Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 8 August 2026 and assigned it the closest of 31 fixed categories, at 64% 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.
Growth
62 measurements spanning 92 days, net -496,372. 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 1,537,340–2,182,624 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 62
Measured (UTC)
Subscribers
Change
7 Nov 2026, 23:14
1,611,796
-7,413
6 Nov 2026, 21:06
1,619,209
-8,320
5 Nov 2026, 18:41
1,627,529
-5,329
4 Nov 2026, 19:38
1,632,858
-20,830
3 Nov 2026, 18:46
1,653,688
-8,842
2 Nov 2026, 20:51
1,662,530
-3,460
1 Nov 2026, 22:00
1,665,990
-6,541
31 Oct 2026, 19:41
1,672,531
-8,476
30 Oct 2026, 21:36
1,681,007
-6,289
29 Oct 2026, 20:01
1,687,296
-3,996
28 Oct 2026, 22:45
1,691,292
-7,561
27 Oct 2026, 18:27
1,698,853
-9,835
26 Oct 2026, 16:49
1,708,688
-6,542
25 Oct 2026, 14:00
1,715,230
-4,977
24 Oct 2026, 13:19
1,720,207
-6,173
23 Oct 2026, 14:55
1,726,380
-4,161
22 Oct 2026, 16:28
1,730,541
-8,811
21 Oct 2026, 10:35
1,739,352
-6,329
20 Oct 2026, 10:35
1,745,681
-5,091
19 Oct 2026, 08:30
1,750,772
first reading
Engagement
111 posts held, back to 26 May 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 191 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.114%
avg views ÷ 1,611,796 subscribers
Avg views / post
1,840
37 posts measured
Reaction rate
0.581%
reactions ÷ views · ER floor
Posts in window
37
of 111 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 36 of 37 measured posts that carry a reaction reading, and over those same posts' views.
What these figures were computed from
Window
Rolling 30 days · latest post in window 6 November 2026
Posts held
111 (26 May 2026 – 6 November 2026)
Views total
68,113
Reactions total
386
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
8 Nov 2026, 22:42 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
937
Videos
90
Links
966
Lifetime counters from Telegram’s own channel header, read 8 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Video runtime
39m 46s
Average length
1m 22s
Measured directly from 29 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.
View velocity
How fast this channel’s own posts pick up views, from re-reading them repeatedly in the hours and days after they were published rather than the single reading most entries on this register get. Coverage is early and only a small minority of channels hold it at all — a gap in this section means the post has not been re-read again yet, not that nothing happened.
Computed from 37 of this channel’s own posts over the last 30 days: across 37 of this channel’s own posts with a clear reading, a typical one reaches half of its last-observed view count within 22 hours of being posted; a typical post has already reached 22.0% of its 24-hour view count within the first hour, and 54.6% within the first six; the median 24-hour reach across those posts is 843 views — 0.052% of this channel’s own subscriber count (90th percentile 958).
8 most recently posted, with a view-velocity reading
Curve is every standard checkpoint we hold a reading for (+1h, +3h, +6h, +12h, +24h, +48h, +7d after posting) — measured where a real reading landed close enough to that age, interpolated where it did not but readings on both sides let one be worked out between them. Nothing is ever extrapolated past the last real reading. Latest reading is the newest view and reaction count we hold for the post, side by side, so a gap between how views and reactions moved is visible without following it into the Observations section above. 24h reach is that one checkpoint on its own, labelled the same way. Half of last-observed views is the age at which a post’s view count crossed half of the highest figure we have read for it so far — an upper bound when the very first reading was already past half (we cannot see the actual crossing), and biased low while the post is still climbing, since “half of final” is dividing by a number that has not finished growing yet. Both caveats are printed inline wherever they apply, never silently dropped.
Reaction mix
1,875 reactions across 107 posts, in 32 distinct kinds. The most used accounts for 39.8% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
746
39.8%
❤
656
35.0%
👍
118
6.29%
❤🔥
81
4.32%
💯
37
1.97%
👏
35
1.87%
😁
32
1.71%
🙏
23
1.23%
🐳
21
1.12%
🤝
17
0.907%
🥰
14
0.747%
🆒
12
0.64%
👾
11
0.587%
🤔
10
0.533%
😍
7
0.373%
👻
6
0.32%
🎅
5
0.267%
🤗
5
0.267%
🦄
5
0.267%
⚡
4
0.213%
12 further kinds
30
1.60%
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 107 of the 111 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 1,875 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 111 most recent posts we hold, published 26 May 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: 8 of 37 posts held from the last 30 days (21.6%) 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).
The Hub is built. What sits on it is not.
That is deliberate. An app listed there opens in front of people who already have an identity, already have a balance, and already have friends on the same surface. The hard part of launching something is already solved. The shelf just needs filling.
