Evaluation of soccer players in Serie A: a data-driven approach

Abstract

Thanks to the technological innovation of electronic motion recording methods, the use of quantitative data in sport to measure performance has increased significantly in recent years, enough to represent a new specialty of statistical studies. The most relevant literature concerning quantitative models for evaluating the price of a football player is examined.

Through OLS, an empirical analysis is conducted that can understand and predict what are the performance variables that can determine a player's trading price. The data relate to the exchanges that took place in the top Italian football championship (Serie A) between 2017 and 2019. The variables that determine the price change due to the role, therefore there is a strong specialization by role. The performance does not fully explain the price changes of the players. Furthermore, the higher investments are not necessarily proportional to the sporting results of the team.