Win Rate vs Risk-to-Reward: The Simple Math That Decides Whether Your Strategy Makes Money
Two traders take 100 trades. Both risk $100 each time.
Trader A wins 70 trades but makes only $50 on each winner. Trader B wins 40 trades but makes $200 on each winner.
Who comes out ahead? Most beginners would point to Trader A: winning 70 times sounds much better than winning 40. But a trade is not just a win or a loss. The size of each outcome matters.
Let's follow the money. By the end, you'll be able to calculate the win rate a strategy needs to break even, read its expectancy, and spot when a good-looking result hides a problem.
Win rate is how often you win
Win rate = winning trades ÷ total closed trades × 100
If 40 out of 100 trades are winners, your win rate is 40%. For this simple example, the other 60 are losers. A trade closed at zero is a break-even trade; when reviewing a real journal, decide consistently whether to count those separately or include them in the total.
Win rate tells you how frequently you win. It says nothing about how much you make on a winner or lose on a loser. A strategy can feel great because it wins most days, then give back those gains in a few oversized losses.
Risk-to-reward is the size of a win compared with a loss
Imagine buying at $50, setting a stop loss at $49, and placing a profit target at $52. The planned loss is $1 per share; the potential gain is $2 per share. That is a 1:2 risk-to-reward ratio: risk one unit to target two units.
In this article, 1R means the amount you planned to risk at the start of a trade. If that amount is $100, a full stop is −1R = −$100, while a full 1:2 target is +2R = +$200.
Planned ratio | Risk | Potential reward |
1:1 | $100 | $100 |
1:2 | $100 | $200 |
1:3 | $100 | $300 |
The first number is risk, the second is potential reward. Planned matters: a target is not a guaranteed exit. If you take profit early at +1.3R or a stop fills at −1.1R, those are the results your journal must record.
“I want to make 3%” does not establish a risk-to-reward ratio. A 3% price target paired with a 1% price stop is 1:3; paired with a 3% stop, it is 1:1. You need both distances, measured on the same basis.
The win rate needed to break even
Here is the useful question: If my wins are a certain size and my losses are a certain size, how often do I need to win just to cover the losses?
Assume every loss is −1R, every win reaches its stated reward, and there are no fees or other outcomes. The break-even win rate is:
Average loss ÷ (average win + average loss)
At 1:2, a win earns +2R and a loss costs −1R. One winner pays for two losers. In three trades, one win and two losses produce +2R − 1R − 1R = 0R. That is one winner out of three trades, or 33⅓%.
Reward on a win | Loss on a loss | Break-even win rate before costs |
+1R (1:1) | −1R | 50% |
+1.5R (1:1.5) | −1R | 40% |
+2R (1:2) | −1R | 33⅓% |
+3R (1:3) | −1R | 25% |
+4R (1:4) | −1R | 20% |
At 1:3, one winner pays for three losers, so one win in four trades breaks even. The table describes mathematical thresholds, not win rates that these setups will actually achieve. Fees, smaller-than-planned winners, and larger-than-planned losses raise the win rate required to break even.
Expectancy puts the two numbers together
Expectancy is the average result per trade implied by your win rate and the actual average sizes of your wins and losses.
Expectancy = (win rate × average win) − (loss rate × average loss magnitude)
Suppose 40% of trades win an average of +2R and 60% lose an average of −1R:
(0.40 × 2R) − (0.60 × 1R) = +0.20R per trade
The winners contribute +0.80R to the average; the losers subtract 0.60R. The difference is +0.20R. If 1R is a constant $100, that translates to an average of $20 per trade before costs under those assumptions.
It does not mean the next trade earns $20, or that 100 trades will earn exactly $2,000. Expectancy is an estimate based on the figures you give it. A strategy's win rate, typical win, and typical loss may change with market conditions and your execution.
Four simple 20-trade examples
To see how different combinations behave, suppose each loss is exactly −1R, each win reaches the shown reward, and costs are excluded. Every row below is a fictional 20-trade sequence.
Win rate and reward | Winners | Losers | Calculation | Net |
70% at 1:0.5 | 14 | 6 | 14 × 0.5R − 6 × 1R | +1R |
50% at 1:1.5 | 10 | 10 | 10 × 1.5R − 10 × 1R | +5R |
40% at 1:2 | 8 | 12 | 8 × 2R − 12 × 1R | +4R |
30% at 1:3 | 6 | 14 | 6 × 3R − 14 × 1R | +4R |
The 70% strategy wins often but has the smallest margin. Its break-even win rate at 1:0.5 is 66⅔%. Small changes in average results could turn that +1R into a loss. The 30% strategy loses 14 of 20 trades yet finishes +4R in this particular example. That lower win rate might also bring uncomfortable losing streaks.
The examples do not mean that a farther target automatically improves a strategy. Move a target from +2R to +3R, and fewer trades may reach it. The size of that change depends on the setup and market.
Back to our two traders: 100 trades later
Now we can answer the opening question. Assume both traders take full −1R losses and full target wins, risk a fixed $100 per trade, and pay no trading costs in this first calculation.
