Sports Data Science: Towards Improved Understanding of Sports and E-Sports Data?

Abstract: While there has always been interest in analyzing sports data, this research area has received significantly more attention in recent years due to both the recognition of the importance of objective statistics and the proliferation of available data. For conventional sports, new technology has enabled the capture of game play at unprecedented levels of detail, including the tracking of positions of all players and game events at all times. And for E-sports, data is starting
to pour in at increasing rates. Instead of being starved for data, analysts now have access to volumes of highly accurate gameplay data. This data deluge requires the development of novel visualization and machine learning tools and is leading to major new developments in sports data science. In this talk, we will cover recent developments in this area and the enabling technologies. We will review our early work on the development of the Statcast Baseball Metrics Engine (BME); then introduce new approaches to analyze data directly from videos; and finally cover new techniques for player valuation. This is joint work with the current and past members of the NYU Sports Analytics team, including Jorge P. Ono, Daniel Cervone, Carlos Dietrich, Marcos Lage, Jianzhe Lin, Guido Petri, Yurii Piadyk, Guande Wu, Peter Xenopoulos, and Shuya Zhao.

Mini-CV: Cláudio T. Silva is a Professor of Computer Science and Engineering and Data Science at New York University. He is also affiliated with the Center for Urban Science and Progress (which he helped co-found in 2012) and the Courant Institute of Mathematical Sciences. His research interests include visualization, visual analytics, machine learning, reproducibility and provenance, geometric computing, urban computing and computer graphics. Recently he has been interested in urban and sports applications. He received his BS in mathematics from the Universidade Federal do Ceará (Brazil) in 1990, and his MS and PhD in computer science at the
State University of New York at Stony Brook in 1996. Claudio has advised 20+ PhD, 10 MS students, and mentored 20+ post-doctoral associates. He has published over 300 publications, including 20 that have received best paper awards. He has over 25,500 citations according to Google Scholar. Claudio is active in service to the research community and is a past elected Chair of the IEEE Technical Committee on Visualization and Computer Graphics (2015–18). Claudio is a Fellow of the IEEE and has received the IEEE Visualization Technical Achievement Award. He was the senior technology consultant (2012-17) for MLB Advanced Media’s Statcast player tracking system, which received a 2018 Technology & Engineering Emmy Award from
the National Academy of Television Arts & Sciences (NATAS). Our lab’s work has been covered in The New York Times, The Economist, ESPN, and other major news media.