Enter your trade sample and all-in cost per trade. The calculator shows the observed win rate with a 95% confidence interval, then adjusts expectancy, profit factor, breakeven rate, and total P&L for commissions and fees.
The observed 45.0% win rate is above the 34.4% after-cost breakeven estimate, but the 35.6–54.8% interval shows the remaining sampling uncertainty.
wins ÷ (wins + losses)
(win rate × average win) − (loss rate × average loss) − cost per trade
sum of positive after-cost trade outcomes ÷ absolute sum of negative after-cost outcomes
(average loss + cost) ÷ (average win + average loss)
With 45 wins, 55 losses, a $300 average win, a $150 average loss, and $5 cost per trade: observed win rate is 45.0% (95% Wilson interval 35.6–54.8%), net expectancy is $47.50 per trade, total net P&L is $4,750, net profit factor is 1.56, and the cost-adjusted breakeven rate is 34.4%.
Formula review: July 20, 2026. Maintained by TestMax. Results are educational estimates based on user inputs and simulated examples. They are not investment advice, a performance forecast, or a substitute for current exchange, broker, or firm rules.
Questions or corrections? Contact us. See our Privacy Policy and Terms of Service.
Costs do not change the observed win percentage, but they reduce every trade result. Net expectancy equals gross expectancy minus cost per trade. The cost-adjusted breakeven rate is (average loss + cost) ÷ (average win + average loss). If cost is greater than the average win, even a 100% win rate cannot produce positive expectancy.
It is a range of win rates compatible with the observed sample under a binomial model. This calculator uses the Wilson score interval because it stays well behaved for small samples and at 0% or 100% observed win rates. It quantifies sampling uncertainty; it does not prove the strategy will keep the same win rate.
There is no universal cutoff. The calculator labels fewer than 30 trades preliminary, 30–99 early, 100–199 useful, and 200 or more stronger. Those labels are practical communication guides, not proof of statistical validity. Regime changes, correlated trades, and changes in execution can matter even with a large sample.
There is no universally good win rate. A 40% win rate can be profitable with large average wins, while a 60% win rate can lose money when losses and costs are too large. Judge win rate with net expectancy, net profit factor, and the uncertainty around the observed rate.
Net expectancy is the estimated average after-cost P&L per trade: (win rate × average win) − (loss rate × average loss) − cost per trade. A positive historical expectancy is descriptive, not a guarantee that the same edge will continue.
TestMax logs every simulated futures trade and calculates performance analytics automatically, so you can test repeatable setups without risking capital.
Start Backtesting Free