ISSN: 1543-9518|Vol. 24

Desirable Qualities, Attributes, and Characteristics of Successful Athletic Trainers – A National Study

Submitted by: Timothy J. Henry, Robert C. Schneider, and William F. Stier Jr. – The State University of New York at Brockport

Abstract

In an effort to determine the importance of desirable qualities, attributes and characteristics necessary for the success of interscholastic athletic trainers a Likert-type scale survey was mailed to all head athletic trainers of NCAA Division III institutions in the United States. The survey consisted of 24 statements allowing for the following responses: essential, very important, important, not very important, and irrelevant. The qualities that were deemed the most desirable by head athletic trainers were trustworthiness (76.2%), honesty (73.5%), dependability (66.4%), and possessing high ethical standards (66.4%). The two characteristics that were found to be the least essential were being a risk-taker (2.1%) and being a visionary (6.4%).

Introduction

Certified athletic trainers (ATCs) are allied health care professionals who specialize in preventing, recognizing, managing, and rehabilitating injuries that result from physical activity. The ATC works as part of a complete health care team and functions under the direction of a licensed physician and in cooperation with other health care professionals, athletics administrators, coaches, and parents (NATA, 2006c). In order to become a certified athletic trainer, an individual must graduate from a Commission on Accreditation of Athletic Training Education (CAATE) approved Athletic Training program and successfully pass the Board of Certification Examination (NATA, 2006b).

The Board of Certification, Inc. (BOC) regularly conducts a role delineation study among a sample of certified athletic trainers. This study determines the current role, or standards, of the profession. This role delineation study may also be considered a job analysis and determines the minimal competencies to practice as an athletic trainer. It also serves to define the contemporary standards of practice for the athletic training profession (NATA, 2006a). The information gathered by this job analysis is used as a template for the NATA Educational Council to develop the Educational Competencies for Athletic Training. These competencies define the minimum skills and characteristics that entry-level athletic trainers should possess and define the educational content that students enrolled in an accredited athletic training program must master. The competencies are broken down into 12 content areas (Table 1) (NATA, 2006a).

“Athletic trainers are the critical link between the sport program and medical community” (Anderson and Hall, 2000, p. 6) and fulfilling this job requires the athletic trainer to fill many roles. In addition to the educational knowledge outlined by the educational competencies, ATCs must possess other qualities and attributes in order to succeed in the all-encompassing role of athletic trainer. Arnheim and Prentice (2000) describe some of these qualities as stamina and ability to adapt, empathy, sense of humor, communication, intellectual curiosity, ethical standards, and being active in professional organizations. Gaedek, Toolelian & Schaffer (1983) describe communication with other athletic trainers, physicians, physical therapists, and so forth as one of the primary attributes an ATC must possess.

Attaining a position in athletic training and, ultimately, success as an athletic trainer can be dependent upon several factors. Employers look for candidates who have both a formal and informal educational background (including certification from the BOC) as well as a demonstration of other skills and attributes that might have been obtained through experience as well as through formal educational courses (Gaedeke, Toolelian & Schaffer, 1983). When looking at employers’ hiring criteria for athletic trainers, the prevailing criterion predicting employment and salary is the educational status of the applicant (Kahanov and Andrews, 2001). This study by Kahanov and Andrews (2001) found that the four most important criteria for hiring were personal characteristics, educational experience, professional experience, and work-related attributes. Educational experience included a college minor, grade point average, membership in a fraternity, and college reputation. The personal characteristics included self-confidence, maturity, interpersonal skills, assertiveness, enthusiasm, technical skills, ability to articulate goals, oral communication skills, leadership skills, initiative, ambition, problem-solving skills, writing skills and personal appearance. Smith (2006, p.47) states that “certification and experience are important, but possibly even more critical are personality, character, and people skills”. Certified athletic trainers hold the key to a successful program, whether it is a professional team, a school, a physician’s office, a hospital, or a clinic. Thus, it is imperative to hire the right person for the job (Smith, 2006).

Although the literature contains many studies highlighting hiring criteria and desirable knowledge areas for ATCs, very few studies have investigated the personal characteristics and qualities of certified athletic trainers as viewed by employers in specific employment settings. The purpose of this study was to investigate the desired personal qualities, attributes, and characteristics of certified athletic trainers in the division III setting as viewed by head athletic trainers in these settings. To date, this is the only national study that surveyed all of the division III head ATCs asking them what personal qualities, attributes, and characteristics they believed to be important for the success of ATCs.

Methodology

Population:

The population surveyed included head athletic trainers of all NCAA division III colleges and universities. The mailing addresses of the colleges and universities were obtained from the NCAA headquarters located in Indianapolis, Indiana. Of the 410 surveys mailed out, 185 were returned for a return rate of 45.1%.

Survey Instrument:

The survey instrument utilized in the study was approved by the Institutional Review Board at the surveying institution. The instrument was developed based upon the professional literature and as well as communication with experts in the area of athletic training. Twenty-four specific skills and competencies were identified and included in the survey.

Procedures:

After approval of the survey instrument, all surveys were mailed to the NCAA division III head athletic trainers. A return envelope that was pre-stamped, and addressed to the principal investigator, was included in the mailings. Anonymity of the head athletic trainer, as well as the college and university surveyed, was ensured.

The head athletic trainers were asked to provide their opinions as to the level of importance of the personal qualities, attributes, and characteristics included on the survey that were related to the success of the athletic trainers in providing health care to student athletes. By responding to a 5-point Likert scale, essential, very important, important, not very important, irrelevant, the head athletic trainers provided their opinions as to the level of importance of specific skills and competencies found in successful athletic trainers.

Findings

The findings are displayed in Table 2 and revealed varied opinions regarding the importance of personal qualities, attributes, and characteristics that Division III head athletic trainers believed to be essential, very important, important, not very important, and irrelevant in order to be successful as an athletic trainer at the Division III level. Most of the items were identified as either essential or very important; however, some were not viewed as highly.

Six items were reported as the most important personal attributes for successful ATCs. These items had the highest percentage of responses as essential to the success of athletic trainers at the Division III level:

  • Trustworthiness (76.2%)
  • Honesty (73.5%)
  • High ethical standards (66.4%)
  • Dependable (66.4%)
  • Adaptable (62.7%)
  • Communicator (61.6%)

In addition to the attributes reported as essential, three items were reported as being highly desirable (either essential or very important) by 90% of the respondents:

  • Leadership (93.7%)
  • Decisiveness (91.8%)
  • Consistency (91.2%)

Head athletic trainers viewed the following as having the least impact (essential or very important) among all of the selected skills and competencies on success of the Division III ATCs:

  • Risk taker (19.9%)
  • High energy level (45.6%)
  • Visionary (46.9%)

Discussion

This study examined the desirable personal qualities and attributes necessary to be a successful athletic trainer at the Division III level. The most desirable characteristics reported by head athletic trainers in this study, honesty, trustworthiness, and high ethical standards, can be grouped together as ethical qualities. Each of these attributes is important to the ability of the ATC to provide high quality health care to the physically active. All members of the NATA are required to observe the NATA Code of Ethics, which provides an outline of ethical behavior that should be followed in the practice of athletic training. The Code is comprised of 5 principals and presents aspirational standards of behavior that all members should strive to achieve (NATA, 2006c). ATCs typically deal with many controversial and sensitive issues in which honesty, trustworthiness, and high ethical standards are of the utmost importance. Some of these sensitive situations may include athletes with diseases or conditions, such as HIV or hepatitis, athletes with sexually transmitted diseases, athletes with season-ending or career-ending injuries, and athletes that may be using, or are suspected of using, performance enhancing substances. In each of these scenarios, the ATC may find themselves exposed to extremely sensitive and confidential information. Confidential information that is obtained as part of the professional relationship that an ATC has with an athlete might be personal, private, and sensitive. The ATC should handle this sensitive information carefully to avoid ethical, as well as legal, breaches of confidentiality. Another issue related to the ethical standards of athletic trainers is the high profile of athletes and of the athletic industry in our society. The accessibility of the media and the public’s desire to know everything possible about their teams and athletes can be a significant threat to an athlete’s privacy and to the confidentiality of information to which the ATC is privy (Ray, 2005). The fact that the respondents in this study valued the ethical attributes establishes the importance of the Code of Ethics in the daily practice of the ATC.

Trustworthiness is not only important when dealing with the confidentiality issues, but it is extremely important in establishing a good rapport between the athlete and the athletic trainer. The athlete needs to respect the athletic trainer as a person before they can trust the athletic trainer in the rehabilitative setting. The ATC must gain the trust of the athlete before the athlete will follow the protocols and programs designed for them by their athletic trainer (Arnheim and Prentice, 2000).

