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Sorting your journal results by day of the week

Here's a simple bit of analysis most journals can already do: sort your trades by the day of the week and look at the results for each day.

It sounds too basic to matter, but the days aren't the same. Mondays often start slowly, with Asian and early European sessions finding direction after the weekend. Fridays can be choppy in the afternoon, as positions get closed before the weekend. Midweek days tend to carry the big data releases. Your strategy might suit some of those conditions better than others.

You might find nothing. That's useful too, since it means you don't need to worry about it. But sometimes one day stands out, with a clearly worse win rate or bigger average loss. If it does, look at why. Maybe it's the market conditions, or maybe it's you, tired on Fridays or rusty on Mondays.

Sample size matters a lot here. Splitting 200 trades into five days leaves about 40 per day, which isn't many. One bad week can distort a day's figures. I'd want a few months of data before acting on anything.

If a day really does stand out, the response doesn't have to be skipping it. Smaller size, fewer trades, or a later start might be enough.

It takes ten minutes in a spreadsheet with a pivot table.

Fairman wrote: Sun Oct 18, 2026 8:25 am Sorting your journal results by day of the week

Here's a simple bit of analysis most journals can already do: sort your trades by the day of the week and look at the results for each day.

It sounds too basic to matter, but the days aren't the same. Mondays often start slowly, with Asian and early European sessions finding direction after the weekend. Fridays can be choppy in the afternoon, as positions get closed before the weekend. Midweek days tend to carry the big data releases. Your strategy might suit some of those conditions better than others.

You might find nothing. That's useful too, since it means you don't need to worry about it. But sometimes one day stands out, with a clearly worse win rate or bigger average loss. If it does, look at why. Maybe it's the market conditions, or maybe it's you, tired on Fridays or rusty on Mondays.

Sample size matters a lot here. Splitting 200 trades into five days leaves about 40 per day, which isn't many. One bad week can distort a day's figures. I'd want a few months of data before acting on anything.

If a day really does stand out, the response doesn't have to be skipping it. Smaller size, fewer trades, or a later start might be enough.

It takes ten minutes in a spreadsheet with a pivot table.

Hello Fairman, traders, scalpers,

Spot on. This is one of those "low effort, high reward" journaling exercises that frequently gets overlooked because newer traders are too busy tweaking their indicators instead of auditing their actual execution.

Your breakdown of the weekly rhythm hits the nail on the head, but analyzing performance by the day of the week actually reveals an intersection of two different factors: market rhythm and personal capital.

Market Rhythm vs. Personal Fatigue

As you mentioned, the market behaves differently depending on the day, but our psychological state also degrades or shifts as the week progresses.

The Monday Warm-Up: The market is often digesting weekend news and establishing the week's initial balance. But from a personal standpoint, traders are often dealing with "weekend rust." If your Mondays are consistently red, you might be forcing setups just out of an eagerness to get back into the market, trading sub-optimal structures before the week's true trend has established itself.

The Midweek Catalyst: Tuesdays through Thursdays are typically the high-volume days with major macroeconomic data drops (CPI, FOMC, ECB announcements). If your win rate spikes here, your strategy likely thrives on momentum and liquidity. If your losses spike, you might be getting chopped up by news volatility or suffering from slippage.

The Friday Trap: Fridays are notorious for afternoon chop as institutions square the books and take profits ahead of the weekend. Psychologically, this is also the most dangerous day of the week. If a trader is down for the week, Friday is when revenge trading peaks. If you notice your average loss is significantly higher on a Friday, it is almost always a sign of breaking rules to force a green week.

The Statistical Trap: Sample Size & Outliers

Your warning about sample size is critical. Forty trades per day is completely insufficient to draw hard conclusions, and it leaves you highly vulnerable to outliers.

When you run this analysis, do not just look at the total PnL or average loss per day. You must look at the median loss and the win rate consistency. A single massive, rule-breaking loss on a Tuesday can heavily skew your Tuesday averages for months, making the day look fundamentally broken when, in reality, it was just one bad trade.

To filter out the noise, you need at least 100 to 150 trades per day of the week before making sweeping changes to your trading plan.

Dialing the Risk Knobs

The best part of your post is the reminder that the solution doesn't have to be binary. You don't have to simply "stop trading Fridays." Institutional desks rarely shut down entirely on a specific day, but they aggressively manage their exposure.

If the data proves a specific day is a persistent leak in your equity curve, try these micro-adjustments:

Halve your position size on the problematic day to reduce the emotional weight of the trades.

Restrict your trading window. If Friday afternoons are your kryptonite, institute a hard "flat by 11:30 AM" rule.

Raise the setup threshold. Require multiple confluences or only trade your absolute "A+" setups on Mondays.

For anyone reading the thread who hasn't done this yet, it really is a ten-minute job. If your journal is in Excel or Google Sheets and has a column with the date, just add a helper column next to it using the formula =TEXT(A2, "dddd"). Highlight the data, insert a Pivot Table, put the new "Day" column in your rows, and your PnL/Win Rate in the values. The data will speak for itself.

Holiday weeks can skew the numbers, so I'd tag them or leave them out. A Monday after a US holiday or a short week before Christmas doesn't behave like a normal day, and a handful of those can pull one weekday's results up or down. Filtering them out and comparing again shows whether the pattern is real or just a few odd sessions. If the difference disappears, it probably wasn't about the day of the week at all. Do the same for every year of data if you have it, since a pattern that only shows up in one year is less convincing.

Combining the day with the session makes it more specific but thins the data quickly. Monday London and Friday New York might be very different from the rest of the week, but you need a lot of trades to tell. A rough approach is to look at days first, and only split by session if one day stands out and you have enough trades to make the split meaningful. Otherwise you end up looking at buckets of five or six trades, which tell you very little. Waiting for more data is usually better than acting early on thin numbers.

Agreed that thin buckets are the trap. One way to get more out of a small sample is to compare each day against the rest of the week rather than against every other day separately. Then each test is one day versus four, and the bigger group stabilises the comparison. Holidays are worth removing too. A Monday that was a bank holiday in the UK or Japan behaves differently from a normal Monday, and two or three of those in a small sample can make one weekday look worse than it really is.

FTtrader, the pivot table walkthrough is helpful, and the ten minute estimate is realistic. One thing to watch when reading the result: five weekdays split a journal into small groups quickly. With a couple of hundred trades, each day has only around forty, so a difference between Tuesday and Thursday may be noise. Checking whether the same pattern shows up in the first half and the second half of the journal separately is a quick sanity test.