Spatial movement pattern recognition in soccer based on relative player movements


Autoři: Jasper Beernaerts aff001;  Bernard De Baets aff002;  Matthieu Lenoir aff003;  Nico Van de Weghe aff001
Působiště autorů: CartoGIS, Department of Geography, Ghent University, Ghent, Belgium aff001;  KERMIT, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium aff002;  Department of Movement and Sports Sciences, Ghent University, Ghent, Belgium aff003
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: 10.1371/journal.pone.0227746

Souhrn

Knowledge of spatial movement patterns in soccer occurring on a regular basis can give a soccer coach, analyst or reporter insights in the playing style or tactics of a group of players or team. Furthermore, it can support a coach to better prepare for a soccer match by analysing (trained) movement patterns of both his own as well as opponent players. We explore the use of the Qualitative Trajectory Calculus (QTC), a spatiotemporal qualitative calculus describing the relative movement between objects, for spatial movement pattern recognition of players movements in soccer. The proposed method allows for the recognition of spatial movement patterns that occur on different parts of the field and/or at different spatial scales. Furthermore, the Levenshtein distance metric supports the recognition of similar movements that occur at different speeds and enables the comparison of movements that have different temporal lengths. We first present the basics of the calculus, and subsequently illustrate its applicability with a real soccer case. To that end, we present a situation where a user chooses the movements of two players during 20 seconds of a real soccer match of a 2016–2017 professional soccer competition as a reference fragment. Following a pattern matching procedure, we describe all other fragments with QTC and calculate their distance with the QTC representation of the reference fragment. The top-k most similar fragments of the same match are presented and validated by means of a duo-trio test. The analyses show the potential of QTC for spatial movement pattern recognition in soccer.

Klíčová slova:

Calculus – Data mining – Games – Musculoskeletal system – Pattern recognition receptors – Qualitative studies – Sequence alignment – Sports


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