Trading Journal Template: What to Track and How to Review

Anders Ericsson's 1993 study on expertise – the paper that launched the "10,000 hours" idea – showed that the quantity of practice alone does not produce mastery. The practice must be deliberate: aimed at specific sub-skills, accompanied by immediate feedback, and continuously recalibrated based on that feedback. For traders, a journal is the feedback loop.

Without a journal, every month is a fuzzy impression of "I think I did OK". With a journal, you have the raw data to answer concrete questions: which setup has the best R-multiple? Which instrument costs me most in slippage? When in the session do my execution errors spike? Those are answerable only when you have logged the data to support them.

A second function: the journal disciplines the trader. Knowing you will have to write one honest line about a trade changes the trades you take. Many marginal setups that would have been taken on a whim do not get taken once the trader has to justify them in writing ten minutes later.

You can use a spreadsheet, a Notion database, Edgewonk, Tradervue, or a plain text file – the tool matters less than the fields. Size each trade first with a position-size calculator so the risk-dollar and R-multiple fields you log are accurate. The twelve below are the ones that pay back the time you spend on them. Fewer than twelve and you lose resolution on execution-vs-plan analysis; more than twelve and most traders abandon the journal within a month because the friction becomes too high.

A rule that experienced prop traders follow: if a field has not driven a single behaviour change after two months of logging, delete it. A journal is a living tool – prune it.

The numeric fields answer "what happened". The qualitative fields answer "why". Three additions pay back strongly:

• Pre-trade emotion (1–5). Calm = 1, mildly anxious = 2, chasing = 4, tilted = 5. Track this field for a month and you will find – as most traders do – a strong correlation between high emotion and low execution rating.
• Screenshot. Annotate entry, stop, target, exit. Future-you reviewing the trade at the weekend needs the visual, not just the numbers.
• Planned vs actual. Did you hold to target? Did you move the stop? Did you add to the loser? The gap between your trading plan and your executed behaviour is the single most actionable data point in the entire journal.

Journaling without reviewing is busywork. Book a fixed 60-minute slot every Saturday or Sunday and run this protocol:

1. 0–10 min – numbers recap. Total R, win rate, expectancy per setup, average R win vs average R loss. Note any outlier trade.
2. 10–25 min – best trade of the week. Why did it work? Did you follow the plan? Could the size have been larger? Replicate the conditions in your notes.
3. 25–40 min – worst trade of the week. Was the loss the result of a broken setup (edge failed, acceptable loss) or broken discipline (moved stop, sized too large)? The two demand different responses.
4. 40–50 min – "plan vs actual" audit. How many trades matched your pre-written plan? Any trades you took that you did not plan? Any plans you refused to execute?
5. 50–60 min – one commitment for next week. Single, specific, measurable. Not "trade better" but "do not move any stop away from entry this week".

The weekly review catches execution errors fast. The monthly and quarterly views catch strategic drift.

• Monthly. Expectancy per setup, R-multiple distribution, equity curve. Any setup with < 20 trades in the month is statistically noisy – do not drop it based on a month of data. Track it and let another month accumulate.
• Quarterly. Strategy-level retrospective. Which setups have the sample size and expectancy to be trusted? Which are statistical noise? Which should be retired or scaled? This is the layer at which an evaluation-style prop-firm trader decides whether to keep the current book or pivot.
• Annual. Equity curve, Sharpe (or Sortino), maximum drawdown, and the single most-valuable habit formed this year. A concise 500-word write-up becomes your trading CV for yourself.

The trade-off is friction vs depth.

• Google Sheets / Excel. Free, infinitely customisable, zero vendor lock-in. The down-side: data entry is manual, which many traders give up on after four weeks.
• Notion / Obsidian. Good for the qualitative side – screenshots, notes, linked setups – but weaker for aggregate analysis.
• Tradervue / Edgewonk / TraderSync. Paid platforms that import trades directly from broker statements, auto-compute expectancy and R-multiple, and support pattern tagging. Pricing $20–40/month in 2026. Worth it once you are taking 20+ trades/week.
• Custom code. A Python notebook that reads broker CSVs into a pandas DataFrame and charts expectancy by setup is a one-weekend project for a programming trader. Maximum control, zero recurring cost.

The best journal is the one you actually fill in. Start with a spreadsheet; upgrade only if the data volume exceeds what the spreadsheet handles cleanly.

1. Journaling only losers. You need the winners to identify what works. A journal that is 80 % losing trades creates a selection bias toward self-criticism.
2. Too many fields. Twenty-five fields per trade is aspirational; you will abandon the journal within a month. Twelve is the sweet spot.
3. Writing before reviewing. Dumping raw data without reflection is data collection, not learning. The review is the forcing function.
4. No pre-trade plan. If you do not write down what you intended before the trade, you cannot measure the gap between plan and execution – the most important field in the journal.
5. Rating every trade 5/5. Self-grading honestly is hard. If your execution ratings don't include 1s and 2s, you are either perfect or lying to yourself.

Terrance Odean's 1998 study documented the disposition effect: traders sell winners too early and hold losers too long. That effect is invisible from inside the trade; it is glaringly obvious across 100 journal entries. Tracking "planned exit" vs "actual exit" across a quarter will show you, explicitly, how much money you leave on the table by booking winners too soon or how much you bleed by refusing to accept losers.

The journal is also where you turn a bad day into a learning event instead of a spiral. Writing the post-mortem of a losing day forces cognitive re-engagement, and the act of committing the lesson to writing measurably reduces the probability of repeating the same mistake in the following week. See the trading psychology guide for the full framework.