Win Rate vs Expectancy
Win rate measures frequency, expectancy measures profit
Win rate is how often a strategy is right. Expectancy is how much it makes per trade on average. They are different numbers, and only one of them decides whether an account grows. A strategy can win most of its trades and still lose money, and it can lose most of its trades and still make money. The difference is the size of the wins against the size of the losses.
Watch: Part 7 of the Volatility Box onboarding series.
“I win 60% of my trades but still lose money”
This is the most common version of the problem, and the win rate is not the cause. If the account bleeds at a 60% hit rate, the wins are too small relative to the losses. That is the profile tight stops and thin targets produce: many small winners given back by a handful of larger losers. The fix is not winning more often; it is changing the size of the average win against the average loss.
This is why the backtester surfaces expectancy and profit factor alongside win rate. Expectancy is the average dollars a setup makes per trade; a positive number means it adds to the account on average. Profit factor is total dollars won divided by total dollars lost; above one means more was won than lost across the whole sample. A setup can win under half its trades and still post a profit factor well above one, because its winners are bigger than its losers. Win rate is context. Expectancy and profit factor are the verdict, and they are why a roughly even hit rate is acceptable for the Volatility Box approach.
The two metrics
Win rate
Win rate is the share of trades that reach the target before the stop. Divide winning trades by total trades. Sixty winners out of 100 trades is a 60% win rate. It is easy to calculate, which is why traders reach for it, but it says nothing about the size of those wins and losses.
Expectancy
Expectancy is the average profit or loss per trade. It folds the win rate and the relative size of wins and losses into one number, the dollars you can expect per trade over a large sample. The formula multiplies the win rate by the average win, then subtracts the loss rate times the average loss:
(win rate × average win) − (loss rate × average loss)
At a 60% win rate, a $150 average win, and a $200 average loss: (0.60 × $150) − (0.40 × $200) = $90 − $80 = $10 per trade. Positive, so the strategy makes money on average despite the larger losses, because it wins often enough to cover them.
The same win rate, opposite outcomes
Two strategies show how far apart frequency and profit can sit. The numbers below are illustrative, chosen to make the math visible.
High win rate, negative expectancy
A strategy wins 68% of 150 trades, with a $85 average win and a $210 average loss. Winning more than two of every three trades looks strong. The expectancy says otherwise: (0.68 × $85) − (0.32 × $210) = $57.80 − $67.20 = −$9.40 per trade. Across 150 trades that is roughly −$1,410, a losing strategy at a 68% hit rate. The cause is the loss being 2.5 times the win. The few large losses erase the many small wins. This is the profile tight stops build: the stop is close enough to lift the win rate, but it turns the risk-reward against you.
Low win rate, positive expectancy
A strategy wins 44% of 150 trades, with a $280 average win and a $120 average loss. Losing more often than winning feels like a failing system. The expectancy: (0.44 × $280) − (0.56 × $120) = $123.20 − $67.20 = +$56 per trade, roughly +$8,400 across 150 trades. The winners run more than twice the losers, so the larger wins more than cover the more frequent losses. This is the profile the Volatility Box approach is built around: an even-or-lower hit rate carried by winners that outrun losers.
Risk-reward sets the win rate you need
The win rate required just to break even is fixed by the risk-reward ratio. At 1:1, risking $100 to make $100, breakeven is a 50% win rate. At 1:1.5, risking $100 to make $150, breakeven drops to 40%. Improve the reward against the risk and the required win rate falls, which makes profitability easier to reach. Push the ratio the wrong way and it climbs: a 2:1 ratio, risking $200 to make $100, needs a 67% win rate just to break even, and 3:1 needs 75%. Tight stops with thin targets create exactly those unfavorable ratios, which is how a high-win-rate strategy ends up losing money. Knowing the breakeven win rate for a given ratio shows whether a strategy is even mathematically reachable before you trade it.
Reading it in the backtester
On any backtest, the two headline numbers to weigh are expectancy and profit factor. A positive expectancy means the setup makes money per trade on average; a profit factor above one means more dollars were won than lost. Both green is the combination to look for, alongside an equity curve that climbs steadily up and to the right rather than bleeding lower. The same name can flip from one profile to the other when you change the model: switching a name from aggressive to conservative, or daily to hourly, can move a negative profit factor above one. Compare setups by expectancy and profit factor rather than sorting for the highest win rate, since the highest win rates often come with the poorest risk-reward.
Calculating your own expectancy
Pull your last 50 trades from your journal or broker statements. Real trades, not a backtest, show how the approach performs with live execution and the decisions that go with it. Divide winners by total trades for the win rate. Average the winners for the average win, and average the losers, as positive numbers, for the average loss. Then apply the formula: (win rate × average win) − (loss rate × average loss). If the result is negative, the strategy loses money over time no matter how disciplined the execution, and the risk-reward or setup selection needs to change before continuing. A small positive number that does not clear costs is the same warning in a quieter form.
Related
Was this article helpful?
Still need help?
Can't find what you're looking for? Our support team is here to help.
Contact Support