Well, Actually: One Golfer's Overengineered Swing Deserves the Cloud It Gets
Bryson DeChambeau has conscripted Google Cloud's deep learning apparatus to dissect his golf swing. The system deploys proprietary 2D and 3D models to track over 30 critical points across body, club, and ball. It parses four discrete swing phases: top of swing, impact, follow-through, and finish. Comprehensive shot-level analysis ensues.
This illustrates the principle of granular biomechanical decomposition. You need not accept aggregate performance metrics when constituent kinematic elements remain available for interrogation. Any repetitive physical skill, properly instrumented, yields to phase-based optimization rather than intuitive correction.
Bryson DeChambeau, professional golfer, in partnership with Google Cloud. The system described is his experimental training infrastructure.
Step 1: Open your smartphone's slow-motion video camera and record yourself performing any repetitive physical action (golf swing, tennis serve, typing posture) from a stable side angle. Step 2: Play back frame by frame and manually identify three distinct phases (preparation, execution, follow-through), noting one body position marker per phase. Step 3: Repeat recording after five minutes of deliberate adjustment to that single marker, comparing before and after side-by-side to verify observable change.