Telegram RegisterThe public register of Telegram
Telegram profile photo for 无锡老师新榜【候选榜单】

Channel

无锡老师新榜【候选榜单】

@wuxilaoshi8

On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Handles named that no longer answer · Cite this entry

16,760subscribers

+432 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-1002744449117
TypeChannel
Username@wuxilaoshi8
CreatedBetween 1 June 2025 and 31 August 2025 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live19 September 2026
Measurements held31
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/wuxilaoshi8

Topic

Other / unclassifiable — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-FP8, prompt version 1) read this channel’s own recent posts on 10 September 2026 and assigned it the closest of 31 fixed categories, at 87% 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 why it has no browse page of its own yet.

Growth

16,32816,76016,5447 August 2026 — 16,328 subscribers8 August 2026 — 16,335 subscribers9 August 2026 — 16,341 subscribers10 August 2026 — 16,349 subscribers11 August 2026 — 16,346 subscribers12 August 2026 — 16,340 subscribers13 August 2026 — 16,337 subscribers14 August 2026 — 16,357 subscribers16 August 2026 — 16,371 subscribers17 August 2026 — 16,393 subscribers18 August 2026 — 16,401 subscribers19 August 2026 — 16,421 subscribers20 August 2026 — 16,440 subscribers22 August 2026 — 16,475 subscribers24 August 2026 — 16,494 subscribers25 August 2026 — 16,511 subscribers26 August 2026 — 16,516 subscribers27 August 2026 — 16,525 subscribers28 August 2026 — 16,560 subscribers29 August 2026 — 16,568 subscribers30 August 2026 — 16,594 subscribers31 August 2026 — 16,605 subscribers1 September 2026 — 16,627 subscribers2 September 2026 — 16,631 subscribers3 September 2026 — 16,666 subscribers5 September 2026 — 16,687 subscribers8 September 2026 — 16,693 subscribers11 September 2026 — 16,742 subscribers13 September 2026 — 16,730 subscribers14 September 2026 — 16,726 subscribers19 September 2026 — 16,760 subscribers7 August 202619 September 2026
31 measurements spanning 43 days, net +432. 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 16,263–16,825 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 31
Measured (UTC)SubscribersChange
19 Sept 2026, 03:0116,760+34
14 Sept 2026, 20:1816,726-4
13 Sept 2026, 05:4116,730-12
11 Sept 2026, 08:1716,742+49
8 Sept 2026, 11:1516,693+6
5 Sept 2026, 06:0016,687+21
3 Sept 2026, 14:1716,666+35
2 Sept 2026, 05:1316,631+4
1 Sept 2026, 06:0216,627+22
31 Aug 2026, 05:4816,605+11
30 Aug 2026, 04:1416,594+26
29 Aug 2026, 01:4416,568+8
28 Aug 2026, 01:0716,560+35
27 Aug 2026, 02:1316,525+9
26 Aug 2026, 00:5316,516+5
25 Aug 2026, 04:2516,511+17
24 Aug 2026, 03:2716,494+19
22 Aug 2026, 09:1316,475+35
20 Aug 2026, 20:0816,440+19
19 Aug 2026, 21:4216,421first reading

Engagement

51 posts held, back to 5 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 56 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.82%
avg views ÷ 16,760 subscribers
Avg views / post
1,480
20 posts measured
Reaction rate
this channel exposes no reaction counts
Posts in window
22
of 51 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.

What these figures were computed from
WindowRolling 30 days · latest post in window 2 September 2026
Posts held51 (5 August 20262 September 2026)
Views total29,576
Reactions total
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 09:46 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
6m 28s
Average length
11s

Measured directly from 35 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

2 Sept 2026, 15:10 UTC926 viewsread 3 September 2026
Photo

【无锡老司机认证】 花名: #奶多多 车牌: @wxnaiduoduo 频道:https://t.me/naiduoduo1 车费: #700p #1300PP 位置: #新吴区 标签: #舌吻 #69 #胸推 #漫游 #口爆 #舌吻 #女上调情 #陪浴 #水中萧 #有各种丝袜制服配合~ 注: 【我是奶多多,胸大无科技,皮肤白长发,服务齐全态度极好 !女友感十足,不催不事,配合度高,期待哥哥们前来调教!】 优惠情况:群内可使用积分兑换出击优惠 🟢无锡老司机大群: https://t.me/+9rTTT4eT_nVkZWI0 🟢无锡其他资源群: @WUXILAOSIJI 📝 给老师写评价 🔍 查看老师所有评价

2 Sept 2026, 15:04 UTC899 viewsread 3 September 2026
Photo

无锡老司机【聊天群】 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 老师:@Mk888521 老师频道:@MK888520 验证报告发布: @CHAXUNJIRIREN_bot #滨湖区 #漫游 #过水 #胸推 #指滑 #调情 #口痧 #拔罐 #口活#👩🏻咪咪💓👩🏻蛋蛋💓69💓丝袜情趣诱惑,法式情趣内衣,性感蕾丝吊带,纯欲白衬衫,眼罩视觉诱惑,面具,各种情趣内衣可随意挑选,可车震,女友感,

2 Sept 2026, 13:57 UTC915 viewsread 3 September 2026
Photo

无锡老司机【聊天群】 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 九黎老师:@jiuli555 老师频道:https://t.me/jiuli55555 #滨湖区 #少妇 #深喉 #AB面 #毒龙 #服务系 #情趣丝袜 #调情

