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Football Analytics Hackathon

MHP00004Support Electives5 ECTSEnglishwinter semesterTUM School of Medicine and Health
AI-edited module sheet. Based on the TUMonline module description, edited for readability.Original in TUMonline

What it is about

You work in interdisciplinary teams on real questions of game analysis in professional football. You learn to specify football-specific concepts from sports science and computer science, develop technical solutions to detect in tracking data, validate them with video, and generate corresponding performance indicators as well as understandable visualizations.

What you will be able to do

  • Understanding typical professional sports data (spatiotemporal tracking data, event data)
  • Application of methods such as network analysis, machine learning and visual analytics
  • Development of sports data products for media, information providers and elite sport

What the module consists of

  • Blockveranstaltung (Hackathon, 12.01.2026–17.01.2026)Solving the posed challenges in teams; implementation and validation of solutions
  • Preparatory sessions (first 4 weeks of the semester)Exercises on the data used in the Hackathon as preparation

Teaching method

  • Project work in interdisciplinary teamsDeveloping practical solutions for match-analysis tasks
  • Working on real spatiotemporal data of the DFLImplementation of intelligent algorithms to derive complex performance indicators
  • Visual AnalyticsCreation of interpretable visualizations to communicate the results
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Official page in TUMonline · Details are not binding.