In March 2011, a sports scientist named Stafford Murray attended a Formula One preseason ritual in Barcelona. For the 12 Formula One teams, these so-called testing events are an opportunity to unveil new cars, try out new technology, and adapt to new racing regulations before the start of the world championship. For McLaren, one of the world’s premier F1 teams, it was also an opportunity for espionage.
As an accredited member of the McLaren team, Murray had access to the Pit Garages building, which had a view over the starting grid, the paddock, and the entire pit lane. He entered the building in his McLaren uniform and went up three floors to the main lounge. He changed into civilian clothes and stashed away his McLaren uniform, just in case he got caught. He then climbed the fire escape to the roof, furtively set up a camera tripod on the parapet just above the pit lane, and started recording.
Back then, McLaren had two former world champion drivers, Lewis Hamilton and Jenson Button, and was one of the main contenders for the championship. The British team was also renowned for its technological innovation. For, instance, it had been the first to develop a sort of Formula One mission control, a room in England from which race engineers could monitor a Grand Prix anywhere in the world and relay race strategy decisions in real time.
When Murray first visited the McLaren headquarters in Woking, south of London, he remembers being struck by the sophistication of mission control. The room had three banks of desks manned by 13 engineers. Several screens on the front wall showed live footage and telemetry feeds from races and practice sessions. One screen showed a map of the track and the location of the cars. Another graph plotted the cars’ position in a circle, making it easier to visualize distances between cars. The engineers watched the screens in silence, communicating between themselves via a secure chat channel. “Bloody hell,” Murray thought. “How can they make decisions from all this data? It’s too much.”
about the author
João Medeiros is features director of Wired UK.
But Murray quickly realized that, in fact, the last thing those engineers wanted was to make decisions, especially during the heat of a Grand Prix. All the data were fed into software running millions of simulations for different variables of the race: timings for pit stops, number of pit stops, different sets of tires, and so on. The output was what McLaren called a decision-support system, a predetermined plan for any possible scenario. And that was crucial to winning races, as evidenced by what happened on May 25, 2008, in the Monaco Grand Prix.
It was raining heavily, and the notoriously difficult Monaco circuit was slippery. The Brazilian Felipe Massa started in pole position, followed on the starting grid by Kimi Raikkonen and Hamilton, then a young McLaren pilot in his second season. For the first five laps, Massa maintained a small lead. On lap six, Hamilton hit a barrier and punctured a rear tire, forcing him to make a pit stop.
Immediately after hitting the wall in Monaco, Hamilton was given precise instructions over the internal audio feed: “Lewis, you’re coming into the pit. You make a change to the steering, the launch switch, make sure you’ve done that—[and] you’re going to get new tire and you’re going to get fuel.” Shortly after, he was told “bail out”—meaning his car would be fueled sufficiently to make it to the end of the race. Because there wouldn’t be any more pit stops.
A puncture at the Monaco Grand Prix, a circuit where it’s notoriously hard to overtake other cars, usually means the race is lost. But thanks to McLaren’s decision-support algorithms, the race engineers had a plan in place and were able to minimize the time lost.
The moment Hamilton hit the barrier, all 13 members of the pit crew already knew exactly what to do. The weather forecast indicated that the track was going to dry up, so they switched drier-condition tires along with refueling the car to last until the end of the race. The pit stop lasted nine seconds. As Hamilton exited the pit lane, he was told which drivers were behind and in front of him.
With more fuel in the tank than rivals, as well as tires better adapted for the track as it dried out, Hamilton went on to win the race—taking him to the top of the Drivers’ Championship. Later that year, Hamilton clinched the title, becoming the youngest-ever world champion, thanks to a team who saw an opportunity to win races in unexpected pit stops.
By 2011, pit stops had gained even more significance for Formula 1 teams in their relentless drive for marginal gains; most teams factored in two pits stops per race, depending on their strategy and how events was unfolding. Typically, the duration of a pit stop depended on how long it took to gas up the car. But in a raft of cost-cutting measures the previous season, the International Automobile Federation, Formula One’s governing body, banned midrace refueling. Now, the length of time a car was parked in the pit depended on how quickly four mechanics could change its tires.
That’s where McLaren had a problem: Its pit crew was too slow. So McLaren’s chief engineer, Dave Redding, contacted Stafford Murray. At the time, Murray was the leader of a team of more than 35 performance analysts and biomechanists who were working with Britain’s Olympic athletes as they prepared for the 2012 Olympic Games in London. Even though McLaren boasted some of the most talented engineers and mechanics in the business, who better than Murray to help it apply the science of athletic optimization to the lightning-fast process of unbolting wheels from race cars and putting on new ones? “They realized that their human performance science was terrible and asked for our help,” Murray says.
