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Sports Analytics

Level: 30hp (Advanced level, Master's thesis)
Number of students: 1-2
Area: Computer Science

We have several possible topics available in the field of sports analytics (particularly ice hockey, but other sports may be discussed).

Example topics:

  • detect complex events that lead to predefined outcomes in an ice hockey game
  • derive key stats for player performance (including minimal sets of key stats and introducing complex stats)
  • derive characteristics for successful line-ups
  • derive meaningful clusters of players
  • analyze injury data
  • build a knowledge graph for ice hockey and SHL in particular

You should have taken a data mining course (or TDDD43 for the last topic) and have an interest in ice hockey.

Contact: Patrick Lambrix.

Level: 16hp (Bachelor level, Bachelor's thesis)
Number of students: 1-2
Area: Computer Science

The topics above may be available if you have a background knowledge in data mining.

Topics related to design and implementation of different components of sports analytics systems are available.

Contact: Patrick Lambrix.

Page responsible: Patrick Lambrix
Last updated: 2018-04-16