R multiple, win rate and profit factor explained
R multiple, win rate, profit factor and expectancy describe different things, and quoting one without the others is how people talk themselves into approaches that lose money. Here is what each measures, where each misleads, and how many trades you need before any of them means anything.
R multiple
An R multiple expresses a result in units of the risk you took. Risk $100 and make $250, and the trade is +2.5R. Risk $100 and lose it as planned, and the trade is −1R.
The value is that it makes trades of different sizes comparable. A $40 profit on a $20 risk (+2R) was a better piece of work than a $300 profit on a $600 risk (+0.5R), and only R makes that obvious at a glance.
It also reframes losses usefully. A −1R loss is the system working: you were wrong and paid the amount you agreed to pay. A −3R loss means something broke — you widened the stop, or the market gapped past it.
Win rate
The share of closed trades that made money. It is the most quoted figure and the least informative alone, because it says nothing about the size of the wins and losses.
| Approach | Win rate | Average win | Average loss | Per 100 trades |
|---|---|---|---|---|
| A | 80% | +0.5R | −3R | 80(0.5) − 20(3) = −20R |
| B | 35% | +3R | −1R | 35(3) − 65(1) = +40R |
Approach A wins four times out of five and loses steadily. Approach B is wrong about two-thirds of the time and is the one you would rather have. Win rate is only meaningful next to the size of the outcomes.
Profit factor
Gross winning money divided by gross losing money. A profit factor of 1.5 means your winners brought in one and a half times what your losers cost, across the trades you logged.
- Below 1.0 — the recorded trades lost money overall.
- Around 1.0 — roughly break-even before you account for anything you forgot to log.
- Well above 2.0 on a small sample — more likely a sign of a short sample or one outsized winner than a strong edge.
It describes the sample you have. It is not a prediction, and it is heavily distorted by single large results in small logs.
Expectancy, the one that ties them together
Expectancy is the average R you can expect per trade:
(win rate × average win in R) − (loss rate × average loss in R)
For approach B above: (0.35 × 3) − (0.65 × 1) = 1.05 − 0.65 = +0.4R per trade. Over 100 trades that is +40R, matching the table.
Expectancy is the number worth watching, because it cannot be gamed by moving one component. Raising your win rate by taking profits early lowers your average win, and expectancy shows the trade-off that win rate alone conceals.
Average R
The mean R across trades recorded in R. It approximates expectancy from your actual log rather than from estimated averages. RATTLE shows it for trades logged in R only, and deliberately does not blend it with percentage-return entries, because averaging two different units produces a number that means nothing.
How many trades before any of this counts
More than people want to hear. The honest position is that these are descriptive statistics on a small, noisy sample, and they stabilise slowly.
| Trades logged | What the numbers are worth |
|---|---|
| Under 20 | Essentially noise. Useful for checking you are following the plan, nothing more. |
| 20–50 | Shape starts showing. Still dominated by individual results. |
| 50–100 | Worth looking at for obvious problems. Not proof of an edge. |
| 100+ | Beginning to describe your behaviour, within one market regime. |
Sample size is the whole argument. A profit factor of 3.0 across twelve trades and one across two hundred are not comparable claims. Whenever you quote one of these figures — to yourself most of all — say how many trades it covers.
One more caveat: regime
Even a hundred trades sample only the conditions those trades happened in. A trend-following approach logged through a trending quarter will look excellent, and the numbers will not warn you that the market did the work. Date your conclusions as well as your trades.
See these figures for your own logNext
For what to record so these numbers are trustworthy, see how to keep a trading journal. For the habits that quietly inflate them, see paper trading mistakes that make results misleading.