Trading expectancy estimates the historical average outcome per trade of a system. It combines two things that can be misleading on their own: how often you win and how much you typically win or lose when you are right or wrong.
Basic formula
A common expression is:
Expectancy = (win probability × average win) − (loss probability × average loss)
If you work in R/risk units, the result can be expressed as R per trade. If you work in money, it will be expressed in currency.
Why win rate is not enough
A strategy can win frequently and still have negative expectancy if average losses are much larger than average wins. It can also have a modest win rate and positive expectancy if winning trades more than compensate for losses.
That is why a 70% win rate is not automatically superior to a 45% win rate.
What positive expectancy means
Positive historical expectancy means that, within the observed sample and under those rules, the average result per trade was positive. It does not mean the next trade will win and it does not guarantee that the relationship will continue unchanged.
Sample size matters
Expectancy can move dramatically with only a few trades. One unusually large winner can temporarily raise the average. Always display trade count and check whether the result persists as the sample grows or across different periods.
Expectancy by strategy, market or timeframe
A global expectancy is useful, but segmentation can reveal important differences. The same strategy may have positive expectancy in one market and negative expectancy in another, or behave differently across timeframes and directions.
Avoid combining too many variables when the resulting sample becomes tiny.
Metrics to review alongside expectancy
- Number of trades.
- Drawdown and maximum losing streak.
- Profit Factor.
- Average win and average loss.
- Distribution of outcomes in R.
- Plan adherence.
How Trading Life Journal can help
TLJ lets you compare expectancy and other metrics by strategy, market, timeframe and different filters. Combining the metric with sample size helps prevent conclusions based only on an attractive percentage.
Practical application
Expectancy estimates how much you can expect to gain or lose on average per trade if the observed behaviour continues. Unlike win rate, it combines how often you win with the size of wins and losses.
Review checklist
- Use net results after commissions and trading costs.
- Always show expectancy together with sample size.
- Segment by strategy, market and context when enough data exists.
- Check stability across different periods, not only the full history.
Frequently asked questions
What is a good expectancy?
There is no universal number. It depends on the unit used, costs, frequency, drawdown and risk. The important point is that it is positive, reasonably stable and supported by enough trades.
Can expectancy change if win rate stays the same?
Yes. A change in average winner or average loser changes expectancy even when the win rate remains unchanged.