How F1 Teams Use Data to Guide Race Engineers
Explore how F1 teams leverage real-time data, AI, and advanced analytics to optimize race strategies and enhance performance on the track.
In Formula 1, success hinges on data. Each car generates 1.1 million data points per second from over 300 sensors, translating into 30 MB of telemetry per lap. This data helps race engineers make split-second decisions, from tire changes to fuel optimization, often deciding races by fractions of a second.
Key highlights:
- Real-Time Monitoring: Cars stream data to the pit wall in as little as 10 milliseconds.
- Driver and Car Insights: Sensors track everything - temperature, pressure, G-forces, and even driver vitals.
- Massive Data Processing: Teams process 4 TB of data per car per race and up to 50 TB weekly.
- AI and Predictive Analytics: Machine learning predicts tire wear, fuel use, and optimal strategies.
- Future Tech: 5G networks and IoT will further reduce latency and enhance decision-making.
Data isn't just a tool in F1 - it's the foundation of every race-winning strategy.
The Amazing Role Of Data, AI And Cloud In Formula 1
How F1 Cars Collect Data
Modern Formula 1 cars are like high-speed data hubs, packed with advanced sensors and monitoring systems. These systems work together to gather an enormous amount of information about the car's performance, helping teams make split-second decisions during races. Beneath the sleek exterior of an F1 car lies a network of technology that powers telemetry and biometric monitoring.
Sensors and Onboard Systems
Each F1 car is equipped with more than 250 sensors that monitor nearly every part of the vehicle. These sensors fall into three main categories: control, instrumentation, and monitoring. Christine Steven, Lead Electronics Development Engineer at Mercedes, explains:
"There are over 250 sensors on the car during an average race weekend, and these can be divided into three main categories: control, instrumentation, and monitoring. All of this delivers pressure temperature, inertial, and displacement data. These sensors are embedded into all systems on the car."
The McLaren TAG 320B ECU acts as the brain, integrating data from these sensors across the car. These sensors measure everything from basic metrics like temperature and pressure to more specialized data points.
- Temperature sensors keep tabs on tires, brakes, engine parts, and the airbox. For example, heat-sensitive brake stickers signal when airflow adjustments might be necessary.
- Pressure sensors monitor tires, fuel systems, and hydraulic components.
- Speed and acceleration sensors provide real-time performance data, while G-force sensors capture the physical stresses on both the car and driver.
Other specialized sensors include pitot tubes for airspeed, ultrasonic sensors for fluid flow, lasers for ground clearance, and damper potentiometers to measure suspension movement. The fuel flow sensor plays a key role in ensuring teams stay within fuel regulations while optimizing performance. Dual-axis sensors track braking and steering inputs simultaneously, offering engineers a detailed view of driver behavior.
Telemetry Systems
All this sensor data feeds into telemetry systems, which are essential for making real-time decisions during a race. Telemetry converts raw data into actionable insights for race engineers. Each car streams approximately 30 MB of data per lap, collecting up to 10,000 data points every second.
Evan Short explains:
"We generate data from a variety of sources. Primarily it's from sensors on the car itself, and those can be anything from measurements of physical quantities, like temperatures, pressures, torques, and speeds, right through to things like the operation of the system like the internal state of all sorts of things on the car, like the gearbox."
To ensure reliable data transmission, circuits are equipped with multiple antennae that maintain nearly 100% coverage, delivering data to the pit wall in just 2 milliseconds. McLaren Electronic Systems provides the standard Electronic Control Unit and antennae used by all teams. This data is not only sent to the pit wall but also forwarded to team factories, where additional engineers analyze it.
On average, teams generate around 4TB of data per car during a race, with weekly data processing reaching up to 40–50TB.
Driver Biometric Monitoring
F1 teams don’t just monitor the car - they also keep a close eye on the driver. Biometric sensors embedded in the driver’s gear track vital signs like heart rate and blood oxygen levels. This data is sent in real time to race control and medical teams.
Dr. Ian Roberts highlights why this is critical:
"We know that the monitoring of people is essential in terms of their medical care and drivers in incidents are no different. We would like to start monitoring and assessing them as soon as we possibly can. There are also times when the driver isn't immediately accessible to us, so if we can't see him or we're not actually next to him, there's limited information that we can get."
