Monotony and Strain: The Overtraining Signal Wearables Miss
ACWR catches load ramps but misses the shape of the training week. Monotony and strain fill the gap by flagging weeks without enough hard/easy variance.
EWMA vs Rolling ACWR: Why the Week-Boundary Math Lies
Rolling-average ACWR creates week-boundary artifacts. EWMA ACWR smooths the signal, handles missed sessions, and produces trend information that matches physiology.
RPE Calibration: Why Your 9 Is Someone Else's 7 (and Why It Matters)
Self-reported RPE drifts with fatigue, stress, and experience. Calibration against objective markers (velocity, RIR, recovery) catches the drift.
Adaptive Training Intelligence: The Load Signal Your Wearable Isn't Showing You
How per-muscle volume tolerance, recovery half-lives, and Bayesian load models translate raw wearable data into actionable training prescriptions.
What Is ACWR and Why Does It Matter for Training?
The acute-to-chronic workload ratio is the single best predictor of training-related injury. Here's what it measures, where the 0.8-1.3 sweet spot comes from, how Omnio calculates yours, and the mistakes that get people hurt.