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Action rate models for predicting actions in soccer

Author

Listed:
  • Uwe Dick

    (Leuphana University of Lüneburg)

  • Ulf Brefeld

    (Leuphana University of Lüneburg)

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.

Suggested Citation

  • Uwe Dick & Ulf Brefeld, 2023. "Action rate models for predicting actions in soccer," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 107(1), pages 29-49, March.
    • Handle: RePEc:spr:alstar:v:107:y:2023:i:1:d:10.1007_s10182-022-00435-x
    DOI: 10.1007/s10182-022-00435-x
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