This biometric data serves two main purposes. First, it helps medical teams assess a driver’s condition in case of an accident. Second, teams are exploring how this data can improve driver comfort and performance during races. Since this information is highly sensitive, teams classify and handle it with care, ensuring compliance with FIA regulations.
Processing and Analyzing Real-Time Data
After collecting data efficiently, teams in Formula 1 face the critical task of processing and analyzing it in real time. F1 cars are equipped with sensors and telemetry systems that generate an overwhelming amount of information. For context, a single car produces 35 megabytes of raw telemetry data every 2-minute lap. Teams rely on advanced processing systems to turn this raw data into actionable insights that can influence race-day decisions.
Fast and accurate data processing is essential for making split-second decisions during races. Over the course of a race weekend, 160 terabytes of data are transmitted between the race circuit and the F1 Media and Technology Center. This immense data flow offers engineers both incredible opportunities and significant challenges.
Data Processing Centers
To handle the massive influx of information, F1 teams operate dual data processing setups. Trackside centers focus on real-time analysis during race weekends, while factory-based centers provide additional processing power and support for analyzing historical data.
Cloud-based platforms play a key role, enabling engineers to access and analyze both real-time and historical data seamlessly. McLaren, for example, has developed a data automation platform that consolidates data from multiple sources for use in pre-race, post-race, and back-office analysis. This processed data serves as the foundation for predictive models and advanced algorithms.
Machine Learning and Predictive Analytics
Machine learning and predictive analytics have revolutionized the way F1 teams interpret and use data. These technologies allow teams to predict tire wear, fuel consumption, and optimal pit stop timing based on live conditions. For instance, one team managed to cut their CFD simulation time by 80%, reducing processing time from 60 hours to just 12 hours, thanks to cloud computing and machine learning.
Aston Martin Aramco combines data on tires, weather, and track conditions using machine learning algorithms to refine their strategic decisions. Similarly, Visa Cash App RB employs AI to compete with precision measured in "hundreds and thousandths of a second", underscoring the importance of these tools in gaining even the smallest performance edge.
Dan Keyworth, McLaren's Director of Business Technology, highlights the power of AI:
"What AI allows us to do from a generative perspective is to actually game out more of those actual scenarios and go, 'What will happen?'"
Clare Lansley, Aston Martin Aramco's Chief Information Officer, adds:
"By adopting this tech, we are going to be able to free up multiple engineers so they can focus more acutely on car performance."
Visualization Tools for Engineers
F1 teams rely on sophisticated visualization tools to make sense of the millions of data points generated during a race. Dashboards, heat maps, and performance charts help engineers dive deep into car performance data and quickly interpret complex information. This data comes from approximately 300 sensors continuously streaming information from the car.
Secure telemetry systems stream this data to the pit wall, where it’s used for real-time decision-making. Many teams also use models - sometimes as simple as Excel spreadsheets - alongside advanced simulation platforms to prototype and predict performance outcomes. These tools allow teams to adapt their strategies on the fly during races.
Otmar Szafnauer, CEO and Team Principal of Aston Martin Cognizant Formula One, sums up the importance of data analysis in F1:
"Formula One teams have always been pioneers in analyzing data for a competitive advantage, especially when milliseconds mean the difference between pole position and starting somewhere in the middle of the pack".
How Teams Share Data Insights with Race Engineers
Building on the earlier discussion about sensor data collection and processing, the next crucial step in Formula 1 strategy is effectively communicating insights. Once data is processed, it must be translated into actionable guidance for race engineers. With F1 cars generating around 3 GB of telemetry data and 4 GB of logging per race, teams face the daunting task of filtering through thousands of data points to deliver only the most critical information for split-second decisions.
A variety of experts, from performance engineers to chief strategists, work together to sift through the data and pinpoint actionable insights. Race engineers play a pivotal role here, acting as the bridge between complex data analysis and the driver. Their job is to distill this information into clear, concise guidance that the driver can act on immediately.
Choosing the Most Important Information
F1 teams monitor over 4,000 ECU parameters during a race, but only a fraction of this data is relayed to race engineers. Sophisticated prioritization systems are used to ensure that only the most relevant information reaches them.
