How to Calculate Trade Expectancy From Your Journal Data
Every closed trade is a row in your journal. Trade expectancy compresses those rows into one number: the average amount you make or lose per trade (TradesViz). It is a useful check on whether your setups actually pay, and it only needs the numbers most journals already store: win rate, average winner, and average loser.
What trade expectancy means
Expectancy answers a simple question. If you run a strategy many times, does the average result pay for the losses in between? A positive expectancy means the approach earns over many trades; a negative expectancy means it bleeds, even when the win rate looks decent (TradeLyser). Expectancy is not a prediction for the next trade. It summarizes a sample of closed trades, so the quality of the sample matters as much as the math.
Expectancy can be quoted in dollars or in R-multiples. In R-multiples, each trade is expressed as a multiple of the risk you took, which lets you compare setups of different position sizes (Tradeify).
The trade expectancy formula
Most references state the trade expectancy formula the same way:
`E = (Win% x Average Win) - (Loss% x Average Loss)`
Where:
This formula comes from TradesViz, which defines expectancy as the average profit or loss you can expect per trade.
- Win% is winners divided by total closed trades.
- Average Win is the mean profit of winning trades.
- Loss% is losers divided by total closed trades, or 1 minus Win% when there are no breakeven trades.
- Average Loss is the mean loss of losing trades.
How to calculate it from your journal, step by step
Keep two data-quality checks in mind. A small sample can swing the result on one outlier, and ignoring spread, commission, and slippage flatters the average winner while understating the average loser (Tradeify).
- Choose a defined sample of closed trades. Open trades have no final P&L yet, so leave them out.
- Sort the trades into winners and losers. If breakeven trades exist, decide in advance how to treat them and stay consistent.
- Calculate win rate: winners divided by total closed trades.
- Calculate average win and average loss. For dollars, sum the profit of winners and divide by the number of winners, then do the same for losses. For R-multiples, convert every outcome to a multiple of risk before averaging.
- Apply the formula above.
Worked example
Trader A wins 40% of trades. Average win is $400, average loss is $150:
E = (0.40 x 400) - (0.60 x 150) = 160 - 90 = $70 per trade
Trader B wins 70% of trades. Average win is $100, average loss is $200:
E = (0.70 x 100) - (0.30 x 200) = 70 - 60 = $10 per trade
Win rate alone makes Trader B look stronger, but expectancy says Trader A's average closed trade is worth more.
Using expectancy in your journal review
The formula is only as good as the data behind it. A trading journal is the natural place to keep that data clean, because every fill, fee, and exit is recorded at the time instead of reconstructed from memory. Astro Trading Journal is one option: it syncs fills from brokers and exchanges such as MetaTrader 5 and TradeLocker, while manual entry works whether or not a broker is connected. Its performance analytics report net and gross P&L, win rate, and average win versus average loss, broken down by symbol, asset class, direction, and setup, so you have the formula's inputs without rebuilding the numbers from broker statements. Compare playbooks side by side to see which setup is actually carrying the expectancy. For the current list of supported connections, see supported brokers and exchanges.
Frequently asked questions
What is a good trade expectancy?
Any positive number means the sample made money on average; any negative number means it lost. Whether an edge is meaningful depends on the size of your average risk and the consistency of the sample, not on the raw number alone.
Should I calculate expectancy in dollars or R-multiples?
Both work. Dollars are easy to read against your account balance; R-multiples make results comparable across trades of different sizes because every outcome is measured against the risk you took (Tradeify).
How many trades do I need before expectancy is reliable?
There is no fixed number. A short sample can be dominated by a single outlier, so review enough closed trades for the average to stabilize. Treat the result as a description of what has happened, not a guarantee of what will happen next (Tradeify).
Can I have a high win rate and negative expectancy?
Yes. The formula subtracts the average loss side from the average win side, so small average wins and large average losses can leave a high-win-rate strategy with negative expectancy. The worked example above shows the reverse as well.
Does Astro calculate expectancy automatically?
Astro's analytics reports the inputs directly: net P&L, win rate, and average win versus average loss, with breakdowns by setup and symbol. You can plug those numbers into the formula above to get expectancy for a single playbook or the whole journal. Broker sync is a Premium feature, and manual entry is available on the free plan; see Astro pricing for plan details.