Calculate your edge and project long-term profitability
R:R ratio = 1:2.0 — Loss is always negative (1R = your risk per trade)
+0.500R
($+50.00)
$+1000
Monthly Return ($)
+50.0%
Monthly Return (%)
33.3%
Breakeven Win Rate
1:2.0
R:R Ratio
Positive expectancy -- You have an edge
With 50% wins at 2R avg, you overcome 50% losses at 1R avg.
| Win Rate | Expectancy (R) | Monthly ($) | Edge |
|---|---|---|---|
| 40% | +0.200R | $+400 | |
| 50%(yours) | +0.500R | $+1000 | |
| 60% | +0.800R | $+1600 | |
| 70% | +1.100R | $+2200 |
20 simulated equity curves with your parameters. Highlighted: best (green), average (yellow), worst (red).
Expectancy tells you how much you can expect to make (or lose) per trade on average, measured in R-multiples. The formula is simple: (Win Rate x Average Win) - (Loss Rate x Average Loss). A positive expectancy means your system has an edge -- over a large enough sample of trades, you will come out ahead.
Expectancy is the single most important metric for any trading system. Without a positive expectancy, no amount of money management can save you. It separates sustainable trading from gambling. Professional traders focus on expectancy over win rate because a system that wins only 40% of the time can still be highly profitable.
A positive expectancy does not guarantee profits on any single trade, or even on any particular sequence of trades. Expectancy is a statistical edge that plays out over a large sample size. You can -- and will -- have losing streaks even with a strong positive expectancy. This is why position sizing and drawdown control are essential companions to expectancy.
Consider a trader who wins only 40% of the time but with a 1:3 R:R (risking 1R to make 3R). Their expectancy is (0.40 x 3.0) - (0.60 x 1.0) = 1.2 - 0.6 = +0.60R per trade. Over 20 trades a month at $100 risk, that is $1,200 in expected profit -- despite losing more often than winning. The R:R makes all the difference.