NFL Launched Ninth Annual Big Data Bowl

The competition challenges participants to analyze NFL Scouting Combine metrics to predict professional success.

Updated on Oct. 7, 2026 in Football

Live Poll

Do you trust data analytics more than traditional scouting to predict a player's professional success?

The NFL and Amazon Web Services have opened registration for the ninth annual Big Data Bowl. Participants will use player tracking data to evaluate performance metrics from the 2023, 2024, and 2025 NFL Scouting Combines.

Why it matters

The league aims to identify which specific physical and athletic metrics from the Scouting Combine most accurately correlate with long-term success on the field in professional games.

The ninth annual competition offers a $100,000 shared prize for participants analyzing player tracking data across five positions. Analysts are tasked with comparing Scouting Combine metrics against professional performance data from 2023 through 2025.

The players

NFL

The National Football League is the premier professional American football league in the United States.

Amazon Web Services

A subsidiary of Amazon that provides on-demand cloud computing platforms and APIs to individuals and organizations.

Kaggle

An online community platform for data scientists and machine learning practitioners to share and analyze datasets.

The details

Hosted on the Kaggle platform, this edition focuses on metrics for wide receivers, tight ends, offensive linemen, defensive linemen, and defensive backs. Participants must analyze this data to determine how pre-draft physical tests predict future on-field performance.

Wednesday, October 8, 2026: Sign-ups for the competition begin.
2023-2025: This range covers the years of player data provided to participants.
2027: Winners are scheduled to present their findings at the NFL Scouting Combine.

Season Trajectory

This competition leverages the NFL Next Gen Stats player tracking system to refine the metrics used by front offices during the draft process. By crowdsourcing these analytics, the league effectively creates a new pipeline for identifying talent that bridges the gap between combine testing and game performance.

The models developed in this competition may directly influence how NFL teams prioritize specific athletic traits during the upcoming draft cycle. Fantasy players and analysts can track these findings to better understand the correlation between pre-draft testing and high-level professional output.

The takeaway

The competition highlights how advanced statistical modeling is becoming essential to modern roster construction and talent evaluation. Aspiring analysts can use this platform to demonstrate their ability to turn raw physical testing data into actionable team strategy.