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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

NOTICE TO THE READER The Publisher has taken reasonable care in the preparation of this book, but makes no expressed or implied warranty of any kind and assumes no responsibility for any errors or omissions. No liability is assumed for incidental or consequential damages in connection with or arising out of information contained in this book. The Publisher shall not be liable for any special, consequential, or exemplary damages resulting, in whole or in part, from the readers‘ use of, or reliance upon, this material. Any parts of this book based on government reports are so indicated and copyright is claimed for those parts to the extent applicable to compilations of such works. Independent verification should be sought for any data, advice or recommendations contained in this book. In addition, no responsibility is assumed by the publisher for any injury and/or damage to persons or property arising from any methods, products, instructions, ideas or otherwise contained in this publication. This publication is designed to provide accurate and authoritative information with regard to the subject matter covered herein. It is sold with the clear understanding that the Publisher is not engaged in rendering legal or any other professional services. If legal or any other expert assistance is required, the services of a competent person should be sought. FROM A DECLARATION OF PARTICIPANTS JOINTLY ADOPTED BY A COMMITTEE OF THE AMERICAN BAR ASSOCIATION AND A COMMITTEE OF PUBLISHERS. Additional color graphics may be available in the e-book version of this book.

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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Jason A. Morelli and Oscar D. Velez

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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Jason A. Morelli and Oscar D. Velez

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

Preface

xi

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.

4

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.


5

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.

6

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


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%


7

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


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


Percent 0.0% 26.3% 57.9% 15.8% 100%

Table 12. Coaches with Other Assigned Duties - Baseball and 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.


9

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


Frequency 6 6

Percent 14.6% 15.8%

Table 17. Advisement of Student Groups (Clubs/Organizations) – Baseball and 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.


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.

14

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


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


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) 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

Burnout in High School Basketball Coaches…

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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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Ryan K. Zapalac, Jay T. Lee and Dale G. Pease

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.


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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Christopher M. Keshock and Shelley Bradford

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.


Chapter 9

IN DEMAND? EXAMINING SPORT MANAGEMENT FACULTY OPENINGS AND HIRES Edward (Ted) M. Kian1, 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.


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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Braden Holcolm, Kurt A. Stahura and James Busser

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

An Empirical Examination of the Presence of Minority Managers…

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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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Braden Holcolm, Kurt A. Stahura and James Busser Table 1 (Continued)

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.

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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

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