What if I told you that some of the most profitable crypto traders have win rates below 40%?
It sounds backwards. How can someone who loses more than half their trades still make money?
The answer is risk-to-reward ratios-and understanding them will fundamentally change how you think about trading.
Most beginners obsess over win rate. They want to be right as often as possible. But being right isn't the same as being profitable. A 70% win rate means nothing if your average loss is three times your average win.
Professional traders understand that it's not about being right more often-it's about making more on winners than you lose on losers. That asymmetry is the foundation of sustainable profitability.
This guide teaches you everything about risk-reward ratios: how to calculate them, how to optimize them, and how to build a trading approach where the math is permanently in your favor.
The risk-reward ratio (R:R) compares how much you stand to lose on a trade versus how much you stand to gain.
If you're risking $100 to potentially make $300, your R:R is 1:3 (one unit of risk for three units of reward).
The formula:
risk-reward ratio = Potential Reward ÷ Potential Risk
Or expressed as:
R:R = (Target Price - Entry Price) ÷ (Entry Price - Stop Loss Price)
For long positions:
- Reward = Target - Entry
- Risk = Entry - Stop Loss
For short positions:
- Reward = Entry - Target
- Risk = Stop Loss - Entry
You're going long on BTC:
- Entry price: $70,000
- Stop loss: $68,000
- Take profit: $76,000
Risk = $70,000 - $68,000 = $2,000
Reward = $76,000 - $70,000 = $6,000
R:R = $6,000 ÷ $2,000 = 3:1
This means for every $1 you risk, you stand to make $3.
Here's a thought experiment that changes how most people think about trading:
Trader A: 80% win rate, 1:1 risk-reward ratio
Trader B: 40% win rate, 4:1 risk-reward ratio
Who makes more money?
Let's run the math over 100 trades, risking $100 per trade:
Trader A (80% WR, 1:1 R:R):
- 80 wins × $100 = $8,000
- 20 losses × $100 = -$2,000
- Net profit: $6,000
Trader B (40% WR, 4:1 R:R):
- 40 wins × $400 = $16,000
- 60 losses × $100 = -$6,000
- Net profit: $10,000
Trader B makes nearly twice as much money while being wrong 60% of the time.
This is the power of risk-reward ratios. Win rate alone tells you nothing about profitability. The relationship between win rate and R:R determines everything.
For any given R:R, there's a breakeven win rate below which you lose money:
| Risk:Reward |
Breakeven Win Rate |
| 1:1 |
50% |
| 1:1.5 |
40% |
| 1:2 |
33.3% |
| 1:3 |
25% |
| 1:4 |
20% |
| 1:5 |
16.7% |
At 1:3 R:R, you only need to win 25% of your trades to break even. Win 30%, and you're profitable.
At 1:1 R:R, you need to win more than 50% just to cover fees and break even.
This math is why professionals focus on R:R as much as (or more than) win rate.
Step 1: Identify your entry price
Where will you enter the trade?
Step 2: Determine your stop loss
Where is the trade invalidated? This should be based on technical levels, not arbitrary percentages.
Step 3: Set your take profit target
Where will you exit if the trade works? Again, based on technical levels-resistance, support, measured moves.
Step 4: Calculate the ratio
Reward (distance to target) ÷ Risk (distance to stop)
Many traders make the mistake of setting targets first, then figuring out the stop loss. This is backwards.
Your stop loss should be at the point where your trade thesis is invalidated-where the market structure says you're wrong. This is fixed by the chart, not your preferences.
Once you know your stop, you can calculate what R:R is available. If the R:R isn't favorable, don't take the trade.
