Break-even win rate: what your reward:risk and costs demand
Educational only, not financial advice. Simulations and backtests are models, not promises. Check every rule with your own firm.
Every strategy has a win rate it must beat just to break even. Costs push that number up, and tight stops push it up further. Here is how to work it out, and how sure you can be that you beat it.
The formula
Measure everything in R, the amount you risk per trade. A win pays b R (your reward:risk), a loss costs 1 R, and every trade pays costs of c R (spread, commission and slippage ÷ the dollar risk). With win rate p, the expectancy per trade is
E = p × b − (1 − p) − c
Set E to zero and solve for p:
break-even win rate = (1 + c) ÷ (1 + b)
The table
| Reward : risk | No costs | Costs 0.05R | Costs 0.10R |
|---|---|---|---|
| 0.5 : 1 | 66.7% | 70.0% | 73.3% |
| 1 : 1 | 50.0% | 52.5% | 55.0% |
| 1.5 : 1 | 40.0% | 42.0% | 44.0% |
| 2 : 1 | 33.3% | 35.0% | 36.7% |
| 3 : 1 | 25.0% | 26.3% | 27.5% |
A 1:1 strategy that wins 52% of the time looks like an edge. After 0.05R of costs it loses money.
Costs in R: why tight stops are expensive
Costs are roughly fixed per trade in dollars, but your risk depends on the stop. So the same cost is a bigger share of R when the stop is tight.
Example on EUR/USD, where one standard lot is worth $10 a pip: assume a 1-pip spread and $7 round-trip commission, so about $17 per lot. With a 10-pip stop you risk $100 per lot, so c = $17 ÷ $100 = 0.17R, and a 1:1 trade needs a 58.5% win rate to break even. With a 30-pip stop you risk $300 per lot, c ≈ 0.057R, and break-even falls to about 52.8%. Your own spread and commission will differ; plug them in.
That’s why scalping on a prop account is hard. It isn’t impossible, but the edge per trade has to clear a much higher bar.
A worked expectancy
Say you win 45% of trades at 1.5:1 with 0.05R costs. Then E = 0.45 × 1.5 − 0.55 − 0.05 = +0.075R per trade. Break-even at those settings is 42%, so you’re 3 points above it. Risking $200 per trade, that’s $15 per trade on average, so a $3,000 target needs about 200 trades. The days-to-target calculator turns that into days and shows the spread around the average.
A higher win rate is not an edge
You can raise your win rate by moving the target closer or the stop further away. If the market gives you no edge, the reward:risk falls by exactly enough to keep the expectancy at zero, before costs. That’s the optional stopping theorem, explained in stops and targets can’t create an edge. The only number that matters is how far your win rate sits above the break-even for your own reward:risk and costs.
How sure can you be?
A measured win rate is an estimate with noise. Its standard error is √(p × (1 − p) ÷ n) for n trades. If you won 55% of 100 trades at 1:1, the rough 95% range is 55% ± 9.8%, about 45% to 65%. That range includes break-even (52.5% with 0.05R costs) and plenty of losing results. With 400 trades it narrows to about 50% to 60%, and even 1,000 trades leaves about 52% to 58%.
In practice, a small edge takes hundreds of trades to confirm. Results from a few dozen trades, or from one passed challenge, prove very little either way.
Using it in a challenge
- Work out your break-even with your real costs before you pick a stop size.
- Put your win rate, reward:risk and costs into the pass-odds calculator. Below break-even, smaller risk lowers your pass odds; above it, smaller risk raises them.
- Read expectancy in the glossary and position sizing for prop challenges for what to do with the number.