🤖 AI Summary
This study addresses the challenge football clubs face in balancing squad enhancement against competitive transfer markets under budget constraints. The authors propose a weighted multi-objective optimization framework that integrates player performance modeling—based on linear mixed-effects models—with transfer pricing and financial limitations. For the first time, the framework incorporates an independent private values auction model coupled with a stochastic reserve price mechanism to simulate multi-club bidding dynamics and generate optimal end-of-season recruitment strategies. Empirical validation using 2018–19 English Premier League data demonstrates that the approach effectively replicates real-world market behavior and quantifies both the competitive effects of transfer decisions and their impact on team performance.
📝 Abstract
The football transfer market is a complex, dynamic environment in which clubs compete to acquire players who strengthen their squads. While several frameworks estimate a player's worth, a comprehensive approach that captures both squad optimisation and transfer market dynamics remains limited. In this paper, we propose a quantitative framework for optimising football transfer strategy under budget constraints, integrated with a competitive bidding paradigm. Using data from professional football leagues, we construct player performance and transfer price models using linear mixed-effects frameworks that incorporate player characteristics, recent performance, team context, and league effects. The predicted ratings and estimated transfer prices are then integrated into a weighted multi-criteria constrained optimisation framework that determines a club's transfer activities at the end of the season. Finally, these optimal transfer decisions are embedded within an independent private-value auction model with a random reserve price to analyse market behaviour when multiple teams compete for the same player. We illustrate our approach using the 2018-19 season of the English Premier League to demonstrate its ability to capture transfer-market dynamics.