What should be on it three months from now?
Play: hub.matchain.io
Build: matchvibe.ai/waitlist
#MatchVIBE
A few weeks in, and a real question for you 💭
Most of you have signed in to the new Hub by now. Your MatchID, your points and farming, your wallet, your NFTs and your friends all live behind that one login, which is the part we set out to build.
The part we did not build all by ourselves is the apps. Those came from this community, and that shelf is still early.
Two questions, and we are asking because the answers …
✅ Quiz answers - chapter seven
1. An identity with a verifiable operator behind it, a Sentinel receipt for every action, and reputation computed from receipted work.
2. Sentinel: hash-chained, metadata-only, verifiable by anyone from a public link.
3. That the agent was allowed to do it. Authorisation is governance; receipts are evidence.
4. Engineering agents: review, security audit, QA, plan, ship - under a named …
📬 the four most-asked this week
1. "Is MatchAgents a model?" - No. It's identity, receipts and reputation for agents built on any model.
2. "Can I register my agent now?" - Not yet. The identity extension is in specification. The receipt layer is in development.
3. "Does a receipt mean the agent was authorised?" - No. It proves what happened, in order, unchanged. Authorisation is the operator's governance.
4. "Who's…
🎬 Who ran that agent?
https://youtu.be/Nyw6KJ3TfDk
Six minutes: the incident pattern (identity, authorisation, evidence - missing in that order), the two we supply, the one that stays with the operator, and the first suite - engineering agents under a named human.
🧵 Devs, this one for ya - what you'd want from an agent identity, what you'd seal first.
#MatchAgents
🔁 Explain it back
Today on X: task → receipt → reputation. An agent acts under its operator's identity; the action is sealed on Sentinel; reputation is computed from the receipts.
Your turn: "Why does an agent need an ID?" - explain it in under 40 words.
Best gets pinned. Bonus for explaining why a receipt doesn't mean the agent was allowed to do it.
#MatchAgents
📖 Chapter seven is live: #MatchAgents - AI agents with a name you can hold accountable.
https://x.com/matchain_io/status/2115727868810727925
Short version: every agent incident this year was missing identity, authorisation and evidence, in that order. MatchAgents supplies two of the three from layers already on the map - an identity that's an extension of a verifiable MatchID (an operator of record), and a Sentinel …
📍 The Matchain Map - chapter seven: the first users who aren't people.
Recap in three lines:
• Chapter one - 1.9M verifiable identities, verify once.
• Chapter six - Sentinel: every action a receipt anyone can check. Live.
• This chapter - give both to AI agents: an identity with a person behind it, and a receipt for everything they do.
🤖 Who ran that agent?
An agent deleted a live database during a code freeze and…
🎪 Arcade Alley is open: booths 5–8!
☄️ MeteorMAT: remember feeding coins into an arcade cabinet just to beat your own high score? Same feeling: dodge the debris, grab the bonus boxes, go again. 👉 meteormat.matchvibe.store
🐦 Angry Coins: you know exactly what to do here. Pull back, aim, fire. Three chapters to knock down the Glass Citadel and free the flock. 👉 angrycoins.matchvibe.store
🥠 Fortune Smash: everyone’s …
Got Sunday plan?
🎪 Booths 1–4 are open at the MatchHub Carnival!
Some of these will feel very familiar
♞ MatCHESS: the classic you learned at a kitchen table. A guided start, then play the bot or pass the board to a friend. 👉 matchess.matchvibe.store
🧱 Pixel Tetra: remember stacking blocks on a tiny screen, refusing to sleep? It’s back, with a story mode. Clear the lines, restore the signal. 👉 pixeltetra.matchvibe…
🎬 We altered one record on camera
https://youtu.be/apXQvIeFOII
Seal a receipt, verify it from a public link, change one past entry, and watch the verifier point at the exact link that broke.
#sentinel
🎪 MatchHub Carnival season has kicked off! 8 community-built games, free to play.
Step right up 👉 hub.matchain.io
Want a booth of your own? Build something today at matchvibe.ai/waitlist
#Matchhub #Matchvibe
🔥4👻2😍1
Showing the 12 most recent of 111 posts we hold for @matchain_fam. 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.
Posts edited after publishing
@matchain_fam edited 2 posts after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.
An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.
First edit seen
17 October 2026
Most recent edit
22 October 2026
Posts recorded as deleted after publishing
We recorded 1 post on @matchain_fam as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
8 October 2026
Most recent seen missing
8 October 2026
Median time before seen missing
9.4 hours
Seen missing in the last 30 days
0
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 3 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.
