ISSN: 1543-9518|Vol. 24

Qualitative Analysis of International Student-Athlete Perspectives on Recruitment and Transitioning into American College Sport

David Pierce (Ball State University); Nels Popp (Illinois State University); Brad Meadows (Ball State University)

### Abstract

Recruiting international athletes is a growing trend in American intercollegiate sport, and international student-athletes play an increasingly prominent role in NCAA competition. This research answers the following questions regarding the recruitment of international student-athletes and their transition to college life: (1) what is the most difficult aspect of the international university experience?; (2) what do international athletes identify as the most important factor for a successful transition to American college?; (3) how did international athletes hear about athletic opportunities in the United States; (4) what advice would current international athletes give international athletes considering a move to the United States to participate in intercollegiate sport?; and (5) what would the athletes have done had they not played college sports in the United States? The researchers solicited the assistance of CHAMPS/Life Skills coordinators at 15 Division I schools who distributed surveys to student-athletes, who in turn completed the survey, sealed it in an envelope, and returned in to the coordinator. A total of 355 athletes completed the survey, including 192 international athletes. Homesickness and adjustment to the U.S. culture were identified as the most difficult aspects of the university experience for international athletes, while the most important elements to a successful transition for international athletes were a strong support system from teammates and coaches and also from friends and family in their native country. Only one-fourth of respondents learned about athletic opportunities from coaches in the U.S., while one-fourth of the respondents learned about these opportunities from friends, family, and other athletes. The top piece of advice given by respondents was to realize that playing sports in the U.S. will require important traits like focus, dedication, hard work, and persistence in order to succeed. The results of this study highlight the importance of transitioning international athletes into college life. Once international athletes are on campus, a member of the athletic department staff should oversee the athlete’s transition into college life, focused on combating the top three challenges identified in this research: homesickness, adjustment to U.S. culture, and language. This staff member should serve as a liaison between athletic department personnel and other campus resources to facilitate a smooth transition.

**Key Words:** international student-athletes, recruiting, transition to college

### Introduction

Recruiting athletes from outside of the United States is a growing trend in college athletics as international student-athletes play an increasingly prominent role in NCAA competition (6, 9, 22). For coaches, who must recruit talented athletes in order to be successful, “the pressures to win, and the penalties for losing, are exacting. Many Division I coaches’ jobs are predicated on the strength of their programs, causing them to recruit the best talent they can find, in many cases from the international pool” (19, p. 860). Evidence of a worldwide search for talent is found in the 17,653 international student-athletes that competed in NCAA competition during the 2009-10 school year, a large increase from the just under 6,000 that competed a decade prior (11). Among Division I schools, over one-third of the male and female athletes in both tennis and ice hockey, and over one-eighth of male and female golfers, were born outside of the United States (11). In addition to increasing participation numbers, international athletes have dominated in individual sports like tennis and golf, and led teams to championship performances (13, 22). However, international athletes face many challenges in adjusting to the language, coursework, dorm life, food, cultural expectations, coaching, paperwork, and the style of play in the United States. As international athletes continue to leave their mark on NCAA sports, coaches and administrators benefit from understanding what difficulties come with transitioning to life as a student-athlete in the U.S. and how international athletes learn about the recruitment process.

Previous research has examined the adjustment process for both international students and international athletes to college. While researchers have noted that a lack of groups with which to socialize is a problem for many international students (7, 10, 20), international athletes have the advantage of being immediately placed within a team structure (14). However, athletes may still face similar obstacles to a successful transition including culture shock, cultural differences, academic adjustment, homesickness, discrimination, and contentment (5). Ridinger and Pastore (17) were the first to create a model of adjustment for international student-athletes, which included four antecedent factors (personal, interpersonal, perceptual, and cultural distance), and five types of adjustment (academic, social, athletic, personal-emotional, and institutional attachment), resulting in two outcomes (satisfaction and performance) to define successful adjustment to college.

Researchers have also examined the recruitment of international athletes. Not only can coaches create winning programs through the recruitment of international athletes, but coaches can also maintain successful teams with international athletes through the establishment of talent pipelines (3-4, 21). Bale (3) identified talent pipelines in which concentrations of athletes from certain countries were found in particular NCAA institutions, with coaches hoping that friend-to-friend recruiting will result in attracting elite athletes from a particular foreign country. Bale (3) noted that institutions unable to compete for homegrown talent, due to lack of prestige or unattractive campus location, established talent pipelines with a foreign country. For example, a talent pipeline of elite track and field stars from Kenya was found at schools like University of Texas El Paso and Washington State University, and a pipeline of track talent from Nigeria was identified at the University of Missouri and Mississippi State University (3). Talent pipelines are an important recruiting strategy, particularly when coaches are unable to compete for local athletes or local talent is not available for certain sports (21).

This research seeks to provide answers the following questions regarding the recruitment of international student-athletes and their transition to college life: (1) what is the most difficult aspect of the international university experience?; (2) what do international athletes identify as the most important factor for a successful transition to college?; (3) how did international athletes hear about athletic opportunities in the United States; (4) what advice would current international athletes give international athletes considering a move to the United States to participate in intercollegiate sport?; and (5) what would the athletes have done had they not played college sports in the United States?

### Methods

The sample for this study included N = 355 athletes from 15 NCAA Division I institutions, including n = 192 international athletes. Schools selected for this study were based on a need to collect data from purposive clusters of Division I institutions, given certain factors may influence international student-athletes’ experiences at their United States institution such as school size, the size of the community within which the school is located, and the geographic location of a school (3). Seven schools were members of the Football Bowl Series (FBS) conferences, while eight were not. Eleven conferences were represented in the study. Eight schools were located in large metro areas with populations over 400,000, while seven were located in communities with populations under 170,000. Six schools were located in the eastern third of the U.S., six were located in the Midwest, and three were located in the western third of the country.

The researchers solicited the assistance of CHAMPS/Life Skills coordinators from the 15 schools via phone to see if they would agree to participate in the study. The researchers then collected the names of all international student-athletes listed on website rosters. The coordinators were instructed to distribute the surveys to the student-athletes, who in turn completed the survey, sealed it in an envelope, and returned in to the coordinator. Participation in the survey was voluntary and a letter indicating the participant’s rights were included, per the approval obtained by the university Human Subjects Review Committee.

A total of 192 athletes representing 57 countries responded to the survey for a response rate of 39.6%. The top three countries represented were: Canada, 24%; England, 8.3%; and Puerto Rico, 7.8%. Males accounted for 45% of the sample and females accounted for 55%. The responses from the open-ended questions in the International Student-Athlete Survey were content analyzed. Two raters independently examined the data and codes were developed to categorize written responses (18). To test intercoder reliability, the coders independently examined 20% of the sample. The codebook and coding protocol were clearly understood, as the correction for chance agreement (Scott’s Pi) exceeded .8 for all but one question, which yielded an acceptable .77 (23).

In addition to frequency counts for each question, chi square was utilized to examine differences between demographic variables, including: gender, native area of origin (Canada, Europe, South America), length of time in the United States (0-2 years, 2.5 to 3.5 years, 4+ years), type of sport (team or individual), class standing (freshman/sophomore and junior/senior), whether or not the athlete used a campus visit, number of schools considered (0-2, 3+), and whether or not the athletes had a full scholarship.

### Results

Ten variables were identified for the first question, “what is the most difficult aspect of the international university experience?” Homesickness was the most difficult aspect, accounting for 24.1% of all answers, followed by adjusting to the U.S. culture, 20.5%; and adjusting to the language, 14.7%. Table 1 displays all ten coded answers for question 1. In order to examine the difference between various demographic variables through chi square analysis, the ten answers in Table 1 were re-coded into four variables (language and cultural adjustments, homesickness, athletic and academic transitions, financial and logistical difficulties, and other). First, chi square analysis revealed that European athletes were more likely to note language and cultural adjustments as a difficult aspect of the international university experience than non-European athletes (χ2 (4, N = 278) = 12.1, p = .017). Second, Canadian athletes were more likely to identify financial and logistical difficulties than non-Canadian athletes (χ2 (4, N = 278) = 29.8, p = .001). Third, athletes participating in individual sports were more likely to identify language and cultural adjustments as a difficult aspect than athletes on team sports, while athletes participating on team sports were more likely to identify homesickness than athletes on individual sports (χ2 (4, N = 278) = 11.4, p = .023). Finally, freshman/sophomore athletes were more likely to identify language and cultural adjustments than junior/senior athletes (χ2 (4, N = 278) = 11.7, p = .020).

Seven variables were identified for the second question, “what were the most important factors in helping you transition to university life in the United States?” Over one-third of respondents indicated that a strong support system from teammates and coaches on their college team was important, and 20.2% indicated that a strong support system from friends and family in their native county was important. Table 2 displays all seven coded answers from question 2. The answers in Table 2 were re-coded into two variables (support system identified as important, support system not identified as important). First, chi square analysis revealed that athletes from the Carribean/South America were less likely to cite the need for a support system from coaches, family, and friends than athletes not from that area (χ2 (4, N = 267) = 7.3, p = .006). Second, junior/senior athletes were more likely to identify the importance of a support system from coaches, family, or friends than freshman/sophomore athletes (χ2 (4, N = 265) = 6.9, p = .006).

Eight variables were identified for the third question, “How did you first learn about opportunities to earn university sports scholarships in the United States?” One-fourth of the respondents learned about these opportunities from friends, family, or other athletes, while another one-fourth indicated they learned from individuals who had previously participated in U.S. sports. Only 23.9% learned from personnel related to U.S. college sports (i.e. coaches and administrators). Table 3 displays all 8 coded answers from question 3. Chi square analysis revealed that athletes playing team sports obtained information regarding U.S. college sports differently than athletes participating in individual sports. Team sport athletes were more likely to obtain recruiting information from those involved in U.S. college sports (i.e. coaches and recruiters) than individual sport athletes (χ2 (1, N = 180) = 4.4, p = .030). Additionally, athletes participating in individual sports were more likely to learn about scholarship opportunities through personal relationships with family, friends, and athletes, while team sport athletes are more likely to learn about scholarship opportunities through those involved with the institutional sport structure (i.e. coaches, administrators, recruiting services) (χ2 (1, N = 180) = 4.9, p = .02)

In a related question, international athletes were asked to compare the athletic facilities and athletic opportunities in the United States and their home country. The respondents overwhelmingly indicated that both the facilities and opportunities were better in the United States. Only ten percent of the international athletes believed that either the facilities or opportunities in their home country were better than what was available in the United States.

Fourteen variables were identified for the fourth question, “what advice would current international athletes give international athletes considering a move to the United States to participate in intercollegiate sport?” However, only four variables occurred in greater than 7% of the responses. The top piece of advice given by one-fifth of the respondents was to realize that playing sports in the U.S. will require important traits like focus, dedication, hard work, and persistence in order to overcome challenges. Second, 18.9% encouraged prospective international athletes to do adequate research on schools before deciding which school to attend, such as getting to know the coaches, athletes, and athletic facilities. Third, 14.2% recommended making the decision to play in the United States because it was such as an excellent opportunity. Fourth, 11.8% indicated it is important to consider academics and majors that can be used to obtain employment in their native country, meaning it is important to find the best overall fit between academics and athletics when deciding on a school.

Finally, international athletes were asked, “what would you be doing now if you had not had this opportunity to play for an NCAA university?” Responses were categorized by what the athlete would be doing (i.e. working, attending college, playing sports) and where they would be living (i.e. native country, United States), as presented in Table 4. Only seven athletes indicated they would be attending college in the United States, while 105 respondents indicated they would be attending college in their native country and only 33 would have continued to play sports in their native country.

### Discussion

American NCAA Division I universities provide opportunities for elite athletes from outside the U.S. to pursue their university degree while continuing to train and compete at a high athletic level, an opportunity not possible in many other countries. However, international athletes face challenges in adjusting to life as a student-athlete. It should come as little surprise that international athletes felt the most difficult aspects of playing university sport in the U.S. were dealing with homesickness, cultural differences, and language barriers. Many cross-cultural sojourners find themselves dealing with similar issues once the initial excitement of being submerged in a new culture wears off (1, 12). In fact, the greater the cultural distance between the sojourner’s native country and the host nation, the greater the adjustments international athletes would be expected to make (17). As was demonstrated in the results, Canadians, whose native country is culturally quite similar to the U.S., were much less likely to indicate a concern with homesickness, cultural differences, and language barriers (for many Canadians, the language barrier is non-existent). Canadian athletes were much more concerned with financial and travel logistics. The results also indicated that freshman and sophomores struggle with these issues more than experienced athletes in their junior and senior years.

The respondents to the survey revealed two key strategies to overcoming these difficulties and successfully transitioning into life as a student athlete during the first year on campus. First, international athletes indicated the high importance of understanding what international-student athletes are “getting themselves into” before committing to an NCAA school. Advice dispensed by the sample in this study focused on understanding the dedication and commitment required of an NCAA Division I athlete, knowing the differences between schools, coaches, and athletic programs at various universities, and learning which schools and academic programs could offer international athletes the best opportunities back in their home country after their college career is complete.

This strategy aligns with prior research. Craven (8) suggested the more athletes and coaching staffs are prepared and educated about the cultural differences they may experience while submerged in another culture, the easier their transition and adjustment to the new environment will be. In Bale’s work, several of his subjects suggested the U.S. college experience was not what they thought it would be, as over 30% encountered problems with U.S. coaches, nearly 25% had difficulties adjusting to the climate in their new location, and over 20% lacked motivation with academic work (2). When offered the chance to be a varsity athlete at an NCAA Division I school, many international athletes are initially so excited about the opportunity and chance to travel to the United States that the location and environment of the specific school they attend is not a key factor (15-16). As the results of this study indicate, however, current international athletes believe it is important for international student-athlete prospects to consider many issues beyond just an opportunity to compete in the U.S. college system before making the commitment to attend a U.S. university.

The second key factor in transitioning into life as a student-athlete is the development of a support system first built on teammates and coaches, but also built on family and friends back home. It is important for coaches and teammates to understand that international student-athletes identified developing a support system with them as the most important element of a successful transition. It is clear the relationships developed with the people international athletes spend the most time with are a key determinant to a successful transition. Coaches should also ensure international athletes have the technical support to maintain relationships with those at home through various video, chat, and online communication resources.

Another key finding in this study was that most of the respondents would not have moved to the U.S. or continued to participate in sports without the opportunities presented through American intercollegiate sport. One of the attractions of U.S. college sport is access to high quality facilities and abundant opportunities. Results indicated that the respondents felt the athletic facilities and athletic opportunities available to them as an NCAA Division I athlete were superior to their options in their native country. This finding could potentially be skewed as young athletes who did have access to better facilities and opportunities in their homeland may not have considered playing in the U.S. college system. However, this finding has key implications for sport managers outside of the U.S. Administrators of sport clubs in non-U.S. countries may lose elite athletes at the peak of their career as those athletes choose to accept an NCAA scholarship. If such club administrators hope to retain these athletes, they may need to examine the attraction of competing in the U.S. collegiate sport system (namely competitive opportunities and facilities) and attempt to replicate those factors in their native country. More research examining this specific issue is needed.

