Behind every incredible play are thousands of data points you might otherwise miss, such as player’s speed, field location, and movement patterns. The NFL uses AWS to track the scale, speed, and complexity of that data. It’s called Next Gen Stats (NGS) and with AWS Machine Learning and Artificial Intelligence technology, the NFL has developed ways to visualize the action on the field, uncover deeper insights, and expand the fan experience by offering a broader range of advanced stats.

Here’s how it works:


Capture Data

Data is captured by placing RFID tags on player’s shoulder pads and the game ball. Ultra-wideband receivers track the players and ball movement down to the inch. The data collected leverages Amazon EC2, S3, and EMR in the capture and storage process.


Analyze It

Next, this real-time data is combined with traditional box score/play-by-play data to calculate 100’s of metrics never captured before. These metrics are run through Machine Learning models built on Amazon SageMaker to output predictions, stats and more.


Distribute Results

Finally, the NFL leverages AWS Lambda, Amazon ElastiCache, Quicksight, RDS, Route S3, API gateway, and DynamoDB to put the insights, predictions, and stats into broadcast analysis, scouting, and coaching tools.



By leveraging AWS’s broad range of cloud-based machine learning capabilities, the NFL is taking its game-day stats to the next level so that fans, broadcasters, coaches, and teams can benefit from deeper insights.


Training data from traditional box score statistics, as well as data collected from the stadium, will run through 100’s of processes within seconds with the output fed into Amazon Sagemaker. From there machine learning models built by the NGS team ingest the data, which continually train and refine the models. The machine learning models are then deployed in real-time during games to generate outputs such as formations, routes, and events.

In the news


By combining the NFL's vast trove of football data and insights with AWS’s expertise in machine learning, AI, and cloud computing, the NFL is expanding its partnership with AWS beyond its Next Gen Stats fan experience, generating new insights into player injuries, game rules, equipment, rehabilitation, and recovery.


Going Long on Machine Learning with the NFL

Want to see the playbook? Read more about the NFL’s machine learning journey, with an introduction from NFL CIO Michelle R. McKenna—and hear from Matt Swensson firsthand how his Next Gen Stat’s team worked with the AWS Machine Learning Solutions Lab to build, train, and deploy their machine learning models on Amazon SageMaker.




One of the biggest benefits of this data is improving the fan experience. The NFL has built several new stats on AWS, each of which relies on different data points. The data-points can output a variety of different stats. Here are just a few examples:

Completion Probability

The probability of a completed pass is based on numerous factors such as the separation of the passer from the nearest rusher at time of throw, where the receiver is on the field, and the separation between the receiver and the nearest defender.

Expected Yards After Catch

Amazon Sagemaker outputs the expected yards after catch, based on numerous factors using tracking data such as how open the receiver is, how fast they’re traveling, and how many defenders/blockers are in the space.

Expected Catch Rate

How often a passer throws a risk pass, based on the probability of an incompletion or interception, using tracking data predictions before the QB releases the ball.



With years of experience using machine learning, AWS is the best choice for the NFL to leverage the power of its data through sophisticated analytics and machine learning. Today the NFL is able to create new stats and the end result is a better experience for fans, players and teams—all in real time.

Here are just a few things that make AWS the right technology partner for the NFL.

Machine Learning

The NFL uses machine learning and data analytics services to boost the accuracy, speed, and insights provided by its Next Gen Stats platform.

Quick Access

Using the business intelligence tool Amazon QuickSight, the NFL is able to gain greater insight while also opening a window for fans, broadcasters, and editorial to engage with data.


Using Amazon SageMaker to build, train, and run predictive models helped reduce the time to get results from as much as 12 hours to 30 minutes.


"We chose AWS because of its combination of advanced cloud offering, powerful machine learning capabilities, and experience operating at the scale we need. By powering Next Gen Stats with AWS, we’ll be able to kick off our [season] with even more impactful and meaningful content, uncovering deeper insights into the game of football than we’ve ever done before."

- Matt Swensson, Vice President, Emerging Products and Technology at the NFL



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