What Is the Expectancy Per Trade Formula?

Expectancy is the average profit or loss you expect to make per trade over the long term, given your current win rate, average win, average loss, and commission costs. It is the single most important metric for determining whether a trading system has an edge.

The expectancy formula is deceptively simple: (Win Rate × Average Win) - (Loss Rate × Average Loss). But this simple equation carries enormous weight. A system with a positive expectancy of +$50 per trade is fundamentally different from a system with a -$10 per trade expectancy. The first makes money over time; the second bleeds capital. The difference determines whether a trader builds wealth or eventually blows up their account.

Professional traders obsess over expectancy. They use it to compare different trading systems, to evaluate whether a change to their approach improves profitability, and to project long-term capital growth. A trader who understands expectancy can make intelligent decisions about position sizing, time commitment, and risk tolerance.

Quick definition: Expectancy is the average dollar profit or loss per trade, calculated as (Win Rate × Average Win) - (Loss Rate × Average Loss). A positive expectancy indicates a profitable system; negative expectancy indicates eventual capital loss.

Key takeaways

• Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss)
• A positive expectancy, no matter how small, indicates a system with an edge
• A negative expectancy of -$1 per trade will lose $250 per month (trading 250 times)
• Use expectancy to compare different trading systems objectively
• Adjust position size based on expectancy: higher expectancy allows larger positions
• Expectancy assumes consistent execution; emotion and discipline affect real results
• Monitor expectancy every 30–50 trades to ensure the system is still performing

The Complete Expectancy Formula

The basic form is:

Expectancy = (Win Rate × Average Win) - (Loss Rate × Average Loss)

A more detailed version that explicitly shows win rate and loss rate:

Expectancy = (% Wins × $ Per Win) - (% Losses × $ Per Loss)

Where:

• % Wins = number of winning trades / total number of trades
• $ Per Win = total profit on all winning trades / number of winning trades
• % Losses = number of losing trades / total number of trades
• $ Per Loss = total loss on all losing trades / number of losing trades

Worked example:

• 50 total trades
• 20 winning trades
• 30 losing trades
• Total profit on winners: $4,000
• Total loss on losers: $2,100
• Win Rate = 20 / 50 = 0.40 = 40%
• Loss Rate = 30 / 50 = 0.60 = 60%
• Average Win = $4,000 / 20 = $200
• Average Loss = $2,100 / 30 = $70
• Expectancy = (0.40 × $200) - (0.60 × $70)
• Expectancy = $80 - $42
• Expectancy = +$38 per trade

This trader has a positive expectancy of $38 per trade. Over 100 trades, the expected profit is $3,800 (100 × $38). This system has an edge.

Expectancy and System Comparison

A critical use of expectancy is comparing different trading systems. Which is better: System A or System B?

System A:

• 100 trades, 45 wins, 55 losses
• Average win: $150
• Average loss: $100
• Expectancy = (0.45 × $150) - (0.55 × $100) = $67.50 - $55 = +$12.50 per trade

System B:

• 100 trades, 40 wins, 60 losses
• Average win: $250
• Average loss: $120
• Expectancy = (0.40 × $250) - (0.60 × $120) = $100 - $72 = +$28 per trade

System B has a higher expectancy (+$28 vs. +$12.50), so it is the more profitable system despite a slightly lower win rate (40% vs. 45%). System B wins fewer trades but wins bigger, resulting in better long-term profitability.

A trader using System A would make an expected $1,250 profit per 100 trades. A trader using System B would make an expected $2,800 profit per 100 trades. Over a year of 1,000 trades, the difference is $12,500 in profit—a massive difference driven by a seemingly small difference in expectancy.

Expectancy and Position Sizing

Expectancy informs position sizing. A trader with a high-expectancy system can afford to take larger positions; a trader with a low-expectancy system should trade smaller.

The Kelly Criterion is a mathematical formula that calculates optimal position size based on expectancy and risk per trade:

Kelly % = (Win Rate × Average Win - Loss Rate × Average Loss) / Average Loss

Simplified:

Kelly % = Expectancy / Average Loss

Worked example:

• Expectancy: +$50 per trade
• Average Loss: $200
• Kelly % = $50 / $200 = 0.25 = 25%

The Kelly Criterion suggests risking 25% of account capital per trade. However, most traders use a "fractional Kelly" approach and risk only 50% or 25% of the Kelly percentage (12.5% or 6.25% in this example) to reduce volatility and avoid over-leverage.

