How to calculate trading expectancy (in dollars and in R)

Expectancy answers one question: on average, how much does one trade make or lose? It combines win rate and the size of wins and losses into a single figure, which is why it is more useful than either number on its own.

This guide gives the formula, two worked examples, the R-multiple version for comparing strategies, and the limits of the number.

The formula

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

• Win rate and loss rate are fractions (60% = 0.60). Loss rate = 1 − win rate, if you have no break-even trades.
• Average win and average loss are positive amounts.

There is a shorter way to get the same number from a trade history:

Expectancy = total net result ÷ number of trades

Both give the same answer. The first form is useful because it shows why the number is what it is.

Worked example in dollars

A hypothetical history of 100 trades (an illustration, not real account data):

• 45 wins, average +$120
• 55 losses, average −$60

Expectancy = (0.45 × $120) − (0.55 × $60) = $54 − $33 = +$21 per trade.

Check it with the short form: 45 × $120 = $5,400 won; 55 × $60 = $3,300 lost; net $2,100 over 100 trades = $21 per trade. Same result.

This trader loses more often than they win and still has positive expectancy, because the average win is twice the average loss.

Expectancy in R-multiples

A dollar expectancy depends on position size. If you trade bigger next month, it changes even if your trading did not. To compare periods or strategies fairly, measure results in R, where 1R is the amount you planned to risk on the trade (the distance to your stop, in money).

Say the trader above risked $50 on every trade. Then:

• Average win = $120 ÷ $50 = 2.4R
• Average loss = $60 ÷ $50 = 1.2R
• Expectancy = (0.45 × 2.4R) − (0.55 × 1.2R) = 1.08R − 0.66R = +0.42R per trade

Notice something in that example: the average loss is 1.2R, more than the planned risk of 1R. Losses bigger than the planned stop usually mean slippage, gaps, or stops being moved. R-multiples make that visible; dollar figures hide it.

R also lets you compare strategies traded at different sizes:

	Strategy X	Strategy Y
Expectancy in dollars	$30 per trade	$12 per trade
Planned risk per trade	$100	$20
Expectancy in R	0.3R	0.6R

X makes more money per trade, but Y earns twice as much per unit of risk.

To use R, you need the planned risk for each trade, which means recording a stop-loss (or the amount you intended to risk) when you enter. Without it, you can only measure expectancy in money.

Use net results, not gross

Commission and overnight swap are paid on every trade, win or lose. If your expectancy is calculated before costs, it is too optimistic.

Using the same 100 trades, suppose costs average $4 per trade. Net expectancy = $21 − $4 = $17 per trade. For a strategy with a thin edge, this can be the difference between a positive and a negative number. See gross vs net P&L for how to find your real costs.

How many trades before you trust it?

Expectancy is an average, and averages from small samples move around a lot. A single large win in 20 trades can make a losing approach look profitable.

There is no fixed number that makes an estimate "reliable", but some practical guidance:

• Under 30 trades: treat expectancy as a first impression only.
• Around 100 trades of the same setup: you can start to make decisions, especially if expectancy is clearly positive or clearly negative.
• Check stability: split your history in halves (or by month). If expectancy is positive in one half and negative in the other, you do not have a clear answer yet.
• Check concentration: remove your single largest win and recalculate. If expectancy flips negative, your result depends on one trade.

What expectancy does not tell you

Expectancy is the average, not the path. Two strategies with the same expectancy can feel very different:

• One may have long losing streaks and deep drawdowns that you, or a prop firm's loss limit, cannot tolerate.
• One may need many more trades to realise its edge.

Look at expectancy together with maximum drawdown and the longest losing streak before deciding a strategy is worth trading.

A common naming trap

Some sources use "expectancy ratio" for average win ÷ average loss. That is a different metric, usually called the payoff ratio. It ignores how often you win, so it cannot tell you on its own whether you make money. When you compare numbers between tools or articles, check which definition they use.

Key points

• Expectancy = (win rate × average win) − (loss rate × average loss), or simply net result ÷ number of trades.
• Express it in R to compare strategies and periods traded at different sizes.
• Calculate it after commission and swap.
• Trust it more as the sample grows and when it holds across different periods.
• Read it alongside drawdown and losing streaks.

If your win rate is high but expectancy is negative, read high win rate but still losing money next.

Where TradeYar fits: the free dashboard shows expectancy as net P&L divided by the number of closed trades with a known result, so commission and swap are already included. It is calculated from the file you import; you do not need to enter anything by hand.