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Squad Optimizing: Integrating Tactics into Football Team Composition Problem via Integer Programming

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  • Guilherme Pettene Dantas

    (UFRGS)

  • Marcus Ritt

    (UFRGS)

Abstract

Football presents a rich domain for applying optimization techniques, as clubs continuously strive for excellence from their players and staff to secure wins. The challenge of football team composition has recently gained attention, spurred by the increasing availability of data. In this article, we introduce a novel integer programming model that aligns seamlessly with the tactical goals of any club and manager. We evaluated the effectiveness of our model across English Premier League clubs. Our findings indicate a consistent enhancement in the skill levels for every squad, irrespective of their financial constraints. Furthermore, the model achieved this goal while exploiting market inefficiencies, allowing for reduced wage expenditures. Lastly, the squad’s overall skill is sustained throughout the optimized period by acquiring young prospects.

Suggested Citation

  • Guilherme Pettene Dantas & Marcus Ritt, 2025. "Squad Optimizing: Integrating Tactics into Football Team Composition Problem via Integer Programming," Environment Systems and Decisions, Springer, vol. 45(3), pages 1-14, September.
    • Handle: RePEc:spr:envsyd:v:45:y:2025:i:3:d:10.1007_s10669-025-10033-2
    DOI: 10.1007/s10669-025-10033-2
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    References listed on IDEAS

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    5. Vineet M. Payyappalli & Jun Zhuang, 2019. "A data-driven integer programming model for soccer clubs’ decision making on player transfers," Environment Systems and Decisions, Springer, vol. 39(4), pages 466-481, December.
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