A trader with an expectancy of +$20 per trade and an average loss of $200 would have:

• Kelly % = $20 / $200 = 0.10 = 10%
• Fractional Kelly (50%) = 5% risk per trade

This trader, with lower expectancy, should take smaller position sizes. If they trade with the same position size as the high-expectancy trader, they will experience larger drawdowns and may give up before the edge compounds.

Expectancy Over Different Time Horizons

Expectancy is typically calculated per trade, but you can also think about it over longer periods:

Monthly Expectancy = Expectancy per Trade × Expected Trades per Month
Quarterly Expectancy = Expectancy per Trade × Expected Trades per Quarter
Annual Expectancy = Expectancy per Trade × Expected Trades per Year

Worked example:

• Expectancy per trade: +$35
• Expected trades per month: 20 (for a day trader)
• Monthly expectancy = $35 × 20 = +$700 per month
• Annual expectancy = $35 × 240 (12 months × 20 trades) = +$8,400 per year

A trader making 20 trades per month with a +$35 expectancy can project a +$8,400 annual profit. However, this is an average—some months will be much better, others worse, depending on variance and market conditions.

Decision Tree

Real-World Example: Three Trader Expectations

Trader A: High-Frequency, Low-Edge System

• 200 trades per month
• Win rate: 52%
• Average win: $40
• Average loss: $45
• Expectancy = (0.52 × $40) - (0.48 × $45) = $20.80 - $21.60 = -$0.80 per trade
• Monthly expectancy: -$0.80 × 200 = -$160 per month
• Annual expectancy: -$160 × 12 = -$1,920 per year

Despite a 52% win rate (above breakeven), Trader A loses money because the average loss exceeds the average win by $5 per trade. Over a year, this small negative expectancy compounds into a $1,920 annual loss. The trader is making 2,400 trades annually to lose money. Trader A should either improve the system (increase average wins or decrease average losses) or stop trading.

Trader B: Moderate Frequency, Strong Edge

• 50 trades per month
• Win rate: 45%
• Average win: $300
• Average loss: $150
• Expectancy = (0.45 × $300) - (0.55 × $150) = $135 - $82.50 = +$52.50 per trade
• Monthly expectancy: +$52.50 × 50 = +$2,625 per month
• Annual expectancy: +$2,625 × 12 = +$31,500 per year

Trader B makes 50 trades per month with a strong expectancy of +$52.50 per trade. The annual expectation is +$31,500. This is a profitable system where the edge is clear and compounding.

Trader C: Low Frequency, Exceptional Edge

• 10 trades per month
• Win rate: 60%
• Average win: $500
• Average loss: $200
• Expectancy = (0.60 × $500) - (0.40 × $200) = $300 - $80 = +$220 per trade
• Monthly expectancy: +$220 × 10 = +$2,200 per month
• Annual expectancy: +$220 × 120 = +$26,400 per year

Trader C makes only 10 trades per month but has an exceptional edge: +$220 per trade. This trader has higher win rate and better risk-reward than Trader B, resulting in nearly the same annual expectancy (26,400 vs. 31,500) with 80% fewer trades. Trader C experiences less stress, lower commission costs, and lower chance of behavioral mistakes.

The comparison shows that a strong edge with low frequency can match or exceed a weak edge with high frequency.

Common Mistakes

Mistake 1: Using backtested expectancy without live validation. Backtested expectancy is often 20–40% higher than live expectancy because backtesting ignores slippage, commission, and the inability to execute exact prices. A system with a backtested expectancy of +$100 might have a live expectancy of +$60. Always validate expectancy with live or paper trading before committing real capital.

Mistake 2: Not updating expectancy after changes to the system. A trader modifies their stop-loss rule or profit-taking rule, but fails to recalculate expectancy. The new expectancy might be negative, but the trader is unaware. Recalculate expectancy every time you make a meaningful change to your system.

