Beyond the stopwatch: Inside the NFL’s new interactive Combine dashboard

When prospects take the field at this year’s National Football League (NFL) Combine February 27–March 3 at Lucas Oil Stadium in Indianapolis, Indiana, they won’t perform only for scouts in the stands—they will generate hundreds of thousands of data points that flow directly into one of sports’ most sophisticated talent evaluation platforms. The NFL’s Next Gen Stats Combine IQ system, powered by Amazon Web Services (AWS) and Amazon QuickSight, represents a breakthrough in how to capture, visualize, and analyze athletic performance data in near real time.

The Next Gen Stats team developed the Combine IQ system to interpret the waves of athletic performance data collected at the NFL Combine. Draft Score incorporates real-time performance data, historical performance comparisons, and position-specific benchmarks to convert granular statistics into player ratings ranging from 50 to 99. These ratings specifically measure player athleticism and analyze how those attributes will contribute to potential success in the NFL, providing a sophisticated complement to traditional prospect evaluation methods.

“For the first time ever, the public will have access to the summary statistics of Combine tracking data through this tool,” explains Mike Band, who leads the NFL’s Next Gen Stats analytics team. “This is the third consecutive year of data collection derived from sensors worn by participants at the Combine. We feel really good and confident about the data we’re capturing, and we can create experiences that allow fans to follow along with that tracking data.”

Making better decisions with data

The challenge facing Band’s team wasn’t simply collecting prospect data—it was making it accessible and meaningful for fans worldwide and making it easier for leagues to apply it to recruiting decisions. The traditional NFL.com Combine tracker has long been a popular destination, but its capabilities were limited to basic sorting and filtering of standard drill results. The new Combine IQ dashboard powered by AWS represents a fundamental reimagining of how to explore and interpret Combine data.

The system processes an extraordinary amount of data for dashboard display. During previous Combines, only a handful of measurements per player were captured—things like 40-yard dash times and vertical jump heights. The new system tracks player movement data every tenth of a second during drills, using sensors worn by each player. This exponential increase in data granularity required a completely new approach to data visualization and analysis.

“What this dashboard really is, is it’s a tool to see everything and a tool to see specific things,” Band explains. “It’s a way to holistically follow and track the Combine in near real-time, see drill results as they come in, and show live research as it’s happening.”

Insights, built with ease

What makes the NFL’s implementation of QuickSight particularly interesting is how it enables domain experts to build sophisticated dashboards without the need for business intelligence experience. “Our dashboards are built by researchers, for researchers,” Band notes. “QuickSight really is this tool that has a low barrier to entry in terms of technical skill set. If you know the data and you know what you’re trying to build, it is more than likely possible to build it.”

This approach allows the NFL’s analytics team to iterate rapidly on visualizations and analysis and make adjustments based on their deep understanding of what matters most in player evaluation. Rather than providing specifications and requirements to a separate engineering team, researchers can directly translate their insights into interactive features.

Analysis at scale

The Combine IQ system’s near real-time capabilities are particularly impressive given the complexity and volume of incoming data for processing. During Combine drills, multiple events take place simultaneously across the field—from foot speed to position-specific drills—all of which generate continuous streams of measurable results and tracking data that need to be processed, validated, and visualized instantly.

This is particularly crucial given the exponential increase in data complexity. “Before 2022, we had data around seven or eight different measurables,” Band notes. “Now with tracking data, it’s beyond a tenfold increase.”

The team developed sophisticated data cleaning and validation pipelines to handle what Band calls “the chaos of the NFL Combine field.” With numerous players performing at the same time, the system needs to properly isolate and validate each athlete’s movements while filtering out noise from nearby activity.

“Every player out on the field wears a tracking sensor,” Band explains. “We’re not just capturing traditional metrics like 40-yard dash times, but deriving speed, acceleration, and change of direction statistics from the on-field workout drills. These statistics reflect underlying player performance across a range of capabilities.”

This tracking data flows into a sophisticated backend system that cleans and validates the data before making it available through the QuickSight dashboard. The system can identify when specific drills start and end, isolate relevant movement data, and update visualizations in near real-time.

Making data digestible

One of the dashboard’s most innovative features is its ability to surface noteworthy performance and historical context. “The dashboard hosts a live blog that continuously updates and contextualizes notable statistics and events at the Combine,” Band says. “When there’s a significant event that merits highlighting within the mountains of live data we’re collecting, we can present it in a digestible way.”

Taking this approach presents a hybrid experience that combines data visualizations with narrative context. Users can seamlessly switch between different ways of understanding the data—from raw numbers to interactive visualizations to written analysis.

Rather than simply noting a player’s 40-yard dash time, for instance, fans can analyze acceleration profile, top speed at different distances, and deceleration patterns. For position drills, dashboard users can quantify things like route-running precision and change-of-direction ability that previously relied solely on scouts’ subjective observations.

Machine learning integration

The QuickSight dashboard doesn’t just make existing player performance data digestible—it integrates the NFL’s sophisticated machine learning models that predict player success probabilities. These models, built using advanced AI and machine learning models, analyze complex interactions between different athletic traits to identify which combinations of attributes matter most for each position.

“We’ve actually created pre-modeling composite measures,” Band explains. “We combine weight, 40-yard dash time and 10-yard split to come up with a composite value that represents your size, weight, and speed relative to others. Or, we combine vertical jump and broad jump together to create an explosiveness metric.”

The system is trained on historical data to predict three key outcomes: the chances a player becomes a starter in their rookie season, the likelihood they become a starter within their first three seasons, and the probability they make the Pro Bowl in those first three years.

“It’s not that you necessarily have to be the fastest player or the biggest player or the most explosive player,” Band notes, “but you do have to meet the ‘fast enough, big enough, strong enough, smart enough’ criteria. The interactions between these measurables is the best way to find the key thresholds where it’s not necessarily linear, it’s more threshold-based.”

Future implications

For data professionals, the NFL’s implementation of Amazon QuickSight demonstrates how the combination of cloud-based business intelligence services and AI can make complex data analysis accessible to broader audiences. The system successfully bridges the gap between sophisticated data science and user-friendly interfaces, allowing everyone from casual fans to professional scouts to derive meaningful insights from the data.

“We need data from multiple draft classes, then we need those draft classes to participate in the NFL, and to know who’s performing well and who’s not,” Band explains. “Only then can we again test to verify these tracking data metrics have high correlation power to predicting NFL success.”

As the system continues to evolve, the Next Gen Stats team plans to incorporate more advanced analytics capabilities. With three years of tracking data now available, they can begin to identify which metrics have the strongest predictive power for NFL success and present these insights through the dashboard.

“We’re trying to mimic what an NFL analytics department would be doing,” Band notes. “The tracking data we collect at the Combine can augment what clubs currently observe and measure. At the team level, we know clubs are very interested in bringing what we offer into their process.”

This latest advance for the NFL illustrates how AWS can help transform raw data into actionable insights at scale. By combining the flexibility of Amazon QuickSight with domain expertise and sophisticated machine learning models, the NFL has created a system that’s not just collecting more data than ever before—it’s turning that data into meaningful insights for everyone who interacts with it.

To explore the NGS Combine IQ dashboard, analyze player performance, and evaluate the next generation of NFL talent, visit nfl.com/combine/iq.