Physics alumnus is part of the KC Royals analytical lineup
Calvin Hoffman didn't just learn to solve problems at Carnegie Mellon University — he learned how to knock new opportunities out of the park.
Calvin, who graduated in 2024 with a major in physics and a minor in computer science, is the Kansas City Royals amateur draft analyst, a role at the intersection of scientific problem solving, programming and a sport he loves.
“I’ve played baseball for as long as I can remember,” says Calvin, who was a second baseman on CMU’s club team. “After graduation I was looking for a role, one that would test my programming, my research capabilities and deductive reasoning.”
As an analyst, Calvin’s job is to evaluate high school and college baseball players eligible to be selected in the MLB draft, which happens in July. The work requires a fast-moving blend of data engineering, analytics and communication. The deadlines are everchanging, the pace of work is blazing fast and high-pressure situations are common.
“I spent two summers doing research with Professor [and head of the McWilliams Center for Astrophysics and Cosmology] Tiziana DiMatteo, and that was my first exposure to large, open-ended research,” Calvin says. “And having done the minor in computer science, the kind of rigor that was constantly used in both areas were two of the most important things I learned.”
Working with Nianyi Chen, a Ph.D. student, Calvin studied the evolution of the universe using ASTRID, a large-scale cosmological hydrodynamic simulation. His focus centered on cataloguing triple and quadruple black holes — work that led to being first author on an article in the Monthly Notices of the Royal Astronomical Society and a presentation at Meeting of the Minds, CMU’s undergraduate research symposium.
“It was one of the first times I had to distill a big body of research into something meaningful for very different audiences,” Calvin says.
For Calvin, the appeal of physics comes back to the power of problem-solving — breaking down complex systems to learn something new. Those same skills accompany him each day in his office behind home plate at Kauffman Stadium.
“It’s kind of crazy that I get to drive to a baseball stadium for work,” he says. “From the highway, you can see the big Crown Vision scoreboard. Seeing that in the morning — especially with the sun just coming over — is so exciting. It’s awesome.”
Baseball has long been a game of instincts, tradition, and timing — but modern front offices increasingly rely on data, predictive models and advanced analytics to gain an edge.
“When a member of our scouting department reaches out, having just watched a player, they want to know a little bit more about the nitty-gritty, what the analytics might entail or indicate about the player’s performance,” Calvin says.
As July’s MLB Draft approaches, the pace intensifies. From February through June, Calvin works through a rush of requests, real‑time evaluations and constant model updates.
“It’s hectic in the best way,” he says. “Draft week is going to be a crazy week and a half—but that’s what makes it fun.”
Calvin said that while he set out to build a baseball career, the intellectual foundation he built at Carnegie Mellon turned out to be exactly what the Royals needed. He credited several courses that were key including Concepts of Mathematics; Parallel and Sequential Data Structures and Algorithms; Quantum Mechanics and Thermal Physics for teaching him how to structure and optimize computations, which are essential for modeling and interpreting high-dimensional baseball data.
He also points to Reading and Writing Science, a course taught by Ken Hovis, associate dean for educational initiatives, and working with Gillian Ryan, director of undergraduate affairs in the Department of Physics, who supported him throughout his job search.
“That class taught me how to communicate technical results to different audiences — skills I use constantly when talking to scouts who come from playing backgrounds rather analytical ones,” he said. “I’m really grateful for the mentorship I had. CMU prepared me to handle fast‑moving projects, think independently and adapt quickly.”