CHICAGO – February 21, 2017 – STATS, the world’s leading sports data and technology company, announced today that it has been named a two-paper finalist in the 2017 MIT Sloan Sports Analytics Conference research competition. Of the eight finalists, two research papers co-authored by STATS’ Director of Data Science Dr. Patrick Lucey are in the running for the research track grand prize.
The papers, entitled “Body Shots: Analyzing Shooting Styles in the NBA Using Body-Pose Attributes” and “Data-Driven Ghosting Using Deep Imitation Learning,” detail methods for applying powerful modern machine learning techniques to better understand how athletes interact with space and how this affects team performance. With these advanced techniques, professional teams can more fully quantify, analyze and compare team and individual behaviors than ever before, using unparalleled modeling capabilities to maximize the value of their data and projections.
“STATS has long been known as the leader in sports data and technology and this signals how swiftly we have extended our industry leadership in data science,” said Lucey. “We are thrilled that two of our trailblazing papers have been recognized as finalists at this year’s MIT competition, and we look forward to introducing this data and modeling system into our future products for football and basketball.”
STATS hopes to add to its accolades in the research and academic community at the 2017 MIT Sloan Sports Analytics Conference, one year after winning the top research paper at the 2016 conference, with the paper “The Thin Edge of the Wedge: Accurately Predicting Shot Outcomes in Tennis Using Style and Context Priors.”
Lucey will be a part of the teams presenting both papers at this year’s conference, taking place in Boston on March 3rd and 4th. An industry panel will select the final winner on the basis of the paper and the presentation at the 2017 Conference.