Similarity of football players using passing sequences

(Ähnlichkeit von Fußballspielern anhand von Passsequenzen)

Association football has been the subject of many research studies. In this work we present a study on player similarity using passing sequences extracted from games from the top-5 European football leagues during the 2017/2018 season. We present two different approaches: first, we only count the motifs a player is involved in; then we also take into consideration the specific position a player occupies in each motif. We also present a new way to objectively judge the quality of the generated models in football analytics. Our results show that the study of passing sequences can be used to study player similarity with relative success.
© Copyright 2022 Machine Learning and Data Mining for Sports Analytics. MLSA 2021. Communications in Computer and Information Science. Veröffentlicht von Springer. Alle Rechte vorbehalten.

Bibliographische Detailangaben
Schlagworte:
Notationen:Spielsportarten Naturwissenschaften und Technik
Tagging:Passspiel
Veröffentlicht in:Machine Learning and Data Mining for Sports Analytics. MLSA 2021. Communications in Computer and Information Science
Sprache:Englisch
Veröffentlicht: Cham Springer 2022
Schriftenreihe:Communications in Computer and Information Science, 1571
Online-Zugang:https://doi.org/10.1007/978-3-031-02044-5_5
Seiten:51-61
Dokumentenarten:Artikel
Level:hoch