Expectancy
Definition
Expectancy is the average amount your strategy makes or loses per dollar risked — it's the single best number for evaluating whether your trading approach has a real mathematical edge.
Example
“Over 200 trades, my system had a 45% win rate, average winner of $220, and average loser of $90. Expectancy was positive at $54.50 per trade — meaning I have a real edge, just not a high win rate.”
Detailed Explanation
The formula is simple: Expectancy = (Win Rate × Average Win) — (Loss Rate × Average Loss). Positive expectancy means you expect to make money over a large enough sample of trades. Negative expectancy means you're losing money on average — possibly slowly, possibly quickly, but the direction is clear. Most retail traders have never calculated their actual expectancy, which is why they can't tell the difference between a rough patch and a broken system.
The power of expectancy is that it unites win rate and risk/reward into a single number. A 30% win rate with a 3:1 risk/reward ratio has positive expectancy. A 70% win rate with a 1:3 risk/reward ratio has negative expectancy. Neither metric alone is enough — you need both sides of the equation. This is why obsessing over win rate without equally tracking the size of wins and losses gives you an incomplete and often misleading picture of your performance.
Expectancy requires a meaningful sample size to be reliable. Fifty trades is barely enough; 100-200 is more useful. Small samples can show positive expectancy through luck alone. If you're trading a new strategy, track expectancy across at least 50 trades before drawing conclusions. If it's negative after 50 trades, investigate whether the issue is setup selection, entries, exits, or sizing — all of which affect the numbers differently. This forensic approach to performance review is what separates serious traders from those who guess.