Trader A | Trader B | |
Win rate | 70% | 40% |
Winner / loser | +0.5R / −1R | +2R / −1R |
Wins in 100 trades | 70 × 0.5R = +35R | 40 × 2R = +80R |
Losses in 100 trades | 30 × 1R = −30R | 60 × 1R = −60R |
Net before costs | +5R = +$500 | +20R = +$2,000 |
Trader B wins 30 fewer times, yet finishes 15R ahead in this constructed example. Win rate alone would have pointed you toward the less profitable result.
Trader A's margin is thin: +5R across 100 trades equals only +0.05R per trade before costs. If round-trip trading costs averaged 0.06R per trade, the total 6R of costs would turn A's +5R into −1R net. B would retain +14R under that same simplified cost assumption. Actual costs vary by market and trade.
Position size changes dollars, not the ratio
Return to the $50 entry, $49 stop, and $52 target. With 100 shares, the plan risks $100 to target $200. With 50 shares, it risks $50 to target $100. Both trades remain 1:2 because the price distances have not changed.
That distinction matters when comparing journals. A strategy can show positive results in R while a trader still suffers a dollar loss because they risked much more on losing trades than on winning ones. To translate R results into money as simply as the tables do, assume the same dollar risk per trade. If risk changes, calculate the actual dollar P&L separately.
Why a good average can still feel difficult
Suppose six losses arrive in a row. At −1R each, that is −6R before the next trade. With $100 of fixed risk per trade, it is −$600. A strategy with positive expectancy can still have that streak; expectancy does not dictate the order of outcomes.
Many beginners want to be right as often as possible. Frequent small wins feel reassuring, while a large loss feels exceptional until it wipes out several winners. This can encourage early profit-taking, moving a stop away, or letting a loser run. Each action changes the average win or loss on which the original math depended.
The other side is difficult too: a strategy aiming for larger winners may lose more often. A trader needs enough data to understand its losing streaks and drawdowns, and risk small enough to follow the rules through a plausible bad run. One or two trades cannot establish a strategy's win rate. Even 100 trades are a sample, not a permanent promise.
A practical journal check
Imagine a fictional strategy with 100 recorded trades: 42 winners, 58 losers, an actual average winner of +2.2R, and an actual average loser of −1R.
Win rate = 42 ÷ 100 = 42%; loss rate = 58%.
Winners contribute 42 × 2.2R = +92.4R.
Losers cost 58 × 1R = −58R.
Net = 92.4R − 58R = +34.4R.
Expectancy = 34.4R ÷ 100 = +0.344R per trade, before any costs not already included.
Based strictly on these assumed numbers, the profile is positive. Its break-even win rate is 1 ÷ (2.2 + 1) = 31.25% before costs. The observed 42% sits above it. That does not establish what happens on the next 100 trades.
For each trade, record the setup, entry, planned stop, planned target, initial risk in dollars, actual exit, outcome in R, fees, and whether you followed the plan. A planned 1:2 winner closed early at +1.2R belongs in the journal as +1.2R. If you use partial exits, record the weighted result for the whole position. The journal should describe what happened, not what the chart briefly offered.
What else should you check?
A win rate calculator or risk-reward calculator can handle the arithmetic. Your trade records must supply the right inputs. Review these together: win rate, average win, average loss, risk per trade, expectancy, number of trades, maximum drawdown, losing streaks, trading costs, market conditions, and consistency of execution.
Watch for the common traps: judging a strategy by win rate alone; chasing distant targets; changing rules after a few losses; sizing positions too large; moving stops; taking profits earlier than the tested plan; and treating a backtest as if its fills were live trades.
Fees and spread reduce the amount you keep. Slippage can change the price you actually receive. A stop trigger does not guarantee the stop price, particularly in a fast market. The SEC and FINRA explain these execution limitations, while the SEC also notes that backtests are hypothetical and past performance cannot predict future results. [1][2][3]
The Simple Math to Remember
Win rate tells you how often you win.
Risk-to-reward tells you the size of a planned winner compared with a planned loser.
Expectancy connects your actual win rate with your actual average outcomes.
At 1:2, one full +2R winner pays for two full −1R losers: three trades, one win, 0R before costs. That is why you do not need to win every trade. You need to see whether the math holds across a meaningful series after costs and real execution.
Peni2Dollarz — Your Chart, Your Rules.
Sources and references
The formulas and all numerical trading results above are original, hypothetical arithmetic examples, not market statistics, historical results, or backtest findings.
U.S. SEC, Understanding Order Types, updated August 18, 2026 — market order execution prices are not guaranteed.
FINRA, Stop Orders: Factors to Consider During Volatile Markets, March 26, 2025 — a stop order can execute away from its trigger price.
U.S. SEC, Investor Bulletin: Performance Claims, September 15, 2022 — costs, hypothetical backtests, and limits of past performance.
Educational disclaimer: This article is for information and education, not financial advice. All trader and journal scenarios are hypothetical. Trading can cause substantial losses, including losses beyond a planned stop in some circumstances. No win rate, ratio, backtest, or expectancy guarantees future results.
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