Austrian Grand Prix

Behind the scenes in F1: a Grand Prix story, made possible by AWS

Every Formula 1 car has between 200 and 300 sensors that collect more than a million data points per second. Much of this data is collected and processed by Amazon Web Services and presented to the public via F1 Insights, with the aim of supporting Formula 1 in its global growth. We discuss the partnership between Formula 1 and the cloud computing giant with Adrian De Luca, Director of Cloud Acceleration at AWS.

by Massimo Ruberti and Glenda Mecaj

26 June 2026

6' min read

Translated by AI

Versione italiana

6' min read

Translated by AI

Versione italiana

Ever since the takeover in 2016, Liberty Media has charted a clear course: to transform Formula 1 into a truly global sport, reaching new audiences and new generations. It was precisely to accelerate this transition that the partnership with Amazon Web Services was launched in 2018. Thanks in part to AWS’s infrastructure, the face of motorsport has changed: today, 42 per cent of viewers are women – an all-time high in the world of sport – and 43 per cent are under 35. These figures are bringing us ever closer to the ultimate goal: reaching one billion fans by 2027.

Having a diverse audience presents a challenge for sports management: making Grand Prix races appealing to everyone is becoming increasingly complex. Indeed, fans have very different preferences when it comes to how they follow the race, with a divide between the more traditional audience, who prefer to watch the entire Grand Prix live on television, and the under-35s, who prefer to watch shorter clips of the race focusing on their favourite drivers: ‘In Formula 1 we have Louis Vuitton and many fashion brands , so there are fans who get excited about what the drivers or sponsors are wearing… There are even fans who don’t watch the race at all!”, reveals Adrian De Luca, Director of Cloud Acceleration at AWS.

This therefore turns the traditional perspective on its head: it is not the fans who follow the sport, but the sport itself that, in a sense, chases after the fans. This is achieved, for example, by focusing on circuits in countries with promising growth prospects, changing the rules to maintain competitive balance, or by improving the viewing experience of races, ‘democratising’ access to a sport that, in terms of its technical complexity, is usually the preserve of a select few. In this regard, F1 TV was created which, amongst its various features, allows viewers to watch targeted highlights and increases the focus on creating content for social media: “AWS not only supports the transmission of images but also how fans interact via F1 TV or the website”.

The narrative challenge of a Grand Prix and the opportunity identified by AWS

The main challenge in covering everything that happens on the track during a race weekend is that the action is spread over several kilometres, with battles taking place simultaneously at different points around the circuit. “When you look at motorsport, compared to a ball sport – such as football or basketball – the situation is very different. In a ball sport, for a broadcaster, the way the narrative is built is by following the ball. Formula 1 and motorsport are much more complex,” explains De Luca. “First of all, the race track is several kilometres long and there are 22 cars all racing on a very wide circuit. Unlike a ball sport, where the competition takes place in a single spot, in Formula 1 the competition unfolds in several places at the same time. There may be a battle between the first and second drivers, but at the same time something interesting may be happening between the sixth and seventh, or even further back.”

At an operational level, all of this is carried out with the understanding that the data must be transformed into a live television commentary that is accessible to all the different viewers of the Grand Prix.

Amidst this complexity, AWS saw an opportunity to use raw data to develop various technologies to predict when the most important moments on the track would occur and to visualise them for the public via F1 Insights, using analytical models, artificial intelligence and historical Formula 1 data.

AWS F1 Insights: from data to graphics during the Grand Prix

At the heart of AWS F1 Insights lies a highly complex data collection system, starting with the 200–300 sensors fitted to each single-seater, which, amongst other types of data, enable the collection of a vast amount of information, including speed and steering angle, to understand the car’s behaviour. Added to this is data sourced directly from the circuits, covering both timing and positioning, as well as historical data for every circuit that hosts Formula 1 races.

