ncaa behavior within the economic analysis of cartel an · pdf filean economic analysis of...

Journal of Sport Management, 1996,10,388-400 O 1996 Human Kinetics Publishers, Inc.

An Economic Analysis of Cartel Behavior Within The NCAA

Timothy D. DeSchriver David K. Stotlar Western Carolina University of

University Northern Colorado

The goal of this paper was to analyze the cartel behavior of the National Col- legiate Athletic Association. The NCAA, with over 1,000 members, has over- seen intercollegiate athletic competition and established rules of play. In addition, the NCAA has maintained a cartel agreement to maximize profits for its members. However, to maintain a cartel, the expected costs of violating the agreement must be greater than the expected benefits of violation. Within this paper, an economic model using NCAA Division I men's basketball tournament revenue data was developed to determine when teams had an incentive to violate the cartel agreement-that is, commit a rules violation. Tournament revenue data from 1982 to 1990 was obtained for teams in six conferences

- f ~ E a f ~ P a e + f + c r e o a s t , and 151g q. 'l'he economic model revealed that teams in the Big East, Big 10, and Pacific 10 conferences had the greatest financial incentive to violate NCAA regulations. The information provided in this paper may be useful to intercollegiate athletic administrators who attempt to reduce the occurrence of rules violations and strengthen the cartel.

The National Collegiate Athletic Association (NCAA) is the largest intercollegiate athletic governing body in the United States. Along with other duties, the NCAA establishes rules of play, administers national championships, and determines student-athlete eligibility standards for over 1,000 members (Falla, 198 1). In addition to its governance role, the NCAA has attempted to use its regulatory power to create a cartel in the market for collegiate athletics in order to maximize profits for its members (Heisher, Goff, & Tollison, 1992). An important facet of maintaining any cartel agreement is to ensure that the expected costs of violating the agreement be greater that the expected benefits from remaining in the cartel. If this is not the case, members have no incentive to remain in the cartel (Waterson, 1988). For example, the economic power displayed by OPEC during the late 1970s and early 1980s diminished

Timothy D. DeSchriver is with the Department of HPER, Western Carolina Univer- sity, Cullowhee, NC 28723. David K. Stotlar is with the School of Kinesiology and Physi- cal Education, University of Northern Colorado, Greeley, CO 80631.

Economics of NCAA 389

due to the inability of its members to punish those nations that forced the sale price of oil below the price established by the cartel (Koepp, 1986).

Within the NCAA, a violation of the cartel agreement occurs when a member commits a rules violation such as the illegal payment or recruitment of an athlete. There may be a variety of reasons for the occurrence of NCAA violations. For example, violations have occurred due to ignorance concerning NCAA regulations, alumni/booster interference, and the illegal involvement of players with sports agents. Some rules violations may have occurred and continue to occur based on the belief that a program may benefit economically by committing violations.

Rules violations such as the illegal recruitment and payment of athletes may help teams acquire the premier athletes. These athletes may, in turn, lead to greater team success than if the program had not committed the rules violations. The more successful team at the Division I level will obtain additional revenue from such sources as ticket sales, booster donations, and NCAA tournament disbursements. The additional revenue, above the normal cartel level, is the expected benefit gained by violating the cartel agreement. However, the possibility exists that the NCAA will detect the rules violations and levy some type of penalty against the violator. Members that are found to have committed a violation face a variety of penalties, ranging from probation to temporary program termination (the "death penalty"). The NCAApenalty may negatively affect the amount of revenue obtained through participation in the sport. The financial loss associated with the penalties is the expected cost of violating the cartel agreement. If the expected cost of violation is greater than the expected benefit of violation, members will have little incentive to commit rules infractions. The purpose of this paper was to develop an economic model that calculated the expected costs and benefits associated with the occurrence of NCAA rules infractions.

There has been some research done on the cartel behavior of the NCAA. The most noteworthy being Fleisher, Goff, and Tollison (1992). Other work includes No11 (1990) and Mawson and Bowler (1989). However, most empirical research on the economics of collegiate athletics has centered on the computation of revenues, costs, and profits. Borland, Goff, and Pulsinelli (1992) found that profits were understated in a study conducted on the athletic department at Western Ken- tucky University. While the university reported a $1.2 million deficit, Borland, Goff, and Pulsinelli's research revealed that the athletic department finished with a $200,000 surplus.

