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Channel

宁波修车公开榜

@nbgkb888

On this record: Topic · Growth · Engagement · Reactions · Posts · Posts edited after publishing · Citations · Cite this entry

22,313subscribers

+396 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-1001163738906
TypeChannel
Username@nbgkb888
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 live19 September 2026
Measurements held33
Confirmed unchanged1 time, most recently 19 September 2026
On Telegramt.me/nbgkb888

Topic

Adult — 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 62% 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

21,73122,88322,3077 August 2026 — 21,917 subscribers7 August 2026 — 21,769 subscribers9 August 2026 — 21,731 subscribers10 August 2026 — 21,772 subscribers11 August 2026 — 21,743 subscribers12 August 2026 — 21,842 subscribers13 August 2026 — 21,965 subscribers14 August 2026 — 21,971 subscribers16 August 2026 — 22,069 subscribers17 August 2026 — 22,092 subscribers18 August 2026 — 22,171 subscribers19 August 2026 — 22,331 subscribers20 August 2026 — 22,402 subscribers21 August 2026 — 22,467 subscribers22 August 2026 — 22,322 subscribers24 August 2026 — 22,468 subscribers25 August 2026 — 22,337 subscribers26 August 2026 — 22,384 subscribers27 August 2026 — 22,480 subscribers28 August 2026 — 22,555 subscribers29 August 2026 — 22,469 subscribers30 August 2026 — 22,497 subscribers31 August 2026 — 22,595 subscribers1 September 2026 — 22,643 subscribers2 September 2026 — 22,686 subscribers4 September 2026 — 22,800 subscribers6 September 2026 — 22,719 subscribers9 September 2026 — 22,883 subscribers11 September 2026 — 22,255 subscribers13 September 2026 — 22,248 subscribers15 September 2026 — 22,401 subscribers16 September 2026 — 22,486 subscribers19 September 2026 — 22,313 subscribers22,3137 August 202619 September 2026
33 measurements spanning 43 days, net +396. 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 21,558–23,056 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 33
Measured (UTC)SubscribersChange
19 Sept 2026, 07:2122,313-173
16 Sept 2026, 20:5722,486+85
15 Sept 2026, 01:2022,401+153
13 Sept 2026, 13:4122,248-7
11 Sept 2026, 19:2122,255-628
9 Sept 2026, 10:5622,883+164
6 Sept 2026, 01:5722,719-81
4 Sept 2026, 00:0122,800+114
2 Sept 2026, 11:1722,686+43
1 Sept 2026, 08:2822,643+48
31 Aug 2026, 08:0422,595+98
30 Aug 2026, 08:3922,497+28
29 Aug 2026, 11:2822,469-86
28 Aug 2026, 10:3622,555+75
27 Aug 2026, 07:1822,480+96
26 Aug 2026, 08:3722,384+47
25 Aug 2026, 11:5322,337-131
24 Aug 2026, 10:3822,468+146
22 Aug 2026, 18:4622,322-145
21 Aug 2026, 07:5522,467first reading

Engagement

211 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 59 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
7.31%
avg views ÷ 22,313 subscribers
Avg views / post
1,630
69 posts measured
Reaction rate
0.14%
reactions ÷ views · ER floor
Posts in window
69
of 211 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 60 of 69 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 3 September 2026
Posts held211 (5 August 20263 September 2026)
Views total112,621
Reactions total139
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken3 Sept 2026, 12:47 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.

Reaction mix

420 reactions across 163 posts, in 9 distinct kinds. The most used accounts for 96.9% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
40796.9%
👍40.952%
👎20.476%
😁20.476%
🎄10.238%
👏10.238%
😍10.238%
🤔10.238%
🥰10.238%

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 181 of the 211 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 420 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 211 most recent posts we hold, published 5 August 2026 to 3 September 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

3 Sept 2026, 10:30 UTC572 views1 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐指数:⭐️⭐️ ⭐️ ⭐️』 【日期】:2026.9.3 【修车编号】:#NBTG1126 【美女昵称】:#江禾 【验证人】:帅帅叔 【地 区 】:鄞州 【联系方式】:@grygbgh 【见面感觉】:8分 【室内光线】:正常 【属性标签】:少妇 【身材曲线】:大长腿 【技术含量】:7 【价格 】:500/p(工兵半价) 【安 全 性】:酒店式公寓 【年龄】:30左右 【身高】:168左右 【体重】:100斤左右 【凶器,是否假奶】:c饱满,手感不错 【肤色,手感】:白,滑 【B内温】:温暖 【BB户型】:没细看 【BB味道】:无 【课表,特色】:添蛋舒服 【人照相似】:8分 【服务过程】: 刚上线就见发任务,一看御姐马上抢了。立马约好出发目的地。 进门一见身材不错,脸也挺漂亮,有点年纪,有妊娠纹。做了四项,第一次做四项不知道针怎么开,感谢群友秒解答。脱衣洗澡有帮浴没有水中箫

