Tyler Jablonski – University of North Carolina at Chapel Hill
Jonathan A. Jensen – University of North Carolina at Chapel Hill
Nels Popp – University of North Carolina at Chapel Hill
Bradley Bates – University of North Carolina at Chapel Hill
More than 85% of NCAA Football Bowl Subdivision (FBS) athletic departments rely on some form of allocated revenue, such as student fees or other type of subsidy from their respective university. However, there is no standard operating procedure that governs the allocation of this support. As a result, it can be difficult for both athletic and academic administrators to compare each institution’s allocated revenue against other institutions, which makes it challenging to justify their own allocated revenue streams. Thus, this study seeks to identify various factors that are predictive of the amount of allocated revenue to athletic departments, then utilize the most influential factors to create a predictive model that estimates how much allocated revenue each athletic department should receive. Data was collected across 107 public FBS institutions. Results demonstrate that variables representing enrollment at Group of Five institutions, changes in conference affiliation, game attendance, graduation rates, and total university expenditures were statistically significant predictors of allocated revenue. In addition to providing empirical evidence of the efficacy of predictive modeling in the context of intercollegiate athletics finance, the model assists both athletic and academic administrators in determining an optimal level of allocated revenue based on a variety of factors.