Most trading journals fail not because traders stop writing in them, but because they log the wrong things. A spreadsheet with date, ticker, and P&L is not a journal. It is a receipt. A receipt cannot tell you which setups you should trade more of, which ones bleed your account, or whether your last losing streak was bad luck or a broken edge. For that you need a specific set of fields, captured the same way on every trade, every time.
This post walks through the fields that matter, why each one is there, and which ones almost everyone skips.
What a journal is actually for
A journal has two jobs. The first is execution audit: did you trade the plan, or something else. The second is edge discovery: which setups, which times, which conditions actually make you money over hundreds of trades.
Both jobs require structured data. If your "strategy" field is sometimes "ORB", sometimes "opening range breakout", and sometimes blank, you cannot filter, group, or measure it. The single biggest improvement most journals need is not more fields. It is the same fields, filled in the same way, on every single trade.
The execution fields (non-negotiable)
These are the bare-minimum mechanical fields. Without them you cannot reconstruct the trade later or compute any meaningful statistic.
- Date and time of entry, in your local timezone or the exchange's. Pick one and stick to it.
- Instrument: MNQ, ES, NQ, the specific contract. Not "futures."
- Direction: long or short.
- Size: number of contracts.
- Entry price.
- Stop price at the moment of entry. Not where you actually exited if it moved against you. The original stop.
- Target price at the moment of entry, or the rule that defines the target ("first 1R", "session high").
- Exit price and exit time.
- Commissions and fees for the round trip.
- Net P&L in dollars.
- R-multiple: the result expressed in units of initial risk. A trade with a 10-point stop that made 15 points is a +1.5R win regardless of size or instrument. R-multiples are how you compare a 1-contract MNQ trade to a 3-contract ES trade on the same axis. The system was popularized by Van Tharp in Trade Your Way to Financial Freedom and is the cleanest way to normalize trade outcomes.
If these eleven fields are not in your journal, nothing below matters yet. Fix this layer first.
Setup classification (the field that finds your edge)
Every trade belongs to a setup. The setup is the reason you took the trade. "Opening range breakout long," "VWAP rejection short," "second pullback in trend." The exact taxonomy is yours. The discipline is that every trade gets exactly one tag from a fixed list.
The point of the tag is not to organize the journal. It is to let you sort. After 200 trades you should be able to filter by setup and see the per-setup expectancy, win rate, average R, and trade count. Most traders discover that two or three of their tagged setups carry the entire account, and one or two bleed it dry. They never would have seen this without the tag.
A second tag layer is also useful: the trigger or confirmation that fired. The setup says "what kind of trade." The trigger says "what specifically made me click buy." This separation lets you discover that, say, your VWAP rejection setup wins 60% on momentum-bar triggers and 30% on inside-bar triggers. That is an actionable finding.
Context fields
Context fields describe the market around the trade. They are slower to fill but explain a lot when you review.
- Session: London open, NY pre-market, NY cash open, lunch chop, afternoon, overnight. Different sessions have different statistical behavior.
- Day of week. Mondays and Fridays often behave differently from midweek.
- Volatility regime: high, normal, low. A simple proxy is the day's expected range against its 20-day average.
- News on the calendar: was there a CPI print, an FOMC release, a Powell speech inside your trade window. The CME Group economic calendar and the BLS release schedule are the canonical sources.
- Trend context: was the daily, hourly, or session trend with you, against you, or unclear.
You will not use every context field on every trade. You will be very glad you have them when you review and notice that 80% of your losses happened in the lunch session.
Process fields (did you trade the plan)
This is the execution audit layer. It is not about whether the trade won. It is about whether you followed your own rules.
- Was this a planned trade or improvised: did you write the setup down before the session, or did it appear and you took it.
- Confirmations checked: a checklist of the conditions your strategy requires. If your rule is "only trade VWAP rejections that align with the daily trend," the journal should record whether that condition was actually true at entry.
- Rule violations: oversized, no stop, moved stop, traded outside session, traded after a losing streak rule was triggered. One field is enough. Yes or no, plus a note.
A profitable trader with a 70% rule-following rate is leaking money on the 30%. They cannot fix it until they can count it. This is the field that tells them.
Psychology fields
The fields most traders skip and the ones that explain the most variance over time.
- Emotional state at entry: calm, hesitant, eager, frustrated, revenge, FOMO. A short fixed list of options beats free text.
- Conviction level: a 1 to 5 rating. Not "how sure I was the trade would work" (you cannot know that), but "how cleanly the setup matched my rules."
- Distractions or fatigue: trading after a poor night of sleep, during a personal stressor, multitasking. One yes or no field with a note.
- Post-trade reflection: one to three sentences written within five minutes of the close. What happened, what you saw, what you felt. Not a critique. A snapshot.
Over a hundred trades, the emotional state field will reveal something specific to you. For some traders it is that "frustrated" entries lose at twice the rate of "calm" ones. For others it is that "eager" entries actually win more often. You cannot guess which one applies to you. The data will say.
The screenshot
One screenshot of the chart at entry, with your stop and target marked, attached to every trade. Not at exit. At entry.
The screenshot is the only field that captures the visual context of the decision. Six months later you will not remember the chart. The screenshot lets you re-evaluate the setup with fresh eyes and ask whether you would take the same trade again. Pattern recognition is built on this kind of review more than on numbers.
If you want a second screenshot at exit to study how the trade played out, that is fine. The entry screenshot is the one that is non-negotiable.
Review notes (separate from per-trade notes)
Per-trade notes are written in the moment. Review notes are written weekly or after every twenty to fifty trades, looking at the data in aggregate. They go in a different place. Mixing them destroys both.
A weekly review note answers three questions:
- What did the data show that I did not expect.
- What rule, setup, or behavior should I change for next week.
- What is one thing I want to watch for.
Three sentences is enough. Reviewing without writing the conclusion down is how traders relearn the same lesson every quarter.
The takeaway
The journal is not a logbook. It is a structured dataset, and its value comes from the fields you fill in identically on every trade. Get the eleven execution fields right first. Add a single consistent setup tag. Layer in context, process, and psychology fields one at a time, only after the prior layer is solid.
A spreadsheet can do this if you are disciplined enough to keep the field values consistent. Most traders are not, which is why dedicated software exists. Tradavity was built around exactly this structure: fixed setup tags, R-multiples computed automatically, screenshots attached, psychology fields available as opt-in. The point is not the tool. The point is that the data has to be clean enough to filter, group, and trust.
Without clean data, you cannot find your edge. With clean data, your edge is hard to hide.