Recently, sports analytics has turned into an important research area of visual analytics and may provide interesting findings, such as the best player of the season, for various kinds of sports. Soccer is a very popular and tactical game, which also attracted great attention in the last few years. However, the search for complex game movements is a very crucial and challenging task. We present a system for searching trajectory data in soccer matches by means of an interactive search interface that enables the user to sketch a situation of interest. Furthermore, we apply a domain specific prefiltering process to extract a set of local movement segments, which are similar to a given sketch. Our approach comprises single-trajectory, multi-trajectory, and event-specific search functions based on two different similarity measures. To demonstrate the usefulness of our approach, we define a domain specific task analysis and conduct a case study together with a domain expert from FC Bayern München by investigating a real-world soccer match. Finally, we show that multi-trajectory search in combination with event-specific filtering is needed to describe and retrieve complex moves in soccer matches.
Lin Shao, Dominik Sacha, Benjamin Neldner, Manuel Stein, Tobias Schreck, "Visual-Interactive Search for Soccer Trajectories to Identify Interesting Game Situations" in Proc. IS&T Int’l. Symp. on Electronic Imaging: Visualization and Data Analysis, 2016, https://doi.org/10.2352/ISSN.2470-1173.2016.1.VDA-510