From game events to team tactics: Visual analysis of dangerous situations in multi-match data

Abstract

Sport analytics in general and soccer analytics in particular constitute quickly growing markets when it comes to professional analyses and visualizations. From a data analysis research perspective, soccer is a rich source of geospatial and temporal movement data, with high details and a controlled environment. However, soccer movement is complex as its compounds are actions and reactions of two opposing teams with inverse goals. Common analyses performed today are typically oriented towards statistical analysis and considering aggregate measurements. In this work, we propose a set of effective visual-interactive methods for investigating set plays as a first step towards semi-automated analysis of tactic behavior. In our analytic design, we follow the so-called Information-seeking Mantra by Ben Shneiderman by providing overview visualizations, interactive refinements, and detailed analysis views. We take an applied approach in showing case studies that give evidence for the applicability and merits of our proposed techniques.