Automated classification of passing in football

Michael Horton, Joachim Gudmundsson, Sanjay Chawla, Joël Estephan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)

Abstract

A knowledgeable observer of a game of football (soccer) can make a subjective evaluation of the quality of passes made between players during the game. In this paper we consider the problem of producing an automated system to make the same evaluation of passes. We present a model that constructs numerical predictor variables from spatiotemporal match data using feature functions based on methods from computational geometry, and then learns a classification function from labelled examples of the predictor variables. In addition, we show that the predictor variables computed using methods from computational geometry are among the most important to the learned classifiers.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
PublisherSpringer Verlag
Pages319-330
Number of pages12
Volume9078
ISBN (Print)9783319180311
DOIs
Publication statusPublished - 2015
Event19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015 - Ho Chi Minh City, Viet Nam
Duration: 19 May 201522 May 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9078
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other19th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2015
CountryViet Nam
CityHo Chi Minh City
Period19/5/1522/5/15

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ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Horton, M., Gudmundsson, J., Chawla, S., & Estephan, J. (2015). Automated classification of passing in football. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9078, pp. 319-330). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9078). Springer Verlag. https://doi.org/10.1007/978-3-319-18032-8_25