Channel
@sapper_996
On this record: Growth · Engagement · Reactions · Posts · Citations · Cite this entry
517subscribers
+1 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1003997152504 |
|---|---|
| Type | Channel |
| Username | @sapper_996 |
| Created | Between 1 April 2026 and 16 July 2026— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 7 August 2026 |
| Measurements held | 2 |
| Confirmed unchanged | 1 time, most recently 7 August 2026 |
| On Telegram | t.me/sapper_996 |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 7 Aug 2026, 13:00 | 517 | +1 |
| 6 Aug 2026, 20:32 | 516 | first reading |
19 posts held, back to 16 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 1 pageof Telegram’s post history, 20 posts per page.
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 3 of 19 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 19 (16 July 2026 – 6 August 2026) |
| Views total | 2,895 |
| Reactions total | 7 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 6 Aug 2026, 20:32 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.
7 reactions across 3 posts, in 3 distinct kinds. The most used accounts for 57.1% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 💩 | 4 | 57.1% | |
| ❤ | 2 | 28.6% | |
| 👍 | 1 | 14.3% |
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 3 of the 19 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 7reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 19 most recent posts we hold, published 16 July 2026 to 6 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.
【时间】：2026.8 【艺名】：念念 【账号】： @nn00n12 【原价】：1300p 【位置】：闵行 【硬件】： 接近25岁，170身高，腿长而直；脸圆，颜值一般，眼妆精致；皮肤较黑，还算细腻；骨架较大，胸大小一般；逼毛有处理，小穴阴唇不大。 【软件】： 温柔的声音，温柔的态度，情趣套装众多可选。 没有什么浴室服务，口技良好，做爱相当配合，屌感出色。 【过程】： 看频道被大长腿吸引，遥控上门后，念念直接穿着女仆装开裆黑丝高跟鞋迎接，哇～ 教室里有一排衣柜，每节课可以选一件。 170的大骨架妹子，胸不算很大，皮肤也不算太白，声音一直都很温柔。交完水费一起洗完澡，念念重新穿上她情趣套装，爬上床头施展起她的口技，技术真好。我也反身展示我的口技，念念下面有点味儿（明明洗得挺仔细的），不过她反馈足够强烈，抽动的双腿和阵阵呻吟。 坐上来后，多么温暖紧润的小穴，还好会夹，多种姿势夹的我好爽。床头摆放一落地镜，以念念的黑丝长腿，谁…
时间：2026.7 老师名字： 琪琪 老师电报号：@qiqi_7520 硬件： 颜值 3.75（脸较小，五官是小美女） 妆品 3.75（脸上粉比较多，穿搭懂得遮掩自己体重身材） 身高体重 170cm 63kg（） 皮肤 3.5（黄皮，四肢略黑，躯干较白，四肢皮肤稍有些粗糙，纹身只有胸口上方一个蓝色小蝴蝶） 胸 4.5（很软很大的脂肪D-胸，乳头乳晕都挺小，乳头敏感易挺立，臀桥时可以轻松含住乳头） 腰 2.25（手感是光滑细腻的，但是好几圈游泳圈，没法看） 臀 3.5（这个体重下，屁股确实挺大的，肉也多） 腿 2.5（身高下长度是有的，但大腿肉粗得夸张，小腿也略粗） 足 4（37码，指甲油比较漂亮，肉不算多，脚底光滑，脚背皮肤很好） 逼 3（毛发完全没有打理，阴唇颜色正常，内粉） 软件： 陪浴 3.75（有事前事后帮洗，前后都洗得仔细；没有帮擦；认真学做水中箫，没有其他服务了） 亲嘴 2.5（没有舌吻…
