AWS for M&E Blog
Formula 1® unlocks the most competitive season yet with AWS
This post is co-authored by Ruth Buscombe-Divey, AWS Motorsports Ambassador and Technical Advisor and Race Strategist at Formula 1.
In the high-octane world of Formula 1® (F1), where milliseconds separate triumph from defeat, data isn’t just valuable—it’s the invisible force reshaping the sport itself.
Since 2018, F1 and Amazon Web Services (AWS) have innovated together to leverage data and cloud technologies to transform the sport. Along with AWS, Ruth Buscombe-Divey, a F1 strategist and now AWS Motorsports and Technical Advisor, has had a front-row seat to this evolution. In particular she has focused on how F1 Insights powered by AWS has revolutionized the fan’s understanding of the sport’s complexities.
The 2024 season proved this in spectacular fashion, delivering the closest field in F1 history, with the cloud computing muscle of AWS transforming 300 million data points during each race into edge-of-your-seat storytelling. While Max Verstappen and McLaren secured their Championship titles by a wider margin than Niki Lauda’s legendary 0.5-point victory over Alain Prost in 1984, this past season was one of the tightest fields we’ve ever seen in Formula 1. Behind these incredibly close margins lies sophisticated artificial intelligence and machine learning technology from AWS. Let’s dive into some of the key turning points during the 2024 season.
When one percent separates an entire grid
The Austrian Grand Prix qualifying session made history when just 0.798 seconds separated P1 from P20—the tightest qualifying spread ever recorded in Formula 1. This wasn’t just a statistical anomaly; it was the culmination of a technological revolution quietly reshaping motorsport’s premier championship.
When the entire field is separated by just over one percent, every aspect of performance becomes critical. The difference between winning and losing comes down to driver skill, team execution, and the ability to leverage data for even the smallest marginal gain.
Behind these razor-thin margins lies the artificial intelligence and machine learning infrastructure of AWS. Amazon SageMaker AI processes hundreds of millions of data points, transforming raw telemetry into the F1 Insights that have become a staple of race broadcasts worldwide. These visualizations don’t just enhance the viewing experience—they decode the sport’s complexity in near real-time.
The Montreal miracle: How data revealed Mercedes’ true potential
The FORMULA 1 AWS GRAND PRIX DU CANADA 2024 provided the perfect case study of data’s transformative power. Mercedes-AMG F1 arrived in Montreal as underdogs, carrying a new front-wing upgrade package designed to address their W15’s handling imbalances. When Lewis Hamilton topped the timesheets in FP3, skeptics dismissed it as engine mode trickery.
The Car Performance Scores analysis by AWS told a different story. The data revealed Hamilton had genuinely outpaced Verstappen in 8 of 14 corners, plus the straights. This wasn’t just a power advantage—it was a fundamental shift in the car’s performance envelope. Near real-time analytics, powered by AWS, broadcasted this revelation worldwide before qualifying even began, setting up the dramatic narrative that would unfold.
What followed was historic: George Russell and Max Verstappen set identical qualifying times of 1:12.000—only the second qualifying dead heat in F1 history after Jerez 1997. Russell secured pole position by virtue of setting his time first, according to F1 regulations. The race delivered everything fans could want: unpredictable weather, strategic gambles, and a three-team battle for victory that would become the season’s signature.
Figure A: F1 Montreal Lap Time Analysis.
AI designs the future—literally
When Max Verstappen claimed victory in Montreal, he hoisted a trophy unlike any other in F1 history—the first designed by generative AI. Using Amazon Titan Image Generator, a foundation model in Amazon Bedrock, AWS created hundreds of trophy concepts in minutes. The winning design elegantly captured the aerodynamic wake of an F1 car, symbolizing the sport’s fusion of technology and competition.
This wasn’t just artistic showmanship. The same AI technology that shaped the trophy had previously contributed to the aerodynamic research behind the 2022-2026 F1 car design, demonstrating how deeply AWS technology has integrated into every aspect of the sport.
The microscope moment: Time Lost F1 Insight debuts in Austin
At the United States Grand Prix Sprint weekend in Austin, while teams brought car upgrades, AWS unveiled a technological upgrade of its own: the new Time Lost, F1 Insight powered by AWS. This revolutionary broadcast graphic breaks down precisely where and how drivers lose time on the track, comparing performance against an optimal reference lap.
The insight’s debut couldn’t have been more dramatic. During Sprint Qualifying, the data exposed how an unintended downshift cost Lando Norris crucial tenths and potentially pole position. By pinpointing the exact section of track where the error occurred, Time Lost made visible what would have remained hidden to all but the most technical observers. This analysis was broadcast live from the Austin podium, adding a new dimension to post-session understanding.
Figure B: F1 Austin-Sprint Qualifying Lap-Time Analysis.
The season of statistical extremes
As the checkered flag fell on 2024, McLaren ended a 26-year Constructors’ Championship drought dating back to 1998. Meanwhile, Max Verstappen secured his fourth consecutive Drivers’ Championship with a drive for the ages—climbing from P17 to victory, a feat achieved only five times previously in F1’s 74-year history.
The 75th anniversary season: Data will decide
The 2025 Formula 1 season—the championship’s 75th anniversary—has already shown signs of being even more competitive. Pre-season testing in Bahrain revealed McLaren’s continued strength, with Lando Norris’s practice race simulation turning heads throughout the paddock.
The data, as always, tells a more complex story. Oracle Red Bull Racing’s reliability issues have obscured their true potential, while Scuderia Ferrari HP’s tire degradation made Charles Leclerc’s race simulation appear slower than it might be in race conditions. Still, Formula 1’s biggest-ever driver transfer (Lewis Hamilton to Scuderia Ferrari HP) remains an unknown quantity, with the seven-time world champion yet to complete a full race simulation for the Scuderia.
Even relative underdogs Mercedes showed flashes of potential, with George Russell setting the fastest overall testing lap at 1:29.545—just 0.021 seconds ahead of Verstappen.
With margins this tight, the role of AWS technology becomes even more crucial. F1 Insights powered by AWS will once again translate raw telemetry into comprehensible strategy breakdowns, performance trends, and near real-time visualizations that make the invisible visible.
In a sport defined by milliseconds, the computational power of AWS is doing more than just enhancing broadcasts—it’s fundamentally changing how Formula 1 tells its story. It is bringing fans closer to the technical battlefield than ever before.