Channel

Tafelrundereloaded

@Davidscave

On this record: Topic · Channels linked by matching posts · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Telegram's recommendations · Cite this entry

6,311subscribers

-110 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Topic

National news — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 12 September 2026 and assigned it the closest of 31 fixed categories, at 77% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.

Channels linked by matching posts

This channel is in a group of 72 registered channels linked by matching posts, directly or through other channels in the group. This channel may share no posts with some of the channels listed below, and listed channels may share none with each other. Links are found by comparing text fingerprints across every channel on the register.

Which channel, if either, published first is deliberately not shown in this list. “First” could only mean first in our own crawl, which depends on how deep we happened to reach into each channel’s history, not on when the content was actually first posted. Our one hand-check read 45 of the highest-confidence flagged pairs against the live Telegram pages. In 18 of them the live page showed a “Forwarded from” credit that our database had no record of, so reading that pair as an unattributed copy was wrong; the check did not measure who published first. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Near-verbatim matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

21 more channels are in this same group but not listed individually here.

Growth

Engagement

234 posts held, back to 6 August 2026 — the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 14 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days

4.90%

avg views ÷ 6,311 subscribers

Avg views / post

309

89 posts measured

Reaction rate

2.23%

reactions ÷ views · ER floor

Posts in window

89

of 234 held

ERR is average views per post over the last 30 days divided by subscribers, the definition TGStat uses, so this figure is comparable with the one you will see elsewhere. It falls structurally as a channel grows: a high ERR on a small channel and a low one on a large channel describe reach mathematics, not quality. We publish the figure and the sample it came from and pass no verdict on it.

ER is defined industry-wide as (forwards + reactions + comments) ÷ views — note the denominator is views, not subscribers. Telegram’s public web preview carries views and reactions but not forward or comment counts, so the reaction rate above is the reactions term only and is therefore a floor: the true ER for this channel is higher by an amount we have not measured and will not estimate. It is computed over the 77 of 89 measured posts that carry a reaction reading, and over those same posts' views.

Views are a single reading per post, taken at the time above. A post published in the last day or two is still accumulating views, which pulls the 30-day average down slightly. That is a property of the standard definition rather than a fault in it, so we keep the definition rather than “correcting” the number into something nobody can reproduce.

Precision. Telegram publishes view counts on its public widget in short form — 8.12K, 3.7M — so any reading at or above 1,000 reaches us rounded to three significant figures, and only counts below 1,000 are exact. Averages and rates derived from them are shown to the same precision rather than to the unit: a figure like 3,701,250 would assert digits nobody measured.

Reaction counts are published per emoji and rounded the same way, so a total below 1,000 is exact and a larger one is a sum that may carry a rounded component from each emoji above 1,000. Because it is a sum, it does not look rounded — read a large reaction total as three significant figures per contributing emoji rather than as the figure it prints.

What this channel posts

Video runtime

26m 31s

Average length

36s

Measured directly from 44 videos with a duration reading, out of the posts we hold for this channel — not this channel’s whole posting history, only the sample this register has actually read. An exact reading to the second, taken from the post itself rather than from Telegram’s own rounded chrome, so it carries no ≈ mark.

Reaction mix

1,057 reactions across 183 posts, in 38 distinct kinds. The most used accounts for 28.9% of them.

No sentiment is inferred, and none should be read in. This table is ordered by count and by nothing else. Emoji do not carry stable meaning across languages or communities — 🙏 is thanks in one channel and mourning in another — so we publish which ones were pressed and how often, and pass no judgement on what an audience meant by them.

Precision. Telegram publishes reaction counts per emoji and short-forms each one — 4.34K, 1.2M — so any single kind at or above 1,000 reaches us at three significant figures, and only counts below 1,000 are exact. The shares above are ratios of those figures and carry the same error. This is also why the total here can differ slightly from a reaction total printed elsewhere on the page: both are sums of the same rounded parts, taken over samples with different edges.

Coverage. Reactions were read on 203 of the 234 sampled posts in this sample. Summed by Telegram’s own count on each post — not by adding up the per-emoji breakdown above — those same posts carry 1,126 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 234 most recent posts we hold, published 6 August 2026 to 6 November 2026, using the newest reading held for each. Telegram Stars are excluded: they are a payment, not a reaction, and they have their own section.

Recent posts

Telegram’s own ‘edited’ marker: 0 of 89 posts held from the last 30 days (0%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).

Showing the 12 most recent of 234 posts we hold for @Davidscave. View and reaction counts are the latest single reading for each post, not a live figure, and a recent post is still accumulating both. A view count marked ≈ was rounded by Telegram before we ever saw it — t.me prints views in full below 1,000 and to three significant figures above, so ≈1,200,000 means somewhere between 1,150,000 and 1,249,999. Unmarked counts are exact. Text is reproduced from the public post preview and truncated for length.

Cite this entry

A live page changes as we take new readings, so a citation should name the measurement it is based on, not just the URL. The line below cites the subscriber count as measured 10 November 2026 — this entry's latest reading, not the date you are reading this.

“Tafelrundereloaded” (@Davidscave), 6,311 subscribers as measured 10 November 2026. Telegram Register, tgregister.com/channel/Davidscave.

Full measurement history, CC BY 4.0. Every reading this register holds for this entry, not just the latest one, as a dated, downloadable record: CSV · JSON. Free to use with attribution to tgregister.com. Each file carries its own generation timestamp, which is the figure to cite for exactly when the data was retrieved.