#喵喵 #在厦 #已验 #6米 #颜值系 #御姐 #莲花路口附近 165/C/48 杭州来的网红小主播‼️高盐超白皮萝莉音🉑️🐍🉑️👅会所一条🐲颜值抗打口技了得👍 👩🏫凯撒阁报告模版 电报:@Zo2314 频道:https://t.me/mm2468
❤2

Channel
@XMBHGA
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
10,717subscribers
-3,446 since we began measuring on 15 August 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
| Telegram ID | -1003112578548 |
|---|---|
| Type | Channel |
| Username | @XMBHGA |
| Created | Between 1 September 2025 and 30 November 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 15 August 2026 |
| Last confirmed live | 8 September 2026 |
| Measurements held | 21 |
| Confirmed unchanged | 1 time, most recently 8 September 2026 |
| On Telegram | t.me/XMBHGA |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 8 Sept 2026, 15:20 | 10,717 | -4,840 |
| 5 Sept 2026, 08:02 | 15,557 | +99 |
| 3 Sept 2026, 09:44 | 15,458 | -352 |
| 2 Sept 2026, 01:04 | 15,810 | +16 |
| 31 Aug 2026, 21:45 | 15,794 | +24 |
| 30 Aug 2026, 19:28 | 15,770 | +20 |
| 29 Aug 2026, 17:56 | 15,750 | +11 |
| 28 Aug 2026, 20:46 | 15,739 | +27 |
| 27 Aug 2026, 17:25 | 15,712 | +42 |
| 26 Aug 2026, 15:13 | 15,670 | +23 |
| 25 Aug 2026, 16:33 | 15,647 | +22 |
| 24 Aug 2026, 19:28 | 15,625 | +1,481 |
| 23 Aug 2026, 01:04 | 14,144 | -1,048 |
| 21 Aug 2026, 14:47 | 15,192 | +160 |
| 20 Aug 2026, 16:28 | 15,032 | +173 |
| 19 Aug 2026, 14:54 | 14,859 | +257 |
| 18 Aug 2026, 15:18 | 14,602 | +90 |
| 17 Aug 2026, 18:18 | 14,512 | +220 |
| 16 Aug 2026, 15:57 | 14,292 | +129 |
| 15 Aug 2026, 08:00 | 14,163 | first reading |
60 posts held, back to 14 August 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 34 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. It is computed over the 58 of 60 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 3 September 2026 |
|---|---|
| Posts held | 60 (14 August 2026 – 3 September 2026) |
| Views total | 67,590 |
| Reactions total | 133 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 3 Sept 2026, 10:45 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.
Measured directly from 38 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.
133 reactions across 58 posts, in 3 distinct kinds. The most used accounts for 98.5% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 131 | 98.5% | |
| 👎 | 1 | 0.752% | |
| 🤮 | 1 | 0.752% |
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 58 of the 60 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 133 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 60 most recent posts we hold, published 14 August 2026 to 3 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.
