Who’s Worth the Millions? Rethinking Football Valuation Through Predictive Modeling in the Big Five European Leagues

This paper explores the multifaceted determinants of football player market valuations in the Big Five European leagues between 2019 and 2024. Using a rich dataset of 1,006 players, the study combines econometric techniques, machine learning models, and behavioral indicators to assess how performance metrics and player notoriety impact market values. The analysis confirms the predominance of subjective assessments, notably player rating and potential, as the strongest predictors, while also highlighting the emerging role of social media as a commercial asset. Results from fixed effects regressions and Random Forest models suggest that market values are driven by a combination of current ability, perceived future potential, and off-field visibility. By integrating both objective and subjective dimensions, this study provides a robust, data-driven framework for understanding and predicting player valuation in contemporary football markets. JEL codes : C55, C53, D40, Z22