Trading expectancy is the average profit or loss a strategy would be expected to produce per trade under a stated distribution of wins and losses.
How it works
A simple formula is: win rate × average win − loss rate × average loss. The inputs can be expressed in money, percentages, or R-multiples as long as they use a consistent unit.
Expectancy is an estimate from a sample, so it should be reviewed together with sample size, costs, drawdowns, and changes in market regime.
Why it matters
Expectancy prevents win rate or reward-to-risk from being judged in isolation. A low-win-rate strategy can still have positive expectancy if winners are sufficiently large, and the reverse can also be true.
Historical expectancy is not a promise. Small samples, overfitting, changing execution costs, and regime shifts can make the estimate unstable.
A simple market example
A strategy that wins 35% at +3R and loses 65% at −1R has expectancy of +0.40R per trade under those assumptions: 0.35×3 − 0.65×1.
Common mistakes
Assuming a 3:1 reward-to-risk setup must be better than a 1:1 setup.
Treating a positive estimate from a small historical sample as a guaranteed future edge.
Frequently asked questions
What is breakeven win rate?
It is the win rate at which average gains and losses offset each other under the stated payoff assumptions.
Can a strategy win less than half the time and still work?
Yes, if average winners are sufficiently larger than average losers after costs.
Is expectancy enough to judge a strategy?
No. Drawdown, tail risk, sample quality, execution, and stability also matter.
Educational content only. Definitions describe common market usage and may vary by jurisdiction, instrument, or institution.