Win rate vs risk-reward ratio: which one actually makes you profitable

Ask ten traders what makes a trading strategy profitable and most will say "a high win rate." Ask the next ten what they actually track in their journal and the answer is the same. It feels obvious. Winning more often than you lose has to be good, right?

It isn't. A 90% win rate strategy can be wildly unprofitable, and a 30% win rate strategy can be one of the best things you'll ever trade. The reason is a single equation that almost no losing trader can write down from memory.

This article walks through that equation, the two numbers that feed into it, and why looking at either one alone will lie to you.

The two numbers

Every trading strategy can be reduced to two numbers:

Win rate is the percentage of your trades that finish in profit. If you take 100 trades and 55 of them are winners, your win rate is 55%.

Risk-reward ratio (often written R/R or R:R) is the size of your average winner divided by the size of your average loser. If your average winning trade makes $200 and your average losing trade loses $100, your risk-reward ratio is 2:1, sometimes written as just "2R."

These two numbers are independent of each other. A strategy can have any combination: high win rate with low R/R, low win rate with high R/R, or anything in between. Neither one tells you whether a strategy is profitable on its own. You need both.

The equation that ties them together

The number that actually matters is called expectancy. It tells you how much you can expect to make (or lose) per trade on average, expressed in units of your risk.

The formula is simple:

Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss)

Where loss rate is just 1 − win rate. If you express the average win as a multiple of the average loss (the R/R), it gets even cleaner:

Expectancy (in R) = (Win Rate × R/R) − Loss Rate

A strategy with positive expectancy makes money over a large enough sample. A strategy with negative expectancy loses money, no matter how good it feels in the short run. Zero expectancy is breakeven before commissions, which means it's a loser once you include costs.

Four real examples

Let's plug in actual numbers and see what falls out.

Example 1: The high-probability scalper 70% win rate, 1:1 risk-reward.

Expectancy = (0.70 × 1) − 0.30 = +0.40R per trade

Risk $100 per trade and you average $40 profit per trade. Take 100 trades and you're up around $4,000 before commissions. Solidly profitable.

Example 2: The trend-follower 30% win rate, 4:1 risk-reward.

Expectancy = (0.30 × 4) − 0.70 = +0.50R per trade

You lose 70% of the time, but the 30% of trades that work pay you four times what each loss costs. Risk $100 per trade and you average $50 per trade. Slightly more profitable than the scalper above, despite winning less than half as often.

This is why trend-following systems work even though they feel awful. The math just needs the wins to be big enough.

Example 3: The flat strategy 50% win rate, 1:1 risk-reward.

Expectancy = (0.50 × 1) − 0.50 = 0R per trade

You go up, you come back down, you pay commissions, you go broke slowly. This is where most "I just need a slightly better entry" traders live.

Example 4: The trap most retail traders fall into 70% win rate, 0.5:1 risk-reward (cutting winners early, holding losers hoping for a recovery).

Expectancy = (0.70 × 0.5) − 0.30 = +0.05R per trade

That's almost zero. Now subtract commissions and slippage and you're underwater. The 70% win rate makes you feel like a great trader. The R/R quietly bleeds you out. Nine winners in a row build false confidence; one outsized loser undoes them all.

This is the most common pattern in unprofitable retail trading: a high win rate that feels great, hiding a risk-reward ratio that makes the whole system negative-expectancy.

The trade-off you can't escape

Here's the part nobody mentions in trading courses: win rate and risk-reward usually move in opposite directions.

If you take profit at 1R you'll hit your target more often than if you wait for 3R, because the market only has to move a third as far in your favor. Tighten your target → win rate goes up, R/R goes down. Loosen your stop → win rate goes up (less chance of getting stopped out by noise), R/R goes down (your average loss is bigger).

Every adjustment trades one for the other. There's no setting where both go up at the same time on the same strategy. The job is to find a combination where the math works in your favor by enough margin to survive a bad streak, and then to actually let it run.

This is also why you can't copy someone else's strategy by mimicking their win rate alone. A trader with a 40% win rate isn't worse than one with 60%. They might be running a much better R/R and making more money per trade. The numbers only mean anything together.

The compounding problem nobody warns you about

So far we've been talking about per-trade expectancy. There's a second thing the math hides: variance.

A strategy with positive expectancy still has losing streaks. Sometimes long ones. With a 30% win rate strategy, the probability of losing 5 trades in a row is about 17%. Losing 8 in a row is about 6%. Losing 10 in a row, around 3%. Take a few hundred trades and a 10-loss streak is almost guaranteed to happen at some point.

This means a positive-expectancy strategy can still blow your account if you size each trade too large relative to your capital. A 3% risk per trade, ten losses in a row, is around 26% drawdown. At 5% per trade, the same streak puts you down 40%. At 10% per trade, you're down 65%. Almost unrecoverable.

The math you actually need is:

1. Expectancy positive enough to overcome commissions and slippage
2. Position size small enough to survive your worst realistic losing streak
3. Discipline tight enough to actually take every signal, including the ones that come right after a string of losses

Drop any one of those three and the equation collapses. This is also why most automated and discretionary strategies fail in real money even when they backtested fine. The trader either oversized or skipped the trades that came after losses, both of which break the assumptions the math is built on.

How to actually measure your own numbers

You can't optimize what you don't track. To know your win rate and R/R you need a record of:

• Every trade you took (including the ones that scratched, not just the ones that hit a target)
• The size of each winner and loser in dollars
• Ideally, the strategy or setup tag for each trade so you can split the numbers per setup instead of mashing everything together

A trade journal (a spreadsheet, a notebook, or a tool like Tradavity) is what makes this possible. The act of logging every trade forces you to be honest about what your actual win rate is (almost always lower than you remember) and what your actual R/R is (almost always worse than you think, because the wins you cut early don't count toward the average).

Once you have 50–100 trades on a setup, plug the numbers into the expectancy equation. If it's positive enough to cover costs and survive your worst drawdown, the strategy is worth keeping. If it's not, no amount of grinding will save it. You need to change the entry, the exit, or the position size.

The takeaway

Win rate alone tells you almost nothing. Risk-reward alone tells you almost nothing. Expectancy is the number that decides whether you make money or not, and you need both inputs to calculate it.

Most unprofitable traders are unprofitable because they fixated on the win rate (the part that feels good) and let the risk-reward quietly destroy them. The fix is boring: log every trade, calculate both numbers honestly, run the math, and only then decide whether to change your strategy or your size.

That's it. That's the whole thing.