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Channel

日本可愛店長可馨|(大阪)專屬出差旅遊外送服務🩷

@db8881

On this record: Growth · Engagement · Posts · Citations · Cite this entry

237subscribers

+4 since we began measuring on 7 August 2026

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

Register entry

Telegram ID-1002868449099
TypeChannel
Username@db8881
CreatedBetween 1 June 2025 and 31 August 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded8 August 2026
Last confirmed live23 August 2026
Measurements held5
Confirmed unchanged1 time, most recently 23 August 2026
On Telegramt.me/db8881

Growth

2332372357 August 2026 — 233 subscribers7 August 2026 — 234 subscribers8 August 2026 — 234 subscribers15 August 2026 — 235 subscribers23 August 2026 — 237 subscribers7 August 202623 August 2026
5 measurements spanning 16 days, net +4. 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 232–238 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
23 Aug 2026, 02:16237+2
15 Aug 2026, 20:24235+1
8 Aug 2026, 10:03234no change
7 Aug 2026, 20:49234+1
7 Aug 2026, 08:31233first reading

Engagement

11 posts held, back to 2 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 1 pageof Telegram’s post history, 20 posts per page.

ERR · 30 days
22.1%
avg views ÷ 237 subscribers
Avg views / post
52.3
11 posts measured
Reaction rate
0%
reactions ÷ views · ER floor
Posts in window
11
of 11 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 11 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 8 August 2026
Posts held11 (2 August 20268 August 2026)
Views total575
Reactions total0
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken8 Aug 2026, 10:03 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.

Recent posts

8 Aug 2026, 04:33 UTC12 viewsread 8 August 2026
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🏯#大阪今日推薦 💕編號:1018 💕身材:159.D.46.25歲 💕職業:服裝店員 熱情主動不冷場 風騷淫蕩 性愛技巧很讚 深喉嚨緊緊吸附你的DD 輕柔撫摸你的每一個敏感帶 靈活的小舌頭溫柔舔弄你的蛋蛋 ,給你觸電般的快感 🇨🇳中文|🇯🇵日文 |🇦🇺English 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789 —————————————— 🧚‍♀️出勤名單:東京→ @yy98820 |大阪→@db8881 🧚‍♀️參考導航:新手→@zw6886 |點評→ @yy98827 🧚‍♀️官方網站:https://www.fb664.com

8 Aug 2026, 04:33 UTC11 viewsread 8 August 2026
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🏯#大阪今日推薦 💕編號:0639 💕身材:160.D.47.25歲 💕職業:牙科助理 青春洋溢、清秀女孩身體敏感多水 幼嫩感十足 非常適合喜歡嫩妹、初戀感的客人 🇨🇳中文|🇯🇵日文 |🇦🇺English 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789 —————————————— 🧚‍♀️出勤名單:東京→ @yy98820 |大阪→@db8881 🧚‍♀️參考導航:新手→@zw6886 |點評→ @yy98827 🧚‍♀️官方網站:https://www.fb664.com

7 Aug 2026, 05:22 UTC30 viewsread 8 August 2026
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🌙 難忘今宵|包夜限定方案 🌙 💎 長時間限定方案 💎 ✨ 4小時|20W 適合想增加相處時間,享受更完整交流 ✨ 6小時|28W 時間更充裕,節奏更舒服,不必匆忙結束 ✨ 8小時|32W 一整晚的放鬆陪伴,慢慢享受每個時刻 ✨10小時|40W 給想擁有最完整體驗的人,留下特別回憶 🌹為什麼很多客人會選擇長時間? ✅ 不用一直計算剩餘時間 ✅ 可以更自然地互動與了解彼此 ✅ 適合想放慢節奏、享受陪伴感的人 有些時光,短暫擁有不如慢慢珍惜。 讓今晚,不只是一次見面,而是一段值得回味的回憶。 💌 難忘今宵|等待與你創造專屬的美好時光 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

7 Aug 2026, 04:45 UTC23 viewsread 8 August 2026
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🏯#大阪強烈推薦 💕編號:1053 💕身材:172.F.50.25歲 💕職業:T臺模特 長髮飄逸 S型的身段 柔美的線條 名模的風采 只為你一人展現 優美曲線 溫婉氣質 柔軟身段 超迷人! 🇨🇳中文|🇯🇵日文 |🇦🇺English 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789 —————————————— 🧚‍♀️出勤名單:東京→ @yy98820 |大阪→@db8881 🧚‍♀️參考導航:新手→@zw6886 |點評→ @yy98827 🧚‍♀️官方網站:https://www.fb664.com

