Slipstream Network

Driving Data Forward

In every professional motorsports paddock across the globe, engineers pour over data, studying monitors filled with large amounts of data.

This number-crunching and analysis is done in the name of performance, in the hopes of achieving the maximum on-track capabilities of both car and driver.

Chris Finch knows what it is like to analyze data to wring more speed out of the car. Finch, a veteran race engineer, has worked with the likes of Riley & Scott, Fernandez Racing, Dreyer & Reinbold Racing, and Schmidt Peterson Motorsports. He began his career as a data engineer, working on sports cars alongside legends like Bob Riley, and eventually worked his way up to the role of race engineer in Indy Lights, in which he was the end-user of the car’s telemetry.

“When I started, a service called Pi was just coming on and people were just starting to use data. There were others out there, but (Pi) was the big boy on the block,” said Finch.


Pi is a software package that allows teams to analyze various data points gathered from sensors mounted across the car. Though there were early software competitors, nearly all teams across professional motorsports now use Pi to study the data gathered from the car.

Finch credits the influence of Formula One technology on American teams for bringing the data technology stateside. “As Formula One developed it and started tapping into Pi’s capabilities, it bled over here into the United States,” said Finch.

The data gathered by the sensors on the car is transmitted via radio signals back to the pits for engineers to study. Engineers can also utilize a hardwire technique by plugging a long black cable, dubbed the “umbilical cord,” into the car to the download the information to computers on the timing stand.

The sensors gather information about everything from steering angle to throttle usage. Engineers calibrate the sensors to measure steering angle and throttle usage, among other metrics. The information is then sent to the car’s onboard computer.


The process seems simple, but converting the data to a usable format is a more complicated process.

“The sensor doesn’t know degrees, only bits and voltage changes,” said Finch. This makes the racing engineer’s job even trickier, requiring a level of translation that can be difficult to understand.

With this information at their fingertips, engineers are empowered to make better decisions in regards to car setup and driver performance. The crews have quantifiable information that shows what the driver is doing on the track, when they simply took the driver at their word before.

The data can show anything from fuel telemetry to how a driver responds to changes the crew makes to the car.

“There are a lot of nuances because in the end, the driver is still human,” said Finch. “Drivers will tell you they’re flat (on the throttle), and the data will tell you they’re not. That tells you, as a race engineer, that they are just breathing the throttle, not making a conscious record of it.” Intermixing the technical data with the conscious thoughts and feelings of the driver is why communication between driver and engineer is so critical to success on track.


Teams also use data as an educational tool, especially on the lower rungs of the motorsports ladder. Engineers can see how closely inexperienced drivers bring their cars to the edge of control, and what they can do to improve their pace, such as changing braking and acceleration points.

Engineers also take the data from the track to enhance their simulations, making them all the more prepared for the next time the car hits the course. By using the telemetry acquired from the car, the team’s simulation programs are bolstered with real-life data, allowing the team to be as prepared as possible before their car hits the track.

Despite the benefits of data in motorsports, Finch is quick to note that as beneficial as the information is, it isn’t the “end-all, be-all” of motorsports engineering.

“You have to use it as a potential predictor of what’s going to happen, but at the same time, you have to be forward thinking with what’s going to happen as the race engineer,” Finch said. “Sometimes you’re in tune with what the data says, but sometimes you work contrary to it.” Although data acquisition is an incredible tool, it is still a historical record of how the car performed in the past, not necessarily what it may do in its next on-track session.

Data acquisition in motorsports has come leaps and bounds in recent decades, but Finch believes that there will be ways for those within the sport to push the technological limit even more. To Finch, progress in data acquisition lies in making sensors and components lighter, while also collecting more data.

All this considered, Finch preaches that it is ultimately up to the engineers to analyze and implement the data.

“Just because we have more data, it doesn’t make us smarter.”

Michael Miller