We have several possible topics available in the field of sports analytics. (We consider different sports, but have most personal interest and contacts with an elite team in ice hockey).

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
• build a knowledge graph for ice hockey and SHL in particular
• visualization of game and season data

For concrete examples of projects look at former theses.

Prerequisites:
For some topics you should have taken a data mining and/or machine learning course. For the knowledge graph topic course TDDD43 is recommended. For the visualization topic a course in HCI is recommended.

Contact: Patrick Lambrix.