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My work has been featured in popular media outlets such as The Athletic, FiveThirtyEight, The Wall Street Journal, and The Washington Post. I am a three-time degree holder from Carnegie Mellon: with a bachelors, masters, and PhD in Statistics. I also have industry experience in both finance and professional sports.

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I am actively working on a textbook titled Statistical Methods in Sports Analytics (to be released in 2027), and occasionally write a newsletter called Statistical Thinking in Sports Analytics.

Statistical Methods in Sports Analytics

Explainability and Analysis of Large Language Models via Evolutionary Methods

Swinging, Fast and Slow: Interpreting Variation in Baseball Swing Tracking Metrics

Exploring the difficulty of estimating win probability: a simulation study

Ron is an Assistant Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University, and the Director of the Carnegie Mellon Sports Analytics Center (CMSAC). CMSAC’s initiatives include an active sports analytics research lab, a summer undergraduate research experience in sports analytics (aka CMSACamp), and the annual Carnegie Mellon Sports Analytics Conference.

His research focuses on developing methods at the interface of inference and machine learning, oriented towards problems in sports analytics and natural language processing.

Sports Analytics

Data Science

Language Processing

Machine Learning & Artificial Intelligence

Ron Yurko Personal Website

Ron Yurko Carnegie Mellon Biography

Ron Yurko Google Scholar

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science-is-changing-the-game-how-research-is-transforming-modern-sports

From the batter's box to the training room, researchers are helping athletes and teams make smarter decisions, improve performance, and gain a competitive edge.

Director, Carnegie Mellon Sports Analytics Center, and Assistant Teaching Professor

Associate Professor, Mechanical Engineering

Associate Professor

Professional sports have always embraced innovation, but today's competitive advantage increasingly comes from science.

Researchers are applying advances in neuroscience, artificial intelligence, biomechanics, data analytics, and human performance to better understand how athletes make decisions, respond under pressure, recover from injury, and maximize performance. What once relied heavily on intuition and experience is now being informed by sophisticated research that can measure, predict, and improve outcomes at every level of competition.

Recent studies from Carnegie Mellon University highlight the growing role science is playing across the sports landscape. Whether examining decision-making in high-pressure situations, analyzing performance strategies, or using artificial intelligence to improve health outcomes, researchers are uncovering insights that can help athletes perform at their best while extending careers and reducing injury risk.

 Ron Yurko is an Assistant Teaching Professor in the Department of Statistics & Data Science at Carnegie Mellon University, and the Director of the Carnegie Mellon Sports Analytics Center (CMSAC).   View his profile  Scott Powers, an assistant professor at Rice University with vast front-office experience in Major League Baseball—including stints with the Los Angeles Dodgers and the Houston Astros—joined forces with Ron Yurko, a director at the Carnegie Mellon Sports Analytics Center, to analyze this cutting-edge data. Their study, published in The American Statistician in 2026, marks a significant advancement in the quantitative understanding of batting dynamics. It uses high-resolution measurements of bat speed and swing length, metrics that were publicly released for the first time in 2024, to explore how hitters modulate their swings under different pitch counts, particularly when facing two strikes.   Eric Yttri is an Associate Professor at Carnegie Mellon University where his research goal is to establish how neural circuits lead to these action selection decisions.  View his profile  As a neuroscientist, I have been working to uncover how the brain decides when to act and when to wait. Recent research from my team and me helps explain why this split-second pause happens, offering insight not only into elite athletic performance, but also how people make everyday decisions when the potential outcome isn't clear. We found that the key to hesitation is a response to uncertainty. This could be where a dropped hockey puck will land, when a race starts, or placing your order at a new restaurant.   Eni Halilaj is an Associate Professor at Carnegie Mellon University where she directs the CMU Musculoskeletal Biomechanics Lab, an interdisciplinary group of engineers seeking to understand and optimize human movement mechanics.  View her profile  According to Eni Halilaj, an assistant professor in mechanical engineering at Carnegie Mellon University and biomechanist who specializes in orthopedic rehabilitation, 60 percent of those who suffer this common knee injury also develop osteoarthritis early in life. The degenerative joint disease, which affects an estimated 32.5 million individuals in the U.S., is especially problematic for younger patients because of the longer time span during which the chronic condition can cause debilitating pain, stiffness and limited mobility. "How can we make the 60 percent have the same long-term outcome as the 40 percent?" asked Halilaj, who is working to understand the difference between those who do and those who do not develop osteoarthritis following knee trauma.   Matthew Walker is a Professor, Astrophysics & Cosmology at Carnegie Mellon University. His research focuses on the astrophysical properties of dark matter, but he is also a former collegiate D1 baseball player and lifelong, passionate fan staying apprised of advancements in the game. View his profile  Carnegie Mellon University physics professor Matthew Walker said the system still has limitations, especially on pitches that are extremely close to the edge of the strike zone. "Every measurement device has a margin of error," Walker said. "ABS is, from what I can tell, somewhere around half an inch -- which means if the ABS call says that the pitch was within half an inch of the border between a ball and a strike, whether it says it’s a ball or a strike is really no better than a guess." Walker said that in those situations, the umpire’s original call should remain in place rather than letting the automated system make the final decision. The influence of science in sports extends far beyond professional athletics. Research developed for elite competitors often finds applications in healthcare, rehabilitation, education, workplace performance, and everyday decision-making.  As teams continue to invest in analytics, wearable technology, artificial intelligence, and performance science, the relationship between research and sports is expected to grow even stronger. The result is a deeper understanding of how humans learn, adapt, compete, and perform under pressure.

If you're covering or looking to know more, we can help! Carnegie Mellon University experts can discuss:  • The growing role of science and technology in sports • Performance optimization and decision-making under pressure • Artificial intelligence and data analytics in athletics • Injury prevention, rehabilitation, and athlete health • The future of sports research and innovation 

Science Is Changing the Game: How Research Is Transforming Modern Sports

On this week's Bet The Process, Ron Yurko comes on to discuss his role at the Department & Data Science at Carnegie Mellon. He currently teaches a course on sports betting where students place wagers on a fake sportsbook, using statistical models.

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Bet the Process with Ron Yurko

Twenty years ago, when MIT hosted the first Sloan Sports Analytics Conference, only a handful of universities dared to treat sports analytics as a serious field of study rather than a niche hobby. There were no dedicated field journals, few courses nationwide, and almost no faculty willing to risk their careers studying it. Today the academic landscape could not look more different. Dozens of universities now offer majors or minors in sports analytics, field journals are thriving, and tenure-track professors, many with team or league experience, are leading cutting-edge research and training the next generation of practitioners. This panel explores how sports analytics became an academic discipline in record time and where it's headed next. We'll dig into the evolution of curricula, the growing ties between universities and professional teams, and the challenges of keeping education aligned with a rapidly changing industry. Panelists will share how academic programs are shaping (and being shaped by) the sports analytics ecosystem, from research priorities to career pipelines. Whether you're an educator, student, or industry leader, this discussion will dig into how universities are powering the next era of innovation, talent, and collaboration in sports data science.

SSAC26: Building the Academic Playbook for Sports Analytics Education

Carnegie Mellon University will debut a new class that aims to teach students the math behind sports betting and the risks that come with it, as wagering becomes increasingly common on college campuses.  Ron Yurko, director of CMU’s Sports Analytics Center, said the idea took shape after he watched students pull out their phones during class, open betting apps, and place wagers within seconds.

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