R-multiple is the ratio of a trade's profit or loss to its initial risk (stop-loss distance). A trade that risks $200 and makes $600 is +3R. A trade that risks $200 and loses $200 is -1R. R-multiple normalizes every trade to the same scale so you can compare performance across instruments, timeframes, and position sizes.

How do you calculate R-multiple?

R = (exit price - entry price) / (entry price - stop price) for longs, flipped for shorts. More practically: R = $ profit or loss / $ at risk. If you risked $100 and made $250, that's +2.5R. Use our free R-multiple calculator for quick math.

Why do pros use R-multiple instead of dollars?

Dollars depend on position size, which distorts performance comparisons. A 1% account gain on a $10k account is $100; on a $100k account it's $1,000. R-multiple is account-size-agnostic. A +3R trade is +3R whether you're a $10k or $10m trader.

What is a good average R-multiple?

For day traders: average winner of 1.5-2.5R is strong. For swing traders: 2-4R is the target. What matters more than the R itself is your win rate × average R. A 50% win rate with 2R average winners vs 1R losers (expectancy = +0.5R/trade) is strongly profitable over time.

Trading Metrics 2026-04-20 8 min read

R-Multiple Explained: The One Metric That Separates Pros From Amateurs

Amateurs track dollars. Pros track R. Here's why R-multiple is the single most important metric in your trading journal — and how to calculate it in 10 seconds.

What R-Multiple Actually Is

R-multiple is a simple ratio: the result of a trade divided by what you risked on that trade.

R = P&L ÷ Initial Risk

If you risk $100 on a trade and win $300, that's +3R. If you risk $100 and lose $100, that's -1R. If you risk $100 and scratch out $50, that's +0.5R.

The number tells you the trade's result as a multiple of how much you had at stake — independent of account size, instrument, or position size.

Why Dollars Are a Bad Metric

Most traders track P&L in dollars. That seems sensible. But dollars hide more than they reveal.

Imagine two traders both made $500 today:

Trader A risked $100 on each trade, hit 5 winners at +1R each.
Trader B risked $500 on one trade and made 1R.

Same dollar result. Completely different traders. Trader A has a repeatable process. Trader B is one bad trade from wiping the week. Dollar P&L cannot distinguish these. R-multiple can.

How to Calculate R-Multiple

The precise formula

R = (Exit − Entry) ÷ (Entry − Stop)
(for long trades; flip signs for shorts)

Example 1: Winning long trade

Entry: $50
Stop: $48 (so risk = $2 per share)
Exit: $56 (so profit = $6 per share)
R = $6 / $2 = +3R

Example 2: Losing long trade

Entry: $50
Stop: $48 (risk = $2)
Exit: $48 (hit the stop, loss = $2)
R = -$2 / $2 = -1R

Example 3: Scratch exit

Entry: $50
Stop: $48
Exit: $51 (bailed early)
R = +$1 / $2 = +0.5R

Or just use a calculator

Our free R-multiple calculator does the math instantly. Input entry, stop, exit, direction — get R-multiple back.

The Metric That Actually Matters: Expectancy

R-multiple by itself is one data point per trade. The magic happens when you aggregate.

Expectancy = (Win Rate × Avg Winner R) − (Loss Rate × Avg Loser R)

A trader with:

Win rate: 45%
Average winner: +2.5R
Average loser: -1R

Expectancy = (0.45 × 2.5) − (0.55 × 1.0) = +0.575R per trade

That means, on average, every trade this person takes makes 0.575R. Over 100 trades at $100 risk per trade, that's $5,750. Over 1000 trades: $57,500. This is the math of a profitable trader.

Without R, you can't do this calculation. Dollar-based metrics change every time you change position size. R is fixed.

R-Multiple Reveals Hidden Problems

Problem 1: Cutting winners too early

If your average winner is 1.2R but your average loser is 1.5R, you have a profit-taking problem. You're too eager to lock in small wins and too hesitant to cut losers. The journal shows this instantly.

Problem 2: Moving stops

If your actual stop-out R is consistently worse than -1R (e.g., -1.4R, -1.7R), you're moving stops when trades go against you. R data doesn't lie about this.

Problem 3: Inconsistent risk sizing

If your risk-per-trade varies wildly (some trades $50, others $400), your R-multiples will be accurate but your dollar results will be chaos. R lets you see this — dollar P&L hides it.

"You can't manage what you don't measure. And you can't measure trading performance properly without R-multiple."

How Journali Calculates R Automatically

Every trade you log in Journali requires entry, stop loss, and position size. R-multiple is calculated automatically and shown on the trade card, in analytics, and in AI Trade Coach feedback.

The dashboard's "Average R" metric tracks your expectancy over time so you can see your edge grow (or shrink) week-over-week. The AI Trade Coach (Premier) flags trades where your actual R was materially worse than expected — usually the revenge trades, the ones where you moved a stop, the ones where you sized up inappropriately.

How to Start Tracking R Today

For every trade, write down: entry, stop, exit
Calculate R = (exit − entry) / (entry − stop) [flip sign for shorts]
Record it alongside your $P&L
After 30 trades, compute: win rate, average winner R, average loser R, expectancy
Fix the biggest mismatch (e.g., winners smaller than losers → hold winners longer)