mlsanityData to 14 Oct 2026

SoccerCPD: Formation and Role Change-Point Detection in Soccer Matches Using Spatiotemporal Tracking Data

arXiv 2206.10926 ↗First posted 22 Jun 2022stat.AP stat.MLcited by 7

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Abstract (arXiv)

In fluid team sports such as soccer and basketball, analyzing team formation is one of the most intuitive ways to understand tactics from domain participants' point of view. However, existing approaches either assume that team formation is consistent throughout a match or assign formations frame-by-frame, which disagree with real situations. To tackle this issue, we propose a change-point detection framework named SoccerCPD that distinguishes tactically intended formation and role changes from temporary changes in soccer matches. We first assign roles to players frame-by-frame and perform two-step change-point detections: (1) formation change-point detection based on the sequence of role-adjacency matrices and (2) role change-point detection based on the sequence of role permutations. The evaluation of SoccerCPD using the ground truth annotated by domain experts shows that our method accurately detects the points of tactical changes and estimates the formation and role assignment per segment. Lastly, we introduce practical use-cases that domain participants can easily interpret and utilize.

Key facts. Cited by 7 papers in the map (data through 14 Oct 2026). Builds on 5 of its 39 references that are in the map. First posted on arXiv 22 Jun 2022.

Builds on

5 of 39 references.

References · 5

  1. 2015Heterogeneous Change Point Inferencecited by 4
  2. 2017Asymptotic Distribution-Free Change-Point Detection for Multivariate and non-Euclidean Datacited by 4
  3. 2015Dirichlet Process Hidden Markov Multiple Change-point Modelcited by 1
  4. 2020Asymptotic distribution-free change-point detection for data with repeated observationscited by 1
  5. 20216MapNet: Representing soccer players from tracking data by a triplet networkcited by 1

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 2; 2024: 1; 2025: 3; 2026: 1.

7 papers.