A Visual Data Analysis Tool for Sport Player Performance Benchmarking, Comparison, and Change Detection

Sports coaches today have access to a wide variety of information sources that describe the performance of their players. However, despite this great wealth of information, most techniques used to analyse performance require a significant amount of manual processing and continue to rely heavily on input from human experts. In this paper we propose an automated approach to analyse player performance. Specifically, we propose a team benchmarking and concept drift tracking based system that (1) generates adaptive baseline player performance norms, (2) interprets player performance over different time lines and (3) identifies and describes key turning points in player performance. The concept drift technique that we describe uses a combination of overlapping data windows and decision tree based learning to process the data.