Score Logic

How Readiness and Sleep scores are calculated in Intervals Companion

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Readiness Score

The Readiness Score is a single daily number (0–100) reflecting how recovered and prepared your body is for training. It draws on overnight physiology, recent training load, and sleep quality, combining them into a weighted composite. Higher is better.

Labels: Excellent (85+), Good (70–84), Fair (60–69), Pay Attention (<60).

Components & Weights

When all data is available, five components contribute to the score. If any component's data is absent, its weight redistributes proportionally across the remaining components — so the score always reflects 100% of available information.

Component	Weight	What It Measures
HRV vs personal baseline	25%	Autonomic nervous system recovery
Sleep quality	30%	Duration + deep/REM stage ratios
Training Load Balance (TSB%)	20%	Fatigue as a percentage of fitness — ((CTL − ATL) / CTL) × 100
Sleeping HR vs baseline	15%	Cardiac recovery overnight
HRV 5-day trend	10%	Directional trajectory of HRV

A minimum data gate applies: at least one of HRV or sleeping HR, and a sleep measurement must be present, or the score returns no result at all.

After all component subscores are combined into a weighted sum, penalty modifiers are applied and the result is clamped to 0–100.

HRV vs Personal Baseline (25%)

Your current morning HRV (rMSSD or SDNN) is compared to your personal trimmed mean from the last 30 days. At least 7 days of history are required; without enough data, this component is omitted entirely. rMSSD and SDNN are maintained on separate baselines and are never cross-compared.

Ratio to personal baseline	Subscore
< 0.60×	0 — severely suppressed
0.60–0.80×	0–40 — notably below baseline
0.80–1.00×	40–80 — normal fluctuation
1.00–1.20×	80–100 — at or above baseline
> 1.20×	100

Baevsky Stress Index modifier

If Baevsky SI is available, it applies an additive adjustment to the HRV subscore. Two scales are supported depending on your calculation method setting:

Scale	Condition	Adjustment
Normal (raw SI, ~10–400+)	SI < 50	+8
	SI 50–100	0
	SI 100–200	−8
	SI > 200	−15
Sqrt (√SI, ~0–10+)	SI < 7	+8
	SI 7–10	0
	SI 10–14	−8
	SI > 14	−15

The Sqrt thresholds are the mathematical square roots of the normal thresholds.

Sleep Quality (30%)

This is the same sleep score computed independently (see the Sleep Score section below) and reused as a readiness component. If sleep stage data is available, it incorporates duration, deep sleep, and REM ratios. Without stage data, duration alone drives the score.

Training Load Balance (20%)

Uses TSB% = ((CTL − ATL) / CTL) × 100, sourced from Intervals.icu. Unlike raw TSB (CTL − ATL), this normalizes by fitness level — a −30% imbalance means the same thing whether the athlete's CTL is 50 or 150. Omitted when CTL or ATL is unavailable.

TSB% Range	Subscore
≥ +25%	100 — tapered / peaked
+10% to +25%	90–100 — fresh
0% to +10%	80–90 — easy week
−15% to 0%	70–80 — normal training
−30% to −15%	55–70 — hard training block
−50% to −30%	30–55 — functional overreaching
< −50%	20 — non-functional overreaching

Sleeping Heart Rate vs Baseline (15%)

Overnight resting HR is an inverted metric — lower relative to your baseline is better. With ≥7 days of history, your personal mean is used. Without sufficient history, an absolute scale (45 bpm = 100, 75 bpm = 0) acts as a fallback.

Ratio to personal baseline	Subscore
< 0.85×	100 — well below baseline, excellent recovery
0.85–1.00×	70–100
1.00–1.10×	40–70 — slightly elevated
1.10–1.25×	0–40 — poor recovery or possible illness
> 1.25×	0

HRV 5-Day Trend (10%)

A linear regression slope is calculated over the last 5 days of HRV values and normalized by the mean. Only declining trends are penalized — stable or rising HRV is always ideal.

Normalized slope	Subscore
≥ −1%/day	100 — stable or rising, ideal
−1% to −3%/day	55–100 — mild decline
−3% to −5%/day	25–55 — notable decline
< −5%/day	15 — sustained steep decline

Modifiers (Penalty Only)

After the weighted component sum is calculated, up to four modifiers apply additive penalties. Modifiers can only reduce the score — normal readings have no positive effect. They represent red-flag conditions that signal something is wrong, not qualities that make you more ready.

