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Channel

深圳#按摩、#SPA、#抓龙筋、#喝茶私家会所

@mchhdtl

On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry

376subscribers

+375 since we began measuring on 12 August 2026

Risers and fallers across the register · movement among entries of Under 1,000.

Register entry

Telegram ID-1003795004849
TypeChannel
Username@mchhdtl
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded13 September 2026
Last confirmed live17 September 2026
Measurements held8
Confirmed unchanged1 time, most recently 17 September 2026
On Telegramt.me/mchhdtl

Growth

11,67783912 August 2026 — 1 subscribers12 August 2026 — 2 subscribers18 August 2026 — 1,677 subscribers22 August 2026 — 959 subscribers30 August 2026 — 727 subscribers9 September 2026 — 395 subscribers13 September 2026 — 395 subscribers17 September 2026 — 376 subscribers37612 August 202617 September 2026
8 measurements spanning 36 days, net +375. 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”.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
17 Sept 2026, 23:20376-19
13 Sept 2026, 07:22395no change
9 Sept 2026, 11:19395-332
30 Aug 2026, 09:37727-232
22 Aug 2026, 17:14959-718
18 Aug 2026, 23:441,677+1,675
12 Aug 2026, 17:142+1
12 Aug 2026, 13:471first reading

Engagement

15 posts held, back to 24 August 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
125.2%
avg views ÷ 376 subscribers
Avg views / post
471
11 posts measured
Reaction rate
0.284%
reactions ÷ views · ER floor
Posts in window
15
of 15 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 2 of 11 measured posts that carry a reaction reading, and over those same posts' views.

What these figures were computed from
WindowRolling 30 days · latest post in window 6 September 2026
Posts held15 (24 August 20266 September 2026)
Views total5,177
Reactions total3
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken13 Sept 2026, 07:22 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

Video runtime
10s
Average length
10s

Measured directly from 1 video 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

3 reactions across 2 posts, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
3100.0%

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 2 of the 15 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 15 most recent posts we hold, published 24 August 2026 to 6 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

4 Sept 2026, 09:58 UTC299 viewsread 13 September 2026

哥哥们:请仔细查看本群置顶信息,包括1、本群自己双周抽奖高阶半价套餐一位,2、C餐男穿女性性感内衣丝足或送小妹原味内裤二选一,3、D餐男穿女性性感内裤➕送小妹原味内裤

4 Sept 2026, 09:56 UTC282 viewsread 13 September 2026
Forwarded from @xbwcc

深圳蟹堡王出餐报告 https://t.me/szxwb 验证留名: 明 上课时间: 8.31 位置坐标: 福田上梅林 老师花名: 安安 上课花费: D套餐半价 联系方式: @Htzlhzzr 服务内容:抓龙筋 上课过程: 预定的是安安,人照8分,身材刚刚好,前凸后翘应有尽有。公寓是loft类型的,很干净高级,浴室装备也很全,一次性内裤 漱口水 浴巾什么的都有,洗完澡后上床先做正面,安安一上来就开始挑逗,二弟也是非常配合的抬了头,浅浅按摩后翻到背面开始正式的按摩。按摩过后开始正戏,安安直接脱去衣服,一边用全身蹭我的身体,一边娇喘,又时不时的用舌头挑逗你的脖子 耳朵,然后涂上润滑液开始胸推,可以感受到安安用胸在蹭我的后背。然后翻到正面,一边挑逗我一边接着用胸蹭我的二弟,后面还有磨棒。最后也是在老师的怀里完美发射。 优点缺点: 没有缺点 推荐程度:强烈推荐 (需要提供预约或付款记录)拒收虚假报告,报告

29 Aug 2026, 09:53 UTC668 viewsread 13 September 2026
Photo

🎰 深圳福田芊芊捉龙筋优惠卷 📮 参与条件: 🎫 加入-深圳#按摩、#SPA、#抓龙筋、#喝茶私家会所 🎫 加入-深圳快乐屋(约课认准轮播和榜单) └ 🎟️ 发言数大于 3 条 🎁 奖品内容: 💰️ 16.88红包 × 2 💰️ D餐半价优惠卷 × 2 ⚠️ 抽奖说明: 三天后开奖,七天有效期 中奖带截图,私聊老师即可 📅 开奖日期:(北京时间) 2026年09月01日 17时50分00秒

29 Aug 2026, 09:42 UTC563 viewsread 13 September 2026
Photo

🎰 芊芊抓龙筋D套餐半价 📮 参与条件: 🎫 加入-深圳研究协会 └ 🎟️ 发言数大于 20 条 🎫 加入-深圳#按摩、#SPA、#抓龙筋、#喝茶私家会所 🎫 加入-深圳研究协会榜 🎁 奖品内容: 💰️ D套餐半价 × 1 ⚠️ 抽奖说明: 禁止转让 七天内使用 🔋 人品加成:⚡️× 9 规则 📅 开奖日期:(北京时间) 2026年09月01日 17时41分00秒

29 Aug 2026, 04:56 UTC514 views2 reactionsread 13 September 2026
Photo

🎉 芊芊古法抓龙筋优惠券抽奖 📝 抽奖说明:中奖主动联系 @Htzlhzzr ,兑奖必须写报告 中奖后三天内有效,预期失效并回收 ✅ 参与条件: 1. 加入 深圳—美少女鉴赏 2. 加入 深圳—少女鉴赏指南 3. 加入 深圳—美少女交流 4. 加入 深圳#按摩、#SPA、#抓龙筋、#喝茶私家会所 5. 加入 免费抽奖导航 🎁 奖品内容: • 芊芊古法抓龙筋1100/1600档位(二选一)半价优惠券 × 1 ⏰ 开奖时间:2026-09-01 20:30 👇 点击下方按钮参与抽奖

2

25 Aug 2026, 14:24 UTC678 viewsread 13 September 2026
Video

小妹的污言垢语能否让小🐔🐔兴奋!!!

Showing the 12 most recent of 15 posts we hold for @mchhdtl. 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

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 12 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.

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 17 September 2026 — this entry's latest reading, not the date you are reading this.

“深圳#按摩、#SPA、#抓龙筋、#喝茶私家会所” (@mchhdtl), 376 subscribers as measured 17 September 2026. Telegram Register, tgregister.com/channel/mchhdtl.

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.