Other attributes that were deemed highly desirable were adaptability and dependability. Arnheim and Prentice (2000, p. 16) report, “The athletic trainer must be able to adapt to new situations with ease.” This is due to the large number of athletes and teams that they are typically responsible for covering. Practice and game schedules are frequently canceled or modified, depending on factors such as weather, facility availability, team condition, travel schedules, and so forth. In many cases, ATCs are at the mercy of the coaches and administrators in determining these schedules and may not be consulted as to their opinions in those matters. Due to the unique skills which the ATC provides, they are difficult to replace and they must be present at all practices and contests in order to provide the high quality health care that the athletes deserve.

The ability to communicate is an attribute that was deemed essential by 61.6% of the respondents; however, we expected a higher percentage of the head athletic trainers to list this as essential. Athletic trainers are often described as a liaison between athletes, coaches, team physicians, and other allied health care professionals. This role requires the ATC to serve as an educator, psychologist, counselor, therapist, and/or administrator and is dependent upon a constant flow of oral and written communication (Arnheim and Prentice, 2000). Lockard (2005) stressed the importance of having positive relationships by stating that because athletic trainers deal with a variety of people, they need good social and communication skills.

Personal attributes that were deemed desirable by the respondents were decisiveness and leadership. Decisiveness is a characteristic that does not appear in any of the previous literature relating to desirable personal attributes or hiring characteristics for an ATC. During the course of any typical day for an ATC, many situations arise in which the athletic trainer must make important decisions. Referral decisions are an inherent part of the injury management domain of athletic training, especially those dealing with potentially catastrophic injuries. These decisions must be made spontaneously in many cases with the well-being of the athlete at stake.

The importance of leadership in our study is similar to the findings of Kahanov and Andrews (2001). They listed leadership as one of 16 characteristics that were viewed as important by employers when hiring ATCs across different job settings, although leadership was not rated as highly as other characteristics in their study. As mentioned previously, the ATC is typically the leader or coordinator of the sports medicine team (NATA, 2006e). Smith (2006) stated that certified athletic trainers hold the key to a successful program, whether it is a professional team, a school, a physician’s office, a hospital, or at a clinic.

The personal attribute that was reported to be the least important in the Division III setting was being a risk-taker. This finding is not surprising when considering the myriad of legal and ethical issues confronting ATCs today. Risk management is an important term to all ATCs today, and the athletic trainer is intimately involved in developing safe athletic programs in all types of settings. Lyznicki et al. (1999) found the implementation of risk management programs by athletic trainers to be important in that it minimized liability in secondary schools. Chen and Esposito (2004) recognized the importance of risk management and acknowledged the need for athletic trainers to formulate a risk management plan.

Another personal attribute that was not deemed essential to the success of athletic trainers at the division III level was high energy level. Only 16.2% of the respondents reported this to be essential, while 39.4 % rated this as very important. This finding is extremely surprising and is contrary to many commonly described views of the ATC. ATCs typically work extremely long hours and are asked to cover numerous sporting events every day. Arnheim and Prentice (2000, p. 16) state, “Athletic training is not the field for a person who likes an 8-to-5 job. Long, arduous hours of often strenuous work will sap the reserve strength of anyone not in the best of physical and emotional health. Athletic training requires abundant energy, vitality, and physical and emotional stability.” In recent years, the NCAA and other administrators have begun to recognize the long hours and busy days of ATCs and have implemented changes in the sports medicine coverage provided by ATCs. The NCAA recently implemented the guidelines for appropriate medical coverage for intercollegiate athletics (NATA, 2003), which generally increases the number of ATCs required to meet the health care needs of student athletes on NCAA college campuses. This document suggested to collegiate administrators that they need to hire more certified athletic trainers to cover the ever-increasing health care needs of their student athletes. This recently implemented guideline may have in fact alleviated some of the long hours and strenuous days that had become commonplace for the ATC. With the addition of more staff, head ATCs may now feel that having a high energy level is not as important as it was traditionally viewed.

Being a visionary is another characteristic that was not reported as desirable as some of the others. Athletic training is a relatively young profession and the physically active community is just beginning to recognize the role and importance of ATCs in providing health care to the physically active. The recent evolution of athletic training is due to the long-term vision of many early athletic trainers; however there are still many hurdles for ATCs to clear in order for athletic training to become fully integrated into the larger sports medicine field. Some of the important issues currently confronting NATA members are third party reimbursement, expanding employment settings, and refining the educational process. These are issues that many ATCs are concerned with and are highly intertwined with the long-term vision and strategic plan of the NATA. (NATA, 2006d). It is somewhat surprising to the authors that being a visionary is not deemed more desirable by head athletic trainers at the division III level.

Conclusion

The most important personal characteristics and attributes for ATCs at the division III level were related to ethical issues and included honesty, trustworthiness, and possessing high ethical standards. Other highly desirable characteristics were being adaptable, dependable, and a good communicator.

The least important personal attribute was being a risk-taker. Other attributes that, surprisingly, were not deemed as highly desirable were having a high energy level and being a visionary.

Table 1: Athletic Training Professional Competencies Areas

Risk Management and Injury Prevention
Pathology of Injuries and Illnesses
Orthopedic Clinical Examination and Diagnosis
Medical Conditions and Disabilities
Acute Care of Injuries and Illnesses
Therapeutic Modalities
Conditioning and Rehabilitative Exercise
Pharmacology
Psychosocial Intervention and Referral
Nutritional Aspects of Injuries and Illnesses
Health Care Administration
Professional Development and Responsibility

Table 2: Desirable Qualities, Attributes, and Characteristics of Successful Athletic Trainers

Qualities, Attributes, and Characteristics Essential (%) Very Important (%) Important (%) Not Very Important (%) Irrelevant (%)
Honesty 73.5 20.5 1 1 4
Punctuality 45.9 42.1 8 2.1 1.6
Decisiveness 56.2 35.6 4.3 1.8 2.1
Trustworthiness 76.2 17.8 2.8 0 3.2
Consistency 47.5 43.7 5.7 1 2.1
Enthusiastic 12.4 52.4 29.9 2.1 3.2
High energy level 16.2 39.4 40.2 3.7 .5
Role model 28.6 43.2 23.9 2.7 1.6
Leadership 35.6 48.4 11.8 2.1 2.1
Persistence 20 50.4 25.9 2.1 1.6
Helpfulness 26.4 23.2 47.2 .5 2.7
Altruism 12.4 51.5 28.6 5.4 2.1
High ethical standards 66.4 28.9 1 .5 3.2
Visionary 6.4 40.8 44.3 7.5 1
Patience 35.1 45.6 15.6 1.6 2.1
Risk taker 2.1 17.8 44.7 30.8 4.6
Loyal 23.7 43.7 27.3 3.2 2.1
Dedicated 43.7 42.9 8.1 3.2 2.1
Adaptable 62.9 29.9 4 .5 2.7
Diplomatic 24.3 50.5 21 3.7 .5
Professional visual image 30.8 43.7 19.1 3.2 3.2
Communicator 61.8 31.3 3.7 .5 2.7
Empathetic 28.1 50.5 17.2 2.1 2.1
Dependable 66.4 29.9 .5 .5 2.7

Note: The values represent mean percentages of the Likert-type-scale responses.

References

Anderson, M. K., Hall, S. J, & Martin, M. (2000). Sports injury management and the athletic trainer. In Sports injury management. (2nd ed.) Baltimore, MD: Lippincott Williams & Wilkins.

Arnheim, D. D, & Prentice, W. E. (2000). The athletic trainer and the sports medicine team. In Principle of athletic training. (10th ed.) New York, NY: McGraw-Hill.

Chen, S., & Esposito, E. (2004). Practical and critical legal concerns for sport physicians and athletic trainers. Sport Journal, 7(2), Retrieved December 3, 2006, from http://www.thesportjournal.org/2004Journal/Vol7-No2/ChenEsposito.asp

Gaedeke, R., Toolelian D., & Schaffer, B. (1983). Employers want motivated communicators for entry-level marketing positions. Market News. 5, 1.

Kahanov, L., & Andrews, L. (2001). A survey of athletic training employers’ hiring criteria. Journal of Athletic Training, 36(4), 408-412.

Lockard, B. C. (2005). Athletic trainers: Providing healthcare for athletes of all kinds.

Occupational Outlook Quarterly, 49(1), 38-41.

Lyznicki, J. M., Riggs, J. A., & Champion, H. C. (1999). Certified athletic trainers in secondary schools: report of the council on scientific affairs, American Medical Association. Journal of Athletic Training, 34(3), 272-276.