Stephen Watt, head of electronics for McLaren Racing, highlights the scale of this challenge:
"The car on the track is only the tip of the iceberg; teams are now heavily data driven"
Data prioritization typically revolves around three main factors: immediate safety concerns, performance optimization, and strategic opportunities. For example, tire wear data becomes critical if degradation exceeds expectations, while fuel consumption takes center stage in tightly contested races. Similarly, unexpected weather changes can quickly shift priorities.
Performance engineers focus on optimizing car setups, while chief strategists evaluate scenarios that might influence pit stop timing and tire strategies. The goal is to ensure that race engineers receive only the most actionable data, avoiding information overload.
Radio Communication Protocols
Once insights are prioritized, they must be communicated securely and efficiently. F1 teams rely on encrypted communication networks to ensure secure and reliable transmissions. However, the speed of data transfer can vary depending on race location. For instance, European races often achieve near-instantaneous transfers within 10 milliseconds, whereas flyaway races might experience delays of up to 300 milliseconds.
To provide a comprehensive picture, teams integrate telemetry, audio, and video feeds. This approach allows engineers to connect real-time data with visual observations of track conditions, competitor movements, and potential incidents. Race engineers receive this information through multiple channels, including live telemetry displays, predictive analytics, and direct updates from factory-based teams.
McLaren exemplifies the sophistication of modern F1 communication systems. The team processes and streams 100kHz of data per second to make real-time decisions. With such a massive data flow, careful filtering is essential to ensure that engineers focus only on the most relevant insights.
Real-Time Decision-Making
The ultimate test of data communication in F1 comes during high-pressure moments when split-second decisions can change the race outcome. Teams seamlessly integrate data analysis with strategy to maximize opportunities.
Zak Brown, CEO of McLaren Racing, underscores the importance of this integration:
"Splunk is very critical in both our on-track and off-track performance. You need to have both because if we're not competitive off track, we won't be competitive on track"
This approach highlights how data communication extends beyond telemetry to include broader performance analysis.
Modern F1 teams increasingly rely on factory-based control centers for complex decision-making. These centers offer advanced data analysis tools and a distraction-free environment, giving them an edge over trackside operations. The Team Content Delivery System has significantly reduced response times, cutting live connection delays from nine seconds to under five seconds. This improvement ensures faster reactions when every millisecond matters.
Chris Roberts, director of IT at Formula 1, explains:
"The team Content Delivery System will further evolve the ways teams consume and process key trackside data to support them in making faster and more informed decisions when they need it most"
In addition, automated systems now play a growing role in F1. These systems make real-time adjustments to car settings based on data, allowing race engineers to focus on higher-level strategies rather than routine tasks. By blending automation with human expertise, teams ensure that performance optimizations are implemented instantly, while complex scenarios are tackled with precision and insight.
The Future of Data in F1
Formula 1 is on the brink of a new era in data management, building on its already advanced real-time data systems. While teams currently process enormous amounts of information, emerging technologies are set to make this process faster and smarter. With tools like 5G, AI, and IoT, the way data is handled on and off the track is about to change dramatically.
5G and Faster Data Transmission
The shift from 4G to 5G is a game-changer for F1, promising speeds up to 100 times faster than 4G LTE and latency as low as 1 millisecond. These upgrades address current limitations, where wireless solutions top out at just 10–12 Mbps.
Some circuits are already testing 5G capabilities. For example, in 2025, NTT Com, Alps Alpine, and Sojitz Tech Innovation created a private 5G setup at Mobility Resort Motegi to test low-latency video streaming from fast-moving cars. Meanwhile, the stc Group rolled out a 5G network at the Jeddah Corniche Circuit for the FORMULA 1 STC SAUDI ARABIAN GRAND PRIX 2025.
In the U.S., T-Mobile showcased 5G during the 2024 FORMULA 1 HEINEKEN SILVER LAS VEGAS GRAND PRIX, enhancing fan experiences with features like immersive camera views and instant replays via the F1 Las Vegas app. They also used 5G network slicing to streamline event operations, including ticketing and transactions.
