Expectancy

The formula

Expectancy = (win rate × average win) − (loss rate × average loss).

With a 40% win rate, an average win of $300 and an average loss of $100: (0.40 × 300) − (0.60 × 100) = 120 − 60 = $60 per trade. That is the number you expect to earn, on average, every time you take the setup — not on any individual trade, but across many of them.

Expressing it in R

Dollars change with account size, so most traders express expectancy in R — multiples of the amount risked per trade. Divide expectancy by average risk: $60 ÷ $100 risked gives 0.6R per trade.

That single number makes everything else calculable. Sixty trades at 0.6R is 36R of expected profit. If you risk 0.5% per trade, that is roughly 18% of the account before compounding — and it tells you immediately whether a profit target is reachable in the time available.

How many trades before you trust it

Also check consistency. Expectancy of 0.5R driven by one enormous winner among a hundred losers is a very different proposition from 0.5R produced steadily, even though the average is identical.

• Under 30 trades: essentially noise. Any number you calculate is dominated by luck.
• 30 to 100 trades: a rough indication, useful for spotting something badly wrong.
• 100 to 200 trades: a reasonable working estimate for most strategies.
• 200 or more: meaningful, provided the market conditions did not change halfway through.

Improving it

• Cut the setups that lose most. Filtering the worst-performing subset usually lifts expectancy more than finding new entries.
• Let winners reach their structural target instead of closing early out of discomfort.
• Reduce costs. Commission, spread and slippage come directly off expectancy on every trade.
• Take fewer, higher-quality trades. Frequency multiplies costs; quality multiplies edge.
• Keep risk per trade constant. Variable sizing makes the average meaningless.

Common mistakes

• Calculating it from too few trades and then changing strategy based on the result.
• Mixing different strategies or market conditions into one figure, which averages away the information.
• Excluding fees, slippage and partial exits, producing a number that does not match the account balance.
• Ignoring the distribution. One outlier can create positive expectancy that will never repeat.
• Optimising expectancy on historical data until it only describes the past.

Put it into practice

Frequently asked questions

What is a good expectancy?

Any positive figure is an edge. In R terms, 0.2R to 0.5R per trade is a solid, realistic range for many strategies. Consistently above 1R per trade is exceptional and worth double-checking for a data error.

Is expectancy the same as profit factor?

No. Profit factor is gross profit divided by gross loss. Expectancy is the average result per trade. They are related, but expectancy tells you what to expect from the next trade.

How do I calculate expectancy from my journal?

You need four numbers: win rate, average win, average loss, and the number of trades. The win rate and expectancy calculator computes it and shows profit factor alongside.

Can expectancy change over time?

Yes. Volatility regimes shift, spreads widen, and strategies decay as conditions change. Recalculate on a rolling window rather than treating one figure as permanent.

Related terms