IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v17y2020i24p9396-d462431.html
   My bibliography  Save this article

What Is the Relevance in the Passing Action between the Passer and the Receiver in Soccer? Study of Elite Soccer in La Liga

Author

Listed:
  • Antonio Cordón-Carmona

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

  • Abraham García-Aliaga

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

  • Moisés Marquina

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

  • Jorge Lorenzo Calvo

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

  • Daniel Mon-López

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

  • Ignacio Refoyo Roman

    (Facultad de Ciencias de la Actividad Física y del Deporte (INEF-Departamento de Deportes), Universidad Politécnica de Madrid, C/Martín Fierro, 7, 28040 Madrid, Spain)

Abstract

Soccer is a high-complexity sport in which 22 players interact simultaneously in a common space. The ball-holder interacts with their teammates by passing actions, establishing a unique communication among them in the development of the game in its offensive phase. The main aim of the present study was to analyze the pass action according to the trajectory of the ball receiver and the space for receiving the ball in terms of success at the end of play. Twenty La Liga 2018/2019 matches of two elite teams were analyzed. A system of notational analysis was used to create 11 categories based on context, timing and pass analysis. The data were analyzed using chi-squared analysis. The results showed that the main performance indicators were the efficiency of the pass, the zone of the field, the trajectory of the receiver and the reception space of the ball, which presented a moderate association with the end of play ( p < 0.001). We concluded that receiving the ball on approach and in separation increased the probability of success by 5% and 7%, respectively, and a diagonal run increased the probability by 7%. Moreover, the combined analysis of these variables would improve the team performance.

Suggested Citation

  • Antonio Cordón-Carmona & Abraham García-Aliaga & Moisés Marquina & Jorge Lorenzo Calvo & Daniel Mon-López & Ignacio Refoyo Roman, 2020. "What Is the Relevance in the Passing Action between the Passer and the Receiver in Soccer? Study of Elite Soccer in La Liga," IJERPH, MDPI, vol. 17(24), pages 1-15, December.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:24:p:9396-:d:462431
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/17/24/9396/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/17/24/9396/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Bruno Gonçalves & Diogo Coutinho & Sara Santos & Carlos Lago-Penas & Sergio Jiménez & Jaime Sampaio, 2017. "Exploring Team Passing Networks and Player Movement Dynamics in Youth Association Football," PLOS ONE, Public Library of Science, vol. 12(1), pages 1-13, January.
    2. Hannes Lepschy & Hagen Wäsche & Alexander Woll, 2018. "How to be Successful in Football: A Systematic Review," The Open Sports Sciences Journal, Bentham Open, vol. 11(1), pages 3-23, June.
    3. Takahiro Kawasaki & Kenichi Sakaue & Ryota Matsubara & Satoshi Ishizaki, 2019. "Football pass network based on the measurement of player position by using network theory and clustering," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 19(3), pages 381-392, May.
    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. 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.
    2. Basile, Vincenzo & Sorooshian, Shahryar & Pizzichini, Lucia, 2024. "A scientometrics-based journal Management framework: A strategic move," Socio-Economic Planning Sciences, Elsevier, vol. 93(C).
    3. 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.
    4. Valerio Ficcadenti & Roy Cerqueti & Ciro Hosseini Varde’i, 2023. "A rank-size approach to analyse soccer competitions and teams: the case of the Italian football league “Serie A"," Annals of Operations Research, Springer, vol. 325(1), pages 85-113, June.
    5. Łukasz Radzimiński & Alexis Padrón-Cabo & Marek Konefał & Paweł Chmura & Andrzej Szwarc & Zbigniew Jastrzębski, 2021. "The Influence of COVID-19 Pandemic Lockdown on the Physical Performance of Professional Soccer Players: An Example of German and Polish Leagues," IJERPH, MDPI, vol. 18(16), pages 1-11, August.
    6. Bruno Gonçalves & Diogo Coutinho & Juliana Exel & Bruno Travassos & Carlos Lago & Jaime Sampaio, 2019. "Extracting spatial-temporal features that describe a team match demands when considering the effects of the quality of opposition in elite football," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-20, August.
    7. Li, Yuesen & Ma, Runqing & Gonçalves, Bruno & Gong, Bingnan & Cui, Yixiong & Shen, Yanfei, 2020. "Data-driven team ranking and match performance analysis in Chinese Football Super League," Chaos, Solitons & Fractals, Elsevier, vol. 141(C).
    8. Marius Ötting & Roland Langrock & Antonello Maruotti, 2023. "A copula-based multivariate hidden Markov model for modelling momentum in football," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 9-27, March.
    9. Jonas Lutz & Daniel Memmert & Dominik Raabe & Rolf Dornberger & Lars Donath, 2019. "Wearables for Integrative Performance and Tactic Analyses: Opportunities, Challenges, and Future Directions," IJERPH, MDPI, vol. 17(1), pages 1-26, December.
    10. 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).
    11. 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.
    12. Bruno Gonçalves & Diogo Coutinho & Bruno Travassos & Hugo Folgado & Pedro Caixinha & Jaime Sampaio, 2018. "Speed synchronization, physical workload and match-to-match performance variation of elite football players," PLOS ONE, Public Library of Science, vol. 13(7), pages 1-16, July.
    13. Külah, Emre & Alemdar, Hande, 2020. "Quantifying the value of sprints in elite football using spatial cohesive networks," Chaos, Solitons & Fractals, Elsevier, vol. 139(C).
    14. Antonello D’Ambra & Pietro Amenta, 2023. "An extension of correspondence analysis based on the multiple Taguchi’s index to evaluate the relationships between three categorical variables graphically: an application to the Italian football cham," Annals of Operations Research, Springer, vol. 325(1), pages 219-244, June.

    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:gam:jijerp:v:17:y:2020:i:24:p:9396-:d:462431. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.