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)
| Step | Source | Year |
|---|---|---|
| Population by age and sex | U.S. Census Bureau — American Community Survey 1-year estimates, 2024 · B01001 (Sex by Age) | 2024 |
| Marital status by age and sex | U.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 height | CDC / 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 income | U.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 age | income year 2025 (CPS ASEC 2026) |
| Education | U.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)
| Step | Source | Year |
|---|---|---|
| Population by age and sex | Swiss 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 sex | Swiss 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 height | Not available. Swiss Health Survey publishes self-reported mean height only — no distribution, so a threshold cannot be modelled. | — |
| Personal income | Not 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. | — |
| Education | Swiss 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 2025 | 2025 |
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
- Base: adults aged 18–79 of the sex you chose (or both).
- 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.
- 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.
- 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.
- 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).
- Where a figure is missing (no education figure for 18–24 in Switzerland), the range runs from zero to the nearest published group.
- 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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