NFL announces finalists for sixth annual Big Data Bowl 

New York — Today the National Football League announced the finalists for the sixth annual Big Data Bowl powered by Amazon Web Services (AWS). The yearly sports analytics competition hosted by the NFL Football Operations Data and Analytics team allows members of the data analytics community to contribute to the NFL’s expanding world of advanced statistics and new metrics. This year’s Big Data Bowl participants are eligible for $100,000 in prize money, with each finalist receiving $12,500 and runners-up receiving $5,000.

The 2024 Big Data Bowl theme is focused on analyzing tackling performance across the NFL. Finalists in the competition were given access to the NFL’s Next Gen Stats (NGS) from Week 1 through Week 9 of the 2022 NFL season, analyzing metrics such as location, speed and acceleration of all 22 players on the field for any given play. This year’s competitors submitted over 300 submissions, a record for the Big Data Bowl.

This year’s competition will conclude with an in-person event at the 2024 NFL Scouting Combine presented by NOBULL in Indianapolis on Wednesday, Feb. 28, with the five finalists competing for an additional $12,500 in prize money. The keynote speaker of the event will be Mike Fitzgerald, vice president of research and development and assistant general manager with the Arizona Diamondbacks, who will discuss how to implement modern data science and analytical tools in professional sports organizations.

“The Big Data Bowl continues to spearhead innovation in football analytics and has caught on as the preeminent worldwide sports data science competition,” said Michael Lopez, senior director of football data & analytics, strategy & business intelligence at the NFL. “We are lucky each year to have such enthusiastic and talented participants who can help us grow and learn about the game.”

Since 2017, the NFL has been proud to utilize AWS’s machine learning and data analytics services to develop new insights via the NGS platform that continually reshape the league and change how fans experience the game. In past years, the Big Data Bowl has generated innovative metrics in the play of offensive and defensive linemen, special teams strategy and pass coverage.

“We continue to be impressed by the passion and skill of participants in the Big Data Bowl,” said Julie Souza, head of sports at AWS. “This competition unites the brightest minds in data science and we can’t wait to see the impact this year’s event will have on the future of football.”

The Big Data Bowl has continued to be a strong pipeline for data scientists looking to begin a career in the sports analytics industry. More than 50 Big Data Bowl contestants have been hired in the sports data and analytics field, with over 30 of those participants being hired by NFL clubs and player-tracking vendors.

For the sixth straight year, the Big Data Bowl featured a mentorship program. This partnership led to outstanding results, with two previous mentees being named 2024 honorable mentions. For the second year, a new coaching-centric track was implemented, which encouraged coaches to partner with data scientists on a submission. Three of our finalists are women in this year’s contest which is the highest on record.

The Big Data Bowl is hosted by Kaggle, the world’s largest community of machine learning practitioners, learners and researchers.

2024 Big Data Bowl Finalists:

• Ben Davis and Nidiyan Rajendran (coaching track), https://www.kaggle.com/code/bendavis71/pull-the-plug
• Matthew Chang, Katherine Dai, Daniel Jiang and Harvey Cheng (metric track), https://www.kaggle.com/code/matthewpchang/uncovering-missed-tackle-opportunities/
• Quang Nguyen, Larry Jiang, Meg Ellingwood, Ron Yurko (metric track), https://www.kaggle.com/code/tindata/momentum-based-fractional-tackles
• Shane Hauck, Marion Haney, Devin Basley and Vinay Maruri (coaching track), https://www.kaggle.com/code/devinbasley26/no-edge-no-chance?scriptVersionId=158207073
• Smit Bajaj and Viren Bhatia; New York University (undergraduate track), https://www.kaggle.com/code/smitbajaj/set-a-framework-to-evaluate-edge-setters/notebook

Runners Up:

• Aidan Cook (coaching track), https://www.kaggle.com/code/amcook/optimization-of-weak-side-schemes-vs-read-option
• Ajay Patel, Rohit Kumar, Ben Wieland and Sam Hoppen (coaching track), https://www.kaggle.com/code/luckyprophet5/scouting-opponents-through-expected-yac
• Allan Paiz (undergraduate track), https://www.kaggle.com/code/allanpaiz/defensive-stopping-power
• Hassaan Inayatali, Aaron White, Jaden Majumdar and Daniel Hocevar (undergraduate track), https://www.kaggle.com/code/hassaaninayatali/every-step-you-take-measuring-a-defender-s-moves/notebook
• Nick Gurol, Tom Bryan, Ben Dominguez and Ben Wolbransky (metric track), https://www.kaggle.com/code/hassaaninayatali/every-step-you-take-measuring-a-defender-s-moves/notebook

Honorable Mentions:

• Ben Jenkins and Steve Jenkins (metric track), https://operations.nfl.com/gameday/analytics/big-data-bowl/2024-big-data-bowl-finalists/
• Danielle Cabel (coaching track), https://www.kaggle.com/code/dcabel02/making-the-tackle-linebacker-trading-cards
• Jesse Fischer (coaching track), https://www.kaggle.com/code/jessefis/nfl-bdb-2024-missed-tackles-and-player-fatigue
• Lauren James (metric track), https://www.kaggle.com/code/laurenjames10/no-edge-no-chance-analysis-on-setting-the-edge/notebook
• Nick Bachelder (metric track), https://www.kaggle.com/code/nickb1125/spatial-density-estimation-for-tackles-eys-pfi?scriptVersionId=161830638
• Raunaq Singh, Arham Habib and Anvit Rao (undergraduate track), https://www.kaggle.com/code/anvitrao/it-takes-a-village-tackle-contributions
• Robert Bajons, Jan-Ole Koslik, Rouven Michels and Marius Ötting (metric track), https://www.kaggle.com/code/robbwu/pep-a-metric-for-evaluating-tackles/report​
• Sam Kirschner, Tim Keller and Andrew May (metric track), https://www.kaggle.com/code/slayerpark/predator