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This work discusses the introduction of a synthetic indicator to summarise the triadic information in a football passing network taking also into account the number of passes occurring between players. To this aim, we aggregate the counts of triads by using a weighting scheme based on the number of connections in each isomorphism class. We compute this measure by using different cutoffs on the weighted network of passes between players. The final indicator can be obtained by averaging the triad-based indicators for a given number of cutoffs. The applicability of this approach is shown through a real dataset regarding three consecutive seasons of the UEFA Champions League.

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A Triad Census-Based Synthetic Indicator to Summarise Cooperation in Football

  • 会议论文

  • 发表日期：

    2025年

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  • Riccardo Ievoli,
  • Lucio Palazzo,
  • Roberto Rondinelli,
  • Giancarlo Ragozini

摘要

This work discusses the introduction of a synthetic indicator to summarise the triadic information in a football passing network taking also into account the number of passes occurring between players. To this aim, we aggregate the counts of triads by using a weighting scheme based on the number of connections in each isomorphism class. We compute this measure by using different cutoffs on the weighted network of passes between players. The final indicator can be obtained by averaging the triad-based indicators for a given number of cutoffs. The applicability of this approach is shown through a real dataset regarding three consecutive seasons of the UEFA Champions League.