Similarity of Football Players Using Passing Sequences Alberto Barbosa, Pedro Ribeiro and Inês Dutra 2021

Abstract

Association football has been the subject of many research studies. In this work we present a study on player similarity using passing sequences extracted from games from the top-5 European football leagues during the 2017/2018 season. We present two different approaches: first, we only count the motifs a player is involved in; then we also take into consideration the specific position a player occupies in each motif. We also present a new way to objectively judge the quality of the generated models in football analytics. Our results show that the study of passing sequences can be used to study player similarity with relative success.

Digital Object Identifier (DOI)

doi 10.1007/978-3-031-02044-5_5

Publication in PDF format

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Journal/Conference/Book

8th Workshop on Machine Learning and Data Mining for Sports Analytics

Reference (text)

Alberto Barbosa, Pedro Ribeiro and Inês Dutra. Similarity of Football Players Using Passing Sequences. Proceedings of the 8th Workshop on Machine Learning and Data Mining for Sports Analytics (MLSA), pp. 51-61, Springer, Bilbao, Spain, September, 2021.

Bibtex

@inproceedings{ribeiro-MLSA2021,
  author = {Alberto Barbosa and  Pedro Ribeiro and Inês Dutra},
  title = {Similarity of Football Players Using Passing Sequences},
  doi = {10.1007/978-3-031-02044-5_5},
  booktitle = {8th Workshop on Machine Learning and Data Mining for Sports Analytics},
  pages = {51-61},
  publisher = {Springer},
  month = {September},
  year = {2021}
}