Required reward-to-risk ratio to break even at any win rate
The single most underrated number in retail trading is the break-even reward-to-risk ratio — the smallest R:R your wins need to cover your losses, given your win rate. Below it, the strategy bleeds money no matter how often it's right. Above it, the strategy makes money before you've added a single point of edge above pure geometry.
The math is one line:
Break-even R:R = (1 − win rate) / win rate
A 50% win rate needs at least 1:1. A 60% win rate needs about 1:0.67. A 30% win rate needs at least 2.33:1. Below the line your expectancy is negative; above it, positive. Use the calculator to see the curve at your current win rate, and to plan the R:R targets a strategy needs to be viable at the win rate you can realistically hit.
Break-even R:R calculator
Why this number is the floor
Break-even R:R isn't a strategy choice — it's a constraint your strategy has to satisfy before you can talk about edge at all. A strategy that wins 60% of the time with 1:1 R:R sounds great until you do the expectancy math: (0.6 × 1) − (0.4 × 1) = +0.20R per trade, which is positive. But the same strategy at 1:0.6 R:R: (0.6 × 0.6) − (0.4 × 1) = −0.04R per trade — meaning the strategy loses money even though it wins 6 times out of 10.
The break-even line is where positive crosses negative. Below it, more trading digs the hole faster. Above it, time and trades are working in your favour.
What the curve shows
The shape of the break-even curve is hyperbolic — it drops fast as win rate climbs, then flattens out. From 30% to 40% win rate, required R:R drops from about 2.33:1 to 1.5:1 — a meaningful improvement. From 70% to 80%, required R:R drops from about 0.43:1 to 0.25:1 — a smaller absolute change, but the trader is now operating in territory where commissions and slippage dominate the small target sizes.
Two regimes that almost everyone underrates:
- Low win rate, high R:R (trend-following). Required R:R is large but achievable on real moves. The challenge is psychological — you live through long sequences of small losses for occasional large wins. Most retail traders quit before the wins arrive.
- High win rate, tight R:R (mean-reversion). Required R:R is small but the trades are quick, frequent, and structurally vulnerable to costs. A strategy at 80% wins with 0.25:1 nominal R:R has almost no margin above the 0.10-0.15% retail cost floor — the strategy works on paper and fails live, regularly.
The middle zone (50-65% win rate, 0.7-1:1 R:R) is where most working retail strategies live. Not because it's optimal, but because it's the regime where commissions don't dominate, edge doesn't need to be enormous, and the equity curve is smooth enough to stay with.
How to use this in practice
The curve is a planning tool, not a trade-execution tool. When you're designing or evaluating a strategy:
- Estimate your achievable win rate honestly — most retail traders overestimate their own win rate by 5-15 percentage points. Use a real sample (300+ trades) when possible. The win-rate confidence interval calculator gives you the band the true rate could be hiding inside.
- Read the required R:R off the curve at the lower end of your confidence interval, not the middle. If your sample says "70% ± 8%", plan for 62% — required R:R 0.61:1 — not 70%.
- Set targets accordingly. If your strategy's structure can't deliver R:R above the required line at your honest win rate, the strategy doesn't have the edge it needs and either the targets need widening or the win rate needs improving.
For the deeper math of how this interacts with sample size, costs, and the broader trade-off curve, the related blog posts on stop-loss placement and why-traders-lose-money cover the full picture.
FAQ
Where does this formula come from?
From the per-trade expectancy equation. Expected value = (Win rate × avg win) − (Loss rate × avg loss). Setting expected value to zero and solving for the win/loss ratio gives the formula: required R:R = loss rate / win rate = (1 − p) / p. The math is the same regardless of asset class; this is general statistics applied to trading.
Does this account for commissions and slippage?
No — this is the pre-cost break-even line. To include costs, treat them as widening the loss size. For typical retail crypto perp costs (0.10-0.15% round trip), add 0.10-0.15% of position size to the average loss. The required R:R nudges up by a few percent. The cost-floor analysis is in the related blog post on minimum edge.
What's the right way to compare strategies on this?
Calculate net edge (actual R:R − required R:R) at each strategy's honest win rate. The strategy with more net edge wins, regardless of which one has the higher headline R:R. A strategy at 60% win rate, 1.2:1 actual R:R has net edge 0.53R; a strategy at 35% win rate, 2.5:1 actual R:R has net edge 0.64R — the second strategy is better despite the lower win rate.
Why does the curve drop so steeply between 10% and 30% win rate?
Because the function is hyperbolic — (1−p)/p — which is dominated by the 1/p term at small p. From 10% to 20% win rate, required R:R drops from 9:1 to 4:1 — a much bigger absolute reduction than from 70% to 80% (0.43:1 to 0.25:1). The implication is that even small improvements in win rate at low win rates dramatically loosen the R:R constraint.
Can I just set my targets at 2:1 and trade anything?
Only if your win rate stays above 33%. Below that, 2:1 isn't enough — you'd need 2.5:1 at 28%, 3:1 at 25%, etc. Setting fixed targets without knowing your win rate is the most common way retail strategies end up with negative expectancy without realising it.
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