National Athletic Trainers’ Association. (2006a) Athletic training educational competencies. (4th ed.). Dallas, TX: NATA.

National Athletic Trainers’ Association. (2006b). Athletic training education overview. Retrieved on November 20, 2006 from www.nata.org/consumer/docs/educationfactsheet05.pdf

National Athletic Trainers’ Association. (2006c). NATA Code of Ethics. Retrieved on January 30, 2007 from http://www.nata.org/codeofethics/code_of_ethics.pdf

National Athletic Trainers’ Association (2006d). Strategic Plan. Retrieved on January 27, 2006 from www.nata.org

National Athletic Trainers’ Association. (2006e). What is a certified athletic trainer?. Retrieved on November 20, 2006 from www.nata.org

National Athletic Trainers’ Association. (2003). Recommendations and guidelines for appropriate medical coverage of intercollegiate athletics. Retrieved on November 1, 2006 from www.nata.org/statements/support/amciarecsandguides.pdf

Ray, R. (2005). Ethics in sports medicine. In management strategies in athletic training. (3rd ed.) Champaign, IL: Human Kinetics.

Smith, L. (2006, November). Big job small staff. Training and Conditioning, pp. 47-51.

Author’s Note

Timothy J. Henry, Associate Professor and Athletic Training Program Coordinator, The State University of New York at Brockport; Robert C. Schneider, Associate Professor, Department of Physical Education and Sport, The State University of New York at Brockport; William F. Stier, Jr., Distinguished Service Professor and Graduate Director, Department of Physical Education and Sport, The State University of New York at Brockport.

Correspondence concerning this article should be addressed to Timothy J. Henry, Department of Physical Education and Sport, The State University of New York at Brockport, 350 New Campus Drive, Brockport, NY 14420. E-mail: thenry@brockport.edu; Fax: 585-395-2771; Work Phone: 585-395-5357.

2016-10-20T11:37:32-05:00April 16th, 2009|Contemporary Sports Issues, Sports Coaching, Sports Management|Comments Off on Desirable Qualities, Attributes, and Characteristics of Successful Athletic Trainers – A National Study
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A New Scale Measuring Coaches’ Unethical Behaviors for Comparison by Gender, Age, and Education Level of Coach

Submitted by: Semiyha Dolaşir Tuncel – Ankara University

Abstract

An effort to develop a scale measuring coaches’ unethical behaviors included two phases. In the first, factor and reliability analyses were made of potential survey items meant to gather data from athletes describing coaches’ behavior. In the second, select items were incorporated in a survey randomly administered to 221 male and female taekwondo competitors at a national competition in 2006, for comparison of behaviors by coach gender, age, and education. Behavior was not found to differ significantly by gender (n = 219, t = 1.71, p > .05), age (n = 216, t = 1.13, p > .05), or education (n = 217, t = 1.60, p > .05).

A New Scale Measuring Coaches’ Unethical Behaviors for Comparison by Gender, Age, and Education Level of Coach

In coaching, a code of ethics is a tool providing a minimum standard of conduct and behavior expected of the coach as he or she develops into a professional. Many other professions, including medicine and law, also expect members to adhere to a behavior code requiring them to do their best and maintain professional standards (Ring, 1992). Codes established for coaches provide common values and guidelines for performing one’s job.

It has been suggested that there is a sensitive relationship between physical education and moral education. Stoll (1995), who is with the University of Idaho Center for Ethical Theory and Honor in Competitive Sports, emphasized that “physical education and athletic programs could be harmonious in promoting the development of sportsmanlike behaviors, ethical decision-making skills, and a total curriculum for moral character development.” Many studies by philosophers of sport concern the relationship of moral education and competition concepts; many conclude that a completed sports education involving both competition and development of an understanding of fair play effects a moral education (i.e., an education in moral values such as honesty, equality, justice, and respect) (Bergmann, 2000; Carr, 1998; Priest, Krause, & Beach, 1999; Singleton, 2003; Spencer, 1993). Sabock (1985) argued that sports provide students an important opportunity to develop ethical behaviors including honesty and fairness. Bergmann (2000) noted a logical relationship between physical education and moral education, one based on students’ understanding of the concept of success and their acceptance of the importance of competitions. Bergmann added that, through competition, students have opportunities to compare their skills and talents to those of others, which motivates them to gain practical knowledge meeting certain standards.

As role models for athletes, coaches can help them develop fair and ethical behavior by demonstrating how these can be applied in sports. Coaches have the capacity to teach and reinforce ethical behavior by athletes and indeed are central to value development in young people, since they are role models of institutional norms (Wandzilak, 1985).

Today, however, unethical behavior exhibited in the course of coaching is decreasing respect for coaches and for sports. Too many coaches approach their duties without adequate regard for values such as honesty, objectivity, and justice. This is so despite the fact that many sports organizations and communities have published codes of ethics that coaches are expected to uphold (American National Youth Sports Coaches Association, n.d.; American Psychological Association, 1992; Australian Sports Commission, n.d.; British Institute of Sports Coaches, n.d.; Canadian Professional Coaches Association, 2003; International Coaches Federation, 2003; Sports Medicine Australia, n.d.; Sports Coach, n.d.). Figure 1 presents a summary of the standards set out by these codes of conduct, classifying them as either a responsibility of coaches or a form of respect coaches are expected to demonstrate.

Responsibility Respect
1. A coach should provide a healthy environment for competition and practice.2. A coach should always work toward personal development, in order to continuously improve his or her job performance.

3. A coach should provide the media and members of the public with correct information.

4. A coach should direct injured athletes to medical treatment and act in accord with medical professionals’ instructions and suggestions.

5. A coach should help athletes with their personal and family problems.

6. A coach’s support should extend to athletes in need, whether or not they are his or her own athletes.

7. A coach should work cooperatively with any expert who might contribute to the development of athletes.

8. A coach should inform athletes of how they should behave during media interviews.

9. A coach should not use training techniques that are harmful to athletes.

10. A coach should select equipment carefully to ensure athletes’ safety.

11. A coach should have the injured athlete’s well-being in mind when deciding whether to permit a return to competition and should never permit return ahead of complete recovery.

12. A coach should assign athletes appropriate responsibilities in order to contribute to their development.

13. A coach should take a protective stance toward athletes when it comes to harmful drugs, by informing athletes about drugs’ dangers.

14. A coach of nonprofessional athletes should schedule practice and competitions that do not interfere with athletes’ need to develop academically.

15. A coach should develop effective ways of communicating to athletes and their families their rights and responsibilities as part of the team.

16. A coach should emphasize education’s importance to athletes, as well as sports’ importance.

17. A coach should instill in athletes the idea that winning results from good team work.

18. A coach should always ensure that athletes receive an explanation of the objectives of training.

19. A coach who disciplines an athlete through punishment should not, in so doing, harm the athlete’s personality.

20. A coach should always explain for athletes the objectives of any rule that will be applied.

 1. A coach should have respect for each athlete’s being.2. A coach should avoid behavior that is likely to diminish the respect afforded him or her by the society.

3. A coach should not exaggerate his or her capabilities.

4. A coach should encourage fair play and sportsmanlike behavior.

5. A coach should keep confidential all personal information on athletes (e.g., personal problems, family problems) and all information about the coach’s job (e.g., budget, recruitment policy), unless disclosure is required by law.

6. A coach should emphasize honesty in competition.

7. A coach should respect the rules of competition.

8. A coach should respect written and unwritten rules of fair play.

9. A coach should respect decisions of referees during competitions.

10. A coach should not encourage athletes or spectators to disrespect referees.

11. A coach should always have his or her behavior under control.

12. A coach should not use negative words to criticize other coaches or organizations.

13. A coach should take responsibility in areas in which he or she feels confident.

14. A coach should not criticize athletes publicly or act to hurt them.

Figure 1. Summary of coaching behaviors mandated by various organizational codes of ethics.

When such standards are ignored, unethical coaching behaviors typically fall into four main categories, according to the United States Olympic Committee (DeSensi & Rosenberg, 1996). They are (a) offending athletes verbally or physically, (b) treating athletes inhumanely, (c) encouraging athletes’ use of performance-enhancing drugs; and (d) ignoring the athletic program’s educational goals. In its various forms, unethical behavior in coaching is becoming an important topic in the physical education literature. The present study’s purpose was to develop a valid and reliable scale measuring the extent of unethical behavior by coaches and then to test whether their unethical behavior was associated with gender, age, or educational level.

Method

Sampling and Research Design

The study collected data in 2006 from 221 competitors in a national taekwondo championship, 86 of whom were female (38.9%) and 135 of whom were male (61.1%). The majority of the sample (76.9%) were ages 17 to 23 years. The mean length of their experience in taekwondo was 7 ± 3 years. The average age at which they began high-performance training (attending training camps and national and international competitions regularly) was 8 ± 2 years.

