Trading Expectancy Explained
Last updated: November 2026 · 3 min read · Educational content, not financial advice
Key takeaways
- Expectancy is the average result per trade, measured in R: E = W × R − (1 − W).
- A high win rate with small winners can have negative expectancy; a low win rate with large winners can be very profitable.
- Subtract costs in R, and measure with your real trade history over a large enough sample.
Win rate tells you how often you win. Expectancy tells you whether winning that often is actually worth it. It is the single number that combines how often you win, how much you win, and how much you lose, and it is the foundation of every other risk calculation on this site.
What expectancy means
Expectancy is the average result of one trade, measured in units of risk. One unit of risk is called 1R: the amount you lose if a trade hits its stop. If you risk $100, then 1R = $100, a trade that makes $250 is +2.5R, and a trade that loses $100 is −1R.
When every loss is exactly 1R, this simplifies to E = W × R − (1 − W), where W is the win rate and R is the reward-to-risk ratio.
Four setups compared
Here are four hypothetical setups. All of them risk 1R per trade.
| Setup | Win rate | Reward : Risk | Calculation | Expectancy |
|---|---|---|---|---|
| A | 40% | 1 : 3 | 0.40×3 − 0.60 | +0.60R |
| B | 55% | 1 : 2 | 0.55×2 − 0.45 | +0.65R |
| C | 70% | 1 : 0.3 | 0.70×0.3 − 0.30 | −0.09R |
| D | 35% | 1 : 5 | 0.35×5 − 0.65 | +1.10R |
Setup C wins seven trades out of ten and still loses money, because its winners are tiny compared with its losers. Setup D loses almost two thirds of its trades and has the best expectancy of the four. Win rate on its own tells you very little.
Turning R into dollars
Suppose you trade a $10,000 account and risk 1% per trade. Then 1R = $100. Setup B, with +0.65R of expectancy, is worth about $65 per trade on average. Over 100 trades with fixed risk, that is roughly $6,500 — but this is an average, not a promise. The actual path will be bumpier, which is why the calculator also shows a distribution of outcomes and a Monte Carlo simulation.
Costs reduce expectancy
Spreads, commissions and slippage take a bite out of every trade. Express them in R as well. If a trade costs you 0.08R in spread and commission on average, your net expectancy is the gross figure minus 0.08R. A setup with +0.10R before costs is effectively break-even after them, while Setup A above (+0.60R) barely notices.
Using your own trade history
In practice, your wins and losses are not exactly the same size every time. The most honest way to measure expectancy is to record the result of every trade in R and take the average:
This automatically includes partial exits, early exits and losses that were smaller or bigger than planned.
How much data is enough?
A measured win rate is only an estimate. The standard error of a win rate is about √(p×(1−p)÷n). For a true 40% win rate, that is about ±6.9 percentage points after 50 trades and about ±3.5 points after 200 trades; double those figures for a rough 95% range. A good-looking 20-trade streak is not evidence of an edge. Use the Number of Trades slider in the calculator to see how much wider the range of outcomes is with a small sample.
Limits of the formula
Expectancy assumes that the future looks like the sample you measured. Markets change, and a setup that worked in one environment can stop working in another. It also says nothing about how deep the losing streaks will be, which is why expectancy should be read together with position sizing and drawdown.
Try the numbers yourself
Try a 55% win rate at 1:2 in the calculator.
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This guide is for education only. It is not financial advice or a trade recommendation, and trading involves substantial risk of loss. See the Terms of Service.