§ 0 how to read this app

/calculator

The live 1RM calculator. Type a top-set (your heaviest set today) and read out estimated 1RM, plate-load, warmup ramp, and Prilepin volume — all from one screen.

/scores

Federation strength scores: DOTS, Wilks 2020, and IPF GoodLift computed in parallel from competition total + bodyweight + sex.

/rankings

Where your lift sits in selectable reference populations: competitive powerlifters, active gym-loggers (StrengthLevel users), or the ACFT baseline (US Army fitness standard, not a civilian baseline). Powerlifting mode also shows meet-history trajectory.

/nutrition

Energy and macros from goal (cut/maintain/bulk), activity level, and body data. The PLAN tab shows kcal + protein/carbs/fat; STRENGTH shows the per-lift retention curve over 12 weeks.

/method

This page. Formula provenance, citations, and what the abbreviations mean.

headline 1RM ≈ X kg ± Y %

The mean of seven 1RM formulas, rounded. ± is the spread between the highest and lowest formula — wider band, less certainty.

RPE

Rate of Perceived Exertion. 6 = easy, 10 = max effort. RPE 9 = "one rep left in the tank".

percentile

Rank inside the selected reference population. 70th percentile = higher than 70 % of that group — not 70 % of all humans. (No "all humans" mode exists, see /metod § 5.9.)

Other abbreviations. NPL = number of prescribed lifts per session. BW = bodyweight (kg). top-set = the heaviest working set of a session. PR = personal record. raw = no equipment beyond belt, sleeves, wraps; no bench shirt or squat suit.

frequently asked

Six questions LiftGauge answers with cited sources, not opinion. Long-form provenance follows in §1–§8.

What is DOTS, and why did the IPF replace Wilks with it?

DOTS (Dynamic Objective Team Scoring) is a strength-comparison coefficient by Konertz / BVDK 2019, adopted by the IPF as the raw-open standard from 2020+. It replaced Wilks after the Wilks formula was shown to skew systematically toward lighter lifters (Vanderburgh & Batterham 1999, PMID 10613442) — a problem documented across multiple federations. LiftGauge computes DOTS, Wilks 2020, and IPF GoodLift in parallel on /scores so you can see how the same total ranks under each system.

How accurate is Epley vs Brzycki for one-rep max?

Both are linear-ish approximations and disagree most at higher reps. At 5 reps the Epley estimate is typically within ~3 % of the actual 1RM for trained lifters; Brzycki tends to underestimate slightly past 6 reps. Validation: LeSuer et al. 1997 (J Strength Cond Res 11:211–213) tested seven 1RM equations across squat, bench, deadlift. LiftGauge shows all seven formulas (Epley, Brzycki, Lombardi, O'Conner, Wathan, Lander, Mayhew) with their spread surfaced — single-formula calculators hide the disagreement.

What dataset does LiftGauge's percentile rank use?

OpenPowerlifting public meet data (CC0 license, snapshot 2026-04). Approximately 141 000 raw-lifter records, segmented by sex, lift, IPF bodyweight class, age (per year, 15–80), and equipment. Schema: Name · Sex · Equipment · BodyweightKg · Age · Best3SquatKg · Best3BenchKg · Best3DeadliftKg · TotalKg · Date · Place. When a requested cohort cell has fewer than 30 lifters, the system widens (exact age → all ages → ±1 BW class → global) and shows the widening explicitly. Source: openpowerlifting.org.

Is the ACFT deadlift standard realistic for civilians?

The ACFT (Army Combat Fitness Test) deadlift uses a hex bar at 3 reps; LiftGauge converts to a conventional barbell 1RM using a 0.92 factor (Swinton, Lloyd, Keogh, Agouris 2011, PMID 21659894) and applies an age curve from NHANES 2011–2014 grip strength (CDC; Strand 2018, PMID 29653890) as a multi-joint strength proxy. This is a military fitness baseline, not a civilian baseline — Mission: Readiness 2009 (NBK202010) found 75 % of US 17–24-year-olds fail current Army recruitment standards. The mode is labelled "ACFT baseline" and a separate civilian-baseline build is documented but not yet shipped (see /method §5.9).

