I grew up playing tennis competitively, and two years ago, before two kids, I was still pretty good (9 UTR). I’ve been getting back into it, but I wish I had a world-class coach telling me what to work on. But good coaches are expensive, selective, and hard to find, whereas models are cheap, available, and should be already good enough. So clearly, @nicochristie and I needed to explore what's possible.
We chained open-source models post-trained on tennis. This cut each broadcast down to live play, found and tracked the players, ball, court, and labeled every stroke with its type and a 65-joint skeleton. We then post-processed this data into 30+ biomechanical traits across serves, forehands and backhands, normalized for each player’s build and the camera.
This included the goat @DjokerNole, @carlosalcaraz, @DaniilMedwed, @FTiafoe, @AlexZverev, @BenShelton, @Taylor_Fritz97, @NickKyrgios, @AndreyRublev97, @janniksin, and @TommyPaul1.
Using the same pipeline, we then processed phone footage of myself and @phamrich_ (ex-D1, used to be >13 UTR) playing. Then we gave Claude all the measurements with a blank context.
What impressed me:
- Without being told, it found my weaker side (forehand) and Richard’s (backhand)
- It joined differences that looked separate into one root cause per stroke
- My own diagnosis of my forehand was wrong. Claude’s makes a lot more sense
What do you think? @bgtennisnation @paul_annacone @darren_cahill
Drop youtube links here if you want Coach Claude to give you tips
Everyday life
34 hours of tennis video turned into biomechanical coaching
Peter Wang and Nico Christie processed broadcasts of 11 ATP players and phone footage of themselves into 30+ biomechanical traits per stroke. Given the measurements with no context, Claude correctly identified weaker sides and root causes, acting as an expert coach.
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- Made with
- Claude, open-source models
- Role
- Neuroscientist, co-founder at Off Policy
- Posted







