Identification, Computational Examination, Critical Assessment and Future Considerations of Distance Variables to Assess Collective Tactical Behaviour in Team Invasion Sports by Positional Data: A Systematic Review
Rico González, Markel
Pino Ortega, José
Nakamura, Fabio Y.
Moura, Felipe Arruda
Los Arcos Larumbe, Asier
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International Journal of Environmental Research and Public Health 17(6) : (2020) // Article ID 1952
The aim of the study was the identification, computational examination, critical assessment and future considerations of distance variables to assess collective tactical behaviour in team invasion sports by positional data. A total of 3973 documents were initially retrieved. Finally, 72 articles met the inclusion criteria, but only 26 suggested original tactical variables based on the distance variables. The distance variables can be classified into player–player, player–space, player–ball, and Geometrical Centre (GC)–GC /player/space/goal. In addition, several nonlinear techniques have been used to analyse the synchronisation and predictability of the distance variables in team invasion sports. Player–opponent distance is of special interest in those sports in which man-marking is commonly used, and in the micro-structure close to scoring situations in all sports. In addition, player–player distances are used to measure the length and the width of the team and player–GC distance to assess the dispersion of the team. Player–space distances have been measured to assess the distance of the player/team-line to relevant areas of the playing space. Several techniques have been applied to analyse the synchronisation (i.e., Hilbert transformation and cluster analyses) and the complexity and regularity or predictability (i.e., approximate entropies, sample entropy, cross-sample entropy and average mutual information) of the distance variables in team invasion sports, revealing the lack of consensus. Although the distance variables may be interesting tactical variables when considered in isolation, it would be enriching to analyse the relationship among these variables.
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