1

3 Sept 2026, 09:10 UTC699 views0 reactionsread 3 September 2026

(正式工兵前缀,可信度较高) 【工兵报告】 『推荐指数:⭐️⭐️⭐️ ⭐️半』 【日期】:2026.9.3 【修车编号】:#NBTG1123 【美女昵称】:#丸子 【验证人】:茶 【地 区 】:鄞州 【联系方式】:@yiyi888887 【见面感觉】:8分 【室内光线】:明亮 【属性标签】:骚劲足 皮肤状态好 【身材曲线】:正常 【技术含量】:8 【价格 】:500/p(工兵半价) 【安 全 性】:出门在外,注意自身防范 【年龄】:28 【身高】:162 【体重】:90 【凶器,是否假奶】:b 【肤色,手感】:滑 白 偏嫩 【B内温】:温暖 【BB户型】:小鲍鱼 【BB味道】:无味 【三点】:正常 【课表,特色】:骚 带劲 风韵犹存 【人照相似】:8分 【服务过程】: 教室实际开在公寓楼上的酒店,安全性待考量,ls说开张了会考虑换安全的地方,位置倒也不难找,地下室电梯直达,初见ls,是一位风韵犹存的少妇胚子,脸上还是有不少

3 Sept 2026, 05:18 UTC946 views4 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐指数:⭐️⭐️ ⭐️ ⭐️』 【日期】:2026.9.2 【修车编号】:#NBTG1122 【美女昵称】:#赵彩儿 【验证人】:大湿兄 【地 区 】:鄞州 【联系方式】:@zhaocai_20 【见面感觉】:8分 【室内光线】:正常 【属性标签】:少妇 【身材曲线】:标准 【技术含量】:5 【价格 】:600/p(工兵半价) 【安 全 性】:酒店式公寓 【年龄】:30左右 【身高】:160左右 【体重】:90斤左右 【凶器,是否假奶】:D饱满,假 【肤色,手感】:黄,滑 【B内温】:温暖 【BB户型】:没细看 【BB味道】:无 【课表,特色】:三件套 【人照相似】:8分 【服务过程】: 捡漏工兵任务,领取后约好时间 出发,到达目的地指挥上来, 见面笑颜湘迎,本人比照片老点,照片美颜了,关门洗澡,浴室里老师洗,洗完,躺在床上等待老师....老师上来就直接口,然后带套干活了

4

3 Sept 2026, 02:23 UTC≈1,190 views3 reactionsread 3 September 2026

(活跃群友,可信度较高。) 『推荐指数:⭐️⭐️⭐️⭐️⭐️』 【日期】:9.2 【修车编号】:#NBTG1076 【美女昵称】:#小软 【验证人】:bwita 【地 区 】:鄞州 【联系方式】: @xiaoruan33 【见面感觉】:软妹甜妹 【室内光线】:正常 【属性标签】:嫩妹 【身材曲线】:修长 【技术含量】:8分 【价格 】:6p 【安 全 性】:公寓 【年龄】:19左右 【身高】:160左右 【体重】:不到90 【凶器,是否假奶】:a,真奶 【胸型】:馒头状 【肤色,手感】 正常黄皮,滑 【课表,特色】:课表都有,漂亮 【服务过程】: 这次是二刷软妹,在一刷后,始终不能忘怀软妹的娇甜可爱,又正遇到软妹的红休期,苦苦等待软妹回归。中午一看到软妹频道的开课通知,立马就约好了时间。心情还是如第一次去见他那般满是悸动与期待。因为前一个是上门的,我就只能在大门等待软妹回来。一声“这里”,我连忙循声望去。没

