Well, Actually: Bryson DeChambeau's Swing Is Now a Google Cloud Thesis Project
Bryson DeChambeau employs Google Cloud's deep learning system with proprietary 2D and 3D biomechanical models. The technology tracks over 30 body, club, and ball key points across shot phases from top of swing through follow-through and finish. Granular performance feedback results.
This teaches you that temporal segmentation of complex physical motion yields actionable insight. You need not accept 'feel' as your only diagnostic. Break any repetitive motion into discrete phases, measure each, and you will find your inefficiencies rather than guessing.
Bryson DeChambeau, professional golfer, in partnership with Google Cloud. The system uses deep learning with proprietary biomechanical models.
Step 1: Record your golf swing (or any repetitive motion) on your phone from face-on and down-the-line angles. Expected outcome: two videos, 5-10 seconds each. Step 2: Upload to a free pose estimation tool such as MoveNet via TensorFlow's web demo or a consumer app like OnForm. Expected outcome: skeletal overlay with joint tracking on your video. Step 3: Compare two swings side-by-side, noting where your lead arm, hip angle, or shaft position diverge at top of swing and impact. Expected outcome: one concrete mechanical discrepancy to address in practice.