😀😀😀😀😀😀🔤😀😀😀😀😀😀 ⚡好运从来没有固定答案 今天的幸运,会不会刚好轮到你‼️ 🎆 Y3国际 精彩随时开启 一份期待,一份惊喜,每一次选择都可能遇见不一样的精彩🥰 🎯好运正在加载中…… 准备好了吗?下一位幸运儿,也许就是你!😋 TG小程序,直达官网 一键登录,方便快捷,免实名零等待 ⚡⚡⚡⚡⚡: y30777.com ⚡⚡⚡⚡⚡: y30778.com 😟😟😟😟 :@Y3VIP333

Channel
(官方)Y3国际
@y30777
On this record: Topic · Growth · Engagement · Reactions · Posts · Citations · Cite this entry
17,581subscribers
-7,180 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1003164458044 |
|---|---|
| Type | Channel |
| Username | @y30777 |
| Created | Between 1 September 2025 and 30 November 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 18 September 2026 |
| Measurements held | 34 |
| Confirmed unchanged | 1 time, most recently 18 September 2026 |
| On Telegram | t.me/y30777 |
Topic
Gambling & betting — 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 100% 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
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 18 Sept 2026, 23:40 | 17,581 | -439 |
| 16 Sept 2026, 13:36 | 18,020 | -298 |
| 14 Sept 2026, 20:39 | 18,318 | -256 |
| 13 Sept 2026, 09:21 | 18,574 | -304 |
| 11 Sept 2026, 11:41 | 18,878 | -443 |
| 8 Sept 2026, 16:40 | 19,321 | -360 |
| 5 Sept 2026, 09:57 | 19,681 | -171 |
| 3 Sept 2026, 10:46 | 19,852 | -64 |
| 2 Sept 2026, 05:24 | 19,916 | -55 |
| 1 Sept 2026, 03:26 | 19,971 | -35 |
| 31 Aug 2026, 00:28 | 20,006 | -27 |
| 29 Aug 2026, 23:58 | 20,033 | -102 |
| 28 Aug 2026, 23:18 | 20,135 | -80 |
| 27 Aug 2026, 23:17 | 20,215 | -14 |
| 27 Aug 2026, 00:43 | 20,229 | -6 |
| 26 Aug 2026, 03:15 | 20,235 | -14 |
| 25 Aug 2026, 05:17 | 20,249 | -12 |
| 24 Aug 2026, 03:16 | 20,261 | -23 |
| 22 Aug 2026, 07:36 | 20,284 | -3,567 |
| 20 Aug 2026, 19:36 | 23,851 | first reading |
Engagement
19 posts held, back to 15 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 57 pages of Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 1.97%
- avg views ÷ 17,581 subscribers
- Avg views / post
- 347
- 5 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 5
- of 19 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.
| Window | Rolling 30 days · latest post in window 1 September 2026 |
|---|---|
| Posts held | 19 (15 July 2026 – 1 September 2026) |
| Views total | 1,733 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 01:00 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.
Reaction mix
14 reactions across 4 posts, in 2 distinct kinds. The most used accounts for 92.9% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 13 | 92.9% | |
| 👌 | 1 | 7.14% |
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 4 of the 19 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 14 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 15 July 2026 to 1 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.
Recent posts
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❤1
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Showing the 12 most recent of 19 posts we hold for @y30777. 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.
Republishes
Channels on the register whose posts this channel has forwarded.
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 40 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
Named by
Channels on the register whose posts name this channel's handle.
@Jdw58 · 96,6741,289 posts菲律宾中文新闻🇨🇳
@Tgbaoi · 95,306695 posts东南亚华人热搜大事件事事通
@hrcgrj_001 · 143,948423 posts东南亚国外新闻
@zdny66 · 94,925390 posts91网红主播鉴黄草榴汤不热
@nvyouzhongzi · 16,85562 posts柬埔寨 菲律宾 越南 东南亚大曝光
@dny2023flb · 87,69243 posts柬埔寨缅甸菲律宾缅北华人新闻曝光
@DNY1978 · 66,02640 posts东南亚日报
@DNYXWC · 39,68140 posts东南亚头条事件大曝光
@adqqjmjj · 258,01438 posts文案馆『 忘忧故事铺 』
@agdhf55 · 31,38537 posts东南亚骗子曝光
@BGHL8 · 57,05336 posts东南亚大事件
@chadnag001 · 56,67436 posts电竞体育 LPL中文推单🫥
@dianjingtuidan1 · 101,99335 posts迪拜黑料大曝光
@kk4568 · 128,78234 posts缅甸缅北东南亚新闻曝光
@nx123 · 771,52034 postsMakati新闻社
@makatinews · 34,54033 posts卡斯兰卡大事件/马来西亚新闻
@YTT783 · 80,98233 posts亚太求职/甩人/找工作
@YTT789 · 319,23433 posts点亮曝光吧🔍
@DLBGB · 596,96732 posts国内吃瓜/国内事件/国内爆料/吃瓜频道
@lee_001122 · 83,81632 posts文案馆向西走/头像/素材
@YTT786 · 86,72132 posts西港日报快讯
@dny_xwdsj · 30,74031 posts【东南亚】曝光悬赏吃瓜
@YTT357 · 307,11030 posts🍉吃瓜中心&搞笑日常
@cggx33 · 51,85929 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.
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 18 September 2026 — this entry's latest reading, not the date you are reading this.
“(官方)Y3国际” (@y30777), 17,581 subscribers as measured 18 September 2026. Telegram Register, tgregister.com/channel/y30777.
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.