Why show seven 1RM formulas instead of one?

Because they disagree by 8–12 % at 5+ reps, and which one fits best depends on the lift, the lifter, and the rep range. Showing all seven plus a min/max spread surfaces the uncertainty instead of hiding it behind a false-precision single number. The mean of the seven is reported as the headline 1RM; the spread is reported as the ±%. Wider band, less certainty.

What is FFMI and what is the natural ceiling?

FFMI (Fat-Free Mass Index) = leanKg / height_m² + 6.1 × max(0, 1.8 − height_m). Class thresholds (untrained <18, ..., elite <26, exceptional ≥26) come from Kouri et al. 1995 (Clin J Sport Med 5:223–228, PMID 7496846), which identified a "natural ceiling" around 25 based on drug-tested lifters. The 1.8 m height correction normalises against a reference individual. LiftGauge displays FFMI alongside BMI-derived BF% and waist/height to triangulate body composition, since each metric misclassifies different populations.

§ 1 1RM formulas

Spread 8–12 % at rep-range 5+. Trust the band, not the point estimate.

Legend: w = load lifted (kg) · r = reps performed · e = Euler's number (≈ 2.718). 1@10 anchor: at one rep, RPE 10, w = 1RM.

1.1Epley

1RM = w · (1 + r/30)

1.2Brzycki

1RM = w · 36 / (37 − r)

1.3Lombardi

1RM = w · r^0.10

1.4O'Conner

1RM = w · (1 + 0.025 · r)

1.5Wathan

1RM = 100 · w / (48.8 + 53.8 · e^{−0.075 · r})

1.6Lander

1RM = 100 · w / (101.3 − 2.67123 · r)

1.7Mayhew

1RM = 100 · w / (52.2 + 41.9 · e^{−0.055 · r})

RPE → %1RM source: Tuchscherer, M. Reactive Training Manual (RTS Press, 2008). RPE-load chart reproduced on /protokoll. Anchor: 1@10 = 100 %.

§ 2 Prilepin's table

The active-row stamp on the table marks the zone matching your current /protokoll input intensity. NPL = number of prescribed lifts per session in that zone; range is the productive band.

Medvedyev, A.S. A System of Multi-Year Training in Weightlifting. Trans. Andrew Charniga Jr. Sportivny Press, 1986. § 3.2.

§ 3 federation coefficients

Three formulas, three different reference populations — which is why the same total produces three different ranks.

3.1DOTS

Konertz / BVDK 2019. Adopted by IPF as the raw-open standard from 2020+. Replaced Wilks in the raw-open competition class after the Wilks formula showed systematic skew toward lighter lifters (Vanderburgh & Batterham 1999).

3.2Wilks 2020

Wilks (1994), 2020-revision coefficients. Replaced by DOTS for raw in 2020-Q4. Kept for parity with old write-ups.

3.3IPF GL

IPF GoodLift 2020. Replaced IPF Points; raw and equipped tables differ — we expose raw open here.

§ 4 data attribution

openpowerlifting.org · CC0 · last percentile-snapshot bundled 2026-04. We do not show beginner / intermediate / advanced / elite badges. Use percentile or don't.

§ 5 cohort data — /jamfor

The /jamfor view aggregates openpowerlifting meet records into pre-computed cohort cells. The runtime never queries the network — the bundled snapshot lives in the service-worker cache after first load.

5.1Source

openpowerlifting.org public dataset. License: CC0. Schema: Name · Sex · Equipment · BodyweightKg · Age · Best3SquatKg · Best3BenchKg · Best3DeadliftKg · TotalKg · Date · Place.

5.2Build

—

5.3Snapshot

—

5.4Cohort axes

Sex (M/F) × Lift (squat/bench/deadlift/total) × BW class (IPF: M 53/59/66/74/83/93/105/120/120+; F 43/47/52/57/63/69/76/84/84+) × Age (individual years 15–80, or all-ages) × Equipment (raw / single-ply / multi-ply). Leave the age field blank for an age-agnostic comparison.

5.5Trajectory

Built from full lifters' meet histories (not limited to the 12-month window) — de-duped on Name + Sex + bodyweight-bucket. Shows real longitudinal progression: median months from first logged meet to current level, plus months to next 20 kg milestone. Cells with n < 30 are suppressed.

