Biomechanical Motion Capture Now Guides Swing Correction
Bryson DeChambeau partnered with Google Cloud to deploy a deep learning pipeline that tracks over 30 anatomical landmarks on the golfer, club, and ball in both 2D and 3D. The system labels each frame with swing phases such as top of backswing, impact, and follow-through, then returns quantitative feedback on posture and club path. The output is delivered through Google Cloud's Vertex AI endpoints for real-time coaching adjustments.
Athletes can replace subjective video review with measurable joint-angle and club-path metrics. This shifts training from feel-based repetition to data-driven micro-corrections that reduce injury risk and shave strokes. Coaches gain an objective baseline they can reference across sessions.
Bryson DeChambeau's camp has used the Google Cloud pipeline during practice rounds to refine driver launch angles, reporting improved consistency on tracked metrics.
Step 1: Upload swing footage to Google Cloud Storage at cloud.google.com/storage. Step 2: Run the Vertex AI Pose Estimation model to extract 30+ body and club keypoints per frame. Step 3: Export the labeled JSON to BigQuery and build a Looker dashboard that flags deviations from target joint angles.