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Channel

丝袜女神-反差福利合集

@MFDLfff

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

24,729subscribers

-623 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1001327542410
TypeChannel
Username@MFDLfff
Description商务合作: @kf528bot
CreatedBetween 1 March 2018 and 31 July 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live16 August 2026
Measurements held9
Confirmed unchanged1 time, most recently 16 August 2026
On Telegramt.me/MFDLfff

Growth

24,72925,35225,040.57 August 2026 — 25,352 subscribers8 August 2026 — 25,289 subscribers9 August 2026 — 25,203 subscribers10 August 2026 — 25,121 subscribers11 August 2026 — 25,082 subscribers12 August 2026 — 24,976 subscribers13 August 2026 — 24,901 subscribers14 August 2026 — 24,844 subscribers16 August 2026 — 24,729 subscribers7 August 202616 August 2026
9 measurements spanning 8 days, net -623. 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 24,636–25,445 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
16 Aug 2026, 04:2524,729-115
14 Aug 2026, 12:4824,844-57
13 Aug 2026, 06:3324,901-75
12 Aug 2026, 09:5324,976-106
11 Aug 2026, 06:2825,082-39
10 Aug 2026, 09:2725,121-82
9 Aug 2026, 08:3325,203-86
8 Aug 2026, 05:0325,289-63
7 Aug 2026, 17:4525,352first reading

Engagement

24 posts held, back to 24 July 2026the reader has not yet reached the start of this channel’s public history, so older posts may sit further back, unread. Read across 26 pagesof Telegram’s post history, 20 posts per page.

ERR · 30 days
2.01%
avg views ÷ 24,729 subscribers
Avg views / post
498
24 posts measured
Reaction rate
0.144%
reactions ÷ views · ER floor
Posts in window
24
of 24 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 10 of 24 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 15 August 2026
Posts held24 (24 July 202615 August 2026)
Views total11,943
Reactions total9
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken16 Aug 2026, 05:42 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
614
Videos
4
Links
197

Lifetime counters from Telegram’s own channel header, read 16 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.

Reaction mix

9 reactions across 7 posts, in 2 distinct kinds. The most used accounts for 55.6% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
555.6%
👍444.4%

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 10 of the 24 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 9reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 24 most recent posts we hold, published 24 July 2026 to 15 August 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

15 Aug 2026, 14:18 UTC91 viewsread 16 August 2026
Photo

Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_71004801

15 Aug 2026, 13:41 UTC97 viewsread 16 August 2026
Photo

#Lucky不懂车 #抖音百万粉车圈网红 抖音百万粉车圈网红 Lucky不懂车 被老公实锤出轨乐道工作人员 偷情性爱视频全网流出 评论区查看完整版资源👇

15 Aug 2026, 13:39 UTC98 viewsread 16 August 2026
Photo

#陈一诺 #重庆大学计算机系 #学妹 #反差 重庆大学计算机系清纯学妹 陈一诺 被学长对镜后入猛干视频流出 评论区查看完整版资源👇

15 Aug 2026, 13:25 UTC95 viewsread 16 August 2026
Photo

#女大学生 #勾引金主 高颜值女大学生 宿舍自拍翻白眼吐舌头漏点 勾引金主爸爸 骚到姥姥家了 评论区查看完整版资源👇

12 Aug 2026, 12:35 UTC304 views1 reactionsread 16 August 2026
Photo

#袁巴元 #张雨绮前夫 #明星吃瓜 张雨绮前夫 袁巴元 早年曝光张雨绮婚内出轨 跟天厚投资ceo 张钱豪 酒店开房 评论区查看完整版资源👇

1

12 Aug 2026, 12:18 UTC283 viewsread 16 August 2026
Photo

抖音 百万粉网红 在在吗 塌房!靠贩卖私密视频捞钱被抓 #反差 #黑丝 #骚女人 人前清纯舞蹈女神,人后....不守妇道的东西 评论区查看完整版资源👇

12 Aug 2026, 12:08 UTC264 views0 reactionsread 16 August 2026
Photo

B站抖音百万粉白杏下海实录曝光! 清纯甜妹变身外围骚货,真实交易对话超露骨,反差直接炸裂 #白杏 #B站网红 #反差婊 #下海 #外围 #清纯崩塌 #真实交易 #尺度炸裂 #宅男女神 #反差 评论区查看完整版资源👇

11 Aug 2026, 11:55 UTC322 viewsread 16 August 2026
Photo

#全子墨 #开封河南大学 开封河南大学 历史学系花 全子墨 与前男友私拍流出 各种姿势啪啪超反差! 评论区查看完整版资源👇

11 Aug 2026, 11:55 UTC269 viewsread 15 August 2026
Photo

#阿文 #极品高颜值巨乳小网红 极品高颜值巨乳小网红 阿文 与男友露脸自拍做爱视频泄密 床上被干的嗯嗯叫! 评论区查看完整版资源👇

11 Aug 2026, 11:55 UTC241 viewsread 15 August 2026
Photo

#吴梦桐 #绝美反差女神 绝美反差女神 吴梦桐 被金主带到户外游玩 在台球厅大胆露出 回家后狠狠玩弄 评论区查看完整版资源👇

8 Aug 2026, 14:15 UTC432 viewsread 15 August 2026
Photo

Telegram必备的搜索引擎,极搜JISOU帮你精准找到,想要的群组、频道、视频、音乐 👉 t.me/jisou2?start=a_71004801

3 Aug 2026, 16:30 UTC894 views1 reactionsread 15 August 2026
Photo

#南山婧婧 08年165的大胸妹 08年165的大胸妹 南山婧婧 兼职外围女酒店骑乘后入 做爱过程超激烈 评论区查看完整版资源👇

1

Showing the 12 most recent of 24 posts we hold for @MFDLfff. 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 — 1,309,057 of 1,481,217entries 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 16 August 2026 — this entry's latest reading, not the date you are reading this.

“丝袜女神-反差福利合集” (@MFDLfff), 24,729 subscribers as measured 16 August 2026. Telegram Register, tgregister.com/channel/MFDLfff.

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.