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Telegram profile photo for 菲律宾修车🇵🇭越韩中日(逍遥宫)

Channel

菲律宾修车🇵🇭越韩中日(逍遥宫)

@xiaoyaogong999

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

1,144subscribers

-19 since we began measuring on 8 August 2026

Risers and fallers across the register · movement among entries of 1,000–3,162.

Register entry

Telegram ID-1003481722332
TypeChannel
Username@xiaoyaogong999
CreatedBetween 1 November 2025 and 31 March 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live16 August 2026
Measurements held4
Confirmed unchanged1 time, most recently 16 August 2026
On Telegramt.me/xiaoyaogong999

Growth

1,1441,1661,1558 August 2026 — 1,163 subscribers9 August 2026 — 1,166 subscribers12 August 2026 — 1,152 subscribers16 August 2026 — 1,144 subscribers8 August 202616 August 2026
4 measurements spanning 8 days, net -19. 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 1,141–1,169 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Aug 2026, 19:351,144-8
12 Aug 2026, 22:571,152-14
9 Aug 2026, 14:121,166+3
8 Aug 2026, 13:311,163first reading

Engagement

3 posts held, back to 8 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 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
1.63%
avg views ÷ 1,144 subscribers
Avg views / post
18.7
3 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
3
of 3 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 8 August 2026
Posts held3 (8 August 20268 August 2026)
Views total56
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 13:31 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
28s
Average length
14s

Measured directly from 2 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.

Recent posts

8 Aug 2026, 09:40 UTC24 viewsread 8 August 2026
Photo

越南🇻🇳新妹 名字: yiyi 年龄: 2002 身高: 160 体重: 45 胸围: 真胸D 会喝酒🍺 🉑中文交流 🉑玩骰子🎲 🉑玩具 🉑毒龙 🉑口爆 🉑口交 🉑制服 🉑颜射 🉑共浴 😍毒龙服务➕2000😍 态度极其温柔 皮肤白皙光滑 身材凹凸有致 每次一服务都给客户留下一次完美的邂逅 感受不一样的激情 3小时2次25000 6 小时两次35000 12小时三次50000 16小时四次70000 细节藏着温柔 全程体验感拉满😍😍😍

8 Aug 2026, 09:40 UTC11 viewsread 8 August 2026
Photo

越南🇻🇳新人 极品 皮肤白 没孩子 大长腿 炮架子 中文名 文文 年龄 21岁 身高 167 体重 90 真胸C 中文沟通 新人 本人超级美 极品 视频都是一比一还原,最重要是面部0整容,纯天然😎 🍎🍎🍎 价格表 25000/3小时 2次 35000/6小时2次 50000/12小时3次 70000/16小时 幽默风趣,态度好,待客如初恋,我的服务很好我很多姿势都可以接受,我很有耐心。 注 🉑中文🉑英文🉑喝酒🍺🉑骰子🎲🉑双飞🉑无套吹萧🉑口交🉑69🉑制服🉑丝袜🉑乳交🉑足交

8 Aug 2026, 09:40 UTC21 viewsread 8 August 2026
Photo

越南🇻🇳新妹 名字: xixi 年纪: 2002 身高: 160 体重: 45 胸围: 真胸c 会中文,🉑喝酒🍺 🉑陪洗🉑双飞🉑口爆 🉑69🉑按摩🉑制服丝袜诱惑 🉑潮喷🉑潮喷 敏感体质 会夹会吸 试过的都说服务棒 喜欢健身 可接受任何性爱姿势 服务非常好 耐心的一个小妹妹 不偷懒 认真服务好每一位哥哥 3小时2次25000 6 小时两次35000 12小时三次50000 16小时四次70000 💗好的服务 更加让人回味无穷

Showing the 3 most recent of 3 posts we hold for @xiaoyaogong999. 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.

Citation-graph rank

Citation-graph rank — 1,089,091 of 1,481,306entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.

Mentions

Named by 1 registered channel — 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.

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 16 August 2026 — this entry's latest reading, not the date you are reading this.

“菲律宾修车🇵🇭越韩中日(逍遥宫)” (@xiaoyaogong999), 1,144 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/xiaoyaogong999.

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.