// the science

No black box.
Real coefficients.

The shipping engine is transparent, rule-based autoregulation — grounded in established sports-science methods, and traceable from trigger to change. Here's what's under the hood, honestly.

The calculations

Methods, signals, and what they drive.

Method
Signal
What it drives
Load–velocity
0.83 m/s
VBT coefficients map bar speed to relative load for live load autoregulation.
Flight-time physics
38.4 cm
Jump height derived from flight time captured on-device.
RSI
2.41
Reactive Strength Index quantifies elastic, fast-twitch quality over time.
Readiness model
0–100
HRV, RHR, sleep and a subjective check-in into a single score.
Normalised scoring
rubric
A shared rubric compares cm, kg and seconds on one axis.
The adaptation principle

Rule-based today. Traceable always.

01 · READ

Compute readiness

Normalise wearable signals against each athlete's own baseline, blend with their check-in.

02 · DECIDE

Apply the rules

Adjust volume, intensity, rest and selection within the coach's program and paradigm.

03 · EXPLAIN

Cite the trigger

Every change is logged with the metric that caused it — visible to coach and athlete.

Shipping today
· Readiness scoring & rule-based daily adaptation
· Injury-aware substitution & NO-GRIND safeguard
· On-device pose estimation for VBT & jumps
· Loading paradigms, phases, schedule-fitting
On the roadmap
· Live wearable integrations in the production app
· ML-assisted adaptation atop the transparent base
· Squad leaderboards & cohort comparison
· Nutrition & recovery expansion

We won't imply a learning black box exists today. The transparent, rule-based engine is what ships — and it's what we think expert coaches should trust over vague “AI” claims.

Kick the tyres.

Bring your hardest questions about the methodology. We'd rather earn the expert buyer than impress the casual one.

Book a demo