Trading metric
Average R multiple
The R multiple measures every trade in one honest unit: how much you made or lost relative to what you risked. Averaged over your trades, it is the cleanest single read on the quality of your trading.
What it is
R is the amount you risk on a trade — the distance from entry to stop, multiplied by position size. A trade that makes twice what you risked is a +2R trade; one stopped out for the full planned risk is −1R. The R multiple normalizes every trade to the same yardstick, so a win on a large position and a win on a small one are directly comparable.
Average R multiple is simply the mean R across your trades. It is closely related to expectancy in R — both express the per-trade edge in risk units — and it is the metric that best isolates trade quality from position size and from account growth. Whether you risk a little or a lot, +0.4R per trade is +0.4R per trade.
Its power is that it forces a defined risk unit. You cannot compute R without a planned stop, which means a trader who tracks R has, by construction, committed to where each trade is wrong before entering it. The metric quietly enforces the discipline it measures.
How to measure it
For each trade, divide the result by the amount you planned to risk on it. Average those R values. The honesty of the number depends entirely on the risk unit being defined before the trade, not after.
Trade R = trade profit/loss ÷ planned risk Average R = mean of all trade R values
- 1
For each trade, record the planned risk in currency: (entry − stop) × size. This is 1R for that trade.
- 2
Take the trade result and divide by that 1R to get the trade in R multiples. A full-stop loss is −1R; a win of twice the risk is +2R.
- 3
Use the planned stop, not a stop you moved later — moving the stop corrupts the risk unit and inflates R.
- 4
Average the R multiples across all trades in the sample.
- 5
Watch the distribution too: a healthy average R built on many small +R trades and capped −1R losses is more robust than one carried by a couple of +6R outliers.
Worked example
Five trades: +2R, −1R, +1R, −1R, +3R. The average is (2 − 1 + 1 − 1 + 3) ÷ 5 = +0.8R. Now suppose on the −1R trades you actually moved your stop and lost −2.5R each. The true average drops to (2 − 2.5 + 1 − 2.5 + 3) ÷ 5 = +0.2R. The gap between +0.8R and +0.2R is the cost of not honoring the risk unit.
What good looks like
A positive average R is a real edge, and because it is risk-normalized it is the fairest way to compare strategies, instruments, and time periods. Over a large sample, an average around +0.3R or higher is strong for discretionary trading; even a steady +0.1R compounds meaningfully with volume.
The mark of quality is not a single huge average but a tight, repeatable one with losses capped near −1R. If your average R is healthy only because of a few enormous winners, the strategy is fragile; if it survives removing the best trade, it is durable.
Negative average R
Trades lose more risk units than they make. The setup or the execution is giving back the edge — the priority is finding which.
+0.1 to +0.3R
A genuine, workable edge that compounds with trade count and consistent risk. Where most durable retail trading lives.
Losses well beyond −1R
A discipline failure, not a strategy result. It means stops are being widened or ignored, and it corrupts every other metric downstream.
What moves it
Moving or ignoring the stop
The instant you let a loss run past 1R, the R unit is meaningless and the average is fiction. A clean −1R is a good trade; a −3R on a setup you planned to risk 1R on is the single most damaging entry in the metric.
An inconsistent risk unit
Sizing by gut instead of a fixed risk means each trade has a different R, and the average stops comparing like with like. A defined risk per trade is what makes R coherent at all.
Cutting winners below their R potential
Closing a trade at +0.5R when the plan and the chart supported +2R caps your upside R while your losers still cost a full −1R. Do it often and the average quietly collapses.
Leaning on outlier winners
An average R propped up by one or two huge trades hides a weak typical trade. Check the median R and how the average holds without the best trade before trusting it.
How Mettle tracks it
Because Mettle holds your planned stop and your fills, it can compute R per trade from the risk you actually defined — and flag when a realized loss ran past the 1R you planned.
Each trade plan carries entry and stop, so 1R is the risk you set before entering, not a number reconstructed afterward.
Imported fills give the result, so the dashboard expresses every trade in R and averages them across any play or period.
When a loss exceeds the planned 1R, the review surfaces it so the corrupted risk unit does not silently inflate your average R.
Whether you honored the stop is something you confirm in review — the tags are self-reported, and Mettle counts them rather than guessing from the chart.
FAQ
What is a good average R multiple?
Over a large sample, a positive average R is a real edge; around +0.3R or higher is strong for discretionary trading, and a steady +0.1R still compounds with volume. What matters most is that losses are capped near −1R and the average does not depend on one or two outlier winners.
How is average R different from expectancy?
They are close cousins. Expectancy in R and average R both express the per-trade edge in risk units and will match when computed the same way. "R multiple" emphasizes the per-trade view and trade quality, while "expectancy" emphasizes the strategy-level expected value. Either way, a defined risk unit is required.
Does Mettle calculate this automatically or do I report it?
The number itself is arithmetic on your logged fills, so Mettle computes it for you on the dashboard. What stays self-reported is the behavioral side — the tags and execution notes you add in review — because only you know whether you followed the plan. The copy never pretends otherwise.
Is Mettle free to start?
Yes. You get full access free for 14 days with no card. We only ask for a card once you have reviewed three sessions — after the product has proven it earns a place in your routine.
Track every trade in R
Log your planned stop, import your fills, and Mettle scores each trade in R — flagging the losses that ran past 1R so your average stays honest.
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Want the workflow behind the numbers? Read the matching guide.