A lot of newer traders judge a system by win rate alone — “it wins 70% of the time, must be good.” That’s an incomplete read, and it’s exactly why some 70%-win-rate systems bleed money while a 35%-win-rate system prints steadily. The three numbers that need to be read together are win rate, risk-reward ratio, and expectancy. Leave one out and you’re grading on incomplete information.
Win rate: it’s not the whole story
Win rate is the percentage of trades that close positive. Simple, intuitive, and the most misleading of the three on its own. The problem: win rate says nothing about how much you make when you win versus how much you lose when you lose. A system with an 80% win rate where each loser costs 5x a winner can still bleed the account steadily — two losses out of ten is enough to wipe out the gains from the other eight.
Win rate is useful next to risk-reward, not standing alone. It’s also why newer traders get pulled toward “high win rate” strategies — martingale, uncontrolled grid trading — without noticing the tail risk quietly building underneath.
Risk-reward ratio: what you’re staking to win what
Risk-reward ratio (R:R) is the relationship between what you stand to lose (entry to stop loss) and what you stand to gain (entry to take profit). A 1:3 ratio means risking $100 for a shot at $300. This number matters because it sets the minimum win rate you need just to break even — at 1:3, you only need to win above 25% of trades to break even before fees; at 1:1, you need above 50%.
The catch: your planned R:R and your realized R:R often diverge, because traders tend to close winners early on small gains (afraid of giving profit back) or push stops further out while losing (reluctant to accept the loss). Logging the actual R-multiple of every trade is the only way to see how far your real ratio has drifted from what’s written in the plan.
Expectancy: the number that decides if a system is worth running
Expectancy answers the one question that actually matters: on average, per trade, does this system make or lose money? The formula:
Expectancy = (Win rate × average R won) − (Loss rate × average R lost)
Example: 40% win rate, average winner 2.5R, 60% loss rate, average loser 1R. Expectancy = (0.4 × 2.5) − (0.6 × 1) = 1.0 − 0.6 = +0.4R per trade. This system loses more often than it wins by trade count, but still has a real edge because winners are so much bigger than losers.
Now compare a system with a much higher win rate: 75% win rate, average winner 0.5R, 25% loss rate, average loser 2R. Expectancy = (0.75 × 0.5) − (0.25 × 2) = 0.375 − 0.5 = −0.125R per trade. This system wins far more often but has negative expectancy — the more you trade it, the more steadily you lose. That’s the exact trap win rate alone can’t catch.
Using all three together
The practical routine: every week or month, calculate all three from your journal, broken out by setup rather than lumped across the whole account. An account showing positive overall expectancy can be hiding one badly negative setup propped up by one strongly positive one — pooled together, you have no way to know which setup to cut and which to keep.
Optimize for expectancy first, not win rate. Chasing a higher win rate without watching R:R usually means stops get pulled too tight or profits get taken too early — both quietly shrink expectancy even as the win rate looks better on the report. A system with stable positive expectancy at a 35-45% win rate is worth running far longer than a 70%-win-rate system with negative expectancy.
More on this in the Trading performance section.