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Using data analytics to capture the strategic and financial decision-making of Europe's top football club

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  • Toma, Pierluigi
  • Campobasso, Francesco

Abstract

Since soccer is the most prominent sport in Europe—not to mention the world—it is no wonder that deep strategizing has become the norm in its management models. In this study we extract from real data the hidden and nontrivial relationships that have developed within the game in order to further the current understanding of how a team's performance is premised on its tactical and financial choices. We adopt, for the first time—in combination with an ordered logit model—inequality indexes at the team level. Our analysis uses a large and unique dataset that includes all of the teams from the top five European national championship leagues, including detailed player and team statistics. The results differ between the top-tier and medium-to-bottom tier teams and highlight an overall strategic evolution over the last decade.

Suggested Citation

  • Toma, Pierluigi & Campobasso, Francesco, 2023. "Using data analytics to capture the strategic and financial decision-making of Europe's top football club," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    • Handle: RePEc:eee:tefoso:v:186:y:2023:i:pa:s0040162522006370
    DOI: 10.1016/j.techfore.2022.122116
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    References listed on IDEAS

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