What to Track in a Trading Journal — 12 Things That Actually Matter

Start with the objective facts: entry price and time, exit price and time, instrument, and direction. These come for free if your journal syncs from your broker, and they anchor everything else. Add the R multiple — your result expressed as a multiple of the risk you took on the trade — because a flat dollar number hides whether a winner was actually large relative to the risk, and R is the unit that lets you compare trades of different sizes fairly.

Then add a setup tag and a session tag. The setup tag (e.g. "opening drive", "failed breakout", "VWAP reclaim") is what lets you later sort your results by what you actually played rather than by ticker. The session tag (Asia / London / NY open / NY afternoon) surfaces time-of-day edges and bleed — many traders find one session quietly funds the others. Both are single clicks, and both are where most of the review insight eventually comes from.

Log an emotion-at-entry note and a mistake flag. Emotion at entry is a one-word tag — calm, fomo, revenge, hesitant — and it is the field that, over a few hundred trades, reveals whether your losses cluster around a particular state of mind. You cannot fix a tilt pattern you never recorded. Keep it to one word so it stays a one-second decision.

The mistake flag is a simple yes/no on whether you broke your own rule, regardless of whether the trade won. This is the most important subjective field, because a winning trade taken on a broken rule is still a process failure that will cost you later. Tracking rule-breaks separately from P&L lets you measure discipline independently of luck — and a screenshot of the chart at entry, attached to the trade, makes the weekly review of these flagged trades far more honest than memory alone.

From those fields, five numbers matter. Win rate is the percent of trades that were profitable — useful, but meaningless on its own because a 40% win rate can be highly profitable and a 70% win rate can lose money. Profit factor (gross profit divided by gross loss) tells you how many dollars you make per dollar you lose; above 1.0 is profitable, and most durable traders sit somewhere between 1.2 and 2.0. Read win rate and profit factor together, never alone.

Expectancy ties them into one number: the average amount you can expect to win or lose per trade, accounting for both how often you win and how big the wins are versus the losses. A positive expectancy that is stable or rising over a rolling window is the clearest single signal that your process is working. Round it out with best day and worst day — your largest single-session gain and loss — because the worst day is your real-world stress test and, for prop traders, the number that bumps up against daily loss limits and consistency rules.

In daily review, the per-trade fields do the work: open the session, look at the mistake-flagged trades first, and write one line on each about what the rule-break cost or saved you. In weekly review, switch to the derived metrics and the setup tags — sort your results by setup and by session, and look for the cluster that is quietly losing money. The combination of a tagged trade log and computed metrics is what turns a journal from a diary into a decision tool.

The trap is tracking fields you never sort by. If you have logged a field for a month and never once filtered or reviewed by it, drop it — the friction is not paying for itself. A tight journal of seven per-trade fields and five computed metrics, reviewed daily and weekly, will tell you more than a forty-column spreadsheet you stop updating. FundedNotes captures these fields per trade and computes the rolling metrics for you, so the review is about reading the numbers rather than rebuilding them.