Powerlifting percentile calculator
Where your lift sits in recorded powerlifting meet results.
dataset scope · 615,721 lift observations
Percentile rank from 615,721 qualifying lift observations contributed by 186,218 of 186,303 eligible OpenPowerlifting rows in the trailing window beginning 2025-05-10 (CC0 source dump dated 2026-05-16; latest included meet 2026-05-10). Cohort cells are segmented by sex × age (per-year, 15–80) × bodyweight class (IPF) × equipment. Repeat competitors may contribute more than one observation.
Competition-only population — meet-result entries from people who registered for a sanctioned meet; this is not a general-population baseline.
Most entries are raw — bar, belt, and knee sleeves. Choose the equipment used for the recorded result so the comparison cohort matches it.
how you compare
how long it took others
Bodyweight-stabilised identity keys with at least two recorded meets. These keys support a meet-history view but are not guaranteed to represent unique people.
other lifts at your level
real competition medians
Median lifts (the 50th percentile) from sanctioned powerlifting meet results, segmented by sex and IPF bodyweight class. The cube contains 615,721 qualifying lift observations from 186,218 contributing rows out of 186,303 eligible rows in the trailing window beginning 2025-05-10 (OpenPowerlifting CC0 source dump dated 2026-05-16; latest included meet 2026-05-10). Repeat competitors may contribute more than one observation. Use the calculator above for your specific age and equipment combination.
| cohort | squat | bench | deadlift | total | total n |
|---|---|---|---|---|---|
| M, 83 kg, age 30, raw | 210 kg | 137.5 kg | 245 kg | 582.5 kg | 182 |
| M, 93 kg, age 30, raw | 215 kg | 142.5 kg | 242.5 kg | 601.3 kg | 280 |
| M, 105 kg, age 30, raw | 235 kg | 152.5 kg | 255 kg | 635 kg | 285 |
| F, 63 kg, age 30, raw | 125 kg | 65 kg | 147.5 kg | 337.5 kg | 89 |
| F, 69 kg, age 30, raw | 125 kg | 70 kg | 150 kg | 345 kg | 121 |
Source: openpowerlifting.org · CC0 · source dump 2026-05-16 · latest included meet 2026-05-10 · “total n” is the qualifying total-lift observation count for that row; each single-lift cell has its own observation count. Repeat competitors may contribute more than one observation. Cohort-axis methodology in /method §5.
method notes
Cells require at least 30 qualifying lift observations. If the exact-age cell is sparse, LiftGauge tries all ages, then ±1 and ±2 bodyweight classes; if no candidate reaches n ≥ 30, it returns no percentile instead of using a global fallback. /rankings does not estimate a general-population percentile. For an age-projection on the same OpenPowerlifting data, see Strength Age. For projection from a top set of one lift, use the bench press 1RM calculator.
how to use it
- Pick lift, sex, and bodyweight class — pick the lift (squat / bench / deadlift / total), your sex, and the IPF bodyweight class that fits your weigh-in weight.
- Pick age and equipment — pick your age (per year, 15–80) and equipment (raw / single-ply / multi-ply). Wraps entries are excluded rather than mixed into raw. Cohorts are computed cell-by-cell, so age and equipment matter.
- Enter your lift — enter your best matching lift in kg. The percentile read is computed against qualifying lift observations in that cohort cell. If n < 30, LiftGauge tries all ages, then ±1 and ±2 bodyweight classes; it shows the widening used and returns no result if none reaches n ≥ 30.
- Compare trajectory and crosslift — both panels use the same resolved age, bodyweight class, sex, equipment and percentile bracket shown in the lead result; any sparsity widening is carried through rather than hidden.
frequently asked
- What does percentile rank mean for powerlifting?
- Your percentile is the fraction of qualifying lift observations in your cohort cell that record a lower lift. A 90th percentile bench means 90 % of matching observations are lower. Repeat competitors may contribute more than one observation. LiftGauge shows percentile p1–p99 plus an explicit decile band so you can read it as "top 10 %" rather than a precise number.
- How big is the OpenPowerlifting dataset behind this?
- The source dump contains 3,925,887 meet-result rows. In the trailing window beginning 2025-05-10, 186,303 rows pass the source filters, 186,218 contribute at least one valid lift, and those lifts create 615,721 percentile observations; 141,828 full-power rows feed cross-lift comparisons. Counts are observations or rows, not unique people: a competitor may have multiple meet results. Source dump dated 2026-05-16; latest included meet 2026-05-10; openpowerlifting.org, CC0 license.
- Why does my cohort widen when I pick an unusual age?
- If your exact age × bodyweight × equipment cell has fewer than 30 qualifying lift observations, LiftGauge tries all ages, then ±1 and ±2 bodyweight classes. Every accepted cell has n ≥ 30 and the widening is shown explicitly. If none qualifies, LiftGauge returns no percentile; it does not substitute a global cohort.
- Does training history (months/years lifting) factor in?
- Not directly — OpenPowerlifting does not record training age. The denominator is qualifying lift observations at the selected bodyweight class, age, sex, and equipment. Observations from novices and long-time competitors can share the same cell; the percentile reflects recorded meet-day output, not the path to it.
- What counts as raw vs equipped?
- Raw = belt + chalk + non-supportive sleeves, no knee wraps, no bench shirt, no squat suit. OpenPowerlifting rows labelled Wraps are excluded from these cubes rather than mixed into raw. Single-ply / multi-ply use separate cohort cells because supportive bench shirts and squat suits define different populations.
- What lift makes you "elite" in powerlifting?
- “Elite” has no universal federation definition. A more reproducible answer is your matched-cohort rank: the 90th percentile means top 10 %, the 95th top 5 %, and the 99th top 1 % for the selected sex, age, bodyweight class, and equipment. Absolute numbers vary heavily by weight class, which is why LiftGauge reports the percentile and cohort rather than assigning an official-sounding label.