Using position data to estimate effects of perceptual features of play on passing decisions in soccer

Silvan Steiner, Stephan Rauh, Martin Rumo, Karin Sonderegger, Roland Seiler

Abstract


Passes are a performance-relevant parameter in many team sports. They must be played in the highly dynamic and unpredictable contexts of interactive team competitions. The difficulty to plan passes in advance requires real-time decisions and highlights the importance of the perceptual information provided by current game contexts. This study estimates the relevance of perceptual information to passing decisions at an ecological scale by analyzing sports data from real competitions. In support of previous findings of a scenario-based investigation, open passing lanes, spatial proximity to the ball carrier, team members’ positions in front of the ball carrier, and loose defense by opposing players all significantly increased team members’ odds for receiving passes. Together, the four kinds of perceptual information enabled the correct prediction of 41% of the passes played. The prediction rate compares to a base rate of 11% and is substantially higher than that for passing decisions made in static game scenarios. The results are interpreted with regard to the relevance of the perceptual information to passing decisions made in time-constrained competitive situations.

Keywords


sports data; decision making; perceptual information

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References


Aquino, R., Puggina, E. F., Alves, I. S., & Garganta, J. (2017). Skill-related performance in soccer: A systematic review. Human Movement, 18(5), 3–24. Doi: 10.1515/humo-2017-0042

Araújo, D., Davids, K., & Hristovski, R. (2006). The ecological dynamics of decision making in sport. Psychology of Sport and Exercise, 7, 653–676. Doi: 10.1016/j.psychsport.2006.07.002

Bandura, A. (2006). Guide for creating self-efficacy scales. In F. Pajares & T. Urdan (Eds.), Self-efficacy belilefs of adolescents (pp. 307-337). Greenwich, CT: Information Age.

Bourbousson, J., & Fortes-Bourbousson, M. (2016) How do co-agents actively regulate their collective behavior states? Frontiers in Psychology, 7, 1732. Doi: 10.3389/fpsyg.2016.01732

Busemeyer, J. R., & Townsend, J. T. (1993). Decision field theory: A dynamic cognition approach to decision making. Psychological Review, 100, 432–459.

Chawla, S., Estephan, J., Gudmundsson, J., & Horton, M. (2017). Classification of passes in football using spatiotemporal data. ACM Transactions on Spatial Algorithms and Systems, 3(2), Article 6.

Cohen, J. (1988). Statistical power analysis for the behavioural sciences. (2nd ed.). New York: Academic Press.

Cohen, J. (1992). A power primer. Psychological Bulletin, 122, 155–159.

Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression /Correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Erlbaum.

Evangelos, B., Aristotelis, G., Ioannis, G., Stergios, K., & Foteini, A. (2014). Winners and losers in top level soccer. How do they differ? Journal of Physical Education and Sport, 14, 398–405. Doi: 10.7752/jpes.2014.03061

Fajen, B. R., Riley, M. A., & Turvey, M. T. (2009). Information, affordances, and the control of action. International Journal of Sport Psychology, 40, 79–107.

Frencken, W. G. P., Lemmink, K. A. P. M., & Delleman, N. J. (2010). Soccer-specific accuracy and validity of the local position measurement (LPM) system. Journal of Science and Medicine in Sport, 13, 641–645. Doi: 10.1016/j.jsams.2010.04.003

Gibson, J. J. (1979). The ecological approach to visual perception. Hillsdale, NJ: Lawrence Erlbaum Associates.

Greeno, J. G. (1994). Gibson’s affordances. Psychological Review, 101, 336–342.

Heck, R. H., Thomas, S. L., & Tabata, L. N. (2014). Multilevel and longitudinal modeling with IBM SPSS (2nd ed.). New York, NY: Routledge.

Hosmer, D. W., & Lemeshow, S. (2000). Applied logistic regression (2nd ed.). New York: Wiley.

Hughes, C. (1990). The winning formula. London, UK: HarperCollins.

Johnson, J. G. (2006). Cognitive modeling of decision making in sports. Psychology of Sport and Exercise, 7, 631–652.

Jones, P. D., James, N., & Mellalieu, S. D. (2004). Possession as a performance indicator in soccer. International Journal of Performance Analysis in Sport, 4, 98–102.

Lienert, G. A., & Raatz, U. (1998) Testaufbau und Testanalyse [Testconstruction and testanalysis] (6th ed.). Weinheim: Beltz.

Memmert, D., & Raabe, D. (2017). Revolution im Profifußball. Mit Big Data zur Spielanalyse 4.0. [Revolution in professional soccer. Using big data for game analysis 4.0]. Berlin: Springer.

Nuri, L., Shadmehr, A., Ghotbi, N., & Moghadam, B. A. (2013). Reaction time and anticipatory skill of athletes in open and closed skill-dominated sport. European Journal of Sport Science, 13, 431–436. Doi: 10.1080/17461391.2012.738712

Oesterreich, R. (1981). Handlungsregulation und Kontrolle [Action regulation and control]. München: Urban & Schwarzenberg.

Ogris, G., Leser, R., Horsak, B., Kornfeind, P., Heller, M., & Baca, A. (2012). Accuracy of the LPM tracking system considering dynamic position changes. Journal of Sports Sciences, 30, 1503–1511. Doi: 10.1080/02640414.2012.712712

Reed, L. (2004). The official FA guide to basic team coaching. London: Hodder & Stoughton.

Siegle, M., Stevens, T., & Lames, M. (2013). Design of an accuracy study for position detection in football. Journal of Sports Sciences, 31, 166–172. Doi: 10.1080/02640414.2012.723131

Stevens, T. G. A., Ruiter, C. J. de, Niel, C. van, Rhee, R. van de, Beek, P. J., & Savelsbergh, G. J. P. (2014). Measuring acceleration and deceleration in soccer-specific movements using a Local Position Measurement (LPM) system. International Journal of Sports Physiology and Performance, 9, 446–456. Doi: 10.1123/ijspp.2013-0340

Tabachnick, B. G., & Fidell, L. S. (2014). Using multivariate statistics (6th ed.). Harlow: Pearson.

Travassos, B., Araújo, D., Davids, K., Esteves, P. D., & Fernandes O. (2012). Improving passing actions in team sports by developing interpersonal interactions between players. International Journal of Sports Science & Coaching, 7, 677–688.

Turvey, M. T., & Shaw, R. E. (1995). Toward an ecological physics and a physical psychology. In R. L. Solso & D. W. Massaro (Eds.), The science of the mind: 2001 and beyond (pp. 144–169). New York: Oxford University Press.

Vercruyssen, V., De Raedt, L., & Davis, J. (2016). Qualitative spatial reasoning for soccer pass prediction. In J. Van Haaren (Ed.), Machine learning and data mining for sports analytics, ECML/PKDD workshop, Riva del Garda, 19 September 2016. Retrieved from https://lirias.kuleuven.be/bitstream/123456789/551174/1/manuscript.pdf

Vilar, L., Araújo, D., Davids, K., & Button, C. (2012). The role of ecological dynamics in analyzing performance in team sports. Sports Medicine, 42, 1–10.


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