Unlike earlier research, the purpose of this paper was to develop a statistical model that determined the expected costs and benefits of violating NCAA regulations. A fundamental problem when examining the revenues of collegiate athletic programs has been the lack of empirical data. The NCAA has issued a report on the financial revenues and expenses of intercollegiate athletics every 4 years since 1978, but these reports have failed to provide university-specific data (Fulks, 1994; Raiborn, 1978). To use such data, the empirical study in this paper was limited to revenues generated from participation in the Division I NCAA basketball tournament by universities in six major conferences. While these revenues were a small percentage of the total revenues in collegiate athletics (approximately 3% of Divi- sion I-A athletic budgets), the data allowed us to empirically represent the expected costs and benefits associated with violating NCAA regulations (Fulks, 1994). However, the methodology of calculating expected costs and benefits to violating the cartel agreement can be easily adapted as additional data become available.

DeSchriver and Stotlar

Financial Disbursement Policies

To build a model estimating the expected costs and benefits of committing an NCAA rules violation with respect to NCAA tournament revenues, the manner in which these revenues were disbursed must be discussed. Prior to 1991, the NCAA distributed payouts directly to tournament participants based on playing success. However, most conferences had revenue-sharing plans that distributed the payouts to all conference members. In this section, the researchers reviewed the conference policies regarding revenue sharing for teams in six conferences as well as the manner in which these conferences distributed revenues to teams that were on NCAA probation. This information has been used to develop a statistical model that predicted the expected costs and benefits associated with committing a violation.

There was no standard procedure that conferences followed in disbursing revenues. Discussion will center on the policies of six conferences: the Atlantic Coast Conference (ACC), the Big East, the Big 10, the Big 8, the Southeastern Conference (SEC), and the Pacific 10. The amount of revenue distributed through these plans was quite large; in 1990, over $35 million was disbursed to the 64 qualifying teams (NCAA Basketball Financial Analysis, 1993).

Since 1985, the NCAA basketball tournament has had a 64-team single elimi- nation format with competition occurring on three successive weekends in March and April. There have been six rounds, with two rounds played per weekend. As a team advanced further in the tournament, the amount of revenue it received increased. For example, all 64 teams that qualified in 1989 received a minimum of $250,200. However, a team that advanced to the Final Four received $1,25 1,000

- f ~ ~ B ~ ~ ~ ~ T ~ ~ ) r S I S , n i s poiicy was altered in 1991 with the signing of a new television contract between the NCAA and CBS.

The contract, which gave CBS the exclusive right to televise the 1991 through 1997 tournaments, has resulted in over $1 billion for the NCAA and its members. After the signing of the television contract, the NCAA implemented a new revenue disbursement plan that decreased the importance of individual team success in the tournament. First, a portion of the revenues has been disbursed to conferences, not qualifiers, as was the policy before 1991. Second, there have been three basic criteria for revenue distribution to the conferences and institutions. The first criteria has been the success of the conference in the tournament during the previous 6 years; over $40 million was distributed to conferences through this process in 1995. However, the amount of these revenues disbursed to individual institutions was determined by the conferences. Another $40 million was disbursed to institutions based on the number of sports in which they competed and the number of athletes that received scholarships. Last, $12 million was given to universities to finance academic support programs for student-athletes (NCAA News, 1995).

Revenue disbursements prior to the 199 1 contract differed substantially from the new plan and varied considerably among conferences. Of all the conferences, the ACC allowed its members to retain the highest percentage of their payout. They retained the full amount of revenue obtained by competing in the first round and 70% of the additional revenues gained after the first round. The remaining 30% of the post-first round dollars were split among all eight conference members (personal communication with T. Mickel, assistant commissioner of the ACC, Feb- ruary, 1993). Of the six conferences studied, ACC teams had the greatest financial incentive to be successful in the tournament.