Some traders take partial profits at multiple levels. In this case, calculate weighted average R:R:
Example:
- Entry: $70,000
- Stop: $68,000 (risk = $2,000)
- Target 1: $73,000, exit 50% of position (reward = $3,000 on 50%)
- Target 2: $76,000, exit remaining 50% (reward = $6,000 on 50%)
Weighted reward = (0.5 × $3,000) + (0.5 × $6,000) = $4,500
Average R:R = $4,500 ÷ $2,000 = 2.25:1
To know if your trading is profitable, you need one formula:
Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss)
- Or simplified: Expectancy = (WR × R) - ((1 - WR) × 1)
Where:
Example 1:
Expectancy = (0.55 × 2) - (0.45 × 1)
Expectancy = 1.10 - 0.45
Expectancy = 0.65
This means for every $1 risked, you expect to make $0.65 over time. That's highly profitable.
Example 2:
- Win rate: 70%
- R:R: 0.5:1 (risking more than reward)
Expectancy = (0.70 × 0.5) - (0.30 × 1)
Expectancy = 0.35 - 0.30
Expectancy = 0.05
Despite the 70% win rate, expectancy is barely positive. Fees would likely make this unprofitable.
Here's a quick reference for profitability at various combinations:
| Win Rate |
1:1 R:R |
1.5:1 R:R |
2:1 R:R |
3:1 R:R |
| 30% |
-0.40 |
-0.25 |
-0.10 |
+0.20 |
| 40% |
-0.20 |
0.00 |
+0.20 |
+0.60 |
| 50% |
0.00 |
+0.25 |
+0.50 |
+1.00 |
| 60% |
+0.20 |
+0.50 |
+0.80 |
+1.40 |
| 70% |
+0.40 |
+0.75 |
+1.10 |
+1.80 |
- Key insight: You can be profitable with a 30% win rate if your R:R is 3:1 or better. You can be unprofitable with a 60% win rate if your R:R is less than 1:1.
There's no universal "best" R:R. The optimal ratio depends on your strategy, the market environment, and the specific setup.
| Strategy Type |
Typical R:R |
Why |
| Scalping |
1:1 to 1.5:1 |
High win rate, small moves |
| Day trading |
1.5:1 to 2:1 |
Balance of win rate and reward |
| Swing trading |
2:1 to 3:1 |
Bigger moves, lower frequency |
| Position trading |
3:1 to 5:1 |
Home runs, lower win rate |
| Breakout trading |
3:1+ |
High failure rate, need big wins |
Different setups have different natural R:R profiles:
High win rate, lower R:R setups:
- Mean reversion trades
- Support/resistance bounces
- Range trading
Lower win rate, higher R:R setups:
- Breakout trades
- Trend continuation trades
- Counter-trend reversals
Neither is inherently better. The key is matching your expectations to the setup's characteristics.
There's an inherent tradeoff between win rate and R:R:
- Wider targets → Higher R:R but lower win rate (target less likely to be hit)
- Tighter targets → Lower R:R but higher win rate (target more likely to be hit)
- Wider stops → Higher win rate but lower R:R (less likely to be stopped out, but risking more)
- Tighter stops → Lower win rate but higher R:R (more likely to be stopped out, but risking less)
The "optimal" point depends on market conditions and your strategy. Testing is the only way to find it.
Asymmetric trades are setups where reward potential significantly exceeds risk. They're the highest-expectancy opportunities in trading.
-
Clear invalidation level (tight stop)
The trade has a nearby point where you know you're wrong, allowing a small stop.
-
Multiple upside targets (big reward)
If the trade works, there's room for substantial gains-not just one target, but potential for extended moves.
-
Favorable probability
Even with the asymmetry, the trade has reasonable odds of working.
Breakout from consolidation:
- Stop: Just below consolidation range (small)
- Target: Full range extension, then trend continuation (large)
- R:R: Often 4:1 to 10:1
Support test in strong uptrend:
- Stop: Just below support (small)
- Target: New highs (large)
- R:R: Often 3:1 to 5:1
Reversal at major level with confirmation:
- Stop: Just beyond the extreme (small)
- Target: Return to mean, then trend continuation (large)
- R:R: Often 5:1+
With asymmetric trades, you can be wrong most of the time and still profit handsomely.
