What is an R-multiple, and why traders measure results in R

Dollar results are hard to compare. A $200 win on a big account and a $20 win on a small one might be exactly the same trade. That's why many traders measure results in R: multiples of what they risked.

What R is

1R is the amount you planned to lose if your stop was hit. Every result is then expressed as a multiple of that:

R-multiple = profit or loss ÷ initial risk

Initial risk = |entry − stop| × position size

If you risked $50:

• You made $110 → +2.2R
• You lost $50 at your stop → −1R
• You closed early for $20 → +0.4R
• You lost $75 → −1.5R

That last one is the interesting one. A loss bigger than 1R means something went wrong: you moved your stop, the price gapped through it, or costs were higher than planned.

Why R beats dollars

• It's comparable. A +2R trade is a +2R trade whether you risked $10 or $1,000, and whether it was BTC or a small altcoin.
• It survives changes in size. As your account grows or shrinks, your dollar risk changes, but R stays on the same scale.
• It shows discipline. If your losses cluster around −1R, you honour your stops. Losses at −1.5R and −2R show where you don't.
• It separates skill from size. A big dollar month can come from one oversized trade. Your average R shows whether the underlying trades were good.

Fees and R

Most traders work out R from the price risk only (entry to stop, times size) and use their net P&L, after fees. That means a clean stop-out usually shows as slightly worse than −1R.

For example, a 0.015 BTC long from 60,000 with a stop at 59,400 risks $9.00 on price. With 0.055% fees each way, a stop-out actually loses about $9.99, which is −1.11R. That's normal, and it's useful: it shows exactly how much fees cost you in R on every trade. Funding on longer holds pushes it further (see how funding rates work).

The numbers that matter

Once your trades are in R, three numbers tell you most of what you need to know.

Average R per trade (expectancy)

Expectancy = total R ÷ number of trades

If 20 trades add up to +6R, your expectancy is +0.3R per trade. At a $50 risk that's about $15 per trade on average. A positive number means the strategy has paid so far; a negative one means it hasn't.

Average win and average loss in R

These show the shape of the strategy. A trend-following approach might win 35% of the time with an average win of +2.8R. A range strategy might win 60% of the time at +1.1R. Both can be profitable; see risk-reward ratio explained for how win rate and R:R fit together.

Your worst losses in R

Look at every loss worse than about −1.2R. Each one is a story: a moved stop, a missing stop, a size mistake. Cutting those out is often the quickest way to improve results without changing the strategy at all.

Getting started

1. Set a stop on every trade, so there's a defined 1R.
2. Record the initial risk at entry, before the result is known.
3. Work out R when you close: net P&L ÷ initial risk.
4. Review by setup after 20 to 30 trades: which setups have positive average R?

TradeTurtle does this automatically. It works out the risk of every trade from your entry, stop and size, shows the R of each closed trade, and breaks down average R and expectancy by setup, emotion, direction and asset.