Channel
@leomatchsafety
On this record: Topic · Growth · Engagement · Posts · Citations · Cite this entry
14,321subscribers
+12,212 since we began measuring on 17 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003839235727 |
|---|---|
| Type | Channel |
| Username | @leomatchsafety |
| Created | 17 August 2026 — measured — dated from the channel’s first post |
| First recorded | 17 August 2026 |
| Last confirmed live | 5 November 2026 |
| Measurements held | 38 |
| Confirmed unchanged | 1 time, most recently 5 November 2026 |
| On Telegram | t.me/leomatchsafety |
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 11 September 2026 and assigned it the closest of 31 fixed categories, at 98% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 5 Nov 2026, 06:59 | 14,321 | +130 |
| 4 Nov 2026, 05:10 | 14,191 | +82 |
| 3 Nov 2026, 06:59 | 14,109 | +104 |
| 2 Nov 2026, 07:08 | 14,005 | +133 |
| 1 Nov 2026, 03:59 | 13,872 | +130 |
| 31 Oct 2026, 03:59 | 13,742 | +127 |
| 30 Oct 2026, 00:47 | 13,615 | +82 |
| 28 Oct 2026, 21:35 | 13,533 | +113 |
| 27 Oct 2026, 18:31 | 13,420 | +109 |
| 26 Oct 2026, 18:29 | 13,311 | +131 |
| 25 Oct 2026, 18:47 | 13,180 | +140 |
| 24 Oct 2026, 16:37 | 13,040 | +113 |
| 23 Oct 2026, 16:04 | 12,927 | +111 |
| 22 Oct 2026, 16:29 | 12,816 | +226 |
| 21 Oct 2026, 11:30 | 12,590 | +277 |
| 20 Oct 2026, 11:51 | 12,313 | +111 |
| 19 Oct 2026, 09:16 | 12,202 | +43 |
| 18 Oct 2026, 10:31 | 12,159 | +31 |
| 17 Oct 2026, 07:40 | 12,128 | +29 |
| 16 Oct 2026, 09:41 | 12,099 | first reading |
13 posts held, back to 17 August 2026 — the reader has reached the start of this channel’s public history, so this is the full archive Telegram still exposes. Read across 6 pages of Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 20 October 2026 |
|---|---|
| Posts held | 13 (17 August 2026 – 20 October 2026) |
| Views total | 23,200 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 5 Nov 2026, 05:53 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.
Telegram’s own ‘edited’ marker: 0 of 1 post 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).
Recognizing Pressure and Manipulation on Leomatch Not every unsafe interaction begins with an obvious threat. Some situations involve pressure, manipulation or attempts to gain someone's trust before making inappropriate requests. When communicating with someone through @leomatchbot, pay attention to behavior such as: • pressuring you to share personal information, private photos or contact details • asking you t…
Meeting Someone from Leomatch Meeting someone new can be exciting, but moving from an online conversation to an in-person meeting requires additional care. If you decide to meet someone you first connected with through @leomatchbot: • choose a public place for your first meeting • tell someone you trust where you are going • arrange your own transportation when possible • avoid sharing sensitive personal or financ…
Privacy and Safety on Leomatch User safety and privacy should work together. Some safety measures may require us to process information in order to assess an account, investigate a report, conduct verification or respond to suspected abuse. Our approach is to use information for legitimate safety purposes while taking into account the privacy of our users. Safety measures should be proportionate to the situation …
Requests from Law Enforcement and Authorities @leomatchbot may receive lawful requests from law enforcement agencies and other competent authorities. Official requests from competent authorities should be submitted through @helpleomatchbot, our official support channel. @helpleomatchbot includes a dedicated section for requests from authorities. Requests are reviewed in accordance with applicable law and the circu…
Fighting Fraud and Abuse on Leomatch Social discovery services can be targeted by scammers, spammers, impersonators and other abusive actors. @leomatchbot uses multiple safety mechanisms, including automated and AI-assisted systems, to help identify and respond to potentially suspicious accounts and activity. Depending on the circumstances and the identified risk, we may: • restrict account functionality • reques…
What Happens When You Report Someone on Leomatch Users can report profiles or behavior that they believe violate the rules of @leomatchbot or may be inappropriate, suspicious or unsafe. Reports are an important part of our safety system. When we receive a report, we may review available information about the reported account and relevant activity to determine whether action is necessary. Depending on the circumst…
How Moderation Works on Leomatch @leomatchbot uses moderation together with automated and AI-assisted safety systems to identify accounts and behavior that may violate our rules or create risks for other users. Moderation and additional review may be initiated based on different types of safety information, including user reports and signals identified by our systems. Depending on the nature and severity of a viol…
Leomatch Trust & Safety pinned «About Safety at Leomatch This is the official safety and trust channel for @leomatchbot. Online safety cannot be achieved through a single feature. It requires multiple layers of protection, continuous improvement, responsible use of technology, and cooperation…»
Protecting Younger Users on Leomatch Protecting younger users is one of our highest safety priorities. No single measure can address every potential risk. For this reason, @leomatchbot uses multiple layers of protection. These include age-based segmentation, moderation, user reports, automated and AI-assisted safety systems, additional verification and account restrictions. Age declaration and segmentation Users…
Age Safety on Leomatch Age is an important part of how safety works on @leomatchbot. Users are required to declare their age when creating a profile. The declared age is used to determine the age-based segmentation, protections and restrictions that apply to the account. Age-based segmentation Leomatch does not treat all users as part of one unrestricted audience. Users are segmented based on their declared age…
Our Safety Principles Our approach to safety at @leomatchbot is based on a few simple principles. Protection should be layered No single feature can address every safety risk. We combine age-based protections, moderation, user reports, verification, automated and AI-assisted systems, and account restrictions. Younger users require additional protection Protecting younger users is one of our highest safety prior…
About Safety at Leomatch This is the official safety and trust channel for @leomatchbot. Online safety cannot be achieved through a single feature. It requires multiple layers of protection, continuous improvement, responsible use of technology, and cooperation between users and the people and systems responsible for keeping the service safe. This channel explains how we approach that responsibility. Here we pub…
Showing the 12 most recent of 13 posts we hold for @leomatchsafety. 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.
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.
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.
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 5 November 2026 — this entry's latest reading, not the date you are reading this.
“Leomatch Trust & Safety” (@leomatchsafety), 14,321 subscribers as measured 5 November 2026. Telegram Register, tgregister.com/channel/leomatchsafety.
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.