Students in this lab design winners

The story of the college athlete is one of sacrifice, skill and snap judgments. With so much at stake, every small advantage can tilt the game. One place those margins hide is in the data.

As the team statistician for Carolina men’s basketball, Conor Kerr had seen how much numbers could bend outcomes — and wanted to extend that winning edge. In 2022, he approached Mario Giacomazzo with an idea: teach more students to do this work.

“I told him that if he wanted to make analytics available to other undergraduates, I’d help,” said Giacomazzo, a teaching associate professor in the UNC College of Arts and Sciences’ statistics and operations research department.

Together, they began building the Sports Analytics and Intelligence Lab, inviting students to try research and leadership at the same time.

“Over time, we realized our graduate students were outstanding at making sure things got done, so we made them the authority,” Giacomazzo says.

That shift opened the door for statistics doctoral student Kendall Thomas, a former Division I athlete, to step in.

“I got injured pretty quickly in my freshman year and wanted to find a way to impact my team without physically being able to be on the field,” she says. “That’s how I fell into sports analytics.” Under Thomas’s leadership, SAIL began threading analytics through every corner of competition.

Meet some of the other SAIL analysts:

Gordan Tao is a junior double-majoring in computer science in the College and in data science in the
UNC School of Data Science and Society.
When staff from the UNC-Chapel Hill football program approached SAIL with mountains of performance data, looking for answers,
Tao set out to help them. Tao filtered the stockpile of metrics down to a handful of key performance indicators — the stats
most telling of an athlete’s game readiness — effectively creating a scorecard for practice quality. Athlete fatigue became
his No. 1 opponent. He hopes this research can unpack the stifling connection between stress and success, give coaches new
insights into what their athletes are missing, and offer more players the opportunity to show what they’re truly capable of.

Khushi Shah is majoring in statistics and analytics and minoring in data science and neuroscience in the College.
As a sophomore, the newly minted SAIL analyst partnered with the UNC-Chapel Hill volleyball team to give them a deeper look into
player trends. Inspecting play-by-play game footage, she extracted everything from player positioning during a set to the mechanics
of every effective block. The result was a rich dashboard of visualizations and heat maps, transforming motion into a nuanced narrative.
By extracting visual details from thousands of clips and using them to train her machine learning model, she could compare every
attempted play to the calculated average, reminding players of their tendencies.

Yunus Mouline is a senior double-majoring in statistics and analytics and economics and minoring in data science
in the College. At SAIL, he began with a deceptively simple question: At any given moment, which five players would give the team
the strongest edge? He scraped play-by-play basketball data from across the nation, building a treasure trove of evidence for his
predictive model to understand how different player combinations might shift the flow of the game. Once trained, every new matchup
becomes a pop quiz — a chance to tell the model where it can improve, sharpening it with each simulation.

Read more about these SAIL analysts.