Trading Expectancy Calculator
The Expectancy Calculator measures your trading strategy's average profit or loss per trade — its statistical edge. It uses Expectancy = (Win% × Average Win) − (Loss% × Average Loss), then normalizes the result into an R-multiple by dividing by average loss. Positive expectancy means the system profits over many trades; it also reports profit factor and a verdict.
- Core formula: Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss). Example: 55% win rate, $150 avg win, $100 avg loss = (0.55 × 150) − (0.45 × 100) = +$37.50 per trade.
- R-multiple expectancy = expectancy ÷ average loss, which normalizes for position size. The above example equals +0.375R, meaning you earn 0.375× your risked amount per trade.
- Verdict thresholds (by R-multiple): +0.5R or higher is Excellent, +0.2R to +0.5R is Good, 0 to +0.2R is Marginal, and below 0R is a Losing system.
- Profit factor = gross profit ÷ gross loss; values above 1.0 are profitable, with 2.0+ indicating a robust edge. It is only meaningful after roughly 100+ trades.
- Three input modes — Simple (win rate + averages), Detailed (trade counts + totals), and Trade-by-Trade (each P&L, up to 200 trades, which also computes standard deviation and 95% confidence intervals).
Calculate how much you can expect to win or lose per trade on average. The single most important metric for evaluating any trading strategy.
How to Use the Expectancy Calculator
Choose Your Input Mode
Simple is fastest — enter your win rate, average win, and average loss. Detailed lets you enter trade counts and totals if you have them from your journal. Trade-by-Trade lets you enter each trade's P&L individually for the most accurate calculation including standard deviation.
Enter Your Trading Statistics
Use real data from your trade journal — at least 30 trades, ideally 100+. Be honest. Inflated numbers give misleading expectancy. If you haven't tracked enough trades yet, that's the first thing to fix.
Read the Results
Focus on the R-multiple expectancy and the verdict. The projections show expected profit over 100, 500, and 1,000 trades. The confidence interval shows the range of likely outcomes (wider = more uncertainty).
Compare Strategies
Click "Add to Comparison" to save the current inputs as a strategy. Change the inputs and add another. Compare up to 3 strategies side-by-side to see which has the best expectancy, profit factor, and verdict.
What Is Expectancy in Trading?
Expectancy is the average amount you expect to win or lose on each trade over a large number of trades. It is the single most important metric for evaluating a trading strategy because it tells you whether the system makes money in the long run.
A positive expectancy means the strategy profits over time. A negative expectancy means it loses. Zero expectancy means breakeven (before costs). Every serious trader should know their expectancy.
The Key Insight
Expectancy combines win rate and trade size into one number. A 40% win rate strategy can have higher expectancy than a 70% win rate strategy if the winners are large enough relative to the losers. Win rate alone tells you almost nothing about profitability.
The Expectancy Formula Explained
E = (Win% × Avg Win) - (Loss% × Avg Loss)
// Example: 55% win rate, $150 avg win, $100 avg loss
E = (0.55 × $150) - (0.45 × $100)
E = $82.50 - $45.00 = $37.50 per trade
// R-Multiple Expectancy (normalized)
E(R) = Expectancy / Average Loss
E(R) = $37.50 / $100 = +0.375R
// Profit Factor
PF = Gross Profit / Gross Loss
PF = (55 × $150) / (45 × $100) = $8,250 / $4,500 = 1.83
The R-multiple version is more useful for comparison because it normalizes for position size. A +0.375R expectancy means you earn 0.375 times your risk on every trade. If you risk $100, you make $37.50 on average. If you risk $500, you make $187.50.
R-Multiples — Van Tharp's Methodology
R-multiples express every trade result as a multiple of the initial risk (R). If you risk $100 per trade:
| Trade Result | P&L | R-Multiple |
|---|---|---|
| Win at 2:1 target | +$200 | +2.0R |
| Win at 1.5:1 target | +$150 | +1.5R |
| Breakeven exit | $0 | 0R |
| Partial loss | -$50 | -0.5R |
| Full stop loss | -$100 | -1.0R |
| Slippage beyond stop | -$130 | -1.3R |
The power of R-multiples is normalization. A $50 win on a $25 risk (2R) is exactly as good as a $500 win on a $250 risk (2R). This lets you evaluate strategy quality independently of position size.
Expectancy Benchmarks in R-Multiples
| R-Multiple | Rating | Meaning |
|---|---|---|
| Above +0.50R | Excellent | Strong edge, very profitable system |
| +0.20R to +0.50R | Good | Solid edge, reliably profitable |
| +0.00R to +0.20R | Marginal | Barely profitable, costs may erode edge |
| Below 0.00R | Losing | Negative edge, loses money over time |
Why Expectancy Beats Win Rate
Most beginner traders obsess over win rate. "I win 70% of my trades!" But win rate alone is meaningless without knowing how much you win and lose.
| Strategy | Win Rate | Avg Win | Avg Loss | Expectancy | Verdict |
|---|---|---|---|---|---|
| High Win Rate | 70% | $80 | $200 | -$4.00 | Losing |
| Low Win Rate | 35% | $400 | $100 | +$75.00 | Excellent |
| Balanced | 55% | $150 | $100 | +$37.50 | Good |
The 70% win rate strategy loses money. The 35% win rate strategy is highly profitable. Expectancy reveals the truth that win rate hides.
