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Trading Expectancy Calculator

Combine win rate with the size of your average winners and losers to estimate the mathematical expectancy of a trading process — in units of initial risk.

Historical trade statistics

%

Use the observed percentage of profitable trades in the sample — not a target win rate.

R

Average profit of winning trades measured against initial risk. Use net results where possible.

R

Enter the average loss as a positive magnitude. A full 1R loss is entered as 1.00, not −1.00.

trades

Sample size does not change the formula; it changes how cautiously the estimate should be interpreted.

Expectancy result

Positive expectancy

Expectancy per trade

+0.20R

On these inputs, the sample implies an average outcome of +0.20R per trade over many trades. This is a sample-based estimate, not a prediction of the next trade.

Payoff ratio
2.00 : 1
Breakeven win rate
33.33%
Observed win rate
40.0%
Vs. breakeven
+6.67 pts

Where the expectancy comes from

Winning contribution
+0.80R
40.0% × 2.00R avg winner
−
Losing contribution
−0.60R
60.0% × 1.00R avg loser
Weighted wins − weighted losses0.80R − 0.60R = +0.20R
Sample context · 50 tradesDeveloping sample

This is useful as an early estimate, but it can still move materially as more trades are added.

Now stress-test this edgeSee the drawdowns and losing streaks it can still produce.

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VSC principle: Win rate alone is not an edge. A trading process has positive expectancy only when the size and frequency of wins outweigh the size and frequency of losses.

How expectancy works

01

Measure what actually happened

Use a consistent set of completed trades to calculate observed win rate, average winner and average loser.

02

Weight wins and losses

Multiply each average outcome by how frequently it occurs. Expectancy is the difference between those two contributions.

03

Judge the estimate cautiously

A positive historical expectancy is evidence from the sample — not proof that the same distribution will persist in future market regimes.

Core formula: Expectancy = (Win rate × Avg winner) − (Loss rate × Avg loser)

What is 1R? R is the initial risk unit for a trade. If the amount initially risked is ₹5,000, then +2R represents +₹10,000 and −1R represents −₹5,000. Expressing outcomes in R helps compare trades even when position sizes differ.

How to read the result

Expectancy in R
The average result per trade in units of initial risk, across the sample you entered. +0.25R means the average trade returned a quarter of what it risked.
The sign matters more than the size
A negative expectancy means the process lost money over that sample regardless of how many individual trades won. No position size fixes a negative number.
Payoff and win rate trade off
A low win rate is not a problem when the average winner is large enough. The two inputs only mean something together, which is what this calculation combines.
A sample is evidence, not a forecast
Expectancy measured on past trades describes those trades. Small samples, a few outliers, or a change in market regime can move it substantially.

Related reading

The framework behind it

Use with