Deep learning has the potential to revolutionize sports performance, with applications
ranging from perception and comprehension to decision. This paper presents a …

Advanced data collection technologies, computational tools, and sophisticated algorithms
have a revolutionary impact on sports analytics on various aspects of sports, from athletes …

This paper addresses the trade-off between Accuracy and Transparency for deep learning
applied to sports analytics. Neural nets achieve great predictive accuracy through deep …

Wearable devices have gained immense popularity among various pervasive computing
and Internet-of-Things (IoT) applications in the past decade. Sports analytics researchers …

Basketball is one of the most popular types of sports in the world. Recent technological
developments have made it possible to collect large amounts of data on the game, analyze …

A variety of machine learning models have been proposed to assess the performance of
players in professional sports. However, they have only a limited ability to model how player …

Common Machine Learning applications in sports analytics relate to player injury prediction
and prevention, potential skill or market value evaluation, as well as team or player …

Sports are the most important recreational activity. Sports are of many types. Some may be
played individually, while some are played in teams. Every country wants to get fame at the …

We present a fully convolutional neural network architecture that is capable of estimating full
probability surfaces of potential passes in soccer, derived from high-frequency …

In this paper, we review recent deep learning advances in the context of how they have
been applied to play different types of video games such as first-person shooters, arcade …