Hello Reader

You can now train with the same science-backed readiness system just validated in Scientific Reports. By tracking HRV, resting heart rate, and well-being together, Athletica helps you know when to push, when to hold, and when to rest—just like the world’s best endurance labs.

That’s exactly the readiness triad we’ve been operationalising in Athletica for years, built on Dan Plews’ PhD work and a long line of studies showing how autonomic markers and subjective status can steer daily training decisions.

What the study did—quickly:
​Twenty-eight experienced male cyclists were randomised for 40 days (9-day baseline + 31-day intervention) into three guidance models:

1. vmHRV only
2. vmHRV + well-being (sleep, fatigue, DOMS, stress)
3. vmHRV + well-being + resting HR

Each morning, athletes logged vmHRV and WB; some also captured RHR. The program told them whether to go High, Low, or Rest that day. Pre-/post- tests covered Pmax, 1-, 5-, and 20-min power.

How this maps to Athletica (and why we’ve gone this way)

From Dan Plews’ early investigations with HRV in elite endurance athletes, our stance has been simple: use autonomic signals and athlete perception to time the work. In Athletica today:

• We pull nocturnal HR and HRV from wearables (Garmin, Oura, Whoop, etc.) or morning measures.
• We layer in resting HR to stabilise interpretation and avoid HRV “saturation” problems at high fitness.
• We add semantic check-ins (post-exercise athlete comments) to capture what the athlete’s actually experiencing.

And crucially, as explained, our AI-Coach does not change your training load (yet). It advises. You’ll see clear, LLM-generated guidance—progress/push, use caution, or prioritise rest/recovery—that mirrors the study’s “High/Low/Rest” logic. Athletes and coaches remain in charge; the system provides context so decisions are made with fewer blind spots.

This advice-first approach is intentional. Adjusting load mechanically without athlete context risks eroding trust and missing nuance (travel, illness, life stress). Advisory intelligence lets you learn your own patterns while still benefiting from the science.

The physiology (in one paragraph)

vmHRV (typically RMSSD) reflects cardiac vagal modulation—the parasympathetic “recovery” arm. It’s sensitive to accumulated stress and adaptation. Resting HR trends help disambiguate HRV shifts (and reduce mathematical bias tied to average HR). Well-being captures the non-physiology noise and the “how do I actually feel?” signal that often precedes performance changes. The trio forms a cross-check: if all agree, green light; if they diverge, adjust intent and execution.

What coaches should do with this (today)

• Keep the triad tight: capture nocturnal HR/HRV, resting HR, and a 30-second check-in daily.
• Plan the work, time the work: set your week in Athletica, then let readiness time the hardest sessions.
• Watch the middle: most errors live between “go” and “stop.” “Use caution” days are ideal for aerobic development, recovery, technique, or shortened intervals—still productive, not destructive.

Reflect weekly: readiness trends + session outcomes beat any single metric. The learning loop is where you improve decision-making.

Closing note

It’s gratifying to see rigorous work land on what many coaches have felt and we’ve engineered toward: readiness is multimodal, and context is everything. The new paper confirms it in cyclists; Athletica puts it in your hands—every day—without adding complexity. Take a beat each morning, listen to your signals, and let the hard days count.

Best,

Paul

Paul Laursen, PhD

​​​​​​