Finally, one surprising finding from this study is only a quarter of respondents indicated university athletic department staff, such as coaches and administrators, were the key source of information regarding the opportunity to compete in the United States college system. As illustrated in the introduction to this paper, recruiting is arguably the most important element in developing an elite college athletic program and many university athletic departments dedicate a relatively large percentage of their resources towards this endeavor. Yet the recruiting process does not seem to be overly efficient in reaching international prospects. Many of the respondents in this study indicated family, friends, and acquaintances that had competed in the U.S. college system were more important sources of information about playing opportunities at NCAA schools than were the coaches whose job it is to recruit these athletes. This study illustrates the need for coaches to more effectively and efficiently recruit the international landscape.

### Conclusions

American college sports provide an opportunity for athletes from countries outside the U.S. to continue their playing careers and educational training in the United States where high-level athletic facilities and strong competitive opportunities abound. International student-athletes must overcome many challenges and obstacles upon arrival on campus, including homesickness, adapting to the culture, and learning the language. Coaches and teammates play an important role in helping international athletes develop a support system that will assist in the successful transition to a student-athlete. Athletic administrators also play a key role, as discussed in the next section.

### Applications In Sport

Once international athletes are on campus, a member of the athletic department staff should oversee the athlete’s transition into college life, focused on combating the top three challenges identified in this research: homesickness, adjustment to U.S. culture, and language. This staff member should serve as a liaison between athletic department personnel (i.e. CHAMPS Life Skills coordinators, compliance, eligibility, coaches) and other campus resources (i.e. academic advising, international office) to facilitate a smooth transition. The liaison can coordinate paperwork deadlines, information updates, cultural sensitivity training in the athletic department, and any programming that might benefit the international athletes. Such programming could include a peer mentoring program, utilizing transition to college coursework, placing international athletes with experts in teaching the English language, offering open forums for athletes to socialize with athletes from other teams, developing information packets with multicultural resources in the community and university, and establishing relationships with host families in the community (under the supervision of the compliance office). Acquainting athletes with American college life should begin as soon as possible, either on an official visit or having international athletes arrive on campus as early as possible to adjust to the language, culture, food, teammates, and academic expectations. Finally, developing a strong relationship with the international office is important in order to ensure all government paperwork is completely in an accurate and timely fashion.

Finally, in contrast to domestic athletes who take official and unofficial visits and have many other opportunities to develop relationships with coaches who are recruiting them, international athletes rely on their personal support system (i.e. club coaches, former athletes, family, friends) to gather information on U.S. colleges. NCAA coaches must continue to improve their international recruiting connections with former athletes and club coaches because they are still the top source of information about competing in the U.S. college system. If NCAA coaches want to successfully recruit international athletes, they should focus on improving recruiting connections with key members of an athlete’s personal support system. Previous research by Bale (2-4) has established some institutions are able to develop talent pipelines where information about an institution is disseminated by athletes who competed for a particular school in the past.

### References

1. Adler, P. (1975). The transitional experience: An alternative view of culture shock. The Journal of Humanistic Psychology, 15, 13-23.
2. Bale, J. (1987). Alien student-athletes in American higher education: Locational decision making and sojourn abroad. Physical Education Review, 10(2), 81-93.
3. Bale, J. (1991). The brawn drain: Foreign student-athletes in American universities. Urbana, IL: University of Illinois Press.
4. Bale, J. (2003). Sports geography (2nd ed.). London: Routledge.
5. Berkowitz, K. (2006). From around the world. Athletic Management, 18(6). Available online at <http://www.athleticmanagement.com/2007/01/15/from_around_the_world/index.php>
6. Brown, G.T. (2004, Dec. 6). Foreign matter: Influx of internationals in college swimming tugs on bond between campus and country. The NCAA News, p. 5.
7. Chapdelaine, R., & Alextich, L. (2004). Social skills difficulty: Model of culture shock for international graduate students. Journal of College Student Development, 45, 167-184.
8. Craven, J. (1994). Cross-cultural impacts of effectiveness in sport. In R.C. Wilcox (Ed.) Sport in the global village, (pp. 433-448). Morgantown, WV: Fitness Information Technology, Inc.
9. Drape, J. (2006, Apr. 11). Foreign pros in college tennis: On top and under scrutiny. The New York Times, p. D1.
10. Furnham, A., & Bochner, S. (1986). Culture shock: Psychological reactions to unfamiliar environments. London: Methuen.
11. NCAA. (2010). 1999-00 – 2009-10 NCAA student-athlete race and ethnicity report. Available online at <http://www.ncaapublications.com/productdownloads/SAEREP11.pdf>
12. Oberg, K. (1960). Cultural shock: Adjustment to new cultural environments. Practical Anthropology, 7, 177-182.
13. Pierce, D., Kaburakis, A., & Fielding, L. (2010). The new amateurs: The National Collegiate Athletic Association’s application of amateurism in a global sports arena. International Journal of Sport Management, 11(2), 304-327.
14. Popp. (2006, September). International student-athlete adjustment to U.S. universities: Testing the Ridinger and Pastore model. Paper presented at the annual meeting of the European Association for Sport Management, Nicosia, Cyprus.
15. Popp, N., Love, A., Kim, S, & Hums, M.A. (2010). International student-athlete adjustment: Examining the antecedent factors of the Ridinger and Pastore theoretical framework model. Journal of Intercollegiate Sport, 3, 163-181.
16. Popp, N., Pierce, D., & Hums, M.A. (in press). A comparison of the college selection process for international and domestic student athletes at NCAA division I universities. Sport Management Review.
17. Ridinger, L. & Pastore, D. (2000). A proposed framework to identify factors associated with international student-athlete adjustment to college. International Journal of Sport Management, 1(1), 4-24.
18. Riffe, D., Lacy, S., & Fico, F. G. (2005). Analyzing media messages: Using quantitative content analysis in research. Mahwah, NJ: Lawrence Erlbaum.
19. Weston, M. A. (2006). Internationalization in college sports: Issues in recruiting, amateurism, and scope, 42 Williamette Law Review 829.
20. Westwood, M., & Barker, M. (1990). Academic achievement and social adaptation among international students: A comparison groups study of the peer-pairing program. International Journal of Intercultural relations, 14, 251-263.
21. Wilson, R. (2008). A Texas team loads up on All-American talent, with no Americans. Chronicle of Higher Education, 54(18), p. A30-A31.
22. Wilson, R., & Wolverton, B. (2008). The new face of college sports. Chronicle of Higher Education, 54(18), p. A27-A29.
23. Wimmer, R., & Dominick, J. (2006). Mass media research: An introduction. Belmont, CA: Thomson Wadsworth.

### Tables

#### Table 1
Most Difficult Aspects of International University Experience

Response Frequency Percent
Homesickness 67 24.1
Adjustment to U.S. culture 57 20.5
Language adjustment 41 14.7
Adjustment to being an athlete 23 8.3
Other 21 7.6
Time management 19 6.8
Academic transition 18 6.5
Financial insecurity or finding a job 15 5.4
Paperwork 12 4.3
Finding transportation 5 1.8
Total 267

Note: Respondents could have multiple answers in their written response

Intercoder Agreement: Scott’s Pi = .89

#### Table 2
Important Factors for Successful Transition to University Life

Response Frequency Percent
Strong support system from teammates and coaches 91 34.1
Strong support system from friends and family back home 54 20.2
Possess of key personality traits (experience, desire, patience, etc.) 49 18.4
Strong support system from academic advisors, tutors, professors, and administrators 25 9.4
Adapting to U.S. culture and the English language 20 7.5
Other 15 5.6
Time management and organization 13 4.9
Total 267

Note: Respondents could have multiple answers in their written response

Intercoder Agreement: Scott’s Pi = .82

#### Table 3
Source of Information Regarding Athletic Opportunity in the United States

Response Frequency Percent
Family, friends, and athletes 45 25
Individuals who had participated in U.S. athletics previously 44 24.4
Coaches and recruiters involved in U.S. college sports 43 23.9
In native country from high school coach or administrator 29 16.1
Personal research 10 5.6
Other 5 2.8
Sport recruitment service 4 2.2
Total 180

Intercoder Agreement: Scott’s Pi = .87

#### Table 4
Life without American College Sports

Working Attending College Playing Sports Total
Native Country 14 105 33 152
Not Specified 9 15 13 37
U.S. 0 7 0 7
Total 23 127 46 196

Intercoder Agreement: Scott’s Pi = .85

### Corresponding Author

Dr. David Pierce
Ball State University
School of Physical Education, Sport, and Exercise Science
Muncie, IN 47306
765-285-2275
<dapierce@bsu.edu>

2013-11-22T22:56:03-06:00January 4th, 2012|Contemporary Sports Issues, Sports Coaching, Sports Facilities, Sports Management, Sports Studies and Sports Psychology|Comments Off on Qualitative Analysis of International Student-Athlete Perspectives on Recruitment and Transitioning into American College Sport
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NCAA Division I Athletics: Amateurism and Exploitation

Anthony W. Miller

### Abstract

In recent days, there has been increased dialogue concerning the topic of compensating college athletes above athletic scholarships. The purpose of this paper was to discuss the NCAA and its member institutions’ exploitation of student-athletes. Amateurism and exploitation were defined and discussed in relation to NCAA Division I athletics. The evolution of intercollegiate athletics and the student-athlete was reviewed in order to better understand the motives for today’s exploitive practices. Using Wertheimer’s two arguments for the exploitation of student-athletes, it was demonstrated some student-athletes are victims of exploitation. However, after examining mutually advantageous exploitation and consensual exploitation, it was determined not all student-athletes are exploited. The NCAA and those responsible for setting student-athlete policy should discuss the implications of these conclusions.

**Key words:** college athletics, NCAA, amateurism, exploitation, student-athletes, athletic scholarships

### Introduction

Last winter, National Collegiate Athletic Association (NCAA) president Mark Emmert was asked by a group of sports media members about the possibility of paying college athletes. Emmert responded, “We can never move to a place where we are paying players to play sports for us” (Garcia, 2010, para. 9). “No, it will not happen – not while I’m president of the NCAA,” he later stated (“NCAA president,” 2011, para. 17). These comments sparked the reoccurring ethical discussion concerning the topic of amateurism and exploitation in college athletics. While many believe as amateurs, college athletes are receiving more than their fair share through athletic scholarships, others argue universities are exploiting their own student-athletes. The questions remain unanswered. Should college athletes be compensated beyond their athletic scholarships, and specifically, are the NCAA and its institutions exploiting student-athletes?

The questions involved in this discussion are unable to be answered with a simple “yes” or “no.” In order to knowledgeably discuss the subject, there first needs to be a foundational understanding of the basic terms of amateurism and exploitation. In addition, the relationship between the two terms and intercollegiate athletics should be clearly defined. A history of the evolution of college sports and the role of student-athletes over the last two centuries must be examined also. The author will attempt to use all of this information to answer several key questions related to the topic of paying college athletes in order to determine if student-athletes are being exploited and, if exploited should they be compensated above their athletic scholarships?

Surprisingly, studies have not demonstrated an overwhelming support for paying student-athletes above their athletic scholarships. Schneider (2001) investigated college students’ perceptions of giving compensation to intercollegiate athletes in addition to the standard grant-in-aids. Of the 458 students (275 males and 183 females from 1 Division 1 athletic conference) surveyed, only a slight majority (54%) of the students believed athletes should receive additional compensation. Nevertheless, it is a subject that has again (even recently) become a hot topic in college athletics.

#### Amateurism and Exploitation in Collegiate Athletics

When it comes to debating whether or not college athletes should be paid, the two most often used terms are amateurism and exploitation. Neither term is new to intercollegiate athletics. Actually, both subjects have been topics of discussion for the NCAA since its inception in the early 1900s (“History,” 2010). Today, these two words drive both sides’ arguments concerning paying and exploiting student-athletes.

##### Amateurism Defined

Simply put, collegiate amateurism refers to the fact the athletes do not receive remuneration for their athletic services. College athletes today are referred to as student-athletes. The governing body of college athletics, the NCAA, views these individuals as students, not as professionals or employees of their member schools. Thus, student-athletes are not currently monetarily compensated (Murphy & Pace, 1994). According to the NCAA, student-athletes’ participation in athletics is just another part of their entire education, not the primary purpose for attending college (Meggyesy, 2000).

Late in the 19th century, college authorities conceived this idea of amateurism in an effort to maintain schools’ educational integrity and middle- and upper- class standing by not technically paying athletes (Flowers, 2009). “A Gentleman never competes for money,” once wrote author Walter Camp (Flowers, 2009, p. 354). As sports’ popularity and revenues increased over the next several years, athletes were given incentives such as free room, board, and tuition. In the middle of the 1900s, the NCAA instituted its key piece of legislation, the Sanity Code, in an attempt to preserve amateur sports while still allowing schools to compensate athletes (Kahn, 2007). By including room, board, and tuition in grant-in-aids (i.e. athletic scholarships), schools were able to reward student-athletes without paying them directly. After the Sanity Code’s establishment of athletic scholarships, the term “amateurism,” not “professionalism,” would be united officially with college athletics (Byers, 1997; Flowers, 2009).

In addition to assigning a fixed amount to athletic scholarships, there are additional ways the NCAA continues to preserve the “amateur” label in collegiate sports. Although the NCAA and the schools reserve the right to use a player’s images and names for commercial purposes, no athlete may be endorsed by or receive any payment from businesses or corporations (Suggs, 2009; Murphy & Pace, 1994). Student-athletes also may not receive financial assistant in addition to their grant-in-aids or be paid for any work with private sports camps related to their sport (Byers, 1997).

##### Exploitation Defined

The biggest issue in the subject of paying college athletes is the idea the NCAA and its member institutions are exploiting student-athletes. Throughout the years, exploitation has been defined countless ways by individuals discussing various topics such as economic, politics, and sports (Wertheimer, 2008). For the discussion involving college athletics, exploitation should be defined as an individual gaining something by taking an unfair advantage of another individual (Wertheimer, 2007).

There are generally two arguments used to demonstrate the exploitation of student-athletes. The first is student-athletes, many of whom are making large amounts of money for their schools, often are not receiving any kind of legitimate, quality education. The second is compensation student-athletes receive in the form of athletic scholarships is not comparable to the marginal revenue products they individually generate for colleges (Wertheimer, 2007; Brown & Jewell, 2004).