Economics of NCAA

The Big East and Big 10 allowed qualifiers to retain 50% of the revenues generated by participation in the tournament. The other 50% was split equally among all conference members (personal communication with C. Plonsky, assistant to the commissioner of the Big East conference, February, 1993; personal communication with M. Rudner, assistant commissioner of the Big 10, February, 1993). Members of the Pacific 10 and the Big 8 kept the lowest percentage of their payout. These conferences pooled all revenues generated by member teams and divided them equally among all conference members (personal communication with T. Allen, assistant commissioner of the Big 8, February, 1993; personal communication with D. Lindbergh, assistant commissioner of the Pacific 10, February, 1993). Therefore, in 1988 when the University of Arizona, a Pacific 10 member, advanced to the Final Four, it received the same amount of tournament revenue as the University of Oregon, which did not qualify for the tournament. This same policy was in effect for the SEC and the Big 8. The only variation was that the SEC, which had 10 members throughout the 1980s, divided the revenues into 11 equal shares. Each school received one share, and the conference headquarters also retained one share to pay for administrative costs (personal communication with J. Watson, assistant to the commissioner of the SEC, February, 1993).

The policies for some conferences have been altered because of the new NCAA disbursement policy effective in 1991. However, the policies of the Pacific 10, the Big 8, and the SEC have remained the same. The total tournament revenue has been divided equally among the conference members. However, the SEC has added two new schools: the University of South Carolina and the University of Arkansas. They have divided the revenues into 13 shares, with the conference office retaining one share (personal communication with T. Allen, assistant commissioner of the Big 8, February, 1993; personal communication with D. Lindbergh, assistant commissioner of the Pacific 10, February, 1993; personal communication with J. Watson, assistant to the commissioner of the SEC, February, 1993).

The Big East has initiated a new policy since 1991. A Big East team has received $120,000 for every round in which they have competed. A team that advances to the championship garhe has played six games and receives $720,000 from the conference. The conference has used the money disbursed from the NCAA to make these payouts. In addition, after disbursing this money to members that qualify for the tournament, the remainder of the NCAA disbursement has been divided equally among the 10 conference members (personal communication with C. Plonsky, assistant to the commissioner of the Big East conference, February, 1993). This plan has maintained the incentive for Big East teams to qualify and advance deep into the tournament.

The Big 10 and the ACC have developed new policies since the inception of the CBS contract, patterning their plans on the Pacific 10's policies. The NCAA's disbursement to the Big 10 and the ACC has been divided equally among all conference members (personal communication with T. Mickel, assistant commissioner of the ACC, February, 1993; personal communication with M. Rudner, assistant commissioner of the Big 10, February, 1993). For conferences with this policy it has appeared that the incentive has been to get the largest possible number of teams in the toumament per year, since one of the NCAA disbursement criteria has been the number of tournament qualifiers over the past 6 years.

Another important feature of the disbursement of toumament revenue has been the different conference policies regarding distribution to teams on NCAA

DeSchriver and Stotlar

probation. A team can be placed on probation for violating any of the NCAA rules pertaining to collegiate athletic competition. As stated earlier, examples of penalties levied against teams have included probation, a ban on postseason competition, limitation of television appearances, and suspension. An important question that must be asked is, Can a team barred from competing in the postseason or on television share in the revenues generated from these sources? For example, Syracuse University was placed on NCAA probation and banned from participating in the 1993 basketball tournament. The obvious financial effect on Syracuse was that it did not have an opportunity to earn the $120,000 per round that the Big East dis- burses to tournament participants. However, would Syracuse be permitted to share in the revenues that the conference distributes to all members, regardless of tournament success? Conferences differ in how they handle such cases.

The Big 8 stated that a team that has been penalized by the NCAA was not permitted to share in revenues generated from competition for which the team has been barred. For example, if a Big 8 team was barred from competing in the NCAA tournament, that team would not share in Big 8 tournament revenues. However, the penalized team was permitted to share in all other disbursements, such as NCAA tournament and television revenues (personal communication with T. Allen, assistant commissioner of the Big 8, February, 1993).

