, 109 personal, 29, 31, 137 personal accomplishment, x, 88, 89, 98, 99, 100, 101, 102 personal goals, 75, 114 personal welfare, 55 personality, 40, 42, 73, 74, 85, 90, 104
160
Index
personality traits, 40, 42 phenomenology, 91 Philadelphia, 104 physical activity, 122 physical education, 116, 123, 128 physical exercise, 53 physical health, 51, 52 physicians, 47, 48 pilot study, 3, 15 play, 27, 29 Player Behavior and Attitude, 45 Player Performance, 46 playing, 35, 56, 73, 78, 92, 119, 136, 137, 138, 139, 151, 152 population, 32, 37, 94, 103, 136, 137, 140, 141, 148, 151 positive attitudes, 67 positive feedback, 112, 116, 119 positive reinforcement, 117 positive relation, 27, 30, 137 positive relationship, 27, 30, 137 power, 40, 42, 139, 149 predictability, viii, 26, 33 preparation, iv, 2 President, 57, 59, 139 pressure, 61, 65, 66, 149 prestige, 56, 62, 136, 139 principles, 52, 53, 54, 82, 109, 121, 123 private, 6 probability, 149 probation, 61, 68 procedural justice, 40 procedures, 41 production, 69 profession, 26, 27, 28, 29, 31, 35, 36 professional baseball, x, 135, 137, 148, 149, 150 professional development, 84, 94 professionals, ix, 37, 40, 42, 71, 88, 108, 113 professions, 35 program, 2, 10, 11, 60, 62 project, 132 promote, 66 psychological, 37 psychological phenomena, 90
psychological variables, 89 psychologist, viii, 43 psychology, iv, 39, 84, 105, 122, 123, 124 public, 6 public interest, 50 public schools, 93 Puerto Rican, 141 punishment, 65
Q qualifications, 133 quarterback, 137 questioning, 72, 82 questionnaire, ix, 2, 3, 14, 15, 31, 36, 87, 94, 95, 115, 116, 127
R race, 28, 36, 37, 38, 39, 74, 135, 141, 142, 147, 150, 151 racial categories, 141, 142 racial differences, 36 racial groups, 141, 148 racism, 150 random, 31, 140 range, 4, 136 reactions, 26, 92 recognition, 55, 72, 102 recommendations, iv, 3, 14 recreation, 8, 122, 128 recreational, 53 recruiting, viii, ix, 13, 21, 46, 56, 59, 60, 61, 62, 63, 64, 65, 66, 67, 69, 76, 78, 79 Recruiting, v, 21, 22, 46, 59, 63, 64, 133 reduction, 37, 61, 65 regression, viii, 25, 33 regression analysis, viii, 25, 33 regulations, 60, 69 rehabilitation, 79 reinforcement, 117 rejection, 143 relationship, viii, 25, 26, 27, 28, 29, 30, 31, 33, 35, 41, 42, 69, 137, 142, 151
Index relationships, 27, 29, 33, 35, 39, 40, 139, 147 relaxation, 53 reliability, 32, 93, 94, 103, 116 Reliability, 34 religion, 149 replication, 140, 147 reproduction, 29, 42 requirements, 52, 73, 91 research, viii, 3, 25, 26, 28, 29, 30, 33, 35, 36, 37, 38, 42, 61, 65, 66, 68, 141, 143, 148, 149, 150 researchers, vii, 61, 72, 73, 74, 82, 83, 103, 108, 127, 128, 131, 132, 149 residence life, vii, 1, 8 resource management, 122 resources, 29, 31, 143 response, 8, 9, 10, 31, 53, 94, 95, 101, 105, 113, 116, 127, 129, 143 responsibilities, vii, 1, 2, 3, 7, 8, 11, 136, 149 revenue, ix, 59, 61, 63, 65, 66, 69 Reversal Theory, vi, ix, 87, 88, 90, 100, 104, 105, 106 rewards, 31, 90, 91 rights, iv, 147 risk, 93, 96, 100, 101, 103 role conflict, 28, 89 Rookie, vi, 107 rules, 35, 48, 61, 62, 63, 66
S sales, 65 sample, viii, 3, 25, 31, 32, 36, 37, 140, 141, 143, 147 sample survey, 3, 14 sampling, 32, 36, 143, 147 sanctions, 61, 62, 65 SAS, 41 satisfaction, viii, 25, 26, 27, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 40, 41, 42, 152 scarcity, 132 scholarship, 62, 65, 70, 121, 140 scholarships, 61
161
school, ix, x, 37, 43, 56, 87, 88, 93, 94, 95, 100, 108, 113, 115, 116, 119, 120, 122, 126, 127, 128, 129, 130, 131, 132, 136, 137 science, 81, 82, 83, 122 scientific understanding, 108 scope, 27, 36, 44, 56 SD, 32 search, 65, 151 security, 30, 114 segregation, 147, 149, 151, 152 selecting, 139 Self, 41, 69 self-efficacy, 74 self-management, 28 self-worth, 118 sensitivity, 92, 102 series, 32 service organizations, 85 sex role, 41 shape, 26, 29, 67 shaping, 29, 35 sharing, 11 shortage, 126, 132 showing, 20, 88 sign, 68 similarity, 29 Singapore, 129 skills, 137, 138, 149 Slippery Rock University Sport Management Department, 3, 14 soccer, 63, 64, 65 social, 37, 42 social environment, 67 social exchange, 42 social network, 103 social norms, 113 social performance, 68 social sciences, 128 social support, 88, 89, 112, 114, 116, 119, 120 society, 118, 139, 149 socioeconomic, 136 sociological, 139, 149 sociology, 74, 128 solicitation of alumni, viii, 13, 19, 21, 22 solution, 52, 99
