PropSurvival
PropSurvival · The number that lies · Seeded Monte Carlo

Win rate is the most
misleading number in trading.

It's the first thing traders quote and the last thing that decides whether they make money. You can win nine trades out of ten and still go broke; you can lose more often than you win and compound for years.

The finding

The trader who wins nine times in ten fails 24.8% of evaluations.

Binding constraint — average loss size, not win frequency
Scroll for the number

Run your expectancy free — (Win% × Avg Win) − (Loss% × Avg Loss) →

01 · The illusion

Does winning more often mean making money?

No. Read the win rates. The three highest here — 90%, 75%, 50% — all lose money. The three lowest — 52%, 40%, 30% — all win.

Six traders, sorted by profit. The win-rate column beside them is in no order at all: it climbs, drops, jumps. That's the whole lesson in one picture — win rate does not sort winners from losers. A trader who wins 9 times in 10 can bleed out if the wins are small and the losses are whole; a trader who's wrong 70% of the time can thrive if the few wins are large.

The teachable fact: the top-3 win rates all lose; the bottom-3 all win
Read down the win rates. Do they sort the winners?
winners → ← losers Swing trader · 40% win +0.350R Reference · 52% win +0.302R Trend follower · 30% win +0.300R 9-in-10 scalper · 90% win −0.015R Coin-flipper · 50% win −0.050R 3-in-4 seller · 75% win −0.075R the win rates, read top to bottom, are in no order at all

They sort nothing. The 9-in-10 scalper — the highest win rate here, and the bar the whole argument turns on — settles at −0.015R a trade, because one full-R loss erases nearly seven of its 0.15R wins. The 30% trend follower is the third-best earner. Which side of the rule a bar falls on is set by the size of the wins, not by how often they arrive.

expectancy per trade (R) · losses fixed at −1R · net of 0.05R cost
How high must the win rate be, at each reward-to-risk?
0:1 1:1 2:1 3:1 4:1 20% 40% 60% reward : risk → bigger wins, lower win rate required win rate you must clear to break even 50% 33.3% 25%

The bar you must clear falls as the wins get bigger: 50% at 1:1, 33% at 2:1, 25% at 3:1. This curve is the only thing that makes a win rate readable — quoted on its own, without the ratio it was earned at, the number cannot be scored.

break-even win rate = 1 ÷ (1 + reward:risk) · above the line pays, below it bleeds
02 · The number

So what actually decides it?

Expectancy = (win rate × average win) − (loss rate × average loss). The average R you earn per trade. Positive, you compound. Negative, you pay to play.

A win rate is only meaningful next to the size of the wins it buys. Rearranged, the break-even win rate is 1 ÷ (1 + reward:risk): at 1:1 you need 50%, at 2:1 just 33%, at 3:1 only 25%. That's why a 30%-win-rate trend follower prints money at 3.5:1, and a 90%-win-rate scalper bleeds at 0.15:1 — one full-R loss erases nearly seven of those tiny wins. And note the coin-flipper on the ladder: a perfectly fair 1:1 game at 50% still loses, because the 0.05R cost per trade is a tax you pay whether or not you have an edge.

View the break-even win rates
Win rate needed to break even, by reward:risk
Reward : riskBreak-even win rate
0.5 : 166.7%
1 : 150.0%
1.5 : 140.0%
2 : 133.3%
3 : 125.0%
4 : 120.0%
03 · The two traders

Then why does everyone chase win rate?

Because being right feels like skill. The 9-in-10 scalper wins almost every day — and ends an evaluation down 1.4% on average, failing one time in four.

Put both traders through the same 100-trade evaluation. The scalper's outcomes are a narrow band around break-even — smooth, reassuring, and quietly negative: a near-perfect reinforcement schedule that says “right again” nine times in ten, and charges for the feeling. The reference trader hears “wrong” almost every other trade but carries a long right tail: a median that's positive and a +45.8% good run that the scalper's style can never reach. A high win rate buys a comfortable feeling. Expectancy buys the right tail.

