The group on Sports Analytics was started at the end of 2017. We are researchers from different labs at Linköping University, primarily from its Department of Computer and Information Science (IDA) with a common interest in various aspects of Sports Analytics.
Sports analytics deals with using data related to sports events to obtain insights about the sport and its surroundings. In our group we interpret this broadly. The insights can relate to such things as player and team performance, strategies, training, injuries, and rules of the game.
In the news
• LiU magasin published an article (in Swedish) on our sports analytics work based on an interview with Patrick Lambrix and Niklas Carlsson. Swedish and English versions were published on the LiU web.
• Articles about our project on visualization of ice hockey data in cooperation with Linköping Hockey Club (LHC) were posted on LHC's web page and hockeysverige.se.
Master/Bachelor thesis subjects
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).
• 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
• visualization of game and season data
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.