What is DOTS, and how does it relate to Wilks and IPF GoodLift?

DOTS is a strength-comparison coefficient by Konertz / BVDK (2019). It is the de-facto raw-open standard on OpenPowerlifting and US raw federations such as USPA, but it is not an IPF formula. The IPF's official coefficient has been IPF GoodLift (IPF GL Points) since 2020, when the IPF's formula review retired Wilks for systematically under-scoring heavier lifters. 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.

What dataset does LiftGauge's percentile rank use?

OpenPowerlifting public meet data (CC0 license, snapshot 2026-05-16). Approximately 143,000 raw-lifter records, segmented by sex, lift, IPF bodyweight class, age (per year, 15-80), and equipment. 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 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 as a multi-joint strength proxy. This is a military fitness baseline, not a civilian baseline — Mission: Readiness 2009 found 75% of US 17-24-year-olds fail current Army recruitment standards. Full breakdown at /acft-deadlift-standards.

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 is reported as the headline 1RM; the spread is reported as the ±%.

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.

method

How to read the app, where the formulas come from, what the numbers mean.

§ 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 /method § 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 how does it relate to Wilks and IPF GoodLift?: DOTS is a strength-comparison coefficient by Konertz / BVDK (2019). It is the de-facto raw-open standard on OpenPowerlifting and on US raw federations such as USPA — but it is not an IPF formula. The IPF's own official coefficient has been IPF GoodLift (IPF GL Points) since 2020, when the IPF's formula review retired Wilks for systematically under-scoring heavier lifters (IPF formula evaluation, 2020). 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 2026-05-16). Approximately 143 000 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). Full breakdown: ACFT deadlift standards.
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 /calculator. Anchor: 1@10 = 100 %.

§ 2 Prilepin's table

The active-row stamp on the table marks the zone matching your current /calculator 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.

intensity (% of 1RM)	reps/set	optimal NPL	range
55–65 %	3–6	24	18–30
70–75 %	3–6	18	12–24
80–85 %	2–4	15	10–20
≥ 90 %	1–2	7	4–10

§ 3 federation coefficients

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

3.1DOTS: Konertz / BVDK 2019. The de-facto raw-open standard on OpenPowerlifting and US raw federations (USPA) — not an IPF formula. Widely adopted because the older Wilks formula systematically under-scored heavier lifters.
3.2Wilks 2020: Wilks (1994), 2020-revision coefficients. Superseded at the IPF by IPF GoodLift in 2020, and on most raw scoreboards by DOTS. Kept for parity with old write-ups.
3.3IPF GL: IPF GoodLift 2020 — the IPF's official scoring coefficient, replacing IPF Points (2019) and Wilks. 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 — /rankings

The /rankings 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 section: 1RM calculator / scores / rankings / nutrition / method (when not typing)
↹↑ / ↓: bump load by 2.5 kg / 5 lb (when load-input focused)

§ 8 nutrition model — TDEE, macros, retention

The /nutrition view uses published nutrition science for the base formulas but combines them in a custom-developed strength-retention model. This section explains what is published and what is liftgauge-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.
8.6BMI-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.
8.7FFMI — 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.
8.8Strength 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 liftgauge-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 retention model + refusal thresholds are liftgauge-derived indicators built on top of published thresholds, not absolute predictions.