Sports involve commonly players and equipment of high dynamics. Their location and
motion data are essential for sports digitalization-related applications, such as from …

There has been rapid growth in the collection of player tracking data in recent years. These
data, providing spatiotemporal locations of players and ball at high resolution, have spurred …

The rapid progress in artificial intelligence (AI) and machine learning has opened
unprecedented analytics possibilities in various team and individual sports, including …

Understanding the principles of real-world biological multi-agent behaviors is a current
challenge in various scientific and engineering fields. The rules regarding the real-world …

In problems such as sports video analytics, it is difficult to obtain accurate frame-level
annotations and exact event duration because of the lengthy videos and sheer volume of …

The art of good defending is to prevent something from happening before it has even
happened. Virgil Van Dijk is considered one of the best defenders in world soccer as he has …

Group activity detection in soccer can be done by using either video data or player and ball
trajectory data. In current soccer activity datasets, activities are labelled as atomic events …

Basketball is one of a number of sports which, within the past decade, have seen an
explosion in quantitative metrics and methods for evaluating players and teams. However, it …

Computational analysis of multi-agent trajectories is a fundamental issue in the study of real-
world biological agents. For trajectory analysis, combining movement data with labels (eg …

Rugby union, like many sports, is based around sequences of play, yet this sequential
nature is often overlooked, for example in analyses that aggregate performance measures …