Channels Telegram recommends alongside this one
Telegram’s own answer, not this register’s. When this register asks Telegram’s API what is similar to this channel, this is the list it returns, in the exact order Telegram returns it — never re-sorted by subscribers or by anything else this register measures. The relationship, and the order, are Telegram’s; we record them and date them, and make no claim of our own about which of these channels actually resemble this one.
Read from Telegram’s recommendation API, most recently 7 August 2026. Telegram holds a list like this for a small and growing share of the register — how this is measured, and why most channel pages show nothing here.
Appears in Telegram’s recommendations for other channels
The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.
MMPro Trust @mmprotrust · 678,852 Telegram ranks this channel #8 of 86 here — alongside 85 others — read 8 August 2026
Monad @MonadChannel3 · 27,903 Telegram ranks this channel #12 of 75 here — alongside 74 others — read 7 September 2026
CANO Kombat News @canoann · 28,999 Telegram ranks this channel #12 of 50 here — alongside 49 others — read 4 September 2026
SpunkySDX @SpunkySDX · 78,859 Telegram ranks this channel #14 of 78 here — alongside 77 others — read 7 September 2026
Coin.News by BabyDoge @coindotnewsann · 459,057 Telegram ranks this channel #14 of 86 here — alongside 85 others — read 9 August 2026
GraphDex @graphdex · 654,297 Telegram ranks this channel #15 of 87 here — alongside 86 others — read 8 August 2026
LayerNet Official @layernetofficial · 44,277 Telegram ranks this channel #16 of 75 here — alongside 74 others — read 22 September 2026
Hexacore RU @hexacore_ru · 25,397 Telegram ranks this channel #18 of 74 here — alongside 73 others — read 11 September 2026
Reserve @whiteswapfinance · 27,202 Telegram ranks this channel #18 of 66 here — alongside 65 others — read 8 September 2026
SafeFolioWallet ANNOUNCEMENT @SafeFolio · 66,198 Telegram ranks this channel #18 of 70 here — alongside 69 others — read 7 September 2026
Cryptogram @Kryptgram · 145,172 Telegram ranks this channel #19 of 88 here — alongside 87 others — read 12 August 2026
Prep 2 | Science | Mr.Ahmed ElBasha @mrahmedelbashaa · 31,024 Telegram ranks this channel #20 of 36 here — alongside 35 others — read 5 September 2026
EARN WITH DELZY❣️💰 @zaddybempire · 20,129 Telegram ranks this channel #22 of 60 here — alongside 59 others — read 22 September 2026
Tabi Announcement @tabi_ann · 1,647,168 Telegram ranks this channel #22 of 88 here — alongside 87 others — read 7 August 2026
Digital swap @digitalswap · 19,243 Telegram ranks this channel #23 of 76 here — alongside 75 others — read 26 September 2026
OverProtocol @OverProtocol · 22,004 Telegram ranks this channel #23 of 83 here — alongside 82 others — read 19 September 2026
TaleX @TaleX_chain · 21,563 Telegram ranks this channel #23 of 79 here — alongside 78 others — read 15 September 2026
OGCommunity @OGC_Announcements_Hub · 434,035 Telegram ranks this channel #23 of 89 here — alongside 88 others — read 9 August 2026
onchain @onchainchain · 704,493 Telegram ranks this channel #23 of 85 here — alongside 84 others — read 8 August 2026
COCA News @coca_card · 18,980 Telegram ranks this channel #24 of 76 here — alongside 75 others — read 29 September 2026
Supermeow Updates @supermeowupdates · 181,120 Telegram ranks this channel #24 of 86 here — alongside 85 others — read 12 August 2026
ONUS Announcements @onus_newsroom · 192,906 Telegram ranks this channel #24 of 87 here — alongside 86 others — read 11 August 2026
HERE Wallet @herewallet · 1,077,625 Telegram ranks this channel #24 of 87 here — alongside 86 others — read 8 August 2026
Telgather Global @TelgatherMinigamesAnn · 30,344 Telegram ranks this channel #25 of 70 here — alongside 69 others — read 8 September 2026
This channel appears in 471 seed channels' Telegram-generated recommendation lists in total, of which the 24 where it ranks highest are shown above. Each is Telegram’s list for THAT channel, not this one — see how this is measured.
Domains linked from posts
2 domains this channel’s own posts have linked to, measured by scanning the post bodies themselves — not the channel’s description, which is the separate Declared links section below when this entry has one. Appearing here is not a claim about who runs the linked site or why the channel linked to it; an advertisement, a news citation and a malicious link all leave the same kind of row.
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 7 November 2026 — this
entry's latest reading, not the date you are reading this.
“Matchain Fam” (@matchain_fam), 1,611,796 subscribers as measured 7 November 2026. Telegram Register, tgregister.com/channel/matchain_fam.
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.