It’s Lights Out … analysing data… and Away We Go

With the Formula 1 (F1) season kicking off this weekend in Bahrain, and after guiltily binge watching season 3 of Netflix’s Drive to Survive, we couldn’t help but want to take a deeper look into how data is used in this incredibly popular motorsport.

Now, if you’re not a numbers man you soon will be after you discover how these F1 teams are utilising big data to reap even bigger rewards! In 1950, Guiseppe Farina cruised his, what we would now consider an extremely basic, Alfa Romeo race car across the finish line to secure the win in the very first F1 race.

A lot has certainly changed since that first race, from the design and look of the cars to the size of each team’s budget and even how the cars are raced. We wanted to figure out how data has aided this transformation and this is what we discovered …

71 years ago drivers’ decisions on track would make or break their race. Nowadays, the success or failure isn’t solely down to the driver’s decision making but instead the real time data analysis, car design and race strategy. One could even debate that the technological advances made now are as important, if not more, than the driver behind the wheel.

Since its inception, F1 has been at the forefront of technology and design in the automotive industry. Modern F1 cars have over 200 sensors which can gather and transmit over 3TB of data per race which is transmitted to teams trackside and back at HQ for analysis, but changes like this didn’t occur overnight.

It all began with stopwatches and chalkboards. I think back to the movie “Herbie Fully Loaded” when they turn an old Volkswagen beetle into a racecar using these simple tools. However, it was a movie after all and there was definitely a need for more advanced tools. Then came the first implementation of information systems and technologies into these cars — telemetry systems. These telemetry systems essentially operated by measuring and collecting data through sensors on the cars, converting it into electrical signals and then transmitting these signals via wire/wireless mediums to a receiver. The data collected helped drivers and crews to gain better insights into how the cars were performing during the race. Improvements to these systems were made again with the introduction of electronic systems in 1980. These systems could only hold a lap’s- worth of data … a mere drop in the ocean regarding total distance if you know anything about F1 racing… and so their research continued. These systems continued to develop, leading to the use of ‘burst’ telemetry which fired radio signals from the car to the garage during a race and finally the real time data streaming we have today!

Today the cars and drivers alike are fitted with sensors which constantly monitor and relay information. Information on speed, exhaust and tyre temperatures, oil and water levels, engine RPMs, G-force, drivers pulse, sweat levels and blood oxygen concentration is gathered continuously in real time.

But why, you might ask? Well, all of this information has multiple purposes and uses. This information helps give teams insights that would otherwise be invisible and inaccessible to the human eye, for example driver’s oxygen blood concentration helps inform decisions in the event of an accident. Perhaps on the less serious and morbid side of things, they are used entirely for winning purposes! The use of data and its transmission is paramount for the success of F1 teams and their drivers, as the slightest of changes in a car, which can be made due to feedback in data, can move cars from the back of the grid to podium challengers. The data is used to generate up-to-date race strategy and inform new car design.

Race Strategy

Data is collected by each team on every single aspect imaginable. Departments such as the engine, the chassis, the front wing and the tyres are all established and data is collected for analysis, hoping to maximise car performance when it comes to race time. However, there is a limited number of team members allowed trackside during a race, as a result only a certain amount of analysis can be made there. Through the use of cloud computing, data can be sent securely over long distances in split seconds. Consider for example a team racing in West Coast America with a HQ in the UK. It would only take teams 17 milliseconds to send their data back to base for analysis. Teams are looking for the slightest of differences and upgrades to give them an edge over their competitors. As a result, the security of this data is also integral. So secure, in fact, that even if a driver is to leave a team at the end of a season, they are isolated and cut out from any data analytics and strategic discussions. To us, this is too intense and ruthless, leading to driver’s losing motivation to be their best for their time remaining in that team. A prime example of this is Sebastian Vettel at Ferrari last season, as they head strategists kept the top secret information hidden from him.

Back to the data anyway, once it is analysed it is used to update race strategy which is then fed back via radio to the driver. Just as race engineers communicate how the car is performing according to their data, the drivers will also tell the engineers how it feels to them. Using both data and driver’s experience, judgements on when to do a pit stop and change tyres can be effectively made to improve lap times. Often, during a race you will hear a driver asking their race engineer to check various aspects of the car for damage. The advantage of this data analysis is that it highlights areas which can be hidden from the human eye and race engineers often tell their driver to pit stop if issues arise post-analysis. The engineer may even tell the driver to pull over and stop the car if they feel that the driver’s safety is at risk.

After doing more research and continuing our binge of Drive to Survive, we picked up some skeptical use of the data. The first of this suspicious data use we saw was between McLaren race strategists and driver, Carlos Sainz. We watched a conversation unfold where the data on of the other McLaren driver’s driving style was shared with Carlos. We felt a sense of unease watching it and questioned whether it was fair to do this. On one side of things we can understand the desire to have the two driver’s performing to their optimum. However, in this sport, it’s driving styles and tactics that are the only thing that separate one team’s driver from another. We believe that instead of copying one driver’s style, teams should look further into the data and manipulate it in order find the best braking zones and spots on the tracks to achieve success.

