IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v178y2024ics0960077923012572.html
   My bibliography  Save this article

A multilayer network framework for soccer analysis

Author

Listed:
  • Novillo, Álvaro
  • Gong, Bingnan
  • Martínez, Johann H.
  • Resta, Ricardo
  • del Campo, Roberto López
  • Buldú, Javier M.

Abstract

In this paper, we define a novel methodology for analyzing soccer matches and teams using spatial multilayer networks. Departing from a segmentation of the pitch into h×v regions, we create 2-layer networks that capture the exchange of ball possessions between teams throughout a match. To assess the significance of each node, we employed eigenvector centrality measures within the constructed multilayer network. Furthermore, we introduce three additional metrics, namely the leakage, recovery and switching factor, which quantify the possession transitions between layers. Finally, we apply our methodology to analyze the performance of Spanish soccer teams over an entire season, using the aforementioned multilayer parameters, and discuss the relation with the playing style and ranking of soccer teams.

Suggested Citation

  • Novillo, Álvaro & Gong, Bingnan & Martínez, Johann H. & Resta, Ricardo & del Campo, Roberto López & Buldú, Javier M., 2024. "A multilayer network framework for soccer analysis," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
  • Handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012572
    DOI: 10.1016/j.chaos.2023.114355
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077923012572
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.chaos.2023.114355?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Narizuka, Takuma & Yamamoto, Ken & Yamazaki, Yoshihiro, 2014. "Statistical properties of position-dependent ball-passing networks in football games," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 412(C), pages 157-168.
    2. Bingnan Gong & Yixiong Cui & Shaoliang Zhang & Changjing Zhou & Qing Yi & Miguel-Ángel Gómez-Ruano, 2021. "Impact of technical and physical key performance indicators on ball possession in the Chinese Super League," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 21(6), pages 909-921, November.
    3. Xiao Fan Liu & Yu-Liang Liu & Xin-Hang Lu & Qi-Xuan Wang & Tong-Xing Wang, 2016. "The Anatomy of the Global Football Player Transfer Network: Club Functionalities versus Network Properties," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-14, June.
    4. Stuart Gollan & Katia Ferrar & Kevin Norton, 2018. "Characterising game styles in the English Premier League using the “moments of play” framework," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 18(6), pages 998-1009, November.
    5. Linxiao Ma & Yuzhu Wang & Yue Wang & Ning Li & Sai-Fu Fung & Lu Zhang & Qian Zheng & Fei Xiong, 2021. "The Hotspots of Sports Science and the Effects of Knowledge Network on Scientific Performance Based on Bibliometrics and Social Network Analysis," Complexity, Hindawi, vol. 2021, pages 1-12, May.
    6. 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).
    7. Herrera-Diestra, J.L. & Echegoyen, I. & Martínez, J.H. & Garrido, D. & Busquets, J. & Io, F.Seirul. & Buldú, J.M., 2020. "Pitch networks reveal organizational and spatial patterns of Guardiola’s F.C. Barcelona," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    8. Gong, Bingnan & Zhou, Changjing & Gómez, Miguel-Ángel & Buldú, J.M., 2023. "Identifiability of Chinese football teams: A complex networks approach," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    9. Gomez, Miguel-Angel & Reus, Marc & Parmar, Nimai & Travassos, Bruno, 2020. "Exploring elite soccer teams’ performances during different match-status periods of close matches’ comebacks," Chaos, Solitons & Fractals, Elsevier, vol. 132(C).
    10. G. P. Clemente & A. Cornaro, 2023. "Community detection in attributed networks for global transfer market," Annals of Operations Research, Springer, vol. 325(1), pages 57-83, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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).
    2. Gong, Bingnan & Zhou, Changjing & Gómez, Miguel-Ángel & Buldú, J.M., 2023. "Identifiability of Chinese football teams: A complex networks approach," Chaos, Solitons & Fractals, Elsevier, vol. 166(C).
    3. 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).
    4. Külah, Emre & Alemdar, Hande, 2020. "Quantifying the value of sprints in elite football using spatial cohesive networks," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    5. Eremin, G., 2018. "Analysis of Factors Influencing the Pricing of Transfers in European Professional Football," Journal of the New Economic Association, New Economic Association, vol. 40(4), pages 174-183.
    6. Katalin Ozogány & Viola Kerekes & Attila Fülöp & Zoltán Barta & Máté Nagy, 2023. "Fine-scale collective movements reveal present, past and future dynamics of a multilevel society in Przewalski’s horses," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    7. Jon Manuel Vega & Asier Gonzalez-Artetxe & Jon Ander Aguinaco & Asier Los Arcos, 2020. "Assessing the Anthropometric Profile of Spanish Elite Reserve Soccer Players by Playing Position over a Decade," IJERPH, MDPI, vol. 17(15), pages 1-9, July.
    8. Zhou, Yunjing & Zong, Shouxin & Cao, Run & Gómez, Miguel-Ángel & Chen, Chuqi & Cui, Yixiong, 2023. "Using network science to analyze tennis stroke patterns," Chaos, Solitons & Fractals, Elsevier, vol. 170(C).
    9. Sergio Caicedo-Parada & Carlos Lago-Peñas & Enrique Ortega-Toro, 2020. "Passing Networks and Tactical Action in Football: A Systematic Review," IJERPH, MDPI, vol. 17(18), pages 1-19, September.
    10. Julen Castellano & Miguel Pic, 2019. "Identification and Preference of Game Styles in LaLiga Associated with Match Outcomes," IJERPH, MDPI, vol. 16(24), pages 1-13, December.
    11. David Matesanz & Florian Holzmayer & Benno Torgler & Sascha L Schmidt & Guillermo J Ortega, 2018. "Transfer market activities and sportive performance in European first football leagues: A dynamic network approach," PLOS ONE, Public Library of Science, vol. 13(12), pages 1-16, December.
    12. Leonardo Lamas & José Vitor Senatore & Gilbert Fellingham, 2020. "Two steps for scoring a point: Creating and converting opportunities in invasion team sports," PLOS ONE, Public Library of Science, vol. 15(10), pages 1-16, October.
    13. Gómez, Miguel A. & Cid, Adrián & Rivas, Fernando & Barreira, Júlia & Chiminazzo, João Guilherme Cren & Prieto, Jaime, 2021. "Dynamic analysis of scoring performance in elite men's badminton according to contextual-related variables," Chaos, Solitons & Fractals, Elsevier, vol. 151(C).
    14. 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).
    15. Carlo Dindorf & Eva Bartaguiz & Freya Gassmann & Michael Fröhlich, 2022. "Conceptual Structure and Current Trends in Artificial Intelligence, Machine Learning, and Deep Learning Research in Sports: A Bibliometric Review," IJERPH, MDPI, vol. 20(1), pages 1-23, December.
    16. 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).
    17. G. P. Clemente & A. Cornaro, 2023. "Community detection in attributed networks for global transfer market," Annals of Operations Research, Springer, vol. 325(1), pages 57-83, June.
    18. Fernando Martins & Ricardo Gomes & Vasco Lopes & Frutuoso Silva & Rui Mendes, 2020. "Node and Network Entropy—A Novel Mathematical Model for Pattern Analysis of Team Sports Behavior," Mathematics, MDPI, vol. 8(9), pages 1-12, September.
    19. 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).
    20. Calzada-Infante, Laura & Lozano, Sebastián, 2016. "Analysing Olympic Games through dominance networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1215-1230.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:chsofr:v:178:y:2024:i:c:s0960077923012572. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Thayer, Thomas R. (email available below). General contact details of provider: https://www.journals.elsevier.com/chaos-solitons-and-fractals .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.