Trading Expectancy and Break-Even Win Rate
Use win rate, average win, average loss, and costs to estimate expectancy and break-even win rate. Includes formulas and a hypothetical example.
By Kru Kook (Krittiya Khunabrimas)
What win rate leaves out
Win rate is the share of trades that make money, but it does not say whether average wins are larger than average losses. A high-win-rate system can still lose if its losses are much larger than its wins. A lower-win-rate system can have positive expectancy when average gains are large enough and costs do not erase the edge.
Expectancy per trade
Using units of initial risk, or R:
Pre-cost expectancy = (win rate × average win in R) − (loss rate × average loss in R)
Net expectancy = pre-cost expectancy − average cost per trade in R
Win and loss rates total 100% when there are no breakeven trades. If breakeven outcomes occur, keep them as a separate category or calculate from the net result of every trade so the denominator remains consistent.
Calculate a break-even win rate
If the average win is W and the average loss is L, expressed as a positive amount, the pre-cost break-even win rate is L ÷ (W + L).
With an average win of 1.6R and an average loss of 1R, the break-even rate is 1 ÷ (1.6 + 1) = 38.46% before costs. The actual break-even rate rises when commission, spread, and slippage are included.
A 100-trade example
Assume 45 wins averaging 1.6R and 55 losses averaging 1R. The pre-cost result is (45 × 1.6R) − (55 × 1R) = 17R, or 0.17R per trade.
If actual average costs equal 0.08R per trade, total costs are 8R and the net result is 9R, or 0.09R per trade. If initial risk varies by trade, calculate R from each trade’s initial risk and use a consistent method.
Interpret the result carefully
- Include fees and slippage rather than using price-only results.
- Segment results by system, product, time period, and market condition.
- Report the number of observations and uncertainty; do not draw conclusions from a handful of trades.
- Do not change rules after the fact to fit the data used to test them.
- Compare historical results with data that was not used to build the system.
Expectancy is an average from past observations, not a forecast for the next trade and not a guarantee of future performance.
Use this with our R-multiple guide and record results in the trading journal guide.