Dollars lie. A $500 win on huge size is worse trading than a $100 win on disciplined size, but a P&L column can't tell you that. This lesson installs the unit that can: R — your predefined risk per trade — and the statistic built from it, expectancy, which converts a pile of trades into a verdict about your edge.
Define 1R before you're in
Before entry, you decide two things: where the trade is wrong (the stop) and how much money you're willing to lose if it's wrong. That amount is 1R. Everything that happens afterward is measured against it: a win that banks twice your risk is +2R; a loss at the stop is −1R; a loss past your stop — the cardinal sin — is −1.5R or worse, and now it's visible instead of buried in dollar noise. This framework was popularized by Van Tharp, and it has one deep purpose: it makes every trade, in every market, on any size, comparable.
Expectancy: your edge, in one number
Read that example carefully, because it breaks the beginner's obsession with win rate: this system loses most of the time and is still solidly profitable — 100 trades ≈ +20R. Meanwhile a system that wins 70% of the time but takes −3R disasters when wrong is a slow-motion blowup. Win rate and payoff size only mean something multiplied together; that's the whole lesson of expected value, and it's why professionals discuss trades in R while amateurs discuss them in dollars.
Two honest caveats. First, expectancy is only as real as the sample behind it — twenty trades tell you almost nothing (the variance math is on the ruin page). Second, expectancy assumes your losses actually stop at −1R. The entire statistic is corrupted by one "just this once" — which is why Lesson 1 came first.
The journal makes it real
None of this works as theory. Log every trade with its planned 1R and its result in R — the trading journal page has the template. After 50–100 trades you own something most traders never see: a measured expectancy, an honest average loss, and a distribution that shows exactly where your discipline leaks.
Assignment
Convert your last 20 trades (real or paper) into R. Compute your win%, average win, average loss, and expectancy. Most traders discover their average loss is bigger than they believed — that discovery is worth more than any indicator you'll ever add.