What time should you post on X?
No single hour of the day produces a measurable engagement advantage in this dataset. Posting hour is a far weaker lever than post format, and the full hourly table below shows why.
Key findings
- Posts published in the 08:00 UTC hour earned 7.3% below the engagement of the same accounts' other posts (95% interval -9.7% to -4.5%), measured across 3,551 X accounts and 16,354 of their posts in the 30 days to 23 August 2026. The effect held for 1,935 of those 3,551 accounts individually.
- 18 of the 24 hours of the day show no measurable engagement difference at all, measured across 5,860 X accounts and 468,482 of their posts in the 30 days to 23 August 2026, so posting hour is a much weaker lever than it is usually described as.
- More posting hours measurably underperform (6) than measurably outperform (0), which makes avoiding the weak hours a more reliable tactic than chasing the strong ones.
Engagement by hour of the day, all 24 hours
The complete table, in clock order rather than ranked. Publishing only the top five hours would make the effect look far stronger and far more reliable than it is; the rows marked as having no measurable difference are the most important thing here.
| Hour published (UTC) | Effect (95% interval) | Accounts compared | Posts |
|---|---|---|---|
| 00:00 UTC | No measurable difference-2.4% to +3.0%, spans zero | 3,100 | 14,406 |
| 01:00 UTC | No measurable difference-0.4% to +7.6%, spans zero | 3,113 | 14,629 |
| 02:00 UTC | No measurable difference-4.0% to +2.3%, spans zero | 3,090 | 14,224 |
| 03:00 UTC | No measurable difference-5.7% to +2.1%, spans zero | 3,121 | 14,695 |
| 04:00 UTC | -4.7%-8.2% to -1.1% | 2,6791,410 agree | 12,050 |
| 05:00 UTC | -4.1%-7.7% to -0.6% | 2,6101,368 agree | 11,790 |
| 06:00 UTC | -6.9%-9.7% to -4.0% | 2,9691,602 agree | 13,180 |
| 07:00 UTC | -6.2%-8.8% to -3.3% | 3,1321,681 agree | 13,934 |
| 08:00 UTC | -7.3%-9.7% to -4.5% | 3,5511,935 agree | 16,354 |
| 09:00 UTC | No measurable difference-5.0% to +0.4%, spans zero | 3,895 | 18,523 |
| 10:00 UTC | No measurable difference-4.2% to +0.1%, spans zero | 4,182 | 19,839 |
| 11:00 UTC | -2.4%-4.7% to -0.2% | 4,6082,384 agree | 21,548 |
| 12:00 UTC | No measurable difference-3.5% to +1.3%, spans zero | 5,045 | 23,657 |
| 13:00 UTC | No measurable difference-1.5% to +3.4%, spans zero | 5,527 | 26,818 |
| 14:00 UTC | No measurable difference-3.2% to +0.3%, spans zero | 5,708 | 27,858 |
| 15:00 UTC | No measurable difference-3.0% to +1.6%, spans zero | 5,860 | 29,691 |
| 16:00 UTC | No measurable difference-3.5% to +0.7%, spans zero | 5,642 | 29,137 |
| 17:00 UTC | No measurable difference-3.4% to +1.3%, spans zero | 5,410 | 27,512 |
| 18:00 UTC | No measurable difference-1.2% to +3.5%, spans zero | 5,039 | 24,568 |
| 19:00 UTC | No measurable difference-1.7% to +2.6%, spans zero | 4,753 | 23,056 |
| 20:00 UTC | No measurable difference-1.9% to +2.5%, spans zero | 4,429 | 21,343 |
| 21:00 UTC | No measurable difference-1.3% to +3.7%, spans zero | 4,019 | 18,599 |
| 22:00 UTC | No measurable difference-1.9% to +4.4%, spans zero | 3,644 | 16,426 |
| 23:00 UTC | No measurable difference-2.2% to +4.6%, spans zero | 3,284 | 14,645 |
A row is only reported as a finding when its 95% interval stays on one side of zero and at least 30 independent accounts contributed a comparison. Measured over the 30 days to 23 August 2026.
What are those hours in local time?
Only the hours that differ measurably are worth converting. Times are computed for today, so daylight saving is already applied.
| UTC | Effect | New York | Los Angeles | London | Mumbai | Tokyo |
|---|---|---|---|---|---|---|
| 11:00 UTC | -2.4% | 07:00 | 04:00 | 12:00 | 16:30 | 20:00 |
| 05:00 UTC | -4.1% | 01:00 | 22:00 (prev day) | 06:00 | 10:30 | 14:00 |
| 04:00 UTC | -4.7% | 00:00 | 21:00 (prev day) | 05:00 | 09:30 | 13:00 |
| 07:00 UTC | -6.2% | 03:00 | 00:00 | 08:00 | 12:30 | 16:00 |
| 06:00 UTC | -6.9% | 02:00 | 23:00 (prev day) | 07:00 | 11:30 | 15:00 |
| 08:00 UTC | -7.3% | 04:00 | 01:00 | 09:00 | 13:30 | 17:00 |
Converted with the current daylight-saving rules for each city, so these labels shift by an hour twice a year while the UTC column never moves.
