When the first F1 race was held at Silverstone in 1950, ‘data’ consisted of an engineer holding up a board at the edge of the track with a time written on it.
These days, it’s a little different.
Of all the advancements Formula 1 has made in its 73-year lifetime, it is perhaps the harvesting and implementation of data that has come on the most.
While the likes of Senna, Prost, Lauda, Stewart and Fangio relied on how the car looked and felt, the current crop have an enormous amount of data they sift through on a race weekend, telling them exactly where they are slow and why.
“When I started racing, there was no data logging other than a person on the pitwall with a stopwatch,” says 1996 champion Damon Hill whose later career saw the start of the digital revolution. “My mum used to do the timing for me!”
Hill was speaking at an event held in Central London by AWS and chances are if you have ever watched a Formula 1 broadcast, those three letters will be familiar to you. AWS, or Amazon Web Services, came into the sport in 2018 and are the ones, alongside F1, behind the stats that viewers will see back home.
The man running that operation is also no stranger to life within the paddock.
“Guys like me, we have been so used to sitting on the pit wall and devouring all of this data to make decisions to make the cars go faster for many, many years,” said Rob Smedley, former Ferrari race engineer and Williams head of car performance and director of data systems at F1, now CEO at Smedley Group. “Now we build the platform in AWS and Formula 1 so that we can get the data and actually start unpacking things.
“For the past five, six years with AWS and Formula 1, we’ve been trying to delight and engage fans by using data.”
While Smedley’s role is now focused on the entertainment side of the sport, he has plenty of experience on the sporting side and his career coincides with F1’s technological boom.
“20, 30 years ago in Formula 1, we started to take simulation data and simulation methodologies and technology from NASA. Now, NASA comes to Formula 1,” he said. “That’s how far we’ve come over the last few years.”
The phrase no stone unturned is perhaps the most apt to sum up just how much data is digested by teams for a race weekend. Think of any kind of data point and there will be measurements, predictions, strategies and everything else based off of that. Deciding a Formula 1 stranger and car development is less guesswork and more eliminating possibilities until you find the absolute best option.
In the old days, finding the best option would come as a result of hundreds of hours of on-track testing, multiple different car designs that are manufactured and generally an ever-expanding bill to pay for all of it. Now, with on-track testing severely limited by the regulations, it is the digital world that teams rely on.
Aside from the rare track tests, the wind tunnel is perhaps the most ‘old fashioned’; equipment is still in use but with the championship winner limited to 28 runs per week, teams have to rely on other systems.
Computational fluid dynamics (CFD) is a hugely useful tool that allows teams to predict the airflow of a digital rendering, saving them an enormous amount in manufacturing bills. It is this invention that meant when Red Bull were handed a 10% reduction in wind tunnel time for breaching the cost cap, lead designer Adrian Newey was not too worried.
But after the many hours of data crunching in specifically designed supercomputers, then it is time for the race which is where Smedley’s team steps in.
“The teams have been working on data and analytics and simulation to prepare for the grand prix from going about six months out,” he says.
“The first thing you’ve got to work with, and our business is the same as any business is, what are your objectives? So what are the objectives of grand prix racing? Well, it’s fairly simple.
“The objective is that we start at the endpoint, which is the race win, and then we’ll work backwards from there.
“So you start from your objectives and then we start putting everything in place. The way that we do that is through analytics and simulation. Formula 1, without a doubt, especially on the team side, is some of the most advanced analytics and simulation on the planet.
“So what are the contributing components? What are the data sources that we look through when we’re trying to consider how to analyse the event before we actually get there?
“The first one is the most difficult one, the driver. Unfortunately, we still have drivers, the bane of my life in the last 10 years.
“Each driver is different, each driver has a different driving experience and a different driving style. So the engineers have to know how to set the cars up for their drivers.
“Then you’ve got the team performance. Your own individual team performance and if you have got limitations or you’ve got advantages. So we take all that into account as well and all that goes into the simulation.
“And then you start getting into the technical stuff, which is the tyre performance. The tyre performance is one of the most complex elements but also the biggest return on investment areas of Formula 1 technology, so the teams invest a huge amount into the tyre performance.
