The back room in the Infiniti Red Bull Racing garage at the Formula One U.S. Grand Prix looks more like a NASA mission control room than it does a garage.
There are more computer monitors than there are eyeballs in the room, where three days before the race, several engineers were already in their seats, running simulations and studying its stream of data.
If the weekend’s race was going to be anything like the Brazilian Grand Prix two years ago, they knew that they had to be prepared, as their performance could mean winning or losing a championship.
The data that the engineers were scouring over at the time was just a fraction of the hundreds of gigabytes of data produced from each car over race weekend – the exact number, a team secret.
What isn’t a secret, however, is the use of big data analytics in Formula One, a sport as technically demanding as building a rocket ship.
Race teams at the U.S. Grand Prix collected more than 243 terabytes of data earlier this month according to AT&T T +0.59%, a few terabytes more data than there are in the Library of Congress.
Using the data, teams are trying to predict where they’ll finish the race before it even starts, based off the data they’ve amassed over the season from their competition and from their own car.