Modifier	Condition	Penalty
Breathing Disturbances	< 10 events/hr	0
	10–20 events/hr	−5
	20–35 events/hr	−12
	> 35 events/hr	−20
Blood Oxygen (SpO₂)	≥ 92%	0
	90–92%	−5
	88–90%	−10
	< 88%	−15
Training Ramp Rate	≤ 5	0
	5–7	−3
	7–10	−8
	> 10	−15
Wrist Temperature (deviation from norm)	≤ +1.0°C	0
	+1.0 to +1.5°C	−3
	+1.5 to +2.0°C	−6
	> +2.0°C	−10

In an extreme scenario, all four modifiers could stack to a combined −59 points — but this would require severe breathing disturbances, low blood oxygen, a steep training ramp, and elevated temperature simultaneously, which is precisely the situation where a dramatic score reduction is warranted.

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Sleep Score

The Sleep Score is a single nightly number (0–100) summarizing how restorative your sleep was. Two methods are available and can be selected in Settings. Both produce scores on the same label scale and both use the same dynamic weight redistribution — if a component's data is missing, the remaining weights normalize to 100%. Neither method applies post-score modifiers; all factors are weighted components.

Labels: Excellent (85+), Good (70–84), Fair (60–69), Pay Attention (<60).

Method 1: Stages + Restfulness

This method uses four components available from Apple HealthKit: total sleep, deep sleep, REM sleep, and restfulness. Three additional factors (sleep efficiency, latency, and timing) are not available from HealthKit, so their weight is redistributed across the four available components.

Component	Weight	Data Source
Total Sleep	35%	Total sleep duration
Deep Sleep	25%	Deep sleep as % of total stages
REM Sleep	25%	REM sleep as % of total stages
Restfulness	15%	Breathing disturbances, or awake time if unavailable

Total Sleep (35%) — U-shaped curve with oversleep taper

Hours	Subscore
< 5h	0–50 (linear)
5–6h	50–70
6–7h	70–85
7–9h	85–100 — optimal window
9–10h	100–85 — mild oversleep taper
10–11h	85–70
11h+	70 — floor

Deep Sleep (25%) — Scored against PSG norm of ~20% of total sleep

Deep sleep %	Subscore
< 5%	0–25
5–15%	25–80
15–20%	80–100
≥ 20%	100

REM Sleep (25%) — Targeting ~20% PSG norm; 15% is clinically low (→65)

REM sleep %	Subscore
< 5%	0–20
5–15%	20–65
15–20%	65–100
≥ 20%	100

Restfulness (15%)

Breathing disturbances data (events per hour) is preferred. If unavailable, awake time as a percentage of total sleep is used as a fallback.

Breathing disturbances (events/hr)	Subscore
< 5	100
5–10	80–100
10–20	50–80
20–35	20–50
35+	10

Awake time (% of total sleep — fallback)	Subscore
< 2%	100
2–5%	85–100
5–10%	60–85
10–15%	35–60
15%+	10–35

Method 2: Duration / Bedtime / Interruptions

A simpler three-factor formula that does not require sleep stage data. It adds bedtime timing as a scoring dimension, rewarding circadian-aligned sleep.

Component	Weight	Data Source
Duration	50%	Total sleep duration
Bedtime	30%	Sleep onset time
Interruptions	20%	Breathing disturbances, or awake time if unavailable

Duration (50%) — Flat optimal window (AASM 7–9h)

Hours	Subscore
< 4h	0–30
4–6h	30–70
6–7h	70–90
7–9h	100 — flat optimal
9–10h	85–100
10–11h	70–85
11h+	65 — floor

Bedtime (30%) — Sleep onset scored against a ~10pm circadian optimal

Hours before 6am are treated as late night (e.g. 1am is scored as late, not early morning).

Bedtime (sleep onset)	Subscore
Before 8pm	60 — unusually early
8–9:30pm	60–80
9:30–11pm	100 — optimal window
11pm–midnight	80–100
Midnight–1am	50–80
1–3am	10–50
After 3am	10

Interruptions (20%)

Uses the same scoring as Method 1's Restfulness component: breathing disturbances preferred, awake time as a percentage of sleep as a fallback.

Comparing the Two Methods

	Stages + Restfulness	Duration / Bedtime / Interruptions
Requires sleep stage data	Yes, for full score	No
Uses bedtime timing	No	Yes — 30% weight
Duration curve shape	Gradual ramp: 85→100 in 7–9h	Flat 100 across entire 7–9h window
Best for	Apple Watch users with sleep stage tracking	Users who want bedtime accountability