Delusion Calculator Criteria: Every Filter Explained
A full reference for every input the calculator takes, what data drives it, and how sharply each one narrows your pool.
The delusion calculator takes six main filters, age range, height, income, body type, education, and marital status, and each one removes a measurable share of the population. Some filters cut deep. Asking for a man who is six feet or taller drops the pool to about 1 in 7 on that trait alone. Others trim it gently. Excluding people below a certain build removes a smaller slice. This page walks through every input in turn: what it controls, which dataset drives it, roughly how sharp the cut is, and a realistic example. It ends with a summary table and an explanation of why the tool does not simply multiply the filters together.
Each field is optional. Leave one blank and you are not filtering on it, so the pool stays wider on that trait. Fill several in and the demands stack, which is where results start to look rare. You can follow along with the male delusion calculator or the female delusion calculator as you read.
Age range
The age filter keeps only people whose age falls between the minimum and maximum you set. It is the first cut most people make, and its sharpness depends entirely on how wide a band you choose. A ten year window covers a large chunk of the adult population. A three year window covers far less.
The data draws on the US Census American Community Survey (ACS), which reports the age structure of the adult population in fine detail. Because age is spread fairly evenly across the dating years, this filter behaves predictably: halve the width of your range and you roughly halve the share that qualifies.
Example. Out of about 128 million adult US men, asking for ages 30 to 40 keeps a broad band, perhaps a fifth of the total. Narrowing to 32 to 35 cuts that to a much thinner slice. The narrower the window, the harder this filter bites, so it can range from mild to severe depending on your setting.
Height
Height is one of the two filters that cut hardest. It sets a floor, keeping only people at or above the height you pick. Small changes in the threshold move the qualifying share a lot, because height clusters tightly around the average.
The numbers come from CDC NHANES, the National Health and Nutrition Examination Survey, which measures height directly rather than relying on self reported figures. The average US male height is about 5 feet 9 inches. Set the floor there and about half of men remain. Raise it to 6 feet and the share drops to about 14.5 percent, close to 1 in 7. Push higher and it falls away fast.
Example. A six foot minimum alone removes about 85 percent of men before any other trait is considered. That is why height so often dominates a result. Our post on what percentage of men are six feet tall breaks the distribution down inch by inch.
Income
Income is the other filter that cuts hardest, and often the sharpest of all at high thresholds. It keeps only people whose individual annual earnings meet the floor you set. Earnings are spread across a long tail, so a modest threshold keeps most workers while a high one keeps very few.
The figures draw on the ACS and the Census Current Population Survey (CPS), which track individual earnings across the working population. About 18 percent of US men earn 100,000 dollars or more on their own. Set the floor at that level and you keep fewer than one in five before layering on anything else.
Example. A 100,000 dollar income floor removes roughly 82 percent of men. Raise it to 150,000 and the remaining share shrinks again, since each step up the income ladder holds far fewer people than the one below it. See what percentage of men make 100k for the full picture.
Body type
Body type is a milder filter than height or income. It uses height and weight together to sort people into builds such as slim, average, or athletic, and keeps those in the band you choose. Because most people cluster in the middle of the range, choosing an average or broad build removes only a modest share.
The underlying measurements come from CDC NHANES, which records both height and weight, allowing the tool to estimate build from body mass rather than self description. The strictness depends on your choice: an average band is forgiving, while a narrow athletic band excludes more.
Example. Asking to exclude only the heaviest end of the distribution might remove a third of the pool or less, a gentler cut than a six foot height floor. Combine a strict build with a strict height, though, and the two compound.
Education
The education filter keeps people at or above an attainment level, most commonly a bachelor's degree or higher. It ranks midway for sharpness: firmer than body type, gentler than height or income.
Attainment data comes from the Census ACS. About 37 percent of US men hold a bachelor's degree or higher. Set that as your floor and a little over a third of men remain on this trait alone. Require a graduate degree and the share drops further, since fewer men hold advanced credentials.
Example. A bachelor's or higher requirement removes roughly 63 percent of men. That is a real cut, but a softer one than height, and it overlaps heavily with income, which matters for how the filters stack.
Marital status
Marital status is among the milder filters. It limits the pool to people in a chosen status, most often single or never married, rather than the full adult population. Because a large share of adults in the prime dating years have not married, this filter trims the pool rather than gutting it.
The data again comes from the ACS, which reports marital status by age. The share who are unmarried is high among younger adults and falls with age, so the strictness of this filter depends heavily on the age range you paired it with.
Example. Among men in their late twenties, a large majority are never married, so the filter removes a small slice. Among men in their forties, more are married or previously married, so the same filter cuts deeper. On its own, though, it is usually one of the gentler inputs.
How the filters stack
Every filter you add makes the pool smaller, and the effect compounds. A six foot floor might keep 1 in 7 men, and a 100,000 dollar floor might keep fewer than 1 in 5. Ask for both and you are looking at a much smaller group than either filter produces alone. This is why a long wish list lands at a rare result even when no single demand looks extreme.
The tempting shortcut is to multiply the frequencies. If 14.5 percent are tall and 18 percent earn six figures, you might guess 14.5 percent times 18 percent, about 2.6 percent, are both. That answer is wrong, because the traits are not independent. Taller men, higher earners, and degree holders overlap more than chance would predict, since height, age, income, and education all correlate in the real population. A tall man is somewhat more likely to be a high earner than a random man is.
Multiplying raw frequencies assumes the traits are unrelated, which overstates how rare a combination is. To avoid that, the calculator applies a correlation adjustment instead of naive multiplication. The adjustment reflects how these traits actually cluster, so a tall high earner comes out somewhat more common than the multiplied figure suggests. The how it works guide covers the adjustment step by step, and the data sources guide lists the vintage of each dataset. Everything here is modeled on the US adult population, and the result is expressed as a matching percentage, a 1 in X figure, and a score from 1 to 10.
Filter reference table
The table below summarizes each filter, the dataset behind it, and roughly how much a typical strict setting removes from the pool. Treat the removal figures as approximate, since the exact cut depends on the threshold you choose and the other filters you pair it with.
| Filter | Primary data source | Rough cut at a strict setting |
|---|---|---|
| Age range | Census ACS | Varies widely; a narrow band can remove most of the pool |
| Height | CDC NHANES | About 85 percent removed at a 6 foot floor |
| Income | Census ACS and CPS | About 82 percent removed at a 100k floor |
| Education | Census ACS | About 63 percent removed at bachelor's or higher |
| Body type | CDC NHANES | Milder; often a third or less at an average band |
| Marital status | Census ACS | Milder; depends heavily on the paired age range |
Read across the table and the pattern is clear. Height and income are the heavy hitters, education lands between them, and body type and marital status are the gentler inputs. If a result surprises you, look first at your height and income floors, since those two almost always drive the outcome. For a plan on adjusting them, see the guide on how to lower your delusion score, and check the methodology page for the full source detail.