“After that, you’ve got rules and regulations. So like any business, we are regulated, and we have to work within the regulatory framework. Then you’ve got the vehicle performance itself.
“You’ve also got the track. So each and every track is a different type of track, you’ve got different altitudes, you’ve got different asphalt surfaces, different asphalt types, different curves, different corners. It’s a different challenge each and every time you go somewhere. Twinned with that is the weather which is constantly changing.”
But it’s one thing having all this data, it is another thing to use it to your advantage and Smedley explained there are two ways to do that.
“There’s two types of analysis that we do. The first one is forecasting, so that is a simulation, and then the second is the analysis itself.
“We use all sorts of different analytical methods. So we use traditional methods, stochastic methods, and deterministic methods, and we also overlay that with machine learning. So we’ve introduced a lot of artificial intelligence to the way that we analyse, we’re trying to predict things going forward.
“And what that does is it helps us to be able to forecast. So we have simulation models that the team will be working on and then we’ll follow the cars that actually go around the track, that feeds all of that data back into the models and makes the models more and more accurate.”
As to how that data is collected, that is another highly complicated process that enables information to be beamed back from sensors within the car to the company’s base in the UK, regardless of where the race is taking place.
“There’s all these sensors on the car and then that data is acquired, usually through a cam link into an electronics box.
“That data is then sent via RF [radio frequency] to an on-premises server, which will be in the team’s area. So the teams will carry their own IT equipment.
“That becomes their proprietary data and then from there, it gets spread out to lots of different clients. So you can imagine that’s coming in at real time and there’s a certain fidelity to that data.
“Then when the car stops, it’s downloaded from the car and there’s a higher fidelity to that data. So you end up with a much higher fidelity, much more accurate data set.
“And then that supersedes obviously the real time [data] from what the engineers look out. So the real time still exists there as a dataset but the engineers then switch to looking at the higher fidelity downloaded data.
“And then all of that data, all of those data sets then gets spread out to different clients. It goes to the regulator [the FIA] so that they can check whether or not you’re cheating, it goes to Formula 1 for entertainment purposes and then the team’s own it themselves.”
While downloaded data is going to be more accurate, the time needed to do that cannot be afforded during a race meaning, as is often the case in Formula 1, speed is key. Moments after a driver has exited a corner, that data will be back at base and Smedley’s team will run 10,000 to a million simulations all within the span of 15 seconds.
F1 then is far less of a guessing game then it was before. Instead of relying on hunches, hopes and suppositions, millions of simulations provide the teams with the knowledge of exactly what will happen and when making the race almost entirely predictable. Well that would be the case if it wasn’t for the flesh and bone part of an F1 car.
“Drivers, we’re not cyborgs just yet,” said Hill, who drove in F1 from 1992 to 1999. “But the information does become very useful. When I started in racing, we didn’t have any data logging at all there.
“So right back in the 1970s they were starting to do this. The potential has always been there but it only really came in about the time that I was getting into Formula 1.
“People had laptops but didn’t have the capacity to store that much data. The only thing that was around at the time was a psion. It was handheld and it was convenient enough to be able to download the data when the car came in but it was only 12kb.
“But you’ve got to start somewhere, haven’t you? They say that the computing power of the space capsule that went to the Moon had less memory and less capacity than the one of the early Motorola phones.”
So what does it mean these days to be a Formula 1 driver? The reality is the task that the likes of Fangio, Farina and then Stewart had to do was far different from what Alonso, Verstappen and Hamilton are tasked with these days.
“I got out at a time when I was beginning to feel redundant,” Hill said with a smile. “I was starting to think well what do I do? All these engineers have their computers so you could see what the car was doing.
“They could start to set the car up according to the information they’re getting and that’s my job. I prided myself on being able to fiddle with the roll bars and the springs and get the car to the right feel. Now you’re just telling them what to do.”
If there ever comes a day when Formula 1 decides to get rid of the driver altogether then the sport will truly have changed but with data being used more and more every year, there is no question that it has gone from being a rarely used gimmick to one of the most powerful tools in a team’s arsenal.