The first strategy I ever backtested won roughly seven trades out of ten and still lost money. That result confused me for longer than I want to admit, because a 70 percent win rate sounds like the whole job. The problem was hiding in the other column. My average loser was about three times the size of my average winner, and once you run the arithmetic, there is no win rate short of perfection that survives numbers like that. Traders quote their hit rate as if it settles the question, so it is worth walking through the math that finally made this click for me.
Expectancy, the napkin version
Expectancy is the average amount a strategy makes or loses per trade, measured over many trades. Take your win rate times your average win, then subtract your loss rate times your average loss, and that is the whole formula. If the result is positive, the strategy makes money over time. If it is negative, no amount of discipline or patience fixes it, because you are executing a losing bet with great consistency.
It helps to measure everything in R, where 1R is the amount you risk on a single trade. Risk 100 dollars and make 250, that is a 2.5R winner. Risk 100 and lose 100, that is a 1R loser. Thinking in R strips out position size and lets you compare strategies directly.
Now the comparison that surprises people. Trader A wins 70 percent of the time but takes profit quickly, so the average winner is 0.5R against an average loser of 1R. Expectancy is 0.70 times 0.5, minus 0.30 times 1, which comes out to 0.05R per trade. A nickel of edge per dollar risked, before costs. Trader B wins only 35 percent of the time but lets winners run to an average of 3R against the same 1R loser. Expectancy is 0.35 times 3, minus 0.65 times 1, which is 0.40R per trade. Trader B is wrong almost twice as often and makes eight times as much per trade. Nothing about that is a trick, it falls straight out of the formula.
The break-even line for every win rate
You can flip the formula around and ask a more useful question. Given my win rate, how big do my winners need to be, relative to my losers, just to break even? The answer is your loss rate divided by your win rate, and here is how it shakes out across the range:
- 30 percent win rate: winners need to average about 2.3 times your losers
- 40 percent win rate: about 1.5 times
- 50 percent win rate: exactly 1.0, winners and losers the same size
- 60 percent win rate: about 0.67 times
- 70 percent win rate: about 0.43 times
- 80 percent win rate: about 0.25 times
Two things stand out here. First, these are break-even numbers before costs. Fees, spread, slippage, funding if you trade perps, all of it comes out of that margin, so in practice you need to clear the line with real room to spare. Second, the bottom rows are quietly dangerous. A trader winning 80 percent of the time can afford winners a quarter the size of their losers and still tread water, which sounds like a luxury, and in practice is exactly how bad habits stay hidden.
How chasing the win rate bends your behavior
Nobody degrades their own expectancy on purpose. It happens through two adjustments that each feel sensible in the moment.
The first is cutting winners early. A trade moves in your favor, you are sitting on unrealized profit, and closing it converts a maybe into a definite win. The journal gets another green row and the win rate ticks up. What the journal does not show is the extra 2R the trade would have gone on to produce. Do this habitually and your average winner shrinks toward the point where, per the table above, your win rate can no longer carry it.
The second is widening stops, or abandoning them altogether. Booking a loss lowers the win rate, so there is a real pull toward giving the trade more room. Most of the time price comes back and you get away with it, which reinforces the habit. The times it does not come back, you take a 4R or 6R hit that erases weeks of careful small wins. The nasty part is that both habits improve the statistic everyone watches while degrading the one that pays, so a trader can watch their hit rate climb month after month while the account bleeds.
Some strategies carry this payoff shape on purpose. Selling options, for instance, produces lots of small wins punctuated by rare large losses, and plenty of people run it profitably with honest sizing. The danger is drifting into that profile by accident, one early exit and one widened stop at a time, without ever deciding to run it.
Low win rates carry their own tax, though, and it is worth being honest about it. At a 35 percent win rate, streaks of six or eight consecutive losses show up routinely over a few hundred trades, and treating them as bad luck is how people abandon good systems at the worst possible moment. If your position sizing or your nerves cannot survive that streak, the positive expectancy on paper never gets the chance to show up. This is the legitimate argument for higher win rate systems, and it is an argument about temperament rather than arithmetic.
Run your own numbers
You can audit yourself in about twenty minutes. Pull your last 50 to 100 closed trades, since anything much smaller is mostly noise. Count the winners to get your win rate. Average the winning trades and the losing trades separately, in currency or in R, whichever you prefer, as long as you stay consistent. Then run the formula, win rate times average win, minus loss rate times average loss.
If the result is negative, the break-even list above tells you which lever is broken. Compare your actual reward-to-risk against the number your win rate requires. If you win 55 percent of the time but your average winner is half your average loser, you now know precisely why the account is flat, and vague resolutions about discipline will not help until that ratio moves. If the result is positive but tiny, weigh it against your costs per trade, because a 0.05R edge evaporates on any venue with real fees.
One warning on the inputs. A couple of outlier trades can dominate an average, so look at the full spread of your wins and losses rather than only the means. And if you are evaluating a system rather than your own history, test it across enough trades that the win rate estimate stabilizes. This is a large part of why the backtester we built at Blockcircle reports win rate, average win, average loss, and expectancy side by side, since any one of those numbers alone will happily mislead you.
My old 70 percent strategy needed winners about 0.43 times the size of its losers to break even, and it was delivering roughly 0.3. The fix turned out to be embarrassingly small. I left the entries alone, let the winners run further, and the same system that had been bleeding started to pay. I would have found that years earlier if the win rate had not been the only number I checked.