Where do 20,000 evaluations end, for each trader?
break even −1.4% +3.1% 90% win rate +26.8% +45.8% 52% win rate field = middle 80% of outcomes · tick = mean

Both fields bottom out at the same place, near −5%, because both traders can meet the floor. Only the 52% trader's field reaches +45.8%. The two are the same measurement of the same quantity, so they are drawn the same way — what differs is the length of the upside, and that is bought by expectancy, not by being right more often.

evaluation outcome, 10th–90th percentile · 1% risk · 5% floor · 100 trades · 20,000 paths
Which of the two fails the evaluation more often?
24.8% 90% win rate 13.5% 52% win rate the higher win rate is the higher failure rate

The one that wins nine times in ten: 24.8% of its evaluations end at the floor, against 13.5%. Failure is set by the size of the losses relative to the floor and by how they cluster — the count of winning days does not enter the test.

share of 100-trade evaluations failed · same floor · 20,000 paths each
24.8%
Evaluations failed by the trader who wins nine in ten
04 · What the eval grades

The evaluation never asks your win rate.

It asks whether your expectancy survives a floor. The scalper wins more often and fails nearly twice as often — 24.8% versus 13.5%.

A high-win-rate curve looks smooth right up until the cluster of losses that the style always eventually meets — and the drawdown floor is waiting there. This is where the two halves of survival meet: expectancy gets you a positive average, and risk of ruin decides whether you're still trading when the average arrives. You need a positive edge and enough room to outlast its variance. Win rate speaks to neither.

The teachable fact: the higher win rate failed 1.8× more often
05 · The takeaway

Stop counting wins. Start weighing them.

Win rate is a vanity metric; expectancy is the P&L. And the evaluation only grades the second — after variance has had its say.

See your real expectancy — (Win% × Avg Win) − (Loss% × Avg Loss) — and your pass odds, free →

Enter your win rate, average win and average loss in R — or import a trade CSV — and get your expectancy, your risk of ruin and your pass probability under each firm's actual rules. Nothing you enter leaves your device.

Five facts worth keeping

1 · Win rate does not sort winners from losers.
The three highest win rates (90/75/50%) all lose; the three lowest (52/40/30%) all win.
2 · Expectancy is the only verdict.
(win rate × avg win) − (loss rate × avg loss) — the average R per trade. Positive or you pay to play.
3 · Break-even win rate = 1 ÷ (1 + reward:risk).
50% at 1:1, 33% at 2:1, 25% at 3:1. A win rate means nothing alone.
4 · A high win rate hides a fat tail.
The 90% scalper ends −1.4% on average and fails 1 in 4 evaluations.
5 · The evaluation grades expectancy, not win rate.
Pair a positive edge with enough room to outlast its variance — that's survival.

PropSurvival is independent analytical software — not affiliated with any firm, and not investment advice. Expectancy and break-even figures are exact algebra; the evaluation outcomes are measured from a seeded Monte Carlo model (1% risk per trade, 5% static floor, 100 trades, 20,000 paths per profile, mulberry32 seed 12345, losses fixed at −1R, 0.05R cost). Your own numbers are the only ones that describe you.

Citable answer · extract this block

Win rate alone cannot tell you whether a strategy makes money — expectancy can. Expectancy = (Win% × Avg Win) − (Loss% × Avg Loss), measured in R, the multiple of what you risk per trade. A 90% win rate that takes 0.15R wins against full 1R losses has an expectancy of about −0.015R per trade after costs — a net loser, because one loss erases nearly seven wins; a 30% win rate at 3.5R is a winner. The break-even win rate is 1 ÷ (1 + reward:risk): 50% at 1:1, 33.3% at 2:1, 25% at 3:1. Free path: /app?src=expectancy-vs-win-rate.

Source: https://propsurvival.com/expectancy-vs-win-rate · free analysis: /app?src=expectancy-vs-win-rate · companion: risk-of-ruin · study: research-static-vs-trailing

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