🏈 AI in College Football: Texas vs. Florida and the Play AI Didn’t Call
College football has never lacked people who know which play to call. Most reveal their genius after the whistle.
Texas briefly gave those critics a new target. A report suggested its new AI platform, Bevo Lab, influenced a failed fourth-down decision against Florida. Athletic director Chris Del Conte clarified that he had offered the play as an example of what the system could suggest. It hadn’t made that call.
The actual project deserves attention. As an example of AI in college football, Texas is bringing game film, athlete data and predictive tools together with support from Google Cloud, Dell and SHI. The aim is to help coaches prepare, evaluate players and make better decisions, while giving students experience building the technology.
One early result offers a practical reason to care: project leader Kirk Goldsberry says automated game-planning reports are already saving the football staff more than 15 hours each week. That creates more time for player development and preparation.
Fifteen hours could mean more time helping a young player understand a mistake, master a skill or regain confidence. What coaches do with those hours will help determine the technology’s worth.
❓ The Big Question About AI in College Football
If AI gives coaches more time, will athletes get more of their attention?
⭐ Why It’s Important
For schools, academies and teams, that question offers a useful way to judge the next technology pitch.
Start with work that consumes a coach’s day. Test whether the tool saves time and produces information the staff can trust. Then put those hours toward teaching, practice and individual feedback.
A coach should also be able to explain a decision and take responsibility for it. A recommendation on a screen deserves the same scrutiny as advice from any assistant.
The machine can finish the scouting report. The coach still has to look a player in the eye.
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