🧮 How We Calculate Rarity

How the number is produced

There are two calculators on this site and they answer different questions.

The one on the homepage asks how rare your combination is among everyone alive. It takes the published frequency of each trait you pick — eye colour, hair colour, blood type and the rest — multiplies them together, and multiplies the result by 8.2 billion. A trait that occurs in 12% of people contributes 0.12. Four traits at 12%, 4%, 2% and 30% give 0.00000288, and 8.2 billion of those is about 23,600 people. The country you select is displayed but deliberately left out of that score, because a country is not a trait you have.

The calculator on each country page asks a narrower and more useful question: how rare is that combination there. It reads the three tables printed on the page — that country’s eye colour, hair colour and blood type — multiplies them the same way, and multiplies by that country’s population instead of the world’s. Nothing is copied into the script: it reads the numbers the page is already showing you, so the calculator and the table can never disagree.

Why the result is rounded

Always to two significant figures. “Roughly 1 in 10,000”, never “1 in 10,417”. The frequencies going in are national estimates given to the whole percent, so the fourth digit of the answer is noise dressed as precision. Below about a thousand expected people the page stops giving a headcount at all and prints only the ratio, because at that size half a point of rounding in one input moves the answer by a sixth.

The assumption that is not true

Multiplying frequencies together is only correct when the traits are independent of one another. Eye colour and hair colour are not: the same pigmentation genes influence both. Blue eyes with blonde hair is genuinely more common than the multiplication suggests, and blue eyes with black hair is rarer. Blood type is independent of both, so that part of the sum is sound. Every result on the site says this rather than hiding it, because a reader hunting for a rare-sounding answer will naturally reach for the discordant combinations — exactly the ones where multiplying is most wrong.

“Other” is not a trait

Some country tables end in an “Other” row covering the colours not listed separately. The country calculator skips those rows. Multiplying two leftover categories together produces a headcount about nobody in particular, and printing it would be worse than printing nothing.

What this is not

It is not research, it is not a medical or genetic test, and it predicts nothing about you. It is arithmetic on published population frequencies. Where those frequencies are firm we say so and name the institution; where they are estimates we say that too — see Data Sources, and Probability Explained for what the numbers do and do not mean.

Last reviewed September 2026.