IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v138y2020ics0960077920305324.html
   My bibliography  Save this article

Characteristics and optimization of core local network: Big data analysis of football matches

Author

Listed:
  • Wu, Yao
  • Xia, Zeyu
  • Wu, Tian
  • Yi, Qing
  • Yu, Runyu
  • Wang, Jun

Abstract

The current study constructed social network using player positions and passing process based on available literature. Multiple indicators were used to measure the importance of positions comprehensively. The results showed that in the football passing process, the attacking midfielder was the most important position, followed by the central defending midfielder. Based on two-sample difference tests, the results showed that the winning teams usually had better performance on positions of forward on left, central forward, defender on left and defender on right. To analyze the effects of playing positions on the whole network and test the sensitivity of passing networks, we deleted n (n = 1, 2, 3…, 10) positions of a team, and then tested the efficiency of the networks based on positions left.

Suggested Citation

  • Wu, Yao & Xia, Zeyu & Wu, Tian & Yi, Qing & Yu, Runyu & Wang, Jun, 2020. "Characteristics and optimization of core local network: Big data analysis of football matches," Chaos, Solitons & Fractals, Elsevier, vol. 138(C).
    • Handle: RePEc:eee:chsofr:v:138:y:2020:i:c:s0960077920305324
    DOI: 10.1016/j.chaos.2020.110136
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920305324
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2020.110136?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. 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. 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.
    3. 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.
    4. 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).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Song, Honglin & Li, Yutao & Fu, Chenyi & Xue, Feng & Zhao, Qiyue & Zheng, Xingyu & Jiang, Kunkun & Liu, Tianbiao, 2024. "Using complex networks and multiple artificial intelligence algorithms for table tennis match action recognition and technical-tactical analysis," Chaos, Solitons & Fractals, Elsevier, vol. 178(C).
    2. 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).
    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).

    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. 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).
    2. Sarmento, Hugo & Clemente, Filipe Manuel & Gonçalves, Eder & Harper, Liam D & Dias, Diogo & Figueiredo, António, 2020. "Analysis of the offensive process of AS Monaco professional soccer team: A mixed-method approach," Chaos, Solitons & Fractals, Elsevier, vol. 133(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).
    4. Rubén Maneiro & Claudio A Casal & Antonio Ardá & José Luís Losada, 2019. "Application of multivariant decision tree technique in high performance football: The female and male corner kick," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-16, March.
    5. Albert Cohen & Jimmy Risk, 2023. "European Football Player Valuation: Integrating Financial Models and Network Theory," Papers 2312.16179, arXiv.org, revised Oct 2024.
    6. Filippo Radicchi, 2011. "Who Is the Best Player Ever? A Complex Network Analysis of the History of Professional Tennis," PLOS ONE, Public Library of Science, vol. 6(2), pages 1-7, February.
    7. Seiler, A. & Papanagnou, C. & Scarf, P., 2020. "On the relationship between financial performance and position of businesses in supply chain networks," International Journal of Production Economics, Elsevier, vol. 227(C).
    8. Gur Yaari & Gil David, 2012. "“Hot Hand” on Strike: Bowling Data Indicates Correlation to Recent Past Results, Not Causality," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-9, January.
    9. Widarti Widarti & Desfitrina Desfitrina & Zulfadhli Zulfadhli, 2020. "Business Process Life Cycle Affects Company Financial Performance: Micro, Small, and Medium Business Enterprises During The Covid-19 Period," International Journal of Economics and Financial Issues, Econjournals, vol. 10(5), pages 211-219.
    10. Modric Toni & Versic Sime & Sekulic Damir, 2021. "Relationship Between Yo-Yo Intermittent Endurance Test-Level 1 and Match Running Performance in Soccer: Still on the Right Path?," Polish Journal of Sport and Tourism, Sciendo, vol. 28(4), pages 16-20, December.
    11. Lot Verburgh & Erik J A Scherder & Paul AM van Lange & Jaap Oosterlaan, 2014. "Executive Functioning in Highly Talented Soccer Players," PLOS ONE, Public Library of Science, vol. 9(3), pages 1-7, March.
    12. 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.
    13. Riccardo Ievoli & Aldo Gardini & Lucio Palazzo, 2023. "The role of passing network indicators in modeling football outcomes: an application using Bayesian hierarchical models," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 153-175, March.
    14. Tomás Rodríguez & Jorge Tovar, 2023. "The hedgehog or the fox: Versatility and performance in professional soccer," Documentos CEDE 20757, Universidad de los Andes, Facultad de Economía, CEDE.
    15. 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).
    16. 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).
    17. António Sérgio Ribeiro & Francisco Lima & Sascha Kraus & Ferran Calabuig, 2022. "Tournaments within football teams: players’ performance and wages," Economic Research-Ekonomska Istraživanja, Taylor & Francis Journals, vol. 35(1), pages 4884-4901, December.
    18. 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).
    19. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.
    20. 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).

    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:138:y:2020:i:c:s0960077920305324. 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.