5.6Sparsity

Cohort widening hierarchy: exact year → all ages → ±1 BW class → global. If the requested age + BW class + equipment combination has fewer than 30 lifters in the dataset, the system widens the comparison group until the sample is statistically meaningful. Widening is shown explicitly in the source-row label.

5.7Bias

IPF / USAPL meets are over-represented (more reporting). Retired lifters' last-meet values are frozen — their "current" is whenever they stopped competing. Equipped → raw is never auto-converted (different sport-physics, different cohort).

5.8Selectable populations

Powerlifting cohort — OpenPowerlifting public meet data. Drug-tested + untested, all federations. Judged 1RM. This is the only mode where the lift you compare is a real measured 1RM at a sanctioned competition.

Active gym-loggers — StrengthLevel.com public strength-standards pages (squat / bench-press / deadlift, kg). 153M+ logged lifts from strength-tracking-app users. 1RM estimated from rep work. Population skews stronger than the average gym-goer — the data is labelled "active gym-loggers" rather than "recreational" because StrengthLevel users have already (a) created a strength-tracking account, (b) log consistently, (c) care enough to compare against percentiles. The casual gym-goer is weaker than p50 in this dataset.

ACFT baseline (US Army) — US Army ACFT 4.0 deadlift standard (FM 7-22 / ATP 7-22.01), hex-bar converted to conventional barbell with factor 0.92 (Swinton, Lloyd, Keogh, Agouris 2011, J Strength Cond Res, PMID 21659894). Squat and bench derived from deadlift via published ratios (NSCA Essentials 4e, ACSM GETP 11e). Age resolution from NHANES 2011-2014 grip-strength decline curve (CDC; Strand 2018 PMID 29653890), proxy for multi-joint strength decline (r ≈ 0.70–0.85). Allometric BW scaling exponent 0.60 (Vanderburgh & Batterham 1999 PMID 10613442; Jaric 2005 PMID 18172672; Cleather 2006 PMID 16686573). This is the military fitness baseline, NOT a civilian baseline — 75 % of US 17–24-year-olds are non-recruitable (Mission: Readiness 2009, NBK202010).

5.9Civilian baseline — why we don't ship one

No nationally representative dataset tests barbell squat, bench, and deadlift 1RM directly on civilian adults. This is not a gap — it is a structural constraint of mass fitness surveys: barbell 1RM testing needs spotters, racks, and carries injury risk that disqualifies it from epidemiological fieldwork. Every existing tool that claims "general population" SBD norms is either competitive-lifter data, gym-app self-report, or extrapolation from functional proxies (grip strength, chair-stand, push-up). Liftcalc previously labelled the ACFT-pipeline "general population" and applied a 0.92 Army→civilian shift; the literature (Mission: Readiness 2009; Bopp 2023 PMC9885292; Knapik 2017 PMID 28403029) places the actual civilian/Army gap at 0.6–0.7, so that label was misleading. The shift has been removed and the mode renamed to ACFT baseline. A future civilian baseline mode (separate file) will stack ACSM GETP 11e bench norms + OpenPowerlifting bulk meet-data deflated via ACSM/OPL bench-ratio + NHANES grip + Senior Fitness Test (Rikli & Jones 2013) for 60+, with per-cell provenance.

5.10What we don't show

No predicted next-PR. No "elite / intermediate / beginner" badges. No vanity-thresholds. The numbers are the cohort distribution; interpretation is yours.

§ 6 what we don't do

No accounts. No ads. No newsletter. No "Pro" tier. Numbers stay on your device. If localStorage is unavailable (private browsing), the calculator still works — you just lose persisted preferences.

§ 7 keyboard shortcuts

↹1 / 2 / 3 / 4 / 5

switch view: protokoll / arkiv / jamfor / nutrition / metod (when not typing)

↹↑ / ↓

bump load by 2.5 kg / 5 lb (when load-input focused)

§ 8 nutrition model — TDEE, macros, SNS, retention

The /nutrition view uses published nutrition science for the base formulas but combines them in custom-developed models for strength retention and the Strength Nutrition Score (SNS). This section explains what is published and what is liftcalc-proprietary.