Before examining further these two claims, some distinctions must be made. Wertheimer (2008) maintains there are several specific types of exploitation that apply to this discussion. The first, called mutually advantageous exploitation, refers to a situation where both parties, both the one doing the exploiting and the one being exploited, gain from the agreement. The second is referred to as consensual exploitation and involves an instance where individuals who are exploited have given voluntarily consent to the situation prior to the transaction. In situations involving these types of exploitation, it can be argued nothing morally wrong has occurred.

In most circumstances involving exploitation, the issue is not whether exploited individuals are making any gains but rather they are not receiving what they ought to receive. In other words, those being exploited are not getting what is considered fair (Wertheimer, 2008). In the example of the exploitation of student-athletes, the specific issue is “they do not receive an appropriate return on the financial surplus” they create for their universities (Wertheimer, 2007, p. 366).

#### The Evolution of Intercollegiate Sports and the Student-Athlete

The face of intercollegiate athletics has changed drastically in the last two centuries. What started as nothing more than student-organized competitions has turned into what has been described as a “sports entertainment enterprise” (Flowers, 2009; Meggyesy, 2000, p. 25). Students who once went to school only for an education and participated in these kinds of competitions in their free time now often attend these same universities solely for the purpose of participating in sports. In most situations, they end up devoting hundreds of hours to sports-related activities and end up becoming athletes first and students second. The end result is a system that uses students to generate millions of dollars for both the NCAA and its universities.

##### The Origins of Intercollegiate Athletics and the Student-Athlete

Modern intercollegiate athletics have their foundations in intra-collegiate competitions. Sports were largely an unknown on most college campuses until the early 1800s when college students began organizing their own class (e.g. freshman, sophomore, etc.) teams to compete against other classes. The popularity of these different competitions grew over the next 50 years to the point that by the 1850s, universities were forming their own intercollegiate teams. At first, school authorities frowned upon these seemingly frivolous and sometimes violent competitions. But by the late 19th century, American colleges recognized the prestige that came from winning intercollegiate contests and the visibility sports teams provided for the school were too valuable to ignore. As the popularity of intercollegiate sports grew, schools realized they could manufacture additional income by charging spectators admission to events. Prestige, visibility, and money – intercollegiate athletics would now be a permanent fixture on college campuses (Flowers, 2009).

The next conclusion drawn by colleges was obvious, and it shaped intercollegiate athletics into what they are today. How can a school garner more prestige, visibility, and money? Win more games. How can a team win more games? Get the best players. So in an effort to field the best teams, schools began accepting students who never would have been admitted previously to these institutions. In order to lure athletes, colleges started in the 1870s to offer both graduates and undergraduates financial assistance in the form of room and board, jobs, and even small cash considerations in exchange for their athletic services (Flowers, 2009). In response to the “dangerous and exploitive athletics practices of the time,” college authorities joined together in 1906 to form the Intercollegiate Athletic Association of the United States, which would later change its name to the NCAA (“History,” 2010, para. 1). In actuality, this new organization was intended to officially legitimize athletics in higher education and control athlete admission to and distribution amongst colleges (thus hopefully eliminating some of the questionable practices of several schools) (Flowers, 2009; Kahn, 2007).

With sports’ popularity growing and athletic revenues increasing, by the 1940s several schools were unashamedly paying their athletes (Kahn, 2007). Realizing amateur intercollegiate athletics were turning into professional athletics, the NCAA modified its constitution in 1956 to allow schools to offer grant-in-aid to any undergraduate athlete. In addition, the NCAA coined the term “student-athlete” (instead of “employee”) to describe those receiving athletic scholarships (Byers, 1997). The amateur code was officially established, and the student-athlete was born.

##### Modern Intercollegiate Sports and Student-Athletes

The current NCAA Division I intercollegiate sports program has evolved into a multi-billion dollar industry where many of the schools’ annual revenues reach above $260 million (Meggyesy, 2000). In addition to fielding teams in the money-making sports of men’s basketball, football, and ice hockey, schools also run programs for sports such as baseball, lacrosse, softball, soccer, swimming, volleyball, and wrestling (Kahn, 2007). Because these programs are not self-supported, they rely on revenues from the men’s basketball and football programs and often some additional state funding (Suggs, 2009). It is not uncommon for the coaches of Division I teams to earn several hundred thousand to several million dollars every year (Wieberg, 2011).

Researchers and economists who have studied intercollegiate athletics have described today’s NCAA as a cartel (Deschriver & Stotlar, 1996; Zimbalist, 2001). A cartel is defined as a joint group of members who create policies in order to promote the mutual interests of the members (Kahn, 2007). Koch (1983) argued the NCAA’s cartel behavior is manifested when it regulates the means of acquiring athletes, puts a fixed value on the amount given to student-athletes, controls the rights to televising athletic events, periodically distributes its profits to members, and enforces policy on its members. According to the NCAA, all of this is done in an effort to create equal opportunity for monetary profit, athlete distribution, and athletic success (Kahn, 2007; Koch, 1983).

The NCAA itself, a non-profit educational organization with 270 employees, has an annual budget of $32 million (Meggyesy, 2000). Each year, it distributes over $500 million to its member schools (Suggs, 2009). Nearly all of the money is collected from revenue generated by men’s basketball and football, specifically the television rights to men’s college basketball’s March Madness and football’s Bowl Championship Series. Just this past year, the NCAA signed a 14-year, $10.8 billion contract with CBS and Turner Sports to have the exclusive rights to show the men’s college basketball tournament (Wieberg, 2011).

History has demonstrated today’s universities recruit student-athletes for the purpose of helping sports teams achieve success on the playing field and thereby increase the school’s prestige and overall revenue. Using financial records from NCAA Division I-A universities as well as NFL and NBA draft data from 1995-1998, Brown and Jewell (2004) estimated a draft-quality college football player earns $406,000 in revenue annually for his school, while a college basketball player earns $1.194 million. Schools today treat student-athletes as more than just typical students (Suggs, 2009). They are given academic assistance, game tickets, clothing and equipment, medical treatment, weight and conditioning training, and money towards room, board, and tuition. A recent analysis by USA TODAY determined the average NCAA Division I men’s basketball player receives at least $120,000 in goods and services each year (Weiner & Berkowitz, 2011). But while these athletes are not living in poverty, the question still remains. Are student-athletes being exploited?

#### Are Today’s Student-Athletes Truly Exploited?

The 2011-2012 NCAA Manual states the mission of the NCAA is to protect student-athletes “from exploitation by professionalism and commercial enterprises” (2011, p. 4). Many would contend the NCAA itself is responsible for exploiting student-athletes. Their proof would hinge on the two previously mentioned arguments that many of these students are receiving neither a legitimate education nor fair compensation for their athletic services (Wertheimer, 2007). In addition to considering Wertheimer’s two arguments, the terms mutually advantageous exploitation and consensual exploitation also factor into this discussion.

##### Wertheimer’s First Argument

Universities’ educational practices are quickly called into question when college players make comments similar to the one made by University of Connecticut men’s basketball’s Kemba Walker. While being questioned this past March about his schooling, the junior basketball star said, “[Forty Million Dollar Slaves: The Rise, Fall, and Redemption of the Black Athlete] is the first book I’ve ever read” (Layden, 2011, para. 26). Often, there are times when athletes are put into either easier courses or courses whose professors are known to like student-athletes so athletes are able to achieve and receive higher grades (Zimbalist, 2001). In these situations, the argument is student-athletes (B) are being exploited by schools (A) because A is profiting thousands, sometimes millions, from B’s efforts while B is receiving nothing of lasting significance (i.e. a quality education) (Wertheimer, 2007).

In response to this argument, the question is whether student-athletes are forced into these positions. It should be determined if student-athletes are required to attend educational institutions with weak or questionable academics. The best schools are not available to everyone. Some athletes are only recruited by schools with poor academic records. Although players are not forced to attend one of those schools, some are financially unable to attend college without the help of an athletic scholarship. A student-athlete under such circumstances would be considered a victim of exploitation. As for an athlete who has his choice of the best schools and still selects a poor academic institution, it has been argued that although he was not coerced into attending a particular school, a teenager should not be expected to choose a school based on whether or not that school will provide him with quality educational opportunities. In this situation, a case for exploitation could also be made (Wertheimer, 2007).

It also must be determined if student-athletes are forced into classes or majors which result in them not receiving a quality education. Of course there are always the “low-ability” level students who struggle academically and really have little chance of ever receiving a college education (Wertheimer, 2007, p.369). However, there are situations where some students do not achieve academic success or graduate simply because they fail to give enough effort in their academics. In these specific examples, an argument for the exploitation of the low-ability student-athletes could be made, but it would be harder for this same argument to apply to student-athletes who do not make an effort academically.

##### Wertheimer’s Second Argument

The second exploitation argument is universities (A) are exploiting student-athletes (B) due to the fact B is not receiving fair compensation in relation to B’s generated surplus. This argument is harder to make because of the difficulty in determining the surpluses of NCAA Division I schools. According to NCAA president Mark Emmert, only 14 out of over 1,150 schools finished the 2009-2010 school year with a financial surplus (Garcia, 2010). But any surplus generated by colleges’ football and basketball programs are used to pay for coaching salaries, academic counselor salaries, and athletic facility renovations. In most circumstances, a portion of the money subsidizes schools’ other intercollegiate sports programs (Wertheimer, 2007; Suggs, 2009). Subsequently, very few schools show a surplus in the end.

In addition to the difficulty in determining universities’ financial surpluses, it is equally difficult determining nonfinancial surpluses. Dating back to the beginnings of intercollegiate athletics, the primary purpose for having these types of sports programs was the prestige and visibility they provided for colleges. Today’s winning sports teams are given hundreds of hours of media attention and television coverage. It is impossible to put a monetary value on the advertisement which each intercollegiate team or each student-athlete is creating for colleges (Wertheimer, 2007).

The answer to this question lies in determining what fair compensation is. At first glance, a $10-40,000 a year education in return for generating $400,000-$1.2 million seems anything but fair (Zimbalist, 2001; Brown & Jewell, 2004). But a teenager with no prior professional experience who receives the equivalent of $120,000 a year is uncommon in other professions. When asked about fair compensation for college athletes, Butler University men’s basketball player Matt Howard replied, “Forty thousand dollars-plus a year to play, that’s a pretty good salary for an 18-year-old who has no college education” (Weiner & Berkowitz, 2011, para. 6).

Determining what is fair becomes even more difficult when considering other situations. First, if athletes are exploited only when they do not receive fair compensation for the surplus they themselves create, then this means only a portion of a school’s student-athletes (in most cases, only football and basketball players) are being exploited and should receive compensation. Is it fair for the volleyball, baseball, and soccer players not to be paid while their fellow schoolmates, the male football and basketball players, are paid? After all, athletes in nonsurplus sports put in the same amount of time and effort into competing for their schools as do athletes in surplus sports. It is no fault of the athletes whose programs are not as popular in American culture as other programs (Wertheimer, 2007). Murphy and Pace (1994) replied to this particular argument with an example from the professional world. In business, do all members of a company’s team receive the same compensation? Is a secretary who works the same number of hours and works just as hard as the boss paid a similar wage? Of course, the answer is no.

Second, if colleges were to pay athletes, any surplus created by those programs would be used to compensate the athletes. Consequentially, many of the non-revenue generating programs would not have adequate funding to continue. Is it fair to those athletes to deprive them of an opportunity to compete collegiately and, for those who would be unable to financially afford school, an opportunity for a college education? On the other hand, requiring universities to use revenues to pay athletes may force schools to cut down some of the exorbitant salaries paid to some Division I coaches and other athletic department employees.

##### A Case for Mutually Advantageous and Consensual Exploitation

In this discussion concerning the exploitation of student-athletes, a case can be made for both mutually advantageous exploitation and consensual exploitation. Mutually advantageous exploitation occurs when A gains from B and B gains from A, leaving both parties in a better position than before the transaction (Wertheimer, 2008). Take, for example, a star high school basketball player from a low-income family who is recruited and signed by a renowned academic institution. He competes four years for that school. Along the way, he helps his team win over 100 games, reach 2 Final Fours, and win a national championship. After 4 years of education (worth a total of approximately $160,000) and instruction from one of the best coaches in the nation, he graduates with a college degree, is named as a NCAA All-American, and one month later is selected in the NBA Draft. Over the next 7 years, the former student-athlete signs 3 NBA contracts worth over $28 million, thanks in large part to the coaching he received while in college. In this example, both parties made gains which left them better off. It could be argued, therefore, no wrongful exploitation took place.

In other examples, athletes have been known to become student-athletes for the sole purpose of receiving expert instruction, media exposure, and training. As a result of those benefits, their future earning power increased (Kahn, 2007). Many of these elite athletes stay in college for only the required amount of time and then leave to become professionals. Again in such situations, both the athletes and the schools have entered into agreements which benefit both groups. Nothing morally wrong has occurred.

When an individual volunteers or gives informed consent to a transaction, it is referred to as consensual exploitation (Wertheimer, 2008). Prior to the start of a student-athlete’s collegiate career, the individual must agree to sign several eligibility forms. One of those forms is the NCAA Student-Athlete Form 10-3a (2010) that reads, “You affirm that you meet the NCAA regulations for student-athletes regarding eligibility, recruitment, financial aid, amateur status and involvement in gambling activities” (p. 2). A separate read and sign section of the same document states:

> You authorize the NCAA [or a third party acting on behalf of the NCAA (e.g., host institution, conference, local organizing committee)] to use your name or picture in accordance with Bylaw 12.5 including to promote NCAA championships or other NCAA events, activities or programs. (p. 4)

The NCAA is not attempting to deceive individuals by having student-athletes sign confusing forms so then the schools can make money off the athletes. Instead, they are presenting a clear, understandable agreement that essentially says, “In order to participate in intercollegiate athletics, you must abide by these terms.” Players must sign the agreement to become student-athletes, but no athlete is forced to sign the NCAA Student-Athlete Form.

There is a common perception athletes are required to attend college in order to become eligible for the professional ranks. This is not the case. The current NBA Draft eligibility rules state a player must be 19 years of age, and 1 year must have elapsed since the player’s graduation from high school (“Article X,” 2009). In the NFL, a player must be out of school for three years before he is eligible for the draft (“NFL Collective Bargaining Agreement,” 2006). In baseball, Major League Baseball teams can draft any player who has graduated from high school, while anyone in hockey who is 19 or older is eligible for the NHL Draft (“First-year Player,” n.d.; “Hockey Operations,” n.d.). Neither athletes of surplus sports nor those participating in nonsurplus sports are required to attend college in order to be drafted into professional sports. In most circumstances, the visibility which comes from playing for prominent sports programs causes most athletes to choose to attend college.

