Estimating the Number of Potentially Compatible Partners in Your Area

Suppose you’re looking for a date. You likely have an idea of the characteristics you’d like the person to have, and the ones you would prefer they not have. The question then becomes: How many such people are there near you? Having an accurate sense of this number could give you a rough idea of how likely it is you’ll find a date in your geographic area.

In Section 5.1 of The Calculus of Happiness I discuss how this problem is like searching for aliens (at least mathematically), in the sense that a famous equation called the Drake Equation that estimates the number of intelligent civilizations in our galaxy can be adapted to help estimate how many potentially compatible dates there are in a given geographic region. I quantify the estimate in equation (5.1) of The Calculus of Happiness. The calculator below uses that equation to estimate the number of potential partners using a variety of inputs that most people would think about when consider whether to date someone. These are:

Feel free to input your best guesses for these values into the green cells below (with the exception of the first green cell (the population), all other inputs should be numbers between 0 and 1, since they’re fractions of a whole), and the calculator will estimate the number of potentially compatible partners in your geographic area. (To get a more accurate estimate, you can use websites like American Fact Finder on census.gov to help pin down your city’s population, etc.) NOTE: Don’t be depressed by the output of the calculator; in the book I discuss an article in The Wall Street Journal of one man’s attempt at this calculation that yielded just 26 women matching his criteria out of the nearly 4 million near him.

Limitations

This calculator omits other characteristics you may consider important (e.g., smoker or non-smoker). It also involves a lot of guesswork, even if you use relatively accurate data from a site like American Fact Finder. All of this is to say that the estimate produced has a large error range.