You are challenged to build an analytical framework that uncovers non-obvious, actionable linkages between 10 Hz Combine sensor tracking data and future regular-season NFL game performance. Your submission should look beyond conventional scouting wisdom and identifying novel signals that help coaches and evaluators identify hidden talent, avoid costly draft busts, and design position-specific player development protocols.
Every spring, college football’s top prospects gather in Indianapolis for the NFL Scouting Combine. For decades, player evaluation at the Combine has relied on standardized stopwatch timings and physical testing numbers, such as the 40-yard dash, short shuttle, 3-cone drill, and vertical jump. While these numbers provide a baseline measure of straight-line speed and explosiveness, player tracking sensors worn during workouts now capture the full details of how athletes move throughout each drill.
The 2027 Big Data Bowl provides player tracking data from the NFL Scouting Combine alongside regular-season NFL game tracking data. The goal of this year’s competition is to better understand how player movement during Combine drills translates to performance on the field during the NFL regular season.
In this competition, participants are tasked with analyzing prospect movement in a way that is actionable and accessible to coaches, scouts, and front offices. This could include creating a new metric or comparing movement traits across position groups. As is often the case in Big Data Bowl analytics competitions, participants are encouraged to focus on one small aspect of movement, a specific position group, or an individual drill, rather than attempting to evaluate every prospect across all drills.
Awards:- $100,000
Deadline:- 07-01-2027
