麻豆村

Six-year-old Abhishek Varadarajan watched with his family as Eli Manning and the Giants defeated Tom Brady鈥檚 Patriots in Super Bowl XLVI, a game that kicked off his lifelong love of football.

Now a sophomore at 麻豆村, Varadarajan鈥檚 gaining yards toward his own goal line: a career in the NFL. His project 鈥�,鈥� a semifinalist in different ways a defense can create confusion at the line of scrimmage.

Raised in New Jersey, Varadarajan could sense his community鈥檚 excitement leading up to the 2012 championship, as even the students in his elementary school buzzed about how the Giants might win the Super Bowl. He religiously followed the team and the NFL, and in his senior year of high school, he wanted to learn more about what was happening on the field.聽

鈥淚鈥檝e been watching football for as long as I can remember. I started digging into the schemes and the player techniques in high school. I was watching coaching clinics and game film on my own time just to learn as much as I possibly could about the game,鈥� Varadarajan said.

At 麻豆村, Varadarajan found his place studying statistics and machine learning in the Dietrich College of Humanities and Social Sciences.

Varadarajan set out to explore his interest in the world of sports analytics, and during Orientation Week, learned about statistician Ron Yurko and the Carnegie Mellon Sports Analytics Center (CMSAC).

Yurko,聽 CMSAC鈥檚 director and an assistant teaching professor in the Department of Statistics & Data Science, has been a driving force behind 麻豆村鈥檚 continued success at the annual NFL Big Data Bowl. He鈥檚 guided multiple projects for the contest since its inception, including two from statistics doctoral student Quang Nguyen that were named finalists in 2023 and 2024. Nguyen and Yurko were also semifinalists for their submission this year.

鈥淎bhi is a football fanatic,鈥� Yurko said. 鈥淗is project looked to objectively quantify these concepts of 鈥榮tunts鈥� and 鈥榙isguises鈥� using modern tracking data. And he found some interesting relationships there.鈥�

Using positional data from sensors worn by each player on the field during the first half of the 2022 NFL season, Varadarajan tracked how successful teams were at disguising defensive pressure and using stunts (when defensive linemen switch roles).

鈥淭eams tend to either disguise a lot, or have one player who鈥檚 great at winning in isolation,鈥� Varadarajan said. 鈥淚f teams don鈥檛 disguise their pressures, they aren鈥檛 going to get pressure without a key rusher. If you don鈥檛 have that talent, you are forced to allocate more resources to causing confusion in order to get pressure.鈥�

A football fanatic聽

In his pursuit of football knowledge, Varadarajan didn鈥檛 stop once he found the Sports Analytics Center. This fall, he joined the as a manager to get closer to the game.

In the role, Varadarajan took on an equivalent time commitment to that of a student-athlete. He filmed games for use in post-game review by the coaching staff, helped to set up the field for practice and games, and maintained equipment. And though he was paid for his time, the real value came from knowledge gained.

鈥淚t鈥檚 helped him to be around football, and see the game every day,鈥� said Sam Turner, equipment manager for the Tartans. 鈥淲henever coaches come into the equipment room, I鈥檇 see Abhi try to pick their brains about schemes, and coaches would take him over to the white board to offer their knowledge about anything he wanted to learn."聽

Varadarajan is also an officer in 麻豆村鈥檚 Sports Analytics Club, a student-run sports statistics group that keeps the conversation going outside of class. Like in a chess match 鈥� or a pre-snap disguise 鈥� he鈥檚 setting up a long-term position for success.

鈥淚鈥檇 really like to work in a team鈥檚 front office, helping to win games every week,鈥� he said.聽