#喵喵 #在厦 #已验 #6米 #颜值系 #御姐 #莲花路口附近 165/C/48 杭州来的网红小主播‼️高盐超白皮萝莉音🉑️🐍🉑️👅会所一条🐲颜值抗打口技了得👍 👩🏫凯撒阁报告模版 电报:@Zo2314 频道:https://t.me/mm2468
❤2
#安妮 #在厦 #已验 #5米 #颜值系 #集美区附近 160/C/108集美区颜值系小姐姐🧍♀️看着就很有欲望🥰这又是谁家小女友出来兼职了‼️且行且珍惜👠错过就不知花落谁家了😂 👩🏫凯撒阁报告模版 频道:https://t.me/hsjshsj35 电报:@anini2000
❤2
#汐柚 #在厦 #已验 #7米 #颜值系 #迷你制服身材 #湖里区附近 165/B/47高颜值小姐姐汐柚🧍♀️🐻围B无科技🍡温柔可爱❤️细嫩白皮耐看型👍热情主动不催‼️甜言暖语不冷场🍿分享指数四颗星🌟还有各种迷你版制服🫣也🉑拍不露脸❤️❤️小视频📹 👩🏫凯撒阁报告模版 频道:https://t.me/xiyou066 电报:@Xiyou_06
❤2
#雨桐 #在厦 #已验 #8米 #颜值系 ➕ #舞蹈生 #湖里万达附近 168/C/48👠高颜值舞蹈老师💃整体形象打8分🍭细嫩白皮性格温柔可冲🌟俗话说没🈶上过大学🫣但必须⬆️大雪生🤔 👩🏫凯撒阁报告模版 频道:https://t.me/Yutong2563 电报:@Yutong13232
❤3
#桃桃 #在厦 #已验 #6米 #颜值系 #思明区SM二期附近 183/D/118👠高颜值大长腿🍭🉑亲🉑蛇 多功能老师👩🏫 个人点评四颗星🌟 👩🏫凯撒阁报告模版 电报:@Tt51885 频道:https://t.me/Taot2536
❤1
#安琪 #在厦 #已验 #4米 #服务系 ➕ #少女系 #湖里区枋湖附近 158/B/93🥤少女届的服务老师👩🏫态度温和👠无机车🉑69特点可以和妹妹小米双开👅 👩🏫凯撒阁报告模版 电报: @anqi520888666 频道:https://t.me/anqi520666888
❤2
#糯米团团 #在厦 #已验 #6米 #颜值系 ➕ #服务系 #湖里区附近 160/D/82😂微微胖胖才是真爱💄糯米小团子👠风骚妩媚👅性感温柔🥰甜美耐心🌈主打态度好情绪💥价值高女友体验感🈵🈵大蟒🐍🉑69制服诱惑👔花式口活🥚🥚🚗各种小玩具🉑配合拍视频🎈视频内容老师🉑检查📗不上镜本人比照片好看。 👩🏫凯撒阁报告模版 频道:https://t.me/xxnmtz 电报:@xxnmtzzz
❤2
#菲菲 #在厦 #已验 #6米 #服务系 #湖里区附近 163/D/108👠高端会所出身👅大胸小腰肥臀😎分套餐ABC💄水床道具等🍡🍡 👩🏫凯撒阁报告模版 电报: @feifeils 频道:https://t.me/qiutinls
❤2
#松韵 #在厦 #已验 #6米 #颜值系 ➕ #身材 #海沧区附近 165/B/92海沧刚下海不久的嫩妹🫣制服三点粉嫩🥤可纯可欲水多多‼️顶级服务全能服务👍 👩🏫凯撒阁报告模版 电报: @XMdoubao 频道:https://t.me/DB0000010
❤1
#阿柒 #在厦 #已验 #7米 #颜值系 #御姐 #莲坂外图附近 162/C/46 云南小麦色皮嫩妹‼️颜值中上🤔不🐍不👅好像混过一段时间女🏍️圈😂自称女友感爆棚情绪价值拉满‼️愿者上钩🎣 👩🏫凯撒阁报告模版 电报:@aqixm1314 频道:https://t.me/aqixm1314520
❤1
Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_7577190751
❤1
#晨晨 #在厦 #已验 #湖里区江头附近 #课费600p #良家女友型 160/C/98👠个人兼职🚗肤白貌美👅乖巧听话🉑毒🐉龙🉑🐻推可👄🔥一流‼️ 👩🏫凯撒阁报告模版 订阅:https://t.me/xiaohuyade 电报:@qwetta66
❤1
Showing the 12 most recent of 60 posts we hold for @XMBHGA. 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.
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.
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 8 September 2026 — this entry's latest reading, not the date you are reading this.
“【厦门凯撒阁公开榜】真人真照真好评” (@XMBHGA), 10,717 subscribers as measured 8 September 2026. Telegram Register, tgregister.com/channel/XMBHGA.
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.