In this project, we want to create a demonstrator able to support existing sports analytics companies that are currently unable to automatically analyze complex player interactions
based on x,y,t-coordinates of players. Building upon UGent research results on the geographical information model QTC (qualitative trajectory calculus), we want to develop a system that can detect similar player patterns within a database of spatiotemporal data. To do so, we want to combine the unique QTC method, that enables efficient data pattern evaluation of moving objects, with the available expertise
in information processing and evaluate the demonstrator with a team of sports tactics specialists. The targeted application is a tool that can be used by trainers, coaches, sports performance
and game analysts, etc., with the objective to measure team organization, to plan tactics and strategies, and to evaluate particular team interventions by the coaching staff. With this
concept, we want to enforce the multi-million sports clubs to obtain deeper quantified insights in sports team tactics, and thereby, improve their performance in order to win more games
and championships. The main goal is to go for a license agreement with one of the (8) companies in this area.