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Channel

上海大道出击报告

@SHDD333

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

13,703subscribers

+4,002 since we began measuring on 14 August 2026

Risers and fallers across the register · movement among entries of 10,000–31,623.

Register entry

Telegram ID-1001482983470
TypeChannel
Username@SHDD333
CreatedBetween 1 April 2019 and 30 September 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded14 August 2026
Last confirmed live26 August 2026
Measurements held7
Confirmed unchanged1 time, most recently 26 August 2026
On Telegramt.me/SHDD333

Growth

9,05813,83011,44414 August 2026 — 9,701 subscribers14 August 2026 — 9,701 subscribers15 August 2026 — 9,634 subscribers18 August 2026 — 9,396 subscribers22 August 2026 — 9,058 subscribers25 August 2026 — 13,830 subscribers26 August 2026 — 13,703 subscribers13,70314 August 202626 August 2026
7 measurements spanning 12 days, net +4,002. 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 8,342–14,546 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
26 Aug 2026, 12:1213,703-127
25 Aug 2026, 12:4913,830+4,772
22 Aug 2026, 13:069,058-338
18 Aug 2026, 20:459,396-238
15 Aug 2026, 17:489,634-67
14 Aug 2026, 19:309,701no change
14 Aug 2026, 19:259,701first reading

Engagement

103 posts held, back to 9 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 17 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.25%
avg views ÷ 13,703 subscribers
Avg views / post
308
103 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
103
of 103 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 26 August 2026
Posts held103 (9 August 202626 August 2026)
Views total31,737
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken26 Aug 2026, 20:20 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
20
Videos
23
Links
1,130

Lifetime counters from Telegram’s own channel header, read 26 August 2026 — not the date at the top of this page, which is when the subscriber count was last read. A count marked was rounded by Telegram before we ever saw it — t.me prints these counters in full below 1,000 and to three significant figures above, so ≈142,000 means somewhere between 141,500 and 142,499.

Recent posts

26 Aug 2026, 14:09 UTC218 viewsread 26 August 2026

💃老师:#Tian 🤖链接:https://t.me/shanghaidadao/12097 💒位置:#闵行 ------------------ 💌出击报告: 课室干净,看得出Tian老师很爱卫生,一见面笑咪咪的,仔细看了一下,漂亮好看一眼就能认出和频道一致的老师,本人挺好看的,当时就觉得这次来对了,帮洗澡,口爆,舌吻,然后给你擦干净进屋,从躺到床上起,服务就正式开始了,老师会先问你要不要穿黑丝,制服很多,配套齐全,老师的小穴很紧,厉害!有很明显的插入感,各种姿势都非常配合,感觉就像是很熟悉自己身体的女朋友一样,皮肤很滑,摸起来手感超级好,一线天的逼逼就是好看,毕竟这样的一线天加鲍鱼逼很难遇到一次,Tian喜欢做爱,很投入,水超级多,最后在依依不舍中约好下次再见。

26 Aug 2026, 14:02 UTC225 viewsread 26 August 2026

💃老师:#甜馨 🤖链接:https://t.me/shanghaidadao/12144 💒位置:#浦东 ------------------ 💌出击报告:体验下来,爽透了老师身材绝了,服务也很刺激 完全打开了新世界的大门,刺激兴奋到大脑皮层发麻,太喜欢这样骚气的老师了。PP结束意犹未尽,遗憾老师还有别的客户不能加时,下次约个长时玩的玩个够,总结下来就是老师人美身材又好还会玩,超骚不可多得。

26 Aug 2026, 13:40 UTC228 viewsread 26 August 2026

💃老师:#嘻嘻 🤖链接:https://t.me/shanghaidadao/12178 💒位置:#普陀 ------------------ 💌出击报告:一进门就看到是一个很活泼的小蛋糕,性格非常好,很有女友感,由于最近太想要了,进门就有感觉,交完水费就开始洗浴,洗完就已经迫不及待的想跟妹妹亲热了,带起小雨伞,女上起手,老师体力有待提高,感觉一下子上来了,赶紧换传教,边舌边桩,能感觉到没一会下面就潮湿了,很有包裹感,妹妹还会夹,一下子就受不了,就这样123交出了第一水;冲完休息片刻,跟老师聊了会天 没一会又来感觉了,叫妹妹先口,然后戴上小雨伞,还是女上起手,然后传教,后入,切换了几个姿势,没一会就有点受不了了,赶紧抱起老师的美腿进行冲刺,最后发射了,完事妹妹也不会催时,在床上休息了会才走了,下次还会返。