8.1Mifflin-St Jeor BMR

BMR (M) = 10·kg + 6.25·cm − 5·age + 5; (F) = same but −161 instead of +5. Mifflin et al. 1990, Am J Clin Nutr 51:241–247 (PMID 2305711).

8.2Activity factors (TDEE multiplier)

1.20 sedentary / 1.375 lightly active / 1.55 moderate / 1.725 active / 1.9 very active. Standard ACSM Harris-Benedict revision (ACSM Guidelines for Exercise Testing and Prescription, 11e 2022, Ch.7).

8.3Protein target

Cut: 2.2 g/kg. Bulk/maintain: 1.8 g/kg. Helms et al. 2014 (J Int Soc Sports Nutr 11:20, PMID 24864135) + Morton et al. 2018 (Br J Sports Med 52:376–384, PMID 28698222) — meta-analysis on protein targets for resistance-trained adults.

8.4Fat + carbohydrate split

Fat: 25 % cut / 28 % maintain / 30 % bulk of target kcal. Carbohydrates = remainder. Within ACSM's 20–35 % fat-of-energy recommendation. ACSM GETP 11e + ISSN Position Stand Aragon et al. 2017 (J Int Soc Sports Nutr 14:16, PMID 28630601).

8.5Cut/bulk thermodynamics

Daily deficit/surplus converted via 7700 kcal/kg of fat tissue. Wishnofsky 1958 constant — accepted first-order approximation, modified by Hall 2008 (Lancet 378:826), which shows the linear model underestimates the plateau after ~6 months. The plateau is approximated inside the projection via a rolling adaptation factor (max 18 %) rather than a separate adaptive-TDEE model, because the view does not log weekly calorie or weight series.

8.6SNS — Strength Nutrition Score (proprietary)

0-100 score. Base 50, plus a protein bonus (+12 if ≥2.0 g/kg, +6 if ≥1.6), a relative-strength bonus (+10 if bench+DL/BW > 1.5, +5 if > 1.0), a deficit/surplus sanity adjustment (cut: +15 if < 10 % deficit, down to −8 if larger; bulk analogous), maintain +8. Liftcalc-proprietary heuristic — no published calibration. Thresholds derived from Helms 2014 + Aragon 2017 + Morton 2018, but the score weights are hand-tuned. Use as direction, not as an absolute number.

8.7BMI-based body-fat estimate

BF% = 1.20·BMI + 0.23·age − 10.8·sex − 5.4 (sex: M=1, F=0). Published population formula from Deurenberg, Weststrate & Seidell 1991 (Br J Nutr 65:105–114, PMID 2043597). Can misclassify muscular lifters; FFMI and waist/height are shown alongside.

8.8FFMI — Fat-Free Mass Index

FFMI = leanKg/(height_m²) + 6.1·max(0, 1.8 − height_m). The height correction normalises against a 1.80 m reference individual. Class thresholds (untrained <18, ..., elite <26, exceptional ≥26) derived from Kouri et al. 1995 (Clin J Sport Med 5:223–228, PMID 7496846), which identified a "natural ceiling" around 25 based on drug-tested lifters.

8.9Strength retention model (proprietary)

weeklyRetentionRate computes the change in weekly 1RM preservation as the sum of energy-status + protein + bodyfat + cut-duration terms. The bulk side follows Helms et al. 2023: 5–15 % surpluses produced similar squat/bench gains while extra bodyweight tracked skinfold/fat gain more cleanly — so 5–20 % surpluses share a similar strength term and larger surpluses mainly raise fat risk. The cut side is derived from Helms 2014, Garthe 2011, and Murphy & Koehler 2022. Coefficient weights and refusal thresholds are liftcalc-derived safety margins, not published prognostic models. Use retention as direction, not as an absolute number.

Summary: Base formulas (Mifflin-St Jeor, Deurenberg BF%, Kouri FFMI, Wishnofsky thermodynamics) are published and freely verifiable. The SNS score + retention model + refusal thresholds are liftcalc-derived indicators built on top of published thresholds, not absolute predictions.