Understanding R-multiples: the only fair way to compare your trades
A +$400 trade and a +$400 trade are not the same trade if one risked $100 and the other risked $800. Until you measure results in R, your P&L is comparing numbers that are not comparable.
The single most useful idea in trade analysis is also one of the simplest: measure every result not in dollars, but in multiples of what you risked. That unit is called R. Once your journal speaks in R, trades of wildly different sizes finally become comparable, and your true edge stops hiding behind position size.
What R actually is
R is the amount you put at risk on a trade — the distance from your entry to your stop, multiplied by your size, expressed in money. If you buy at 100, place your stop at 98, and trade a size where each point is worth $50, then your risk is 2 points × $50 = $100. That is 1R for this trade.
The result of the trade, expressed in R, is simply your profit or loss divided by that 1R risk. Close it at 104 for +$200 and you made +2R. Get stopped at 98 and you lost −1R. A trade that ran to +$300 on the same risk is +3R. Now a scalp on a tiny account and a swing on a large one can sit in the same column and mean the same thing.
R-multiple = trade P&L ÷ initial risk (entry-to-stop distance × size in money). A −1R trade lost exactly what you planned to risk. A +2R trade paid you twice your risk.
Why dollars mislead you
Dollar P&L blends two different decisions — how good the trade was and how big you sized it — into one number. A trader who makes $5,000 by risking $2,500 per trade is not outperforming one who makes $3,000 risking $500; the second trader has a dramatically better edge and simply sizes smaller. Ranked in dollars, the first looks better. Ranked in R, the truth is obvious. If you size inconsistently — and almost everyone does — dollar averages are close to meaningless.
From R to expectancy
Once every trade has an R value, you can compute the number that actually predicts whether you make money: expectancy, your average R per trade. The formula is straightforward:
Expectancy = (win rate × average win in R) − (loss rate × average loss in R).
Say you win 40% of the time, your winners average +2.5R and your losers average −1R. Expectancy = (0.40 × 2.5) − (0.60 × 1.0) = 1.0 − 0.6 = +0.4R per trade. Every trade you take is worth, on average, four-tenths of your risk unit. That is a genuine edge — and notice it comes with a *losing* win rate. R-multiples are how a strategy that loses 60% of its trades can still be highly profitable.
What R reveals that nothing else does
- Whether you cut winners short. If your average winner is +1.1R while your best trades reach +4R, you are exiting too early. The R distribution shows it at a glance.
- Whether your losers are really 1R. Losers averaging −1.4R means you are letting stops slip or moving them. Your risk is not what you think it is.
- Whether a high win rate is a trap. A 70% win rate with +0.5R winners and −2R losers is a slow bleed. Only expectancy tells you.
The one requirement
R only works if you record your stop, or your intended risk, at entry. For trades taken without a hard stop, define risk another way — a fixed dollar amount you were willing to lose on the idea — and compute R from that. A journal that captures risk on every trade can speak in R. One that only captures P&L is stuck comparing numbers that were never comparable in the first place.
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Every idea in this guide — R-multiples, prop-rule room, session stats and on-plan tracking — is built into the journal. Free to start, no card required.
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