Quantifying NIL Superstardom: Athlete Mobility, Digital Capital, and Structural Disparities in Collegiate Sports

Abstract

The rapid emergence of Name, Image, and Likeness (NIL) rights in collegiate athletics has transformed the economic landscape of amateur sports, granting student-athletes new opportunities to monetize their personal brands. Yet, despite this democratization of commercial rights, NIL deal activity and valuation remain highly concentrated among a small subset of athletes. This thesis investigates the factors that define and drive NIL superstardom, testing the hypothesis that NIL success is not determined by athletic performance alone but arises from a multifaceted blend of media engagement, institutional context, and structural market dynamics. To explore these relationships, the study constructs a novel multi-source panel dataset encompassing approximately 4,000 NCAA athletes their respective NIL disclosures from July 2021 through March 2025. Using an integrated empirical strategy, we apply linear regression models, ElasticNet and XGBoost ensemble methods, K-Means clustering, and simulation-based counterfactual analyses to quantify the drivers of NIL deal volume and valuation, and to forecast potential athlete trajectories. The findings reveal that while athletic performance remains foundational, social media engagement consistently emerges as the most powerful predictor of NIL outcomes. Team success metrics further amplify individual valuations, while transfer status alone exhibits limited standalone impact. Crucially, gender-based simulations expose significant structural disparities: female athletes, even with comparable engagement and performance levels, face persistent undervaluation. This research advances both theory and practice by extending Superstar Theory to the NIL context, offering actionable insights for athletes, institutions, and policymakers aiming to navigate this evolving market and promote a more equitable collegiate sports economy.