### Conclusions

Even after knowing all the facts, the questions related to paying college athletes and the exploitation of student-athletes are difficult to answer. However, there is no doubt the current model for compensating college athletes is ethically questionable at best. If this were not the case, then President Emmert would not continue to make statements suggesting the necessity of exploring ways to increase the financial assistance given to student-athletes (Wieberg, 2011). Just last week, several NCAA conference commissioners began discussing ways to compensate their athletes above athletic scholarships. Conference USA commissioner Britton Banowsky said, “Unless the student-athletes in the revenue-producing sports get more of the pie, the model will eventually break down… [I]t is only a matter of time” (Schad, 2011, para. 3). When the current model does break down, the NCAA’s members will be forced to consider the topic of student-athletes’ exploitation prior to establishing a new model.
Going forward, the NCAA and its member institutions must address several ethical situations in order to avoid the continued exploitation of student-athletes. The first step is re-defining amateurism in college athletics. Currently, intercollegiate sports are amateur in name only (a practice continued today by colleges in an effort to avoid providing workers’ compensation and to continue eligibility for tax exemption status) (Haden, 2001; Murphy & Pace, 1994). The second step is deciding whom to pay. If it is determined only scholarship athletes in revenue-producing programs (i.e. basketball, football, and ice hockey) should be compensated, then the NCAA will have to be prepared to justify excluding some athletes, including the non-scholarship basketball, football, and hockey players (Murphy & Pace, 1994). Due to Title IX, which mandates equitable opportunities and benefits for women competitors, there is a possibility schools would be required eventually to extend remuneration to other student-athletes (Francis, 1993). The third step is determining what fair compensation is for student-athletes, a difficult task based on the information mentioned previously. The final step is choosing where to get the money to pay athletes.
Deciding where to get additional money opens the door to a vast array of ethical questions. Should the money made by men’s basketball and football be used to fund other athletic programs? Instead, should the money be used to pay the basketball and football players only? Will Title IX allow for only a portion of a school’s athletes to be paid? Are college coaches overpaid, or are their large paychecks justified by the prestige, visibility, and money they are helping to generate for their schools? If smaller schools are lacking the funds required to pay student-athletes, is it fair to raise regular students’ tuition prices to help cover costs (Schneider, 2001)? These are just a few of the questions which will have to be addressed.
Determining which student-athletes are being exploited is a difficult task. What is clear is both the NCAA’s current amateur rules and the questionable educational practices of some schools make it more likely for students-athletes to be exploited (Murphy & Pace, 1994). Deciding how to compensate student-athletes more fairly could potentially result in completely restructuring intercollegiate athletics. If the NCAA and its member schools truly desires to protect their student-athletes “from exploitation by professional and commercial enterprises,” then they will be forced to reexamine their own practices (2010-2011 NCAA Manual, 2010, p. 4).

### Applications In Sport

The topic of paying college athletes is one of, if not the most debated issues in collegiate athletics. Understanding the terms of amateurism and exploitation, a history of intercollegiate athletics, and how student-athletes are possibly being exploited may assist in helping to decide if NCAA student-athletes should be compensated above athletic scholarships.

### References

1. 2011-2012 NCAA Manual. (2011). Retrieved from <http://www.ncaapublications.com/productdownloads/D112.pdf>
2. Article X: Player eligibility and NBA Draft. (2009). Retrieved from <http://www.nbpa.org/sites/default/files/ARTICLE%20X.pdf>
3. Brown, R. W., & Jewell, T. (2004). Measuring marginal revenue product in college athletics: Updated estimates. In J. Fizel & R. Fort (Eds.), Economics of college sports (pp. 153-162). Westport, CT: Praeger.
4. Byers, W. (1997). Unsportsmanlike conduct: Exploiting college athletes. Ann Arbor, MI: University of Michigan Press.
5. Deschriver, T. D., & Stotlar, D. K. (1996). An economic analysis of cartel behavior within the NCAA. Journal of Sport Management, 10(4), 388-400.
6. First-year player draft rules. (n.d.). Retrieved from <http://mlb.mlb.com/mlb/draftday/rules.jsp>
7. Flowers, R. D. (2009). Institutionalized hypocrisy: The myth of intercollegiate athletics. American Educational History Journal, 36(2), 343-360.
8. Francis, L. P. (1993). Title IX: Equality for women’s sports?. Journal of the Philosophy of Sport, 20/21(1), 32-47.
9. Garcia, M. (2010, December 15). NCAA president: We can never get to place where athletes are paid. USA Today. Retrieved from <http://www.usatoday.com/sports/college/2010-12-15-mark-emmert-ncaa-pay_N.htm?csp=ip>
10. Haden, C. W. (2001). Foul! The exploitation of the student-athlete: Student-athletes deserve compensation for their play in the college athletic arena. Journal of Law and Education, 30(4), 673-681.
11. History. (2010). Retrieved from <http://www.ncaa.org/wps/wcm/connect/public/NCAA/About+the+NCAA/Who+We+Are/About+the+NCAA+history>
12. Hockey operations guidelines. (n.d.) Retrieved from <http://www.nhl.com/ice/page.htm?id=26377>
13. Kahn, L. (2007). Markets: Cartel behavior and amateurism in college sports. Journal of Economic Perspectives, 21(1), 209-226. doi:10.1257/jep.21.1.209
14. Koch, J. V. (1983). Intercollegiate athletics: An economic explanation. Social Science Quarterly (University of Texas Press), 64(2), 360-374.
15. Layden, T. (2011, April 11). UConn’s drive to survive. Sports Illustrated. Retrieved from <http://sportsillustrated.cnn.com/vault/article/magazine/MAG1184204/index.htm>
16. Meggyesy, D. (2000). Athletes in big-time college sport. Society, 37(3), 24-28.
17. Murphy, S., & Pace, J. (1994). A plan for compensating student-athletes. Brigham Young University Education & Law Journal, (1), 167-186.
18. NCAA president: Pay-for-play won’t happen under his watch. (2011). USA Today. Retrieved from <http://www.usatoday.com/sports/college/2011-02-13-ncaa-emmert_N.htm>
19. NCAA Student-Athlete Form 10-3a. (2010). Retrieved from <http://fs.ncaa.org/Docs/AMA/compliance_forms/DI/DI%20Form%20XX-3a.pdf>
20. NFL Collective Bargaining Agreement 2006. (2006). Retrieved from <http://images.nflplayers.com/mediaResources/files/PDFs/General/NFL%20COLLECTIVE%20BARGAINING%20AGREEMENT%202006%20-%202012.pdf>
21. Schad, J. (2011, May 19). Power brokers discuss paying NCAA athletes. ESPN. Retrieved from <http://sports.espn.go.com/ncaa/news/story?id=6566975>
22. Schneider, R. G. (2001). College students’ perceptions on the payment of intercollegiate student-athletes. College Student Journal, 35(2), 232-241.
23. Suggs, W. (2009). Old challenges and new opportunities for studying the financial aspects of intercollegiate athletics. New Directions for Higher Education, (148), 11-22. doi:10.1002/he.364
24. Wieberg, S. (2011, March 30). NCAA president: Time to discuss players getting sliver of revenue pie. USA Today. Retrieved from <http://www.usatoday.com/sports/college/mensbasketball/2011-03-29-ncaa-pay-for-play-final-four_N.htm?sms_ss=gmail&at_xt=4d93d876081f62dd,0%22#>
25. Wertheimer, A. (2007). The exploitation of student athletes. In W. J. Morgan (Ed.), Ethics in sport (pp. 365-377). Champaign, IL: Human Kinetics.
26. Wertheimer, A. (2008). Exploitation. In E. N. Zalta (Ed.), The Stanford Encyclopedia of Philosophy. Retrieved from <http://plato.stanford.edu/entries/exploitation/>
27. Weiner, J., & Berkowitz, S. (2011, March 30). USA Today analysis finds $120k value in men’s basketball scholarship. USA Today. Retrieved from <http://www.usatoday.com/sports/college/mensbasketball/2011-03-29-scholarship-worth-final-four_N.htm>
28. Zimbalist, A. S. (2001). Unpaid professionals: Commercialism and conflict in big-time college sports. Princeton, NJ: Princeton University Press.

### Corresponding Author

Anthony W. Miller, MEd
4 Amity Lane
Greenville, SC 29609
<awmiller@students.ussa.edu>
864-906-2548

Anthony W. Miller is a doctoral candidate at the United States Sports Academy. He is also a faculty member of Bob Jones University.

2016-04-01T09:31:59-05:00January 3rd, 2012|Contemporary Sports Issues, Sports Facilities, Sports Management|Comments Off on NCAA Division I Athletics: Amateurism and Exploitation
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The Effects of Conference Realignment on National Success and Competitive Balance: The Case of Conference USA Men’s Basketball

Martin M. Perline, G. Clayton Stoldt, Mark C. Vermillion

### Abstract

Collegiate athletic conferences serve multiple functions, including providing regular opportunities for members to compete in a relatively equitable environment and contributing to the financial well being of member institutions. Many conferences have undergone realignment in recent years, and the effects of those changes may impact the degree to which conferences realize those desired outcomes. The purpose of this paper is to assess how the churning of various institutions (i.e., changes in conference membership as institutions leave or are added) within Conference USA over a 10-year period affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. Both national success and competitive balance within the conference can significantly impact the financial well-being of the conference. Results of the study indicate decreases in both the competitive success of the men’s basketball programs at the national level and the in-conference competitive balance between the 2000-2001 through 2004-2005 and the 2005-2006 through 2009-1010 time periods.

**Key Words:** college athletics, competitive balance, conference realignment, basketball, conference USA

### Introduction

While amateur athletic conferences serve many functions for the individual member institutions, one important purpose is to attempt to enhance the financial status of their members. Although there are numerous ways this can be achieved, two important ways include (1) an attempt to accumulate a group of conference teams that are successful nationally against teams from rival conferences, and (2) an effort to insure teams are somewhat evenly matched within the conference—what is referred to as competitive balance.

Both winning against non-conference opponents and competitive balance are important as they tend to enhance the financial status of conference members. Indeed, “everyone loves a winner,” and is willing to attend games featuring successful teams more often and pay more to attend. Likewise, while people want their teams to win, fans like the games to be exciting and not a foregone conclusion as to the winner (5, 9, 12, 17, and 18).

Almost all major college athletic conferences have experienced changes in their membership within the last six years. These changes—commonly referred to as churning as members come and go—impact conferences in many ways. Competitive success at the national level and in-conference competitive balance are among the desired outcomes commonly impacted.

The purpose of this study was to assess how churning within Conference USA over a 10-year period has affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. The study is important because it assesses the impact of churning on two key but unrelated dimensions. A conference may be well balanced competitively but have negligible success at the national level. Conversely, a conference may be highly unbalanced, but the few teams who win consistently in-conference, may also enjoy considerable success at the national level. This can provide considerable financial rewards for the conference.

Competitive success at the national level and the financial well-being of conference members are inextricably linked because the number of teams a conference places in the NCAA national championship tournament and the number of victories those teams accrue determine the NCAA’s payout to participating conferences. Other studies have examined the effects of churning on competitive balance (see, for example, 13-15, 18) or the relationship between realignment and program revenue (8). This project is the first to combine both considerations, allowing for a more comprehensive assessment of churning outcomes.

### Related Literature

College conferences are comprised of college and universities that have established an association, one of the purposes of which is regular athletic competition (1). In 2011, Staurowsky and Abney (20) stated conferences “establish rules and regulations that support and sustain a level playing field for member institutions, while creating in-season and postseason competitive opportunities” (p. 149). And Rhoads (18) has observed that “(i)t is reasonable that conferences should be quite active in ensuring optimal levels of competitive balance” (p. 5).

Sustained competition among equitable teams is not the sole purpose of athletic conferences, however. Depken (4) observed:

> Sport leagues exist, in part, to insure profitability of their member franchises. Although the NCAA specializes in amateur sports, in which players do not receive direct salaries for their athletic performance, it is readily apparent that the schools that comprise the NCAA are often anxious to earn as much profit as possible from the sports programs (p. 4).

College athletic conferences contribute to their member institutions’ revenue by distributing rights fees from media agreements, corporate sponsorships, licensing and other forms of revenue received by the league (7). One source of revenue for NCAA Division I conferences are distributions from the annual Division I Men’s Basketball Championships. Payouts to conferences are based on financial values linked to units, which are accrued each time a conference member plays a game in the tournament (22). For example, a conference member advancing to the third round (i.e., “Sweet Sixteen”) is valued at three units. Payments to conferences are based on six-year averages of the financial values associated with units accrued (22).

#### Conference Churning

As illustrated in Table 1, 10 of the 11 conferences in the NCAA Division I’s Football Bowl Subdivision (FBS) experienced membership changes between 2005 and 2011. Additional changes at the FBS level are planned for 2012, and Quirk (16) has observed similar instability among non-FBS Division I conferences. Fort and Quirk (6) argued that football is the predominant consideration when institutions change conference affiliations. Competitive imbalance in existing conferences often results in churning because enhanced competitive balance is linked to desirable financial outcomes. Other scholars (5, 9, and 17) support that argument, observing that consumer uncertainty of a game’s outcome is linked to increased demand. Rhoads (18) specifically linked competitive balance with increased ticket sales and enhanced television rights fees.

Little scholarly attention has been devoted to effects of conference churning on competitive success against non-conference opponents. Minimal research has been devoted to evaluating conference realignment in terms of financial outcomes. One exception is Groza (8), who found FBS teams that changed conferences enjoyed an increase in attendance, even controlling for increased quality in competition. Of course, ticket sales (i.e., attendance) is only one of many financial factors that may be impacted by churning. Others include, but are not limited to, BCS and other bowl related revenue, NCAA tournament payouts; media rights fees, athletic donations, and corporate sponsorship fees.

Several studies have been conducted assessing the effects of conference churning on competitive balance within select sport programs. Rhoads (18) examined the Western Athletic and Mountain West conferences and found that membership changes in those conferences had resulted in enhanced competitive balance in football. The changes had no impact on competitive balance in men’s basketball however. Perline and Stoldt (13-14) conducted two studies focusing on competitive balance before and after the Big 8 Conference expanded to become the Big 12. Their first study focused on men’s basketball, for which they concluded that competitive balance within the sport decreased after the conference’s expansion (13).Their second study centered on football, for which they concluded that competitive balance improved after the merger (14). The same scholars also examined competitive balance in women’s basketball before and after the merger between the Gateway Collegiate Athletic Conference and Missouri Valley Conference (15). Multiple methods of assessing of competitive balance produced mixed results, with more measurements indicating more competitive balance after the merger.

#### Conference USA: History and evolution

Conference USA (C-USA) was formed in 1995 during a time of great upheaval in college athletics, which included the dissolution of the Southwest Conference and the formation of the Big XII in 1996 (21). C-USA is a Division I-A league that is divided into two competitive divisions: East and West. In the eastern division members include East Carolina University, Marshall University, the University of Memphis, Southern Mississippi University, University of Alabama- Birmingham, and the University of Central Florida. The western division includes the University of Houston, Rice University, Southern Methodist University, Tulane University, the University of Tulsa, and the University of Texas- El-Paso (2).

