How AWS Turns the Super Bowl into a Real-Time Data Lab

Have you ever thought about ways in which data is measured at the Super Bowl?

Put it this way: it's not just touchdowns and yardages that are being counted.

At the annual league championship game of the National Football League – the NFL’s most watched event – AWS powers an immense computational system that transforms every player movement into immediate insight.

But how? Every game of the NFL season – including the Super Bowl – generates millions of positional data points from RFID chips embedded in player pads and footballs. 

More than 20 ultra-wideband receivers track each of the 22 players 10 times a second and the ball itself at 25 times per second. 

The system’s core, Next Gen Stats, converts that torrent of telemetry into decision-grade analytics in under a second.

AWS: Forming the digital backbone of the NFL

“Football, for 100-plus years, has been a box score game: you’ve got yards, you’ve got touchdowns, you’ve got tackles,” says Mike Band, Senior Manager of Research and Analytics with NFL’s Next Gen Stats in conversation with AWS.

But just as the game has grown, so too has the technology that surrounds it.

The inflection point came in 2018, when the NFL and AWS expanded a partnership that shifted tracking from a tactical tool into a strategic one. That’s when the league introduced completion probability – an ML metric built with Amazon SageMaker using XGBoost models.

The model considers factors such as pressure, receiver separation and throw depth to calculate a single percentage score for each pass attempt.

“That became our entry point into machine learning,” he says.

​This has helped the NFL turn raw tracking into a real-time product.

By deploying AWS’ infrastructure – spanning SageMaker, AWS Lambda and Amazon QuickSight – the NFL’s analytics backbone has drastically evolved. 

During the Super Bowl, those tools support broadcasters, coaches and analysts with sub-second feedback, ensuring every play can be decoded visually and statistically for fans around the world.

“Every NFL game generates millions of raw-tracking data points, yet the raw feed is only the substrate,” AWS says.

“The real data growth comes from the models that convert coordinates into usable football insight. Pressure probability, for example, estimates how likely a defender is to affect the quarterback at each moment of a pass rush and produces more than a dozen secondary metrics.”

Mike estimates that Next Gen Stats (NGS) now produces between 500 and 1,000 stats per play.

AWS says that keeping the system responsive depends on the providers’ infrastructure to ingest the feed, run the models, return results within seconds for teams and broadcasters, and store the wider data trove for deeper analysis.

Shaping rules, safety and strategy with data

At the league level, this capability extends beyond entertainment. NGS models inform player safety policies, officiating reviews and even rule changes. 

For instance, the dynamic kickoff introduced in the 2024 season stemmed from NGS analysis that quantified the risks of high-speed collisions. 

“The season before, we were showing Next Gen Stats animations of the space and relative speeds of the players, and that analysis became a critical part of the rules change,” says Mike Lopez, Senior Director of NFL Football Data and Analytics.

The data-driven redesign reduced lower-extremity injuries by 35% while increasing return plays and overall in-game excitement. 

Two seasons of data show the dynamic kickoff is working: the 2025 return rate jumped to 75% from 32% in 2024 and, even with 1,157 more plays, lower-extremity injuries dropped 35% while concussion rates remain below the old kickoff format.

This is not all that AWS’ data is shaping, however.

AWS’ influence now extends far past the server room as new optical tracking systems – installed across every NFL venue – use 4K cameras to capture full three-dimensional skeletal movement, creating digital models of each player.

“The explosion in the volume of data can be daunting,” says Dashiell Flynn, AWS’ Principal Sports Consultant. 

“But once folks wrap their heads around it, the ideas start flowing very quickly.”

Each stadium now hosts AWS servers that process the data within about 700 milliseconds. The processed, simplified data is then sent to the cloud, where ML models run in less than 100 milliseconds and returns analysis to the production team, keeping the full capture-to-analysis pipeline to under a second.

For AWS, the Super Bowl has become an annual showcase of what enterprise-grade AI systems can accomplish in real time. 

Ten years into the partnership, the NFL’s data infrastructure looks less like a collection of servers and dashboards and more like a sport’s neural network – one that’s learning, predicting and evolving with every movement.