How to track R-multiples in a trading journal

Dollars tell you what the account did. R-multiples tell you what your decisions did. A 300 dollar loss can be a perfectly executed trade, and a 300 dollar win can be a size mistake that got lucky.

One R is the amount you planned to lose if your original stop was hit. Every result gets divided by that number, and suddenly a futures scalp, a stock swing and a crypto trade sit on the same scale.

Fix 1R before the entry, not after the exit

R breaks the moment you decide what your risk "was" after the trade closed. Record the planned stop and the position size at entry, while the number is still honest.

Worked example. You enter long at 100 dollars, stop at 98, size 100 shares. Planned risk is 200 dollars, so 1R = 200.

• Exit at 104: +400 dollars, which is +2R.
• Stop hit as planned: −200 dollars, which is −1R.
• You move the stop and exit at 96.60: −340 dollars, which is −1.7R.

That third line is the one worth staring at. In dollars it looks like a bad day. In R it's 1.7 planned losses in a single trade, and it takes almost two clean 1R winners to repair.

What to record for every trade

Ten fields, under 2 minutes per trade:

Use net results. A trade marked +1R before costs can be +0.82R after them, and that gap decides whether a high-frequency setup is worth trading at all. If you want to see the drag without paying for it, GlanWick's simulator prices crypto trades with 0.4% fees and 0.01% to 0.05% slippage per order.

The 20-trade example that dollars hide

Here's a month that looks fine on the account statement and terrible in R.

The account is up 140 dollars. Per trade, the month averaged −0.09R. The dollar profit came from taking 3 times the planned risk on a handful of trades, and the R column says the process behind them lost money.

That's the whole argument for R. Dollars reward you for size. R grades the decision.

Scale-outs, partials and the mistake that inflates win rates

Keep 1R fixed at the full planned risk of the original position, then divide the total net result of the whole trade by it.

• Half off at +1R, the rest stopped at breakeven: total +0.5R, not +1R.
• Half off at +1R, the rest at +3R: total +2R.

Log the whole position as one trade. Logging each partial as its own win turns a 45% win rate into a 70% one and quietly deletes the trades that hurt.

Tag the rule breaks, or the average lies

A −1R loss where the stop did its job and a −1.7R loss where you moved it both cost money, and they need opposite fixes. Tag them: moved stop, added to loser, oversized, entered outside a listed setup, re-entered within 10 minutes of a loss, traded after the daily stop.

Then read expectancy twice: across all trades, and across rule-following trades only. If the rule-following group is positive and the total is negative, the setup works and the execution is where the money goes. That is an execution problem, and a new indicator will not touch it.

The formula, in R: (win rate × average win in R) − (loss rate × average loss in R). At a 45% win rate with +2R winners and −1R losers, that's (0.45 × 2) − (0.55 × 1) = +0.35R per trade.

Read the distribution, not just the average

A +0.2R average built on one +8R outlier is a story, not an edge. Look at the shape:

• How many losses went past −1R, and why?
• How many winners were cut below +0.5R?
• Where does the biggest single R loss sit against your daily limit?

For prop firm traders that last question is the one that ends accounts. Your edge is measured in R, the firm's daily loss limit is measured in dollars, and three ordinary −1R losses can sit uncomfortably close to a line you can't cross.

Sample size, honestly

Ten trades are noise. Thirty start to suggest something. A hundred with stable rules give you a number you can argue with. Mark the date whenever you change the setup definition, the session you trade or the stop logic, and don't blend the old behavior into the new average.

GlanWick shows R-multiple distribution and expectancy in R on every plan, including the free one, with win rate per setup and the drawdown chart from Starter. The useful output is the receipt: it shows where execution starts slipping, trade by trade.

Start tonight

Take your last 20 closed trades. Add two columns: planned risk at entry, and net result. Divide. Then sort by R and read the worst three trades with the tags you just wrote.

If the R column disagrees with the dollar column, believe the R column. It's measuring the part of trading you actually control.