Since its inception in 1995, C-USA has endured much change. In the beginning the conference consisted of the University of North Carolina-Charlotte, the University of Cincinnati, DePaul University, the University of Houston (starting competition in 1996), Marquette University, the University of Memphis, Tulane University, St. Louis University, University of Alabama- Birmingham, and the University of Southern Florida. Mike Slive was appointed as the first commissioner, but left to become the commissioner of the Southeastern Conference in 2002 (19), leaving C-USA to appoint Britton Banowsky as its new commissioner. Additionally, in 2002, the C-USA headquarters moved from Chicago to Irving, Texas (2).

The major realignment of C-USA in 2005 was set in motion by larger conference realignment issues. The Atlantic Coast Conference’s (ACC) desire for football prestige triggered a mass reordering of conferences (23). Specifically, the ACC invited the University of Miami (FL), Virginia Polytechnic and State University, and Boston College to join their conference, thereby depleting the Big East Conference. In order to reestablish its conference, the Big East invited C-USA members the University of Cincinnati, DePaul University, Marquette University, the University of Louisville, and the University of South Florida (11). Additionally, four other institutions relinquished their C-USA memberships in 2005. Texas Christian University left to join the Mountain West Conference, the University of North Carolina-Charlotte and St. Louis University left to join the Atlantic 10 Conference, and the U.S. Military Academy (aka Army) became independent [11). Figure 1 lists the various institutions that have been members of C-USA, the dates of their memberships, and their current conference affiliations.

Crytzer (3) noted the unusual current geographical size of C-USA (over 1,500 miles separate the eastern most and western most schools) is a barrier for many of the member schools, which range in student population from 5,000 to 50,000. Additionally, conference defections over the past 15 years helped fuel speculation that future NCAA conference realignments could render C-USA obsolete.

### Methods

The purpose of this paper was to assess how churning within Conference USA over a 10-year period has affected the conference’s men’s basketball programs in regard to success at the national level and competitive balance within the conference. We employed two tactics each in evaluating winning success nationally and competitive balance.

#### Winning Success

In order to measure winning success, we measured the success of Conference USA teams against outside competition before the departure of teams in the 2004-05 season and after the addition of teams in the 2005-06 season. While the conference mean will always be .500, the non-conference mean could vary. We also measured the number of Conference USA teams that participated in the NCAA post-season tournament in both periods. The latter was a major source of revenue to the conference and ultimately to each team. The value of each appearance in the tournament varied from $94,086 in 2001 to $222,206 in 2010 and has continued to grow in magnitude over time. These values were paid annually for six years. Thus one appearance in 2001 would be worth $564,516 to the conference and one appearance in 2010 would be worth $1,333,236 to the conference over the six-year period. It is, therefore, readily apparent that the more appearances a conference makes in the tournament, the more revenue it receives.

#### Measuring Competitive Balance

There were several methods used in measuring competitive balance. The most appropriate of these methods depended on what the researcher was attempting to specifically measure (9). Methods most appropriate for measuring competitive balance within a given season may be different from those used to measure competitive balance between seasons (10). To measure competitive balance within a given year, we rely on the standard deviation of winning percentages and to measure competitive balance between seasons, we use the Hirfindahl-Hirschman Index (HHI).

##### Standard Deviation of Winning Percentages

Possibly the method most often used to measure competitive balance within a conference in a given season is the standard deviation of winning percentages. Since there will, outside of a tie, always be one winner and one loser for each game, the average winning percentage for the conference will always be .500.

In order to gain insight into competitive balance, we would need to measure the dispersion of winning percentages around this average. To do this we can measure the standard deviation. This statistic measures the average distance that observations lie from the mean of the observations in the data set. The formula for the standard deviation is:

![Formula 1](/files/volume-14/441/formula-1.jpg)

The larger the standard deviation, the greater is the dispersion of winning percentages around the mean, and thus the less competitive balance.

#### Championship Imbalance

While using the standard deviation as a measure of competitive balance provides a good picture of the variation within a given season, it does not indicate whether it is the same teams winning every season, or if there is considerable turnover among the winners, i.e., whether there is between season variation. Therefore, another method economists have used to measure imbalance is the Hirfindahl-Hirschman Index (HHI), which was originally used to measure concentration among firms within an industry ([10). We determine the HHI by counting the number of times a team won a championship during a given period, summing those values and then dividing by the number of years in the period considered.

![Formula 2](/files/volume-14/441/formula-2.jpg)

Using this method, the greater the number of teams that achieve championship status over a specific time period, the greater would be the competitive balance.

### Results

#### Winning Success

Table 3 gives the winning percentages for Conference USA teams against non-conference opponents in the two periods under consideration. For the earlier period the mean winning percentage was .606 and for the latter period it was .577—an approximate 5% differential favoring the earlier period. It should be noted that the highest winning percentage over this total period was .638 (2003-04) and the lowest was .539 (2005-06). The data suggest that Conference USA was more successful against outside competition in the earlier period.

Table 4 reflects the number of Conference USA members participating in the NCAA post-season tourney, the unit value of each appearance and the dollars received in each year from conference participation. The data in Table 4 indicates that in the 2001-05 period the conference received $30,722,250, and in the 2006-10 period the conference receipts were only $21,269,388. These numbers reflect a participation of 39 appearances in the earlier period and 19 in the latter period. Consequently, even though the dollars per unit were considerably higher in the latter period, the conference earned almost $10 million more in the earlier period.

#### Competitive Balance

##### Standard Deviation of Winning Percentages

Tables 5 and 6 display the winning percentage for men’s basketball for the years 2000-01 through 2004-05 and for 2005-06 through 2009-10. Table 7 displays the standard deviations for both time periods.

As shown in Table 7, the mean standard deviation was .208 for 2000-01 through 2004-05, and it was .250 for 2005-06 through 2009-10. As indicated above, the lower the standard deviation the greater the competitive balance. This is a 20.3% difference favoring competitive balance in the earlier period. It should also be pointed out that not only was the mean standard deviation lower for the earlier period, but the lowest standard deviation for the period, .173 (2000-01), was lower than the lowest standard deviation for the later period, .238 (2006-07). Likewise the highest standard deviation for the later period, .261 (2009-10) was higher than the highest standard deviation, .236 (2003-04) in the earlier period. As a matter of fact the standard deviation was lower every year of the earlier period than for the later period.

Why the standard deviation was lower for the earlier period can also be seen by the range of the means in the two periods. As indicated in Table 5 (the earlier period) the range was a high of .725 (Cincinnati) and a low of .266 (East Carolina). This was a range of .459 from top to bottom of the standings. On the other hand, and as indicated Table 6 (the latter period), the means ranged from a high of .948 (Memphis) to a low of .216 (East Carolina). This was a range of .732 from top to bottom. Indeed in this period Memphis had a perfect record of 16-0 in three of the five years investigated, while two teams, East Carolina and SMU, had losing records all five years.

##### Championship Imbalance

Using the data from Table 8 to construct the HHI to measure competitive balance between the two periods we find the results are consistent with the results found when using the standard deviation. Using the regular season standings we find that during the 2000-01 through 2004-05 period (see Table 8), three teams–Cincinnati, Marquette and Louisville–won the championship once each. Multiple teams shared the title for two seasons–2001-02 when Cincinnati and Southern Mississippi tied and 2003-04 when there was a five-team (DePaul, Memphis, Cincinnati, UAB and Charlotte) tie for first. If we give one point for each outright championship, .5 for a two-team tie, and .2 for a five-team tie, we find:

HHI = 1.72 + 12 + 12 + .52 + .22 + .22 + .22 + .22= 2.89 + 1 + 1 + .25 + .04 + .04 + .04 + .04 = 5.3/5 = 1.06

When measuring the HHI over the 2005-06 through 2009-10 period (see Table 8), we find considerably less competitive balance. During this period one team, Memphis, won the regular season championship four times and another team, UTEP, won the championship the other year. Measuring these results we find:

HHI= 42 + 12 = 16 + 1 = 17/5 = 3.4

These calculations indicate less competitive balance during the 2005-06 through 2009-10 period.

### Conclusions

The results of this study offer strong evidence that the churning that occurred in C-USA over the 10-year period 2000-2001 through 2009-2010 had negative effects for men’s basketball in terms of both competitive success at the national level and competitive balance within the conference. Both of the indicators of national success—winning percentage against non-conference opponents and revenue derived from member appearances in the national championship tournament—were better during the earlier period than the latter. In addition both measures of competitive balance within the conference—standard deviation of winning percentages and the HHI—indicate more competitive balance in the earlier period.

It is also important to note that while this study examined the financial ramifications of C-USA’s success, or lack thereof, in the men’s basketball national championship tournament, that revenue stream was but one of several that determine the overall financial well-being of the conference and its members. However, Crytzer (3) has observed that as the financial benefits of the C-USA’s success in men’s basketball from 2003-2005 in particular run out, the conference’s long-term viability may be at risk. Clearly, multiple factors relating to a variety of sport programs will affect whether C-USA is susceptible to additional churning and/or will even survive. However, the findings of this study pertaining to one flagship sport, men’s basketball, indicate the conference faces significant challenges in the near future.

### Applications In Sport

While the results of this study are not to be generalized to other sports programs or other conferences, they do align with the findings of other studies that have examined the effects of conference churning on competitive balance in men’s basketball. While Rhoads (9) found realignment in the Western Athletic and Mountain West conferences had enhanced competitive balance in football, it did not have the same positive effect in men’s basketball. And two studies on the effects of churning in the Big 12 found improved competitive balance in football (14) but diminished competitive balance in men’s basketball (13). Since football is recognized as the primary factor in conference realignment (6), it may be that conference churning commonly results in desirable outcomes for that one sport program while others (i.e., men’s basketball) do not enjoy the same benefits. Given the potential for revenue generation in men’s basketball, and perhaps a few other sport programs aside from football (depending on the institution), the appeal of competitive success on a national level, and the importance of in-conference competitive balance, university and college leaders are well advised to consider likely ramifications for multiple sport programs when considering conference affiliation options.

### Tables

Conference Last Change Description
Atlantic Coast Conference 2005 Boston College joins
Big East Conference 2011 Texas Christian joins
Big Ten Conference 2011 Nebraska joins
Big 12 Conference 2011 Two institutions withdraw
Conference USA 2005 Five institutions join, four withdraw
Mid-American Conference 2007 Temple joins as football-only member
Mountain West Conference 2011 Two institutions withdraw, Boise State joins
Pac-10 Conference 2011 Two institutions join
Southeastern Conference 1990 Two institutions join
Sun Belt Conference 2010 New Orleans withdraws
Western Athletic Conference 2011 Boise State withdraws

#### Table 2
Evolution of C-USA, 1995-2011

Conference Last Change Description
UNC Charlotte 1995-2005 Atlantic 10
Cincinnati 1995-2005 Big East
DePaul 1995-2005 Big East
Houston 1995-Present C-USA
Louisville 1996-Present C-USA
St. Louis 1995-2005 Atlantic 10
Southern Miss 1995-Present C-USA
Tulane 1995-Present C-USA
Alabama, Birmingham 1999-Present C-USA
Southern Florida 1995-2005 Big East
Central Florida 2005-Present C-USA
Texas Christian 1999-2005 Mountain West1
East Carolina 1996-Present C-USA
Army 1997-2005 Independant
Marshall 2005-Present C-USA
Rice 2005-Present C-USA
Southern Methodist 2005-Present C-USA
Tulsa 2005-Present C-USA
Texas, El-Paso 2005-Present C-USA

1. Moving to the Big East in 2011-2012 season

#### Table 3
Conference Winning Percentage in Games Against Non-Conference Opponents

Year Winning Percentage
2000-01 .550
2001-02 .622
2002-03 .607
2003-04 .638
2004-05 .615
5-Year Mean .606
2005-06 .539
2006-07 .590
2007-08 .585
2008-09 .589
2009-10 .583
5-Year Mean .577

#### Table 4
NCAA Tournament Appearances and Related Revenue

Year NCAA Appearances Unit Volume ($) Yearly Value ($) 6 Year Value ($)
2001 5 94,086 470,430 2,822,580
2002 4 100,672 402,688 2,416,128
2003 9 130,697 1,176,273 7,057,638
2004 11 140,964 1,550,604 9,303,624
2005 10 152,038 1,520,380 9,122,280
5-Year Totals 39 618,457 5,120,375 30,722,250
2006 5 163,981 819,905 4,919,430
2007 4 176,864 707,456 4,244,736
2008 5 191,013 955,065 5,730,390
2009 3 206,020 618,060 3,708,360
2010 2 222,206 444,412 2,666,472
5-Year Totals 19 960,084 3,544,898 21,269,388

#### Table 5
Winning Percentage for Men’s Basketball Teams, 2000-01 through 2004-05

Year Cin Char Marq StL Lou DeP SouM Mem USF UAB Hou Tul ECar TCU
2000-01 0.688 0.625 0.563 0.5 0.5 0.25 0.688 0.625 0.563 0.5 0.375 0.125
2001-02 0.875 0.688 0.813 0.563 0.5 0.125 0.25 0.75 0.5 0.375 0.563 0.313 0.313 0.375
2002-03 0.562 0.5 0.875 0.562 0.688 0.5 0.313 0.813 0.438 0.5 0.375 0.5 0.188 0.188
2002-04 0.75 0.75 0.5 0.563 0.563 0.75 0.375 0.75 0.063 0.75 0.188 0.25 0.313 0.438
2004-05 0.75 0.75 0.438 0.375 0.875 0.625 0.25 0.563 0.313 0.625 0.563 0.25 0.25 0.5
Mean 0.725 0.663 0.638 0.513 0.625 0.45 0.375 0.700 0.375 0.55 0.413 0.288 0.266 0.375

#### Table 6
Winning Percentage for Men’s Basketball Teams for 2005-06 through 2009-10

Year Memphis UAB UTEP Hou UCF Tulsa Rice Tulane Marshall SMU So.Miss E.Car.
2005-06 0.929 0.857 0.786 0.643 0.5 0.429 0.429 0.429 0.357 0.286 0.214 0.143
2006-07 1 0.438 0.375 0.625 0.688 0.563 0.5 0.563 0.438 0.188 0.563 0.063
2007-08 1 0.75 0.5 0.688 0.563 0.5 0 0.375 0.5 0.25 0.563 0.313
2008-09 1 0.688 0.625 0.625 0.438 0.75 0.25 0.438 0.438 0.188 0.25 0.313
2009-10 0.813 0.688 0.938 0.438 0.375 0.625 0.063 0.188 0.688 0.438 0.5 0.25
Mean 0.948 0.684 0.645 0.604 0.512 0.573 0.248 0.399 0.484 0.27 0.418 0.216

