Who is it for?
Users with reviewable data or a trade sample Anyone testing assumptions before real capital
Statistical Strategy Analysis
Expectancy Analyzer
Calculate trading expectancy from win rate, average win/loss and costs, then review profit factor, break-even win rate and uncertainty.
FreeNo installationEducational & analytical
Free with a TupTrader account
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The guide and calculation method stay public on this page. Sign-in is only required to open the interactive workspace.
Tool guide
What is trading expectancy?
Expectancy is the average outcome per trade under a specified win/loss model. This version subtracts a constant per-trade cost from expectancy, so the break-even win rate includes the same cost. The displayed confidence interval is a simplified approximation for an IID two-outcome model with fixed win and loss sizes.
Logic / formula
Net E = p×W − (1−p)×L − C; cost-adjusted break-even win rate = (L + C) ÷ (W + L). Displayed profit factor is gross, before C.
Read the output
Net expectancy is the primary result. Read it with cost-adjusted break-even win rate, gross PF, sample size and the approximate interval; this CI is not a full model of variable win/loss distributions.
TT-FT-009 · versioned engine expectancy@2.0.0 · educational/analytical use; not investment advice.
Full guide, examples, and sources
When should you not rely on it?
A small, incomplete, or cherry-picked sample Using the result as a guarantee of future performance
Logic, formula and methodology
Expectancy is the average outcome per trade under a specified win/loss model. This version subtracts a constant per-trade cost from expectancy, so the break-even win rate includes the same cost. The displayed confidence interval is a simplified approximation for an IID two-outcome model with fixed win and loss sizes. Net E = p×W − (1−p)×L − C; cost-adjusted break-even win rate = (L + C) ÷ (W + L). Displayed profit factor is gross, before C.
Net and gross expectancy, cost per trade, gross and approximate net profit factor, break-even win rate, projected R and money outcome, standard error, 95% confidence interval, and approximate probability that expectancy is positive.
Worked example
Example
45% win rate, 2R average win, and 1R average loss
With a 45% win rate, 2R average win and 1R average loss, win rate alone is insufficient; payoff size determines the expectation.
With a 45% win rate, 2R average win and 1R average loss, win rate alone is insufficient; payoff size determines the expectation.
How to read the result
No single metric is sufficient for judgement. Sample size and data quality are part of the result.
Read net expectancy together with profit factor, break-even win rate, sample size and the uncertainty interval. If the interval crosses zero, the sample is not decisive. Outlier sensitivity shows whether a few large trades are carrying the estimate.
What the TupTrader version adds
The value of this version is not cosmetic; the result, assumptions and workflow are connected to the practical capabilities below.
- Outcome contribution decomposition
- CI visualization
- CI-crosses-zero warning
- Sample-size strip
- Outlier sensitivity
- Cost sensitivity
- Break-even comparison
- Saved sample
Turn the result into a workflow
Related tool →Validate the result with a second tool. Run out-of-sample or Monte Carlo analysis. Record executable rules in the plan.
Common mistakes and limitations
- Overfitting or choosing parameters after seeing results
- Omitting costs and unfavourable trades
- Mixing incompatible samples
- A simple two-outcome model and normal approximation may miss tails, serial dependence, regime shifts and multimodal outcomes. Positive historical expectancy does not guarantee a future edge.
Frequently asked questions
Does a high win rate imply high expectancy?
No. Average win, average loss and costs matter; win rate is only one component.
What does it mean if the interval crosses zero?
Under the model and sample size, uncertainty is large enough that the sign of the edge is not firmly established.
Are profit factor and expectancy the same?
No. Profit factor compares gross profits with gross losses; expectancy expresses average value per trade.
Sources and research method
This guide combines the tool’s versioned specification, the earlier TupTrader educational page and the authoritative sources below. External sources are used for definitions and scientific boundaries, not for signals.
- CME Group — The Mathematics of Trading SuccessMathematical expectation from win/loss frequency and average win/loss size.
- NIST — Bootstrap confidence intervals / resampling documentationEstimating uncertainty from resampled statistics and recognizing unstable estimates.
This tool is for education, scenario analysis and process control. It is not investment advice, a buy/sell signal or a guarantee of future performance.