Reassessing the impact of shared experience in football

This study investigates the impact of shared experience on football performance through macro-level (match outcomes) and micro-level (passing dynamics) analyses. Using machine learning models on 19,721 matches, the macro study found that conventional metrics like FIFA rankings and team strength over...

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Bibliographic Details
Published inJournal of big data Vol. 12; no. 1; pp. 157 - 19
Main Authors Le Coz, Sebastian, Carling, Christopher, Houde, Titouan, Imbach, Frank
Format Journal Article
LanguageEnglish
Published Cham Springer International Publishing 08.07.2025
Springer Nature B.V
SpringerOpen
Subjects
Big Data and Data-driven in Sports
Cohesion
Communications Engineering
Computational Science and Engineering
Computer Science
Confounding (Statistics)
Data Mining and Knowledge Discovery
Database Management
Datasets
Decision making
Decision trees
Football
Information Storage and Retrieval
Machine learning
Mathematical Applications in Computer Science
Networks
Passes
Ratings & rankings
Shared experience
Soccer
Tournaments & championships
Cohesion
Shared experience
Football
Passes
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ISSN2196-1115
2196-1115
DOI10.1186/s40537-025-01239-x

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Summary:This study investigates the impact of shared experience on football performance through macro-level (match outcomes) and micro-level (passing dynamics) analyses. Using machine learning models on 19,721 matches, the macro study found that conventional metrics like FIFA rankings and team strength overshadowed shared experience, which showed no independent influence on results. In contrast, micro-level analysis of 1,602 matches revealed that shared experience combined with successful prior interactions significantly predicted pass success. Decision tree models highlighted that player pairs with over 10 successful passes achieved higher completion rates, particularly for low, ground, and high passes, while pass length and receiver position further modulated outcomes. Temporal analysis showed that both short-term (20-day) and long-term (12-month) shared experience windows were predictive, with no added benefit from exponential decay weighting. The findings emphasize that shared experience’s value lies in the quality of successful coordination rather than mere familiarity or time spent together. This dual-level approach challenges assumptions about cohesion’s uniform impact, advocating for context-sensitive models that prioritize interaction quality in team performance analysis.
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ISSN:2196-1115
2196-1115
DOI:10.1186/s40537-025-01239-x