Well, Actually, Your Golf Swing Is a Data Problem Now
Australian Golf Digest tested an AI swing analysis app developed over two years with input from a No. 1 ranked Golf Digest teacher and motion analysis experts. The author filmed one swing. In about one minute, the app returned scored assessments across multiple swing areas, not raw data. The app uses something called a neural network, which you could think of as a statistical pattern-matching engine that learns from thousands of swings.
This demonstrates the principle of scored abstraction, wherein complex biomechanical data is converted into actionable, comprehensible metrics. You should expect this in your own workflows: raw sensor or video data becomes useless without interpretive layers. The technique to adopt is identifying which metrics actually predict outcomes, rather than drowning in measurements you cannot act upon.
The unnamed app was developed by a company that spent two years building it, with consultation from a No. 1 ranked Golf Digest teacher and experts in motion analysis and coaching. Australian Golf Digest conducted the test.
Step 1: Record a 10-second video of yourself performing any repeatable motion, such as a tennis serve or a kettlebell swing, using your phone's slow-motion mode at 240 frames per second. Step 2: Upload this video to a consumer AI analysis tool such as SwingVision for tennis or OnForm for general movement, both of which offer free tiers with scored feedback. Step 3: Compare the app's numerical scores to one specific element you can self-identify, such as knee bend or arm position, and note whether the scoring aligns with your own observation of that element.