Risk/Reward Ratio in Crypto: Why Win Rate Alone Means Nothing

"85% win rate!" sounds great until you learn that the average loss is six times the average win. Win rate on its own tells you almost nothing about whether a strategy makes money. What does is expectancy: how often you win and how much you win compared with what you lose. The risk/reward ratio is half of that equation.

Risk/reward in one line

The risk/reward ratio compares what a trade can make with what it can lose:

Risk/reward = (target − entry) ÷ (entry − stop-loss)

Entry 100, stop 95, target 107.50: you risk 5 to make 7.50, a ratio of 1.5, usually written 1.5R (or 1:1.5). R is simply the amount at risk, the entry-to-stop distance; we explain the notation in how to read a crypto signal.

Expectancy: where win rate meets risk/reward

Average result per trade, in R:

Expectancy = (win rate × average win) − (loss rate × average loss)

Three strategies:

• Wins 35% at 2R: 0.35 × 2 − 0.65 × 1 = +0.05R per trade. Loses most of the time, still slightly ahead.
• Wins 50% at 1.5R: 0.5 × 1.5 − 0.5 × 1 = +0.25R per trade.
• Wins 80% at 0.2R: 0.8 × 0.2 − 0.2 × 1 = −0.04R per trade. Wins four times out of five, slowly loses money.

The third one is what a lot of signal-group marketing looks like from the inside.

The break-even win rate

For a fixed target and stop, the win rate you need just to break even (before fees) is 1 ÷ (1 + R):

Target	Break-even win rate
1R	50%
1.5R	40%
2R	33%
3R	25%

Check a strategy against this table before anything else. A 40% win rate is a loss at 1R and a profit at 2R.

The high-win-rate trap

Tiny targets and wide stops produce gorgeous win rates. Most trades drift a little way in your favor at some point, so a small target gets hit often, while the rare loss at a distant stop wipes out many wins at once.

We fell for a version of this ourselves. An early version of Cruxlee's rules hit its target most of the time, and still lost money, because its targets were small and its stops wide. That's why our results are reported in R rather than as a win rate, and why every signal shows its target in R next to the stop.

Why not always aim for 3R?

Because a further target is reached less often, and trades that need longer to get there have more time to reverse. The ratio and the hit rate trade off against each other, and the right balance depends on the strategy.

When we compared targets for our own rules, a closer 1.5R target meant more trades reached it, and overall results were about the same or a little better than at 2R, with more trades ending in profit. That matters more than it sounds: a smoother ride is what keeps people following the rules through a losing streak.

Fees take a cut of every R

A round trip costs something like 0.1% of the position on spot. With a stop 2% away, that's 0.05R per trade, every trade. With a stop 0.5% away it's 0.2R per trade, enough to turn a decent strategy into a losing one. Tight stops and small targets don't only change the ratio, they make the costs much bigger in R terms. (This is a big part of why our signals run on the 4-hour chart.)

Keep score in R

If you journal your trades, record each result in R: +1.5R, −1R, +0.4R. It makes trades on different coins and with different sizes comparable, shows your real expectancy after a few dozen trades, and stops one big dollar win from hiding a bad habit.

The takeaway

Ignore win rates quoted on their own. Ask for wins and losses in R, check the win rate against the break-even table, and remember that the most comfortable-looking numbers (very high win rates) often hide the worst ratios. When a signal provider shows you every result in R, you can do this math yourself, which is the whole idea behind publishing every result.