Money Making Matching Markets: Analyzing Student-Athlete Sorting and Welfare Outcomes under NCAA NIL-Policy

Abstract

This paper studies how the introduction of Name, Image, and Likeness (NIL) policy affects student-athlete welfare and sorting in NCAA Division I athletics. I develop a two-sided matching model that combines a predicted NIL earnings framework, a conditional logit model of school choice, and a deferred acceptance algorithm to simulate equilibrium outcomes. The results show that NIL generates large increases in average athlete welfare, but also substantially increases inequality, with gains concentrated among high-ability and high-visibility athletes. In addition, NIL shifts sorting patterns away from performance-based matching toward schools with larger market size and greater commercial opportunities. Allowing preferences to adjust reinforces this pattern, suggesting that NIL affects both income and how athletes value school characteristics. A counterfactual revenue-sharing policy increases welfare further and modestly reduces inequality, but does not reverse the market-oriented allocation of talent. These findings highlight how NCAA compensation reforms can increase total surplus while reshaping the distribution and structure of equilibrium outcomes.