In figure skating, the margin of error is razor sharp. Skaters can miss out on podiums by a few tenths of a point; a slight under-rotation, a scratchy landing, tiny details that are hard to see but easy to penalize. Skaters know those mistakes are hiding in plain sight; correcting them is the real challenge. That’s where an AI-powered app makes its entrance and American skater Andrew Torgashev has been utilizing it to the fullest.

To test the app, Torgashev performed the simplest quad jump (a jump with four revolutions), the toe loop. His execution looked clean, almost perfect. But AI caught what the human eye missed. He was a quarter of a rotation short, an error that would take off a few tenths from his score in competition.

Normally, spotting the difference between a fully rotated jump and a slightly under-rotated one would be near impossible in real time, but the app flagged it instantly. The app in question is OOFSkate, an AI-powered analytics tool built specifically for figure skaters.

All it needs is a phone camera, no sensors, no wearables, and no extra hardware. With just a quick capture, the app tracks a skater’s jump height, rotation speed, airtime, and even landing quality. It delivers real-time, actionable feedback, giving skaters the kind of insight that once required specialized equipment.

“Our vision for the system is to automate the technical calling of the sport. This manifests itself in a combination of using AI-assisted computer vision, but also the knowledge of figure skating, essentially taking out the stuff that should be judged without subjectivity,” said Jerry Lu, who built this system with his old college roommate Jacob Blindenbach.

The goal is simple: skaters focus on their performance, and the machine handles the technical details. Using it is just as easy. Mount your phone or tablet on a stand, hit record, and skate. The app tracks your movements in real time, maps the ideal body position for every jump or spin, and logs the same metrics judges rely on in competition.

“So if I’m Andrew Torgashev and I’m at Champs Camp [Winter Olympics bootcamp for US skaters] I can do a quad toe loop and can compare it against myself, along with all the other athletes that have executed this. ‘Am I spinning as well as Mikhail Shaidorov? Or a previous version of myself?”

Building state-of-the-art tech is never easy, but these roommates managed to crack a problem skaters have dealt with for years. So what’s next for them?

OOFSkate is keeping things realistic while aiming for widespread use

Both Lu and Blindenbach know that people don’t embrace change overnight. Take tennis’ Hawk-Eye system, for instance: the technology has been around for nearly two decades, yet Wimbledon only replaced human line judges with it last year.

And when it comes to the Olympics, existing partners like Omega are rolling out upgrades at their own slow pace. So for now, OOFSkate isn’t dreaming too far ahead.

The duo is tightening every bolt, and for now, their prime objective is perfecting the system so that it can serve athletes, judges, and even commentators as the skating world gears up for Milano-Cortina this February after they were requested by NBC to implement their technology in figure skating.

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“We don’t want to step on toes. When you go fully AI and take the human out of the loop, people generally get mad, and the results are poor,” said Blindenbach.

“We want to assist. If that’s jump height or rotation, or if someone under-rotates by a quarter, these are easy things to do with AI, relatively speaking, compared to trying to capture something artistic. That’s where we see ourselves.”

Backed by U.S. Figure Skating, OOFSkate has even partnered with reigning World and Grand Prix final champion Alysa Liu as well as Jason Brown to enhance the app.

With a clear vision in mind, the founders aren’t looking to make an impact at the upcoming Winter Games, but will they be able to in future Winter Games? Only time will tell.