#于晚晚 #800p #市中心 #天府广场 #锦江区 联系方式: @yuwanwan5201314520 【妹子花名】:#于晚晚 【所在位置】:#市中心 #天府广场 【修车费用】:#800p 【备注】: 【凶器罩杯】:g奶 【身高身材】:身高160.体重90 【大概年纪】:22 【服务内容】:陪洗 制服 毒龙 口爆 莞式一条龙服务。角色扮演,艳舞 【标签】 #市中心 #感觉车 #服务车 #毒龙 #大胸 #口爆 #包时 群友报告:报告榜单搜索 #于晚晚

Channel
成都总群公开
@olddriveGKB
On this record: Growth · Engagement · What this channel posts · Posts · Posts edited after publishing · Citations · Cite this entry
9,817subscribers
+67 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
Register entry
| Telegram ID | -1002274306776 |
|---|---|
| Type | Channel |
| Username | @olddriveGKB |
| Description | 成都 修车 |
| Created | Between 1 September 2024 and 31 March 2025— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 11 August 2026 |
| Measurements held | 4 |
| Confirmed unchanged | 1 time, most recently 11 August 2026 |
| On Telegram | t.me/olddriveGKB |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 11 Aug 2026, 12:22 | 9,817 | +42 |
| 8 Aug 2026, 17:40 | 9,775 | +25 |
| 7 Aug 2026, 19:01 | 9,750 | no change |
| 7 Aug 2026, 18:57 | 9,750 | first reading |
Engagement
8 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 14 pagesof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 11.8%
- avg views ÷ 9,817 subscribers
- Avg views / post
- 1,160
- 8 posts measured
- Reaction rate
- —
- this channel exposes no reaction counts
- Posts in window
- 8
- of 8 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.
| Window | Rolling 30 days · latest post in window 11 August 2026 |
|---|---|
| Posts held | 8 (26 July 2026 – 11 August 2026) |
| Views total | 9,240 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 13 Aug 2026, 05:51 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
- ≈2,690
- Videos
- ≈100
- Links
- ≈29
Lifetime counters from Telegram’s own channel header, read 13 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.
- Video runtime
- 17s
- Average length
- 9s
Measured directly from 2 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
#朵儿 #600p #建设路 #东门 #成华区 联系方式: @duoer223 【妹子花名】:#朵儿 【所在位置】:#东门 #建设路 【修车费用】:#600p 【备注】: 【凶器罩杯】:c 【身高身材】:身高160体重43公斤 【大概年纪】:25 【服务内容】:陪洗 舌吻 69 制服 毒龙 口爆 莞式一条龙服务。 【标签】 #成华区 #上门 #感觉车 #服务车 #毒龙 #69 #口爆 #包夜 #包时 #舌吻 群友报告:报告榜单搜索 #朵儿
#许诺 #900p #武侯区 #南门 #神仙树 联系方式:@XuNuo1314520 【妹子花名】:#许诺 【所在位置】:#武侯区 #神仙树 【修车费用】:#900p 【备注】: 【凶器罩杯】:36D 【身高身材】:身高174体重103 【大概年纪】:26 【服务内容】:陪洗 浅吻 水中萧 深喉 【标签】 #深喉 #女友感 #感觉车 #御姐车 #态度车 #南门 #水中萧 群友报告:报告榜单搜索 #许诺
#只只 #700p #成都东站 #东门 #成华区 联系方式:@w353201 【妹子花名】:#只只 【所在位置】:#成华区 #成都东站 【修车费用】:#700p 【备注】:新人转公开 【凶器罩杯】:b➕ 【身高身材】:身高160体重90 【大概年纪】:20 【服务内容】:陪洗 浅吻 水中萧 深喉 【标签】 #深喉 #女友感 #感觉车 #态度车 #东门 #深喉 #水中萧 群友报告:报告榜单搜索 #只只
#Muse #1000P #环球中心 #高新区 #南门 联系方式: @MuseSoftDesire 【妹子花名】:#Muse 【所在位置】:#高新区 #环球中心 #南门 【修车费用】:#1000P 16PP 【备注】:新人转公开 【凶器罩杯】:c 【身高身材】:身高160体重44 【大概年纪】:25 【服务内容】:见课表 【标签】 #白虎 #69 #舌吻 #御姐 #颜值车 #服务车 #高新区 群友报告:报告榜单搜索 #Muse
#树可可 #700p #天府二街 #南门 #武侯区 联系方式:@Shucoco 【妹子花名】:#树可可 【所在位置】:#南门 #天府二街 #武侯区 【修车费用】:#700p 【备注】:新人转公开 【凶器罩杯】:c 【身高身材】:身高163体重46kg 【大概年纪】:26 【服务内容】:陪洗 舌吻 69 制服 【标签】 #69 #御姐 #颜控 #感觉车 #态度车 #南门 群友报告:报告榜单搜索 #树可可
云南哪有真情在,花椒树下谈恋爱! 你麻我来,我麻你! 克嫖最有性价比! 欢迎加入云南昆明电报群! https://t.me/KMDBQ 群内正在抽取大量现金红包!
#墨涵 #500P #西门 #金沙 #青羊区 联系方式: @amh521 【妹子花名】:#墨涵 【所在位置】:#青羊区 #金沙 【修车费用】:#500P 【凶器罩杯】:D 【身高身材】:身高161 体重116 【大概年纪】:28 【服务内容】:见课表 【标签】#胸推 #双飞 #69 #车震 #大胸 #态度车 #服务车 群友报告:报告榜单搜索 #墨涵
Showing the 8 most recent of 8 posts we hold for @olddriveGKB. 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
@olddriveGKB edited 2 posts 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
- 8 August 2026
- Most recent edit
- 10 August 2026
Mentions
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 11 August 2026 — this entry's latest reading, not the date you are reading this.
“成都总群公开” (@olddriveGKB), 9,817 subscribers as measured 11 August 2026. Telegram Register, tgregister.com/channel/olddriveGKB.
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.