Calculate trade expectancy from win rate, average win and average loss to get the expected profit per trade, the breakeven win rate and a monthly figure.
Trade Expectancy Formula
Expectancy is the average dollar result of one trade, combining how often you win with how much you win and lose:
E = (W * AW) - ((1 - W) * AL)
Dividing by average loss expresses expectancy in average-loss units. This differs from initial-risk R unless average loss equals the supplied initial risk:
Average-loss multiple = E / AL
Variables:
- E is the expectancy - the average profit or loss per trade ($)
- W is the win rate as a decimal (0.45 for 45%)
- AW is the average winning trade ($)
- AL is the average losing trade, entered as a positive number ($)
- E / AL is expectancy per average-loss unit; initial-risk R is not calculated
Enter your win rate and average win and loss from your trading journal - most platforms report all three. Use consistent after-cost statistics on winning and losing trades, excluding flat trades from both the rate and frequency basis. The calculator returns USD expectancy, average-loss multiples, implied profit factor, win/loss ratio and breakeven rate. Optional average monthly frequency scales unrounded expectancy to monthly and12-month expectations, including zero frequency. These are not forecasts.
Expectancy per $100 Risked
Average result per trade when the average loss is $100, across win rates and win sizes.
| Win rate | Avg win $150 | Avg win $200 | Avg win $300 |
|---|---|---|---|
| 30% | -$25.00 | -$10.00 | $20.00 |
| 40% | $0.00 | $20.00 | $60.00 |
| 50% | $25.00 | $50.00 | $100.00 |
| 60% | $50.00 | $80.00 | $140.00 |
The table illustrates the joint effect of win rate and payoff size. A positive modeled average does not establish statistical reliability or future profitability.
Example Problems
Example 1: A trend-following profile.
Win rate 45%, average win $450, average loss $200.
E = 0.45 * 450 - 0.55 * 200 = 202.50 - 110 = $92.50 per trade, or92.50 /200 =0.4625average-loss units. At40trades per month, the same fixed assumptions give an expected $3,700; actual results can differ.
Example 2: A high win rate that still loses.
Win rate 70%, average win $80, average loss $250.
E = 0.70 * 80 - 0.30 * 250 = 56 - 75 = -$19 per trade. Despite winning 7 of 10 trades, the system bleeds money - the classic profile of cutting winners and letting losers run.
Frequently Asked Questions
What is a good expectancy?
Positive estimated expectancy after costs is one input to evaluation. No universal good threshold follows from these three statistics; sampling uncertainty, dependence, changing conditions and risk exposure also matter. Average-loss multiples are not initial-risk R.
How many trades do I need before my expectancy is trustworthy?
There is no universal trade count that makes an estimate trustworthy. Reliability depends on outcome dispersion, dependence and stability; these inputs do not provide a confidence interval. Small samples and outliers can strongly affect the estimated average.
How is expectancy different from profit factor?
Implied profit factor divides probability-weighted average wins by probability-weighted average losses. It is undefined when the modeled loss contribution is zero. Expectancy is an average per trade; multiplying it by frequency scales the expectation, without forecasting its range or accounting for changing assumptions.
