Other / unclassifiable — 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 10 September 2026 and assigned it the closest of 31 fixed categories, at 49% 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 why it has no browse page of its own yet.
Growth
32 measurements spanning 41 days, net -515. Dots are measurements; the straight line between them is drawn to join them, not to claim we know the path taken in between — snapshots are recorded only when a count changes, so gaps mean “no change observed”, never “interpolated”. The vertical axis spans 28,541–29,210 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 32
Measured (UTC)
Subscribers
Change
17 Sept 2026, 23:40
28,618
-22
15 Sept 2026, 17:01
28,640
-27
13 Sept 2026, 21:37
28,667
-23
12 Sept 2026, 05:38
28,690
-18
10 Sept 2026, 00:38
28,708
-42
6 Sept 2026, 17:00
28,750
-26
4 Sept 2026, 06:02
28,776
-17
2 Sept 2026, 17:43
28,793
-24
1 Sept 2026, 14:44
28,817
-12
31 Aug 2026, 17:26
28,829
-11
30 Aug 2026, 20:44
28,840
-6
29 Aug 2026, 20:57
28,846
-18
28 Aug 2026, 17:23
28,864
-15
27 Aug 2026, 15:53
28,879
-13
26 Aug 2026, 19:05
28,892
-21
25 Aug 2026, 20:34
28,913
-21
24 Aug 2026, 18:06
28,934
-24
22 Aug 2026, 23:58
28,958
-18
21 Aug 2026, 15:58
28,976
-14
20 Aug 2026, 16:12
28,990
first reading
Engagement
78 posts held, back to 26 July 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 60 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
9.57%
avg views ÷ 28,618 subscribers
Avg views / post
2,740
46 posts measured
Reaction rate
2.58%
reactions ÷ views · ER floor
Posts in window
46
of 78 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.
What these figures were computed from
Window
Rolling 30 days · latest post in window 18 September 2026
Posts held
78 (26 July 2026 – 18 September 2026)
Views total
126,040
Reactions total
3,249
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
19 Sept 2026, 06:57 UTC
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
Photos
≈45
Videos
≈936
Links
≈1,070
Lifetime counters from Telegram’s own channel header, read 19 September 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked ≈ was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.
Video runtime
3h 06m
Average length
2m 49s
Measured directly from 66 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
6,681 reactions across 78 posts, in 17 distinct kinds. The most used accounts for 24.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
💯
1,629
24.4%
❤
1,189
17.8%
🔥
1,098
16.4%
👍
891
13.3%
🙏
627
9.38%
🤯
531
7.95%
👏
380
5.69%
🤔
143
2.14%
😱
59
0.883%
⚡
52
0.778%
👀
45
0.674%
🤩
21
0.314%
🏆
5
0.075%
👌
5
0.075%
❤🔥
4
0.06%
😍
1
0.015%
🥰
1
0.015%
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 78 of the 78 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 6,681 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 78 most recent posts we hold, published 26 July 2026 to 18 September 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.
Never stop talking about the Epstein files
Join now: @stormwatch17✅️
The following videos will not be for the faint hearted. This is a compilation of the biggest leaks yet to be published. For those that don't like what you see, you can remove this channel from your list. Join below:
https://t.me/SpecialQForces 💥
https://t.me/SpecialQForces 💥
🔻ROTHSCHILDS PATENTED CV19
- EXPOSED
🇺🇸 SHARE
Join now: @stormwatch17✅️
The following videos will not be for the faint hearted. This is a compilation of the biggest leaks yet to be published. For those that don't like what you see, you can remove this channel from your list. Join below:
https://t.me/SpecialQForces 💥
https://t.me/SpecialQForces 💥
WHISTLEBLOWER Kris Newby: "TICKS WERE TURNED INTO A POOR MAN’S NUKE"
The U.S. military bred ticks, fleas, and mosquitoes as BIOWEAPONS — loaded them with plague, rabies, and other killer diseases.
Their sick goal? A cheap, silent killer at just $1.33 per life to devastate populations and collapse healthcare systems from within.
Stealthy. Lethal. Released on us.
Now Bill Gates enters the picture, funding tick gene…
Eight years ago, David Wilcock, went straight in on the Draco-Reptilian ETs, and he wasn’t mincing words.
“So what’s been happening apparently is these, we have these negative beings that do actually appear reptilian. They have vertical slit pupils, they have the scaly skin.”
