UnFOOT: Unsupervised Football Analytics Tool

1Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

Labelled football (soccer) data is hard to acquire and it usually needs humans to annotate the match events. This process makes it more expensive to be obtained by smaller clubs. UnFOOT (Unsupervised Football Analytics Tool) combines data mining techniques and basic statistics to measure the performance of players and teams from positional data. The capabilities of the tool involve preprocessing the match data, extraction of features, visualization of player and team performance. It also has built-in data mining techniques, such as association rule mining, subgroup discovery and a proposed approach to look for frequent distributions.

Cite

CITATION STYLE

APA

Coutinho, J. C., Moreira, J. M., & de Sá, C. R. (2020). UnFOOT: Unsupervised Football Analytics Tool. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11908 LNAI, pp. 786–789). Springer. https://doi.org/10.1007/978-3-030-46133-1_52

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free