SEC teams found in violation of NCAA regulations have been punished more severely than violators in any of the other five conferences. The conference has not allowed a team on probation to share in any revenues generated by that sport. Thus, if the University of Tennessee basketball team was not permitted to compete in the postseason tournament, it did not share in the revenues generated from this - source -- or an_;ytelevision contr_acts_that~cooer~basketball3ennes~ee~woulL have been permitted to share in revenues generated from all other sports, primarily bowl and football television revenue (personal communication with J. Watson, assistant to the commissioner of the SEC, February, 1993).

The ACC policy regarding the revenue sharing privileges of its teams varies depending on the seriousness of the violations. When a team has been placed on probation by the NCAA, the member institutions have decided by majority vote whether the team was allowed to share in revenues. Through discussion with the Assistant Commissioner of the ACC, it was found that, in general, teams on probation for serious rules violations have not been permitted to share in revenues for that sport. However, the schools have been permitted to share in revenues from other sports (personal communication with T. Mickel, assistant commissioner of the ACC, February, 1993).

The Big East and Big 10 policies regarding violators have been the most lenient. In these conferences, violators have been permitted to maintain their full share of revenues. So, to answer our earlier question-yes, Syracuse would receive its full share of the NCAA basketball tournament disbursement (personal communication with C. Plonsky, assistant to the commissioner of the Big East conference, February, 1993; personal communication with M. Rudner, assistant commissioner of the Big 10, February, 1993). Syracuse would also receive its full share from all other revenue sources. However, there is still an expected loss in revenue for Syracuse. As stated earlier, the Big East pays its members $120,000 for every round they play in the tournament. Syracuse would have missed the opportunity to earn this revenue.

The Pacific 10 policy regarding teams found in violation has not been strictly


defined. In general, the Pacific 10 has handled this situation on a case-by-case basis. According to the Assistant Commissioner of the Pacific 10, teams on probation usually have been permitted to remain in the revenue-sharing plan (personal communication with D. Lindbergh, assistant commissioner of the Pacific 10, February, 1993). For this analysis, it was assumed that a Pacific 10 team on probation shares in tournament revenues.

Empirical Analysis of the Incentive to Violate NCAA Regulations

The empirical analysis was undertaken in two phases. First, a theoretical model was developed that determines when it was beneficial for a team in any of the six conferences to commit an NCAA rules violation. Second, a regression equation was constructed to calculate predicted values of the expected costs and benefits associated with violations for teams in the six conferences. The combination of the theoretical model and the regression equation allowed us to determine which teams had the greatest incentive to commit NCAA rules violations. It must be restated that this model has dealt solely with revenues obtained through competition in the NCAADivision I Men's basketball tournament; all other sources of revenue, such as television rights fees and gate receipts, were ignored.

Several assumptions were imbedded in the proposed theoretical model: 1. Fielding a more successful team was an incentive for an athletic program

to commit a violation wherein a more successful team had a greater probability of qualifying and advancing in the tournament, which, in turn, led to revenues greater than the normal share of cartel revenues.

2. The increased expected revenue was the benefit of committing a violation. 3. An expected cost associated with a violation occurred if a team was de-

tected and punished by the NCAA, resulting in restrictions on tournament qualifi- cation and revenues.

4. Costs and benefits varied across conferences, depending on the different revenue-sharing and probation policies described previously.

5. Schools in a given conference were assumed to be identical. For example, Indiana University and Northwestern University both have competed in the Big 10. Historically, Indiana has been a basketball powerhouse while Northwestern has been a perennial loser. Therefore, holding all else constant, one would have expected Indiana to have a greater probability of qualifying for the tournament. In treating Indiana and Northwestern as similar, the model did not capture this effect. However, two similar regression equations were developed with team and conference qualitative variables replacing the specified revenue-sharing plan qualitative variables. An F-test revealed no significant difference in the predictive power of the three regression equations. Therefore, the conference qualitative variable was used for this analysis.

6. The probability a team was placed on probation was a constant, and the calculation of costs and benefits was limited to a single basketball season. In addition, the calculation of costs and benefits assumed that if a team violates NCAA rules, it benefited for only 1 year, and the length of the probation was limited to 1 year.

