Team-based invasion sports such as football, basketball, and hockey are similar in the
sense that the players are able to move freely around the playing area and that player and …

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

It is common practice amongst coaches and analysts to search for key performance
indicators related to attacking play in football. Match analysis in professional football has …

The sports domain presents a number of significant computational challenges for artificial
intelligence (AI) and machine learning (ML). In this paper, we explore the techniques that …

In soccer, the most frequent event that occurs is a pass. For a trained eye, there are a myriad
of adjectives which could describe this event (eg," majestic pass"," conservative" to" poor …

Although the collection of player and ball tracking data is fast becoming the norm in
professional sports, large-scale mining of such spatiotemporal data has yet to surface. In this …

The" Moneyball" revolution coincided with a shift in the way professional sporting
organizations handle and utilize data in terms of decision making processes. Due to the …

One of the main shortcomings of event data in football, which has been extensively used for
analytics in the recent years, is that it still requires manual collection, thus limiting its …

To the trained-eye, experts can often identify a team based on their unique style of play due
to their movement, passing and interactions. In this paper, we present a method which can …

Quantitative evaluation of the ability of soccer players to contribute to team offensive
performance is typically based on goals scored, assists made, and shots taken. In this paper …