见面付,不要定金,见到人之前要钱的都是诈骗,做完之后说不满意可以退款的也是诈骗,本人在电报只有这一个号,有冒充我的都是骗子,✅认准唯一用户名: @TG16860 🙈🙊🙈🐣🙈🐤

Channel
全国同城约❤️(未满十八禁入)
@wdtg1655
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
13,114subscribers
+10,063 since we began measuring on 9 October 2026
Risers and fallers across the register · movement among entries of 10,000–31,623.
Register entry
| Telegram ID | -1003912916173 |
|---|---|
| Type | Channel |
| Username | @wdtg1655 |
| Created | Between 1 April 2026 and 31 August 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 9 October 2026 |
| Last confirmed live | 2 November 2026 |
| Measurements held | 12 |
| Confirmed unchanged | 4 times, most recently 2 November 2026 |
| On Telegram | t.me/wdtg1655 |
Topic
Adult — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B, prompt version 1) read this channel’s own recent posts on 24 October 2026 and assigned it the closest of 31 fixed categories, at 94% confidence. This is a model’s judgement about what the channel is likely to be about, not a fact this register measured the way a subscriber count or a view count is measured — it can be revised on a later pass, and it carries no weight anywhere else on this page. How this classification works, and the other topics.
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 30 Oct 2026, 10:54 | 13,114 | +1 |
| 28 Oct 2026, 05:46 | 13,113 | +1 |
| 27 Oct 2026, 08:45 | 13,112 | -1 |
| 24 Oct 2026, 05:16 | 13,113 | +1 |
| 23 Oct 2026, 02:20 | 13,112 | +2 |
| 22 Oct 2026, 03:06 | 13,110 | +1 |
| 17 Oct 2026, 17:30 | 13,109 | +1 |
| 16 Oct 2026, 18:08 | 13,108 | +1 |
| 15 Oct 2026, 21:05 | 13,107 | +1 |
| 14 Oct 2026, 23:36 | 13,106 | +4 |
| 13 Oct 2026, 13:56 | 13,102 | +10,051 |
| 9 Oct 2026, 15:22 | 3,051 | first reading |
Engagement
20 posts held, back to 8 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
- 0.432%
- avg views ÷ 13,114 subscribers
- Avg views / post
- 56.7
- 20 posts measured
- Reaction rate
- 0%
- 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 2 of 20 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 9 October 2026 |
|---|---|
| Posts held | 20 (8 October 2026 – 9 October 2026) |
| Views total | 1,134 |
| Reactions total | 0 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 9 Oct 2026, 15:22 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
- 4s
- Average length
- 1s
Measured directly from 4 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
搞个落地玻璃窗的房间,在酒店里突然就想尝试一下在这个风景下操了起来。 全国同城约❤️ 联系方式 @TG16860
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:温州 微信号:sa**** 得吃记录: 大晚上直接把妹子接到我家里面,自己住就是方便想干嘛干嘛,直接连操一晚上都没人打扰啊。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:漳州 微信号:LK**** 得吃记录: 脱完衣服我才看到她穿的这么骚,没想到这么骚啊,看到这么骚,我也不能辜负她,第一炮就操了半个多小时。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:深圳 微信号:Lk**** 得吃记录: 有的女人就像是我最爱吃的东西一样,越叫我就越兴奋,好久没有这么爽过了,就是这么对我的鸡巴胃口。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:湖南 微信号:ff**** 得吃记录: 就这身材不使劲卖力操这种骚穴都是浪费,不过确实是太累了,玩两炮就有点扛不住了。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:保定 微信号:PI**** 得吃记录: 现在回想起来都觉得带劲,真的很舒服,实实在在操了一晚上,这段时间脑子里面都是她了。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:三亚 微信号:Jz**** 得吃记录: 骚货的屁股好大,看得我性欲大起,让她坐在我的鸡巴上,必须记录下来,都没操到过屁股这么圆的
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:大同 微信号:sd**** 得吃记录: 操逼就不爱戴套,本来她让我戴的,我操到一般直接把套子摘了,妹子也没说什么,酒喝多了就上头了。
全国同城约❤️ 🌸小中大圈 🌸洋妞 🌸学生 🌸空姐🌸 主打妹子服务态度好,让各位老板满意 联系方式 @TG16860
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:常州 微信号:Ro**** 得吃记录: 叫声还是很淫荡的呢,每次操到性起要高潮的时候都会夹我一下,说实话喝完酒再操逼还蛮爽的。
🐰全国同城约❤️🐰 一个只有激情不谈爱情的私密场所 城市:长治 微信号:Q8**** 得吃记录: 我很喜欢这样的女人,像这么主动的人,我自己可以省很多事,也能让我操她更久,喝多了真的会让性欲放大。
Showing the 12 most recent of 20 posts we hold for @wdtg1655. 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.
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 30 October 2026 — this entry's latest reading, not the date you are reading this.
“全国同城约❤️(未满十八禁入)” (@wdtg1655), 13,114 subscribers as measured 30 October 2026. Telegram Register, tgregister.com/channel/wdtg1655.
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.