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Deb, B, Navarro, JF, McRobert, AP and Jarman, I (2024) Finding repeatable progressive pass clusters and application in international football. Journal of Sports Analytics, 9 (4). pp. 289-303. ISSN 2215-020X
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Abstract
Progressive passing in football (soccer) is a key aspect in creating positive possession outcomes. Whilst this is well established, there is not a consistent way to describe the different types of progressive passes. We expand on the previous literature, providing a complete methodological approach to progressive pass clustering from selection of the number of clusters (k) to risk-reward profiling of these progressive pass types. In this paper the Separation and Concordance (SeCo) framework is utilised to provide a process to analyse k-means clustering solutions in a more repeatable way. The results demonstrate that we can find stable progressive pass clusters in International Football and their efficacy with progressive passes “Mid Central to Mid Half Space” in build-up and “Mid Half Space to Final Central” into the final 3rd having the best balance between risk (turnover) and reward (shot created) in the subsequent possession. This allowed for opposition profiling of player and team patterns in different phases of play, with a case study presented for the teams in the Last 16 of the 2022 World Cup.
| Item Type: | Article |
|---|---|
| Subjects: | Q Science > QA Mathematics > QA75 Electronic computers. Computer science G Geography. Anthropology. Recreation > GV Recreation Leisure > GV561 Sports |
| Divisions: | Computer Science & Mathematics Sport & Exercise Sciences |
| Publisher: | IOS Press |
| SWORD Depositor: | A Symplectic |
| Date Deposited: | 19 Feb 2024 12:00 |
| Last Modified: | 19 Feb 2024 12:00 |
| DOI or ID number: | 10.3233/jsa-220732 |
| URI: | https://researchonline.ljmu.ac.uk/id/eprint/22645 |
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