26 Aug 2026, 08:47 UTC234 viewsread 26 August 2026

💃老师:#爱己 🤖链接:https://t.me/shanghaidadao/12128 💒位置:#闵行 ------------------ 💌出击报告:进门之后老师热情迎接,帮忙拿水,说话很温柔,坐一会聊了一会天就帮忙洗澡很仔细。老师身材非常好,皮肤白。洗完澡牵到床上开始服务,口的非常认真,深喉很舒服,后面老师上来上位一边🐍一边输出,感觉是在美妙,没几分钟就交代了。然后老师帮忙清理抱着聊天

26 Aug 2026, 07:19 UTC239 viewsread 26 August 2026

💃老师:#迪娜拉 🤖链接:https://t.me/shanghaidadao/12151 💒位置:#静安 ------------------ 💌出击报告:关注老师很久了,终于各种条件都凑够让我得以约见迪娜拉老师,幸运的是还是头课。 地方比较好找,一见面就是惊喜,比照片的好看,双眼皮,眼睛大,身材真的好S型,真胸,手感超级好,皮肤白的好光滑,是我喜欢类型,在床上还是喜欢老师的吻和大奶子,真的特别能加分,现在回味一下不知不觉都硬了……口的很认真,叫的很激情,姿势很刺激,菊花是真的好紧,兄弟们一定要来尝试,忍不住一下缴械,后面就和老师聊了聊,说话也很亲密,真好。以后有机会还会出击

26 Aug 2026, 07:14 UTC247 viewsread 26 August 2026

💃老师:#苏叶 🤖链接:https://t.me/shanghaidadao/12157 💒位置:#浦东 ------------------ 💌出击报告:看了老师的频道对上眼了,就立马联系,约课表上课,一到课室就发现物有所值,老师热情的拥抱,甜甜的体香,让人欢喜,服务周到,态度很好,口活也特别好,口了很久,69看到蜜穴挺嫩,不试试就太可惜了,一切准备就绪,就开始大干一场,一发意犹未尽,马上增加课时继续深入了解,做的太爽了,就是水多多,小穴比较紧致,腿也可以随意摆弄,屌感真的不一样,最后顺利出水!!来财真是宝藏女孩,性价比高!老师口技了得,脾气好,态度好,会提供情绪价值,皮肤好滑,艹得非常有感觉

26 Aug 2026, 06:52 UTC259 viewsread 26 August 2026

💃老师:#美柚 🤖链接:https://t.me/shanghaidadao/12172 💒位置:#黄浦 ------------------ 💌出击报告:进门就很惊艳,人照一致,胸是我见过最大的老师了,服务很细致,很舒服,很惊喜,正面反面都很到位,人美腿长。

26 Aug 2026, 06:37 UTC260 viewsread 26 August 2026

💃老师:#果粒 🤖链接:https://t.me/shanghaidadao/11851 💒位置:#浦东 ------------------ 💌出击报告: 家附近的老师交通便利、我比较看重服务和态度,去之前在老师频道看了各位狼友留下的好评,就有点忍不住想去立马体验、顺利约上课、见面果然老师说话很温柔、会帮洗制服丝袜也都有、非常热情主动、会主动问敏感点去服务你、服务很认真不敷衍,口活很棒、口的时候很舒适没有齿感很不错、眼神特别到位,各种爱爱姿势配合度很高、浪叫骚话不断、情绪价值拉满、让老师事后萧老师也蛮配合、不催钟、很棒的一次体验!