Since 2019, AWS has developed twenty-four different insights grouped into three broad categories, one of which is race strategy, where historical data is used to predict possible tyre management and pit stop decisions. One example is the Pit Strategy Battle Insight, in which analytical data is used to predict, with a certain level of confidence, the probability of success of an undercut – that is, the strategy that allows a driver to overtake a rival by making an early pit stop.

What goes on behind the scenes? Production and commentary on the race during the live TV broadcast

As soon as the race begins, the AWS systems automatically generate all the scheduled insights, but only some of these are selected by the producers at Formula 1’s headquarters in Biggin Hill to actually be broadcast. Given the vast amount of information collected, deciding what to show was becoming increasingly difficult. That is why Amazon Web Services developed Track Pulse, a visualisation system that allows producers to see, from a television production perspective, what is happening on the track and what is likely to happen next. All the information is displayed organised into different categories, allowing producers, if they wish to explore a particular story in more depth, to expand the category and provide further details.

This system not only supports the teams, but also the TV commentators: ‘As fans, we like to know the statistics: how many times has my favourite driver won on this circuit? In the past, a team of analysts would prepare a multi-page document containing all the statistics before every race. It was useful, but there was a huge amount of information to take in. Formula 1 races are highly unpredictable. If something unexpected happens, commentators don’t necessarily have that data to hand at that moment. That’s why Formula 1 StatBot was developed.” Using generative artificial intelligence, the model has been trained on all historical Formula 1 data and allows commentators to interact with the chatbot to quickly uncover interesting facts to share during the race.

Limitations on the use of F1 Insights and future prospects

Despite the great support provided by F1 Insights, there are still limitations when it comes to data management in Formula 1. In fact, of all the sensors fitted to the cars, the FIA only has access to forty data channels – including position, speed and steering angle – whilst the remainder are owned by the teams. As De Luca points out, drawing on his four years’ experience at Scuderia Ferrari, the teams use up to 200 sensors internally to monitor vital and highly confidential parameters. Due to this level of confidentiality, certain strategic information – such as a car’s fuel load – is not available: “Nobody knows; it’s a secret that every team wants to keep to itself.”

From the perspective of implementing AWS technologies to support regulatory decisions – for example, in the event of rule breaches during the Grand Prix – all the data underpinning F1 Insights is transmitted from the cars via low-frequency radio signals and GPS units installed along the circuit, but the GPS systems are not yet accurate enough to draw conclusions about rule breaches during the race and thus enable the stewards’ decisions to be automated.

To gradually overcome the limitations of GPS – including measuring how close the single-seaters are to the wall, particularly on street circuits such as the Monaco Grand Prix – AWS has created the ‘Close to the Wall’ insight using computer vision: ‘Using a high-definition, high-frame-rate camera at 60 frames per second, we feed the video into the system, track the car’s rear tyre in relation to the wall and measure the distance. This type of technology is being used more and more in Formula 1: not only does it help us identify interesting moments, but our hope is that it can also be used increasingly to govern and regulate the sport.”

The Austrian Grand Prix

If Formula 1 continues to hold such strong global appeal, it is also down to the stories of its protagonists, which are characterised by successes but also by difficult periods. Lewis Hamilton’s recent return to victory by Lewis Hamilton with Ferrari, two years on from his last win, has reignited fans’ enthusiasm and proved wrong those who feared the end of the British driver’s career. At the same time, the 2026 season is unfolding in an unexpected way: Andrea Kimi Antonelli currently leads the world championship standings, partly as a result of the crash in Barcelona. This convergence of events, combined with Ferrari’s technical resurgence, is creating a dual focus of media and sporting interest for Italia.

For the eighth round of the season, the World Championship heads to the Red Bull Ring for the Austrian Grand Prix. The weekend will follow the traditional format. On Friday, the first two free practice sessions are scheduled for 1.30 pm and 5.00 pm respectively. On Saturday, following the third free practice session scheduled for 12.30, qualifying will take place at 16.00 to determine the starting grid. The lights will go out for Sunday’s race at 15.00. The entire weekend will be broadcast live on Sky Sport F1, with qualifying and the race also available as a delayed broadcast on TV8 at 18.30.