Consider a trader who only takes 4:1 R:R setups:
- Win rate: 30% (loses 70% of trades)
- Per 100 trades, risking $100 each
- Wins: 30 × $400 = $12,000
- Losses: 70 × $100 = $7,000
- Net: $5,000 profit
This trader is wrong 70% of the time but makes $5,000 per 100 trades. That's the power of asymmetry.
Look for situations where:
-
Market structure provides a close invalidation point
Recent swing low, support level, trendline-somewhere obvious where "this is wrong" exists nearby.
-
Significant room exists to the target
No major resistance between entry and target. Clear path for price to move.
-
Catalyst or context supports the direction
Trend alignment, volume confirmation, sentiment shift-something beyond just the chart says this could work.
These combinations create the asymmetric opportunities worth waiting for.
Your take profit placement dramatically impacts R:R and overall profitability. Here's how to approach it systematically.
- The best targets are technical levels where price is likely to react: For long positions:
- Previous resistance levels
- Fibonacci extension levels
- Measured move targets
- Round psychological numbers
- Volume profile high-volume nodes
For short positions:
- Previous support levels
- Fibonacci retracement levels
- Measured move targets
- Volume profile low-volume areas
Some traders set targets based purely on their risk:
- 1R target = Gain equals risk
- 2R target = Gain is 2x risk
- 3R target = Gain is 3x risk
This simplifies position management and creates consistency.
Partial exits at multiple targets can balance win rate and R:R:
Example scale-out:
- Exit 1/3 at 1R
- Exit 1/3 at 2R
- Let 1/3 run with trailing stop
Pros:
- Locks in some profit even if full target isn't hit
- Higher psychological win rate
- Captures runners when they happen
Cons:
- Reduces maximum profit on full winners
- More complex execution
Whatever method you use, establish a minimum R:R below which you won't trade:
Minimum R:R filter by strategy:
- Scalping: 0.75:1 minimum
- Day trading: 1.5:1 minimum
- Swing trading: 2:1 minimum
If the setup doesn't meet your minimum, pass on it-no matter how good the entry looks.
- The problem: Placing stops based on how much you're willing to lose ("I'll stop out if it drops $500") instead of where the trade is actually invalidated.
The fix: Stop loss placement should be technical. Identify where the trade thesis breaks, put your stop there, then calculate R:R. If R:R isn't favorable, don't take the trade.
-
The problem: Setting unrealistic targets to make the R:R look better on paper, then watching price reverse before hitting them.
-
The fix: Targets should be at levels price is likely to reach. An "amazing" 10:1 R:R is worthless if the target never gets hit. Be honest about realistic targets.
-
The problem: Taking low R:R trades assuming you'll make up for it with high win rate, but win rate doesn't actually support the math.
-
The fix: Calculate expected value using your actual historical win rate. If you don't have data, assume conservative win rate until you do.
-
The problem: Planning trades with 2:1 R:R but not measuring what R:R you actually achieve after exits.
-
The fix: Track planned R:R vs. realized R:R. If there's a gap, figure out why-are you cutting winners short? Moving stops?
Setup: BTC breaks above consolidation range with volume
-
Entry: $71,000
-
Stop: $70,000 (below consolidation, $1,000 risk)
-
Target: $74,000 ($3,000 reward)
-
R:R: 3:1
-
Analysis: This is a favorable R:R. At 3:1, you only need 25% win rate to break even. If this setup hits 40% of the time, expectancy is:
(0.40 × 3) - (0.60 × 1) = 0.60
You make $0.60 for every $1 risked. Over 100 trades at $1,000 risk, that's $60,000.
Setup: ETH touches intraday support, looking for bounce
-
Entry: $3,500
-
Stop: $3,480 ($20 risk)
-
Target: $3,520 ($20 reward)
-
R:R: 1:1
-
Analysis: At 1:1 R:R, you need >50% win rate to profit after fees. If this setup wins 60% of the time:
(0.60 × 1) - (0.40 × 1) = 0.20
You make $0.20 per $1 risked. It's profitable, but barely. Fees of just 0.1% per trade would significantly eat into this.
