Since its creation in 1950, Formula 1 has been considered the premier racing car championship. Each year, around twenty Grand Prix races are held at various locations around the world. In 2025, twenty drivers from ten teams will compete for the drivers' and constructors' championships, with Cadillac set to join as the eleventh team in 2026.

In today's rapidly changing world, data technologies are reshaping the Formula 1 landscape fundamentally. Data has indeed become a vital asset, enabling teams to maximise their cars' performance on the track.

Additionally, testing has been minimised over the last few decades, accompanied by strict budget caps. This has prompted teams to seek new performance gains more efficiently and to increasingly turn towards digital solutions, particularly data-driven ones.

In this article, we explore how data has reshaped the Formula 1 landscape.

Unlocking performance through real-time telemetry, historical datasets, and environmental analysis

Nowadays, Formula 1 cars are equipped with over 300 sensors located around the single-seat vehicle. This enables engineers to extract over 1.1 million data points per second. These datasets can then be quickly analysed by comparing them directly with previous data collected and stored since the creation of the F1 championship.

Furthermore, the pit crew also have access to real-time meteorological data, enabling them to anticipate weather changes, and adapt the car according to track conditions, such as the likelihood of rain and changes in grip.

These changes also benefit the drivers. The sensors help drivers to improve their performance by analysing data such as their reaction times at the start of a race and the pressure they apply when accelerating or braking.

Overall, the integration of real-time telemetry, historical datasets and environmental information has transformed Formula 1 into a sport where decisions are made with increasing precision and predictability. Engineers, strategists and drivers now rely on advanced analytics to optimise not only performance on race day, but also long-term development programmes.

Data-Driven Savings: Optimising F1 Operations

In addition to increasing the number of data sources for optimised analytics, data enables teams to simulate runs using advanced virtual technology. This allows them to test changes in real track conditions and reduce testing costs (e.g. fuel, track rental, logistics).

Also, since a Formula 1 car comprises between 14,000 and 16,000 parts, data is essential for optimising stock and operations. This allows a team to ensure that unnecessary parts are not produced in its factory. Conversely, it can organise the transport of specific parts to repair broken cars by quickly identifying the necessary components.

The data is also relevant for monitoring the quality of the parts and ensuring that the car is fit for purpose when it leaves the track. This means that the car is fully functional, reducing the risk of losing time in reverse situations.

Racing Within Limits: Using Data to Manage F1 Budgets and Avoid Penalties

As previously mentioned, budget caps were introduced in 2021 to prevent powerful teams from spending unlimited amounts on developing their cars, at a time when less powerful teams were struggling to survive the season with limited resources.

Thanks to data, teams have been able to optimise their use of resources and implement tools that allow them to monitor spending in line with financial regulations. This reduces the risk of fines. Teams are subject to penalties when they fail to comply with these regulations.

For example, in October 2022, the FIA announced that Red Bull Racing had breached the 2021 cost cap by overspending by approximately £1.86 million (around 1.6%). The FIA then imposed a sanction. Consequently, Red Bull was fined $7 million (£6.1 million).

From Analytics to AI: Designing the Next Generation of F1 Performance

Formula 1 is becoming increasingly data-driven, especially with the new regulations arriving in 2026. AI will notably have a greater impact, making it possible to build the perfect car for any track conditions. AI solutions, analyse and study every race scenario in real time to determine the most probable outcome.

Teams have recognised the potential of data-driven solutions and AI, and these technologies are now fully integrated into their strategies. Many teams have formed partnerships with IT organisations that extend beyond marketing. Google, for instance, is McLaren's technological partner, while Oracle plays a similar role with Red Bull Racing.

These partnerships will be increasingly important by 2025, when regulations will limit the use of wind tunnels and other traditional testing resources, while leaving AI-driven simulations untouched. This will allow teams to freely explore potential performance gains.

Data is crucial in reducing costs and risks, and in optimising performance. As well as organisations as a whole, teams must be involved in designing a data governance framework to prepare for the future of Formula 1 — a future that is more efficient, powerful and strategic.

However, the drivers — the human decision-makers — will always be at the helm. They interpret insights, make strategic decisions and guide the team using judgement and experience that cannot be replaced by data alone. While technology amplifies their capabilities, the ultimate direction is determined by human vision, intuition, and leadership.