Win-rate breakeven
Expectancy per trade is (win rate × average win) − ((1 − win rate) × average loss). Setting expectancy to zero and solving for win rate is the breakeven identity. The widget then counts simulated paths at whatever win rate you enter.
Win rate in the widget is an input, not an output. The table is the closed-form breakeven for a stated R-multiple pair.
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Breakeven win rate = average loss ÷ (average win + average loss), when both are in the same R units. For +1.70R / −1.00R that is 1.00 ÷ 2.70 = 37%.
| Average win (R) | Average loss (R) | Breakeven win rate |
|---|---|---|
| 1.70 | 1.00 | 37% |
Above that win rate, expectancy is positive; below it, negative. Positive expectancy is not the same as a low risk of ruin — a streak can still reach the floor. That is why the widget exists beside the identity.
Identity vs simulation
The identity ignores sequencing, daily caps, and floors. The widget includes those as fields. The free personal-rule engine currently models a stated Max Drawdown allowance as a fixed floor measured from your starting balance, not a floor that ratchets upward with a new equity peak.
Expectancy vs win rate · methodology.
FAQ
- What is breakeven win rate?
- The win rate at which expectancy per trade is zero: average loss divided by (average win plus average loss), when both averages are in the same units.
- If I am above breakeven, is ruin impossible?
- No. Expectancy is an average. A losing streak can still reach a stated floor. The widget counts those sequences; the identity does not.
- Does this recommend a win rate?
- No. Win rate is measured from a history or entered as a model input. The page reports the arithmetic of the numbers entered.
Run it against your own numbers
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