Six laps into the 2008 Monaco Grand Prix, Lewis Hamilton’s McLaren race car skidded on the rain-slicked pavement, bumped against a barrier, and blew out its right rear tire. At the time, Hamilton, a gifted, impatient driver and one of auto racing’s biggest stars, was in second place. A puncture is a serious setback in any Formula One competition. In Monaco, the most prestigious title on the schedule, it’s a disaster: The course is laid out on the principality’s twisting, hilly streets, rather than a purpose-built racetrack, so passing is nearly impossible, and ground lost is particularly hard to regain. The three-time Formula One champion Nelson Piquet once likened the race to “riding a bicycle around your living room.” Rain only compounds the challenge.
When Hamilton clipped the barrier, 13 members of the McLaren race team were sitting in a windowless control room in the English town of Woking, 900 miles away. Outside, herons stood in the manmade lake that laps at the curving glass facade of the McLaren Technology Centre. The men and women at the banks of monitors, dressed in the same black and white uniforms as their teammates at the track, included strategists, systems engineers, performance engineers, mechanical engineers, and IT specialists; dozens of others in the building were patched in as well. Many of the decisions about the car’s setup and management over the course of the race are made here, not at the track. The team now had less than 30 seconds, the time it would take Hamilton to ease his car into the pit area, to make a very important call.
In the weeks and days leading up to the race, McLaren engineers had been running thousands of simulations, testing components, configurations, settings, and strategies. After the race started, the simulations continued to run, their predictive power improving lap by lap as information from the track was fed in. That meant there was a recommendation in the system for exactly what happened—Hamilton needing a pit stop in the sixth lap in a drizzle expected to soon taper off. Just six seconds after Hamilton called in his flat, a note of panic in his voice, the race engineer got on the radio and calmly told the pit crew to ready a set of tires—not deep-treaded “full wets,” but intermediate tires that could grip drier pavement as well. At almost the same instant the team manager told the crew to pump in extra fuel.
Both decisions were calculated gambles: The extra gas would weigh the car down, and the intermediates wouldn’t perform quite as well in the rain, but Hamilton would be able to stay out on the track past the point when his competitors would need to refuel and change their tires, gaining ground on them when they did. Within 10 laps, Hamilton had climbed back to third place, and when the two drivers ahead of him had to pit, Hamilton took over the lead. He held it until the checkered flag. It was one of the most dramatic Monacos in memory, and Hamilton would go on to win that season’s Drivers’ Championship.
“It’s all probabilistic,” says Mark Williams, McLaren’s head of vehicle engineering. “Because the system is running races live in the background, you can say to it, ‘How am I going to beat the guy in front?’ It goes off and specifically looks at all the options that he could do and you could do and comes up with the best solution based on probabilistic analysis. You may or may not beat him, but the closest you’ll get to him is by doing this strategy.”
McLaren has long had a reputation as a data-obsessed racing operation. It makes the telemetry systems for all its Formula One competitors, along with the computerized engine control units for Formula One, IndyCar, and Nascar. When a McLaren car is on the track, more than 120 sensors transmit a torrent of information on tire pressure, torque, temperature, and downforce (the vertical pressure, vitally important in cornering, created by airflow over a moving object).