Is the day of the week a stronger signal than the hour?
On this dataset, yes, and by some distance. The largest hourly effect is smaller than the largest daily one, and the day-of-week table has a single clear loser rather than a spread of near-flat rows. That comparison is set out in full on the best day to post. If you are choosing where to spend effort, format decisions still beat both: outbound links move engagement further than any hour of the day measured here.
Frequently asked questions
- What is the best time to post on X (Twitter)?
- In this dataset no single hour of the day produces a measurable engagement advantage. Posting hour is a much weaker lever than post format.
- What is the worst time to post on X?
- Posts published in the 08:00 UTC hour earned 7.3% below the engagement of the same accounts' other posts (95% interval -9.7% to -4.5%), measured across 3,551 X accounts and 16,354 of their posts in the 30 days to 23 August 2026. The effect held for 1,935 of those 3,551 accounts individually. Avoiding the weakest hours is a more dependable tactic than targeting the strongest, because the negative effects in this dataset are larger than the positive ones.
- Are these times in my local time zone?
- No. Every hour on this page is UTC, because that is the only time zone the underlying post timestamps share. A conversion table for five major cities is included above, computed for today so daylight saving is already accounted for.
- Does posting time matter as much as people say?
- Not on this evidence. Across 5,860 X accounts and 468,482 of their posts in the 30 days to 23 August 2026, 18 of the 24 hourly buckets have a 95% interval that spans zero, meaning no difference can be stated for them at all. Format decisions measured on the same posts move engagement several times further than the hour of publication does.
- Why compare each account only against itself?
- A raw comparison of interaction counts by hour would mostly show which hours large accounts prefer. Comparing each account's posts in one hour against that same account's posts in every other hour, over the same 30-day window, removes account size from the comparison and leaves the timing effect on its own. It also makes the account the unit of evidence, which is what allows a confidence interval to be computed at all.
How this was measured
- Method
- Public posts are collected per account and replies and reposts are discarded. Within each account, the median engagement of the posts in a bucket is compared against the median engagement of that same account's posts outside it, producing one ratio per account. The reported effect is the median of those per-account ratios, with a distribution-free 95% interval around it. Account size therefore cancels out instead of being re-measured, and the unit of evidence is the account rather than the post, because posts inside one account are not independent observations of how the platform behaves.
- What an effect percentage means
- An effect of +10% means the typical measured account earned 10% more engagement on posts in that bucket than on its own posts outside it. The interval beside it is a 95% confidence interval on that figure; where the interval spans zero the page reports no measurable difference rather than a small effect. It is not a click-through rate and not a guarantee for any individual account.
- Sample and window
- 13,508 X accounts carry an engagement aggregate, built from 675,955 collected posts. Every aggregate covers a trailing 30-day window, last recomputed on 23 August 2026. Interaction counts are read at collection time and reflect that moment, not a live figure.
- How uncertainty is handled
- Every effect carries a distribution-free 95% confidence interval and the number of independent accounts behind it. A result is only stated as a finding when that interval stays entirely on one side of zero; where it spans zero the page says no measurable difference rather than printing a small number that would get quoted without its caveat. Accounts are the unit of evidence, not posts: several thousand posts from one account are one observation of how the platform behaves, not several thousand.
- What we do not claim
- These are observational differences, not a controlled experiment. A format that correlates with higher engagement here has not been shown to cause it: posts that carry a link, or an image, or a hashtag also differ in what they are about, and this data cannot separate the format from the content. A flat result means the interval spans zero, not that the true effect is exactly nothing.
- How the hour is assigned
- Each post is bucketed by the UTC hour of its publication timestamp as reported by the platform. No local-time inference is attempted, because the audience location of a post is not observable from public data and guessing it would push a made-up variable into a real measurement.
Cite this page
The aggregate findings on this page are published under CC BY 4.0. You may reuse them anywhere, including in AI-generated answers, provided the source is named. The licence covers the derived statistics only, not the underlying post text, which is not redistributed.
PlayerSells. "What time should you post on X?." PlayerSells X Engagement Insights. Data measured 23 August 2026. https://playersells.com/insights/best-time-to-post
More from the same dataset
- What is a good engagement rate on X?
Engagement rate percentiles across every large X account we measure, with the median, the quartiles and the gap between mean and median.
- What is the best day to post on X?
Median engagement by day of the week, including the one weekday that measurably underperforms every other.
- Do links hurt reach on X?
Posts with an outbound link measured against posts without one - the largest single effect in the dataset.
- Do images get more engagement on X?
Posts carrying an image or video measured against text-only posts, with video split out separately.
- Does post length affect engagement on X?
Median engagement across four length bands, from under 80 characters to over 280.
- Do hashtags work on X?
Median engagement by hashtag count, and what happens to the effect once the sample is large enough to see it.
- What changed in the X research, and when?
A dated log of every finding this research loop published, revised or withdrew, with the run that changed it. Findings are corrected for multiple comparisons and re-tested on every pass.
- What actually drives engagement on X
The hub: every measured effect in one place, plus the accounts with the strongest engagement for their size.
The full dataset index lives at https://playersells.com/insights.