What expectancy tells you
Expectancy is the average result of a trade. If it is positive, the strategy makes money over a large number of trades; if it is negative, no position sizing or discipline will rescue it. Measured in R, the amount you risked on each trade, it becomes comparable across instruments, account sizes and years.
expectancy (R) = total R ÷ number of trades = win rate × average win − loss rate × average loss
The two forms give the same answer. The first is what this calculator uses on your actual list; the second shows which lever you are pulling: win more often, win bigger, or lose smaller.
R-multiples: why results are measured in risk
An R-multiple is a trade’s profit or loss divided by the amount risked at entry: the distance from entry to stop, times position size. A full stop-out is −1R. A trade that makes three times what it risked is +3R. A trade closed at breakeven is 0R.
Measuring in R separates the quality of the trading from the size of the account. A +$400 trade on a $400 risk and a +$4,000 trade on a $4,000 risk are both +1R: the same decision, made twice. It also exposes problems that dollar figures hide. A loss of −2.4R means the stop was moved or slipped badly, because the plan was to lose 1R.
If you paste results in money, enter your usual risk per trade and the calculator converts them. That works when you risk roughly the same amount each time. If your risk varied a lot, convert each trade to R yourself first, or the average will be skewed towards the larger trades.
Reading the other numbers
- Win rate on its own means little. A 30% win rate with 3R winners beats a 65% win rate with 0.5R winners.
- Payoff ratio is the average win divided by the average loss. Together with the win rate it sets the expectancy. The risk-reward calculator shows the win rate each ratio needs to break even.
- Profit factor is gross profit divided by gross loss. Above 1.0 the strategy made money; 1.5 means it made $1.50 for every $1.00 it lost.
- Longest losing streak and maximum drawdown are what you have to sit through. They decide how much you can safely risk per trade, which is the subject of risk of ruin.
- Standard deviation measures how much results vary from trade to trade. It drives how many trades you need before the expectancy means anything.
Is your sample big enough?
The most common mistake with expectancy is believing it too early. Trade results are noisy, and a small sample of a losing strategy can easily show a positive average.
The calculator gives a rough margin of error: two standard errors, or 2 × standard deviation ÷ √(number of trades). If the expectancy minus that margin is still above zero, the edge is unlikely to be luck. If not, you do not know yet.
The sample loaded above shows the problem. Forty trades, a 45% win rate, average win 2.13R, average loss 0.98R, and an expectancy of +0.47R a trade. That looks excellent. But the standard deviation is 1.59R, so the margin of error is 2 × 1.59 ÷ √40 ≈ ±0.50R, wider than the expectancy itself. The same trader could have a true edge of nothing at all. Another 60 to 100 trades like these would settle it.
Two more things shrink a sample in practice. Results only count if the rules did not change during the sample, and a strategy tested in one market condition may behave differently in another. Keeping trades grouped by setup, as a journal does, is what makes the sample honest.
From expectancy to position size
A positive expectancy says a strategy is worth trading; it does not say how much to risk. The streak and drawdown figures do that. In the sample above, the worst run was six losses in a row and the deepest fall was 7.9R. At 2% risk per trade, a 7.9R drawdown is about 15% of the account; at 1% it is about 8%. Pick the risk that keeps the worst drawdown you expect to see well inside what you would tolerate, then size each trade with the position size calculator.