Backtesting Win Rate Calculator
Calculate strategy win rate, expectancy, and drawdown from backtesting trade results. Enter values for instant results with step-by-step formulas.
Formula
Expectancy = (Win% x Avg Win) - (Loss% x Avg Loss) | Profit Factor = Gross Profit / Gross Loss
Expectancy measures the average profit per trade. Profit factor compares total gains to total losses. Kelly Criterion = (W x R - L) / R, where W is win rate, L is loss rate, and R is reward-to-risk ratio. These metrics together determine if a strategy has a genuine edge.
Worked Examples
Example 1: Trend-Following Strategy Backtest
Problem: A trend-following strategy was backtested over 200 trades with 80 winners. Average win: $300, average loss: $120. Starting balance: $10,000.
Solution: Win Rate = 80/200 = 40%\nLoss Rate = 60%\nReward-to-Risk = $300/$120 = 2.50\nExpectancy = (0.40 x $300) - (0.60 x $120) = $120 - $72 = $48 per trade\nTotal Profit = (80 x $300) - (120 x $120) = $24,000 - $14,400 = $9,600\nProfit Factor = $24,000 / $14,400 = 1.67\nReturn = $9,600 / $10,000 = 96%\nKelly = (0.40 x 2.50 - 0.60) / 2.50 = 16%
Result: Win Rate: 40% | Expectancy: $48/trade | Profit Factor: 1.67 | Total Profit: $9,600 | Kelly: 16%
Example 2: Scalping Strategy Evaluation
Problem: A scalping strategy had 500 trades with 375 winners. Average win: $50, average loss: $80. Initial balance: $25,000.
Solution: Win Rate = 375/500 = 75%\nLoss Rate = 25%\nReward-to-Risk = $50/$80 = 0.625\nExpectancy = (0.75 x $50) - (0.25 x $80) = $37.50 - $20 = $17.50 per trade\nTotal Profit = (375 x $50) - (125 x $80) = $18,750 - $10,000 = $8,750\nProfit Factor = $18,750 / $10,000 = 1.875\nReturn = $8,750 / $25,000 = 35%
Result: Win Rate: 75% | Expectancy: $17.50/trade | Profit Factor: 1.88 | Total Profit: $8,750 | Kelly: 35%
Frequently Asked Questions
What is a backtesting win rate and why does it matter for trading?
A backtesting win rate is the percentage of trades that resulted in a profit when a trading strategy is tested against historical market data. It is calculated by dividing the number of winning trades by the total number of trades and multiplying by 100. However, win rate alone does not determine whether a strategy is profitable. A strategy with only a 30 percent win rate can be highly profitable if winning trades are much larger than losing trades. Conversely, a 90 percent win rate strategy can lose money if the few losses are catastrophic. Professional traders analyze win rate alongside reward-to-risk ratio and expectancy to get a complete picture of strategy viability.
What is maximum drawdown and how is it estimated from backtesting data?
Maximum drawdown is the largest peak-to-trough decline in your account equity during the backtesting period, expressed as a dollar amount or percentage. Backtesting Win Rate Calculator estimates maximum drawdown by computing the probable longest losing streak using probability theory and multiplying it by the average loss per trade. The formula uses the natural logarithm of total trades divided by the natural logarithm of one over the loss probability to estimate consecutive losses. Real drawdowns can exceed this estimate because losses may cluster and individual losses vary. Professional traders typically require that maximum drawdown stays below 20 to 25 percent of the account. A strategy with an expected drawdown exceeding 30 percent is generally considered too risky for most traders.
What are common backtesting pitfalls that make results unreliable?
The most common backtesting pitfall is overfitting, where a strategy is tuned to match historical data perfectly but fails on new data. This happens when traders optimize too many parameters or test on too short a time period. Survivorship bias occurs when backtesting only includes currently existing instruments while ignoring delisted companies or failed assets. Look-ahead bias happens when the strategy uses data that would not have been available at the time of the trade, such as using end-of-day prices for intraday decisions. Ignoring transaction costs, slippage, and spread can make a marginally profitable strategy appear much better than it truly is. Always include realistic commission and slippage estimates and test on out-of-sample data.
What factors influence exchange rate movements?
Key drivers include interest rate differentials between central banks, economic indicators (GDP, employment, inflation), geopolitical events, trade balances, and market sentiment. Central bank policy decisions often cause the largest short-term moves.
Is my data stored or sent to a server?
No. All calculations run entirely in your browser using JavaScript. No data you enter is ever transmitted to any server or stored anywhere. Your inputs remain completely private.
How do I interpret the result?
Results are displayed with a label and unit to help you understand the output. Many calculators include a short explanation or classification below the result (for example, a BMI category or risk level). Refer to the worked examples section on this page for real-world context.