Sean Dermody wasn’t just another University of Virginia baseball fan in attendance at the Cavaliers’ season-opening series against Wagner College.
The fourth-year student spent a February afternoon at Disharoon Park, casually rattling off to his immediate company insights on players, matchups and even first-year coach Chris Pollard’s strategy.
The running analysis prompted a tap on the shoulder.
“How do you know all of this stuff?” a woman seated behind Dermody asked.
He had an answer. Dermody was one of more than 20 students on , a behind-the-scenes group that turns data into on-field decisions.
The woman had a reason for asking – she was Taylor Gracia, the mother of UVA star outfielder A.J. Gracia.
Her son, she told him, was a fan of Dermody’s work.
“I was asking her about how often A.J. looks at these metrics,” Dermody said. “She’s like, ‘Oh, yeah, he’s looking at them all the time.’
“That made me so happy.”
A.J. Gracia is a , a player whose future could unfold in big-league ballparks. Dermody, meanwhile, is an economics and statistics major who will start a job as a strategy analyst at CarMax after graduation next week. He hasn’t played baseball since age 9, instead spending his college career in the Cavalier Marching Band and as an admissions tour guide.
A.J. Gracia completes the swing for one of his 12 home runs this season. The future high MLB Draft pick uses metrics from the analytics team to help improve his game. (Virginia Athletics photo)
It takes more than the players on the field to fuel a 30-plus-win team and position the Cavaliers for another NCAA Tournament appearance.
“It’s really cool being here, where there’s so much interest and willingness from our student body to try to be a part of it and contribute,” UVA baseball staff member John Natoli said.
Natoli, the Hoos’ director of player development, also serves as the liaison to the team’s student-powered analytics department.
One of Natoli’s most frequent texters is Adam Chow, a School of Data Science graduate student and volunteer director of the analytics department, who oversees Dermody and the rest of the group.
“We’re talking all the time,” Natoli said, “whether it’s basic scheduling stuff or related to in-depth projects.”
Data comes from TrackMan, an in-stadium radar system that records every pitch and batted ball – velocity, spin rate and launch angle included. On game days, students run the system, logging each pitch in real time.
TrackMan is the source of from the official UVA baseball account mere moments after a Cavalier home run.
Launched 🚀
— Virginia Baseball (@UVABaseball)
Popularized by the 2011 film “,” analytics have reshaped baseball, especially at the highest levels.
A player’s batting average and runs batted in total are no longer the only factors in determining a hitter’s value, or even the most important. At UVA, they focus on weighted on-base average, or , a metric that measures each method of reaching base in terms of its impact on scoring runs.
The same goes for pitchers, where, in addition to earned run average, there’s an emphasis on their CSW metric, which stands for “called strikes plus whiffs,” or the percentage of pitches that freeze or fool hitters. Chow calls it “the single best snapshot of a pitcher’s command (control) and stuff (movement) combined.”
“CSW is the best way to predict future performance,” Natoli added, “not just how well someone’s performed to that point.”
CSW and wOBA are just a few of the many metrics tracked on dashboards built by Chow and Dermody.
“I love figuring out how to win,” said Chow, who hopes to become an MLB general manager someday. “That’s what this is – finding ways to optimize it.”
John Natoli is UVA baseball’s director of player development and the liaison between the analytics team and the Cavalier players. (Virginia Athletics photo)
Analytics help explain why Gracia – once a prototypical middle-of-the-order power hitter – now bats leadoff.
The junior is second on the team with a .552 wOBA.
“A.J. is a very good example of a new-school leadoff hitter,” Natoli said, “because he gets on base a ton.”
Analytics can also change how players evaluate their performance. A 0-for-4 day at the plate looks different if every ball is hit at a high velocity.
“If I see that every ball went over 95 miles per hour, but the outfielder just ran them down, you can’t be too mad at yourself,” junior catcher Jake Weatherspoon said. “And then it goes the other way. You can’t get too high on yourself for swinging at a bad pitch and getting lucky with a soft hit.”
