Assessment of the market value of Liga MX footballers based on their sporting performance and qualitative variables in the 2021-2022 season

This work identifies the key variables influencing the market value of Liga MX soccer players, using performance information from the 2021-2022 season and other qualitative data. We employed three algorithms to predict the market value assigned by Transfermarkt: multiple linear regression, decision trees, and random forests. According to the model with the lower mean squared error (random forests), the performance variables with the greatest impact on a player's market value are total actions, dribbles, and duels in which the player participate. In addition to performance in the previous season, highly relevant qualitative variables include the player's team, contract year, and participation in the national team. We recommend that Liga MX clubs use similar analytical methods to allocate their financial resources more efficiently.