Action rate models for predicting actions in soccer

Uwe Dick () and Ulf Brefeld ()
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Uwe Dick: Leuphana University of Lüneburg
Ulf Brefeld: Leuphana University of Lüneburg

AStA Advances in Statistical Analysis, 2023, vol. 107, issue 1, No 3, 29-49

Abstract: Abstract We present a data-driven approach to predict the next action in soccer. We focus on passing actions of the ball possessing player and aim to forecast the pass itself and when, in time, the pass will be played. At the same time, our model estimates the probability that the player loses possession of the ball before she can perform the action. Our approach consists of parameterized exponential rate models for all possible actions that are adapted to historic data with graph recurrent neural networks to account for inter-dependencies of the output space (i.e., the possible actions). We report on empirical results.

Keywords: Soccer analytics; Football; Elite sports; Actions; Rate models; Game flow; GRNNs (search for similar items in EconPapers)
Date: 2023
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DOI: 10.1007/s10182-022-00435-x

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