6 Aug 2026, 04:43 UTC46 viewsread 8 August 2026
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🏯#大阪強烈推薦 💕編號:2189 💕身材:164.D.42.21歲 💕職業:設計助理 溫柔體貼 不冷場 下面緊 很敏感易 喜歡前戲多的愛愛,會主動挑逗你 手口並用真的很讚做完像小女友般依偎在你懷裡 🇨🇳中文|🇯🇵日文 |🇦🇺English 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789 —————————————— 🧚‍♀️出勤名單:東京→ @yy98820 |大阪→@db8881 🧚‍♀️參考導航:新手→@zw6886 |點評→ @yy98827 🧚‍♀️官方網站:https://www.fb664.com

6 Aug 2026, 04:43 UTC46 viewsread 8 August 2026
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🏯#大阪強烈推薦 💕編號:1067 💕身材:166.C.47.19歲 💕職業:學生校花 第一次兼職 很羞澀的可愛學妹 配合度極高哦 乳頭身體都很敏感 🇨🇳中文|🇯🇵日文 |🇦🇺English 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789 —————————————— 🧚‍♀️出勤名單:東京→ @yy98820 |大阪→@db8881 🧚‍♀️參考導航:新手→@zw6886 |點評→ @yy98827 🧚‍♀️官方網站:https://www.fb664.com

5 Aug 2026, 04:24 UTC65 viewsread 8 August 2026
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💓店長推薦「#清純鄰家女」系列 👱‍♀ •番號:1066 •身高:156cm •年齡:23歲 •罩杯:Fカップ •體重:47kg 全套服務:*️⃣帶套做 *️⃣調情 *️⃣ 共浴 *️⃣全身舔舐*️⃣無套口交 *️⃣舔蛋蛋 *️⃣指進入 *️⃣ 69 *️⃣ 舔乳頭 *️⃣乳交 *️⃣ 手交 *️⃣按摩 預約免車馬費 約120分鐘免1w 約180分鐘送特殊服務 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

5 Aug 2026, 04:24 UTC58 viewsread 8 August 2026
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💓店長推薦「#清純鄰家女」系列 👱‍♀ •番號:1062 •身高:155cm •年齡:23歲 •罩杯:Cカップ •體重:43kg 全套服務:*️⃣帶套做 *️⃣調情 *️⃣ 共浴 *️⃣全身舔舐*️⃣無套口交 *️⃣舔蛋蛋 *️⃣指進入 *️⃣ 69 *️⃣ 舔乳頭 *️⃣乳交 *️⃣ 手交 *️⃣按摩 預約免車馬費 約120分鐘免1w 約180分鐘送特殊服務 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

3 Aug 2026, 04:25 UTC101 viewsread 8 August 2026
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💓店長推薦「#私房菜」系列 👱‍♀ •番號:8563 •身高:164cm •年齡:21歲 •罩杯:Fカップ •體重:47kg 全套服務:*️⃣帶套做 *️⃣調情 *️⃣ 共浴 *️⃣全身舔舐*️⃣無套口交 *️⃣舔蛋蛋 *️⃣指進入 *️⃣ 69 *️⃣ 舔乳頭 *️⃣乳交 *️⃣ 手交 *️⃣按摩 預約免車馬費 約120分鐘免1w 約180分鐘送特殊服務 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

3 Aug 2026, 04:25 UTC90 views0 reactionsread 8 August 2026
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💓店長推薦「#私房菜」系列 👱‍♀ •番號:5279 •身高:166cm •年齡:22歲 •罩杯:Dカップ •體重:50kg 全套服務:*️⃣帶套做 *️⃣調情 *️⃣ 共浴 *️⃣全身舔舐*️⃣無套口交 *️⃣舔蛋蛋 *️⃣指進入 *️⃣ 69 *️⃣ 舔乳頭 *️⃣乳交 *️⃣ 手交 *️⃣按摩 預約免車馬費 約120分鐘免1w 約180分鐘送特殊服務 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

2 Aug 2026, 05:12 UTC93 viewsread 8 August 2026
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🪶大阪今日部分出勤勤🪶 🏯番號:1187 🏯番號:1452 🏯番號: 1018 🏯番號:1044 🏯番號: 1038🏯番號:1020 🏯番號: 1060🏯番號:1021 🏯番號:8451 🏯番號:8427 🏯番號: 6947 🏯番號:5389 🏯番號:4085 🏯番號:1846 🌸約妹福利,我要你性福 🎀約60分鐘免車馬費 🎀約120分鐘免1w 🎀約180分鐘送特殊服務 🧦提前預約送情趣絲襪 🎀 可馨Telegram:@yy9882 🎀 可馨GLeezy :yy789

Showing the 11 most recent of 11 posts we hold for @db8881. 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 — 721,259 of 1,623,166entries 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 4 registered channels — 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.

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

“日本可愛店長可馨|(大阪)專屬出差旅遊外送服務🩷” (@db8881), 237 subscribers as measured 23 August 2026. Telegram Register, tgregister.com/channel/db8881.

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.