Constructing Spaces and Times for Tactical Analysis in Football

A possible objective in analyzing trajectories of multiple simultaneously moving objects, such as football players during a game, is to extract and understand the general patterns of coordinated movement in different classes of situations as they develop. For achieving this objective, we propose an...

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Veröffentlicht in:IEEE transactions on visualization and computer graphics 2021-04, Vol.27 (4), p.2280-2297
Hauptverfasser: Andrienko, Gennady, Andrienko, Natalia, Anzer, Gabriel, Bauer, Pascal, Budziak, Guido, Fuchs, Georg, Hecker, Dirk, Weber, Hendrik, Wrobel, Stefan
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container_issue 4
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container_title IEEE transactions on visualization and computer graphics
container_volume 27
creator Andrienko, Gennady
Andrienko, Natalia
Anzer, Gabriel
Bauer, Pascal
Budziak, Guido
Fuchs, Georg
Hecker, Dirk
Weber, Hendrik
Wrobel, Stefan
description A possible objective in analyzing trajectories of multiple simultaneously moving objects, such as football players during a game, is to extract and understand the general patterns of coordinated movement in different classes of situations as they develop. For achieving this objective, we propose an approach that includes a combination of query techniques for flexible selection of episodes of situation development, a method for dynamic aggregation of data from selected groups of episodes, and a data structure for representing the aggregates that enables their exploration and use in further analysis. The aggregation, which is meant to abstract general movement patterns, involves construction of new time-homomorphic reference systems owing to iterative application of aggregation operators to a sequence of data selections. As similar patterns may occur at different spatial locations, we also propose constructing new spatial reference systems for aligning and matching movements irrespective of their absolute locations. The approach was tested in application to tracking data from two Bundesliga games of the 2018/2019 season. It enabled detection of interesting and meaningful general patterns of team behaviors in three classes of situations defined by football experts. The experts found the approach and the underlying concepts worth implementing in tools for football analysts.
doi_str_mv 10.1109/TVCG.2019.2952129
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source IEEE Electronic Library (IEL)
subjects Agglomeration
Aggregates
Companies
coordinated movement
Data mining
Data structures
Data visualization
Football
Games
movement data
Moving object recognition
Reference systems
soccer
sport analytics
Sports
Trajectory
Trajectory analysis
Visual analytics
title Constructing Spaces and Times for Tactical Analysis in Football
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