Updates

The NFL announced the finalists for the seventh annual Big Data Bowl, the League’s crowdsourcing competition for the sports analytics community that challenges applicants to use Next Gen Stats to generate insights to enhance the game. Each finalist.

Powered by Amazon Web Services (AWS), this year's competition highlighted data collected from what happens before the snap to produce insights and actionable predictions into what the offense or defense does after the snap. Pro Football Focus scouting data was also included to help identify formations, wide receiver routes and blocking assignments. Each contestant was placed in one of three tracks: design a metric, coaching presentation or undergraduate students. More than 400 data scientists from around the world participated in this year’s event – a record high for the Big Data Bowl competition.

“Each year we see an incredible rise in participants as well as skill levels, reflecting a growing appetite to explore new aspects of football,” said Mike Lopez, senior director of football data and analytics at the NFL. “This year's competition highlighted the increasing importance of pre-snap tendencies in scouting and play design, uncovering fascinating ways teams conceal their plays. The NFL continues to be inspired by the innovation and talent emerging from this competition and their impact on the future of the game.”

The 2025 Big Data Bowl will culminate with an in-person event at the NFL Scouting Combine in Indianapolis on Feb. 26. Each finalist received $12,500 for being selected and will compete for an additional $12,500 in prize money. The event will feature a keynote discussion with Dr. Eric Tulsky, general manager of the Carolina Hurricanes. The finalists will also have an opportunity to interact with the estimated 200 analytics staff members, coaches and front office personnel who will be in attendance.

"Year after year, the Big Data Bowl raises the bar for what's possible in football analytics," said Julie Souza, global head of sports at AWS. "This year has drawn the largest pool of participants yet, with aspiring data scientists tackling one of football's most strategic moments. These talented builders are developing innovative approaches to understanding the complexity of pre-snap decisions. The creativity and technical skill demonstrated in this competition continues to impress us and showcases the bright future of sports analytics."

Submissions to the seventh annual Big Data Bowl were made on Kaggle, a data science competition platform. The finalists, semi-finalists and honorable mention finishers are listed below with links to their submissions.

finalists - $12,500

Coaching track

Ben Wendel
https://www.kaggle.com/datasets/benwendel/wendel-big-data-bowl-2025

Undergraduate track

Smit Bajaj, Vishakh Sandwar (New York University)
https://www.kaggle.com/code/smitbajaj/exposing-coverage-tells-in-the-presnap

Lindsay Fleishman (University of Georgia), Daniel Soriano (University of California, Davis), Eric Steinberg (Emory University), Lucca Ferraz (Rice University)
https://www.kaggle.com/code/ericthesteinberg/tendenciq

Metric track

Ryan Brill, Cole Jacobson, Justin Lipitz, Jonathan Pipping
https://www.kaggle.com/code/colejacobson/safety-entropy

Sarah Pollack
https://www.kaggle.com/code/sarahpollack/under-cover-2-predicting-disguised-defenses

Semi-finalists - $5,000

Andrew Akers
https://www.kaggle.com/code/andrewakers9/dialing-up-the-pressure

Jonah Lubin, Charles Wells (Rice University)
https://www.kaggle.com/code/jonahdlubin/keep-em-separated

Quang Nguyen, Ron Yurko
https://www.kaggle.com/code/tindata/down-set-hut

Matt Polsky (University of North Carolina at Chapel Hill)
https://www.kaggle.com/code/mattpolsky/it-s-a-bluff-predicting-receiver-decoy-motions

Abhi Varadarajan (Carnegie Mellon University)
https://www.kaggle.com/code/abhishekvaradarajan/trench-chess

Honorable Mentions

Dan Bickelhaupt
https://www.kaggle.com/code/danbickelhaupt/read-em-weep

Miguel Duarte
https://www.kaggle.com/code/miguelmd123/disguised-intentions

Nick Gurol, Shaan Chanchani, Ben Wolbransky, Tim Bryan
https://www.kaggle.com/code/brochillington/camo-the-art-of-pre-snap-disguise

Luke Neuendorf
https://www.kaggle.com/code/lukeneuendorf/motion-for-more

Randy Short
https://www.kaggle.com/datasets/randallshort/frr-eaze-nfl-big-data-bowl-2025-randy-short

Guy Haiby, Roee Haiby (University of California, Santa Cruz)
https://www.kaggle.com/code/guyhaiby/decoding-audibles-leveraging-pre-snap-signals

Rachael Kaplan (Duke University), Madalyn Elwood (Buena Vista University)
https://www.kaggle.com/code/madalynelwood/motion-metrics-te-motion-impact-on-rushing-lanes

Shekhar Shah, Jack Sullivan (University of Wisconsin-Madison)
https://www.kaggle.com/code/sshah30/cat-and-mouse-motion-vs-defensive-alignment

Learn more about the Big Data Bowl.