3

3 Sept 2026, 01:35 UTC≈1,010 views1 reactionsread 3 September 2026

(非活跃群友,可信度低。) 『推荐指数:⭐️⭐️⭐️⭐️⭐️(贱评/差评/中评/中上/好评,)』 【日期】:9/2 【修车编号】:#NBTG1118 【美女昵称】:#猫猫 【验证人】:我爱老师 【地 区 】:#鄞州 【联系方式】: @hvcsqa 【见面感觉】:很满意 【室内光线】:正常灯光偏暗 【属性标签】: 【身材曲线】:前凸后翘 【技术含量】:10 【价格 】:500/p 【安 全 性】:小区 【年龄】:目测25多 【身高】:161 【体重】:95左右 【凶器,是否假奶】完全真实大奶 【胸型】:轻微下垂 【肤色,手感】正常 【B内温】:烫 【BB户型】: 【BB味道】: 【三点】:微粉 【课表,特色】:深喉很顶,身材很好很滑 【人照相似,真人打几分】:遇到第一个如此接近照片视频的老师。没有美颜。 【服务过程】:得知老师来到宁波,看了照片视频后很有感觉,火速约课,开车70多分钟到达。小区停车方便而且两小时内免费,这点点

1

3 Sept 2026, 00:58 UTC892 views0 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐指数:⭐️⭐️⭐️⭐️ 半』 【日期】:2026.9.2 【修车编号】:#NBTG1117 【美女昵称】:#诱丽御姐 【验证人】:大奶 【地 区 】:海曙 【联系方式】:@dnyuss 【见面感觉】:8.5分 【室内光线】:正常 【属性标签】:服务系,御姐 【身材曲线】:前凸后翘 【技术含量】:9.5 【价格 】:500P(工兵半价) 【安 全 性】:公寓 【年龄】:30+ 【身高】:160左右 【体重】:95斤左右 【凶器,是否假奶】:c真 【肤色,手感】:偏白,较滑 【B内温】: 【BB户型】: 【BB味道】:无 【课表,特色】:标准莞式 【人照相似】: 【服务过程】: 粉色暧昧的灯光 白色晃动的乳房 恍惚间我好像回到了那年的东莞 虽然未曾踏足, 却享受着那里的服务。 现在有这般才艺的已经少之又少了。 之前听闻,刚入行的时候 很多老师甚至用香蕉来练口交技术 求道如此。 这位

3 Sept 2026, 00:29 UTC867 views1 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐指数:⭐️⭐️⭐⭐半〗 【日期】:9.2 【修车编号】:#NBTG1122 【美女昵称】:#赵彩儿 【验证人】:鸭 【地 区 】:鄞州 【联系方式】:@zhaocai_20 【见面感觉】:人照合一,高于预期。看似高p图但实则还好。 【室内光线】:明亮 【属性标签】:沉浸系做爱 【身材曲线】:s 【技术含量】:没有传统技术,靠感觉引导 【价格 】:6p 【安 全 性】:小众公寓网约房 【年龄】:28 【身高】:164 【体重】:95斤 【凶器,是否假奶】:做的d🐻 【胸型】:半球 【肤色,手感】 :正常肤色,背面没打粉微偏小麦 【课表,特色】:快餐课表。相处态度自然,不循规蹈矩 【服务过程】: 约的妹妹来宁波的头课,出发前多次提醒提前买四项,但还是罚站半小时。一开门妹子说没想到还挺帅,好感增加。见面高于预期,妹子比较瘦,长得有点像爱情公寓的宛瑜,能看出少许之前做ktv公主熬

1

3 Sept 2026, 00:22 UTC875 viewsread 3 September 2026

(正式工兵前缀,可信度较高) 【工兵报告】 『推荐指数:⭐️⭐️⭐️⭐️半』 【日期】:2026.9.1 【修车编号】:#NBTG1116 【美女昵称】:#米蓝 【验证人】:tom 【地 区 】:鄞州 【联系方式】:@jiriheb 【见面感觉】:9 【室内光线】:一般 【属性标签】:服务系少妇皮肤很白 【身材曲线】:大架子 【技术含量】:8 【价格 】:500P(工兵半) 【安 全 性】:公寓 【年龄】:30左右 【身高】:165左右 【体重】:110左右 【凶器,是否假奶】:d 【肤色,手感】:白,滑 【B内温】:温暖 【BB户型】:蝴蝶 【BB味道】:无味 【课表,特色】:服务到位,皮肤的很白 【人照相似】:9 【服务过程】:看到返场阿姨果断拿下,进门人照一致,本人更好看,很白妆画的也蛮好,身材属于阿姨党顶级,如果再年轻几岁完全可以走御姐路线了,交完水费脱光洗澡,浴室比较小只有简单帮洗,没有做水中萧提出应该会有,洗完

