Corpus ID: 237532680

Predicting the outcome of team movements - Player time series analysis using fuzzy and deep methods for representation learning

@article{Shokrollahi2021PredictingTO,
  title={Predicting the outcome of team movements - Player time series analysis using fuzzy and deep methods for representation learning},
  author={Omid Shokrollahi and Bahman Rohani and Amin Nobakhti},
  journal={ArXiv},
  year={2021},
  volume={abs/2109.07570}
}
We extract and use player position time-series data, tagged along with the action types, to build a competent model for representing team tactics behavioral patterns and use this representation to predict the outcome of arbitrary movements. We provide a framework for the useful encoding of short tactics and space occupations in a more extended sequence of movements or tactical plans. We investigate game segments during a match in which the team in possession of the ball regularly attempts to… Expand

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