Given these admittedly restrictive assumptions, the following framework was developed for determining the expected benefits and costs of violation. The expected benefit for team I of violating NCAA rules was as follows:

394 DeSchriver and Stotlar

where

EBI = expected benefit to team i from committing a violation; P = probability of advancing one more round due to violating NCAA

regulations (0 < P < 1) ; R, = additional revenue to team i from advancing one more round.

This equation can be rewritten as

EB, = (x Pj) X Ri (2) , = I

The expected cost of violation for team I was

where EC, = expected cost to team i from violating NCAA regulations; Q = probability of being placed on probation by the NCAA for a rules

violation ( 0 < Q < 1 ) ; LI = total annual loss of revenue to team i due to being placed on probation.

Thus, we see there was an incentive for team i to violate NCAA regulations if

EB, > EC, (5 )

We also see the expected costs and benefits to violation were dependent on P and Q, the probability of advancing an additional round and the probability of being placed on probation. The above equation was rewritten as

P - P > A Q ( 1 - P ) Ri

The result was a model that allowed discussion of the incentives for teams to commit a violation.

As P, the probability of advancing an additional round due to violation approached zero, Q must have simply been greater than zero for there to have been no incentive to commit a violation. As Q approached zero, the probability of being caught violating became smaller, and all teams had an incentive to violate because the expected cost tended to zero. As P and Q both approached one, the left side of equation 7 approached 5. In this case, the loss associated with being on probation, L,, must have been at least five times greater than RI, the additional revenue from advancing another round, for there to have been no incentive to violate.

To complete the model, Li and R1 were estimated. A regression equation


provided estimates of the additional revenue obtained by advancing another round and the total annual loss associated with being placed on probation. An independent estimate of Q was obtained that predicted, for the six conferences, the value of P that resulted in violations.

Before discussing the regression model, a brief description of the data is appropriate. Tournament revenue and NCAA probation data were obtained for the 55 institutions that competed in the 6 conferences discussed earlier. All revenue data was converted to inflation-adjusted dollars using the Consumer Price Index. The data covered 1982 through 1990. This time period seemed appropriate given that the NCAA initiated the new tournament revenue sharing plan in 1991, which greatly affected the disbursement of revenues.

The following regression model was used to estimate expected costs and benefits of being placed on probation (results are contained in Table 1):

where the dependent variable was REV, = expected inflation-adjusted NCAA basketball championship revenues for team i (in thousands of dollars); the explana- tory variables were RD = the number of rounds played by team i (maximum = 5); the revenue-sharing plan qualitative variables were Cl = 1 if team i was in a conference that allowed a tournament qualifier to retain half of the payout and the other half was divided equally among all conference members (such as in the Big 10 and Big East); 0 otherwise; C2 = 1 if team i was in a conference that divided all tournament revenues equally among all members (such as in the SEC, Pacific 10, and Big 8); 0 otherwise; probationary plan qualitative variables were PI = 1 if team i was on probation and in a conference that did not permit probationary teams to share in revenues; 0 otherwise; P2 = 1 if team i was on probation and in a conference that permitted probationary team to share in revenues; 0 otherwise; CR = the number of tournament rounds played by all conference teams, excluding team i; RTR = inflation-adjusted revenues the NCAA generated from the toumament (in millions of dollars).

The RD variable was included because the amount of inflation-adjusted revenues was a function of the number of tournament games played by a team. Given that the increase in revenue for team i from advancing an additional round de- pended on the revenue-sharing rule for team i's conference, the RD variable was interacted with Cl and C2. Also, given that all conferences had some type of revenue-sharing plan, the number of tournament games played by other conference teams also determined the level of revenues. The CR variable was included to handle that situation, and similar to the RD variable, it was interacted with the revenue-sharing plan qualitative variables.

In addition, the revenue-sharing policy and probationary policy qualitative variables allowed for the prediction of the expected revenues for teams in each conference, depending on their probationary status. As stated earlier, it was determined that revenue-sharing policy was statistically more important than the specific team or conference affiliation in predicting real revenues. Thus, a revenue- sharing qualitative variable was used as opposed to a team or conference variable.

