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Coordinate Transformations for Characterization and Cluster Analysis of Spatial Configurations in Football

Andrienko, Gennady ; Andrienko, Natalia ; Budziak, Guido ; Landesberger von Antburg, Tatiana ; Weber, Hendrik (2016)
Coordinate Transformations for Characterization and Cluster Analysis of Spatial Configurations in Football.
European Conference, ECML PKDD 2016. Riva del Garda, Italy (September 19-23)
doi: 10.1007/978-3-319-46131-1_6
Konferenzveröffentlichung, Bibliographie

Kurzbeschreibung (Abstract)

Current technologies allow movements of the players and the ball in football matches to be tracked and recorded with high accuracy and temporal frequency. We demonstrate an approach to analyzing football data with the aim to find typical patterns of spatial arrangement of the field players. It involves transformation of original coordinates to relative positions of the players and the ball with respect to the center and attack vector of each team. From these relative positions, we derive features for characterizing spatial configurations in different time steps during a football game. We apply clustering to these features, which groups the spatial configurations by similarity. By summarizing groups of similar configurations, we obtain representation of spatial arrangement patterns practiced by each team. The patterns are represented visually by density maps built in the teams' relative coordinate systems. Using additional displays, we can investigate under what conditions each pattern was applied.

Typ des Eintrags: Konferenzveröffentlichung
Erschienen: 2016
Autor(en): Andrienko, Gennady ; Andrienko, Natalia ; Budziak, Guido ; Landesberger von Antburg, Tatiana ; Weber, Hendrik
Art des Eintrags: Bibliographie
Titel: Coordinate Transformations for Characterization and Cluster Analysis of Spatial Configurations in Football
Sprache: Englisch
Publikationsjahr: September 2016
Verlag: Springer
Buchtitel: Machine Learning and Knowledge Discovery in Databases, Proceedings, Part II
Reihe: Lecture Notes in Computer Science (LNCS); 9853
Veranstaltungstitel: European Conference, ECML PKDD 2016
Veranstaltungsort: Riva del Garda, Italy
Veranstaltungsdatum: September 19-23
DOI: 10.1007/978-3-319-46131-1_6
Kurzbeschreibung (Abstract):

Current technologies allow movements of the players and the ball in football matches to be tracked and recorded with high accuracy and temporal frequency. We demonstrate an approach to analyzing football data with the aim to find typical patterns of spatial arrangement of the field players. It involves transformation of original coordinates to relative positions of the players and the ball with respect to the center and attack vector of each team. From these relative positions, we derive features for characterizing spatial configurations in different time steps during a football game. We apply clustering to these features, which groups the spatial configurations by similarity. By summarizing groups of similar configurations, we obtain representation of spatial arrangement patterns practiced by each team. The patterns are represented visually by density maps built in the teams' relative coordinate systems. Using additional displays, we can investigate under what conditions each pattern was applied.

Freie Schlagworte: Cluster analysis
Fachbereich(e)/-gebiet(e): 20 Fachbereich Informatik
20 Fachbereich Informatik > Mathematisches und angewandtes Visual Computing
Hinterlegungsdatum: 08 Mai 2019 06:33
Letzte Änderung: 22 Jul 2021 18:31
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