Profit Factor vs. Expectancy
Profit factor and expectancy both measure profitability, but from different angles:
| Metric | Formula | What It Tells You | Benchmarks |
|---|---|---|---|
| Expectancy | W×AvgWin - L×AvgLoss | Average dollar gain per trade | Positive = profitable |
| Profit Factor | Gross Profit / Gross Loss | How many dollars won per dollar lost | >1.5 good, >2.0 excellent |
Use both together. A system with $10 expectancy and 1.1 profit factor is barely profitable and fragile — a small change in market conditions could flip it negative. A system with $50 expectancy and 2.0 profit factor has a robust edge.
Beware Misleading Profit Factors
A profit factor of 3.0 from 10 trades means nothing — it's noise. Profit factor becomes meaningful only after 100+ trades. Also, a strategy that takes few large wins and many small losses can show a high profit factor while having mediocre expectancy.
How Many Trades Before You Trust Your Edge?
Statistical confidence requires sufficient sample size. With too few trades, measured expectancy is dominated by luck.
| Sample Size | Win Rate Error (±) | Reliability | Guidance |
|---|---|---|---|
| 10 trades | ±30% | Very Low | Essentially useless for evaluation |
| 30 trades | ±18% | Low | Rough directional estimate only |
| 100 trades | ±10% | Moderate | Reasonable for initial evaluation |
| 200 trades | ±7% | Good | Reliable for strategy decisions |
| 500+ trades | ±4% | High | Statistically robust |
The confidence intervals in the results section use standard deviation to show how much your actual results might vary from the expected value. Wider intervals mean more uncertainty — either increase your sample size or accept the variance.
Improving Your Expectancy — Actionable Tips
Since Expectancy = (Win% × AvgWin) - (Loss% × AvgLoss), there are exactly three levers to pull:
1. Increase Your Win Rate
- Add confluence filters — only trade when multiple signals align.
- Avoid trading during low-liquidity sessions where patterns are less reliable.
- Improve entry timing with lower-timeframe confirmation.
- Be selective — skip setups that don't meet all your criteria.
2. Increase Your Average Win
- Use trailing stops to let winners run beyond initial targets.
- Scale out in portions — take partial profit and let the rest ride.
- Trade higher-timeframe setups for larger moves.
- Avoid moving take profit closer out of fear.
3. Decrease Your Average Loss
- Tighten stop losses (but not so tight they get hit on noise).
- Exit early when the setup is clearly invalidated — don't wait for the stop.
- Avoid moving your stop loss further away from entry.
- Reduce position size on lower-conviction setups.
Frequently Asked Questions
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Trading expectancy is the average amount you expect to win or lose per trade over a large number of trades. It is calculated as: Expectancy = (Win Rate x Average Win) - (Loss Rate x Average Loss). A positive expectancy means the strategy is profitable over time. It is the single most important metric for evaluating any trading system.
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Expectancy = (Win% x Average Win) - (Loss% x Average Loss). For example, with a 60% win rate, $100 average win, and $100 average loss: E = (0.60 x $100) - (0.40 x $100) = $60 - $40 = $20 per trade. To express in R-multiples, divide by your average loss: $20/$100 = +0.20R.
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In R-multiples: above +0.50R is excellent, +0.20R to +0.50R is good, 0R to +0.20R is marginal (costs may eat your edge), and below 0R is a losing system. In dollars, context matters — $20 per trade is great if you risk $50, but marginal if you risk $500. Always evaluate expectancy relative to risk.
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An R-multiple expresses profit or loss as a multiple of your initial risk (R). If you risk $100 and make $200, that is a +2R trade. If you risk $100 and lose $100, that is -1R. R-multiples normalize results across different position sizes, making it easy to compare strategies and measure expectancy independently of how much money you trade with.
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Profit factor is gross profits divided by gross losses. A profit factor of 1.0 means breakeven. Above 1.5 is good. Above 2.0 is excellent. It tells you how many dollars you win for every dollar you lose. Unlike expectancy, profit factor doesn't tell you the absolute gain per trade — just the ratio of wins to losses.
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Win rate ignores trade sizes. A 70% win rate with small wins and large losses is a losing system. A 35% win rate with large wins and small losses can be highly profitable. Expectancy combines win rate and average win/loss into a single number that tells you the true dollar value of your edge.
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At minimum 30 trades for a rough estimate, 100+ for reasonable confidence, and 200-500+ for statistical reliability. The confidence intervals in the calculator show how much your results might vary. With fewer trades, the intervals are very wide, meaning your measured expectancy could be far from the true value.
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Absolutely. A 30% win rate with an average win of $400 and average loss of $100 gives: E = (0.30 x $400) - (0.70 x $100) = $120 - $70 = $50 per trade. Many successful trend-following strategies have win rates of 30-40% but are highly profitable because their winners are 3-5x their losers. The R:R ratio compensates for the low win rate.
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They are the same concept. Expected value (EV) is the probability-weighted average of all possible outcomes, used widely in statistics and gambling. In trading, expectancy is the expected value per trade. Both represent the average result you'd converge toward over many repetitions.
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Three levers: (1) increase win rate through better trade selection and entry timing, (2) increase average win by letting winners run with trailing stops, and (3) decrease average loss through tighter stops and faster exits on invalidated setups. Focus on whichever factor has the most room for improvement in your specific system.
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No. Expectancy is a long-run average. In the short term, randomness can produce losing streaks even with strong positive expectancy. The standard deviation of your trades determines how bumpy the equity curve is. High expectancy with low standard deviation is ideal — steady, predictable profits. High expectancy with high standard deviation means the edge is real but the ride is volatile.
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Standard deviation measures the spread of your trade results around the average. Higher standard deviation means wider swings between winning and losing periods. The 95% confidence interval for N trades is approximately: Expected Profit +/- 1.96 x StdDev x sqrt(N). This tells you the range within which your actual results will likely fall.
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