“I’m not saying that this means that people in the Deep State are shapeshifters… As far as we know, anybody who’s biological, your biology ca…
A secret phone call between Rihanna and her friend Wendy has been leaked, in which she openly explains the covert Satanism within the music industry and how many artists (including herself) sell their souls in exchange for fame and money. Despite knowing that they are manipulating their own fans.
Join now: @stormwatch17✅️
🚨💥CANADA 🇨🇦 The first 'major world politician' TO APOLOGIZE to the unvaccinated:
"They were right, we were wrong"
"Calls unvaccinated people the 'most discriminated-against group' he's ever seen"
A STUNNING ADMISSION. As excess deaths continue to rise due to C0VID vaccines; WE MUST DEMAND ACCOUNTABILITY AND MAKE THE GUILTY PAY ⚔️🔥
Join now: @stormwatch17✅️
🚨💥Turkish Press Revelations on Zelensky's Secret Accounts and the Diversion of U.S. Public Funds🚨
An investigative report from the Turkish newspaper Aydınlık accuses Zelensky's inner circle of a vast corruption network. According to this, more than 50 million dollars—presumably from Western aid funds—are laundered monthly through companies in the United Arab Emirates.
According to the report, the funds stem from em…
They killed the child and ate him.
They shared this poor little girl amid tears, they ate the child, and she's recounting what happened.
Only this could be expected from the gang that attacked Iran to shut down the Epstein files.
Join now: @stormwatch17✅️
Johnny Depp Reveals 'Cannibal' Mark Zuckerberg 'Ate His Own Baby' to Stay in Illuminati
Mark Zuckerberg "cannibalized" five of his own children to stay in the Illuminati, according to bombshell revelations by Johnny Depp.
According to Depp, Zuckerberg ate one of his own babies on Facebook Live, before an audience of millions, as part of a depraved Illuminati humiliation ritual.
Join now: @stormwatch17✅️
🚨 BREAKING
The United States and Israel should be concerned now.
The famous hacking group “Anonymous” has announced that it will soon release all files related to Jeffrey Epstein, promising to gradually expose everyone involved.
Join now: @stormwatch17✅️
⚠️ FINAL WARNING: ACCOUNT AT RISK OF PERMANENT SUSPENSION ⚠️
We noticed that your account has not been properly linked to a verified phone number or recovery em…
👍69👏26💯8🏆5⚡2
Showing the 12 most recent of 78 posts we hold for @stormwatch17. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.
Mentions
Named by 4 registered channels — every channel on the register whose own posts have named this one, by its current username or any other username it currently holds, merged from two separately captured readings of the same fact so a namer caught by only one of them is not missed and a namer both caught is not counted twice. A username this channel has since dropped is not matched — that handle may belong to someone else now, and crediting today’s namer to yesterday’s owner would misattribute it.
Named by
Channels on the register whose posts name this channel's handle.
A mention is a weaker signal than a forward and is counted separately for that reason — naming a channel is not republishing it, and a handle in a post body is easy to place deliberately. The post counts beside each row below are distinct posts in which the handle appeared, from posts we have read on both sides — the “Named by N registered channels” figure above is a different count, of distinct NAMING CHANNELS rather than posts, and is not the sum of the rows under it.
Handles this channel named that no longer answer
Dead references
3
handles named in this channel’s posts, vacant today
Evidenced gone
0
we ourselves saw one of these resolve, at some point
Never seen alive
3
vacant every time we have ever looked
@stormwatch17 named 3 handles that resolve to nothing today. That is a fact about the reference, not necessarily a fact about the handle’s history — see the two groups below.
Most of these may never have existed as a live channel at all. A handle a channel names can be a typo, an aspirational name nobody registered, or a channel that was already gone before this one ever mentioned it. Unless a row below is marked evidenced, all we know is that it references a handle that is not a live channel today — not that anything “died”. How this is measured.
Never seen alive
References a handle that is not a live channel — we have no record it ever was one.
@antarcticahiddentech named in 13 posts, 8 August 2026 – 16 August 2026
@freeenergyrevealed named in 13 posts, 8 August 2026 – 16 August 2026
@zeropointdisclosure named in 13 posts, 8 August 2026 – 16 August 2026
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 17 September 2026 — this
entry's latest reading, not the date you are reading this.
“STORM WATCH 17” (@stormwatch17), 28,618 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/stormwatch17.
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.