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

TL;DR

This paper introduces a visualization method using GoogleVis Motion Charts to analyze and interpret spatio-temporal player movements in team sports, demonstrated through a basketball case study.

Contribution

It proposes a user-friendly visualization approach for sports movement data, filling a gap in accessible tools for analyzing high-definition trajectory data.

Findings

Visualization aids in understanding player movements

Supports preliminary analysis in sports research

Facilitates interpretation of complex spatio-temporal data

Abstract

To analyze the movements and to study the trajectories of players is a crucial need for a team when it looks to improve its chances of winning a match or to understand its performances. State of the art tracking systems now produce spatio-temporal traces of player trajectories with high definition and frequency that has facilitated a variety of research efforts to extract insight from the trajectories. Despite many methods borrowed from different disciplines (machine learning, network and complex systems, GIS, computer vision, statistics) has been proposed to answer to the needs of teams, a friendly and easy-to-use approach to visualize spatio-temporal movements is still missing. This paper suggests the use of gvisMotionChart function in GoogleVis R package. I present and discuss results of a basketball case study. Data refers to a match played by an italian team militant in "C-gold" league on March 22nd, 2016. With this case study I show that such a visualization approach could be useful in supporting researcher on preliminar stages of their analysis on sports' movements, and to facilitate the interpretation of their results.