Competition-Wide Evaluation of Individual and Team Movements in Soccer

Laszlo Gyarmati, Mohamed Hefeeda

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

1 Citation (Scopus)

Abstract

It is challenging to get access to datasets related to the physical performance of soccer players. The teams consider such information highly confidential, especially if it covers in-game performance. Hence, most analysis and evaluation of the players' performance do not contain much information on the physical aspect of the game. We propose a novel method to solve this issue by deriving individual and team movements in soccer. We use event-based datasets allowing us to analyze the movement profiles of potentially tens of thousands of players. By analyzing the similarity of players based on their movements we find that C. Ronaldo and Ruben Castro were extremely similar despite having two orders of magnitude in their market values, 29 players are more similar to Ronaldo than the most similar counterpart of Messi based on the consistency and uniqueness of their trajectories, and that teams use an abundance of unique attacking schemes, 8909 unique attacks were launched in the 2012/13 season of the Spanish league. Our study reveals novel, actionable insights for the soccer industry at an unprecedented scale.

Original languageEnglish
Title of host publicationProceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
EditorsCarlotta Domeniconi, Francesco Gullo, Francesco Bonchi, Francesco Bonchi, Josep Domingo-Ferrer, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Ricardo Baeza-Yates, Zhi-Hua Zhou, Xindong Wu
PublisherIEEE Computer Society
Pages144-151
Number of pages8
ISBN (Electronic)9781509054725
DOIs
Publication statusPublished - 2 Jul 2016
Event16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 - Barcelona, Spain
Duration: 12 Dec 201615 Dec 2016

Publication series

NameIEEE International Conference on Data Mining Workshops, ICDMW
Volume0
ISSN (Print)2375-9232
ISSN (Electronic)2375-9259

Other

Other16th IEEE International Conference on Data Mining Workshops, ICDMW 2016
CountrySpain
CityBarcelona
Period12/12/1615/12/16

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Keywords

  • Football
  • Movements
  • Soccer
  • Sport analytics

ASJC Scopus subject areas

  • Computer Science Applications
  • Software

Cite this

Gyarmati, L., & Hefeeda, M. (2016). Competition-Wide Evaluation of Individual and Team Movements in Soccer. In C. Domeniconi, F. Gullo, F. Bonchi, F. Bonchi, J. Domingo-Ferrer, R. Baeza-Yates, R. Baeza-Yates, R. Baeza-Yates, Z-H. Zhou, & X. Wu (Eds.), Proceedings - 16th IEEE International Conference on Data Mining Workshops, ICDMW 2016 (pp. 144-151). [7836659] (IEEE International Conference on Data Mining Workshops, ICDMW; Vol. 0). IEEE Computer Society. https://doi.org/10.1109/ICDMW.2016.0028