FORMULA 1 is a battle between the world’s best drivers, but it’s also a battle of some of the world’s most innovative engineers. No other sport has been as dynamic in its evolution and embrace of new technology. While some of the tech goes to helping drivers, who are hitting speeds as high as 230 MPH, taking pit stops in under 2 seconds, and flying around corners with a force of 5G, much of it goes to enhance the experiences of its growing base of over a half a billion fans. This is why AWS is proud to be both the official cloud service and machine learning provider for FORMULA 1.

Here’s how it works:

the Series

Technology has always played a central role in the evolution of the sport, but serverless and machine learning are changing how F1 automates, collects, analyzes, and leverages data to make decisions.

Increasing Action
on the Track

F1 is taking the competition to the next level by altering some of the rules around car design. F1 simulates these changes using AWS High Performance Compute services to make sim cycles faster and more sophisticated.

Delivering Deeper

F1 uses Amazon SageMaker to build machine learning models that help fans better understand the split-second decisions made by a driver or pit crew that can dramatically affect the outcome.

In the news

Learn More About Car Analysis / Car Development from the Expert

Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight. Focusing on the three core elements of F1 car development, the graphic will measure development of performance in Aerodynamic Drag, Aerodynamic Downforce, and Engine Power, built on lap time analysis and using telemetry data as the primary source input.

Read the blog ›

Learn More About Corner Analysis from the Expert

Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight, Corner Analysis. This provides an insight into the detail of why some cars perform better than others through high and low speed corners – the single most important area for performance for an F1 car – by analyzing and comparing the performance through the principal sections of a corner via car telemetry data.

Read the blog ›

AWS and Formula 1 Announce New Racing Performance Stats for 2020 Season

First of six real-time racing statistics to debut July 3 weekend with the launch of “Car Performance Scores” at the season opening Grand Prix in Spielberg, Austria

Read the press release ›

Learn More About Car Performance Scores from the Expert

Rob Smedley, Chief Technical Engineer - F1 Performance Engineering and Analysis, details the importance of the new F1 Insight Car Performance Scores. These important aspects of Formula 1 car performance give fans a much clearer understanding from the very outset of how the different cars perform relative to each other.

Read more ›

Formula 1 Works With AWS To Develop Next Generation Race Car

The F1 Computational Fluid Dynamics project utilized over 12,000 hours of compute time to design the race car for the 2021 season. Watch F1 Chief Technical Engineer Rob Smedley’s re:Invent keynote on partnering with AWS to change the design and improve the fan experience. Visit the link below to read the press release about project.

Read more ›


Want to look under the hood and see how it’s done? Learn more about how AWS and F1 are using data to teach Amazon SageMaker complex machine learning algorithms that deliver new insights and increase action for fans, predicting outcomes with impressive accuracy as races unfold, and using data to design the next race car.

Read more >
F1 eBook Cover(2)
Image credit placeholer


During a FORMULA 1 Grand Prix every car contains 120 sensors which generate 1.1M telemetry data points per second transmitted from the cars to the pits. This real-time data is combined with over 69 years of historical race data stored on S3 to inform fans and teams about the unparalleled track-side decision making.



By sourcing historical data and using it to teach Amazon SageMaker complex machine learning algorithms, F1 can predict race strategy outcomes with increasing accuracy for teams, cars, and drivers. These models are then able to predict future scenarios using refreshed realtime data as Grand Prix races unfold to deliver a rich and engaging fan experience.


Battle Forecast

Throughout F1 history, some of the most exciting racing action on track has come from driver ‘battles’ —when a chasing driver gets close enough to attempt an overtake. The resulting fight for position results in an unpredictable and sometimes dangerous combination of offensive and defensive driving action between the drivers involved. The Battle Forecast graphic analyses track history and projected driver pace to provide an insight into developing driver battles during the race that are not always obvious to the audience.

Pit Strategy Battle

Undercutting and overcutting are strategies used by F1 teams during close racing scenarios to gain a lead over a rival, with the margin between success and failure measured in tenths of a second. Pit Strategy Battle provides fans and commentators with real-time insight on the position of the two rival drivers, the predicted gap after their respective pit stops, and the percentage chance of an overtake, helping fans to assess how successful each driver’s strategy will be in real time and its potential outcome.

Tyre Performance


F1 teams are allowed a range of tyre compounds providing performance ranging from higher grip to longer lifespan. Tyre performance and degradation is a primary concern of the teams during a race and finding the perfect balance between lap time and tyre condition is a critical element of a race winning strategy. By analyzing timing and telemetry information and estimating lap time lost due to tyre power and tyre energies, Tyre Performance gives fans and commentators a better understanding of the current performance level.


Getting Started With Professional Services

In 2018 F1 engaged with the AWS Professional Services team, who has since delivered two models to support race graphics: Pit Stop Advantage in March 2019, and Battle Forecast in July 2019. F1 continues to innovate with the Professional Services team and Amazon ML Solutions Lab Team to accelerate development of F1 Insights by prototyping use cases and develop new proofs of concept. The ProServ team then helps F1 get models in to production and integrated into the F1 infrastructure.

Ready to get Started?
Learn more about working with AWS Professional Services