In 2010 economist Peter Backus adapted the Drake equation – used to estimate the number of alien civilisations – to estimate why he didn’t have a girlfriend. He found only 26 women in London who might be suitable. The result is a playful way to see how each preference narrows the field.
How to use the Drake Equation for Love Calculator
- Population of your city
- Share of preferred gender
- Share in your preferred age range
- Share who are single
- Share with the education you want
- Share you find attractive
- Share who would find you attractive
- Share you would get on with
Results update as you type, and every field accepts the units shown in its menu.
How it works
Enter your city’s population and the share of people who match each criterion. Defaults roughly follow Backus’s original assumptions.
Tips
- Results are estimates meant for planning and fun – adjust the inputs to match your situation.
- Everything runs in your browser, so you can try as many variations as you like.
- Share the result link with friends so everyone sees the same numbers.
- For safety-related hobbies (hammocks, balloons, tents), follow the manufacturer’s limits.
Common mistakes to avoid
- Using default values when you know your own figures.
- Treating rough rules of thumb as exact.
- Forgetting to add breaks, travel or setup time.
Inputs explained
| Field | What to enter |
|---|---|
| Population of your city | A number |
| Share of preferred gender | In % |
| Share in your preferred age range | In % |
| Share who are single | In % |
| Share with the education you want | In % |
| Share you find attractive | In % |
| Share who would find you attractive | In % |
| Share you would get on with | In % |
What each result means
- Potential partners = [Population of your city]×[Share of preferred gender]÷100×[Share in your preferred age range]÷100×[Share who are single]÷100×[Share with the education you want]÷100×[Share you find attractive]÷100×[Share who would find you attractive]÷100×[Share you would get on with]÷100
- Chance a random person is a match = [Potential partners]÷[Population of your city]×100
- One in = [Population of your city]÷max([Potential partners], 1e-9)
Example values
How the main result changes when Population of your city changes and everything else stays at the example values above:
| Population of your city | Potential partners |
|---|---|
| 500,000 | 1.9 |
| 750,000 | 2.8 |
| 1,000,000 | 3.8 |
| 1,250,000 | 4.7 |
| 1,500,000 | 5.6 |
| 2,000,000 | 7.5 |
Formula
Potential partners = population × gender share × age-range share × single share × education share × attractive share × mutual-attraction share × compatibility shareWorked example
Inputs — Population of your city: 1,000,000; Share of preferred gender: 50 %; Share in your preferred age range: 20 %; Share who are single: 50 %; Share with the education you want: 30 %; Share you find attractive: 5 %; Share who would find you attractive: 5 %; Share you would get on with: 10 %.
Results — Potential partners = 3.8; Chance a random person is a match = 0.00038 %; One in = 266,667.
Frequently asked questions
Is this a real scientific formula?
No – it's a light-hearted adaptation of the Drake equation by economist Peter Backus.
How many matches did Backus find?
26 potential girlfriends among London's 4 million women in 2010.
How can I improve my odds?
Loosen one or two criteria – each one multiplies the result.