Redding wanted to know if it was possible to reduce McLaren’s average 4.5-second pit stop to 2.5 seconds. The first thing Murray had to work out was why rival pit crews were so much faster than McLaren’s. This is why in March 2011 he was climbing on roofs and standing on toilets at Barcelona’s Circuit de Catalunya covertly scouting McLaren’s competitors.
What Murray learned would lead him to an astounding insight about the importance of vision to the athletic performance of pit crews.
During a pit stop, a car enters the pit lane at speed and slows down to the mandated speed limit of about 50 mph to approach its team’s garage. Eventually it stops within the so-called pit box, which is clearly marked out on the lane by tough-wearing adhesive tape that indicates where the wheels should be positioned.
During his sleuthing that day, Murray obtained extensive recordings of Toro Rosso, Ferrari, Force India, and Red Bull’s pit stops. In analyzing the footage, Murray was struck by how most drivers—and Red Bull’s in particular—were consistently and accurately hitting their pit box marks. The McLaren cars, in comparison, seemed to always be either a few inches short or past its lane marks, which meant that the crew was wasting valuable time just dragging equipment and tires up to the car.
“If your engineer knows exactly where the car is going to stop, he can start reacting before the car actually stops,” Murray says. “The guy at the front can start attacking with the machine that lifts the car up. He can actually start approaching the car before it stops, because they’ve got confidence in where the car is going to be.”
The following day, over breakfast, Murray told Redding about his findings. Redding was taken aback and told Murray not to divulge the information to anyone, especially not to the drivers. Murray wasn’t quite sure why Redding was so reticent. He realized why that afternoon: The preseason testing wasn’t going according to plan. McLaren had been beset by a series of problems, from engine failure to lack of spare parts, and they were being outpaced by Red Bull on the track. Pundits were calling McLaren’s new car a “mess.” Pilots Hamilton and Button were vocal about their team’s predicament.
As he sat in the paddock, Murray was given a pair of headphones linked to the McLaren audio feed and heard a conversation taking place between Redding and Hamilton:
“Carry on. The car’s fine. Carry on,” Redding said.
“No, the car’s pulling to the left,” Hamilton replied.
“No, it isn’t. The data’s showing it’s fine. The car’s fine. Please carry on.”
“Hang on a minute—it is. I can feel it. I’m going to pull in.”
“Don’t pull in. The data’s fine.”
“Bollocks. The car’s pulling to the left. I’m going to pull in.”
Murray was taken aback by how little authority the engineers seemed to have over the drivers. It was now clear why telling the best drivers in the world that they were not being particularly accurate when they stopped their car in the pit was not going to be an easy conversation.
“They’re the guys driving around at 200 miles an hour and risking their lives every day,” Murray says. “Data is one thing, but data doesn’t show the feel of the car. It doesn’t represent the difficulty of driving the bloody thing.”
Of course, there was still the issue of the pit crew’s performance. When Murray met again with Redding and his team, he was bombarded with questions about what they had to do to improve their pit stop timings. Was it physical? Was it mental? Was it about nutrition? Jet lag? Actually, Murray told them, it’s probably about your visual behavior.
“At the beginning, I had no idea what the problem was,” Murray says. “But it was clear you can’t expect a mechanic to just drop what he’s doing with an engine and change a tire under pressure. They were spending millions of pounds in technology and engineering, trying to keep up with the competition, and the thing that was holding them back was the fact that they were asking these guys to do the equivalent of playing chess in 2.5 seconds.” To Murray, changing a tire quickly was a skill just like any other, and these men were going to have to be treated as athletes in their own right.
A tall, amicable man in his late thirties, who combines the no-nonsense manner of a sports coach with the academic enthusiasm of a scholar, Murray is widely considered to be one of the best performance analysts in the world. He has headed the performance analysis team at the English Institute of Sport since its inception in 2002.
The institute had been established in the aftermath of the 1996 Olympic Games in Atlanta, when Great Britain ranked only 36th in the medal table, finishing below countries like Algeria, Belgium, and Kazakhstan. That was their worst-ever result, a dismal performance labeled a national scandal by the British press. The government was compelled to intervene. Money was promised; a dedicated agency, UK Sport, was set up to distribute the funds, a vast proportion of which were sourced from National Lottery revenue.