Last, there was an increase over time in the inflation-adjusted dollar payout per round to qualifying teams. The RTR variable was included to account for this


trend. The payout per round was a function of the total revenues the NCAA received from the tournament. The increase in the inflation-adjusted tournament revenues posed a problem in the statistical analysis due to the presence of serial correlation. Serial correlation occurs when the regression equation error term in one period is correlated with the error term in the previous period. To correct for serial correlation, originally the value of the RTR variable in the previous period was included as an independent variable. This statistical technique was used success- fully by Baade & Tiehen (1990) in their attempt to analyze Major League Baseball attendance from 1969 to 1987. However, the lagged RTR variable was excluded from the final regression equation because it was not found to be statistically significant.

Results and Conclusions The regression equation (Table 1) revealed several interesting results. First, an ACC team had an increase in expected revenue of $118,139 for every additional round played in the tournament, holding all else constant. A team in the Big East or Big 10 had an increase in expected revenue of $77,246 and a SEC, Pacific 10, or Big 8 team's expected revenues increased by $15,985 for every additional round played in the tournament. These numbers were used to represent R, for each conference. Second, the parameter estimates for CI and C2 were both negative. If CI and C2 were zero, team i was in the Atlantic Coast Conference, and expected revenues for a team in the ACC were $17,673 greater than those for a team in the Big 10 and the Big East. Expected revenues for an ACC team were also $26,899

~eate~theexpecte&wen-ble~-f~ra-team-in-thePa~ifi~l Q,Big&or-theSEC. Examination of the probation policy qualitative variables (PI and P2) revealed that a team in a conference that did not allow revenue sharing while on probation had expected revenues $191,244 less than a team that was not on probation. In addition, a team on probation in a conference that allowed the continuance of revenue sharing received $1 1,220 less than a team not on probation. However, the

Table 1 Estimation of Inflation-Adjusted NCAA Basketball Tournament Revenues, 1982-1991

Mean Parameter Standard T for HO: Variable value estimate error Parameter = 0

RD RD*Cl RD*C2 P1 P2 CR CR*Cl CR*C2 RTR

F value = 375.574. Adjusted R-square = .8724. Degrees of freedom = 493.


parameter estimate for P2 was not significantly different from zero. Therefore, L,, the loss of revenue due to cheating, was not statistically different from zero for teams in these conferences (Big East, Big 10, and Pacific 10).

For every $1 million increase in tournament revenue collected by the NCAA, team i received an additional $3,968. Therefore, the sum of the increased expected revenues for the 55 teams studied was $218,240. In other words, 21.824% of a $1 million increase in tournament revenues for the NCAA was distributed to these six conferences. Last, given team i was in the ACC, every additional round played by another team in the conference increased the expected revenue for team i by $4,701. If team i was in the Big 10 or Big East, an additional round played by another conference team increased team i's expected revenues by $7,909. If team i was a Pacific 10, SEC, or Big 8 member, its expected revenues increased $14,577 for every additional round played by another conference team. The regression model also allowed for an estimate of expected revenues for teams in each conference while they were either on or off probation. By using the mean of each of the quan- titative dependent variables and the probationary and revenue-sharing qualitative variables, the annual lost revenue due to a team being placed on probation was calculated. These results are contained in Table 2.

As can be seen, teams in the ACC had the highest nonprobation revenues. This result corresponded with the revenue-sharing rules previously discussed. Since ACC teams were not permitted to share in revenues while on probation, it was of no surprise that they suffered the greatest loss from being placed on probation.

Another interesting result of the empirical data was that P2 was not statistically significant at a = .05. Therefore, the change in revenues for a team placed on

Table 2 Expected NCAA Tournament Revenues for Teams in Six Major Conferences

Expected additional

Expected revenue due to Expected Expected annual lost advancing an

revenues when revenues when revenue due to additional round Conference not on probation on probation probation (L,) (R,)

ACC $189,697 $0 $189,697 $118,139 Big East 172,024 172,024 0 77,246 Big 10 172,024 172,024 0 77,246 Pacific 10 162,798 162,798 0 15,985 Big 8 162,798 0 162,798 15,985 SEC 162,798 0 162,798 15,985

