Noah Shelton & John Simmons

Introduction

College athletics are vastly popular and it is widely known that college athletes have to attempt to find the perfect balance between student and athlete. It is often discussed whether or not student athletes should stay in school and finish out their degree programs, or leave college early and go play professionally in their respected sport. There is a moderate level of disagreement on this topic; some believe if a student-athlete is able he should go follow his dream of playing professionally and bypass school, but others believe student-athletes should finish their degree no matter their skill level because not all student-athletes can go pro and its nice to have a safety net if a career-ending injury occurs or if an athlete wants a job in their degree field upon retirement from the sport. Our paper touches on an aspect of this topic of student-athlete graduation and explores the idea that a team’s winning percentage can positively or negatively affect a team’s graduation success rate. This paper investigates the relationship between team winning percentages and team graduation success rates and raises the question: In the National Collegiate Athletic Association (NCAA) Football Bowl Subdivision (FBS) and NCAA Division 1 Men’s Basketball, is winning percentage negatively related to the team graduation success rate? An emphasis is placed on correlations between the measurements of a team’s success along with the resulting graduation success rate. The principal finding is that, in the FBS and NCAA Division 1 Men’s Basketball, there appears to be a positive correlation between team success and school type. On the contrary, winning percentage and success level negatively affects graduation rates for college football teams.

This question is important for a few reasons because it is a university’s responsibility to provide an environment that fosters academic success for their athletes. First, this study allows us to investigate whether student-athletes have adequate time to balance the demands of school and their sport. Also, using team winning percentage as a measure to determine graduation rate allows us to see if there is an impact if athletes on a team with a losing record have less incentive to work hard in school because they don’t need to keep their grades up to be on the active roster, or if a losing record and no postseason events allows individuals more time to study, thus leading to a higher graduation rate. On the other hand, we can investigate if a winning record leads to a higher graduation rate because individuals have to keep their grades up to be eligible to participate or if more on the field success negatively affects graduation rate due to more time being dedicated to the sport. Hopefully, by understanding the relationship between team winning percentage and team graduation success rate, colleges and universities around the United States will have more information available to them about the demands of a student-athlete and how they can, if need be, improve the college education and graduation rates of their student-athletes.

Our paper investigates the impact of team winning percentage on team graduation success rate. There are not many articles that investigate this intriguing relationship, but there is one of Amato (1996) that investigates the effect of the bowl system in NCAA Football on football player graduation rates. They found no significant impact of team success on player graduation rate, and the only negative effects found related to the postseason bowl system. These findings extend from the fact that postseason practice hours take away from the graduation prospects of the football players.

Our paper differs from that of Amato (1996) because we investigate both NCAA Division 1 Football Bowl Subdivision (FBS) and NCAA Division 1 Men’s Basketball. We also use more current data, as we gathered data from the timeframe that spanned from 1998 to 2009 and introduced additional variables such as type of institution, city population and student enrollment numbers.

Model Specifications

The dependent variable of the regression model is team graduation success rate, GSR, which is, according to the NCAA, “the proportion of first-year, full-time student-athletes who entered a school on athletics aid and graduated from that institution within six years.” The variables that we considered in our model include measures of team success, academic quality, and the environment of the college or university. We gathered GSR statistics from the official NCAA GSR database and referred to sportsreference.com for team success statistics. Table 1 gives the means and standard deviations for each of the variables included in the study. These variables are explained below.

Academic Quality Variable

The variable (PRIVATE) is a dummy variable having a value of one if the college or university is private, and zero if the academic institution is publicly supported. Our reasoning for the PRIVATE variable is to control for the assumption that private schools offer a higher quality education than publicly funded institutions. Also, private schools may have a structure that resembles a private firm, which implies the school has a greater incentive to graduate students. Under these assumptions, a positive sign is expected for this variable’s coefficient since a private school is likely to positively affect the graduation rates of its athletic teams.

Table 1. Variable Descriptive Statistics Division I Men’s Basketball Schools FBS Schools Variable Description and Range Mean SD Mean SD GSR Team graduation success rate (0-100) 67.49 20.99 67.73 12.75 WIN% Team Win Percentage (0-1) 0.51 0.18 0.51 0.22 PRIVATE Private school dummy (1 = private; 0 = public) 0.31 0.46 0.15 0.36 CITY Local City Population (1,308-8,491,000) 477,440 1,225,671 302,255 510,218 ENROLL School Enrollment (1,608-110,000) 18,790 13,853 27,170 12,199

Team Success Variable

The most common and accepted way to measure the success of a team is by the win-loss record. The variable (WIN%) measures the percentage of wins that a team achieved for each season during the 1998-2009 timeframe. The expected sign of the coefficient for WIN% is more ambiguous than other variables considered in this model. One assumption is that the more success a team has, the less time that players have for academics. Another assumption expects a lower WIN% to positively affect a team’s graduation rate. If a team is unsuccessful, and the likelihood of postseason participation is low, it would be expected that players could have more time for academics. Also, prestigious academic institutions tend to allocate less money to athletics, which implies a lower win-loss record.

Environment Variables

The variable (ENROLL) measures the relevant academic year enrollment at each college or university. Our assumption surrounding this variable is a that an institution with a large enrollment is likely to be flexible with admission requirements, which could lead to a tendency to accept athletes that are less proficient in academics. Also, a larger school is likely to have an impersonal environment, which could be capable of lowering the graduation rates of athletes. The expected sign for the ENROLL variable in our model is negative.