As a result, national sporting centers were built, and athletes were able to train full time. This funding also supported, in 2002, the launch of UK Sport’s technology, science, and medicine arm, the English Institute of Sport. The goal of the institute is to apply sport science—in the form of coaches, physiologists, psychologists—to the UK’s national teams, a kind of a team behind the team that could help athletes and coaches improve performance in an objective, scientific way.
The investment had quick returns. In the Athens Olympic Games in 2004, Great Britain finished in 10th place. At Beijing in 2008, the country surprised the world by finishing in fourth place with a haul of 47 medals.
As a discipline, performance analysis is still a relatively new branch of sports science, so whenever Murray gives a talk about his work, he always includes a slide spelling out the definition: “A specialist discipline involving systematic observation of performance allowing the provision of objective statistical and visual feedback.”
Because, as it turns out, even experienced coaches are not as objective as they might like to believe. Murray would then cite a number of studies conducted in the late ’80s that showed that, for instance, during a match, international soccer coaches could recollect only 30 percent of the key factors that determined a successful performance.
Worse, 45 percent of what they could recall was simply wrong. Together, those studies shattered the belief that coaches had special expertise in accurately recalling and judging the critical elements of sports performance. In fact, it emerged that their decisions were being corrupted by the very same cognitive biases that affected any person with a brain: memory overload, subjective bias, halo effect, on and on.
As a performance analyst, Murray’s expertise lay in collecting objective data that would eliminate guesswork, opinion, and bias across a range of sports. His job was to find out what really happened, as opposed to what coaches thought had happened, often with the help of bespoke technology.
When UK Sport worked with British Cycling, for instance, it developed a timing system with defense company BAE Systems that used lasers and barcodes on the cyclists to give exact split times and velocity data. Bikes were fitted with instrumented cranks that captured force measurements, velocity, and acceleration using a system developed by McLaren. (Yes, that McLaren.)
Guided by UK Sport, the analysts at British Canoeing were using data-logging sensors developed by BAE Systems and McLaren to collect acceleration and power information. Biomechanists embedded with the track and field team had their Laveg laser guns, for calculating horizontal and vertical velocities in the triple jump and working out the optimal speeds before take-off.
Murray brought in Des Blackburn, a tae kwon do analyst, to help him run the McLaren project. When Murray and Blackburn met the pit crew at the McLaren Technology Centre, they had them do a few trial tire changes. In the first few runs, engineers pushed the car into the pit and stopped it right on the line. Then a test pilot drove the car into the grid at medium speed, and finally at normal speed.
The data on the pit crews were clear: Of the four mechanics acting as gun-men, the front left mechanic was consistently the fastest—he would get the job done in two seconds. The question was why.
To every member of the crew, typically around 20 strong, Murray gave visual tracking goggles that would continuously measure their point of gaze. They then performed hundreds of pit stops while Murray studied them. Murray’s team calculated percentages of how much time crew members spent looking at the car, the wheel, the nut, and at irrelevant environmental cues.
As expected, the difference between the fastest mechanic and the slowest mechanic came down to gaze patterns. As the car was coming into the pit stop, the slowest mechanics would typically be looking at the sky, at the ground, at their feet. In contrast, the fastest mechanic would be completely focused on the relevant cues—the tires and the wheel nuts. The problem was now clear: The pit crew was looking at the wrong things at the wrong time.
In 1992, a kinesiology professor at the University of Calgary named Joan Vickers conducted a study of the gaze patterns of golf players. She equipped a group of low and high handicap golfers with an eye-movement helmet and asked them to do consecutive putts from a distance of 10 feet. The best players, it turned out, applied a distinct gaze pattern: They fixed their eyes steadily on the ball before initiating the backswing and kept their gaze there for longer—approximately 300 milliseconds longer. They also fixed their gaze on the green after the ball was struck. In total, this period lasted for 2.5 seconds. Vickers would later call it the quiet eye period.
After this study, Vickers found similar results in other sports. For instance, when making a basketball free throw, the best players tended to focus on the front of the rim for about a second before initiating their shot. In soccer penalty kicks, the most effective players looked at the top corners of the net for about 900 milliseconds and then shifted their gaze to the ball during the run-up. The more complicated the task, the longer the quiet eye fixation. Elite athletes, on average, fixated their gaze earlier and held it on a target 62 percent longer than other the average athlete. “The eyes are part of the brain,” Vickers says. “They gave us a direct insight into the ability to perform.”