Note. R, is the regression coefficient for the RD variable, number of rounds played, which is interacted with the revenue-sharing plan qualitative variables. The expected additional revenue for team i from advancing an additional round is the sum of P,, P,(C1) and P,(C2). For example, C1 and C2 equal zero for an ACC team. Therefore, the expected additional revenue for an ACC team from advancing an additional round is the value of P,, which is $118,139. This approach is used to calculate R, for teams in all six conferences.


probation in a conference that allowed revenue sharing was not significantly different from zero. In this case, Li = 0 and equation 7 can be rewritten as

If one assumes that P and Q were greater than zero but less than one, all teams in the Big East, Big 10, and Pacific 10 always had an incentive to commit a violation, and the expected cost was zero.

The model was powerful because it allowed for the estimation of the value of P for a variety of values of Q and L,. If we assume Q was the same for teams in all conferences, it can be used to determine the minimum probability of advancing an additional round above which it was not in the best interest of a team to commit a violation.

Let's use an ACC team as an example. If we arbitrarily select the value of Q as .1 (i.e. the probability of being caught committing an NCAA violation was lo%), and L, = $189,697, equation 6 can be rewritten for an ACC team as

p - p6 189,697 ( I - P ) '(118,139 )( . I )

Solving for P we obtained P > .138. A team in the ACC had an incentive to commit a violation if it believed that the probability of advancing an additional round by committing a violation was greater than 13.8%. This same type of rea- soning produced a minimum P value of .497, or 49.7%, for the Big 8 and SEC conferences. Additionally, if we assume that P = SO, the probability of advancing an additional round by committing a violation is 50%, then Q = .602 for ACC teams and Q = .095 for Big 8 and SEC teams. In other words, if an ACC team believed that P = SO, it had an incentive to commit a violation if it believed that the probability of being caught committing a violation is less than 60.2%. The Q value was 9.5% for teams in the Big 8 and SEC. These empirical results allowed for the determination of when a team in any of the six conferences had an incentive to commit a violation for all possible values of P and Q. The assumption that Q = 1 and P = .5 were constant across schools was arbitrary, but it did allow the development of a gauge of the incentive to violate NCAA rules.

In summary, the regression results allowed for a comparison of the violation incentives across conferences. Assuming Q and P were identical across conferences, the Big East, Pacific 10, and Big 10 teams had the greatest incentive to violate. The ACC was next, and the Big 8 and SEC had the least incentive.

As mentioned earlier, there may be a number of reasons for the incidence of rules violations. However, given the amount of revenue that may be gained through fielding a more successful team, the occurrence of violations based on economic gain is plausible. Unfortunately, given the lack of available data, the analysis has been restricted to NCAA tournament revenues.

Additionally, it is difficult to measure the predictive power of the model. Ideally, a comparison between the probability of rules violations as predicted by


the model and the actual occurrence of violations by conference teams would allow for such an empirical analysis. However, the incidence of infractions detected by the NCAA may not be an accurate measure of the number of occurrences. Fleisher et al. (1992) found that historically the NCAA has not uniformly detected violations across institutions. Institutions that have had an increase in winning percentage over a short period of time have also had the highest incidence of NCAA penalties. Traditional powers have rarely received NCAA sanctions. Therefore, it appears that the number of infractions acted on by the NCAA may not be an appropriate measure of the number of violations committed over the same time period. This has made it difficult to analyze the predictive power of the model.

The model developed in this paper is embedded in the theory that the expected cost associated with a violation of the cartel agreement must be greater than the expected benefits. If this does not occur, cartel members will have an incentive to commit violations. The results of this study may be helpful to the NCAA and conferences as they attempt to minimize rules violations. It is apparent that with respect to NCAA tournament revenues, of the six conferences studied, teams from the Big East, Big 10, and Pacific 10 had the greatest incentive to commit rules violations. The economic cost associated with committing such violations must be greater than the economic benefit, or member teams will have less incentive to refrain from such behavior. Some steps have been taken, such as the development of the new NCAA disbursement policy in 1991, to decrease the economic benefits from fielding a successful team.

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