Data Driving Formula 1 Racing to New Heights

What happens when a sport becomes so steeped in data analytics that it would be practically paralyzed without it? With big data increasingly becoming its digital backbone, Formula 1 Grand Prix racing is on the road to find out.

In addition to the fuel exhaust coming from the Formula 1 race cars, the sport is rich with another kind of exhaust: data exhaust. Every piece of data is of concern to these racing teams – from temperature, humidity, and other physical things both on the track and in the car, to race data including lap times, pit stops, and more.

In fact, F1 data use is now so refined that none of the action would ever happen without it, wrote NetApp Cloud Czar, Val Bercouvici in a recent article. From the stands, to the track, the entire sport is entrenched in using data analytics as the backbone of its evolution and continued existence.

One of the most important examples of how data is forging the future of the sport is how race tracks and the accompanying stands are built now days. In the past, it was left largely to nature to mold the various contours of the raceway. Many celebrated tracks enjoy this nature-induced design, however not all riders agree that being long-celebrated makes for a good race track. Nelson Piquet once described the famous Monaco street track as “riding a bicycle around your living room.”

Currently, tracks are designed using a plethora of rich graphical information systems (GIS) data in computer-aided design systems. Using high performance computers stuffed to the gills with data about every imaginable condition, Engineers can test for everything from driver (and crew) safety, comfort in the stands, and even advertising locations.

Data has changed the speed and efficiency of the race cars as well. Using computational flow dynamics and computer-aided manufacturing, the aerodynamics of the F1 race car has crossed a threshold of science that approaches on the bizarre. According to Bercouvici, the aerodynamic data and resulting automated computer models have evolved to such a degree that the down force generated in theses amazingly fast vehicles is strong enough to pin an F1 car to the ceiling if it were being driven upside down.

Upside down, or right side up, once the car is in action, telemetry data is being collected by the individual race teams, all of which is used towards the goal of shaving as much time off of the race performance as possible. Details about the equipment, the weather, the track, the elevation down to the car’s speed, its gearing during the race, brake pressure, and more. (note: an example of F1 telemetry data can be seen here)

All of this data is collected initially during practice runs and crunched into actionable information which they use to tune the vehicles before the race. From chassis tuning to determining fuel load and the strategy on which tires to use, data is being used to inform every decision.

Finally, when the race starts, the data collection and analysis doesn’t stop. Sensors monitor everything that can be monitored, and data is being fed into the pit wall, where race engineers are interpreting it. All told, the modern F1 car is equipped with about 130 sensors producing enough data in two hours to fill several telephone books.

Of course, F1 racing is ahead of most of the rest of the world when it comes to the data curve, but when you consider what the use of data has done for this sport, it’s hard not to marvel and wonder what it will do for the rest of the world. The competitive drive in Formula 1 isn’t too far removed from the competitive drive happening in enterprise today.

We look forward to seeing this evolution unfold before our eyes.

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