Harvard Baseball's Andrew Abler is Changing the Game Through AI

Artificial intelligence is heading with increased velocity for the world of sports. 

“It’s going to change everything,” said Harvard baseball player Andrew Abler ’27, a right-handed pitcher and first baseman. “What feeds AI is data. As data has gone up, the average speed of the MLB fastball has gone up almost a mile per hour each year.”

Over the summer, Abler, a double concentrator in mathematics and computer science, completed an internship that helped further the AI revolution. Working with the baseball development company Tread Athletics gave him the opportunity to program and test a digital tool for analyzing the mechanics of high-performance pitchers.

The experimental tool Abler created for Tread has the long-term goal of making training more effective. It will enable coaches to set more precise mechanical baselines for the pitchers they work with and better monitor changes as training continues. The idea is empowering coaches who provide mechanical feedback to large groups of players while ultimately improving outcomes. 

Abler dreamed up the project last spring while enrolled in a Gen Ed course titled “Rise of the Machines? Understanding and Using Generative AI.” 

“I really enjoyed that class and that led me to start some self-learning on machine learning,” Abler shared. Before long, he was pitching the project in an unsolicited email to Tread.

“He came to us with this idea for this analysis tool,” recalled Courtney Semkewyc, a sports biomechanist at the company. “That was an idea we also had, and having someone who is very passionate about this project was a no-brainer.” 

Abler kicked off his summer with an in-person meeting at Tread Athletics’ headquarters in Pineville, North Carolina. From there, the Novi, Michigan native balanced the internship with his full-time commitment to playing for the Royal Oak Leprechauns of the Northwoods League — a collegiate summer league spread over several states in the Upper Midwest. 

According to Semkewyc, Abler’s direct contact on the project, the undergraduate made enormous headway given these time constraints. That meant working on the AI pitching coach while Abler was riding the bus between games — or alone in quiet motel rooms across Minnesota and Wisconsin. Tread supplied him with sample biomechanical data and other raw information he needed to start coding.

“I was provided videos with pitchers from the side and behind, so you could really see the mechanics develop,” Abler said. “I was really interested to see if you could make an AI pitching coach with just video.”

“I was insanely impressed by Andrew,” Semkewyc offered, “especially by the fact that he was a first-year, the fact that he had the knowledge to do this project this early on.” 

The son of a math teacher and a computer information systems professional, Abler has been playing baseball since early childhood. He picked up coding during his sophomore year of high school. 

“My dad majored in computer information systems, and he always loved working in that industry,” Abler said. “When I was a sophomore, he made me take the intro to Python class, and I really didn’t want to. But when I took it, it was really fun, and I was really surprised by that.”

Working with Tread has allowed Abler, for the first time, to chase both of his passions at once.

“Throughout my whole life, I’ve had two main loves — baseball and coding,” he said. “To be able to integrate those was super fun. I was on the team bus every day, having fun with coding.”