The variable (CITY) measures the population size where a college or university is located. A common assumption is that a larger population implies a larger opportunity for recreational and nonacademic activities. If a team is located in a large city, athletes are likely to trade study time for nonacademic activities, which could lower the rate at which athletes graduate. The expected sign of the CITY variable is negative in our model.

Results

A data set was collected on all the above variables for 118 of the 128 FBS universities and colleges, and for 310 of the 351 NCAA Division I Men’s basketball schools. All the data was obtained from the sources that were mentioned in the previous section.

Table 2. Regression results: relationship between football/basketball player graduation success rate, win percentage, school type, city population, and enrollment 1998-2009 (dependent variable: GSR) Variable Division I Men’s Basketball Schools (A) FBS Schools (B) Intercept 55.98 (21.18) Coef. (t-stat) 70.46 (38.45) Win% 12.34 (6.29) -5.32 (-2.07) Private 15.50 (18.39) 15.11 (15.38) CITY -0.000001 (-3.58) -0.000005 (-8.39) ENROLL -0.00010 (-3.53) -0.0001 (-4.76) R2 0.13 0.25 N (schools) 238 118

Table 2 presents two regression estimates for graduation success rates, GSR, for football and basketball players. The first regression result within this table includes the coefficients for our model using the sample of men’s basketball schools. The second regression result contains the coefficients using the sample of FBS schools. In Column (A), the regression results for Win% and PRIVATE show coefficients of significant value. According to these results, in men’s basketball, team success and school type are positively correlated with team graduation rates. The finding that team success is significantly positive in estimating team graduation rates is contrary to our hypothesis. In Column (B), the regression results for PRIVATE was of similar significance. Also, while both environment variables produced negative coefficients as expected, the effect is minimal. The CITY and ENROLL coefficients are approximately zero for both FBS and men’s basketball. Therefore, when it comes to the local city population or the enrollment of an academic institution, it seems that neither affects graduation rates of student athletes.

The most important finding of this study is represented by the contrast in comparing the effect of team success on graduation rates between basketball and football. Column (B) shows that our indicators of team success, Win%, negatively affects the graduation rates of teams in college football. This finding agrees with our previously mentioned hypothesis. It seems that schools with FBS teams are either accepting football players with less academic skill, or, the demands of being a player on a FBS team requires a notable tradeoff between time spent studying and athletics.

There are two possible explanations for the negative correlation between team success and graduation rates in our college football sample. First, football at the FBS level requires intense physical and mental preparation. This could cause players on a successful team to substitute study time for extra athletic preparations for longer periods of the year. In contrast, a player on an unsuccessful team may choose to focus on academics since the motivation for devoting time to a losing team could be low. Second, football players on a successful FBS team are likely to envision a future in pro football. This expectation of playing pro football could lead to decreased study time and more athletic preparation or even the possibility of leaving college early to enter the National Football League (NFL) draft. Both situations mentioned have the possibility of causing a player to delay college graduation.

The R2 values for the men’s basketball sample (0.13) and the FBS sample (0.25) calculated from our model suggest that the academic and team success variables are slightly more significant in explaining the variations for FBS teams when compared with Division I basketball teams. These findings suggest that FBS teams’ graduation success rates are more closely related to the academic quality of their schools and the team’s success than Division I basketball teams. One possible explanation for the slightly less significant correlation indicated between our model’s variables and Division I basketball graduation rates is the frequency of players who leave for the National Basketball Association (NBA) after their freshman year. The high turnover rate of college basketball players is likely to cause graduation rates to decline for some schools regardless of the team’s success.

Conclusion

Our analysis in this paper determines that a higher winning percentage for a private university in men’s basketball leads to significant, positive correlation with graduation success rate. It also determines that lower graduation rates prevail for college football teams that find success on the field. The college football results are similar to those of Amato et al. (1996) and our paper confirms their findings that success on the field and postseason prowess leads to lower graduation success. However, in response to our research question, only in the NCAA FBS does winning percentage negatively relate to the team graduation success rate.

Since a university’s primary responsibility is to foster an academic environment and help steer its student population to success post graduation, universities should strive to have a high graduation success rate regardless of on the field production. Perhaps one solution could be for the NCAA to implement policies to limit practice hours across the league so student-athletes can better balance school and sport.

Our conclusions in this paper are subject to several limitations. First, it does not take into account the ongoing conflict universities face to maximize sports revenue and deliver a top-notch athletic program while simultaneously harboring an excellent academic environment. Second, our paper does not perfectly adjust for certain college sports phenomena such as “one-and-dones” and leaving school early in pursuit of dreams of playing their respected sport professionally. Lastly, it is unclear whether these results can be generalized and applied to other collegiate sports outside of Division I college football and men’s basketball (including women’s sports and lower divisions). Those specifications are outside of the scope of this paper and will require future research in the field of college sports and graduation rates.

References

Amato, Gandar, Irvin Tucker & Richard Zuber. 1996. Bowls versus playoffs: The impact on football player graduation rates in the national collegiate athletic association. Economics of Education Review 15: 187-195.

“Graduation Rates,” National Collegiate Athletics Association, accessed March 17, 2017, http://www.ncaa.org/about/resources/research/graduation-rates.