After an explosive end to the season in 2021, which saw Max Verstappen beat Lewis Hamilton to the title on the last lap of the final race, Formula 1 is a sport on the rise.
The success of Netflix series Drive to survivewho over the past four years has offered fans a glimpse behind the curtain, has certainly played a significant role in the revival of the sport.
So has the emergence of Red Bull as a real challenger to Mercedes, a team that has dominated the grid in recent years, winning the constructors’ championship in each of the past eight seasons.
However, there is another less obvious reason why Formula 1 has captured the attention of so many several million new viewers (opens in a new tab) this season. And it has everything to do with data.
According to Rob Smedley, a Formula 1 legend now employed as a consulting engineer, new initiatives resulting from a partnership with Amazon Web Services (AWS) are helping to breathe new life into the viewing experience.
“On the pit wall, you are emotionally engaged in the race. We’re introducing tools and ideas that engage fans in this race and really communicate the danger,” Smedley said. Tech Radar Pro.
“With the amount of data we have in Formula 1, providing a cloud a partner like AWS really speeds up the system and allows us to bring data into the fans’ subconscious.
Deciphering Formula 1
One of the primary goals of the AWS collaboration is to help unpack the intricacies of F1 for everyone. While most sports are pretty straightforward to follow, even if they don’t pick up on the nuances, F1 requires a bit more background knowledge and may have suffered from its inscrutability.
“F1 is the most technologically advanced sport. But as a by-product, it is also the most complex from a strategic and tactical point of view,” Smedley explained.
“To understand what is really going through the single medium of video, even for someone like me, is nearly impossible.
Since partnering with AWS in 2018, F1 has devoted considerable energy and resources to developing new data-driven experiences for fans called F1 Insights. The general idea is to ensure that viewers are able to more effectively follow the small on-track developments, which come together to form a complete picture of a race.
Using a combination of in-race signals and historical data, F1 performs various on-the-fly calculations to provide insight into each driver’s pit stop strategy, tire degradation, likelihood of a and more. All of this information is presented to viewers in the form of simple graphics, which commentators can explain in more detail if necessary.
New for the 2022 season are additional data points that help explain the intricacies of qualifying, the race against the clock that determines starting grid positions for Sunday’s race. Given the pace and number of moving parts, qualifying can be a little tricky to follow, but F1 has rolled out new graphics that better highlight each team’s progress through the session.
Separately, AWS and F1 recently announced a full-scale launch archive migration project which saw the pair bring hundreds of thousands of hours of racing footage into a centralized system database. Although fans won’t have access to the footage library itself, the archive will likely serve as the basis for future F1 Insights.
Although there was initially some level of resistance from some quarters, as expected, the new data initiatives have been successful. Fans are asking for more and more, Smedley told us.
New car, new race
Another crucial way that data insights from the AWS partnership has informed fans’ viewing experience is on the track itself.
In 2017, F1 conducted an extensive survey to find out what fans were looking for the most and, presumably, why number of viewers (opens in a new tab) were in decline. The resounding conclusion: fans were hungry for closer, wheel-to-wheel racing.
The problem, Smedley told us, is that the top teams have been too good at optimizing aerodynamic efficiency, which in turn creates turbulent airflow behind the car. The consequence is that chasing riders cannot follow closely without losing downforce, with obvious ramifications for racing spectacle.
To redress the balance and meet fan expectations, the sport and its governing body, the FIA, have spent the past few years working on a major overhaul of stock car regulations and design.
“The DNA of Formula 1, at its heart, is excellence of man and machine, so the best teams and drivers should always win the races and the world championships. of the sport’s DNA,” Smedley said.
“However, what we want are very close battles, as we saw between Hamilton and Verstappen last season.”
The result of 7,500 simulations carried out in the AWS cloud, the 2022 car is equipped with a new ground effect floor, which modifies the aerodynamic profile to limit the amount of “dirty air” expelled rearward. The front fender and nose have also been redesigned, with the same goal in mind.
The 2021 car is estimated to have lost almost 50% of its downforce when it is less than a car length from the driver in front. With the new design, F1 management hoped to bring that number down to 18%, and the races so far this season are testament to their success.
“The key objective has always been for the cars to be able to follow closer together, and all the key metrics in terms of overtaking from the first races show it has been a resounding success,” Smedley said.
“It was a lesson in exactly how technology should be used; you identify a subject matter expert, set clear goals and bring the necessary technology. When it works like that, it’s a thing of beauty.
In its quest to translate data into new experiences for fans and optimize for races closer to the track, Formula 1 still has a lot to do.
“The potential for what F1 and AWS can do together is huge, absolutely huge,” Smedley told us. “We were able to make huge progress, but we are only a very small part of the way.”
One of the key benefits of the partnership so far has been the ability to significantly reduce the time and cost required to perform complex simulations that help refine the design of the F1 car.
Previously, it took around 40 hours to complete a full simulation, effectively placing a hard limit on the extent of year-over-year improvements. However, looking at the unique cloud attributes, AWS was able to reduce the simulation time to just six hours. And with new advances in computing, storage, and networking technologies, that time is set to fall even further.
Historically, the cost of computing has also provided an advantage to wealthier teams, who could afford to buy more capable hardware and therefore run more simulations based on the stock car design.
However, the maturation of cloud computing has been a game-changer, combined with a new sliding scale that limits the time teams can spend on simulation based on how well they are performing on track.
The expected result is that the performance gap between the best and worst teams will decrease over time, making races much less predictable and more variety on the podium.
“The cloud is the great equalizer because it democratizes computing power. It’s so much more affordable and available than on-premises,” Smedley added.
“The fact that technology is changing at such a rapid pace means that CapEx would be obsolete in two years. But the cloud is the leveler between the haves and the have-nots, as it is readily available and is getting cheaper and cheaper.