2 Sept 2026, 07:43 UTC≈1,270 viewsread 3 September 2026
Photo

【无锡老司机认证】 花名: #十七 车牌: @MasonCole7994 频道:https://t.me/coiolniojmj999 车费: #700p #1300PP 位置: #新吴区 标签: #吸咪咪 #吸蛋蛋 #女上调情 #陪浴 #丝足 #有各种丝袜制服配合~ 注: 【我是十七,上海模特兼职,极品黑丝大长腿,皮肤白长发,服务齐全态度极好 !女友感十足,不催不事,配合度高,期待哥哥们前来调教!】 优惠情况:群内可使用积分兑换出击优惠 🟢无锡老司机大群: https://t.me/+9rTTT4eT_nVkZWI0 🟢无锡其他资源群: @WUXILAOSIJI 📝 给老师写评价 🔍 查看老师所有评价

1 Sept 2026, 15:27 UTC649 viewsread 2 September 2026
Photo

无锡老司机聊天群 候选榜单 认证榜单 上榜联系 吉吉🐰 电话 : 17851927412 @wxjjt123 老师频道: https://t.me/wxjjt1234 验证报告发布: @WXBG_bot

1 Sept 2026, 15:16 UTC667 viewsread 2 September 2026
Photo

加群入口: 无锡老司机【加群入口】 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 【双向点此】 无锡一键加入 钱钱老师: @qqsmxa 频道:@qqsmxb #梁溪区 #健身 #御姐 #蜜桃臀 #蛇纹 #69 #女友感 #无纹身#不抽烟 #陪浴 #情趣丝袜

31 Aug 2026, 12:02 UTC≈1,530 viewsread 2 September 2026
Photo

加群入口: 无锡老司机【加群入口】 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 【双向点此】 无锡一键加入 浅浅老师新号:@l9688880 老师频道:@xinqianqian123 验证报告发布: @CHAXUNJIRIREN_bot #梁溪区 #陪浴 #胸推 #包时 #舌吻 #六九 #情趣丝袜

30 Aug 2026, 15:49 UTC≈1,800 viewsread 2 September 2026
Photo

【无锡老司机认证】 花名: #妮妮 车牌: @nini9986 频道:https://t.me/xiaogushinini 车费: #700p #1400pp 位置: #梁溪区 标签: #毒龙 #舌吻 #舔奶 #过水 #陪浴 #全套AB面 #有各种丝袜制服配合~ 注: 【我是妮妮,胸大无科技,护士兼职,皮肤白长发,服务齐全态度极好 !女友感十足,不催不事,配合度高,期待哥哥们前来调教!】 优惠情况:群内可使用积分兑换出击优惠 🟢无锡老司机大群: https://t.me/+9rTTT4eT_nVkZWI0 🟢无锡其他资源群: @WUXILAOSIJI 📝 给老师写评价 🔍 查看老师所有评价

29 Aug 2026, 16:27 UTC≈2,010 viewsread 2 September 2026
Photo

加群入口: @WUXI_LAOSIJI 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 【双向点此】 无锡一键加入 呆呆酱老师:@WUXIDDJ 老师课表:@WUXIDAIDAIJIANG 验证报告发布: @CHAXUNJIRIREN_bot

29 Aug 2026, 07:32 UTC≈1,860 viewsread 1 September 2026
Photo

加群入口: @WUXI_LAOSIJI 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 【双向点此】 无锡一键加入 卷卷老师:@meimeiyyds 老师课表:@hihwji 验证报告发布: @CHAXUNJIRIREN_bot

29 Aug 2026, 06:41 UTC≈1,390 viewsread 31 August 2026
Photo

【无锡老司机认证】 花名: #楚楚 车牌: @chuchubaby1 频道:@chuchubaby3 车费: #1000p(45分钟) #1800pp (90分钟) #包2小时2500(不限次) 位置: #无锡 标签:#可69、#可舌吻(无口臭)、#水中萧、#指滑调情、#制服、#丝袜、#花式口活、 注: 【我是楚楚,乖巧听话,配合度高,热恋女友般的体验,服务齐全态度极好 !不催不事,配合度高,期待哥哥们前来调教!】 优惠情况:群内可使用积分兑换出击优惠 🟢无锡老司机大群: https://t.me/+9rTTT4eT_nVkZWI0 🟢无锡其他资源群: @WUXILAOSIJI 📝 给老师写评价 🔍 查看老师所有评价

28 Aug 2026, 04:02 UTC≈1,740 viewsread 30 August 2026
Photo

加群入口: 无锡老司机【加群入口】 开课老师查询 新老师实习榜单 嫩妹榜单 认证优质严选榜 上榜联系 【双向点此】 无锡一键加入 老师:@wxmumu 频道: https://t.me/wuximumu #新吴区 #舌吻 #大胸 #水多 #御姐 #不抽烟 #女友感

Showing the 12 most recent of 51 posts we hold for @wuxilaoshi8. 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.

Forward network

Republished by

Channels on the register that have forwarded this channel's posts into their own feed.

Built only from forwarded posts we have actually read, on both sides. Coverage is early and deliberately incomplete: a missing link means we have not read the post that would prove it, never that the relationship does not exist. Counts are distinct forwarded posts observed, so they only ever go up as we read more.

Mentions

Named by 5 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 19 September 2026 — this entry's latest reading, not the date you are reading this.

“无锡老师新榜【候选榜单】” (@wuxilaoshi8), 16,760 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/wuxilaoshi8.

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.