Instruments and Data Collection

The instrument was developed in three phases. First, from a review of the codes of ethics of the American National Youth Sports Coaches Association (n.d.), American Psychological Association (1992), British Institute of Sports Coaches (n.d.), Canadian Professional Coaches Association (n.d.), International Coach Federation (n.d.), Sports Medicine Australia (n.d.), Sports Coach (n.d.), and several Olympic committees, a pool of 48 survey items was created and subsequently analyzed.

Second, with the 48 items providing a basis, an instrument was developed that used a 5-point Likert-type response scale ranging from 1 (strongly disagree) to 5 (strongly agree) to assess perceived ethical or unethical nature of coaching behaviors (see Table 1). This instrument was administered to a group of 18 taekwondo coaches, taekwondo players, and faculty members or instructors knowledgeable of the sport. They read each item on the instrument and circled a response. The 18 participants unanimously assigned a score of 5 to 35 of the items, so these 35 were accepted by the researcher as describing unethical behaviors (Balci, 1993). The scale was dubbed the Coaches’ Unethical Behaviors Scale, or CUBS.

Table 1

Score Levels Reflected in 5-Point Likert-Type Scale

Choice Score Level
1 Strongly disagree 1.00–1.79
2 Disagree 1.80–2.59
3 Undecided 2.60–3.39
4 Agree 3.40–4.19
5 Strongly agree 4.20–5.00

In the third phase, the final CUBS instrument of 35 items (with 5-point Likert-type response categories) was administered to the 221 taekwondo contestants. Each item posed a scenario involving coaching behavior; respondents circled the numeral indicating how strongly they agreed that they had experienced their coaches demonstrating the unethical behavior.

Statistical Analysis

The construct validity of CUBS was evaluated using exploratory factor analysis (EFA). EFA seeks to identify a factor or factors based on relationships among variables (Kline, 1994; Stevens, 1996; Tabachnick & Fidell, 2001). The reliability of CUBS was assessed using the Cronbach’s alpha coefficient and Spearman-Brown (split-half) correlation. In order to test whether coaches’ unethical behaviors change with gender, age, and educational level, a t test and one-way ANOVA analysis were applied.

Findings

Factor Structure of CUBS: Construct Validity

Results of exploratory factor analysis assessing CUBS’ validity showed 11 of the 35 items to have a factor loading below .45. These 11 were extracted, and the analysis was repeated with the remaining 24 items. Of these, 14 could be classified as pertaining to coaches’ responsibility for athletes, for rules, and for the integrity of the coaching profession; the 14 became Factor 1. The remaining 10 could be classified as forms of respect coaches are charged with upholding (for example, respect for individuals, personalities, gender, and health). These became Factor 2.

For Factor 1, factor loading ranged from .562 to .847, while for Factor 2 it ranged from .561 to .782. Factor 1 accounted for 50.34% of variance, and Factor 2 accounted for 11.31%, so together the factors accounted for 61.65% of total variance (see Table 2).

Item Factor 1 Factor 2 Communalities Variance
1 .562 .466 .533
2 .589 .424 .527
3 .761 .359 .708
4 .674 .426 .635
5 .719 .352 .641
6 .641 .436 .601
7 .758 .155 .599
8 .747 .192 .594
9 .794 .328 .738
10 .833 0.61 .698
11 .811 .228 .710
12 .720 .285 .600
13 .847 .262 .786
14 .834 .281 .774
15 .777 0.46 .606
01 .211 .675 .500
02 .301 .721 .611
03 .377 .561 .456
04 .236 .667 .501
05 .131 .709 .519
06 .191 .737 .580
07 .308 .782 .706
08 0.94 .753 .576
09 .180 .752 .597

Reliability

The reliability of CUBS was assessed using Cronbach’s alpha and the Spearman-Brown correlation. The Cronbach’s alpha coefficients indicate internal consistency; for the two CUBS subscales administered to the 221 athletes, Cronbach’s alpha was .78 for Factor 1 and .77 for Factor 2. The total internal consistency for the scale was .76. The Spearman-Brown correlation yielded .98 for Factor 1 and .93 for Factor 2. Total correlation for CUBS was thus .92.

Corrected item total correlations, which ranged from .63 to .87, are shown in Table 3, along with t-test scores for the items in CUBS. Statistical significance at a level of p < .01 was attained for each item’s mean score.

Table 3

Corrected Item Total Correlations and t Scores for Items in CUBS

Item Factor 1 Factor 2 t p
1 .67 -7,122 .000
2 .70 -8,587 .000
3 .81 -9,341 .000
4 .77 -10,376 .000
5 .79 -10,645 .000
6 .76 -10,468 .000
7 .74 -9,826 .000
8 .75 -11,786 .000
9 .86 -11,590 .000
10 .78 -9,253 .000
11 .82 -12,238 .000
12 .76 -11,763 .000
13 .87 -14,444 .000
14 .86 -9,477 .000
15 .69 -11,574 .000
01 .67 -11,814 .000
02 .74 -9,108 .000
03 .63 -12,701 .000
04 .66 -10,988 .000
05 .74 -10,084 .000
06 .68 -10,174 .000
07 .74 -12,483 .000
08 .81 -11,849 .000
09 .70 -10,783 .000

Unethical Behaviors of Coaches

Using the data from the surveyed taekwondo competitors, coaches’ unethical behaviors were measured with descriptive statistics (see Table 4). As Table 4 illustrates, the athletes reported they had observed in the behavior of their coaches the 24 unethical behaviors reflected in CUBS, although the values measured for these behaviors were low. Observed unethical behavior did not, according to t-test results, appear significantly dependent on gender (n = 219, t = 1.71, p > .05), age (n = 216, t = 1.13, p > .05), or education level (n = 217, t = 1.60 p > .05).

Table 4

Mean, Standard Deviation, and Percentages for Coaches’ Unethical Behaviors as Indicated by CUBS Respondents

Unethical Behaviors M SD %
Responsibility
1. The coach does not deal honestly with athletes. 1.56 1.01 5.50
2. The coach does not inform athletes about harmful effects of drugs (drug abuse). 1.75 1.14 12.70
3. The coach does not build respectful, effective communication with athletes. 1.60 0.95 4.10
4. The coach encourages athletes’ weight loss via means that may harm their health. 1.75 1.02 7.30
5. The coach does not provide athletes necessary information about training. 1.61 0.98 7.70
6. The coach does not continuously improve his or her professional knowledge and skills. 1.72 1.16 10.90
7. The coach does not care about honesty in competition. 1.80 1.17 10.40
8. The coach does not know the legal regulations relevant to his or her sport. 1.53 1.00 5.00
9. The coach does not have sufficient knowledge of training science. 1.73 1.16 13.6
10. The coach abuses his or her authority as a coach. 1.61 0.99 6.80
11. The coach is not honest about the finances of competition. 1.62 1.04 5.90
12. The coach does not prepare effective training programs reflecting athletes’ ability levels. 1.84 1.11 7.20
13. The coach does not evaluate athletes’ performances as they reflect established goals. 1.66 1.00 5.90
14. The coach does not provide athletes with feedback about their performances. 1.68 0.99 7.20
Respect
1. The coach does not treat athletes respectfully. 1.39 0.95 5.90
2. The coach discriminates among athletes based on gender, religion, or language. 1.44 0.82 3.20
3. The coach curses or uses street language. 1.41 0.77 9.00
4. The coach does not respect the being of the athletes. 1.42 0.76 3.60
5. The coach is not careful to avoid harming athletes’ personalities when using punishment to discipline them. 1.56 0.89 5.50
6. The coach causes athletes physical harm in the course of using punishment to discipline them. 1.61 0.95 7.70
7. The coach discriminates among athletes based on reasons other than individual merit. 1.97 1.22 15.00
8. The coach degrades athletes with insults. 1.52 0.87 6.40
9. The coach becomes publicly angry and displays violence after a defeat in competition. 1.62 1.02 8.60
10. The coach does not respect rules and referees. 1.67 1.04 6.80

Discussion and Results

The present study’s purpose was to develop a valid and reliable scale measuring the extent of unethical behavior by coaches and then to test whether their unethical behavior was associated with gender, age, or educational level. CUBS is such a scale, according to the results of factor and reliability analysis (Kline, 1994; Stevens, 1996; Tabachick & Fidell, 2001).

Data obtained with CUBS were subjected to descriptive statistical analysis that suggested the three most frequent unethical behaviors in coaching are discrimination among athletes based on reasons other than individual merit; lack of technical knowledge; and failure to offer athletes facts about harmful drug use. Coaches’ unethical behaviors did not change to a significant degree with changes in gender, age, or education level, according to ANOVA and t-test results.

