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How the Dating Pool Calculator works — sources, model and limits

The calculator starts from the official adult population (18–79) of the chosen sex in a supported country, then applies each filter with the rate published for the same age group and sex: marital status, measured height percentiles, personal income and education. Income and education are related, so together they give a range between independence and full overlap. Grouped, missing or tail data also widens the range. Results are modelled estimates, rounded, never exact counts.

Most dating-pool calculators multiply a handful of percentages and print a suspiciously exact number. This one uses official tables, applies them where they were measured, and gives you a range when the data cannot support more.

Supported countries

A country is offered only when its official statistics cover the steps honestly. Today: the United States and Switzerland. Where a filter has no trustworthy source, it is disabled for that country and says why — it is never filled with a guess.

United States (dataset us-2024, version 1)

StepSourceYear
Population by age and sexU.S. Census Bureau — American Community Survey 1-year estimates, 2024 · B01001 (Sex by Age)2024
Marital status by age and sexU.S. Census Bureau — American Community Survey 1-year estimates, 2024 · B12002 (Sex by Marital Status by Age for the Population 15 Years and Over)2024
Adult heightCDC / National Center for Health Statistics — Anthropometric Reference Data for Children and Adults: United States, 2015–2018 (NHANES) · Vital and Health Statistics Series 3, No. 46 — Table 9 (females, cm) and Table 11 (males, cm)2015–2018
Personal incomeU.S. Census Bureau — Current Population Survey, 2026 Annual Social and Economic Supplement (CPS ASEC) · PINC-11 (Income Distribution to $250,000 or More for Males and Females: 2025) — all-ages brackets; PINC-01 (Selected Characteristics of People 15 Years Old and Over by Total Money Income in 2025...) — by ageincome year 2025 (CPS ASEC 2026)
EducationU.S. Census Bureau — American Community Survey 1-year estimates, 2024 · B15001 (Sex by Age by Educational Attainment for the Population 18 Years and Over)2024

Switzerland (dataset ch-2025, version 1)

StepSourceYear
Population by age and sexSwiss Federal Statistical Office (FSO/BFS) — Population and Households Statistics (STATPOP) · px-x-0102010000_102 — Permanent and non permanent resident population by canton, sex, marital status and age, 2010-2025 (filtered: Switzerland, permanent resident population, 2025)2025
Marital status by age and sexSwiss Federal Statistical Office (FSO/BFS) — Population and Households Statistics (STATPOP) · px-x-0102010000_102 (marital status × sex × single year of age, permanent resident population, Switzerland, 2025)2025
Adult heightNot available. Swiss Health Survey publishes self-reported mean height only — no distribution, so a threshold cannot be modelled.
Personal incomeNot available. Official Swiss statistics publish wage percentiles for employees in full-time equivalent, not the personal income of all residents, so it cannot be combined with the population.
EducationSwiss Federal Statistical Office (FSO/BFS) — Swiss Labour Force Survey (SAKE/ESPA) · je-d-15.08.02.01 (T 15.8.2.1) — Abgeschlossene Ausbildungen der ständigen Wohnbevölkerung nach Alter und Geschlecht, sheet 20252025

All tables were retrieved on 2026-09-23. The raw figures are kept in the repository next to the dataset.

How the pool is computed

  1. Base: adults aged 18–79 of the sex you chose (or both).
  2. The population is split into the age groups published by the source (single years in Switzerland, ACS groups in the US). If your age range cuts through a group, people are assumed evenly spread inside it.
  3. In each age group and sex, each active filter is applied with the rate measured for that group: share not currently married, share with a degree, share of people at or above an income threshold. Rates are never carried across ages they were not measured for.
  4. Height uses the published percentiles for adults 20+ by sex, interpolated linearly between them. Beyond the 5th or 95th percentile, the result becomes a range (for example 0–5%). Height is assumed independent of the other filters.
  5. Income and education together: they are positively related, so multiplying them would understate the pool. The result is bounded between the independence product (low end) and the smaller of the two shares (high end).
  6. Where a figure is missing (no education figure for 18–24 in Switzerland), the range runs from zero to the nearest published group.
  7. The sum over all groups gives the pool; people counts are rounded to two significant figures.

The biggest filter is the one whose removal would grow the pool the most. The 1 in X framing appears only when the pool is under half of the base.

Why multiplying probabilities misleads

“Half are single, a quarter are tall enough, a third earn enough — so 4%” assumes the filters are unrelated. Age changes marital status, education changes income, and so on. Applying rates inside age groups removes the biggest error; showing a range for the remaining correlation removes the fake precision.

What it cannot tell you

Official statistics record legal marital status, not who is dating, in a relationship or looking. They record sex, not gender identity or sexual orientation. They cannot say who would be interested in you, or whether a filter is reasonable. Survey margins of error are not included. The result is a modelled estimate for curiosity, not a fact about anyone.

Privacy

The calculation happens in your browser. Your filters are not sent to Wabiro or to analytics. A share link stores only the resulting range, the number of filters and which one mattered most.

Versioning

Model version 1. A new data vintage or a change to the model creates a new dataset or model version.

Dating Pool Calculator

Set your filters and watch the pool shrink. Official statistics, honest ranges, and the one filter doing most of the damage.

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