#### Table 7
Standard Deviation for Winning Percentages

Year SD
2000-01 0.173
2001-02 0.223
2002-03 0.202
2003-04 0.236
2004-05 0.205
5-Year Mean SD 0.208
2005-06 0.253
2006-07 0.238
2007-08 0.256
2008-09 0.243
2009-10 0.261
5-Year Mean SD 0.250

#### Table 8
Regular Season Conference Champions, 2000-01 through 2004-05

Year Champion(s)
2000-01 Cincinnati, Southern Mississippi
2001-02 Cincinnati
2002-03 Marquette
2003-04 DePaul, Memphis, Cincinnati, UAB, Charlotte
2004-05 Louisville
2004-05 Louisville
2005-06 Memphis
2006-07 Memphis
2007-08 Memphis
2008-09 Memphis
2009-10 UTEP

### References

1. Abbott, C. (1990). College athletic conferences and American regions. Journal of American Studies, 24, 220-221.
2. C-USA: Official site of Conference USA. (2011). About Conference USA. Retrieved March 21, 2011 from <http://conferenceusa.cstv.com/ot/about-c-usa.html>
3. Crytzer, J. (2009, August 30). The future of college football and the death of Conference USA 1995-2011 [Web log post]. Retrieved from <http://bleacherreport.com/articles/245204-the-future-of-college-football-and-the-death-of-conference-usa-1995-2011>
4. Depken II, C.A. (2011). Realignment and profitability in Division IA college football. Unpublished paper. Retrieved April 2, 2011 from <http://www.belkcollege.uncc.edu/cdepken/P/confsize.pdf>
5. Depken, C.A., & Wilson, D. (2005). The uncertainty outcome hypothesis in college football. Department of Economics, University of Texas-Arlington.Paper under review.
6. Fort, R., & Quirk, J. (1999). The college football industry. In J. Fizel, E. Gustafson and L. Hadley (Eds.) Sports economics: Current research (pp. 11-26). Westport, CT: Praeger.
7. Grant, R.R., Leadley, J., & Zygmont, Z. (2008). The economics of intercollegiate sports. Mountain View, CA: World Scientific.
8. Groza, M.D. (2010). NCAA conference realignment and college football attendance.Managerial and Decision Economics, 31, 517-529.
9. Humpreys, B. (2002). Alternative measures of competitive balance. Journal of Sports Economics, 3, (2), 133-148.
10. Leeds, M., & von Allmen, P. (2005).The Economics of Sports.Boston: Pearson-Addison Wesley.
11. Nunez, T. (2010, June 6). Conference realignment will have ripple effect on Conference USA. The Times-Picayune. Retrieved from <http://www.nola.com/tulane/index.ssf/2010/06/conference_realignment.html>
12. Paul, R.J., Wachsman, Y., & Weinbach, A. (2011). The role of uncertainty of outcome and scoring in the determination of satisfaction in the NFL. Journal of Sports Economics, 12, 213-221.
13. Perline, M.M., & Stoldt, G.C. (2007a). Competitive Balance and the Big 12. The SMART Journal, 4 (1), 47-58.
14. Perline, M.M., & Stoldt, G.C. (2007b). Competitive balance and conference realignment: The case of Big 12 football. The Sport Journal, 10 (2). <http://www.thesportjournal.org/2007Journal/Vol10-No2/Perline08.asp>.
15. Perline, M.M., & Stoldt, G.C. (2008). Competitive balance in women’s basketball: The Gateway Collegiate Athletic Conference and Missouri Valley Conference merger.Women in Sport and Physical Activity Journal, 17 (2), 42-49.
16. Quirk, J. (2004).College football conferences and competitive balance. Journal of Managerial and Decision Economics, 25, 63-75.
17. Rein, I., Kotler, P., & Shields, B. (2006). The elusive fan.New York: McGraw-Hill.
18. Rhoads, T.A. (2004). Competitive balance and conference realignment in the NCAA. Paper presented at the 74th Annual Meeting of Southern Economic Association, New Orleans, LA.
19. SECSports.com (2011). About the SEC. Retrieved March 21, 2011 from http://www.secdigitalnetwork.com/SECSports/Home.aspx
20. Staurowsky, E.J., & Abney, R. (2011). Intercollegiate athletics. In P.M. Pedersen, J.B. Parks, J. Quarterman, & L. Thibault (Eds.) Contemporary sport management (4th ed., pp. 142-163). Champaign, IL: Human Kinetics.
21. The State of Conference Realignment. (ND). The national championship issue: Perspectives on college football. [Web log post]. Retrieved March 22, 2011 from <http://thenationalchampionshipissue.blogspot.com/2008/01/state-of-conference-realignment.html
22. Where the money goes. (2010). Champion. Retrieved April 2, 2011 from http://www.ncaachampionmagazine.org/Exclusives/WhereTheMoneyGoes.pdf>
23. Wieberg, S. (2005, June 29). Conference shakeup continues as schools seek right fit. USA Today. Retrieved March 22, 2011 from <http://www.usatoday.com/sports/college/2005-06-28-conference-hopscotch_x.htm>

### Corresponding Author

G. Clayton Stoldt
Wichita State University
Department of Sport Management
1845 Fairmount
Wichita, KS 67260-0127
clay.stoldt@wichita.edu
P: (316) 978-5441

Martin Perline is a professor and Bloomfield Foundation fellow in the Department of Economics at Wichita State University. G. Clayton Stoldt is chair and professor in the Department of Sport Management at Wichita State University. Mark Vermillion is an assistant professor in the Department of Sport Management at Wichita State University.

2015-11-08T07:40:19-06:00January 3rd, 2012|Contemporary Sports Issues, Sports Coaching, Sports Management, Sports Studies and Sports Psychology|Comments Off on The Effects of Conference Realignment on National Success and Competitive Balance: The Case of Conference USA Men’s Basketball
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The Effect of Music Listening on Running Performance and Rating of Perceived Exertion of College Students

Randy Bonnette, Texas A&M University-Corpus Christi; Morgan C. Smith III, Texas A&M University-Corpus Christi; Frank Spaniol, Texas A&M University-Corpus Christi; Liette Ocker, Texas A&M University-Corpus Christi; Don Melrose, Texas A&M University-Corpus Christi

### Abstract

The purpose of this study was to investigate how listening to music while running affects performance and perceived exertion of college students. Twenty-eight undergraduate kinesiology students (17 males, 11 females; age = 22.9 ± 5.9 yrs) were studied to determine if running performance and rating of perceived exertion were affected by listening to music. Running performance (RP) was measured by a 1.5-mile run. Two trials were performed, the first was a running performance without music listening (RPWOML = 12.94 ± 3.35 min) and the second trial was a running performance while music listening (RPWML = 12.50 ± 2.48 min). The second trial was measured five days post the initial trial. Listening to music (music listening) was defined as the subject’s self selection of music tracks and use of a personal digital audio player (e.g. IPod, MP3) during exercise. Perceived exertion without music listening (PEWOML = 14.7 ± 1.3) and perceived exertion with music listening (PEWML = 15.2 ± 2.4) was measured by the Borg 6 to 20 RPE scale. Data analysis was performed on the raw data by utilizing dependent t-tests to calculate and compare sample means. Statistical analyses determined a significant difference (p < .05) between running performance without music listening (RPWOML = 12.94 ± 3.35 min) and running performance with music listening (RPWML = 12.50 ± 2.48 min). However, no significant difference (p < .05) was determined between perceived exertion without music listening (PEWOML = 14.7 ± 1.3) and perceived exertion with music listening (PEWML = 15.2 ± 2.4) as measured by the Borg 6 to 20 RPE scale. In conclusion, the results of this study indicate that music listening has a significant effect on running performance during a maximal 1.5-mile run. However, music listening had no significant effect on rating of perceived exertion at this distance. Based on the results of this study it is recommended that coaches, athletes, and traditional exercisers consider listening to music during training to enhance performance.

**Key Words:** Music Listening, Aerobic, Performance, Rated Perceived Exertion (RPE)

### Introduction

In the past listening to music was relegated to travelling in automobiles, while in the home, while engaged in recreational activities and occasionally at work. Today, the portable music industry (e.g. cassettes, compact discs, and iPod/MP3 digital audio devices) has popularized music “on the go” and invaded just about every environment including training venues. These devices have made it easier for people to enjoy their music and create their own style of workouts with relative ease, regardless of the setting, and has transcended into a multi-million dollar industry (14). Similarly, the sports arena is an environment where music has flourished. Traditionally, music has been used to motivate and inspire people prior to an important event (e.g. pre-game of a critical contest) as well as when they engage in sports and training for competition. Thus, athletes and traditional exercisers alike have used music as an accompaniment to exercise to sustain motivation, resist mental and emotional fatigue, and potentially enhance their physical and athletic performance (10). Scientific inquiry has revealed three key ways in which music can ‘influence’ preparation and competitive performances through dissociation, arousal regulation, and synchronization (3, 4, 6, 8-10). More specifically, research indicates music to be particularly effective in distracting exercisers away from their perceived exertion.

#### Conceptual Framework

Conceptually the underlying framework of using motivational music in exercise and sport devised by Karageorghis et al. (7) indicated two main hypotheses regarding arousal regulation and fatigue dissociation. First, music can be used to alter emotional and physiological arousal and thus can act either as a stimulant or sedative prior to and during physical activity. Therefore, an athlete can use various music tempos as a ‘psych-up’ strategy in preparation for a competition or perhaps an aid to calming over anxiousness. Second, music diverts a performer’s attention from sensations of fatigue during exercise. This diversionary technique, known as dissociation, lowers perceptions of effort. Effective dissociation can promote a positive mood state, thus turning the attention away from thoughts of physiological sensations of fatigue (7).

#### Rated Perceived Exertion

Noble and Robertson (13) define perceived exertion as the subjective intensity of effort, strain discomfort and/or the fatigue that is experienced during an exercise. Currently, the most consistent findings suggest that perceived exertion will rate in lower values when participants exercise to music (12, 13, 22, & 24). The research data compiled from over the past two decades has found music particularly effective in distracting exercisers away from their perceived exertion during physical activity. A study by Nethery, Harmer, and Taaffe (12) found that perceived exertion while exercising to music was lower than for other attentional distracters and for the no distraction condition. Furthermore, Thornby et al. (22) tested exercising participants in the presence of music, no music and noise. They discovered that participants reported a lower perceived exertion while exercising in the presence of music in comparison to the no music and noise conditions.

These findings coupled with the popularity and substantial profits generated between the association of music and training (14) would seem to indicate a correlation between the use of music and performance. However, the effects of listening to music on performance and other physiological measures are less clear. Therefore, the purpose of this study was to investigate the effect listening to music has on running performance and rating of perceived exertion of college students.

### Methods

#### Experimental Approach to the Problem

Listening to music (music listening) was defined as the subject’s self selection of music tracks and use of a personal digital audio player (e.g. IPod, MP3) during exercise. Running performance was determined by a maximal 1.5 mile run to predict VO2 max. Subjects were asked to complete the distance run in the fastest time possible. Results were recorded in minutes and seconds. A common field test equation, V02 max (ml*kg-1*min-1) = 3.5 + 483 / (time in minutes), was selected to access cardio-respiratory fitness of the subjects utilizing their 1.5 mile running performance (1). Perceived exertion was determined by the Borg 6 to 20 RPE scale. Rating of perceived exertion summarizes the exertion levels between rest and maximum effort numerically from 6 to 20 (2).

#### Subjects

Twenty-eight undergraduate kinesiology students (17 males, 11 females; age = 22.9 ± 5.9 yrs) from a south Texas university were studied to determine if running performance and rating of perceived exertion were affected by listening to music. Institutional Review Board approval and subject informed consent were obtained prior to commencement of the research study.

#### Procedures

All participants were required to fill out an informed consent document two days prior to testing. Participants were then instructed to obtain sufficient sleep (6-8 hours) and avoid food, caffeine, tobacco products, or alcohol for 3 hours prior to testing the 1.5-mile run (1). Prior to testing, a 1.5-mile course was measured with a Rolatape® distance measuring wheel. The start/finish line and .75-mile line were marked off with two cones each on the large sidewalk course. Three testers were used to ensure subjects completed the 1.5-mile run, two researchers were stationed at the start/finish line to collect run times and RPE scores for each participant, while another tester was stationed at the .75-mile line or turn around portion of the course. To complete the 1.5-mile run each participant had to begin at the starting line, run to the .75-mile line, and then simply turn around and run back to the start/finish line. Stopwatches were used to measure 1.5-mile run times. Following the course explanation; the participants were encouraged to warm-up and stretch before starting the 1.5-mile run, as well as verbally read the following instructions for use of the Borg 6 to 20 RPE scale:

> During the exercise test we want you to pay close attention to how hard you feel the exercise work rate is. This feeling should be your total amount of exertion and fatigue, combining all sensations and feelings of physical stress, effort, and fatigue. Don’t concern yourself with any one factor such as leg pain, shortness of breath, or exercise intensity, but try to concentrate on your total, inner feeling of exertion. Try not to underestimate or overestimate your feeling of exertion, be as accurate as you can (20).

The participants completed two separate 1.5-mile runs as a group during their regularly scheduled class time on their campus. The first trial was performed in silence without any form of digital audio device (IPod, MP3) which would enable music listening. Five days post the initial trial, a second 1.5-mile run was administered during the regularly scheduled class meeting. However, in this 1.5-mile run test participants were required to use digital audio devices during the trial to enable music listening. Music selection was not controlled during this experiment; therefore the participants were able to select their favorite musical tracks to accompany them on their second trial run. All run times were recorded as the participants crossed the finish line, and RPE was obtained shortly thereafter when the subjects were asked to pick the number best reflecting their exertion from the Borg 6 to 20 scale poster board on site.

#### Statistical Analysis

An experimental one-group pretest-posttest design was utilized. The subjects completed two 1.5-mile run trials to test the effect of music listening on running performance and rating of perceived exertion. Dependent t-tests were utilized to compare mean data from the experimental conditions: music listening and without music listening. Significance was determined at the probability level of .05.

### Results
The results are divided into two sections: running performance and rating of perceived exertion. Data analysis was performed on the raw data by utilizing dependent t-tests to calculate and compare paired sample means. The mean and standard deviation values for these two measures, according to experimental conditions, are summarized in Table (1).

#### Running Performance

Dependent t-tests were conducted on the subjects running performance times in conditions without music listening and with music listening. Two trials were performed, the first was a running performance without music listening (RPWOML = 12.94 ± 3.35 min) and the second trial was a running performance while music listening (RPWML = 12.50 ± 2.48 min). Statistical analyses found music listening had a significant t (26) = 1.75, p = .0478 impact on running performance as shown in Figure 1. In addition, music listening was found to have a significant t (16) = 2.07, p = .0445 effect on running performance for male subjects, whereas female subject t (10) = 1.23, p = .12 indicated non significance.

