Trading Expectancy: How Much You Make per Trade, on Average

Reviewed by Leon Moyer - Published October 9, 2026 - Last reviewed October 9, 2026

Trading expectancy is the average profit or loss per trade for a group of trades, after fees. Expectancy = (win rate x average win) - (loss rate x average loss). A positive expectancy means that group of trades made money on average; a negative one means it lost money, however often it won.

Expectancy is the single most useful number in a trading journal, because it answers the question an edge is about: on average, what does one more trade like this add to the account? It builds on the strategy and setup fields from How to Find Your Trading Edge, since expectancy only means something for a group of trades that were made the same way.

How do you calculate trading expectancy?

You need four numbers from your journal, all after fees:

• Win rate: winning trades / total trades.
• Loss rate: losing trades / total trades.
• Average win: total dollars won / number of winners.
• Average loss: total dollars lost / number of losers, written as a positive number.

Then multiply each average by how often it happens and subtract. A shortcut gives the same answer: expectancy = net profit / number of trades.

Trades that broke exactly even can be left in the trade count with a result of zero. They lower the win rate and the loss rate without changing the net profit, so the shortcut still works.

Why can a high win rate still lose money?

Because win rate leaves out the size of the losses. Options strategies that sell premium often win most of the time, collecting a small credit, and occasionally take a loss many times larger. Whether that adds up to money depends on the balance between the two.

What win rate do you need to break even?

Setting expectancy to zero and solving gives a useful target. Break-even win rate = average loss / (average win + average loss).

• Journal A: $120 / ($100 + $120) = about 55%. It wins 60%, so it clears the bar.
• Journal B: $250 / ($50 + $250) = about 83%. It wins 80%, so it falls short.

This is the most practical way to use the formula. If you sell a spread that typically makes $100 and loses $300 when it goes wrong, you need to win at least $300 / $400 = 75% of the time just to break even after fees. Your journal tells you whether you do.

How do you calculate expectancy in R-multiples?

Dollar expectancy depends on position size: doubling every trade doubles it. Expectancy in R, where R is each trade's planned risk, does not, so it is the fairer way to compare strategies traded at different sizes.

The simplest form uses each trade's R-multiple: expectancy in R = sum of R-multiples / number of trades.

If every loser in Journal A lost exactly its planned risk, an average loss of $120 would be 1R and an average win of $100 would be about 0.83R. Expectancy = (0.60 x 0.83R) - (0.40 x 1R) = about +0.10R per trade. Journal B, on the same basis, is (0.80 x 0.2R) - (0.20 x 1R) = -0.04R.

In practice, losers rarely lose exactly 1R, so average the R-multiples you recorded rather than assuming.

What can expectancy not tell you?

Expectancy is an average, and averages hide things:

• One huge trade can carry the whole number. Profit factor shows how to check for that.
• Mixed strategies blur each other. A positive expectancy for the whole journal can hide one strategy that loses money, which is what analyzing performance by strategy and setup is for.
• Small samples are noisy. Forty trades give a rough estimate, not a proof, as How Many Trades Do You Need? shows.
• Open trades are not results yet. Calculate expectancy on closed trades only, including any assigned stock you have since sold.