IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0221368.html
   My bibliography  Save this article

Extracting spatial-temporal features that describe a team match demands when considering the effects of the quality of opposition in elite football

Author

Listed:
  • Bruno Gonçalves
  • Diogo Coutinho
  • Juliana Exel
  • Bruno Travassos
  • Carlos Lago
  • Jaime Sampaio

Abstract

Spatiotemporal patterns of play can be extracted from competitive environments to design representative training tasks and underlying processes that sustain performance outcomes. To support this statement, the aims of this study were: (i) describe the collective behavioural patterns that relies upon the use of player positioning in interaction with teammates, opponents and ball positioning; (ii) and define the underlying structure among the variables through application of a factorial analysis. The sample comprised a total of 1,413 ball possession sequences, obtained from twelve elite football matches from one team (the team ended the season in the top-5 position). The dynamic position of the players (from both competing teams), as well as the ball, were captured and transformed to two-dimensional coordinates. Data included the ball possession sequences from six matches played against top opponents (TOP, the three teams classified in the first 3 places at the end of the season) and six matches against bottom opponents (BOTTOM, the three teams classified in the last 3 at the end of the season). The variables calculated for each ball possession were the following: ball position; team space in possession; game space (comprising the outfield players of both teams); position and space at the end of ball possession. Statistical comparisons were carried with magnitude-based decisions and null-hypothesis analysis and factor analysis to define the underlying structure among variables according to the considered contexts. Results showed that playing against TOP opponents, there was ~38 meters game length per ~43 meters game width with 12% of coefficient of variation (%). Ball possessions lasted for ~28 seconds and tended to end at ~83m of pitch length. Against BOTTOM opponents, a decrease in the game length with an increase in game width and in the deepest location was observed in comparison with playing against TOP opponents. The duration of ball possession increased considerable (~37 seconds), and the ball speed entropy was higher, suggesting lower levels of regularity in comparison with TOP opponents. The BOTTOM teams revealed a small EPS. The Principal Component Analysis showed a strong association of the ball speed, entropy of the ball speed and the coefficient of variation (%) of the ball speed. The EPS of the team in possession was well correlated with the game space, especially the game width facing TOP opponents. Against BOTTOM opponents, there was a strong association of ball possession duration, game width, distance covered by the ball, and length/width ratio of the ball movement. The overall approach carried out in this study may serve as the starting point to elaborate normative models of positioning behaviours measures to support the coaches’ operating decisions.

Suggested Citation

  • 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.
  • Handle: RePEc:plo:pone00:0221368
    DOI: 10.1371/journal.pone.0221368
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0221368
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0221368&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0221368?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
    ---><---

    References listed on IDEAS

    as
    1. Daniel Link & Martin Hoernig, 2017. "Individual ball possession in soccer," PLOS ONE, Public Library of Science, vol. 12(7), pages 1-15, July.
    2. Julen Castellano & David Casamichana, 2015. "What are the differences between first and second divisions of Spanish football teams?," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(1), pages 135-146, March.
    3. Jaime Sampaio & Tim McGarry & Julio Calleja-González & Sergio Jiménez Sáiz & Xavi Schelling i del Alcázar & Mindaugas Balciunas, 2015. "Exploring Game Performance in the National Basketball Association Using Player Tracking Data," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-14, July.
    4. 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.
    5. 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.
    6. Bruno Travassos & Keith Davids & Duarte Araújo & T. Pedro Esteves, 2013. "Performance analysis in team sports: Advances from an Ecological Dynamics approach," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 13(1), pages 83-95, April.
    7. Daniel Link & Steffen Lang & Philipp Seidenschwarz, 2016. "Real Time Quantification of Dangerousity in Football Using Spatiotemporal Tracking Data," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-16, December.
    8. Julen Castellano & David álvarez & Bruno Figueira & Diogo Coutinho & Jaime Sampaio, 2013. "Identifying the effects from the quality of opposition in a Football team positioning strategy," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 13(3), pages 822-832, December.
    9. Tim McGarry, 2009. "Applied and theoretical perspectives of performance analysis in sport: Scientific issues and challenges," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 9(1), pages 128-140, April.
    10. Pedro Silva & Ricardo Duarte & Pedro Esteves & Bruno Travassos & Luís Vilar, 2016. "Application of entropy measures to analysis of performance in team sports," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 16(2), pages 753-768, August.
    11. Carlota Torrents & Angel Ric & Robert Hristovski & Lorena Torres-Ronda & Emili Vicente & Jaime Sampaio, 2016. "Emergence of Exploratory, Technical and Tactical Behavior in Small-Sided Soccer Games when Manipulating the Number of Teammates and Opponents," PLOS ONE, Public Library of Science, vol. 11(12), pages 1-15, December.
    12. A. Tenga & A. Zubillaga & O. Caro & L. Fradua, 2015. "Explorative Study on Patterns of Game Structure in Male and Female Matches from Elite Spanish Soccer," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 15(1), pages 411-423, March.
    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. Diogo Coutinho & Bruno Gonçalves & Hugo Folgado & Bruno Travassos & Sara Santos & Jaime Sampaio, 2022. "Amplifying perceptual demands: How changes in the colour vests affect youth players performance during medium-sided games," PLOS ONE, Public Library of Science, vol. 17(1), pages 1-16, January.
    2. 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).

