A Matrix-Based Visual Comparison of Time Series Sports Data

Abstract

In sports, large amounts of data are measured and stored with the help of modern sensors and electronic devices. In particular, for endurance sports events, time-varying data are recorded and can be used to analyze the athletes' performance. Finding patterns and issues can help better understand results in sports competitions, which is of interest for the athletes, sports managers, and trainers alike. In this paper, we introduce a matrix-based approach to visually compare similar and dissimilar periods in performances of athletes. We differentiate the performances and visually encode these differences as color-coded matrix cells. The strengths of our approach are illustrated in a case study investigating the performances of two riders in the prologue of Tour de France 2012.