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Is a social network approach relevant to football results?

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  • Medina, Pablo
  • Carrasco, Sebastián
  • Rogan, José
  • Montes, Felipe
  • Meisel, Jose D.
  • Lemoine, Pablo
  • Lago Peñas, Carlos
  • Valdivia, Juan Alejandro

Abstract

We study the relevance of considering social network analysis in determining soccer results. As a benchmark, we start using a simple regression model based on past performance to try to determine the main trends of a soccer match based on probabilities of winning, losing or tying, as home or visiting teams. The success of this simple model, based on historical performance, is improved by the addition of network descriptors of both teams in a game. Therefore, such network measures do offer additional useful information in determining match outcomes. We validate our approach using the data of the Spanish League (La Liga) 2012–2013. We observe that betweenness centrality seems to provide additional relevance information related to the performance of a team during the tournament.

Suggested Citation

  • Medina, Pablo & Carrasco, Sebastián & Rogan, José & Montes, Felipe & Meisel, Jose D. & Lemoine, Pablo & Lago Peñas, Carlos & Valdivia, Juan Alejandro, 2021. "Is a social network approach relevant to football results?," Chaos, Solitons & Fractals, Elsevier, vol. 142(C).
    • Handle: RePEc:eee:chsofr:v:142:y:2021:i:c:s0960077920307633
    DOI: 10.1016/j.chaos.2020.110369
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    Cited by:

    1. Beheshtian-Ardakani, Arash & Salehi, Mostafa & Sharma, Rajesh, 2023. "CMPN: Modeling and analysis of soccer teams using Complex Multiplex Passing Network," Chaos, Solitons & Fractals, Elsevier, vol. 174(C).
    2. Ichinose, Genki & Tsuchiya, Tomohiro & Watanabe, Shunsuke, 2021. "Robustness of football passing networks against continuous node and link removals," Chaos, Solitons & Fractals, Elsevier, vol. 147(C).
    3. Ballı, Serkan & Özdemir, Engin, 2021. "A novel method for prediction of EuroLeague game results using hybrid feature extraction and machine learning techniques," Chaos, Solitons & Fractals, Elsevier, vol. 150(C).

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