#### Rating of perceived exertion
A paired two sample dependent t-test was conducted on the subjects rating of perceived exertion after completing a 1.5-mile running performance in conditions without music listening and with music listening. The result of the two trials found the subjects rated perceived exertion without music listening (PEWOML = 14.7 ± 1.3) to be lower than ratings of perceived exertion with music listening (PEWML = 15.2 ± 2.4). Statistical analysis found the effect of music listening on the groups rated perceived exertion to be non significant t (26) = -1.22, p = .11 as shown in Figure 2. However, music listening was found to have a significant t (10) = -2.96, p = .01 directional effect on reported female rating of perceived exertion scores while non significance t (16) = -.18, p = .4263 was found among male rating of perceived exertion scores.

### Discussion

The effects of listening to music on running performance and the rating of perceived exertion during maximal 1.5-mile runs were investigated. By comparing the recorded ratings of perceived exertion and running times of the two situations, it became clear when the subjects exercised to music their running performance improved collectively. Previous research by Thornby et al. (22) also found that the time spent exercising, the amount of work done, and heart rate were all significantly higher in the presence of music than in the other conditions. Similarly, Edworthy and Waring (4) make the suggestion, in regards to music’s effect on running performance, that the pace of music will influence the pace of exercise. Therefore, the assumption can be made that exercising to fast tempo music should produce faster running performance. However in this study’s case, music selection was not controlled; therefore some participant’s personal preferences might not have met the tempo or vigorous nature of the exercise conducted. Even so, the results of the two trials found the subjects running performance while listening to music (RPWML = 12.50 ± 2.48 min) to be substantially faster than running performance without music listening (RPWOML = 12.94 ± 3.35 min).

These results indicate that music listening has a significant effect (p < .0478) on running performance during a maximal 1.5-mile run. Therefore, the research null hypothesis in regards to music’s effect on running performance has been rejected. Furthermore, male subjects in particular were found to perform better while listening to music.

Additionally, music listening was found to have no significant effect on rating of perceived exertion during a maximal 1.5-mile run. The findings of the most recent research reported the effectiveness of music on the subjects’ perceived exertion rate during submaximal exercise, Copland and Franks (3), Szmedra and Bacharach (20), and Potteiger, et al. (15). These authors suggested that in the absence of external stimulation (e.g. music) participants may focus more strongly on their own efforts and perceive them to be higher. This reasoning provides an explanation as to why traditionally subjects experience decreased RPE, particularly in submaxial exercise where music has been shown to effectively dissociate sensations of fatigue and promote a more enjoyable exercise experience. However, this study evaluated music’s effectiveness on a maximal 1.5-mile run. The result of the two trials found the subjects rated perceived exertion without music listening (PEWOML = 14.7 ± 1.3) to be lower than ratings of perceived exertion with music listening (PEWML = 15.2 ± 2.4). Previous research by Yamishita and Iwai (22) suggest that music’s effect on RPE is limited by the intensity of the exercise. Schwartz et al. (17) experienced similar findings stating that at 75% V02max RPE values did not significantly differ for participants between music and control conditions. Accordingly, these findings share the similar reasoning of Rejeski (16) which suggest that when subjects work at maximal intensities beyond anaerobic threshold, physiological cues dominate the attentional processes leading to external cues, such as music, to become less effective on RPE. Additionally, the results indicate listening to music has no significant effect (p < .05) on rating of perceived exertion during a maximal 1.5-mile run. Therefore, the research null hypothesis regarding music’s effect on rating of perceived exertion has been accepted. Furthermore, female subjects were found to rate RPE more difficult while listening to music. This further supports that music’s dissociative properties exhibited in sub max exercise are not transferred into maximal exercise over 75% VO2 max.

It is important to note that although none of the trials were conducted in wet conditions, wind speed and wind direction could not be standardized between trials and this may have been an additional error source. Both performance trials were conducted outdoors at 75 degrees Fahrenheit. However, wind speeds differed between trials; trial one experienced wind speeds of 8 mph with gusts of 14 mph while trial two experienced wind speeds of 18 mph with gusts of 25 mph. Due to these confounding factors conducting the research indoors would have addressed this problem. Unfortunately, an indoor track was not yet available at the university where the research was conducted. Secondly, the participants completed the two running trials together as a group. A natural tendency to compete may have compromised the internal validity of the study. However, the threat to internal validity was preferred to the potential lack of motivation had participants been required to complete the task individually (18).

### Applications In Sport

Music has been found to be an ideal accompaniment for exercise. It has the ability to alter emotional and physiological arousal as well as dissociate a performer’s attention from sensations of fatigue during exercise (19). The tempo of the music can also be used to influence exercise performance as their arousal level will be heightened by the fast tempo (7). If music is applied to these types of situations, music’s impact may have the ability to change the context in which physical work or exercise is performed and become a viable way of positively influencing an individual’s disposition as well as performance (10).

Due to the aforementioned training benefits of listening to music coaches, trainers, as well as performers should be cognizant of this revelation when planning their training regimens. Obviously, this would be especially relevant when engaging in a training session that the athlete and/or coach/trainer identify as being particularly taxing on the performer’s physiological systems. This extra-musical association could very well promote thoughts that inspire physical activity or relaxation within the athlete. For example, an athlete may associate vigorous exercise with the theme from the popular “Rocky” movie series, or possibly dreams of Olympic glory from Vangelis’ “Chariots of Fire.” The resultant association can be attributed not only to the inherent musical characteristics, such as tempo or rhythm, but to the influence of elements of popular culture, such as cinema, television, and radio (6).

In general, the results of the research indicate that exercising to music makes training a more exciting and pleasant experience leading to improved performance. Accordingly, music used as a motivational aid can provide individuals an alternative to address the repetitiveness and mundane nature of many physical activities associated with aerobic performance training.

### Acknowledgements

The authors would like to acknowledge the efforts of Ms. Elizabeth Perez, administrative assistant, in the author’s department for her tireless efforts in support of this study. Her editorial prowess and knowledge of APA style was tremendously helpful in creating a quality manuscript.

### References

1. American College of Sports Medicine. ACSM’s guidelines for exercise testing and prescription (5th ed.). Baltimore, MD: Lippincott Williams & Wilkins, 2000.
2. Borg, E. and Kaijser, L. A comparison between three rating scales for perceived exertion and two different work tests. Scandinavian Journal of Medicine & Science in Sports, 16: 57-69, 2006.
3. Copland, B. and Franks, B. Effects of types and intensities of background music on treadmill endurance. The Journal of Sports Medicine and Physical Fitness, 31(1): 100-103, 1991.
4. Edworthy, J. and Waring, H. The effects of music tempo and loudness level on treadmill exercise. Ergonomics, 49: 1597-1610, 2006.
5. Gfeller, K. Musical components and styles preferred by young adults for aerobic fitness activities. Journal of Music Therapy, 25: 28-43, 1988.
6. Karageorghis, C. and Terry, P. The psychophysical effects of music in sport and exercise: a review. Journal of Sport Behavior, 20(1): 54-68, 1997.
7. Karageorghis, C., Terry, P., and Lane, A. Development and initial validation of an instrument to assess the motivational qualities of music in exercise and sport: The Brunel Music Rating Inventory. Journal of Sport Sciences, 17: 713-724, 1999.
8. Karageorghis, C., Jones, L., and Low, D. Relationship between exercise heart rate and music tempo preference. Research Quarterly for Exercise and Sport, 77(2): 240-251, 2006.
9. Karageorghis, C., and Priest, D. Music in Sport and Exercise: An update on research and application. The Sport Journal, 11(3): Retrieved October 25, 2008, from
<http://www.thesportjournal.org/article/music-sport-and-exercise-update-research-and-application>, 2008.
10. Mohammadzadeh, H., Tartibiyan, B., and Ahmadi, A. The effects of music on the perceived exertion rate and performance of trained and untrained individuals during progressive exercise. Physical Education and Sport, 6(1): 67-74, 2008.
11. Nethery, V. Competition between internal and external sources of information during mental exercise: influence on RPE and the impact of exercise load. Journal of Sports Medicine and Physical Fitness, 17: 172-178, 2002.
12. Nethery, V, Harmer, P, and Taaffe, D. Sensory mediation of perceived exertion during submaximal exercise. Journal of Human Movement Studies, 20: 201-211, 1991.
13. Noble, B. and Robertson, R. Perceived exertion. Champaign, IL: Human Kinetics, 1996.
14. O’Rourke, B.K. Email interview, March 5, 2011.
15. Potteiger, J., Schroeder, J., and Goff, K. Influence of music on rating of perceived exertion during 20 minutes of moderate intensity. Perceptual and Motor Skills, 91: 848-854, 2000.
16. Rejeski, W. Perceived exertion: An active or passive process. Journal of Sports Psychology, 75: 371-378, 1985.
17. Schwartz, S., Fernall, E., and Plowman, S. Effects of music on exercise performance. Journal of Cardiopulmonary Rehabilitation, 10: 312-316, 1990.
18. Simpson, S. and Karageorghis, C. The effects of synchronous music on 400-m sprint performance. Journal of Sport Sciences, 24(10): 1095-1102, 2006.
19. Smoll, F. and Schultz, R. Relationships among measures of preferred tempos and motor rhythm. Perceptual and Motor Skills, 8: 883-894, 1978.
20. Szmedra, L. and Bacharach, D. Effect of music on perceived exertion, plasma lactate, nor epinephrine, and cardiovascular homodynamic during treadmill running. Journal of Sports Medicine and Physical Fitness, 19(1): 32-37, 1998.
21. Thompson, D. and West, K. Ratings of perceived exertion to determine intensity during outdoor running. Canadian Journal of Applied Physiology, 23(1): 56-65, 1998.
22. Thornby, M., Haas, F., and Axen, K. Effect of distractive auditory-stimuli on exercise tolerance in patients with COPD. Chest, 107: 1213-1217, 1995.
23. Yamashita, S. and Iwa, K. Effects of music during exercise on RPE, heart rate and the autonomic nervous system. Journal of Sports Medicine and Physical Fitness, 46: 425-430, 2006.

### Tables

#### Table 1
Effects of Music Listening on Running Performance and RPE

Conditions Running Performance RPE
No Music Listening Music Listening No Music Listening Music Listening
Groups M SD M SD M SD M SD
Female (N=11) 14.51 3.81 13.74 1.98 14.73 1.35 15.82 1.60
Male (N=17) 11.94 2.69 11.70 2.49 14.65 1.37 14.76 2.77
Combined (N=28) 12.95 3.36 12.50 2.48 14.67 1.33 15.18 2.40

### Figures

#### Figure 1
Running performance mean comparison among groups

![Figure 1](/files/volume-14/440/figure-1.jpg)

#### Figure 2
RPE mean comparison among groups

![Figure 2](/files/volume-14/440/figure-2.jpg)

### Corresponding Author

Randy Bonnette, Ed.D.
Department of Kinesiology, Unit 5820
6300 Ocean Drive
Corpus Christi, TX 78412
<Randy.Bonnette@tamucc.edu>
(361)825-3317

Randy Bonnette is the chair of the Kinesiology Department in the College of Education at Texas A&M University – Corpus Christi.

2013-11-25T14:47:27-06:00January 3rd, 2012|Sports Exercise Science, Sports Management, Sports Studies and Sports Psychology|Comments Off on The Effect of Music Listening on Running Performance and Rating of Perceived Exertion of College Students
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Implications of State Income Tax Policy on NBA Franchise Success: Tax Policy, Professional Sports, and Collective Bargaining

Timothy E. Zimmer

### Abstract

The paper examines the relationship between state income tax rates and the success of National Basketball Association (NBA) franchises. The model indicates that state income tax policy has an influence on team performance. The higher the rate for the top marginal tax bracket, the greater the negative bias on team performance. Team performance is dependent on the successful acquisition of quality resources which include players, coaches, and team management. The results infer that NBA franchises located in high tax states impose a burden on the ability of team ownership to attract the best resources in order to achieve success. The relationship could have broader implications on professional sports and their Collective Bargaining Agreements.

**Key words:** National Basketball Association (NBA), Professional Sports, Collective Bargaining Agreement (CBA), Salary Cap, Bias, Free Agency, State Income Tax Policy

### Introduction

The National Basketball Association (NBA) is a sports entertainment enterprise with yearly revenues surpassing $4 billion (5). The majority of these revenues are derived from ticket sales, merchandising and television revenues. The distribution of these revenues between franchises and players has been negotiated and is governed by the Collective Bargaining Agreement (CBA). The current version of the CBA was implemented before the 1984-85 season and was most recently re-negotiated prior to the 2005 season. The current CBA contract expires following the 2010-2011 NBA season, but league owners have the option to extend the agreement through the 2011-2012 NBA season (5).

A large component of the CBA is the provision of a salary cap. The salary cap dictates a fixed percentage of league revenues which are to be paid to players in terms of salaries and benefits. NBA teams are presented with a yearly salary cap number to be used as player compensation. This amount can only be exceeded utilizing certain exceptions as further defined by the CBA.

One justification for the salary cap is the concept that it is designed to benefit middle and small market teams. It is argued that larger market teams have significantly more ability to profit from ticket, merchandising and television revenues. This advantage could be used to enlist top talent by paying salaries far exceeding those of smaller markets. In using superior financial resources to lure and retain better talent (players, coaches and management), it is feared that larger market teams could dominate the league over a prolonged period.

The salary cap system, it is argued, should allow every NBA franchise an equal opportunity in acquiring and obtaining comparable resources. While not a perfect system, the CBA should work to distribute resources (player skill, coaching talent and management expertise) more evenly throughout the league. While the CBA only governs player salaries, the even distribution of quality players throughout the league should also dissuade quality coaches and management from concentrating and distribute them throughout the league.

League ownership believes that an equal chance of team success should promote larger game attendance and provide for a healthier competitive balance in the league. However, these goals have repeatedly been disputed in research (7, 3, 9) which have found increased disparity of play after the imposition of revenue sharing amongst teams and other results inconsistent with stated goals. This paper will extend this research by examining potential causes of the breakdown between the intended goals of the CBA and its results.

In assessing NBA franchise success, the incentive structure facing potential resources (players, coaches, management) should be examined. The different tax environment of NBA franchises is a potential variable which could disrupt league parity. It is argued in this paper that resources are influenced by the financial incentives created by varying state income tax rates applied to the differing NBA franchises based on location. The implications of these findings could have impacts on future CBA negotiations.

### Methodolgy

The study examines the potential for state tax income tax policy to influence NBA team success. The model employs data for eleven years (2000 through 2010) of previous NBA seasons. Also included are the rates (in percentage terms) for the individual states top marginal tax brackets for these eleven years.

The basketball data was assembled using information from a sports database website (6). The income tax bracket data was derived using information from the tax foundation website (10). For ease of computation and data gathering, only the top marginal tax bracket was used. As NBA salaries escalate, the importance of lower tax brackets becomes nominal.

