Through the gaps: uncovering tactical line-breaking passes with clustering

Karakuş, Oktay ORCID: https://orcid.org/0000-0001-8009-9319 and Arkadaş, Hasan 2026. Through the gaps: uncovering tactical line-breaking passes with clustering. Presented at: 12th International Workshop, MLSA 2025, Porto, Portugal, 15 September 2025. Published in: Rios-Neto, Hugo, Robberechts, Pieter, Van Roy, Maaike and Zimmermann, Albrecht eds. Machine Learning and Data Mining for Sports Analytics. Communications in Computer and Information Science. Communications in Computer and Information Science , vol.2833 Cham: Springer, pp. 86-96. 10.1007/978-3-032-15165-0_7

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Abstract

Line-breaking passes (LBPs) are crucial tactical actions in football, allowing teams to penetrate defensive lines and access high-value spaces. In this study, we present an unsupervised, clustering-based framework for detecting and analysing LBPs using synchronised event and tracking data from elite matches. Our approach models opponent team shape through vertical spatial segmentation and identifies passes that disrupt defensive lines within open play. Beyond detection, we introduce several tactical metrics, including the space build-up ratio (SBR) and two chain-based variants, LBPCh and LBPCh, which quantify the effectiveness of LBPs in generating immediate or sustained attacking threats. We evaluate these metrics across teams and players in the 2022 FIFA World Cup, revealing stylistic differences in vertical progression and structural disruption. The proposed methodology is explainable, scalable, and directly applicable to modern performance analysis and scouting workflows.

Item Type:	Conference or Workshop Item - published (Paper)
Date Type:	Publication
Status:	Published
Schools:	Schools > Computer Science & Informatics
Publisher:	Springer
ISBN:	9783032151643
ISSN:	1865-0929
Last Modified:	09 Feb 2026 12:31
URI:	https://orca.cardiff.ac.uk/id/eprint/184545

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