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Transforming Football Data into Object-centric Event Logs with Spatial Context Information

arXiv 2507.12504 ↗First posted 16 Jul 2025cs.DB cs.AIcited by 0

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Abstract (arXiv)

Object-centric event logs expand the conventional single-case notion event log by considering multiple objects, allowing for the analysis of more complex and realistic process behavior. However, the number of real-world object-centric event logs remains limited, and further studies are needed to test their usefulness. The increasing availability of data from team sports can facilitate object-centric process mining, leveraging both real-world data and suitable use cases. In this paper, we present a framework for transforming football (soccer) data into an object-centric event log, further enhanced with a spatial dimension. We demonstrate the effectiveness of our framework by generating object-centric event logs based on real-world football data and discuss the results for varying process representations. With our paper, we provide the first example for object-centric event logs in football analytics. Future work should consider variant analysis and filtering techniques to better handle variability

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 2 of its 12 references that are in the map. First posted on arXiv 16 Jul 2025.

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References · 2

  1. 2022A Comprehensive Review of Computer Vision in Sports: Open Issues, Future Trends and Research Directionscited by 21
  2. 2021Privacy and Confidentiality in Process Mining -- Threats and Research Challengescited by 6

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