As a former high school athlete, Drew Kearny ’25 loves sports and the way they bring people together. Whether he is playing or watching, the experience enthralls him.
“It’s like a never-ending Netflix series where the show just goes on and on, and there are always surprises,” he said.
Kearny also appreciates the role of strategy in sports, particularly “trying to figure out how to outsmart your opponents and find small edges that increase your chances of winning.” In addition to feeding his competitive streak, that passion inspired his decision to major in statistics at Texas A&M University and his career goal of becoming a data scientist for a professional baseball or football team. He hopes to use his degree to help professional sports teams improve their performance to gain an edge over competitors.
This past summer, Kearny got a glimpse into his future when he applied for a research project directed by Dr. Alan Dabney, an associate professor in the Department of Statistics. After he was chosen for the project, he was given the opportunity to select a research topic. As a throwback to his days playing high school baseball, he decided to analyze pitching data for the Texas A&M baseball team. He spent the summer on exploratory data analysis of pitching and learned how to code in a free software environment for statistical computing called R. He even dipped his toes into the world of machine learning. At the conclusion of the project, Dabney helped him write a research paper that was submitted to the academic journal Teaching Statistics.
The college journey became so much more rewarding and fun once I figured out exactly why I was interested in statistics and how I could combine it with my love for sports to build a career.
Kearny says the project gave him practical experience analyzing statistics and applying the data he gathered to a real sports team. Along the way, his research uncovered insights that have helped the baseball team refine its strategies for player development. For example, he discovered that the most relevant pieces of data behind better pitches are strike percentage and swing-miss rate. After analyzing the data, Kearny also worked with team members to improve slider pitches. Knowing what makes a successful pitch will also help with scouting as the baseball team evaluates prospective players.
“Dr. Dabney was amazing throughout the summer,” Kearny said. “He helped me learn the R programming language and other statistical processes that I wouldn’t know without him.”
By parlaying his passion for sports into a statistics education and an overall Texas A&M experience that will lead to a career he loves, Kearny says he has found his sense of purpose.
“The college journey became so much more rewarding and fun once I figured out exactly why I was interested in statistics and how I could combine it with my love for sports to build a career,” Kearny added.
Kearny says he and Dabney continue to meet regularly and that he has benefited greatly from Dabney’s advice and mentorship — an experience that Dabney is confident will deliver exponential dividends for others in the near future.
“Drew possesses a unique skill set, including solid theoretical foundations in statistics, programming excellence and a deep understanding of sports, not to mention greater-than-average maturity for an undergraduate and a strong work ethic," said Dabney, a 2021 Presidential Professor for Teaching Excellence. "He is exactly the kind of numbers nerd (intended as a compliment) that sports teams should be lining up to recruit for their analytics work.
"Everyone knows now that proper analytics can help teams find an edge over their competition. I predict that Drew is going to make some lucky pro team very happy soon."