Estimated 1RM Trend

A 1RM estimate (e1RM) predicts the maximum single-rep load from a submaximal set's load and reps, using a rep-max formula. Two common ones:

• Epley: 1RM = load × (1 + reps/30)
• Brzycki: 1RM = load × 36 / (37 − reps)

Example (Epley): 100 kg × 5 reps → 100 × (1 + 5/30) = 100 × 1.167 ≈ 116.7 kg estimated 1RM.

The value of e1RM for the data layer is normalization: a set of 5×100 kg and a set of 10×85 kg become directly comparable strength outputs, so progress shows up as a rising e1RM trend even when set/rep schemes change across a program. Trending e1RM per main lift is a core kpis-strength for strength goals.

Accuracy notes:

• Formulas are most accurate in the ~1–10 rep range; beyond ~10–12 reps they drift and overestimate, because endurance, not maximal strength, becomes limiting.
• e1RM is sensitive to proximity to failure — a set at RIR 4 underestimates true 1RM. Take e1RM from sets near failure (low RIR) or interpret loosely (see rpe-rir-logging).
• Treat single-session e1RM as noisy; smooth it with a moving average and read the slope over weeks (see trend-vs-noise). Use a tested max (see one-rep-max-test) only periodically.

• Epley: 1RM = load × (1 + reps/30). Brzycki: 1RM = load × 36 / (37 − reps).
• Example: 100 kg × 5 ≈ 116.7 kg (Epley).
• Best accuracy in ~1–10 reps; overestimates at high reps.
• Sensitive to reps-in-reserve — take from near-failure sets for fidelity.
• Trend the smoothed e1RM slope, not single sessions.

• estimated-1rm — the underlying estimation methods and norms.
• personal-records — an all-time-high e1RM is a logged PR.
• trend-vs-noise — smooth e1RM before judging progress.
• kpis-strength — e1RM trend is a primary strength KPI.
• rpe-rir-logging — effort context for interpreting e1RM.