The National Football League is working with Amazon Web Services to create AI-powered algorithms that extract meaningful data from games and decipher patterns in player performances.
The AWS and NFL partners have focused on developing machine-learning models that can provide data relating to, according to Amazon. The first application is giving the AI the ability to identify blockers and pass rushers in pass plays. Second, teaching the tool how to quantify “pressure” in a game. And lastly, the development of a process to detect individual blocker-rusher matchups.
In the game of football, quantifying the performance of offensive players and the rushers that tackle them can be a difficult feat, even for game experts who have the eye for these quick movements. Player reactions can happen in split moments and an individual’s performance in these high-speed exchanges can be hard to track and let alone quantify. Things like how close a defender got to the offensive lineup can help a coach understand the strength of their plays.
. In every participating NFL venue, there are at least 20-30 ultra-wide band receivers inside the field and there are 2-3 radio-frequency identification tags inside each players’ shoulder pads and on other game gear, like balls and posts. These data transmitters collect information that is fed through a graphic neural network model , which allows the data to be relayed in real time. Using AI, the stats being extracted can be made into meaningful insights.
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