Trading Expectancy Calculator

Trading expectancy is the average profit or loss you can expect from a single trade, calculated as a probability-weighted mean across all trade outcomes. It combines your win rate, average winning trade, and average losing trade into one number. A positive expectancy means your system is profitable on average over many trades; a negative expectancy means it is a losing system regardless of how good any individual trade feels.

The formula is: Expectancy = (Win Rate × Average Win) − (Loss Rate × Average Loss), where Loss Rate = 1 − Win Rate and both rates are fractions (not percentages). For example, a 55% win rate with a $400 average win and a $300 average loss gives: (0.55 × 400) − (0.45 × 300) = 220 − 135 = $85 per trade.

Any positive expectancy — even $1 per trade — means your system has a statistical edge that compounds over hundreds of trades. A common benchmark is 0.2R or higher (earning at least 20 cents per dollar risked per trade). The raw dollar figure is less meaningful than the R-multiple form: a $50 expectancy on a $500,000 account is a tiny edge, while $50 on a $5,000 account is substantial.

Yes. Many profitable trend-following systems win on only 30–40% of trades but achieve large average wins relative to small, tightly controlled average losses. A 40% win rate with a 3R average win and a 1R average loss gives expectancy = (0.40 × 3) − (0.60 × 1) = 0.6R per trade — solidly positive. Win rate alone does not determine profitability; the ratio of average win to average loss matters equally.

Expectancy in R-multiples (popularised by trading educator Van K. Tharp) expresses the average profit per trade relative to 1R — the amount you risk on each trade (typically |entry − stop| × position size). An expectancyR of 0.5 means you earn, on average, half your risk per trade. This form is account-size-independent, which makes it the best metric for comparing strategies across different account sizes or instruments.

Win rate tells you what fraction of your trades close profitably, but says nothing about how much you make on winners versus lose on losers. A 70% win rate sounds great, but if winners average $50 and losers average $200, expectancy is (0.70 × 50) − (0.30 × 200) = 35 − 60 = −$25 per trade — a losing system. Expectancy captures both dimensions: frequency and magnitude.

Expectancy measures the expected value (mean profit) of a single trade in currency or R-multiples. Profit factor is the ratio of gross profits to gross losses across all trades — how many dollars of profit you earn for every dollar you lose. A profit factor above 1.0 is the equivalent condition to a positive expectancy, but the two are on different scales. Expectancy is more actionable for position sizing and equity projection; profit factor is more useful for quick system comparison.

The risk-reward ratio (R:R) is the ratio of your planned reward to your planned risk on a single trade — 2:1 means you target a $200 gain and risk $100. Expectancy incorporates R:R plus win rate: a 2:1 system needs a win rate above 33% to be profitable. If your actual average win and loss match your planned R:R, expectancy = (winRate × reward) − (lossRate × risk). Expectancy is the full picture; R:R is one input.

No. Expectancy is a long-run statistical average — it only manifests reliably over many trades (the law of large numbers). In the short run, even a high-expectancy system produces losing streaks. Expected total profit over N trades is expectancy × N, but the actual result scatters above and below that mean. Positive expectancy means your system has an edge; consistent execution and proper position sizing turn that edge into realised profit.

Yes — for a realistic figure, your average win and average loss must already include all transaction costs (commissions, spread, and slippage). A system with a gross expectancy of $5 per trade can turn net-negative once a $3–5 round-trip commission is subtracted. Always compute expectancy from your net trade results, not your gross results.

As a rule of thumb, at least 30 trades are needed for a meaningful expectancy, and 100 or more are preferred for a stable estimate. With fewer trades, sampling error is large enough that a positive figure may not be statistically significant — it could reflect lucky runs. Below 30 data points, treat your expectancy as tentative and keep collecting trade data.

Expectancy measures the average profit per trade. The System Quality Number (SQN, also from Van Tharp) goes further by accounting for consistency: SQN = (mean R-multiple ÷ standard deviation of R-multiples) × √(number of trades). An SQN above 1.6 is tradeable; above 5 is excellent. Expectancy tells you the direction and size of your edge; SQN tells you how reliably you achieve it.