Bryson DeChambeau Turns Motion Capture into a Training Algorithm
DeChambeau's system uses deep learning with proprietary 2D and 3D models. It tracks over 30 body, club, and ball keypoints and classifies swing phases such as top of swing, impact, follow-through, and finish. The output feeds performance metrics back to the player in real time.
Athletes move from subjective feel to objective kinematic data. Coaches replace video review with quantified joint angles and timing. Training plans shift from guesswork to iterative, model-driven adjustments.
Bryson DeChambeau partnered with Google Cloud to run these models during practice sessions. The collaboration produced swing diagnostics that DeChambeau publicly credits for distance gains and consistency improvements.
Step 1: Open Google Cloud Vision or MediaPipe Pose at https://cloud.google.com/vision and enable 3D pose detection. Step 2: Upload or stream swing footage so the model extracts 30-plus keypoints per frame. Step 3: Export the resulting joint-angle CSV and compare phase timing across sessions to identify the swing variable that most affects distance.