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Channel

承欢出击记

@huan99877

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

70subscribers

+0 since we began measuring on 7 October 2026

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

Register entry

Telegram ID-1004433883669
TypeChannel
Username@huan99877
Description一个老狼的瞎编的出击记录!
First recorded7 October 2026
Last confirmed live7 October 2026
Measurements held2
On Telegramt.me/huan99877

Growth

707 Oct 2026, 15:47 — 70 subscribers7 Oct 2026, 16:22 — 70 subscribers7 Oct 2026, 15:477 Oct 2026, 16:22
2 measurements taken within a single day. 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 69–71 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
7 Oct 2026, 16:2270no change
7 Oct 2026, 15:4770first reading

Engagement

20 posts held, back to 1 October 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 1 page of Telegram’s post history, 20 posts per page.

ERR · 30 days
114.6%
avg views ÷ 70 subscribers
Avg views / post
80.2
20 posts measured
Reaction rate
0.862%
reactions ÷ views · ER floor
Posts in window
20
of 20 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 1 of 20 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 October 2026
Posts held20 (1 October 2026 – 6 October 2026)
Views total1,604
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken7 Oct 2026, 16:22 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

Photos
64
Videos
5
Links
36

Lifetime counters from Telegram’s own channel header, read 7 October 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.

Reaction mix

1 reaction across 1 post, in 1 kind.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤1100.0%

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 1 of the 20 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 1 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 20 most recent posts we hold, published 1 October 2026 to 6 October 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

6 Oct 2026, 16:11 UTC53 viewsread 7 October 2026
Photo

【时间】2026.10.6 【老师】小纱雾 【联系】@xiaoshawu520 【地址】宁波海曙区某公寓 【课费】500/P 【身材】身高155,体重115,真胸B 【年龄】20 【颜值】6 【经过】 水群无意看到“小纱雾”老师,有狼友说她是女版桩基,那得试试。 初见小纱雾,颜值较为普通,黄头发,但确实比较嫩,上身米色长袖毛衣,下身格子裙,我刚坐在沙发上就依偎过来和我聊天,挺活泼,也很热情,一看就是比较外向性格的女孩,在我的提议下我们褪去衣物,全身赤裸的小纱雾呈现在我眼前,微胖,肚子上有些肉肉,不过不影响,我来之前她也提前给我说过了微胖让我有了思想准备,浴室比较宽敞,快速冲洗结束直冲大床而去,至于水中萧我们都忘了。 小纱雾老师很主动上来就要舌吻,我本来好好闭着眼睛品尝呢,小纱雾硬是把我眼睛掰开让我盯着她舌,她舌饱之后才开始舔我咪咪,这个我没感觉呀,开始口活表演,小纱雾直接坐床上,把我屁股抱在怀中对我的小唧唧啃食起来,技术在嫩妹中…

6 Oct 2026, 02:33 UTC64 viewsread 7 October 2026
Photo

【时间】2026.10.4 【老师】舒淇 【联系】@shuqi5203 【课费】2500/包夜 三刷,因为是复刷三维数据就不写了 【经过】 得知“舒淇”老师换地方了,新房第一个包夜我来了,提前联系好老师,约好包夜,时间快到了就来了片科技。 先在客厅聊天熟络一下,参观了一下新房子后就去洗澡,水中萧依然那么自然,到了房间后就是熟悉的舌吻,诱惑,口活,爱爱,和她爱爱真的很投入呀,就像女朋友一样,大概做了8分多钟。 做完有点晚了,关灯打算睡觉,有和她聊天聊挺多,估计到了凌晨四点才彻底睡着,但是由于新房床垫垫的比较少(这个不怪老师,毕竟刚租的),弹簧硌的慌睡的很浅,早上大概9点多起来背有点痛,再和舒淇干了一发,这次时间有点长大概20分钟,可惜没干出来,不过舒淇还是很敬业的,一直努力配合,我估计自己也没办法出来了就提议结束。 穿衣后舒淇早上给我喝了一大杯温水,时间也11点了,就下楼和她吃了早+中饭(她请我的),最后挥手告别,本次出击结束。 …

3 Oct 2026, 11:43 UTC101 viewsread 7 October 2026
Photo

滴滴,工兵券,哈哈! 【时间】2026.10.3 【老师】泡沫 【联系】@paomo_nb 【地址】宁波鄞州区某公寓 【课费】500/BT(工半价) 【身材】身高160,体重95,真胸C 【年龄】30 【颜值】7 【经过】 昨日在“宁波大学群”抽奖,意外获得“泡沫”老师工兵券,半套我是很久没体验了,今天去探探深浅,得知老师不远,扫了共享电驴就出发。 初见泡沫,与照片九分相似,中短发,年约30,气质端庄贤淑,身着粉色性感连衣裙,酥胸饱满,山峦起伏,她坐在床头像鹌鹑般被我的闯入吓了半跳,急忙起身相迎,我果断伸手探向酥胸,真胸C,非常饱满,不知是如何维护的,教室环境温馨,干净整洁,地上居然还有地毯,半套老师细节就是不一样,“喝点什么?”“冰可乐”,坐在沙发寒暄几句,缴纳水费,帮我沐浴,泡沫洗的很仔细,我也把泡沫的身体弄明白了,皮肤挺滑的,奈子真是一绝,小腹平坦没有生过的痕迹,顺带水中萧,帮我拭干水渍,询问“喜欢什么情趣衣物,可以自己…

Showing the 12 most recent of 20 posts we hold for @huan99877. 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.

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.

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.

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 7 October 2026 — this entry's latest reading, not the date you are reading this.

“承欢出击记” (@huan99877), 70 subscribers as measured 7 October 2026. Telegram Register, tgregister.com/channel/huan99877.

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.