It’s all about speed in this sport. F1 racing is renowned for its lightning fast pit-stops which can lead to huge wins for teams by scraping milliseconds off their lap times, needless to say a lengthy pit stop could cost a driver his race. The importance of speed is seen in data transmission too, with delays often causing drivers to lose the race.

On that note of pit-stops, pit crews have even been fitted with biometric sensors and combined with video analysis teams can also learn how to save valuable time here!

New Car Design

Data analysis doesn’t simply end after the four wheels pass the checkered flag. The data collected is also used to review how the car performed and how it can be improved for the next race whilst also being used to redesign and re-engineer new cars. Information gathered by sensors coupled with CAD and finite element analysis is used to investigate the aerodynamics of different car profiles. Ultimately aiming to minimise drag resistance and improve performance.

Despite this huge technological resource, limitations exist. Engineers and human beings are still the forefront behind the innovations and design of the cars. They can only use the data to a certain extent and when gaps in their knowledge occur, we noticed spying on their rivals was the next best thing! This went as far as team Racing Point buying information off Mercedes relating to their season winning car’s components. Racing Point became the joke of the paddock being labelled the ‘Pink Mercedes’, but this joke stemmed from jealousy as Racing Point became one of the quickest teams. We found this method of spying and buying information sneaky but we can’t help but admit it was brilliant.

Pre-season testing also provides a data dive into what’s working and what’s not. Information is gathered on short pace, long pace, lap time, gap to ideal lap time, allowing teams to test their design and strategies.

We took a look at the Formula One website to see just how much data was collected by the company itself… it was endless! We narrowed down our investigation to the data gathered from the most recent events, the practice sessions on Friday 26th March for the Bahrain Grand Prix. Massive comparisons between cars were made by F1, highlighting where cars outperform each other and where they lie in terms of raw numbers. With the season just beginning, it’s impressive to see how much data has already been collected and how predictions are being made for the season that lies ahead.

Some of the data collected after Friday’s session included the following;

• Red Bull read the quickest after Friday, with both short and long pace being the best out of all cars but the gap to Mercedes is tight
• McLaren look slow on the slow and medium corners in comparison to their competitors, while it’s blisteringly quick on the straights to make up the gap. This analysis was confirmed by the McLaren drivers as they declared their discomfort in the car after their initial practice.
• The data this year suggests that there will be a much closer fight between all of the teams this year. After Mercedes’ domination over the last 7 years, it looks like they are now the underdog’s going into this season after the early performance of the Red Bull cars.
• For many of the other teams, they again have narrowed the gap to the top and look like they will be fighting for podium positions.All of this is music to the ears of F1 fans, as this season looks to be the most exciting for many years…

We think they may have information systems, technologies and data to thank… what do you think?

P.s. if you haven’t already watched Drive to Survive we would highly recommend it but don’t hold us accountable if your college work ends up taking a back seat :D

— Lando Norris’ biggest fans, Louise and James

References:

Intel. 2021. How Big Data And Analytics Power Formula 1. [online] Available at: <https://www.intel.co.uk/content/www/uk/en/it-management/cloud-analytic-hub/big-data-powers-f1.html> [Accessed 27 March 2021].

Stackify. 2021. What is Telemetry? How Telemetry Works, Benefits, and Tutorial. [online] Available at: <https://stackify.com/telemetry-tutorial/> [Accessed 27 March 2021].

SimScale. 2021. How to Optimize the Front Wing of an F1 Car With CFD | SimScale. [online] Available at: <https://www.simscale.com/blog/2016/10/front-wing-f1-car-optimize/> [Accessed 27 March 2021].

Formula 1® — The Official F1® Website. 2021. Ten fascinating facts about the very first F1 race. [online] Available at: <https://www.formula1.com/en/latest/features/2016/5/f1-first-race-1950-silverstone.html> [Accessed 27 March 2021].

Formula1.com. 2021. 5 things we learned from Friday practice for the 2021 Bahrain Grand Prix | Formula 1®. [online] Available at: <https://www.formula1.com/en/latest/article.5-things-we-learned-from-friday-practice-for-the-bahrain-grand-prix.2pZh7pAiR7PJQLTkmONPOx.html> [Accessed 27 March 2021].

Grupo MAPFRE Corporativo — Acerca de MAPFRE. 2021. Data analysis in Formula 1: the difference between victory and defeat — Grupo MAPFRE Corporativo — Acerca de MAPFRE. [online] Available at: <https://www.mapfre.com/en/insights/innovation/data-analysis-in-formula-1-the-difference-between-victory-and-defeat/> [Accessed 27 March 2021].