IDEAS home Printed from https://ideas.repec.org/a/eee/chsofr/v135y2020ics0960077920302344.html
   My bibliography  Save this article

Using network science to unveil badminton performance patterns

Author

Listed:
  • Gómez, Miguel–Ángel
  • Rivas, Fernando
  • Leicht, Anthony S.
  • Buldú, Javier M.

Abstract

Bipartite networks are related to non-linear and ecological approaches where, at least, two different kinds of entities are considered. In sports, we can consider players as entities that base their decisions (actions and reactions) on opponents and their own actions. Incorporation of bipartite networks into modelling of racket sport performances may bridge the gap between the performance analysis sub-discipline and coaches for greater preparation of training sessions and competitions for enhanced success. Thus, the main aim of this study was to create badminton stroke networks (BSN), from the match activities of a player and their opponents, to describe and quantify the performance of elite Olympic badminton players. The use of a Network Science approach required the development of a series of methodologies that accounted for strokes played by all medallists within an Olympic tournament and included: (i) the construction of BSN; (ii) the one-mode projections of bipartite networks (self- and opponent- networks); (iii) the centrality of one-mode projections; and (iv) the identifiability of badminton players. The BSN identified different playing patterns for medallists with the Silver medallist categorised with the less predictable and defined style of play, the Bronze medallist exhibiting the most defined style; and the Gold medallist exhibiting the greatest predictability, but only when losing points (self-networks). The use of Network Science enabled the identification of distinctive styles of play (self- and opponent–related), based on stroke performance, during successful and unsuccessful points within an Olympic tournament. Specifically, the identifiability of each player's network and its associations with point outcome, provided a better understanding of stroke performances and individual features of world-class badminton players. The use of non-linear approaches (such as bipartite networks) to measure and visualize player's performances, accounting for the specific nature of badminton and opponents, may support coaches and players with the contextualized demands of playing patterns and their performances (i.e., winning and losing points) for future success.

Suggested Citation

  • Gómez, Miguel–Ángel & Rivas, Fernando & Leicht, Anthony S. & Buldú, Javier M., 2020. "Using network science to unveil badminton performance patterns," Chaos, Solitons & Fractals, Elsevier, vol. 135(C).
    • Handle: RePEc:eee:chsofr:v:135:y:2020:i:c:s0960077920302344
    DOI: 10.1016/j.chaos.2020.109834
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960077920302344
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.chaos.2020.109834?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. 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.
    2. Jürgen Perl, 2001. "Artificial Neural Networks in Sports: New Concepts and Approaches," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 1(1), pages 106-121, July.
    3. Gemma Robinson & Peter O’Donoghue, 2007. "A weighted kappa statistic for reliability testing in performance analysis of sport," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 7(1), pages 12-19, January.
    4. Wolf Gawin & Chris Beyer & Marko Seidler, 2015. "A competition analysis of the single and double disciplines in world-class badminton," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(3), pages 997-1006, December.
    5. Jürgen Perl, 2002. "Game analysis and control by means of continuously learning networks," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 2(1), pages 21-35, August.
    6. Javier Abian-Vicen & Adrian Castanedo & Pablo Abian & Javier Sampedro, 2013. "Temporal and notational comparison of badminton matches between men’s singles and women’s singles," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 13(2), pages 310-320, August.
    7. Júlia Barreira & João Guilherme Cren Chiminazzo & Paula Teixeira Fernandes, 2016. "Analysis of point difference established by winners and losers in games of badminton," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 16(2), pages 687-694, August.
    8. Pablo Abián & Adrian Castanedo & Xing Qiao Feng & Javier Sampedro & Javier Abian-Vicen, 2014. "Notational comparison of men’s singles badminton matches between Olympic Games in Beijing and London," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 14(1), pages 42-53, April.
    9. Yahaya Abdullahi & Ben Coetzee, 2017. "Notational singles match analysis of male badminton players who participated in the African Badminton Championships," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(1-2), pages 1-16, March.
    10. Jie Wang, 2019. "Comparison of table tennis serve and return characteristics in the London and the Rio Olympics," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 19(5), pages 683-697, September.
    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. Galeano, Javier & Gómez, Miguel-Ángel & Rivas, Fernando & Buldú, Javier M., 2022. "Using Markov chains to identify player’s performance in badminton," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    3. 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).

    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. Miguel A Gomez & Anthony S Leicht & Fernando Rivas & Philip Furley, 2020. "Long rallies and next rally performances in elite men’s and women’s badminton," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-16, March.
    2. Galeano, Javier & Gómez, Miguel-Ángel & Rivas, Fernando & Buldú, Javier M., 2022. "Using Markov chains to identify player’s performance in badminton," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    3. Miguel-Ángel Gomez & Fernando Rivas & Jonathan D. Connor & Anthony S. Leicht, 2019. "Performance Differences of Temporal Parameters and Point Outcome Between Elite Men’s and Women’s Badminton Players According to Match-Related Contexts," IJERPH, MDPI, vol. 16(21), pages 1-18, October.
    4. 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).
    5. 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).
    6. Mario Terol-Sanchis & María José Gomis-Gomis & Carlos Elvira-Aranda & David Cabello-Manrique & José Antonio Pérez-Turpin, 2023. "AirBadminton for Physical Activity and Well-Being in Spanish Students: Post-COVID-19," IJERPH, MDPI, vol. 20(5), pages 1-12, February.
    7. 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.
    8. Albert Cohen & Jimmy Risk, 2023. "European Football Player Valuation: Integrating Financial Models and Network Theory," Papers 2312.16179, arXiv.org, revised Oct 2024.
    9. 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.
    10. Adrián Escudero-Tena & Bernardino Javier Sánchez-Alcaraz & Javier García-Rubio & Sergio J. Ibáñez, 2021. "Analysis of Game Performance Indicators during 2015–2019 World Padel Tour Seasons and Their Influence on Match Outcome," IJERPH, MDPI, vol. 18(9), pages 1-8, May.
    11. Kęstutis Matulaitis & Tomas Bietkis, 2021. "Prediction of Offensive Possession Ends in Elite Basketball Teams," IJERPH, MDPI, vol. 18(3), pages 1-11, January.
    12. 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.
    13. 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).
    14. 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.
    15. Gimenez-Egido, José María & Ortega-Toro, Enrique & Palao, José M & Torres-Luque, Gema, 2020. "Effect of scaling equipment on U-10 players tennis serve during match-play: A nonlinear pedagogical approach," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    16. Sebastián Feu & Javier García-Rubio & María de Gracia Gamero & Sergio J Ibáñez, 2019. "Task planning for sports learning by physical education teachers in the pre-service phase," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-18, March.
    17. 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.
    18. 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).
    19. 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.
    20. Brian Skinner, 2012. "The Problem of Shot Selection in Basketball," PLOS ONE, Public Library of Science, vol. 7(1), pages 1-8, January.

    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:135:y:2020:i:c:s0960077920302344. 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.