162
Index
solutions, 67 South Korea, 129 specialization, 130 speculation, 50 sponsor, 4 sport management, x, 28, 36, 122, 125, 126, 127, 128, 129, 130, 131, 132, 133, 134 sports, ix, 59, 61, 62, 63, 64, 65, 66, 68, 69, 70, 136, 140, 147, 149, 150, 152 staff members, 49, 109 standard deviation, 23, 96 standards, 151, 152 state, 55, 78, 90, 91, 92, 93, 96, 98, 100, 101, 102, 103, 130 states, 62, 88, 91, 92, 96, 99, 100, 102, 103, 130 statistics, 33, 96, 132 stereotypes, 41, 152 stereotypical, 139 strategies, 28, 41 stress, 2, 44, 45, 46, 47, 48, 49, 50, 51, 52, 53, 54, 55, 56, 57, 80, 88, 89, 90, 91, 92, 101, 103, 105, 106 stressors, 42, 45, 46, 47, 48, 49, 57 structural equation model, 41 structure, x, 30, 35, 85, 91, 109, 110, 113, 135, 136, 138, 139, 140, 144, 148, 149, 151 structuring, 26, 112, 117 student enrollment, 7, 68 student group, 9 students, 2, 7, 9 style, 74, 77, 85, 88, 89, 108, 112, 118, 120 Styles, 94 subjective, 61, 66, 138, 149 subjective experience, 91 succession, 151 superiority, 139 supervision, 122, 123 supervisor, viii, 25, 26, 28, 29, 30, 31, 32, 33, 35, 36, 37, 38, 39, 41, 42, 43, 152 supervisor satisfaction, viii, 25, 27, 31, 32, 33, 35 supervisors, 29, 30 support services, 89 support staff, ix, 43
susceptibility, ix, 87, 89, 93 Sweden, 123 sympathy, x, 87, 91, 92, 93, 97, 98, 99, 100, 102, 103
T tactics, 39, 66, 112, 119, 120 talent, 62, 76, 77, 78, 79, 80, 81 teacher, viii, 43, 75, 105 teachers, 37, 47, 101, 105, 132 teaching, vii, 1, 2, 7, 8 team leaders, 137 team members, 26, 45, 48, 76, 78, 110, 111, 114 team sports, 86, 108, 123, 150 teams, x, 45, 47, 62, 64, 102, 106, 108, 111, 113, 115, 119, 120, 124, 135, 140, 141, 142, 143, 149 techniques, 51, 53, 54, 95, 112, 123 technology, 37, 40, 110 telephone, 127 television, 61 television coverage, 61 tension, 91, 92, 101, 103 tenure, 2, 32, 36, 129, 130 testing, 33, 37, 38, 46, 113, 141 test-retest reliability, 116 Texas, 59 theory, ix, 28, 29, 30, 39, 40, 42, 59, 61, 65, 67, 68, 70, 136, 139 Theory of Planned Behavior, 59 thesaurus, 150 thoughts, 11, 74 time, 8, 10, 31 time frame, 111 Title I, 42 tokenism, 139, 149 traditions, 149 training, viii, 43, 89, 111, 112, 113, 116, 117, 119, 123, 133, 137 training programs, 123 trait anxiety, 88, 89 traits, 38, 40, 42, 136, 137, 138 transcendence, 92
Index treatment, ix, 61, 66, 71, 72 trickle down, 138, 139 trust, 29, 30, 39 Turkey, 129 turnover, 26, 27, 28, 35, 36, 37, 38, 39, 40, 42, 89 typology, 69
U ubiquitous, 31 uncertainty, 138, 149, 151, 152 United, iv, x, 59, 68, 94, 112, 115, 125, 126, 128, 129, 135, 148 United Kingdom, 94 United States, iv, x, 59, 112, 115, 125, 126, 128, 129, 135, 148 United Way, 68 universities, x, 6, 57, 61, 66, 125, 126, 127, 128, 129, 130, 131, 132, 133 upward mobility, 139, 150 urban, 6 USA, 1, 13, 25, 43, 71, 87, 125
V vacancies, 131, 132 vacuum, 74 validation, 106, 123
163
validity, 3, 68 values, 30 variable, 32, 33, 37, 42 variables, 32, 41, 42, 74, 77, 89, 92, 95, 96, 103, 105, 109, 110, 113, 124 variance, 36 varimax rotation, 98, 99 varsity basketball coaches, ix, 87, 88, 93, 100 veteran athletes, x, 107, 118, 119, 120 Virginia, 1 visible, 140 volleyball, 115, 116 vulnerability, 44
W Wales, 104 Washington, 41, 104, 105 websites, 141, 143 welfare, 55, 56, 112, 119 winning, 5, 61, 65 women, 31, 32, 41, 42, 61, 64, 66, 138 work environment, 26, 28, 36 workers, 37, 101 working population, 37
Y yield, 95