    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. Fernando Manuel Otero-Saborido & Rubén D. Aguado-Méndez & Víctor M. Torreblanca-Martínez & José Antonio González-Jurado, 2021. "Technical-Tactical Performance from Data Providers: A Systematic Review in Regular Football Leagues," Sustainability, MDPI, vol. 13(18), pages 1-15, September.
    2. Markel Rico-González & José Pino-Ortega & Fabio Y. Nakamura & Felipe Arruda Moura & Asier Los Arcos, 2020. "Identification, Computational Examination, Critical Assessment and Future Considerations of Distance Variables to Assess Collective Tactical Behaviour in Team Invasion Sports by Positional Data: A Sys," IJERPH, MDPI, vol. 17(6), pages 1-14, March.
    3. 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.
    4. Eduard Pons & Tomás García-Calvo & Ricardo Resta & Hugo Blanco & Roberto López del Campo & Jesús Díaz García & Juan José Pulido, 2019. "A comparison of a GPS device and a multi-camera video technology during official soccer matches: Agreement between systems," PLOS ONE, Public Library of Science, vol. 14(8), pages 1-12, August.
    5. Devansh Patel & Dhwanil Shah & Manan Shah, 2020. "The Intertwine of Brain and Body: A Quantitative Analysis on How Big Data Influences the System of Sports," Annals of Data Science, Springer, vol. 7(1), pages 1-16, March.
    6. 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.
    7. 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.
    8. 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.
    9. Daniel Linke & Daniel Link & Martin Lames, 2020. "Football-specific validity of TRACAB’s optical video tracking systems," PLOS ONE, Public Library of Science, vol. 15(3), pages 1-17, March.
    10. Juan M. García-Ceberino & Antonio Antúnez & Sebastián Feu & Sergio J. Ibáñez, 2020. "Quantification of Internal and External Load in School Football According to Gender and Teaching Methodology," IJERPH, MDPI, vol. 17(1), pages 1-18, January.
    11. Bernd Frick & Pamela Wicker, 2018. "The Monetary Value of Having a First Division Bundesliga Team to Local Residents," Schmalenbach Business Review, Springer;Schmalenbach-Gesellschaft, vol. 70(1), pages 63-103, February.
    12. Tullio Facchinetti & Rodolfo Metulini & Paola Zuccolotto, 2023. "Filtering active moments in basketball games using data from players tracking systems," Annals of Operations Research, Springer, vol. 325(1), pages 521-538, June.
    13. 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.
    14. Liandi Van den Berg, 2019. "The variance of information management by South African sport coaches within different competitive levels," Proceedings of International Academic Conferences 9912356, International Institute of Social and Economic Sciences.
    15. Jorge Serna & Verónica Muñoz-Arroyave & Jaume March-Llanes & M. Teresa Anguera & Queralt Prat & Aaron Rillo-Albert & David Falcón & Pere Lavega-Burgués, 2021. "Effect of Ball Screen and One-on-One on the Level of Opposition and Effectiveness of Shots in the ACB," IJERPH, MDPI, vol. 18(5), pages 1-16, March.
    16. Nimai Parmar & Nic James & Mike Hughes & Huw Jones & Gary Hearne, 2017. "Team performance indicators that predict match outcome and points difference in professional rugby league," International Journal of Performance Analysis in Sport, Taylor & Francis Journals, vol. 17(6), pages 1044-1056, November.
    17. José Pino-Ortega & Daniel Rojas-Valverde & Carlos D. Gómez-Carmona & Markel Rico-González, 2021. "Training Design, Performance Analysis, and Talent Identification—A Systematic Review about the Most Relevant Variables through the Principal Component Analysis in Soccer, Basketball, and Rugby," IJERPH, MDPI, vol. 18(5), pages 1-19, March.
    18. Toma, Pierluigi & Campobasso, Francesco, 2023. "Using data analytics to capture the strategic and financial decision-making of Europe's top football club," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    19. Stijn Baert & Simon Amez, 2018. "No better moment to score a goal than just before half time? A soccer myth statistically tested," PLOS ONE, Public Library of Science, vol. 13(3), pages 1-17, March.
    20. Rosa Fabbricatore & Maria Iannario & Rosaria Romano & Domenico Vistocco, 2023. "Component-based structural equation modeling for the assessment of psycho-social aspects and performance of athletes," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 343-367, March.

    More about this item

    Statistics

    Access and download statistics

    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:plo:pone00:0221368. 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: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    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.