3 Sept 2026, 00:21 UTC≈1,040 views4 reactionsread 3 September 2026

(非活跃群友,可信度低。) 『推荐指数:⭐️⭐️⭐️⭐️⭐️(贱评/差评/中评/中上/好评,)』 【日期】:9/1 【修车编号】:#NBTG1118 【美女昵称】:#猫猫 【验证人】:小k总 【地 区 】:#鄞州 【联系方式】: @hvcsqa 【见面感觉】:温柔性感小网红类型 【室内光线】:正常灯光 【属性标签】: 【身材曲线】:前凸后翘 【技术含量】:10 【价格 】:500/p 【安 全 性】:小区 【年龄】:目测20多 【身高】:167 【体重】:95左右 【凶器,是否假奶】完全真实大奶 【胸型】:圆润饱满 【肤色,手感】正常 【B内温】: 【BB户型】: 【BB味道】: 【三点】: 【课表,特色】:深喉 胸推 网红气质 身材很好很滑 【人照相似,真人打几分】:比照片视频好看很多 【服务过程】:满怀期待来到楼下,进门果然并没有令我失望,一进门就看到一双修长美腿和修身包臀裙 更绝的是老师的颜值和气质完全不输大网红,有

4

2 Sept 2026, 14:33 UTC≈1,540 views0 reactionsread 3 September 2026

群被炸了,正在联络恢复中。 明天还没恢复的话,先启动备用签到群。

1 Sept 2026, 14:45 UTC≈3,160 views9 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐数:⭐️⭐️⭐️⭐️⭐️ 【日期】:2026.9.1 【修车编号】:#NBTG1118 【美女昵称】:#猫猫 【验证人】:聂风 【地 区 】:鄞州 【联系方式】:@hvcsqa 【见面感觉】:9分 【室内光线】:偏暗 【属性标签】:御姐 【技术含量】:7 【价格 】:500/p(工兵价) 【安 全 性】:公寓 【年龄】:26-28 【身高】:168 【体重】:100左右 【凶器,是否假奶】C~D 【胸型】:圆形 【肤色,手感】:常规 【B内温】:热 【BB户型】:小蝴蝶 【BB味道】:无 【三点】:正常 【课表,特色】:御姐 【人照相似,真人打几分】:9分 【服务过程】: 颜值:跟颜值视频一模一样几乎没有搞什么美颜, 因为脸蛋比较尖瘦,类似以前网上那种网红型, 真人在光下做笑着说话欢迎的时候,还有有明显的面部法令纹、嘴角纹等显现出来的。 颜值相对还是比较漂亮的。 身材

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1 Sept 2026, 13:49 UTC≈2,260 views2 reactionsread 3 September 2026

(正式工兵报告,可信度较高。) 【工兵报告】 『推荐指数:⭐️⭐️⭐️⭐』 【日期】:8.31 【修车编号】:#NBTG1121 【美女昵称】:#苏涵 【验证人】:独轮车驾驶员 【地 区 】:鄞州 【联系方式】: @suhan5670 【见面感觉】:8 【室内光线】:微暗 【属性标签】:bbw 【身材曲线】:丰腴 【技术含量】:7 【价格 】:600p工兵半价 【安 全 性】:安全 【年龄】:23 【身高】:160 【体重】:盲猜120+ 【凶器,是否假奶】:D,真 【肤色,手感】:黄,滑 【B内温】:热 【BB户型】:蝴蝶 【BB味道】:无味 【三点】:略黑 【人照相似】: 7 【服务过程】: 汽车人!出击! 老年人出击,一般都是半夜为什么呢,因为腿脚不方便了,爬的比较慢。。 跟老师约了时间得知有两个疯狗准备蹲我,于是我带上了准备许久的杖剑,就是抖音上那个广告挺多的,螺纹钢那么粗的钢棍

2

Showing the 12 most recent of 211 posts we hold for @nbgkb888. 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

@nbgkb888 edited 6 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
10 August 2026
Most recent edit
1 September 2026

Forward network

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 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.

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.

“宁波修车公开榜” (@nbgkb888), 22,313 subscribers as measured 19 September 2026. Telegram Register, tgregister.com/channel/nbgkb888.

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.