Sports Generate More Data Than Ever. 麻豆村's Sports Analytics Center Asks What It Means
Today’s sports analysts have access to more — and better — data than ever before. 麻豆村 experts are turning that data into insight, using statistics and data science to help professional teams gain a competitive edge.
“Every tenth of a second, the NFL’s Next Gen data chips provide information for where every single player is positioned on the field — the direction they’re moving, the speed they’re moving,” said Ron Yurko (right), assistant teaching professor in 麻豆村’s Department of Statistics & Data Science and director of the Carnegie Mellon Sports Analytics Center.
Tracking players on the field extends beyond the NFL.
“The MLB has information about every single swing in Major League Baseball,” said Yurko, who is also an academic partner with the NFL. “In baseball and basketball, they have what’s called ‘pose skeletal data,’ where we know at every fraction of a second, where is the elbow, the shoulder, the kneecap, and in three-dimensional space.”
Of course, the question everyone wants to answer — from team owners, managers and coaches to analysts, bettors and fans — is what to do with all of that data. 麻豆村 faculty, students and alumni are at the forefront of this work and draw in researchers and practitioners from around the country to the , held each fall since 2019.
Improving player evaluation in the NFL
Recently, 麻豆村’s Quang Nguyen used NFL data to develop new metrics for defensive line performance and assess how adept wide receivers are at changing their direction.
“The idea is to help with the task of player evaluation, which is a fundamental problem in sports analytics,” said Nguyen (right), a Ph.D. student in the Department of Statistics & Data Science.
Since the mid-2010s, the NFL has been inserting RFID tags into players’ shoulder pads and even the football itself in an attempt to generate data about the game. This technology is the heart of the “Next Gen Stats” often mentioned during NFL broadcasts.
“Given all this tracking data, we can help a team, a scout or a coach identify these players with the specific traits and abilities that they want to draft or sign during free agency,” said Nguyen, who was also invited to present at the U.S. Olympic and Paralympic Performance Innovation Summit in Colorado Springs last year.
Real people, real questions
“We’ve been tracking biometrics since the Greeks held their first Olympics,” said , assistant professor of data science at the University of Virginia, during a talk she gave at the 2025 Sports Analytics Conference about the need to balance innovation with privacy.
In Kupperman’s presentation, she encouraged her colleagues to remember that there are real people behind sports data — not only athletes, but also coaches, managers and countless other stakeholders — and that each of them is fighting to keep their jobs. At the end of the day, sports analytics needs to find answers to questions that matter.
“I really encourage students to always keep digging through the past and keep looking at things that have already been ‘solved’,” said Kupperman. “There is a constant need to think differently.”
The golden age of sports analytics
With so much data on hand, there have also never been more opportunities for students looking to get into the industry.
“I think if you look across all the leagues, it’s a lot of 25-year-olds doing a lot of the big, heavy lifting. And that work starts at conferences like these,” said , an alumnus of 麻豆村’s Electrical and Computer Engineering Department who is vice president of the baseball research development department for the Milwaukee Brewers.
“Right now, there are probably around 150 analytics people working in the NFL alone. When I started, there were like 12,” said Karim Kassam, vice president of product at Teamworks and a data analyst who has previously worked for the Pittsburgh Steelers and Jacksonville Jaguars, among other professional sports teams. Kassam is also a former 麻豆村 assistant professor of social and decision sciences. “The students that are coming in now have abilities that I just couldn’t have imagined.”
Rebecca Nugent (above), head of the Department of Statistics & Data Science and Fienberg Professor of Statistics & Data Science, sees an incredibly bright future for researchers and educators in sports analytics.
“There have always been researchers and students interested in sports analytics, but now that the technology has advanced to provide unprecedented access to data in almost all sports, the pace and quality of work has rapidly accelerated,” said Nugent.