Competitive skiing has been filmed for decades. But outside of elite teams, video has never truly been used to drive progression.
Today, three things are changing:
video is everywhere (smartphones, GoPros, drones)
AI can finally analyze movement in real time
athletes expect feedback instantly
A few weeks ago, we started testing RideLvL with ski instructors in Giant Slalom. We filmed dozens of runs and tested real-time feedback loops with athletes and coaches.
This time, we stepped into a Super-G, with a different audience: competitive athletes, coaches, and clubs. We captured 500+ race runs in real conditions and started testing real-time feedback loops with athletes and coaches.
Huge thanks to Esprit Racing (and to Laurent Moreau 🙏) for the invite and access to the race in safe and perfect filming conditions!
Product angle (UX + tech)
What we’re building is not just performance analysis. It’s a new way to interact with performance.
ultra simple UX → usable by coaches in seconds
live usage → during the session, not after
remote usage → same video can be easily shared and reused later for deeper feedback
Under the hood, we’ve started to integrate:
pose estimation
super slow-motion analysis
smart drawing tools
structured feedback layers
The goal is simple:
👉 make advanced analysis usable in real-world conditions for clubs, coaches and competitors
Concrete example
The feedback: “extend the arms forward and bring the elbows in to stay more compact and improve aerodynamic efficiency.”
Above is what this looks like in practice: a Super-G video run the way it looks in our coaching app.
And here below, the racer finishes his run. 30 seconds later, he’s watching it again with visual feedback, directly on the slope, through AR glasses.
“Immediate video feedback after a run - that’s a game changer.”
This trip confirmed what we strongly believe: video will become the default interface for progression in action sports. Just like GPS changed how runners train, video will change how athletes improve.
What’s next
We’re leaving Serre Chevalier with:
strong validation from athletes and coaches
new ideas for features (UX, live feedback, trajectory analysis)
and clear opportunities for partnerships with clubs and competitive ecosystems
It clarified where to push the analysis layer further. In competitive environments, precision matters.
We’re exploring more advanced approaches such as:
higher FPS capture for better temporal accuracy (recent mobiles go up to 120 FPS even in 4K)
deeper pose analysis across more frames
and 3D reconstruction to unlock more advanced insights
The goal is to go beyond visual feedback and start quantifying performance elements like:
center of gravity dynamics
balance and weight distribution
body angulation and alignment
trajectories
Next step: expanding our field tests to moguls and freestyle in Megève, to explore how RideLvL performs across different disciplines.
If this works, progression in action sports won’t look the same in a few years.
And yes, Luc Alphand slope was pure carving heaven ⛷️⛷️⛷️
