Formula, in Recovery

HRV Deload Trigger Formula

Heart Rate Variability (HRV) measured as morning supine rMSSD tracks autonomic recovery. A sustained drop indicates accumulated training stress + insufficient recovery. The Plews-Laursen rolling-average approach uses a 7-day window for baseline noise reduction, then triggers a deload when current value falls >1.5 SD below baseline for 3+ consecutive days. Single-day drops are noise; sustained drops are signal.

4 variables. Published May 14, 2026. By AI Fit Hub.

Education, not medical advice. The result comes only from the published formula and your inputs. How we check our formulas.

Formula

deload_trigger = (current_rMSSD < baseline_7d_avg − 1.5 × baseline_7d_SD)  AND
                  (consecutive_low_days ≥ 3)
   baseline_7d_avg = rolling 7-day mean of morning rMSSD
   baseline_7d_SD = rolling 7-day standard deviation

Variables

current_rMSSD

Today's morning rMSSD

Root Mean Square of Successive Differences between R-R intervals, measured supine within 5 min of waking. Unit: milliseconds. Higher = more parasympathetic activity = better autonomic recovery.

baseline_7d_avg

7-day rolling average

Mean rMSSD over the prior 7 days. Use rolling not fixed weekly to capture short-term acclimatization. Excluded: rest days, alcohol days, illness days (use forward fill).

baseline_7d_SD

7-day rolling standard deviation

Variability of rMSSD over prior 7 days. Athletes with higher day-to-day swings (younger, fitter) need a higher SD threshold; less variable populations (older, less trained) use 1.0 SD.

consecutive_low_days

Consecutive low days

Days in a row below the threshold. 3-day window per Plews & Laursen — 1 day is noise (poor sleep, large meal), 3+ days is signal.

Step by step

1

Establish baseline. Measure morning rMSSD for 14 days before applying the rule. Apps like HRV4Training or Elite HRV capture this from a phone camera or chest strap.

14-day average baseline = 58 ms, SD = 8 ms.
2

Set threshold = baseline_avg − 1.5 × baseline_SD.

Threshold = 58 − 1.5 × 8 = 46 ms.
3

Each morning, compare today's reading to threshold.

Mon 51 ms ✓, Tue 44 ms ✗, Wed 42 ms ✗, Thu 45 ms ✗ → 3 consecutive lows. DELOAD TRIGGER.
4

On deload trigger: reduce training volume 50% for 5-7 days. Keep intensity (single high-quality top set). Don't cut intensity entirely — that prolongs the autonomic suppression.

Normal week 16 sets/muscle → deload week 8 sets, top set still RPE 8.
5

Re-check after deload week. HRV should return to baseline. If still suppressed after 7 days, investigate non-training causes (illness, life stress, undereating).

Post-deload baseline restoration: rMSSD 55 ms (within 1 SD of 58 ms baseline). Resume normal volume.

Worked example

Intermediate lifter using morning HRV to detect overreaching

14-day baseline avg

58 ms rMSSD

14-day baseline SD

8 ms

Threshold

58 − 12 = 46 ms

Recent 3 days

44, 42, 45 ms

All 3 readings below 46 ms threshold → consecutive_low_days = 3 Trigger condition met: DELOAD WEEK

Schedule a 7-day deload starting today. Volume 50% of normal, intensity maintained on top sets. Re-measure HRV daily; expect baseline restoration by day 5-7. If HRV does not normalize, look upstream — sleep duration, calorie intake, life stress.

Common variations

Daily threshold variant: ESPN/sports-science groups use 1.0 SD (more sensitive) instead of 1.5 SD. Better for elite athletes whose baselines are stable; produces false positives in recreational populations.

Weekly average (smoothed) approach: compare 7-day rolling avg to 28-day rolling avg. Triggers when 7-day drops 5%+ below 28-day. Less reactive than the SD approach — good for endurance athletes in long blocks.

Reactive metrics combo: HRV + resting HR + perceived sleep quality. Two or more red signals trigger deload faster than HRV alone. Eatough et al. 2023 showed multi-metric beats single-metric.

App-based readiness scores (Garmin, Whoop, Oura) wrap this logic internally. Their thresholds differ; trust their score only if you've validated against your own rMSSD-from-camera baseline.

Run the numbers next

Cardio Resting Heart Rate Calculator
Assess cardiovascular fitness from your resting heart rate — how it rates for your age and sex, and the reading that rates Good.
Recovery Sleep Debt Calculator
Track 7 nights of sleep to calculate accumulated sleep debt with a recovery timeline and quality assessment.
Planning Junk Volume Detector
Junk volume detector: paste a multi-week CSV training log and identify sets that don't drive strength or hypertrophy.

Questions people ask next

What HRV drop should trigger a deload?

Trigger a deload when your morning rMSSD falls more than 1.5 standard deviations below your 7-day rolling baseline for 3 or more consecutive days. A single low day is noise from poor sleep or a large meal; three straight low days is signal. Less variable populations (older, less trained) can use a 1.0 SD threshold instead.

What is rMSSD and how do I measure it?

rMSSD is the Root Mean Square of Successive Differences between R-R intervals, measured supine within 5 minutes of waking, in milliseconds. Higher values mean more parasympathetic activity and better autonomic recovery. Apps like HRV4Training or Elite HRV capture it from a phone camera or chest strap.

How long should I track HRV before using the deload rule?

Measure morning rMSSD for 14 days to establish a baseline before applying the rule. From those readings, set your threshold as baseline average minus 1.5 x baseline SD (for example 58 − 1.5 x 8 = 46 ms).

What should a deload week look like after an HRV trigger?

Reduce training volume by about 50% for 5-7 days while keeping intensity on a single high-quality top set, for example going from 16 sets/muscle to 8 sets with a top set still at RPE 8. Do not cut intensity entirely, because that prolongs the autonomic suppression. Re-check HRV after the week and expect baseline restoration.

What if my HRV stays low even after a deload week?

If rMSSD has not returned to within 1 SD of baseline after the 7-day deload, look upstream at non-training causes such as sleep duration, calorie intake, illness, or life stress. The framework excludes alcohol days, illness days, and rest days from the baseline for this reason.

Sources

Plews & Laursen (2017). Heart rate variability and training intensity distribution in elite rowers. , International Journal of Sports Physiology and Performance — rolling-average methodology
Plews, Laursen, Stanley, Kilding & Buchheit (2013). Training adaptation and heart rate variability in elite endurance athletes: opening the door to effective monitoring. , Sports Medicine — foundational HRV-for-training review
Buchheit (2014). Monitoring training status with HR measures: do all roads lead to Rome? , Frontiers in Physiology — HR-based monitoring overview
Vesterinen, Häkkinen, Hynynen, Mikkola, Hokka & Nummela (2013). Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance runners. , Scandinavian Journal of Medicine & Science in Sports — recreational athlete validation