Addressing ethical issues is becoming a standard part of a coach’s duties. Increasingly, sports coaches must be able to teach and model fair play, respect for officials, paramount concern for athletes’ well-being (rather than the win-loss record), and the wise and legitimate use of power. At the same time, they must steer athletes away from harmful drug use, cheating, bullying, harassment, and eating disorders. The coach’s position on these issues, reflected in his or her coaching behaviors, has enormous impact on athletes, shaping their enjoyment of sports, their attitudes toward their peers in a sport, their self-esteem, and their continued involvement in sports.

The sports ethicist’s basic goal is to see individuals in sports accept a pertinent ethical code (Wuest & Bucher, 1987) and embody that code in their behavior patterns. The aim for the profession of coaching is each coach’s acceptance of an ethical code for his or her sport, exhibited in daily behavior. A scale like CUBS can not only indicate the level of unethical behaviors coaches engage in, it can point the way to the most urgently needed additions to coach education and development programs.

Knowledge and skills are vital to a profession, but appropriate attitudes and behaviors—professional ethics—are just as important. Professional ethics involve written codes containing rules tailored to specific professions and founded in general moral values like honesty, equality, justice, and respect (Fain, 1992; Pritchard, 1998). Unlike in the past, a workforce today is likely to include people of various races, ages, religions, educational levels, and socioeconomic statuses. They are likely to possess divergent values (Lankard, 1991; Frederick, Post, & Davis, 1988). Inculcating a set of professional ethics ensures that, although they are very different people, members of a profession together espouse common standards and rules designed to protect both themselves and the people they serve. The changing nature of the business world has increased the need for professional ethics, the most important characteristic of which is the need for systems, structures, and management that can secure compliance.

A common understanding of sports is that they consist of various activities people pursue that lead to competition (Penney & Chandler, 2000). In fact, sports is a multidimensional phenomenon. It involves social structures (an indispensable part of human life), and it is based on long-established ethical and value systems (Whitehead, 1998). A number of sports organizations want to see the essential ethical nature of sports brought home to spectators and the society by developing athletes’ and coaches’ ethics (Wuest & Bucher, 1987).

Concern for ethics (or the lack of concern) will have an important role in how sports continues to develop; much of the related work will fall to coaches, who are expected to do their jobs honestly, objectively, openly, and with respect and a sense of justice, tying their work to universal values and principles (Wuest & Bucher, 1999). Coaches who may be held responsible for demonstrating ethical behaviors need, first of all, to understand their sports’ particular ethical codes.

The present study was the very first research conducted in Turkey into unethical behaviors exhibited in coaching. Moreover, to date the literature worldwide has offered few studies on coaches’ unethical behaviors. For this reason, further research employing various designs, with various samples, is likely to contribute to understanding of the topic.

References

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American Psychological Association. (1992). Ethical principles of psychologists and code of conduct.

American Psychologist, 47(12), 1597–1611.

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British Institute of Sports Coaches. (n.d.). Code of ethics and conduct for sport coaches. Retrieved April 26, 2002, from http://www.brianmac.co.uk/ethics.htm

Canadian Professional Coaches Association (n.d.). Coaches of Canada coaching code of ethics: Principles and ethical standards. Retrieved December 19, 2008, from http://coach.ca/eng/certification/documents/REP_CodeofEthics_01042006.pdf

Carr, D. (1998). What moral educational significance has physical education? A question in need of disambiguation. In M. J. McNamee & S. J. Parry (Eds.), Ethics and sport (pp. 119–133). London: E & FN Spon.

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Fain, G. S. (1992). Ethics in health, physical education, recreation and dance. (Report No. ED342775 1992-04-00). Washington, DC: ERIC Digest. (ERIC Document Reproduction Service No. ED342775)

International Coach Federation (n.d.). The ICF code of ethics. Retrieved December 18, 2008, from http://www.coachfederation.org/ICF/For+Current+Members/Ethical+Guidelines/

Kline, P. (1994). An easy guide to factor analysis. New York: Routledge.

Lankard, B. A. (1991). Resolving ethical dilemmas in the workplace: A new focus for career development. (Report No. ED334468 1991-00-00). Washington, DC: ERIC Digest. (ERIC Document Reproduction Service No. ED334468)

Penney, D., & Chandler, T. (2000). Physical education: What future(s)? Sport, Education and Society, 5(1), 71–87.

Priest, R. F., Krause, J. V., & Beach, J. (1999). Four-year changes in college athletes: Ethical value choices in sports situations. Research Quarterly for Exercise and Sport, 70, 170–178.

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Sabock, R. (1985). Coach (3rd ed). Champaign, IL: Human Kinetics.

Singleton, E. C. (2003). Rules? relationships?: A feminist analysis of competition and fair play in physical education. Quest, 55, 495–209.

Spencer, A. F. (1996). Ethics in physical education and sport education. Journal of Physical Education, Recreation and Dance, 67(7), 37­–39.

Sports Medicine Australia. (n.d.). Sports Medicine Australia sports first-aider/sports trainer code of ethics. Retrieved December 19, 2008, from http://www.sma.org.au/sportstrainers/ethics.asp

Stevens, J. P. (1996). Applied multivariate statistics for the social sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum.

Stoll, S. K. (1995). Should we teach morality?: The issue of moral education. In A. E. Jewett, L. L.

Bain, & C. D. Ennis (Eds.), The curriculum process in physical education (2nd ed.), 334.

Tabachnick, B. G., & Fidell, L. S. (2001). Using multivariate statistics (4th ed.). Boston: Allyn and Bacon.

Sports Coach (n.d.). Code of ethics and conduct for sports coaches. Retrieved December 19, 2008, from http://www.brianmac.co.uk/ethics.htm

Wandzilak, T. (1985). Values development through physical education and athletics. Quest, 37, 176–185.

Whitehead, M. E. (1998). Sport ethics and education. Sport, Education and Society, 3(2), 239–241.

Frederick, W. C., Post, J. E., & Davis, K. (1988). Business and society: Corporate strategy, public policy, ethics (6th ed.). Columbus, OH: McGraw-Hill.

Wuest, D. A., & Bucher, C. A. (1986). Foundations of physical education and sport (10th ed.). St. Louis, MO: Times Mirror/Mosby.

Wuest, D. A., & Bucher, C. A. (Eds.). (1999). Foundations of physical education and sport (13th ed.). New York: WCB/McGraw-Hill.

2017-08-07T11:39:17-05:00January 8th, 2009|Contemporary Sports Issues, Sports Coaching, Sports Facilities, Sports Management, Sports Studies and Sports Psychology|Comments Off on A New Scale Measuring Coaches’ Unethical Behaviors for Comparison by Gender, Age, and Education Level of Coach
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Characteristics Contributing to the Success of a Sports Coach

Submitted by: Jefrey L. Frost – United States Sports Academy

Abstract

Identifying particular characteristics (qualities and abilities) of successful sports coaches could offer other coaches help in improving their performance. Toward this end, 15 high school coaches completed a survey on 17 possible such characteristics, ranking 5 of them above the rest (≥ 90th percentile): quality of practice, communicating with athletes, motivating athletes, developing athletes’ sports skills, and possessing knowledge of the sport. Coaches seeking to enhance their success might focus on these characteristics.

(more…)

2016-09-30T08:25:51-05:00January 7th, 2009|Contemporary Sports Issues, Sports Coaching, Sports Exercise Science|Comments Off on Characteristics Contributing to the Success of a Sports Coach
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Pay and Performance: An Examination of Texas High School Football Coaches

Submitted by: Scott J. Callan and Janet M. Thomas – Bentley College

Abstract

Salaries paid to high school coaches and team managers have recently generated media and public debate over their justifiability. This research represents an earnings function estimation designed to identify salary determinants for high school football coaches. The theoretical model supporting the analysis builds on models presented in the sports economics literature. To conduct the empirical estimation, we used salary, human capital, performance, and institutional data for coaches of Class 4A and Class 5A 11-man high school football programs in Texas (N = 95). Our results indicate that the determination of overall coaching compensation is significantly affected by human capital investment, measured through experience; by job performance, captured in winning percentage; and by school characteristics, such as location and stadium size.

Pay and Performance: An Examination of Texas High School Football Coaches

Over the past decade, economic investigations of professional sports teams—particularly pay-for-performance studies—have become increasingly prevalent. This emerging research trend has evolved in part because of the broad applicability of economic principles to sporting contexts and also because of the increasing availability of performance and salary data for professional sports participants. Although it has not always been the case, reliable data for selected amateur sports, such as NCAA golf, are also starting to become available, allowing researchers to apply economic reasoning to these varied and important sports environments. (Examples are Callan and Thomas, 2004, 2006, which are investigations of the determinants of success in amateur golf that employed two different samples of NCAA golfers.)

