Powerlifting isalive, and getting stronger.
Every drug-tested and untested meet on record, turned into trends, career-arc benchmarks, and hard statistics. Or search a million lifters and see how any career ranks, meet by meet.
- Meet entries indexed
- 3.9M
- Median meets per career
- 2.0
- Median first-meet age
- 23.5
- Avg meets to reach 400 Dots
- 3.1
- Avg YoY participation growth (last 20y)
- +13.1%
The arguments the gym floor keeps having, settled with data.
Is the sport actually dying?
Every so often someone declares powerlifting dead. Trends plots distinct lifters per year for whatever slice you pick — the count rarely agrees with the eulogy.
See the participation curveWhat should meet #5 actually look like?
Career Arc traces the typical Dots curve from debut through meet 30+, with a p25–p75 band so you're measuring against the real spread, not the genetic outliers filling your feed.
See the average arcDoes debuting young raise your ceiling?
Analysis runs the regression and states it in plain English — effect size first, so a tiny result on a huge sample stops passing itself off as "highly significant."
See the regressionWhere does your last meet really rank?
Lifter Lookup drops your Dots into its exact slice — event, equipment, weight class, division — and grades every meet against others at the same stage of their career.
Look yourself upFour lenses on the same data.
Trends
Year-over-year movement of the sport. Participation, average strength, federation share, sliced any way you want.
- Plot any group of lifters against any year range
- Group by weight class, equipment, federation, sex, or age class
- Catch shifts the gym-floor narrative misses
Career Arc
What a typical career actually looks like, meet by meet and age by age, for the group of lifters you care about.
- Average Dots curve from debut through meet 30+
- p25 / p75 bands so you see the realistic range
- Retention curves: how many lifters reach meet 5? meet 10?
Analysis
Linear regression over millions of entries with a plain-English verdict. No PhD required.
- Effect size first, p-value second. No "very significant" labels on trivial effects
- Tests participation vs strength, debut age vs peak, career length predictors
- Every regression card explains itself
Lifter Lookup
Pull up any lifter's career and benchmark every meet against the group of lifters that actually compares.
- Percentile by Dots within event, equipment, weight class, and division
- Per-meet "vs avg" tile showing your delta and rank within the group
- Benchmark your debut against other debuts
Send it.
Missing an analysis you'd find useful? Spotted a regression that doesn't smell right? Want a new way to filter? Email ideas@powerliftingtrends.com. Every email gets read; the best ideas tend to land in the next deploy.