Trading Expectancy: The Only Metric That Predicts Whether You'll Survive

Ask a trader how they're doing and they'll quote a win rate. Ask them if the strategy is actually profitable and most of them have to go check, because win rate and profitability aren't the same question. One measures how often you're right. The other measures whether being right pays for being wrong.

That second question has an answer, and it's a single number: trading expectancy.

What Trading Expectancy Actually Measures

Expectancy is the average amount you make or lose per trade, once you account for how often you win, how often you lose, and how big each outcome is. The formula:

Expectancy = (win% × average win) − (loss% × average loss)

Run that number and you get a dollar figure — or an R-multiple, if you size in risk units — that tells you what one trade is worth to you on average, over a large enough sample. Positive expectancy means the strategy pays over time. Negative expectancy means it doesn't, no matter how good it feels in the moment.

Win rate alone tells you nothing about that. It's the size of the wins and losses, not just their frequency, that decides whether the math works.

The 60% Win Rate That Loses Money

Take a trader running a strategy with a 60% win rate. Average win: $100. Average loss: $200. That ratio is common — it shows up whenever a trader lets winners go small (taking profit early, out of relief) and lets losers run large (holding, hoping, out of denial).

Expectancy = (0.60 × $100) − (0.40 × $200) Expectancy = $60 − $80 Expectancy = −$20 per trade

This trader is right most of the time and still bleeding $20 a trade. Over 100 trades, that's a $2,000 hole, built entirely from being right more often than they're wrong. The win rate is genuinely good. It's just paying for a loss size that's twice the win size, and the math doesn't care how the trader feels about being right 60% of the time.

The 40% Win Rate That Prints

Now take a different trader. Win rate: 40%. Average win: $300. Average loss: $100. This is the profile of someone who cuts losses fast and lets winners run — a smaller number of correct calls, but each one pays out three times what a wrong call costs.

Expectancy = (0.40 × $300) − (0.60 × $100) Expectancy = $120 − $60 Expectancy = $60 per trade

Same 100 trades, this trader nets $6,000. They're wrong 60% of the time — more often than not — and it's the more profitable strategy by a wide margin. Nobody feels good being wrong six times out of ten. That discomfort is exactly why so many traders unconsciously optimize for a high win rate instead of a high expectancy: it feels better to be right often, even when being right often is the losing structure.

Why This Is the Number, Not Win Rate

Win rate is a vanity metric because it can be gamed by instinct without you noticing. Cut winners short and let losers run, and win rate climbs while expectancy quietly goes negative. It's the easiest way to feel like a good trader while slowly losing money, because every individual trade that goes right reinforces the wrong lesson.

Expectancy forces the win-size and loss-size into the equation, which is where the real decision-making happens. Every trade has two separate choices baked into it: when to get in, and how the position gets managed once it's live — how quickly you cut it if it's wrong, how long you let it run if it's right. Win rate is mostly a function of the first choice. Expectancy is a function of both, which is why it's the number that actually correlates with the account balance.

This is also why expectancy is the right thing to journal toward, not win rate. A journal that only tracks wins and losses as a percentage is tracking the wrong axis. A journal that tracks average win size, average loss size, and win rate together — and calculates expectancy from all three — tells you whether your process is one you should keep running or one you need to fix, independent of how any single trade felt.

Where Expectancy Breaks Down

Two things to hold in mind alongside the formula.

First, sample size. Expectancy is an average, and averages need enough trades to mean anything. A strategy with genuinely positive expectancy can still lose money over ten trades if the losses cluster early — that's variance, not a broken edge. Judging expectancy off a small sample is how traders abandon working strategies and keep broken ones, because ten trades isn't enough data to tell the difference.

Second, expectancy assumes the win and loss sizes stay roughly consistent with your historical averages. If a trader lets one loss run five times larger than their normal average loss — the classic "it'll come back" trade — that single outlier can wipe out the expectancy built from the last fifty trades. The formula only holds if the inputs stay disciplined, which is a position-sizing and stop-discipline problem, not a math problem.

What to Do With This Tomorrow

Pull your last 20 to 30 trades and calculate three numbers: win rate, average win, average loss. Run the formula. If the result is negative, you now know something your win rate was hiding from you — and you know exactly which lever to pull, because expectancy tells you whether the fix is win rate, win size, or loss size. If it's positive, you have a number worth defending on the trades that don't go your way, instead of a feeling worth chasing on the ones that do.

Either way, stop asking "was I right?" after each trade. Start asking "what did that trade do to my expectancy?" That's the question that predicts whether you're still trading a year from now.

I built Fourdesk to systematize this kind of tracking — the journal calculates expectancy automatically from your logged trades, and it's free.