Literature DB >> 33750889

Space evaluation in football games via field weighting based on tracking data.

Takuma Narizuka1, Yoshihiro Yamazaki2, Kenta Takizawa3.   

Abstract

In football game analysis, space evaluation is an important issue because it is directly related to the quality of ball passing or player formations. Previous studies have primarily focused on a field division approach wherein a field is divided into dominant regions in which a certain player can arrive prior to any other players. However, the field division approach is oversimplified because all locations within a region are regarded as uniform herein. The objective of the current study is to propose a fundamental framework for space evaluation based on field weighting. In particular, we employed the motion model and calculated a minimum arrival time [Formula: see text] for each player to all locations on the football field. Our main contribution is that two variables [Formula: see text] and [Formula: see text] corresponding to the minimum arrival time for offense and defense teams are considered; using [Formula: see text] and [Formula: see text], new orthogonal variables [Formula: see text] and [Formula: see text] are defined. In particular, based on real datasets comprising of data from 45 football games of the J1 League in 2018, we provide a detailed characterization of [Formula: see text] and [Formula: see text] in terms of ball passing. By using our method, we found that [Formula: see text] and [Formula: see text] represent the degree of safety for a pass made to [Formula: see text] at t and degree of sparsity of [Formula: see text] at t, respectively; the success probability of passes could be well-fitted using a sigmoid function. Moreover, a new type of field division approach and evaluation of ball passing just before shots using real game data are discussed.

Entities:  

Year:  2021        PMID: 33750889      PMCID: PMC7970928          DOI: 10.1038/s41598-021-84939-7

Source DB:  PubMed          Journal:  Sci Rep        ISSN: 2045-2322            Impact factor:   4.379


  3 in total

1.  Spatial dynamics of team sports exposed by Voronoi diagrams.

Authors:  Sofia Fonseca; João Milho; Bruno Travassos; Duarte Araújo
Journal:  Hum Mov Sci       Date:  2012-07-05       Impact factor: 2.161

2.  Quantifying the performance of individual players in a team activity.

Authors:  Jordi Duch; Joshua S Waitzman; Luís A Nunes Amaral
Journal:  PLoS One       Date:  2010-06-16       Impact factor: 3.240

3.  A public data set of spatio-temporal match events in soccer competitions.

Authors:  Luca Pappalardo; Paolo Cintia; Alessio Rossi; Emanuele Massucco; Paolo Ferragina; Dino Pedreschi; Fosca Giannotti
Journal:  Sci Data       Date:  2019-10-28       Impact factor: 6.444

  3 in total
  1 in total

1.  Application of Machine Learning and Information Coverage Centralized Genetic Method in Safety Management of Football Training.

Authors:  Chao Zhang; Fang Tu
Journal:  Comput Intell Neurosci       Date:  2022-07-14
  1 in total

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