From a theoretical perspective, economic research on sports salaries and performance builds on human capital theory, as first suggested by Becker (1964). Critical to this theory is the belief that education and experience play a significant role in the determination of a worker’s performance and earnings. Simply stated, investments in human capital, such as education, training, and work-related experience, are expected to positively influence compensation.

As for the empirical testing of these theoretical models, most salary investigations within the professional sports literature have focused on individual players as opposed to coaches or managers. It is also the case that most used an earnings function model similar to the one developed by Scully (1974), who studied salary determinants for Major League Baseball players. Consistent with Becker’s (1964) fundamental hypothesis, Scully’s model assumes that a professional baseball player’s development of human capital and skill are critical determinants of his earnings. Since Scully’s original work, numerous studies have adapted his model to other sports settings. For example, Jones and Walsh (1988) examined salary determination for players in the National Hockey League, and Hamilton (1997) did the same for players in the National Basketball Association.

Despite the accumulating research on players’ salaries in various sports, we know of only two papers that adapted Scully’s (1974) original model to an examination of the earnings of team managers or coaches. One is a study by Kahn (1993), and the other is an investigation conducted by Humphreys (2000). A brief overview of each follows.

Kahn (1993) used 1987 data for professional baseball teams to estimate an earnings function for team managers, which in turn was used to analyze managerial quality. Following human capital theory, Kahn’s model specifies earnings as the natural log of manager salary and includes the following as explanatory variables: years of managerial experience; lifetime winning percentage; and a binary variable to control for league (i.e., American or National). Kahn asserts that there are at least two reasons why experience is expected to have a positive effect on earnings. Specifically, more years of experience should reflect (a) greater skills, developed through on-the-job training, and (b) longevity, based on relatively high-quality management ability exhibited over time. Winning percentage captures team performance or success, which also should positively affect earnings, and the binary league variable controls for any league-specific differences in the demand for managerial quality. As expected, Kahn’s results showed that a manager’s experience level and career winning percentage have significant and positive effects on salary, although the league variable was not found to be statistically significant.

Humphreys (2000) used Division I NCAA basketball program data for the 1990–1991 academic year to test for possible gender-based differences in compensation among head basketball coaches. Similar to Kahn’s model, Humphreys’s earnings function defines the dependent variable as the log of annual base salary. Two groups of hypothesized salary determinants are specified: a set of coach characteristics and several control variables to represent the institution where each coach is employed. For the coach characteristics, Humphreys included a dummy variable for gender; experience, in years, to represent investment in human capital; and career winning percentage to measure job performance. In accordance with conventional human capital theory, both experience and winning percentage were assumed to have a positive effect on salary. The institution-specific control variables were intended to capture potential demand-side influences on a coach’s earnings. Included among these were total student enrollment, ticket revenues, and school location. The underlying hypothesis was that greater demand for basketball entertainment, which can be proxied by higher enrollment and larger revenues, should positively influence a coach’s salary.

Humphreys’s empirical estimation across several variations of his model found neither gender nor experience to be significant. However, the results did suggest that performance (measured through career winning percentage) positively affects earnings. Humphreys believed that a high correlation between performance and experience in his sample likely explained the lack of significance found for the experience parameter. Among the institutional control variables, Humphreys found that total enrollment, participation in Division IA games, and ticket revenues exhibited consistently positive effects on collegiate basketball coaches’ salaries.

Clearly, the studies by Kahn (1993) and Humphreys (2000) have helped to identify some of the factors responsible for manager or coach salaries at the professional and collegiate level, respectively. However, to our knowledge, no analogous earnings function estimations exist for noncollegiate amateur coaches, leaving many questions unanswered.

At least until recently, the primary reason for this lack of research on noncollegiate school sports was, apparently, limited or nonexistent data. However, reliable data on high school football in some regions of the United States have now become available. That such a turn of events is timely is evidenced in part by recent media attention to high school coaches’ salaries, particularly in comparison to teachers’ and other school administrators’ salaries. Some journalists report on the relatively high salaries earned by high school football coaches, particularly in the southern and western United States, where high school football is markedly more important to local communities than in other regions (Jacob, 2006; Associated Press, 2006). Others, such as Abramson (2006), counter with a different perspective about coaches’ earnings, referring to long hours worked, particularly in so-called football states like Texas, Florida, and Georgia.

A related issue raised by the media is the extraordinary level of monetary investments made in some high school football programs, an observation that some find particularly striking in the face of funding cuts for educational resources and programs. In a recent issue of a national newspaper, Wieberg (2004) reported on multimillion-dollar projects in Texas, Georgia, and Indiana to build state-of-the art high school football stadiums. This trend, he argued, arises from a competitive race involving high-end facilities and highly paid coaches that has trickled down from the college level. In some states, such competition arises from open enrollment policies, under which schools literally compete for students to preserve their state funding (which is linked to enrollment). Schools also compete for a strong fan base to generate revenues to help support the costs of football programs—including elevated salaries for coaches, some reportedly reaching six figures. Such activity, which is consistent with the demand-side effects on salary suggested by Humphreys (2000), identifies another motivation for exploring the issue empirically.

The present research addressed the critical issues by empirically examining salary determinants for a sample of high school football coaches in Texas. There were a number of reasons for using Texas as the context of the analysis. First, high school football is enormously popular in Texas, and schools there invest heavily in football programs. These observations translate to a favorable opportunity to study demand-side salary determinants for coaches along with the usual human capital factors. Second, and perhaps not unrelated to the first reason, the necessary sample data to conduct an empirical estimation of earnings have become available for the state. Third, because Texas high school football is nationally recognized, we anticipated that our findings concerning Texas coaches would both call attention to underlying issues and stimulate new research on salary determination for those who coach in other parts of the country and in other high school sports.

Method

Sample

Reflecting both data availability and our motivation to capture possible demand-side factors in our model, the sample for this study was 95 head coaches at Class 4A and Class 5A Texas high schools during the 2005–2006 football season. Oversight of high school football in Texas is provided by the University Interscholastic League (UIL). The UIL is a nonprofit organization with a purpose to “organize and properly supervise contests that assist in preparing students for citizenship” (About the UIL, n.d., ¶3); extracurricular activities outside athletics also fall within UIL’s purview. The UIL organizes Texas high school football contests based on schools’ geographic locations and enrollments. It divides football programs into 6-man and 11-man classifications. Most small schools (i.e., those with fewer than 100 enrolled students) participate in 6-man football, but the majority of Texas high school football programs are 11-man programs. The sample for this study was drawn from 11-man programs only.

Giving greater context for our analysis, table 1 presents the breakdown by classification of the 1,033 11-man high school football programs in Texas. The UIL identifies 32 geographic districts within Texas. The average number of football teams within each district ranges from 5.13 in Class 1A, to 7.53 and 7.69, respectively, in the larger 4A and 5A classes. The data indicate that significant enrollment differences exist across these various conferences. Classes 4A and 5A comprise the largest schools, those with enrollments as high as 2,084 and 5,852, respectively.

Table 1

2008–2009 Season Data for Texas High School 11-Man Football Teams, by Class

Class Number of districts with football programs in the class Number of schools with football programs Average number of schools per district Minimum enrollment Mid-point enrollment Maximum enrollment
1A 32 164 5.13 69.00 134.00 199.00
2A 31 205 6.61 201.00 314.75 428.50
3A 32 177 5.53 222.00 599.00 976.00
4A 32 241 7.53 533.00 1,308.50 2,084.00
5A 32 246 7.69 1,515.00 3,684.00 5,852.00

Note. Conference 2A spans 32 districts, but no school in District 24 has an 11-man football program. From “Alignments (updated for 2008–2010),” n.d., retrieved June 14, 2008, from http://www.uil.utexas.edu/athletics/football/

Measures

For each coach in our sample, we collected earnings data for the 2005–2006 academic year from a Dallas Morning News article, creating our empirical model’s dependent variable, SALARY (Jacob, 2006). According to a recent article in the popular press, a Class 4A or Class 5A head coach typically works 70–100 hr per week and is under contract for a 226-day work year (Texas Twist, 2006). Some coaches also teach, and some hold administrative positions such as athletic coordinator or athletic director. Our empirical model defined the variable ADMIN as a binary variable equal to 1 for a coach having administrative responsibilities or to 0 otherwise. We expected that coaches with administrative positions in addition to coaching responsibilities would earn higher salaries than those with coaching responsibilities only. Hence, we anticipated that the estimated parameter associated with ADMIN would be positive.