The data from the Canadian-based team was removed. The examination is on the impact of income taxes on player decisions, which in the United States will be uniform at the federal level and vary only at the state level. Canadian players face differing income tax systems at both the federal and state/province level. Rather than trying to incorporate or properly account for these significant differences, the Canadian observations were removed.

A team’s success for a year is influenced by the players it has on the team from prior seasons. A proxy for the ability of players from prior seasons is created, which is the winning percentage for the team from prior years. Three years of winning percentages were lagged to account for anomalies in play in any one given year. While this proxy has shortcomings, it should provide a good baseline of team ability.

When a NBA team struggles to achieve success, the coaching position is often assessed. Coaching turnover in the NBA is prevalent and its impact on team performance must be considered. Teams will react differently to coaching change. Team ownership chooses a coach in the hopes that the new coach will develop player skills and enact schemes of play which will positively impact performance. For some teams, new coaching techniques might take some time to integrate into their play. For this reason, a lagged coaching change variable is created to account for this learning period.

A method for adding players is through the NBA draft. A variable is created to control for player acquisition through the player draft. A lagged variable is also created to account for maturation of these drafted players.

The use of financial incentives to pool resources in larger markets, has been somewhat muted by the CBA and the salary cap. However, larger metropolitan areas can provide amenities and lifestyle options not found in many smaller markets, which may still bias resources towards these markets. Additionally, salaries for coaches and management are not governed by the CBA and thus a larger market team could use financial resources to attract higher quality talent. To account for the potential residual bias in regard to market size, a control variable is created. The data incorporated is the 2000 Census Metropolitan Area found on the U.S. Census website (11).

NBA franchises attempt to achieve success by attracting the high-quality resources. These resources include players, both the addition and retention of high skilled free agents, coaches, and management personnel. While the significance of changes has been examined, particularly with regard to coaching and drafting of players, the issue of quality has not been addressed. The tax environment of each franchise may influence the potential of the team to attract the highest quality resources in order to achieve success. The tax environment of the team will bias the best resources (players, coaches, and management alike) towards certain franchises and away from others creating a performance bias. The decision process of these resources is contemplated the year prior to a given season. For this reason, the state income tax is lagged by a year.

The top marginal tax rate and metropolitan population for each team in 2010 is provided in Table 1. Tax information is time dependent and may vary in each year of the study. Also, in some instances teams switched host cities and states, such as the Sonics moving in 2008 from Seattle to Oklahoma. In these instances, not only would the tax information change, but so would the metropolitan population data. This type of movement increases data variation and helps to provide a more robust analysis. Descriptive statistics for all non-binary variables in the study are found in Table 2.

Using larger data sets can account for player injury. Player injury is frequent in the NBA and can have a substantial impact on team performance. By utilizing a large number of years, it can assume that player injury is random. Player injury is a risk every team takes when committing a large contract to a free agent. It is assumed that the risk of injury is normally distributed among the teams over a large sample.

The following equation is used to estimate the winning percentage of the team for the current season.

(Equation 1)

The dependent variable, WinPcti, t, represents the winning percentage of “i” team in the current “t” year. Yearly influences are captured through the use of a binary year variable Yeart, with the variable for 2005 dropped to prevent linear dependency. The regressor WinPcti,(t-1) is the winning percentage of the “i” team from one year prior. The variables WinPct(t-2) and WinPct(t-3), represent the winning percentage of the “i” team lagged two and three years respectively.

Coaching change is accommodated in the model through the Coachi,t variable. This is a binary variable and is positive if a new coach for the “i” team is in place at the start of current “t” year or if a coaching change is made during the year. To account for the potential of the learning period, this variable is further lagged one period and represented by the Coachi,(t-1) variable.

A NBA team can improve by changing its roster through the player draft.

The selection order of the NBA draft is the inverse of how the teams finished the season in terms of winning percentage. The draft is structured so that the worst teams, determined by winning percentage, have the best opportunity (in a lottery format) for high selections. In order to assess the influence of drafted players, a team is awarded points for the first pick in the first round of the NBA draft. Only the best pick was awarded points in the rare instance of a team having multiple first round picks. The first pick is awarded 30 points, scaled down one point for each pick down to the last pick of the first round which was awarded 1 point. The trading of draft picks is not considered as it is assumed the teams would require equal compensation for the traded draft pick.

The picking order of teams in the draft is scaled linearly. However, changes in player ability throughout the draft are likely non-linear. To account for the non-linear scaling of talent, draft points are squared to emphasis the ability of earlier picks to immediately influence team performance. The variable DraftSqri,t represents the value of the draft pick for team “i” going into the current “t” year. As these players mature and develop their skills, an additional lag variable DraftSqri,(t-1) is employed to capture these effects. The variable captures the lag effects for one period.

The variable MetroSizei represents the population of the metro or surrounding area to each NBA franchise. The variable is team dependent “i”, but is time invariant. The variable will detect larger market bias in the data.

Finally, the variable StateIncTaxi,(t-1) is the top marginal tax bracket for the state in which the “i” team competes lagged one period from the current “t” year. The variable will capture the effect of taxes on performance.

It is important to note that the dependent variable in “Equation 1” is integer-valued with a discrete distribution. To address this concern, it is possible to assume that the score differential Y is a manifestation of an underlying continuous variable Z. Where Y is determined by rounding Z to the nearest integer, and to assume Z follows the model (12):

(Equation 2)

Previous studies have indicated that for most purposes “Equation 1” provides an adequate approximation to the model determined by “Equation 2” (1). As a result, “Equation 1” can be estimated using ordinary least squares (OLS).

### RESULTS

The estimation results are presented in Table 3. The binary year variables are all shown to be insignificant, thus discounting the influence of yearly variation.

The prior two years’ season performances are an accurate predictor of a team’s level of play in the current season. The positive and significant coefficients two years lagged winning percentage implies commonality in team play over multiple seasons. The result also implies that it is difficult to altering a team success and may require several years of rebuilding a losing franchise. The third year being significant and negative suggests the cyclical nature of team success in a league governed by a salary cap restrictions and draft ordering process focused on parity.

The coaching variable is highly significant and negative. Rather than guiding a team towards success, a change in coaching personnel is associated with a negative response in team performance. There also does not appear to a learning curve with respect coaching change, as the lagged coaching variable is insignificant. Not only does the team suffer negatively in the short term from coaching change, the team does not improve in the longer term even after allowing time for the team to absorb the new coach’s playing philosophy.

The draft variables are shown to be insignificant. At least in the short term, drafted players do not have an impact on team performance in terms of winning percentage. The time required to develop these players may exceed the two years accounted for in this model. While accepting the potential for non-linear skill distribution of drafted players marginally increased the viability of the draft variable, it never appeared statistically significance.

Market size is shown not to bias team success. NBA franchises in larger markets are shown to be unable to significantly leverage their market size into acquiring superior skilled resources (players, coaches, and management) as reflected by team success.

Finally, of particular note is the significant and negative relationship between team success and state income tax policy. Teams which play in states with higher top marginal tax rates have less success and a lower winning percentage. The prolonged disparity in winning percentage is argued as an inherent bias of better resources avoiding teams in locations of high taxes. Teams in high tax states could have a more difficult time obtaining comparable talent compared to NBA franchises in low tax states.

### Conclusions

The study examined the potential incentive that state income taxes have on the ability of NBA teams to lure top talent and gain a competitive advantage. The results provide several insights which can be incorporated in the operation of the league and the collective bargaining agreements (CBA).

The results indicate commonality in team success over multiple periods. If a team wishes to alter its winning percentage, the data suggests that one season is insufficient to achieve this goal. Progress is only witnesses as a gradual process over several seasons.

The results also indicate that the window of opportunity for an established team having success is approximately two years before parity efforts begin to take affect and the team’s winning percentage begins to revert to the norm. Team management must understand that the opportunities for a successful team are fleeting and urgency is required for decisions during this period to maximize winning potential.

Once a decision is made to reconstitute a team, it is difficult to accomplish this task quickly. Fans are inherently impatient, which often manifests itself in team management making hasty decisions with regard to coaching. Coaching change is shown to have a negative impact on team performance. The data suggests that rebuilding progress can only be witnessed gradually.

The impact of the NBA draft is shown to have a negligible immediate impact term team performance in the short term. The benefits of the draft do not materialize in the model, even when considering the potential of a non-linear distribution of skill level in the draft. Also of negligible importance on team success is market size. The argument that larger markets can attract superior players due to lifestyle benefits and superior coaches/management through financial considerations is unsubstantiated by the data.

Finally, it is determined that a state’s top marginal tax bracket in which a particular team plays has a negative influence on the team’s success. The data suggests that NBA teams in states with high income taxes are negatively biased when attempting to lure superior talent in terms of player ability, coaching talent or management skill. The state tax influence on team success is indirect, suggesting that subsequent research can be done to detect the direct method of transmission of this influence through players, coaches, management, or some combination. Further research can also be conducted to determine if other professional sports exhibit a similar negative relationship between state tax policy and team success.

### Application In Sports

The Collective Bargaining Agreement (CBA) was recently renegotiated in the NBA. If owners and players in professional sports are interested in promoting league parity, thus ensuring an equal chance of team success and fan excitement, perhaps they should consider a scaled salary cap to benefit teams in high-taxed markets. A tax adjustment index could be applied to the salary cap thus ensuring equal opportunity to acquire equal resources and minimizing the negative bias.

### Tables

#### Table 1
State Income Tax Rate (Highest Marginal Bracket)

Team State Top Marginal Tax Bracket Market Size (2000 Census)
Metropolitan Areas (in millions)
Blazers OR 11.00% 2.265223
Clippers CA 10.55% 16.373645
Kings CA 10.55% 1.796857
Lakers CA 10.55% 16.373645
Warriors CA 10.55% 7.039362
Knicks NY 8.97% 21.199865
Nets NJ 8.97% 21.199865
Wizards Washington, DC 8.50% 7.608070
Wolves MN 7.85% 2.968806
Bobcats NC 7.75% 1.499293
Bucks WI 7.75% 1.689572
Cavs OH 5.9325% 2.945831
Grizzlies TN 6.00% 1.135614
Hawks GA 6.00% 4.112198
NO-Hornets LA 6.00% 1.337726
Sonics OK 5.50% 1.083346
Celtics MA 5.30% 5.819100
Jazz UT 5.00% 1.333914
Nuggets CO 4.63% 2.581506
Suns AZ 4.54% 3.251876
Pistons MI 4.35% 5.456428
Pacers IN 3.40% 1.607486
76ers PA 3.07% 6.188463
Bulls IL 3.00% 9.157540
Heat FL 0.00% 3.876380
Magic FL 0.00% 1.644561
Mavs TX 0.00% 5.221801
Rockets TX 0.00% 4.669571
Spurs TX 0.00% 1.592383

Tax data from [Tax Foundation Website](http://www.taxfoundation.org)

Population data from [U.S. Census](http://www.factfinder.census.gov)

#### Table 2
Descriptive Statistics

Variable Observations Mean Standard Deviation Min Max
Winning Pct 312 0.5030 0.1503 0.15 0.82
Tax Rate 312 0.0539 0.0342 0.00 0.11
Draft Position 312 13.3494 10.2441 0.00 30.00
Metro Size (in millions) 312 5.7900 5.7315 1.08 21.20

#### Table 3
Basketball Team Winning Percentage Estimation

Variable Coefficient Standard Error
Variable Coefficient Standard Error
Constant 0.2464
2001 -0.0175 0.0310
2002 -0.0162 0.0309
2003 -0.0290 0.0309
2004 -0.0050 0.0310
2006 -0.0105 0.0303
2007 -0.0379 0.0306
2008 -0.0279 0.0308
2009 -0.0094 0.0304
2010 -0.0195 0.0300
Win Pct Lagged 1 Year (WinPct(t-1)) 0.5656 0.0942***
Win Pct Lagged 2 Year (WinPct(t-2)) 0.1586 0.0963*
Win Pct Lagged 3 Year (WinPct(t-3)) -0.1148 0.0587**
Coach (Coachi,t) -0.0808 0.0155***
Coach Lagged 1 Year (Coachi,(t-1)) -0.0066 0.0160
Draft Squared (DraftSqri,t) 0.00005 0.00004
Draft Squared Lagged 1 Year (DraftSqri,(t-1)) 0.00006 0.00004
Metro Size (MetroSizei) -0.0011 0.0012
State Income Tax Lagged 1 Year (StateIncTaxi,(t-1)) -0.4167 0.2167**
Observation 281
R-squared 0.4612
F(18,262), Prob>F 12.46 0.0000***

* Significant at the 10% level
** Significant at the 5% level
*** Significant at the 1% level

### References

1. Harville, D. (2003). The Selection or Seeding of College Basketball or Football Teams for Postseason Competition. Journal of the American Statistical Association. 98, 17-27.
2. Kahn, Lawrence M. (Summer, 2000). The Sports Business as a Labor Market Laboratory. The Journal of Economic Perspectives. 14 (3), 75-94.
3. Kaplan, R. A. (October, 2004). The NBA Luxury Tax Model: A Misguided Regulatory Regime. Columbia Law Review. 104 (6), 1615-1650.
4. Kendall, T.D. (October, 2003). Spillovers, Complementarities, and Sorting in Labor Markets with an Application to Professional Sports. Southern Economic Journal. 70 (2), 389-402.
5. NBA data website: www.insidehoops.com.
6. NBA data website: www.basketballreference.com.
7. Rosen, S. and Sanderson A. (February, 2001). Labour Markets in Professional Sports. The Economic Journal. 111 (469), F47-F68.
8. Scully, Gerald W. (March, 2004). Player Salary Share and the Distribution of Player Earnings. Managerial and Decision Economics. 25 (2), Sports Economics, 77-86.
9. Szymanski, S. and Kesenne, S. (March, 2004). Competitive Balance and Gate Revenue Sharing in Team Sports. The Journal of Industrial Economics. 52 (1), 165-177.
10. Marginal Tax Data: www.taxfoundation.org.
11. United States Census Data: <http://www.factfinder.census.gov>.
12. Zimmer, Timothy and Kuethe, Todd. (2008). Major Conference Bias and the NCAA Men’s Basketball Tournament. Economics Bulletin. 12 (17), 1-6.
13. Zodrow, G., and Mieszkowski, P. (1986). Pigou, tiebout, property taxation, and the underprovision of local public goods. Journal of Urban Economics. 19, 356-370.

### Corresponding Author

Timothy E. Zimmer, Ph.D.
6718 W. Stonegate Dr.
Zionsville, IN 46077
timothyzimmer@alumni.purdue.edu
317-769-0336

### Author Bio

Tim Zimmer is an adjunct professor of economics at Butler University.

2016-05-16T11:16:23-05:00January 2nd, 2012|Sports Management, Sports Studies and Sports Psychology|Comments Off on Implications of State Income Tax Policy on NBA Franchise Success: Tax Policy, Professional Sports, and Collective Bargaining
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