Salary Percentile Calculator

Work out salary percentile instantly with clear inputs, formula shown and shareable results.

About Salary Percentile Calculator

Converting a salary into a percentile requires the market mean and standard deviation. The z-score measures how many standard deviations you sit from the mean, and the normal distribution then translates that into the share of the market you are paid above.

Formulas

Standard score

z = (Your salary - Market mean) / Market standard deviation

Percentile

Percentile = 50 x (1 + erf(z / sqrt(2)))

Worked example

With the default values below, Salary Percentile Calculator returns Your salary percentile of 70.39%. Change any input above and every figure here is recalculated in your browser.

Inputs used

Your salary: 1,450,000
Market mean salary: 1,300,000
Market standard deviation: 280,000
Benchmark sample size: 420

Results

Your salary percentile: 70.39%
Standard score: 0.536
Benchmark peers earning more: 124
Gap to the market mean: $150,000.00

Step by step

1Values used
2Standard score
3Percentile
4Your salary percentile= 70.39
5Standard score= 0.536
6Benchmark peers earning more= 124
7Gap to the market mean= 150,000.00

Assumptions and limits

The result is derived only from the 4 inputs listed above. Anything not among them is not part of the calculation.
In particular, this calculator does not take inflation, tax, fees or charges or compounding frequency into account.
Figures are rounded for display to 3 decimal places, so totals built from several rounded parts can differ slightly from the unrounded arithmetic.

How these calculators are built and tested is described on the Methodology page. If a figure looks wrong, please report it.

Frequently Asked Questions

Are salary distributions really normal?

They are right-skewed, so the true percentile at the top end is usually a little higher than the normal model suggests. Log-normal fits better.

Does sample size matter?

Yes. A benchmark from 20 respondents has wide confidence intervals; treat percentile precision from small samples with caution.