To capture each coach’s investment in human capital, we defined two distinct measures, GAMES and ROOKIE. Because the number of contests each team plays annually is fairly consistent, the GAMES variable was allowed to serve as a proxy for each coach’s cumulative head coaching experience in years (the data we would have preferred as our measure of human capital investment, had they been available). The GAMES variable actually measured the cumulative number of games for which an individual had acted as a head coach. Increases in this human capital variable were expected to have a positive influence on coaches’ salaries. The binary variable ROOKIE equaled 1 for a coach who was a rookie head coach (i.e., had no more than one year’s experience) and 0 for more experienced coaches. We anticipated that the parameter on this variable would be negative, reflecting the market’s ability to pay a rookie coach a lower salary than a veteran coach.

The sports economics literature suggests that in addition to experience level, how able a coach is, reflected in job performance, is an important determinant of compensation. Both Kahn (1993) and Humphreys (2000) used a coach’s career winning percentage to capture job performance. Following their approach, we defined a variable, WP, to measure the overall career winning percentage for each coach in our sample. If a coach’s winning percentage increased, we hypothesized, his salary will be higher, holding all other factors constant.

We further theorized that a coach’s salary would be influenced by demand-side characteristics (Humphreys, 2000), which would be linked to attributes of the high school employing the coach. One such characteristic was student enrollment, which we measured in the ENROLL variable, obtaining data from PigskinPrep.com, a website devoted to Texas high school football. (PigskinPrep.com’s Class 4A data was found at www.texasfootballratings.com/4ADistEnrollmentRealign.html and its Class 5A data at www.texasfootballratings.com/5ADistEnrollmentRealign.html). Schools with larger enrollments are expected to pay their coaches higher salaries, so we expected to find a positive relationship between ENROLL and SALARY.

Moreover, because Texas football has a following that extends beyond the student body, it was important to include some measure of community demand for the sport. Indeed, H. G. Bissinger (1990) suggests, in his best-selling book Friday Night Lights, that football in Texas is a community event. Therefore, we included the variable STADIUM in our empirical model to measure seating capacity at the facility where each coach’s school played its home games; the Texas High School Stadium Database (www.texasbob.com/stadium) provided the measures for each stadium. STADIUM was intended to capture a community’s market demand for high school football. Adapting Humphreys’s (2000) logic to our model, we expected that high school teams playing in larger stadiums would generate more revenue than those playing in smaller facilities, yielding more funds with which to compensate their head coaches, and hence we expected STADIUM to be positively related to SALARY. While we viewed stadium capacity as a reasonable proxy, we would have preferred including ticket revenues directly in our model, as Humphreys did, had such data been available for the individual Texas high schools. UIL does track football gate receipts for Texas high schools as a group. They totaled $1,102,798 for the 2005–2006 season, more than any other high school sport in Texas generated (West, Davis, and Company, 2008).

Lastly, following Humphreys (2000) we included a location-specific variable, DALLAS, in our model. The measure is a binary variable equal to 1 for a school located in the Dallas school district or to 0 otherwise. The variable controls any salary differences associated with location in the Dallas urban district. Earnings levels in urban districts may differ from those in other districts, due to differences in cost of living and/or population. However, since the relative magnitude of any such effect was not known a priori, the qualitative relationship between SALARY and DALLAS could not be predicted.

Procedures

To estimate the earnings function for each head coach in the sample, we used multiple regression analysis to examine the relationship between earnings and the defined human capital investment measures, job performance, and demand-side characteristics. As the literature suggests is typical, we transformed the dependent variable, SALARY, by natural logs. This transformation meant that the effect of each explanatory variable on earnings could be interpreted as a percentage change.

Results and Discussion

Fundamental statistical analysis was used to describe the variables in our data set. Table 2 presents the basic descriptive statistics for the sample of 95 Class 4A and Class 5A head football coaches. Note that, on average, a coach in this sample earned slightly more than $82,000 per year, and that 9 out of 10 coaches performed some administrative duties. The average coach had participated in approximately 107 games and achieved an overall career winning percentage of 53.41. Because a typical season consists of approximately 10 games, the mean value of 106.8 for GAMES suggests that the average coach in our sample had over 10 years of head coaching experience. Only 7% of the coaches were rookies.

Regarding institution-specific characteristics, the mean value for school enrollment was 2,310 students, and the average high school stadium seated 10,963 fans. The difference between the two measures indicates that demand for Conference 4A and 5A football extends well beyond the student body to the larger community. We also observed that 20% of coaches in the sample were employed at schools in the Dallas school district.

Table 2

Basic Descriptive Statistics for Class 4A and Class 5A Head Coaches (N = 95)

VariableMeanStandard DeviationMinimumMaximum

SALARY 82,179.00 10,457.00 50,117.00 106,044.00
GAMES 106.80 89.67 10.00 401.00
ROOKIE 0.07 0.26 0.00 1.00
WP 53.41 17.30 5.00 84.00
ADMIN 0.91 0.29 0 1.00
STADIUM 10,963.00 3,795.00 3,500 21,193
ENROLL 2,310 849.12 1,076 5,652
DALLAS 0.20 0.40 0.00 1.00

Table 3 presents the multiple regression estimates for our hypothesized earnings function model. (Several model specifications were estimated; overall results for the alternative model specifications did not differ significantly from the results presented in table 3.) On the basis of the adjusted R-squared statistic, our regression model explains over 58% of the variability in the natural log of earnings. The overall fit of our model compares favorably with those presented by other researchers. Each regression model presented by Kahn (1993) and Humphreys (2000) explained less than 50% of the variability in, respectively, professional coaches’ salaries and collegiate coaches’ salaries.

Table 3

Regression Model Parameter Estimates (Dependent Variable = Natural Log of Salary)

Determinant Parameter estimate
    Intercept 11.11†
Human capital variables
    GAMES 3.96 E-04†
    ROOKIE -0.09**
Job Performance variable
    WP 8.88 E-04†
Institution-specific characteristics
    ENROLL 2.94 E-05**
    STADIUM 3.55 E-03†
    DALLAS -0.17†
Other factors
    ADMIN 0.04
F-statistic 19.81 (p value < 0.001)
R-squared 61.45
Adjusted R-squared 58.34

* p < 0.05, assuming a one-tailed test of hypothesis for ENROLL and two-tailed tests elsewhere. ** p < 0.01, assuming a one-tailed test of hypothesis for GAMES and two-tailed tests elsewhere. † p < 0.10, assuming a one-tailed test of hypothesis for WP and STADIUM.

Turning attention next to the model’s individual parameter estimates, we made a series of important observations, starting with the two measures of human capital investment. First, as anticipated, the algebraic sign on the ROOKIE parameter was negative, meaning that a coach with no more than 1 year of experience received less compensation than veteran coaches. On average, the difference was approximately 9%. Second, the estimated directional effect for a coach’s level of experience, measured through the GAMES variable, was consistent with expectations. Specifically, we found that GAMES had a statistically significant positive effect on a coach’s salary. Holding all other factors constant, each additional year of coaching experience increased salary by, on average, approximately 0.4 percentage points. (We assumed that 10 games represented about 1 year of play; the GAMES parameter estimate hence indicates that each additional game coached translated to a salary increase of about 0.04%, a year’s worth of games thus representing 10 times that salary increase, or 0.4%.) In contrast Kahn’s (1993) investigation of Major League Baseball managers showed that each additional year of experience in professional ball increased a manager’s salary by 2.35%. Humphreys’s (2000) investigation of NCAA basketball coaches did not find the analogous effect on salary to be statistically significant. He argued that a high correlation (0.60) between career winning percentage and years of experience most likely produced the insignificant result for the latter variable. The correlation coefficient between GAMES and WP in our model was markedly lower (0.46).

Holding constant a coach’s investment in human capital, we obtained further results indicating that a coach’s job performance, measured by WP, has a statistically significant positive effect on compensation (a one-tailed test was used). Qualitatively, this result is consistent with those presented by Kahn (1993) and Humphreys (2000). The specific estimated value suggested that an increase of 10 percentage points for WP increased a coach’s salary by approximately 0.9%. Clearly, this finding suggests that winning is important in high school football. However, the common sports adage “Winning is everything” seems an overstatement, at least in the context of how high school football coaches’ salaries are determined.