Mistake 3: Confusing expectancy with actual profit. A system with a +$50 expectancy per trade does not mean you will make +$50 on every trade. It means the long-term average is +$50. In the short term, you might lose on 10 consecutive trades. Expectancy is an average; you must survive the variance with adequate capital and loss limits.

Mistake 4: Accepting very small positive expectancy. An expectancy of +$0.50 per trade on a $10 per contract commission is a losing system (after commission, it becomes -$9.50). Always calculate expectancy after all costs: commissions, slippage, and bid-ask spreads. The threshold for a viable system is expectancy that significantly exceeds your costs.

Mistake 5: Over-leveraging on the basis of positive expectancy. A trader sees a +$50 expectancy and calculates that they can trade 10 positions simultaneously to make $500 per trade. But this ignores correlation risk and drawdown severity. Positive expectancy does not mean zero drawdown risk. The Kelly Criterion provides guidance on position sizing based on expectancy, but even the Kelly percentage should often be fractionally reduced for safety.

FAQ

How often should I recalculate expectancy?

Recalculate expectancy every 30–50 trades. Do not update based on a single trade or a week's results. Over 50 trades, the metric is relatively stable; changes after 50 trades reflect genuine shifts in your system performance, not variance.

What is a "good" expectancy per trade?

This depends on your costs. If commissions and slippage total $5 per trade, an expectancy of +$10 is barely viable. An expectancy of +$50 is very good. A professional trader typically targets an expectancy of at least +$20–$50 per trade after all costs.

Can I have a positive expectancy but still lose money?

Yes, if variance is high and drawdowns exceed your capital. A system with a +$10 expectancy per trade might have such high variance that you hit a 30-loss streak before your account recovers, leaving you unable to continue. This is why loss limits and adequate capitalization are critical.

How does expectancy change with different market regimes?

Calculate expectancy separately for trending markets, range-bound markets, and volatile markets. Your system might have +$60 expectancy in trends but -$20 in ranges. This reveals that your system should only trade during the regimes where it has an edge.

Should I combine expectancy from multiple different systems?

Only if they are truly independent. If you run two systems that trade the same instruments, they are correlated and combining their expectancies is misleading. If you run a stock system and a forex system simultaneously, you can sum their individual expectancies for a combined overall expectancy.

What if my expectancy is negative? Should I continue trading?

No. A negative expectancy system will eventually deplete your capital, no matter how much you have. Either improve the system (increase wins, decrease losses) or abandon it. Trading a negative expectancy system is betting against yourself.

How do commissions affect expectancy?

Commissions reduce expectancy on every trade. If you make 100 trades and pay $10 in commission per trade, you lose $1,000 total. This reduces your expectancy by $10 per trade. Always subtract commission costs from your average wins and average losses before calculating expectancy.

Is expectancy enough to prove I have a trading edge?

Expectancy is necessary but not sufficient. You need positive expectancy after all costs, calculated from a large sample size (>100 trades) in a consistent market environment, and you must have the discipline to execute the system without deviation. Many traders have positive expectancy in backtests but negative expectancy in live trading due to emotion and slippage.

Related concepts

• Win Rate and Risk Reward Math — The components of expectancy
• Daily Loss Limit That Stops Trading — Managing variance until expectancy compounds
• Monthly Loss Limit That Stops Trading — Protecting capital during drawdown periods
• Risk of Ruin Overview — How negative expectancy leads to account destruction

Summary

Expectancy is the average profit or loss per trade: (Win Rate × Average Win) - (Loss Rate × Average Loss). A positive expectancy, no matter how small, indicates a system with a mathematical edge. A trader with a +$35 expectancy making 20 trades per month can project a +$8,400 annual profit. Expectancy is used to compare trading systems objectively, to determine position sizing via the Kelly Criterion, and to monitor whether a system remains profitable after changes. The gap between expectancy and reality is often explained by slippage, commissions, and emotion—a system with a backtested expectancy of +$100 might deliver +$60 in live trading. Always calculate expectancy from actual live or paper-trading results after accounting for all costs, recalculate every 30–50 trades, and abandon any system with negative expectancy. Positive expectancy is the foundation of long-term trading profitability, but it must be paired with loss limits to survive the variance periods that precede consistent gains.

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Read next: Consecutive Loss Streak Probability