Estimating the maximal speed of soccer players on scale

Research output: Contribution to journalConference articlepeer-review

Abstract

Excellent physical performance of soccer players is inevitable for the success of a team. Despite of this, a large-scale, quantitative analysis of the maximal speed of the players is missing due to the sensitive nature of trajectory datasets. We propose a novel method to derive the in-game speed profile of soccer players from event-based datasets, which are widely accessible. We show that eight games are enough to derive an accurate speed profile. We also reveal team level discrepancies: to estimate the maximal speed of the players of some teams 50% more games may be necessary. The speed characteristics of the players provide valuable insights for domains such as player scouting.

Original languageEnglish
Pages (from-to)96-103
Number of pages8
JournalCEUR Workshop Proceedings
Volume1970
Publication statusPublished - 2015
Event2nd Workshop on Machine Learning and Data Mining for Sports Analytics, MLSA 2015, co-located with 2015 European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML PKDD 2015 - Porto, Portugal
Duration: 11 Sept 201511 Sept 2015

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