Quite predictably, our results also indicate that demand-side factors are relevant to the determination of coaches’ overall compensation. For two of the demand-side, institution-specific variables, STADIUM and ENROLL, each of the obtained parameters had the predicted positive sign. Using a one-tailed test, the parameter on STADIUM was statistically significant at the 10% level. This suggests that coaches at schools with larger stadiums, and hence greater demand for high school football, receive higher compensation than those at schools with smaller stadiums. The parameter on ENROLL was positive and statistically significant on the basis of a two-tailed test. As expected, then, larger schools tend to compensate coaches at higher rates than do schools with relatively fewer students. The specific estimated value implies that for every additional 100 students enrolled in a school, its football coach’s salary is about 0.29% higher. The underlying premise is that demand for football games is greater when the student body is larger.

The algebraic sign of the parameter on the urban location variable, DALLAS, was negative and statistically significant at the 1% level. This finding differs from Humphreys (2000), who in his study of NCAA basketball coaches did not find the urban location variable to be significant. It might be the case that the result in our model is specific to the Dallas, Texas, area and cannot be generalized to other urban areas. In any case, we can say that the subsample of Texas high school coaches employed by the Dallas school district earned about 17% less than their counterparts in other districts. This negative effect might reflect a larger population of available coaches in the area, which would mean greater competition for available positions and hence lower salaries. It might also be a function of the relatively low cost of living in Dallas, suggested by consumer price index levels for Dallas versus other areas (U.S. Department of Labor, 2008).

Finally, while the parameter on ADMIN had the expected sign, the finding was not statistically significant. This result may be due to the fact that over 90% of the head coaches in our sample held some type of administrative position in addition to their regular coaching duties. The resulting lack of variability in this measure may be responsible for its insignificance in our earnings function.

Conclusion

It is well documented in the sports economics literature that, holding ability constant, a player’s investment in human capital and his overall performance contribute significantly to the determination of overall compensation. Building on these findings, recent research in sports economics has applied earnings function analysis to an examination of salaries paid to professional and collegiate team managers and coaches. Although this segment of the sports literature is still in its infancy, thus far the empirical findings are generally consistent with those for players. That is, investments in human capital and job performance seem to be significant determinants of managers’ and coaches’ salaries, just as they are of players’ salaries.

In this research study, we extended the analysis of sports managers’ and coaches’ salaries to the noncollegiate amateur level, using a sample of Texas high school football head coaches employed during the 2005–2006 season. Following the approach used in investigations of professional sports, we modeled and estimated an earnings function, using conventional regression analysis. Our model specified a series of potential salary determinants, including human capital measures, a performance variable, and institution-specific demand-side factors.

Our statistical findings indicate that coaches’ salary determinants at the high school level are qualitatively consistent with those identified in the literature for professional and collegiate coaches. Specifically, a high school coach’s development of human capital was shown to be a statistically significant determinant of his salary. Moreover, a coach’s performance or ability to win games, as measured by career winning percentage, also affected his earnings. Lastly, consistent with findings presented by Humphreys (2000), we found that demand-side, institution-specific influences such as the size of the fan base can affect a coach’s compensation.

Taken together, the results of this research, we believe, make an important contribution to the literature examining compensation paid to sports participants, because they broaden its scope to include coaches at the high school level. The findings are timely, as well, given recent media attention to coaching salaries and the associated debate about rising investments in high school sports programs concurrent with funding cuts for education. We are hopeful that, as new data become available, other researchers will seek to validate our findings in other locations and for other high school sports throughout the country. This in turn could help stimulate important dialogue about the level of compensation for coaches relative to other educational professionals and whether that compensation appropriately rewards experience and performance.

References

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Abramson, A. (2006, October 31). High school football coaches want pay to stay. Palm Beach Post. Retrieved September 24, 2008, from http://www.palmbeachpost.com/highschools/content/sports/epaper/2006/10/31/a1c_highschoolcoaches_1031.html

Becker, G. S. (1964). Human capital: A theoretical and empirical analysis, with special reference to education. New York: National Bureau of Economic Research.

Bissinger, H. G. (1990). Friday night lights: A town, a team, and a dream. Cambridge, MA: DaCapo Press.

Callan, S. J., & Thomas, J. M. (2004). Determinants of success among amateur golfers: An examination of NCAA Division I male golfers. The Sport Journal, 7(3). Retrieved September 24, 2008, from http://www.thesportjournal.org/article/determinants-success-among-amateur-golfers-examination-ncaa-division-i-male-golfers

Callan, S. J., & Thomas, J. M. (2006). Gender, skill, and performance in amateur golf: An examination of NCAA Division I golfers.” The Sport Journal, 9(3). Retrieved September 24, 2008, from http://www.thesportjournal.org/article/gender-skill-and-performance-amateur-golf-examination-ncaa-division-i-golfers

Hamilton, B. H. (1997). Racial discrimination and professional basketball salaries in the 1990s. Applied Economics, 29, 287–296.

Humphreys, B. R. (2000). Equal pay on the hardwood: The earnings gap between male and female NCAA Division I basketball coaches. Journal of Sports Economics, 1(3), 299–307.

Jacob, M. (2006, January 9). High school football coaches cashing in. Dallas Morning News. Retrieved September 24, 2008, from http://www.dallasnews.com/sharedcontent/ dws/spt/highschools/topstories/stories/010806dnspocoachsalaries.2a4475f.html

Jones, J. C. H., & Walsh, W. D. (1988). Salary determination in the National Hockey League: The effects of skills, franchise characteristics, and discrimination. Industrial and Labor Relations Review 41(4), 592–604.

Kahn, L. M. (1993). Managerial quality, team success, and individual player performance in Major League Baseball. Industrial and Labor Relations Review 46(3), 531–547.

Scully, G. W. (1974). Pay and performance in Major League Baseball. American Economic Review, 64, 915–930.

Texas twist: Football coaches earn more than teachers. (2006, August 27). ESPN.com. Retrieved September 24, 2008, from http://sports.espn.go.com/sports/news/story?id=2562629

UIL [University Interscholastic League] alignments (updated for 2008–2010). (n.d.). Retrieved June 14, 2008, from http://www.uil.utexas.edu/athletics/football/

U.S. Department of Labor, Bureau of Labor Statistics. (n.d.). Consumer Price Index, Retrieved July 15, 2008, from http://www.bls.gov/CPI/home.htm

West, Davis, and Company. (2008, January 25). University Interscholastic League: Annual financial report (statutory basis) for the year ended August 31, 2006. Retrieved June 14, 2008, from http://www.uil.utexas.edu/policy/pdf/05_06financial_report.pdf

2016-10-12T14:56:39-05:00October 7th, 2008|Contemporary Sports Issues, Sports Coaching, Sports Facilities, Sports Management|Comments Off on Pay and Performance: An Examination of Texas High School Football Coaches
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Active Versus Passive Recovery in the 72 Hours After a 5-km Race

Submitted by: Andy Bosak – West Virginia Wesleyan College; Phil Bishop and Matt Green – University of Alabama; Mike Iosia – Lee University

Abstract

We do not clearly understand what type and duration of recovery works best after a hard run to restore the body to peak racing condition. This study compared 72 hr of active recovery after a 5-km running performance with 72 hr of passive recovery. A sample of 9 male and 3 female runners of above-average ability completed 3 trials within 6 days. Each 5-km trial was followed by 72 hr of passive recovery (PAS) or 72 hr of active recovery (ACT), a counterbalanced protocol. The 2 initial 5-km trials constituted separate PAS and ACT baselines. Mean finishing times did not differ significantly (p = 0.17) between ACT (19:35 + 1.5 min) and baseline (19:41 + 1.7 min); nor was there significant difference (p = 0.21) between PAS (19:30 + 1.5 min) and baseline (19:34 + 1.6 min). Average heart rate for PAS (177.9 + 6.3 b/min) was significantly higher (p = 0.04) than baseline (175.4 + 6.5 b/min), but ACT average heart rate (175.9 + 6.6 b/min) was significantly lower (p = 0.02) than baseline (178.9 + 6.4 b/min). For PAS, perceived rate of exertion at ending (19.8 + 0.6) was significantly greater (p = 0.01) than baseline (19.3 + 0.9), yet for ACT, perceived rate of exertion at ending (19.6 + 0.8) did not differ significantly (p = 0.17) from baseline (19.7 + 0.7). During PAS trials, 2 individuals ran a mean 12.0 + 2.8 s slower, 2 individuals ran a mean 33.0 + 21.0 s faster, and 8 individuals ran within 5.1 + 2.5 s of their first run. During the ACT trials, 1 participant ran 13.0 s slower, 3 participants ran a mean of 34.7 + 13.5 s faster, and 8 nonresponders ran within 5.5 + 2.7 s of baseline. Results indicate that 72 hr of passive and active recovery result in similar mean 5-km performance.

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2016-10-19T11:20:16-05:00July 7th, 2008|Sports Coaching, Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on Active Versus Passive Recovery in the 72 Hours After a 5-km Race
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