Learning to Rate Player Positioning in Soccer

Publikationen: Beiträge in ZeitschriftenZeitschriftenaufsätze

Authors

We investigate how to learn functions that rate game situations on a soccer pitch according to their potential to lead to successful attacks. We follow a purely data-driven approach using techniques from deep reinforcement learning to valuate multiplayer positionings based on positional data. Empirically, the predicted scores highly correlate with dangerousness of actual situations and show that rating of player positioning without expert knowledge is possible.

OriginalspracheEnglisch
ZeitschriftBig Data
Band7
Ausgabennummer1
Seiten (von - bis)71-82
Anzahl der Seiten12
ISSN2167-6461
DOIs
PublikationsstatusErschienen - 18.03.2019

DOI

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