Given the recent trend in Data Science (DS) and Sports Analytics, an opportunity has arisen
for utilizing Machine Learning (ML) and Data Mining (DM) techniques in sports. This paper …

Researching the field of business intelligence and analytics (BI & A) has a long tradition
within information systems research. Thereby, in each decade the rapid development of …

The increasing number of vision-based tracking systems deployed in production have
necessitated fast, robust camera calibration. In the domain of sport, the majority of current …

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 a basketball play, players who are not in possession of the ball (ie, off-ball players) can
still effectively contribute to the team's offense, such as making a sudden move to create …

With the proliferation of commercial tracking systems, sports data is being generated at an
unprecedented speed and the interest in sports play retrieval has grown dramatically as …

Sports field registration in broadcast videos is typically interpreted as the task of
homography estimation, which provides a mapping between a planar field and the …

Data visualization has the power to revolutionize sports. For example, the rise of shot maps
has changed basketball strategy by visually illustrating where “good/bad” shots are taken …

Learning physics can be seen by many as a problem, as the standard method of learning
tends to focus on remembering and using concepts that fail to construct meaning. To …

Predicting outcomes in sports is important for teams, leagues, bettors, media, and fans.
Given the growing amount of player tracking data, sports analytics models are increasingly …