How Bryson DeChambeau Uses Deep Learning to Analyze Every Swing
Bryson DeChambeau employs a Google Cloud system that runs deep learning algorithms on proprietary 2D and 3D models. The system tracks over 30 key body points plus club and ball positions during top of swing, impact, follow-through, and finish phases. It records shot outcomes to quantify performance at each stage.
This approach shows users how to replace subjective feel with measurable kinematic data. Athletes and coaches can adopt quantitative tracking to refine technique instead of relying on memory or video review alone. The method turns practice sessions into structured experiments with repeatable metrics.
Bryson DeChambeau collaborates with Google Cloud on this motion analysis platform. Early tests have produced measurable improvements in swing consistency and club path accuracy.
Step 1: Open Google Cloud Vertex AI at https://cloud.google.com/vertex-ai and upload swing video footage. Step 2: Apply the Pose Detection model to extract 30-plus body keypoints across swing phases. Step 3: Review the generated kinematic report to identify deviations from target metrics and adjust technique accordingly.