-
Setup: Major support level holds after capitulation wick
-
Entry: $62,000
-
Stop: $60,500 ($1,500 risk)
-
Target 1: $68,000 ($6,000 reward) - exit 50%
-
Target 2: $75,000 ($13,000 reward) - exit 50%
-
Weighted R:R: ($6,000×0.5 + $13,000×0.5) ÷ $1,500 = 6.3:1
-
Analysis: This is highly asymmetric. Even at 25% win rate:
(0.25 × 6.3) - (0.75 × 1) = 0.825
You make $0.825 per $1 risked. You can be wrong 3 out of 4 times and still profit significantly.
R:R is a component of expectancy, not the whole picture. Here's how to build a system with consistently positive expectancy.
What specific conditions must exist for you to take a trade? Write these down precisely.
Not all setups should have the same R:R requirement:
- High-probability setups (support/resistance bounces): Minimum 1.5:1
- Moderate-probability setups (trend continuations): Minimum 2:1
- Low-probability setups (reversals, breakouts): Minimum 3:1
After 50+ trades, you'll have data showing:
- Win rate per setup type
- Average R:R achieved per setup type
- Expectancy per setup type
Your data might show:
- Setup A: 65% win rate, 1.2:1 R:R → Expectancy 0.43
- Setup B: 35% win rate, 3.5:1 R:R → Expectancy 0.58
- Setup C: 50% win rate, 1:1 R:R → Expectancy 0.00
Setup B is your best setup despite the lowest win rate. Setup C is breakeven-cut it or modify it.
Trading systems aren't static. Markets change. Continue tracking and adjusting.
Start with a minimum 2:1 R:R requirement. This provides buffer for learning mistakes while ensuring profitable math if you can achieve even moderate win rates. As you gain data, you can optimize.
Exit early only if your thesis is invalidated-not because you're uncomfortable. Closing before your stop means taking a guaranteed loss instead of giving the trade room to work. Let your stops do their job.
Better trade selection. Wait for setups where stops can be tight (close invalidation) and targets can be far (clear path to move). This often means trading less frequently but with higher quality.
Crypto's volatility allows for larger moves, making higher R:R more achievable than in traditional markets. Many successful crypto traders target minimum 2:1 on day trades and 3:1+ on swing trades. Use crypto's volatility to your advantage.
Yes. If your targets are so far that they rarely get hit, your win rate will be so low that expectancy turns negative. The key is realistic targets that balance win rate and reward.
Most crypto traders fight for edges measured in fractions of a percent. They analyze charts endlessly looking for any small predictive advantage.
Meanwhile, the R:R edge is sitting right there-obvious, mathematical, available to anyone who understands it.
By simply refusing to take trades below 2:1 R:R, you guarantee that your winners will be twice as large as your losers. That asymmetry compounds over hundreds of trades into substantial profits.
You don't need to predict the market perfectly. You don't need insider information. You don't need to be right 70% of the time.
You just need to make more when you're right than you lose when you're wrong.
That's it. That's the secret that separates consistently profitable traders from everyone else.
Calculating risk-reward ratios should be automatic, not something you do in your head (or worse, skip entirely).
Thrive builds R:R analysis into every trade:
- Automatic R:R calculation - Enter your entry, stop, and target. Instant R:R display.
- Minimum R:R alerts - Get warned when a trade doesn't meet your threshold
- Historical R:R tracking - See your planned vs. actual R:R over time
- Expectancy calculator - Real-time expected value based on your win rate and R:R
- Setup-specific R:R analysis - Which setups give you the best risk-adjusted returns
- Weekly AI Coach - Identify when you're taking suboptimal R:R trades and why
Stop guessing whether trades are worth taking. Start knowing.
Trade with the math on your side.
→ Start Tracking Your R:R with Thrive
