Finalists named for fourth annual NFL Big Data Bowl powered by AWS
NEW YORK, NY (February 16, 2022) – The National Football League announced today the finalists of the fourth annual Big Data Bowl powered by Amazon Web Services (AWS). The Big Data Bowl is designed to engage the data and analytics community and rethink player performance.
The theme of this year’s competition centers on Special Teams. Participants were given access to the NFL’s Next Gen Stats, including the speed, direction, and location information of all 22 players on the field, as well as the football, from Special Teams plays from 2018 to 2020. More than 200 submissions reviewed punt, field goal, and kickoff strategies from both team and player perspectives. Participants also received Special Teams data from PFF, allowing entrants to blend tracking and scouting metrics together.
Five open entry and three college entry finalists were selected and will share a prize pool of $90,000. An additional $10,000 will be awarded to the winning group of the upcoming Big Data Bowl virtual show, bringing their competition total to $100,000. This year’s Big Data Bowl virtual show will showcase each of the eight finalist presentations with a focus on how teams could use each approach to improve performance.
«The Big Data Bowl continues to push the envelope for integrating modern analytical tools with creative football ideas,» said Michael Lopez, Senior Director of Football Data and Analytics at the NFL. «We are amazed at the growth of our contest and the passion of participants, and we look forward to the upcoming Big Data Bowl virtual show.»
In addition to innovation, the competition also helps the League identify and develop future industry leaders. Since the Big Data Bowl launched in 2018, this competition has served as a pipeline for NFL teams and vendors, as well as other leagues. To date, more than 30 Big Data Bowl participants have been hired to work in data and analytics roles in sports, including 22 that were hired in football. In addition, the winning algorithm from the 2020 Big Data Bowl – expected rush yards – has been adopted into the Next Gen Stats suite of metrics.
For the second consecutive year, the Big Data Bowl also features a mentorship program where a dozen junior data scientists from diverse backgrounds are paired with experienced NFL analytics experts to help curate a Big Data Bowl submission.
Below are the eight Big Data Bowl finalists for 2022, as well as the ten honorable mention entrants along with summaries of their submissions.
College Finalists:
- Jack Lichtenstein, Duke University, https://www.kaggle.com/jacklichtenstein/expected-field-position-on-punts
- Jay Li, & Rahul Kasar, MIT, https://www.kaggle.com/wonkydiamond/firetime-evaluating-gunners-and-vises
- Robyn Ritchie, Brendan Kumagai, Ryker Moreau, & Elijah Cavan, Simon Fraser University, https://www.kaggle.com/robynritchie/punt-returns-using-the-math-to-find-the-path
Open Finalists:
- Ian Barnett, https://www.kaggle.com/ianjamesbarnett/nfl-big-data-bowl-2022-introducing-coyote
- John Miller, & Uri Smashnov, https://www.kaggle.com/jpmiller/augmented-reality-for-kickoffs-and-punts
- Joseph Rudoler, Tai Nguyen, Ryan Brill, & Ryan Gross, https://www.kaggle.com/jrudoler56/optimal-run-path-for-kick-returners
- Marc Richards, Wei Peng, Jack Werner & Sam Walczak, https://www.kaggle.com/model284/where-should-punters-aim
- Robert Sims, https://www.kaggle.com/rxsims/evaluating-punters-relative-to-optimal-punting
Honorable Mention:
- Andrew Akers, https://www.kaggle.com/andrewakers9/net-punt-yards-gained
- Charles Giess, https://www.kaggle.com/charlesgiess/optimising-gunner-and-vise-tactics-and-techniques
- Conor Malone, https://www.kaggle.com/connyfromtheblock/valuing-blocking-on-kick-return-plays
- Jesse Fischer, https://www.kaggle.com/jessefis/nfl-big-data-bowl-2022
- Maxwell St. John, & Nicholas Mills, University of Virginia, https://www.kaggle.com/maxwellstjohn/expected-kickoff-return-yards
- Nate Hawkins, & Jacob Mark Miller, Brigham Young University, https://www.kaggle.com/jacobmarkmiller/improving-punt-returner-decision-making
- Quinn MacLean, https://www.kaggle.com/qmaclean/evaluating-gunner-s-performance
- Sarah Hu, Zach Bradlow, & Zach Drapkin, University of Pennsylvania, https://www.kaggle.com/husarah/deeps-dive-a-process-oriented-approach-to-returns
- Scott Maran, Stanford University, https://www.kaggle.com/smaran2430/big-data-bowl
- Zac Rogers, https://www.kaggle.com/zacrogersuk/playertv-by-zacrogers-excluding-appendix
For a complete view of this year’s competition, visit the NFL’s Kaggle competition page. To learn more about the Big Data Bowl and this year’s virtual show, click here.
