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Player position relationships with centrality in the passing network of world cup soccer teams: Win/loss match comparisons

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  • Clemente, Filipe Manuel
  • Sarmento, Hugo
  • Aquino, Rodrigo

Abstract

Among elite national soccer team play of the 2018 FIFA World Cub, we analyzed (a) network centrality variations between playing positions during passing sequences, and (b) their relationship to match outcomes. We observed and coded the 64 matches played by 32 teams and collected passing distribution data between teammates. We then converted it into adjacency matrices to calculate passing network data. We found large decreases in degree prestige (inbound pass links) among players in winger positions compared to external defenders (−41.8%; ES (effect size): −1.79). Large decreases in degree prestige were also found in central forwards in comparison to external defenders (−38.7%; ES: −1.62), central defenders (−42.3%; ES: −1.60), defensive midfielders (−47.1%; ES: −1.87) and midfielders (−40.8%; ES: −1.59). Comparisons of passing network centrality levels between won and lost matches revealed small increases in degree prestige among midfielders (17.4%; ES: 0.31) and small increases among forwards (33.9%,; ES: 0.53) among matches won. Thus, match outcome (and possibly scoring status during the match) was somewhat related to the passing network centrality of various playing positions during passing sequences.

Suggested Citation

  • Clemente, Filipe Manuel & Sarmento, Hugo & Aquino, Rodrigo, 2020. "Player position relationships with centrality in the passing network of world cup soccer teams: Win/loss match comparisons," Chaos, Solitons & Fractals, Elsevier, vol. 133(C).
    • Handle: RePEc:eee:chsofr:v:133:y:2020:i:c:s0960077920300242
    DOI: 10.1016/j.chaos.2020.109625
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    References listed on IDEAS

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    1. Filipe Manuel Clemente & Fernando Manuel Lourenço Martins & P. Del Wong & Dimitris Kalamaras & Rui Sousa Mendes, 2015. "Midfielder as the prominent participant in the building attack: A network analysis of national teams in FIFA World Cup 2014," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(2), pages 704-722, August.
    2. Filipe Manuel Clemente & Fernando Manuel Lourenço Martins & Dimitris Kalamaras & P. Del Wong & Rui Sousa Mendes, 2015. "General network analysis of national soccer teams in FIFA World Cup 2014," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(1), pages 80-96, March.
    3. Jordi Duch & Joshua S Waitzman & Luís A Nunes Amaral, 2010. "Quantifying the Performance of Individual Players in a Team Activity," PLOS ONE, Public Library of Science, vol. 5(6), pages 1-7, June.
    4. Paulo Paixão & Jaime Sampaio & Carlos H. Almeida & Ricardo Duarte, 2015. "How does match status affects the passing sequences of top-level European soccer teams?," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(1), pages 229-240, March.
    5. Yuji Yamamoto & Keiko Yokoyama, 2011. "Common and Unique Network Dynamics in Football Games," PLOS ONE, Public Library of Science, vol. 6(12), pages 1-6, December.
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    Cited by:

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    5. Marcelino, Rui & Sampaio, Jaime & Amichay, Guy & Gonçalves, Bruno & Couzin, Iain D. & Nagy, Máté, 2020. "Collective movement analysis reveals coordination tactics of team players in football matches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
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