Most trade logs die in the first two weeks.
Not because logging trades is hard. Because the spreadsheet does not do anything with what you type into it.
You enter the date, the ticker, maybe a note. Then nothing happens. No stats. No pattern. A column of numbers getting longer and less useful by the week.
So the tab sits open, half filled in, until it does not get opened at all.
A trade log that does not calculate anything is a diary.
Log an entry, an exit, a size, and a stop, and this one does the rest on its own. Planned risk. Realized P&L. R-multiple. Win rate. Expectancy. Profit factor.
Pick any Monday and Sunday and the Weekly Review tab pulls the exact trade count, win rate, and total R for that week, straight from the log, no formula-building required on your end.
You fill in eight columns. It calculates the other three, plus a full stats dashboard that updates the second a new trade lands.
Two hundred rows. Blue cells to fill in, black cells that do the math. Opens in Excel, Google Sheets, or Numbers.
A Trading Habits Tool
The Trade Log
A trading journal and stats dashboard that calculates itself.
- Format Excel workbook (.xlsx), opens in Excel, Google Sheets, or Numbers
- Tabs Trade Log, Weekly Review, Stats Dashboard, Instructions
- Capacity 200 trade rows and 26 weeks of review rows, both extendable
- Delivery Instant download right after checkout
Log the trade. The math handles itself.
What's Inside
What's Inside The Trade Log
- 01A 200-row trade log with 8 columns you fill in and 3 that calculate themselves the moment you enter a trade: planned risk, realized P&L, and R-multiple.
- 02A Weekly Review tab where you type a Monday and a Sunday date, and the trade count, win rate, total R, and total dollar result for that exact week pull straight from the log.
- 03A Stats Dashboard with nine running numbers, including win rate, average win, average loss, expectancy, largest win, largest loss, and profit factor, all recalculating live.
- 04A built-in Long/Short dropdown, so every row stays consistent and a stray typo never breaks a formula.
- 05Formulas that leave an open position blank instead of throwing an error, so a trade you have not closed yet does not skew today's numbers.
- 0626 weeks of Weekly Review rows built in, each with two open note columns for what worked and what you'd adjust.
- 07Color-coded cells, blue for what you type, black for what calculates, so you always know what's safe to edit.
- 08A worked example row on the Trade Log tab showing exactly how the math flows before you log your first real trade.
- 09No macros, no add-ons, no subscription. One file. Opens in Excel, Google Sheets, or Numbers.
HABITS
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Behind The Tool
Where The R-Multiple And Expectancy Came From
The Concept
A trading journal only becomes useful once results stop being measured in dollars and start being measured against the risk taken to get them. A $500 win means almost nothing on its own. A $500 win on a trade that risked $250 (a 2R win) means something different from a $500 win on a trade that risked $2,000 (a 0.25R win), even though the dollar result is identical.
That's the idea behind the R-multiple: every trade's result expressed as a multiple of the amount that was actually risked going in, so wins and losses of wildly different sizes can sit in the same column and mean the same thing.
Where It Comes From
Trading psychologist and coach Van K. Tharp laid out the R-multiple and its companion, expectancy, in his 1998 book Trade Your Way to Financial Freedom. His core point: win rate by itself doesn't say whether a system makes money. A system that wins 40% of the time can still be profitable, and a system that wins 60% of the time can still lose money, once the size of the average win and average loss is factored in.
Trading journals themselves go back further, most notably to trader and author Alexander Elder's Trading for a Living (1993), which argued that a detailed, honest record of every trade is what separates traders who improve from traders who just repeat the same year.
Why Win Rate Alone Doesn't Tell The Story
Illustrative example, not a real trading result. Expectancy = (win% × avg win R) − (loss% × avg loss R). The lower win-rate system is the profitable one here, because its average win is large relative to its average loss. This is exactly what the Stats Dashboard's expectancy figure is built to catch.
Try It: Calculate Your Own Expectancy
Same formula as the chart above, run on your own numbers. Pull the win rate and average win/loss size off your last 20 or 30 trades and see whether your system's real expectancy is positive, not just its win rate.
Common Questions
What's the difference between R-multiple and just tracking dollars?
Dollars don't travel between trades. A $500 win means something different depending on what got risked to earn it. R-multiple fixes that: every result gets expressed as a multiple of the amount risked, so a 2R win and a 0.25R win sit in the same column honestly instead of looking identical at $500 each.
Can a system with a 60% win rate actually lose money?
Yes, and Van Tharp's 1998 book is largely built around proving it. If the average loss is bigger than the average win, a high win rate can still produce a negative expectancy. The chart above shows exactly that: a 60% system losing to a 40% system once average win and loss size get factored in.
How many trades does it take before expectancy actually means anything?
The live calculator above works off whatever numbers you enter, but a stat built from five trades and a stat built from fifty tell very different stories. Most traders sampling their own results wait for 20 to 30 closed trades before trusting the expectancy number much.
Is a trading journal really necessary if the strategy already works?
Alexander Elder's 1993 argument, cited above, is that a journal is what separates traders who improve from traders who just repeat the same year on a loop. A strategy that works in theory and a strategy that's actually been tracked closely enough to prove it works are two different claims.