"At T-Mobile, we want to leverage our unique capabilities to help our partners find new ways to innovate. Building on the success of the inaugural Las Vegas Grand Prix race, we are shifting things into high gear this year to go even further, beyond event connectivity, to improve the fan experience and onsite operations during race weekend", said Mike Katz, President of Marketing, Strategy and Products, T-Mobile.
For teams, 5G's V2X (Vehicle-to-Everything) communication enables real-time hazard alerts, collision avoidance, and seamless data sharing between cars and track infrastructure. Additionally, it allows teams to access cloud-based tools instantly during races. With this connectivity in place, artificial intelligence is poised to take real-time decision-making to the next level.
AI-Assisted Race Engineering
Artificial intelligence is transforming how race engineers interpret and act on data. Teams like McLaren F1 already leverage machine learning to simulate thousands of scenarios, testing how configurations and parts affect car performance. This precision is crucial as recent championship battles have been decided by mere thousandths of a second.
Andrew McHutchon, Head of Data Science at McLaren, highlights AI's potential:
"Today, a Formula 1 car is built by our intelligence – but that means it's limited by human insight... AI is a potential way to extend that... It's a tool, and like any tool, it makes you stronger and able to do things you wouldn't otherwise be able to do – but instead of augmenting strength or dexterity, it augments our thinking. This allows us to unlock designs we would have never considered, and gain understanding from the car we otherwise would never have seen."
AI systems excel at analyzing vast amounts of data, from engine performance to tire wear and fuel consumption. These tools can recommend optimal pit stop strategies, simulate race scenarios, and even predict competitor strategies based on track conditions and driver behavior.
United Autosports has adopted AI through Valkyrie AI, which streamlines decisions about part replacements and analyzes race data to predict safety car deployments and yellow flags.
Rob Smedley, CEO of Smedley Group and former Ferrari and Williams engineer, explains:
"There's something like 3,000 different components, or different parameters that you can change on the car... you've got 7.4 billion computatorial effects of how you can set your car up."
AI is evolving rapidly, moving from answering specific questions to integrating diverse data sources, including telemetry, images, and audio. This broader approach gives teams a more complete understanding of performance.
"At McLaren we see there is a great future for AI in F1. It can easily become a Championship-decider", McHutchon adds.
But AI isn't the only technology reshaping the sport. The Internet of Things is also expanding what's possible on and off the track.
Expanding IoT in F1
The Internet of Things (IoT) is pushing the boundaries of F1's data capabilities, offering insights that go beyond traditional telemetry. IoT advancements are enabling real-time analytics, predictive maintenance, and enhanced driver performance monitoring.
Teams like Mercedes-AMG Petronas and Red Bull Racing are leading the charge with advanced simulators. These systems use both historical and real-time data to prepare drivers for specific circuits without risking tire wear or vehicle damage. Engineers can also study how cars respond to various weather conditions and configurations.
James Allison, Technical Director of Mercedes, emphasizes this comprehensive approach:
"The Formula 1 racing calendar requires a feat of human performance, race operations and logistics like no other... We wish to measure and optimize every aspect of how our engineers and drivers operate across multiple time zones, as well as how we manage a large number of off-car devices and equipment to give us the best chance of on-track success."
IoT sensors are revolutionizing predictive maintenance by identifying wear on critical components before failures occur. This prevents costly mechanical issues during races. Additionally, IoT enables advanced driver monitoring, tracking physical conditions to prevent fatigue or health risks.
Lewis Hamilton, driver for Mercedes, sees immense potential in IoT:
"Formula 1 is all about new technologies and pushing the boundaries as far as we can; that's what I love about the sport... The 'Internet of Things' has the potential to bring huge competitive advantages to our team's operations, and change how fans experience the sport too. That's what makes it so exciting. I can't wait to see the ideas from fans for this challenge."
With 5G and satellite connectivity, IoT is maximizing data usage on the track. It also enhances fan engagement through apps and wearables, offering unprecedented access to race data and driver stats. From simulators replicating real race conditions to sensors tracking every detail, IoT is reshaping F1 in ways that will define its future.
