Readiness
Also known as: Recovery State, Pre-Training Wellness
The athlete's arrival state before training — how rested, sore, and mentally prepared you are when you walk in. Readiness is the third layer of Afitpilot's load model (alongside internal load and external load), capturing context that load metrics alone cannot.
Formula
Captured daily via the 5-axis Hooper-Mackinnon scale (sleep, soreness, fatigue, mood, stress). Sum of the five axes = Hooper Index.Example
Slept 5 hours, very sore from yesterday's squats, average mood, low stress, average fatigue: readiness scores 6/3/4/4/3 → Hooper Index 20 (mid-range; some recovery debt).
How Afitpilot Uses This
A short prompt (DailyReadinessPrompt) appears at the first authenticated app open of each calendar day. The athlete picks 1-7 on each axis or skips. We persist one document per UTC date — resubmissions overwrite. The coach drawer shows a 14-day drift chart; the athlete Profile view shows the same chart plus a per-day submission history. Missing days render as gaps, not zeros, so coaches can't mistake "didn't submit" for "feeling great."
Readiness in research and practice
| Who / Context | Value | Note |
|---|---|---|
| Most predictive items | Sleep, soreness, fatigue | If we trim the survey under drop-off pressure, these are the three to keep |
| Elite team sport | Daily wellness questionnaire is standard | Combined with HRV for objective + subjective coverage |
| HRV alternative | Objective but device-dependent | Self-coached app makes HRV a weak default; subjective Hooper is more universal |
| Coach use | Drift chart > daily value | A single Hooper score is noisy; the 14-day trend is the actionable signal |
Known Limitations
- •Self-reported. The same physiological state can produce different Hooper scores on different days depending on mood, attention, and recall.
- •Daily compliance is the real risk. A 5-question survey has measurable drop-off after 7-14 days of prompts, especially without a feedback loop the athlete cares about.
- •Readiness is not yet wired into plan adaptation — it's captured and visualised, but the LLM does not yet auto-modify a session based on a low Hooper morning. That's a future hook.
- •Hooper convention (1 = best, 7 = worst) is counter-intuitive on first read; we display values as-is so they're comparable to research norms, but it costs a moment of cognitive overhead per glance.
What We're Improving
Science Context
Readiness monitoring sits in the broader recovery / fatigue literature (Kellmann 2018, Saw et al. 2016). Subjective wellness scales correlate with objective recovery markers (HRV, salivary cortisol) at the group level but with substantial within-athlete noise. The practical upshot: readiness is descriptive, not diagnostic — it flags drift but does not by itself determine training prescription. We use it alongside AU and external-load metrics, not as a replacement.