DeepQB: Deep Learning to Quantify Quarterback Decision-Making with Brian Burke - TWIML Talk #297
Published:Sep 5, 2019 18:11
•1 min read
•Practical AI
Analysis
This article from Practical AI discusses Brian Burke's work on using deep learning to analyze quarterback decision-making in football. Burke, an analytics specialist at ESPN and a former Navy pilot, draws parallels between the quick decision-making of fighter pilots and quarterbacks. The episode focuses on his paper, "DeepQB: Deep Learning with Player Tracking to Quantify Quarterback Decision-Making & Performance," exploring its implications for football and Burke's enthusiasm for machine learning in sports. The article highlights the application of AI in analyzing complex human behavior and performance in a competitive environment.
Key Takeaways
- •The article focuses on the application of deep learning to analyze quarterback decision-making in football.
- •Brian Burke, an ESPN analytics specialist, is the central figure, drawing parallels between quarterbacks and fighter pilots.
- •The discussion revolves around Burke's paper, "DeepQB," and its implications for the sport.
Reference
“In this episode, we discuss his paper: “DeepQB: Deep Learning with Player Tracking to Quantify Quarterback Decision-Making & Performance”, what it means for football, and his excitement for machine learning in sports.”