Data-driven approach to defining football styles in major leagues

Andres Chacoma and Orlando V. Billoni

Chaos, Solitons & Fractals, 2025, vol. 200, issue P1

Abstract: This study proposes a data-driven methodology to define and compare styles of play in football, with a focus on the top four teams from the English, French, German, Italian, and Spanish leagues during the 2017/2018 season. Using event-based metrics derived from possession intervals, we constructed a feature matrix representing tactical behaviors at the match level. A Principal Component Analysis, followed by Varimax rotation, revealed four interpretable and distinct emergent playing styles. By projecting matches onto this style-based representation, we evaluated stylistic differences across leagues. A one-way Anova test confirmed significant inter-league variation in style prevalence. Furthermore, a random forest classifier successfully identified leagues based on the style representation, and a game-theoretic feature importance analysis uncovered consistent associations between specific styles and leagues. These findings provide a robust, reproducible framework for empirically analyzing football playing styles across competitive contexts.

Keywords: Complex systems; Game theory (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:200:y:2025:i:p1:s0960077925009397

DOI: 10.1016/j.chaos.2025.116926

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