26 Aug 2026, 04:42 UTC264 viewsread 26 August 2026

💃老师:#米丽 🤖链接: https://t.me/shanghaidadao/11816 💒位置:#浦东 ------------------ 💌出击报告:见到第一眼妹子皮肤很好,胸摸着也有弹性。人也随和。服务很好,口的我都快忍不住了,带上套套,坐在上面妹子一阵输出,感觉妹子累了换我上看到妹子得B,很漂亮,粉粉的。刺激之下又是一阵输出,妹子被我插的呻吟,说我的🐔巴好硬好硬,我感觉快要射了,让妹子平趴在闯入,后入进去,摸着妹子性感的屁股再也控制不住了,舒服极了。然后聊了会儿,临走抱抱。哈哈哈哈

25 Aug 2026, 13:07 UTC229 viewsread 26 August 2026

💃老师:#甜柚 🤖链接:https://t.me/shanghaidadao/11836 💒位置:#闵行 ------------------ 💌出击报告:甜柚站在门前,眉眼温柔,笑起来时眼角有浅浅的梨涡。见我站门口呆呆的,递过来一瓶水:“怎么不进来啊?”声音柔柔的的,像初夏的风。我的脸瞬间红透,接过水时指尖都在抖,连句谢谢都说得磕磕绊绊。她耐心地给我问我累不累,会温柔地安抚紧张的心情,我的心,就这样一点点陷了进去。 我攒钱攒很久,就为了见甜柚一面,就像夜空中星星,明亮又温柔。我想找个机会告诉她,我喜欢她,很喜欢很喜欢,但话到嘴边,就是开不了口,我始终不敢。 中间剧情自然不用多说,洗澡温柔,前戏温柔,做的温柔,事后还是温柔,无论是给我的感受,还是抱起来的感觉,温柔的跟水一样,柔情似水。 离开的时候,我回头望了一眼,ls正站在门口,笑着看着我,阳光穿过穿了窗帘,落在她身上,依旧温柔耀眼。时光依旧,岁月匆忙,从此,她是我心底一

25 Aug 2026, 12:21 UTC234 viewsread 26 August 2026

💃老师:#苏岚 🤖链接: https://t.me/shanghaidadao/11779 💒位置:#闵行 ------------------ 💌出击报告:场地很温馨。多多真人很漂亮性格幽默甜美有种初恋女友的清纯感脱衣服身材s曲线。🐻挺拔A4腰有马甲线。看着立马硬邦邦。躺床上老师很主动。制服诱惑制服很多,口技让人欲罢不能正戏女上进入好紧。前后一直摇。深蹲。换姿势后入翘屁股顶起来好有弹性好紧。最后趴下边蛇边顶发射。。。。回去后依然回味无穷

25 Aug 2026, 12:17 UTC474 viewsread 26 August 2026

💃老师:#梦梦 🤖链接:https://t.me/shanghaidadao/11891 💒位置:#浦东 ------------------ 💌出击报告:刚开始看照片以为是过度美颜,到了见到真人9成像,老师讲话比较嗲,有点儿台湾调调,听到很有马上想把她按倒的冲动,抓紧洗了澡上床,妹子很配合不太过分的要求可以,口的忍不住直接带T开始。妹子表情很有感觉,叫声一直在控制不敢太大声,这样让我更有征服欲,下面粉粉嫩嫩的,换了两个姿势直接缴械了。不想写评价的这种嫩妹只想自己反食

Showing the 12 most recent of 103 posts we hold for @SHDD333. 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.

Posts edited after publishing

@SHDD333 edited 1 post after it first published — the same permalink now carries different wording than the one this register originally read, caught because our own crawl held a copy of the earlier text.

An edit is not deception. Typo fixes, price updates and corrections look exactly like this too — this register can tell you the wording changed and when, not why. How this is measured.

First edit seen
24 August 2026
Most recent edit
24 August 2026

Citation-graph rank

Citation-graph rank — 4,418 of 1,620,105entries 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.

Forward network

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

“上海大道出击报告” (@SHDD333), 13,703 subscribers as measured 26 August 2026. Telegram Register, tgregister.com/channel/SHDD333.

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.