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Autor*innen: Brandt, Markus; Brefeld, Ulf
Titel: Graph-based approaches for analyzing team interaction on the example of soccer
Aus: ECML/PKDD (Hrsg.): Proceedings of the ECML/PKDD Workshop on Machine Learning and Data Mining for Sports Analytics 11 September 2015 Porto, Portugal, Porto: European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2015 , S. 8
URL: https://dtai.cs.kuleuven.be/events/MLSA15/papers/mlsa15_submission_3.pdf
Dokumenttyp: 4. Beiträge in Sammelwerken; Tagungsband/Konferenzbeitrag/Proceedings
Sprache: Englisch
Schlagwörter: Deutschland; Fußball; Gruppe; Interaktion; Prognose; Spiel; Sport
Abstract (english): We present a graph-based approach to analyzing player interaction in team sports. A simple pass-based representation is presented that is subsequently used together with the PageRank algorithm to identify the importance of the players. Aggregating player scores to team values allows for turning our approach into a predictor of the winning team. We report on empirical results on five German Bundesliga seasons. (DIPF/Orig.)
DIPF-Abteilung: Informationszentrum Bildung