AI Jab Analysis Example: Real mmaGPT Output

Setup

Amateur boxer, eight months of training, uploaded a single 47-second bag round to mmaGPT. The footage shows continuous jab work, occasional 1-2 combinations, and one short flurry. The athlete asked for a defensive review with no specific focus area selected, so the system ran the default Defense > Stance > Mechanics > Tactics priority pass.

What mmaGPT observed

The system flagged a recurring rear-hand drift on jab retractions — the rear glove leaves the cheekbone on roughly 58% of retractions and stops at the collarbone. The drift averages 4 inches and is largest after the second jab in any double-jab sequence. Secondary issues include a small lead-shoulder pre-load and a lead-foot crossover when reaching for distance. The drill ladder returned was the tape-and-snap progression.

The full AI output

Exactly as the session returned it.

Corrections applied

1. Tape-and-snap drill for two sessions, both bag and mitt work.
2. Cap double-jabs at single jabs until the rear-hand reset is reliable.
3. Mirror jab between rounds for visual feedback on guard position.
4. Stance reset to a 45-degree angle to reduce squaring-up amplification.