Conclusion: Data as the Foundation of F1 Success
Formula 1 has evolved from a sport reliant on instinct to one dominated by precision and data. Modern F1 cars generate an astonishing 3 GB of telemetry data per race, creating a wealth of information that drives strategic decisions on and off the track.
Each week, teams handle 40–50 TB of data and transmit 160 TB during a race weekend. This immense stream of information equips race engineers with the tools to make critical, split-second decisions that often define the outcome of a race.
Christian Horner, CEO of Oracle Red Bull Racing, captures this transformation perfectly:
"Data is in the team's lifeblood. Every element of performance – how we run a race, how we develop a car, how we select and analyze drivers – it's all driven by data."
This reliance on data has led to groundbreaking achievements, from record-setting pit stops to race-winning strategies. These results stem from exhaustive analysis of practice sessions, simulations, and real-time data. Zack Brown, managing director of McLaren, highlights the importance of focusing on quality over sheer volume:
"I think where Alteryx helps us … is it's one thing to get data, it's another thing to amalgamate it, get it quickly, and get the most relevant data. Otherwise, it's just a lot of noise. The more accurate data you have, the more different types of data … the better your decision-making can be."
A great example of data's power is Mercedes' perfectly executed pit stop for Lewis Hamilton during the 2019 British Grand Prix. By analyzing tire wear, fuel levels, and competitor positions in real time, engineers crafted a strategy that turned raw data into a race-winning decision.
The level of sophistication continues to rise. For instance, Oracle Red Bull Racing runs 1 billion simulations before each race, while McLaren collects over 200 million data points by the end of race day. This computational power allows teams to anticipate scenarios, fine-tune performance, and avoid mechanical issues. As Ed Green, Head of Commercial Technology at McLaren Racing, puts it:
"You're only going to find those tenths of seconds by really searching through the data."
This blend of real-time analysis and strategic planning has reshaped Formula 1. With advancements like 5G, artificial intelligence, and IoT, the sport is set to push boundaries even further. Today, 1.1 million telemetry data points per second flow seamlessly from the car to the pit wall, enabling decisions where milliseconds can mean the difference between pole position and missed opportunities. In modern Formula 1, data isn't just an asset – it's the very foundation of success.
FAQs
How do F1 teams keep car-to-pit data secure and reliable during a race?
Formula 1 teams lean on cutting-edge technology to keep the data shared between the car and pit wall both secure and dependable. They use end-to-end encryption to safeguard sensitive information, ensuring that only authorized parties can access it and that the data remains intact. Additionally, teams communicate over specific frequencies to prevent interference and maintain a steady flow of information.
To tighten security even further, they deploy intrusion detection systems that actively monitor for any unusual or unauthorized activity. The FIA also plays a crucial role by overseeing data transmissions during races, adding another layer of oversight and ensuring teams stick to strict guidelines. Thanks to these robust measures, teams can confidently make split-second decisions, knowing their data is both protected and precise.
How do F1 teams use artificial intelligence to improve race strategies?
Artificial intelligence (AI) is reshaping the way Formula 1 teams operate, giving them the tools to make quicker and more informed decisions during races. With the ability to process huge amounts of data in real time, AI enables teams to simulate race scenarios and fine-tune strategies for pit stops, tire choices, and overall race performance.
Through predictive analytics, AI helps teams pinpoint the perfect timing for crucial actions like pit stops and tire changes, minimizing mistakes that could cost precious seconds. As Formula 1 continues to push the boundaries of technology, AI has become a key player in crafting strategies that can swiftly adapt to the unpredictable nature of racing.
How will 5G technology change the way F1 teams use data during races?
The introduction of 5G technology is set to transform the way Formula 1 teams operate on race day. Thanks to its lightning-fast speeds and minimal delay, 5G allows teams to transmit huge amounts of telemetry data from the car to the pit crew in real time. This means race engineers can quickly assess critical factors like track conditions, tire degradation, and fuel usage, enabling them to make swift, informed decisions that could change the course of a race.
Beyond data transmission, 5G also improves communication between drivers and engineers. It allows for precise, real-time adjustments to car settings and race strategies, ensuring teams can adapt seamlessly to the ever-changing demands of the track. In the high-stakes environment of Formula 1, this enhanced connectivity could be the key to gaining an edge over the competition.