2020-21 Big Data Bowl

Recap of the NFL's third annual Big Data Bowl.

The third annual Big Data Bowl, powered by Amazon Web Services (AWS), called on both professional and aspiring data analysts to devise innovative and data-driven approaches to analyzing pass coverage in the NFL.

Using Next Gen Stats powered by AWS, the 2020-21 Big Data Bowl called on both professional and aspiring data analysts to devise innovative and data-driven approaches to analyzing pass coverage in the NFL.  

"The Big Data Bowl has changed how NFL clubs and their fans ingest and understand the game," said NFL Director of Football Data and Analytics Mike Lopez. "This year's event covered new ground in football analytics – defending the pass play. More than 250 participants submitted a unique approach, and the eight finalist teams represent the best of the best public football analytics work done to date. Today's event was the culmination of their hard work, as well as a celebration of how data is transforming what happens on the field and in front offices of the NFL."

2020-21 Big Data Bowl Winners

The 2020-21 Big Data Bowl winning announcement. 

The winning group of Wei Peng, Marc Richards, Sam Walczak, and Jack Werner took home an additional $10,000 prize, bringing their competition total to $25,000.

See the 2020-21 Big Data Bowl winning submission on Kaggle.

The group generated play outcome models for each frame of the data, as well as classified man versus zone coverage schemes to measure the before and after pass ability of each defender.

2020-21 BIG DATA BOWL judges & guests

Hear from Baltimore Ravens head coach John Harbaugh as he joined the program.

Each finalist presented their respective algorithms to a panel of judges made up of Cynthia Frelund, three former Big Data Bowl participants and a data scientist from AWS:

  • Katherine Evans, Phd, Director of Strategic Research – Toronto Raptors
  • Cynthia Frelund, Predictive Analytics Expert – NFL Network
  • Nate Sterken, Lead Data Scientist – Cleveland Browns
  • Adam Vonder Haar, Football Research Analyst – Dallas Cowboys
  • Colby Wise, Sr. Deep Learning Scientist – AWS AI

Baltimore Ravens head coach John Harbaugh joined the program for a football analytics conversation alongside Frelund and Lopez. Harbaugh shared why the Ravens organization values data and analytics, advice for aspiring football data analysts, and his thoughts on the annual competition.

"This Big Data Bowl is a great way to broaden the perspective of the sport and to get more people involved in it in a fun way," said Harbaugh. "There are so many perspectives and ways to look at anything, especially football because it's a complex, crazy game."

2020-21 BIG DATA BOWL Finalists 

Below are summaries of each presentation from the finalists in the "Open" and "College" categories presented during the 2020-21 Big Data Bowl:

Open Finalists 

Joe Andruzzi
Joe analyzed individual defender success while guarding a receiver making a cut or double move.

Hear from finalists Matthew Gartenhaus and James Venzor as they discuss their Big Data Bowl submission. 

Dani Chu, Matthew Reyers, Meyappan Subbaiah, Lucas Wu
The group of Meyappan, Dani, Matthew and Lucas isolated various parts of defensive coverage throughout a pass play to evaluate defender contribution.

Matthew Gartenhaus, James Venzor
The group of James and Matthew modeled six different defender attributes which take place during different stages of a pass play.

Asmae Toumi, Marschall Furman, Sydney Robinson, Tony ElHabr
The group of Asmae, Marschall, Sydney and Tony created target and completion probability models to build a defender effectiveness metric. Their metric accounts for both the ability to divert targets as well as the ability to break up passes.

College Finalists 

Zach Bradlow, Zach Drapkin, Ryan Gross, Sarah Hu – University of Pennsylvania
The group of Zach, Zach, Ryan and Sarah created a relative skill rating system based upon success in coverage matchups to measure defender skill.

Listen to finalist, Ella Summer as she shares her Big Data Bowl presentation.

Ella Summer – University of Virginia
Ella used statistical modeling to isolate individual defender effects on target and completion probability.

Jill Reiner – Denison University
Jill used statistical modeling to determine which defenders are best at averting targets, closing on targeted receivers and defending passes, and clustered each based on their strengths and weaknesses.

The Big Data Bowl also helps the league identify and develop future industry leaders. Dating back to the first Big Data Bowl in 2018, it has helped 15 participants secure jobs with either NFL clubs or affiliate vendors.

For the 2020-21 Big Data Bowl, the league added a mentorship program alongside the competition where 16 junior data scientists from diverse backgrounds were matched with experienced NFL analytics experts to curate a Big Data Bowl submission. Two participants in the mentorship program, Ella Summer and Jill Reiner, emerged as college finalists.

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