ML Anthology

Probabilistic Movement Models and Zones of Control

Ulf Brefeld, Jan Lasek, Sebastian Mair
MLJ 2019 pp. 127-147
doi:10.1007/S10994-018-5725-1 /mlj/2019/brefeld2019mlj-probabilistic/

Abstract

Coordinated movements of players are key to success in team sports. However, traditional models for player movements are based on unrealistic assumptions and their analysis is prone to errors. As a remedy, we propose to estimate individual movement models from positional data and show how to turn these estimates into accurate and realistic zones of control. Our approach accounts for characteristic traits of players, scales with large amounts of data, and can be efficiently computed in a distributed fashion. We report on empirical results.

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Text

Brefeld et al. "Probabilistic Movement Models and Zones of Control." Machine Learning, 2019. doi:10.1007/S10994-018-5725-1

Markdown

[Brefeld et al. "Probabilistic Movement Models and Zones of Control." Machine Learning, 2019.](https://mlanthology.org/mlj/2019/brefeld2019mlj-probabilistic/) doi:10.1007/S10994-018-5725-1

BibTeX

@article{brefeld2019mlj-probabilistic,
  title     = {{Probabilistic Movement Models and Zones of Control}},
  author    = {Brefeld, Ulf and Lasek, Jan and Mair, Sebastian},
  journal   = {Machine Learning},
  year      = {2019},
  pages     = {127-147},
  doi       = {10.1007/S10994-018-5725-1},
  volume    = {108},
  url       = {https://mlanthology.org/mlj/2019/brefeld2019mlj-probabilistic/}
}