Dating Theory Calculator

Apply the 37% rule (optimal stopping theory) to your dating timeline: see how many people to date before you start committing, and the age at which to stop searching and settle down.

Quick Facts

Method
37% rule (secretary problem / optimal stopping theory)
Reject the first ~36.8% of your expected candidate pool, then commit to the next person who beats everyone before them.
Best-case odds
~36.8% (1/e)
This is the mathematically optimal chance of landing the single best-ranked partner under this strategy, as your pool grows large.

Your Results

Calculated
People to reject first
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Optimal "look phase" length before you compare seriously
Cutoff age
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Age your look phase ends, under the 37% rule
Success probability
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Chance this strategy lands your best possible match
Current phase
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Look vs. leap, based on progress so far

Ready

Enter your dating timeline and press Calculate.

Understanding the 37% Rule for Dating

This tool applies optimal stopping theory — specifically the classic secretary problem — to a dating timeline. The setup: you will meet a sequence of potential partners, one at a time, and you can rank each new person only against everyone you've dated so far. Once you pass on someone, you can't go back. Mathematics gives a provably optimal strategy for maximizing your odds of ending up with the single best-ranked person: reject a fixed fraction of your expected pool outright, then commit to the very next person who beats everyone who came before them.

The formula

If you expect to seriously date N people in total, the optimal number to reject first, r, is the integer that maximizes the classic secretary-problem success formula P(r) = ((r−1)/N) × Σ (from i=r to N) of 1/(i−1). As N grows, the optimal ratio r/N converges to 1/e ≈ 0.368 — the origin of the "37% rule" name — and the resulting success probability also converges to 1/e, about 36.8%. This calculator computes the exact optimal r and exact success probability for your specific pool size, rather than only the large-N approximation.

To translate the candidate count into a real calendar age, the same rejection fraction (r/N) is applied to your dating age window: cutoff age = start age + (end age − start age) × (r/N). Before the cutoff age you're in the "look phase" — date freely, but don't commit. After it, you're in the "leap phase" — commit to the next person who's better than everyone you've dated so far.

How to read your results

"People to reject first" is r, the number of early candidates you should date and learn from without committing. "Cutoff age" maps that same fraction onto your stated age range. "Success probability" is your exact chance, under this strategy, of ending up with the single best-ranked partner out of your full expected pool — not just "a good one," but the very best. "Current phase" compares how many people you've already dated to r and tells you whether you're still gathering data or should be ready to commit.

Assumptions worth stating plainly

The model assumes you can rank every candidate you meet from best to worst with no ties, that you know roughly how many people you'll date in total, that candidates arrive in random order, and that "success" means landing the single top-ranked person rather than any of your top few. Real dating rarely satisfies all of these perfectly — but the 37% rule is still a useful, mathematically grounded heuristic for pacing a search where you can't un-reject someone once you've moved on.

Frequently Asked Questions

What is the 37% rule in dating?
The 37% rule comes from the secretary problem in optimal stopping theory. If you expect to date N people before settling down, the strategy that gives you the best mathematical odds of picking the single best partner is to reject the first N divided by e (about 36.8%) of them outright, then commit to the very next person who is better than everyone you saw before them.
How many people should I date before committing to someone?
Under the optimal stopping strategy, the number to reject first equals whichever integer maximizes the classic secretary-problem success formula, which lands close to your total expected pool divided by e. For an expected pool of 12 people, that works out to rejecting roughly the first 4 to 5 before you start comparing seriously.
What age should I stop searching and settle down?
Mapping the rule onto an age range gives a cutoff age of your starting age plus your rejection fraction times the length of your dating window. For example, starting at 18 and wanting to be settled by 35 with a typical rejection fraction near 37%, the cutoff lands around age 24 to 25 — the point where you stop just gathering data and start committing to the next great match.
What is my probability of finding the best possible partner with this strategy?
As your expected pool of candidates grows large, the optimal strategy's success probability converges to 1/e, about 36.8%. For a smaller, specific pool size the calculator computes the exact probability using the standard secretary-problem formula. This assumes you can rank every candidate you meet and that "best" means the single top-ranked person, which is a simplification of real relationships.