老师:Nana 位置:#杭州 #拱墅 课费:p800 pp1500 联系:@NNNY520 双向: @nnny520_bot 标签:kiss 调情 🐒喉 制服诱惑 舔🥚 鸳鸯浴 🔖 报告 评论区自提输入 大尺度视频 【Nana01】【Nana02】

Channel
🆂杭州、寻花郎公开榜
@dfbrexhb
On this record: Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
9,098subscribers
+244 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1002967406707 |
|---|---|
| Type | Channel |
| Username | @dfbrexhb |
| Description | 杭州福利姬(大尺度) t.me/wefsdvadgr 寻花郎公开榜 t.me/dfbrexhb 寻花郎交流群 t.me/xbdfsht 免费上榜 @choujiang002 |
| Created | Between 1 August 2025 and 31 October 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/dfbrexhb |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 11:13 | 9,098 | +76 |
| 10 Aug 2026, 06:51 | 9,022 | +168 |
| 6 Aug 2026, 23:01 | 8,854 | no change |
| 6 Aug 2026, 22:46 | 8,854 | first reading |
Engagement
13 posts held, back to 26 July 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 15 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 2.97%
- avg views ÷ 9,098 subscribers
- Avg views / post
- 270
- 13 posts measured
- Reaction rate
- 0%
- reactions ÷ views · ER floor
- Posts in window
- 13
- of 13 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 13 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 13 August 2026 |
|---|---|
| Posts held | 13 (26 July 2026 – 13 August 2026) |
| Views total | 3,516 |
| Reactions total | 0 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Aug 2026, 10:13 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
- 98
- Videos
- 14
- Links
- 16
Lifetime counters from Telegram’s own channel header, read 15 August 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.
- Video runtime
- 1m 13s
- Average length
- 9s
Measured directly from 8 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
老师:露思 位置:#杭州 #西湖 课费:1100p 2000pp 联系:@xiaoxiai34 标签:舌吻 调情 制服诱惑 鸳鸯浴 69 嫩妹 🔖 报告 评论区自提输入【露思01】 大尺度视频
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老师:u米 位置:#杭州 #拱墅 课费:1500p 2800pp 联系: @ummym1111 标签:舌吻 调情 制服诱惑 鸳鸯浴 🐻推 好评: 报告1 报告2 报告3 报告4 报告5
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老师:安娜 位置:上海,浦东 课费:p600 pp11000 联系:@anabibi1999520 标签:舌吻 调情 🐒喉 制服诱惑 舔🥚 鸳鸯浴 🐻推 报告1️⃣,一进门就看见老师穿着性感吊带黑丝,绝对好评,娇滴滴的模样,完全戳中我的小心脏,真人和照片一致,皮肤感觉更加白一点,洗完澡老师还热情的给我擦拭身体,我也贪婪的享受着老师抚摸我的身体,随后就进卧室趴在床上,老师的双手以及那丰满的胸在我全身上下游走,我闭眼感受这幸福的时光,特别灵活,不敷衍,正面先对着jj抚摸然后口,接着🐍,过程就是一个字爽,重点💦巨多,又特别紧致。 🔖 报告 评论区自提 【贝贝1】大尺度视频 大尺度1 大尺度2 大尺度3 大尺度4
老师:小泡芙 位置:#上海 #虹口 课费:1200/p,2000/ pp 联系:@x_paofu222 标签:🐍吻 69 口交 骑乘 鸳鸯浴 调情 制服诱惑 丝袜诱惑 好评: 🔖 报告 评论区自提 【贝贝1】大尺度视频 大尺度1 大尺度2 大尺度3 大尺度4 报告1 报告2 报告3 报告4 报告5 大尺度、好评投稿 @jggqq001bot
Showing the 12 most recent of 13 posts we hold for @dfbrexhb. 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 — 1,095,919 of 1,480,688entries 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.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“🆂杭州、寻花郎公开榜” (@dfbrexhb), 9,098 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/dfbrexhb.
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.