Vickers compares the quiet eye period to a GPS system for the brain, providing the maximum amount of visual information at the right time and allowing the brain to successfully coordinate limbs, body, and emotions. It was also, as she puts it, a “shortcut to expertise.” In 2000 she developed a training protocol for the quiet eye in basketball free-throw shooting. She tested it on a women’s basketball team that had a dismal free-throw percentage of 54 percent.
First, Vickers taught players about the concept of the quiet eye. The players also were shown videos of their own gaze and movement patterns, and videos of the quiet eye of an elite performer, frame by frame, to see if they could spot the differences. Then they were taught the following three-step routine:
Take your stance at the line with your head up and direct your gaze to the hoop. Bounce the ball three times, slowly repeating the phrase: “Nothing but net.”
Hold the ball in your shooting stance and maintain focus on a single location of the hoop for around 1.5 seconds. Keep your gaze stable on that location and repeat “sight, focus.” You may fixate on either the front, middle, or back rim.
Shoot quickly using a fluid motion. The ball should move through the center of your visual field, temporarily occluding the target.
Over two seasons, these players improved their free-throw ability so much that their final season accuracy of 76.6 percent was superior to the NBA average. “I thought people are going to think I’m crazy,” Vickers recalls. “You just don’t get a 20 percent improvement with elite athletes.”
This protocol could be applied to any sport. Stafford Murray himself already had conducted a few projects with Blackburn that involved training athletes’ quiet eye in shooting, squash, badminton, and tae kwon do. “It was fascinating, because before all the research had been done on static actions like putting and scoring a penalty,” Murray says. “In tae kwon do, we were looking at the sort of cues the players were using before a kick or a punch.”
In the abstract, skill acquisition experts break down the gaze patterns of quiet eye into three elements: tracking the object in space, aiming, and executing an action that interacts with the object. In the specific case of the pit crew, these different phases corresponded to the car entering the box, the car entering the box to the pneumatic gun-on, and the crucial moments from gun-on to gun-off.
Murray and Blackburn conducted a detailed a detailed analysis of quiet eye period of the front-left gunman, the fastest and most effective of the crew.
During the tracking stage, he would kneel low, rotating shoulders to face the car, level-headed, staring attentively as the car approached. By this point, his gun was already up and in the periphery of his vision. His focus wouldn’t deviate from the target. As the car entered the box—the aiming phase—the wheel nut became visible and he would shift his focus immediately to it, gun positioned in anticipation to intercept. Still kneeling, the man would then lean in and intercept the nut just before the car stopped. Then the execution: As the wheel came off and was replaced by a new one, he would screw the wheel nut as soon as possible and then signal with his hand: task completed. Two seconds.
On early 2012, Murray met again with Redding and McLaren’s pit crew to present his analysis. That season, the McLaren’s pit crew was already under criticism for a series of blunders that had seriously compromised the aspirations of their star drivers. At the Chinese Grand Prix, Button had lost nine seconds in a pit stop when he had been in pursuit of frontrunner Nico Rosberg. In Bahrain, the pit crew struggled to fit Hamilton’s left rear tire. One of the gunmen already had been relieved of his duties.
Murray told them that what separated the best athletes from the rest was this ability to control the gaze. Experts zeroed in on the correct information even when under the overwhelming pressure of a Formula One Grand Prix. And in the case of the pit crew, that focus should be on the nut and the wheel. Murray provided step-by-step instructions for what the pit crew should be doing in every phase as the car came into the pit lane, when the car entered the pit box, and when the car stopped. His final slide included a recommendation to make the wheel nuts impossible to miss: “PAINT NUTS ORANGE!!!”
Murray wrote a seven-page manual describing the results of the project, “Analysis of visual behavior during a pit stop,” and it was classed by McLaren as confidential intellectual property until 2015. The report said that the role of tire changer was almost a sport in itself, and so McLaren began auditioning people for the job.
“Previously, they used to just pick the four strongest guys,” Murray says. Now, using the new insights into performance, they were taught how to operate the wheel guns with maximum efficiency—which eye was dominant, which knee they should put forward. They were also taught how to twist and how to lunge and given workshops in mental rehearsal, hydration, and sleep hygiene to fight jet lag. “The pit crew were flying eight hours across the world, sleeping for four hours, and then working 18 hours,” he says.
In short, the pit crew was trained like a team of elite athletes. Soon, they were performing like one. That season, McLaren’s crew went on to set pit stop record times in Canada, Valencia, and Silverstone. On July 22, at the German Grand Prix in Hockenheim, they serviced Button’s car in just 2.31 seconds, breaking the record for the fastest pit stop in history.
Game Changers by João Medeiros is out now (Hardback, Little, Brown)
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