Definition, as the journal computes it
- Expectancy (money) = net P&L ÷ closed trades, breakevens included. It comes back exact and rounded to a whole minor unit, halves away from zero.
- Expectancy in R is the average R (below). The engine returns the same object for both.
- Average win = net P&L of winning trades ÷ number of winning trades.
- Average loss = net P&L of losing trades ÷ number of losing trades. It is negative.
From the journal's written definitions: Expectancy; Average win and average loss
On this page
What is expectancy in trading?
Expectancy is what an average trade made: your net P&L divided by the number of closed trades, breakevens included. It is the one number that combines how often you win with how much you win and lose.
Positive expectancy means your trades made money on average over the period, after costs. Negative means they lost.
How do you calculate expectancy?
Expectancy = net P&L ÷ closed trades. The sample account made $100.00 over 10 closed trades, so its expectancy is $100.00 ÷ 10 = +$10.00 per trade.
The journal rounds it to the cent, halves away from zero, and shows the working: “Net P&L ÷ closed trades = $100.00 ÷ 10 = +$10.00 per trade.” The sample’s trades are listed on the trading metrics page.
How does expectancy relate to win rate and average win and loss?
Expectancy = win rate × average win + loss rate × average loss, where the average loss is negative. For the sample account that is 0.40 × $97.50 + 0.50 × (−$58.00) = $39.00 − $29.00 = $10.00, the same answer.
- Wins0.40 × $97.50= $39.00
- Losses0.50 × −$58.00= −$29.00
- Expectancy$39.00 − $29.00= $10.00
The two ways agree exactly because breakevens are counted as closed trades: they’re in the 10 that every rate is divided by, and they add $0.00. A tool that leaves breakevens out of the win rate won’t get the same answer this way.
What is expectancy in R?
Expectancy in R is your average R: the sum of R over the trades that have an initial stop, divided by how many there are. It compares trades of different sizes fairly, because each one is measured against what it risked.
A trade logged without a stop has no R, so expectancy in money and in R can cover different sets of trades. The journal says how many trades were left out. See how R-multiples are measured.
How are average win and average loss worked out?
Average win = net P&L of winning trades ÷ number of winning trades, and average loss is the same for losing trades. Breakevens are in neither, and with no wins (or no losses) the average is shown as unavailable rather than zero.
In the sample account the winners made $390.00 over 4 trades, an average win of $97.50, and the losers lost $290.00 over 5 trades, an average loss of −$58.00.
Is positive expectancy enough?
It’s necessary, but on a small sample it can be luck. The journal flags fewer than 30 closed trades as a small sample, and even after that a few large trades can carry the average.
In the sample account, the largest win alone (+$150.00) is more than the whole net P&L (+$100.00). Take that one trade out and the other 9 lost $50.00 between them. Check the largest win and loss beside expectancy before trusting it.