Expectancy is the average amount you can expect to win (or lose) per trade over many trades. It's the number that decides whether a strategy is profitable — and it explains why win rate alone is meaningless. Let's compute it with real numbers.
The equation
Expectancy = (win% × average win) − (loss% × average loss). Say you win 45% of trades, your average winner is $150, and your average loser is $80. Then: (0.45 × $150) − (0.55 × $80) = $67.50 − $44.00 = +$23.50 per trade. Positive expectancy — despite a sub-50% win rate — because winners are nearly 2× losers. Over 200 trades that's roughly +$4,700 of expected edge, before costs.
Why it beats win rate
Flip it: a 70% win rate sounds great, but if your average winner is $50 and average loser is $150, expectancy = (0.70 × $50) − (0.30 × $150) = $35 − $45 = −$10 per trade. You win most trades and lose money, because the few losers are too big — the classic cut-winners-let-losers-run trap. Expectancy captures both frequency and size; win rate captures only frequency, which is why it lies.
Win rate tells you how often you're right. Expectancy tells you whether being right that often, by those amounts, actually makes money. Only one pays the bills.
Using it in R
Expressed in R-multiples, expectancy is your average R per trade — cleaner because it's sizing-independent. Track it over a real sample (dozens of trades, not five) via your journal metrics, and let it, not any single day, tell you whether your edge is real. A positive expectancy plus consistent sizing plus enough trades is, quite literally, the whole game. NoVo's job is to protect that expectancy with clean fills and disciplined exits.