Miller said the goal of the league is to create a “digital athlete” that can become a virtual representation of the actions, movements and impacts an NFL player experiences on the field during a game and can be used to help predict and hopefully prevent injury in the future.
“That is novel for us and obviously has great importance in how we think about making the game safer for the athletes,” Miller said “It will have an effect on training and coaching, certainly. It will have an effect in rules without a doubt. It will definitely have an impact in terms of equipment, and benefits that we can see from equipment because now for the first time we’ll have a pretty good appreciation for every time somebody hits their head during the course of an NFL game, and therefore, we will look for ways to prevent many of those.”
Priya Ponnapalli, senior manager with Amazon’s Machine Learning Solutions Lab said the potential for machine learning to analyze past data but also make forward-looking projections will be helpful in the future in helping create a digital version of players at all positions and analyze the types of hits they take.
“Machine learning is a very intuitive process and you get to a certain level of performance, and in this case we’ve got some pretty accurate and comprehensive models,” Ponnapalli said. “And as we collect more data, these models are going to get better and better.”