R-multiple calculator
The cleanest way to measure the quality of any individual trade is the R-multiple — the gain or loss expressed as a multiple of the risk taken to open the position. A trade that lost exactly the planned stop distance is "−1R". A trade that returned twice that distance is "+2R". The number is independent of position size, instrument, account currency, and time horizon — it just answers: relative to what you risked, how much did you make or lose?
Most retail traders measure trades in dollars, which makes comparisons meaningless across different sizes. A $50 win on a $500 risk is identical in quality to a $200 win on a $2,000 risk — both are +0.4R. Logging in dollars hides this. Logging in R makes it obvious. The calculator below converts any individual trade into its R-multiple given entry, stop, and exit prices, with the direction auto-detected from the entry-stop relationship.
R-multiple calculator
Why R-multiples beat dollar P&L
Two trades:
- Trade A: $500 risked on a setup with a $2,000 stop distance. Exited for $1,000 profit. +0.5R.
- Trade B: $5,000 risked on a setup with a $200 stop distance. Exited for $1,000 profit. +5R.
Both made $1,000. They are not the same trade. Trade A returned half the risk taken; Trade B returned five times the risk taken. The dollar number hides the gap. R hides nothing.
This is why every serious trade journal logs in R, not dollars. Comparing two trades meaningfully requires a unit that strips out the position size — and "the planned loss if the stop had fired" is the only natural unit available. Once trades are logged in R, expectancy, profit factor, and Sharpe-style stats become meaningful across instruments and account stages. Dollar logs don't compose; R logs do.
What "R" actually is
R is shorthand for risk, specifically the planned dollar loss on the trade if the stop had fired exactly at the entered stop price. If you risked $50 on a trade and the stop fired, the loss is −1R = −$50. If the trade went to the target and exited at +2× that risk distance, it's +2R = +$100. The number is the same regardless of what the dollar amount is, which means a +2R win on a $5,000 trade and a +2R win on a $50,000 trade are identical events, even though one is 100× larger in dollars.
The unit is silent on win rate, costs, and time. It just answers: relative to what was risked, what came out. To use R well, the journal also needs context — which strategy fired, which session, what the thesis was. R is the outcome variable; everything else is the explanatory variable.
How to use this in practice
Three workflows that the calculator above supports:
Logging a closed trade. Type the entry, stop, and exit you actually took. The R-multiple is what goes into your trade log. Over 100 trades, the distribution of R-multiples (with the mean and the standard deviation) tells you more about your trading than any single account-balance number can.
Sanity-checking a planned trade. Before clicking buy, type the entry, stop, and intended target. The "R-multiple at target" tells you what reward-to-risk you're signing up for. A target that returns less than +1R should clear a higher-than-50% honest win rate; a target that returns +2R or more can survive lower win rates. The break-even math is in the break-even-rr tool.
Comparing trades across instruments. A +1.5R BTC trade and a +1.5R ETH trade are equivalent quality even though the dollar numbers differ. R is the only metric that lets you compare across markets without fixed dollar adjustments. For aggregating multi-asset performance, R-totals work; dollar totals require careful normalisation.
For the broader picture of how R fits into expectancy and profit-factor analysis, the profit-factor-vs-expectancy blog post covers the full framework.
FAQ
What's a "good" R-multiple to aim for?
Depends entirely on your win rate. At 50%, you need average wins above 1R to clear costs. At 70%, average wins above 0.43R cover the math. At 35%, average wins above 1.86R do the job. The break-even-rr tool runs the math the other direction — input your win rate and read the required R off the curve.
Does R account for fees and slippage?
The calculator above is pre-cost. Real fills shave a few basis points off the R-multiple — typically 0.05-0.10R per trade at typical retail costs. Negligible for trades that go above 2R; meaningful for trades that finish under 0.5R. For the cost-floor analysis, see the related blog post on minimum edge.
Why is the headline number sometimes worse than −1R?
Either you held past the planned stop and got a worse exit, or your exchange's stop fill slipped past the entered price on a fast move. Both produce a worse-than-1R loss. Worth journaling honestly — distinguishing between "I widened the stop" (a strategy-discipline issue) and "the exchange filled me at a worse level" (a market-microstructure issue) is the kind of post-mortem that catches real problems.
How do I average R-multiples across many trades?
Just take the simple mean. The result is your "expectancy in R" — the average per-trade outcome you'd expect if the next trade is drawn from the same distribution. Multiply by trades-per-year to project annual return in R-units; multiply that by typical risk-per-trade-as-percent-of-account to get an account-percent return. The trade-outcomes-paste tool does this for a list at once.
Can I use this for futures and options too?
Yes for futures and perpetuals — the math is identical. For options the "stop" concept is fuzzier (you might exit on a Greek threshold rather than a price level), but as long as you can name a planned loss number for the trade, you can compute an R-multiple from realized P&L divided by that planned loss. The calculator's price-based fields don't fit options as cleanly; treat the inputs as proxies for "planned loss" and "actual P&L".
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