Calculate expectancy per trade from your win rate, average win and average loss.
How this is calculated
Expectancy = (win rate × average win) − (loss rate × average loss)
Loss rate = 1 − win rate
Expectancy in R = expectancy ÷ average loss
Projected total = expectancy × number of trades
Worked example
Win rate 45%, average win $450.00, average loss $200.00, sample of 100 trades.
Expectancy = (0.45 × 450) − (0.55 × 200) = 202.50 − 110.00 = $92.50 per trade.
Expressed in R: 92.50 ÷ 200 = 0.46R per trade.
Projected across the 100-trade sample: 92.50 × 100 = $9,250.00 before costs.
Understanding expectancy
Expectancy is the arithmetic mean outcome per trade implied by a win rate and the average size of wins and losses. It restates a track record as a single number, which is why it is the standard way to compare two sets of results that have different hit rates and different average trade sizes. A method that wins 30% of the time with large winners and one that wins 65% of the time with small ones can be placed side by side once both are expressed as expectancy.
The R form is the more portable of the two outputs. Dividing expectancy by the average loss removes the account size and the instrument from the figure, so 0.46R per trade means the same thing on a $5,000 account trading micros as on a $500,000 account trading equities. It also makes the projection line honest: multiplying an R figure by a trade count tells you the expected result in units of risk, which is the only unit that stays constant while the balance changes.
The figure describes the sample it came from and nothing else. Small samples produce unstable averages, and a few outsized results can dominate the mean entirely — remove the single best trade from a fifty-trade record and the expectancy of many otherwise reasonable methods turns negative. Before drawing conclusions, check whether the average win is representative or whether it is really one outlier and forty-nine ordinary trades. Median outcomes alongside the mean are a quick way to see this.
Costs belong inside the inputs. Use net average win and net average loss, after commissions, fees and realistic slippage, if you want the output to describe money that actually reached the account. Gross expectancy is a property of the strategy; net expectancy is a property of the strategy as you are able to execute it, and the difference is often the whole margin on higher-frequency approaches.
Finally, expectancy says nothing about sequence. Two records with identical expectancy can have completely different drawdown paths depending on how the losses cluster, and the one with longer losing runs is far more likely to end an account or breach an evaluation limit before the average has any chance to assert itself. Read it alongside drawdown recovery and risk of ruin rather than on its own.
Frequently asked questions
What inputs do I need?
Win rate as a percentage, plus the average profit on winning trades and the average loss on losing trades, taken from your own records.
Should averages include costs?
Use net figures after commissions and fees if you want the result to describe realised performance.
How many trades make the number meaningful?
There is no fixed threshold, but small samples produce unstable averages and can be dominated by a few outliers.
What does negative expectancy mean?
That the sample you entered produced an average loss per trade. It describes past results, not a forecast.