MotoGP is high-speed, high-tech motorcycle racing. The fastest riders in the world compete on specialized, purpose-built motorcycles from companies like Ducati, Honda, Yamaha on the world stage in this series, which is considered the most prestigious in the game. Riders reach incredible speeds on their machines up to 220 miles per hour, and races can go 350 turns with gravity-defying leaning that scrapes elbows and knees. This Grand Prix is for the toughest of the tough on the moto circuit. 

Behind the riders and the machinery is a boatload of data and technology; we’re talking massive amounts of data in numbers that make your head spin. As tech company Lenovo puts it, when it comes to MotoGP–a sport in which every millisecond counts–data can mean the difference between a first and last place finish. 

Lenovo and Italian motorbike manufacturer Ducati work hand in hand to create a champion racing team with information gathered by 50-plus sensors that track tire rotation, speed, grip, acceleration, and more. Motorcycle racing, at the highest echelon, has evolved way beyond just the machinery or even the skill of the rider. Without the technology, any team would be left in the dust. 

The data journey

In the past, the only way to evaluate the outer limits of what a motorbike could endure was to disassemble a crashed bike. Today, a multi-pronged approach to data collection takes that process up several notches. Every time a bike enters the pit garage, an in-person team and a crew from the Ducati Lenovo Remote Garage at Ducati’s headquarters in Bologna, Italy analyzes performance. 

No matter where the team is racing, data streams in from the motorbike sensors. Off-site engineers analyze information from the track, making tiny tweaks to the bike and its operation. That way, every qualifying lap may be reviewed and fine tuned for the best competitive outcomes. 

“We debrief after each session, aligning with the rider on the sections and corners in which we think that he can improve his performance,” says David Attisano, the data and performance analysis manager for Ducati Racing. “We review with the rider his maneuvers and what we can expect to improve and how. For example, if the data shows that the rider can brake two meters later than he is, that’s a huge distance in this race.” 

For the MotoGP series, Ducati has three different teams with a total of six riders. Each Ducati rider receives the data not just about his own ride but for all the other riders, so they can track what the other five are doing. That’s a giant amount of data.

“We can push each other to the limit because we can see what the other riders are doing and comparing, then we can highlight and suggest some changes in their riding style,” Attisano explains. 

Data leads to improvements for road bikes, too 

Per official MotoGP rules, the sensors can’t transmit the data while the bikes are in motion. As soon as the bike gets to the garage, the engineers download the data. From this point, the data analysis process begins. At this point, the partnership is especially critical as the servers are developed by Lenovo specifically for Ducati. On top of that, there are data signals created with a custom algorithm and simulating based on engineering knowledge about the bikes. The team can even create a detailed “digital twin” of the course that maps each twist and turn, using 200GB of data per circuit.

“If the rider tells us that the traction control is not working properly, our electronics engineers can adjust the ECU,” says Attisano. “In our competition, the human factor is very important. We rely on the data and the humans do the last mile to gain the result and to achieve victory.” 

Sure, data clearly plays a big part, but human interpretation is still a critical aspect to translate the results. Even those who know nothing of motorcycles can create algorithms or artificial intelligence to offer some hints or tips, but without input from the team, the data has no context. The technology, Attisano emphasizes, is intended to augment the capabilities of human beings, not to replace them. 

“The behavior of the bike is very complicated–it’s very difficult to understand if you have not studied it at university,” he says. “In our experience, the exchange of knowledge between engineers and data scientists is very important.” 

Ducati’s data collection on the competitive side feeds into the safety and reliability for all riders, including those who like to take their motorbike for a spin on any given Sunday; not just competitive situations. Every time the bike emerges from the pit at a MotoGP race, the engineers strive to be sure it’s in good form and safe for the rider. Every improvement via the data collected from 50 tiny sensors on each factory-made racing bike leads to a better ride for casual street riders, too.

 

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