Stats Perform to Present Two Key Sports AI Research Papers at the 2021 MIT Sloan Sports Analytics Conference

Stats Perform Papers “Making Offensive Play Predictable - Using a Graph Convolutional Network to Understand Defensive Performance in Soccer” and “Predicting NBA Talent from Enormous Amounts of College Basketball Tracking Data” will be presented at the 2021 MIT Sports Analytics Conference

CHICAGO & LONDON--(BUSINESS WIRE)--Stats Perform, the Sports Tech leader in data and AI, today announced that two research papers authored by the company’s AI team will be presented in the research track at the 2021 MIT Sloan Sports Analytics Conference.

Each year the conference’s Research Paper Competition highlights cutting-edge research that influences the way media and professional teams across various sports analyze performance. The papers — “Predicting NBA Talent from Enormous Amounts of College Basketball Tracking Data” and “Making Offensive Play Predictable - Using a Graph Convolutional Network to Understand Defensive Performance in Soccer”—represent some of the exciting work Stats Perform’s AI team has accomplished recently.

The paper, “Predicting NBA Talent from Enormous Amounts of College Basketball Tracking Data,” uses the company’s proprietary computer vision technology, AutoStats, to generate college basketball tracking data that was once immeasurable. Using the new tracking datasets, the authors illustrate how NBA analysts can glean new insights and better predict players’ skills and traits at the NBA level. This paper is one of 7 finalists that will vie for the overall best paper award.

The paper, “Making Offensive Play Predictable - Using a Graph Convolutional Network to Understand Defensive Performance in Soccer,” uses a sophisticated graph neural network to measure defensive value of player actions which has previously yet to be accurately measured.

“These two papers represent some of the pioneering work of our AI team, and I am thrilled to see them recognized by the judging panel at Sloan,” Stats Perform’s Chief Scientist Dr. Patrick Lucey said. “Both of these papers represent significant advancements in using computer vision and machine learning to generate new data and insights that can be applied across many different sports. This represents a significant step forward in the way teams can measure performance and make objective decisions using our differentiated data and models.”

In the past five years, Stats Perform has reached the MIT Sloan Best Research Paper Track finals four other times, winning best paper in 2016 and runner-up in 2017 and 2018.

The full paper can be downloaded on the MIT Sloan Best Research Paper Track website here.

About Stats Perform

Stats Perform is the market leader in SportsTech providing the most trusted sports data and the latest advancements in applying AI and machine learning to deliver better predictions for teams, sportsbooks and a more engaging broadcast, media and fan experience.​ The company collects the most detailed sports data to create new experiences across sports. Leveraging the richest sports database, Stats Perform enhances sports competition and entertainment through machine learning and computer vision to create advanced predictions and analysis – be that for digital and broadcast media with differentiated storytelling, tech companies with reliable and fast data to power their innovations, sportsbooks with in-play betting and integrity services, or teams with first-of-its-kind AI analysis software. For more information, visit StatsPerform.com