Spatio-Temporal Movements in Team Sports: A Visualization approach using Motion Charts

A new approach to performance analysis in team sports consists in study- ing movements and trajectories of players during the game. State of the art tracking systems produce spatio-temporal traces of players that have fa- cilitated a variety of research aimed to to extract insight from trajectories. Several methods borrowed from machine learning, network and complex sys- tems, geographic information system, computer vision and statistics have been proposed. However, the use of an effective and easy-to-use visual tool in support to these methods is of major importance. To this scope this pa- per suggests the use of motion charts, built by means of the open-source gvisMotionChart function in googleVis package in R, a user-friendly pro- cedure that also allows to easily import data. A basketball case study is presented. Data refers to a match played by an italian team militant in C-gold league on March 22nd, 2016. Analyses show that motion charts give insights on different spacing structures among offensive and defensive actions, corroborating evidences from other supporting analyses.