Expectancy, Win Rate and R-multiples

R: the amount you planned to risk

Before entering a trade, you set an exit level. The money lost if that exit is hit is 1R. If you plan to lose $500, 1R = $500.

Every result can then be expressed in R. Make $1,250: that's +2.5R. Lose $600 because the price gapped past your exit: that's −1.2R. Measuring in R lets you compare trades of different sizes.

Expectancy: what an average trade is worth

Expectancy = (win rate × average win) − (loss rate × average loss), all in R.

Trader A: wins often

Wins 70 per cent of trades, average win +0.4R. Loses 30 per cent, average loss −1.2R (they let losers run a bit).

(0.7 × 0.4) − (0.3 × 1.2) = 0.28 − 0.36 = −0.08R per trade.

Seven wins out of ten. Losing money.

Trader B: loses often

Wins 35 per cent, average win +2.5R. Loses 65 per cent, average loss −1R.

(0.35 × 2.5) − (0.65 × 1) = 0.875 − 0.65 = +0.225R per trade.

Wrong most of the time. Making money, on these numbers.

Then add costs

Brokerage, spreads and slippage come off every trade. If they cost 0.1R per trade, Trader B drops to +0.125R and Trader A to −0.18R. Over 100 trades with 1R = $500, that's roughly +$6,250 for B and −$9,000 for A. Costs matter most to strategies with small average wins.

Why people misjudge this

• Winning feels good, so a high win rate feels like evidence of skill.
• Taking small profits quickly and holding losers is the disposition effect in action, and it drags expectancy down.
• A low-win-rate strategy needs the temperament to sit through long losing streaks. Trader B could easily lose eight or ten in a row.
• Twenty trades isn't enough to know your real numbers. Small samples mislead.

What to do with this

Take your last 30 closed trades (or as many as you have). Record each result in R using the exit you planned at entry. Calculate your win rate, average win, average loss and expectancy after costs. If you didn't set an exit at entry, that's the first thing to fix.