老师在苏州开课中 @nannan1090 原账号是骗子
【时间】：2026.8 【艺名】：林凡凡 【账号】： @susuQx 【原价】：1100p 【位置】：徐汇 【硬件】： 实打实168身高，全身软软的。C胸柔软好摸，长腿笔直匀称。全身只有左肩有玫瑰与牡丹纹身，皮肤非常细腻，晒不到的地方相当白皙。小穴粉嫩敏感。 【软件】：天生的顶级小女友灵动感，青春可爱。可舌吻，可舔逼。 【过程】： 先前有狼友评价景甜赵今麦的合体，景甜的五官我没太看出来，但是确实有几分像脸更圆一些的赵今麦感觉。妆不浓，后面妹妹当我面卸妆后，真人和妆后差别很小。 见面时妹子还在吃鸡，我悄悄环抱着看她成盒，她也没有拒绝。小女友的灵动感或许真是一种天赋，我和她甫一见面就恍若小情侣般直接嬉笑打闹起来，可能这就是来电吧。 拉扯中一起来到浴室，看到那和水管分离的花洒让我不禁大笑，还可以玩小水管了。我为她脱下内衣，互相仔仔细细清洗，当然也少不了深深拥吻一番，好甜的小嘴～ 从浴室出来凉飕飕得赶紧和凡凡一起钻入被窝，怀抱软妹…
时间：2026.6 老师名字： 小小 老师电报号：@XiaoXooo8 硬件： 颜值 3（普通路人，没化妆下，脸上的皮肤状态很差，还有点精灵耳） 妆品 3（忙于搬家，素颜，只有一个纹眉，穿搭也很普通） 身高体重 173cm 50kg（高挑匀称） 皮肤 3.75（身上皮肤很白皙，手感细腻光滑，但素颜脸上可能过敏了，一下子拉低了；无纹身） 胸 4（C胸微翘，不算很饱满，手感很软，一含乳头就挺，不过乳头较大；乳晕硬币大小，颜色都正常褐色） 腰 3.75（腰本身不算很细，但和臀比起腰线明显，看不出马甲线，但能感受到腰有力量，站立坐下都有小肚子） 臀 4.5（自称没有锻炼，但骨盆宽，又有肉又紧实，手感顶级，弹性十足） 腿 4.25（1.73配上不差的比例，腿长不错，大腿匀称，肉稍有点肉了，小腿细长） 足 3.5（36码埃及脚，脚底有些许老茧，无异味，没有太多肉） 逼 3.5（毛有点多，没有打理；蝴蝶b，阴唇颜色较深…
👍1💩1
【时间】：2026.8 【艺名】：雯雯 【账号】： @Mpbjb 【原价】：1000p 【位置】：闵行 莘庄 【硬件】：160，瘦瘦的，皮肤不白，手感非常光滑，纹身很多；穴小，无毛发处理；脚好看！ 【软件】：女友感良好，总是能自然依偎在身边，相处很愉快。但是没有舌，没有口（头一回）。 【过程】： 8月的第一发盲盒探访嫩妹雯雯，闵行的老小区，安全度还行。 妹子自述13岁就开始纹身，身上纹身很多，皮肤很光滑，好摸爱摸。 自称被家里逼婚烦了来上海开课，业务上不成熟，但女友感又很不错，自然可爱，没有舌吻但又一直可以小啄。 身上到处都好敏感，耳朵、胸、手指，脚趾都一舔就缩回去啊。做爱也同样，不要问会什么，但是一切反应都突出一个真实强烈。 雯雯的小脚真的让我爱不释手，解锁了雯雯🦶的第一次也不亏哈哈哈。 【总结】 一个优缺点都非常突出的妹子，来上海也没上几节课，没上一节课可能就可以多解锁一点技能。 推荐星级：⭐️ #女友感 #…
【艺名】：林啾啾 【账号】： @xiuxiu698 【位置】：#长宁 【原价】：1000p 【时间】：2026.7 【硬件】： 人照略有差距，但圆脸挺可爱的。皮肤较黑，手感细腻，纹身很多，但比欣欣美观一点。 C胸，大大软软，屁股有肉，个子也更高一些。 【软件】： 总体快餐服务，有舌吻。做爱配合，叫床激情。相处也更和谐。 【过程】： 每天在群里看到啾啾，百闻不如一见。尽管人照不是很接近，但小圆脸很可爱，身材也是前凸后翘，小小的身子，大大软软的c胸。 服务虽然总体比较快餐，但是啾啾小舌头好灵活，啾啾啾得，三点口得我好美，吹得我差点想发射了。在床上啾啾配合度很高，怎么都听话，爸爸妈妈乱喊，毫不吝啬音量，一番盘肠大战让人心满意足。 【总结】： 硬件软件都强于林欣欣，值得打卡。 推荐星级：⭐️ #快餐 #林啾啾 #性价比
【艺名】：林欣欣 【账号】： @xinxin5679 【位置】：#长宁 【原价】：1000p 【时间】：2026.7 【硬件】： 人照接近，瘦瘦小小，不到80斤。皮肤较黑，手感尚可，纹身很多 胸略强于板上钉钉，屁股有一点肉。 【软件】： 快餐服务，叫床够骚，可浅舌吻。客厅有些烟味。愿意配合的姿势不多 【总结】： 就床上那一阵阵不顾隔音的浪叫，半价快餐是可以的。 推荐星级：原价没必要 #快餐 #林欣欣 #瘦
我的好兄弟隔壁老王为她果果老师投稿一篇 【验证时间】：2026.7.24 【妹子艺名】：果果 【联系方式】： @Ssguoguo 【上课水费】：包天 【位置环境】：5 【罩杯手感】：c 【身材描述】：棒 【服务类型】：顶级 【服务态度】：顶级 【屌感体验】：很不错 【个人总结】：众里嫣然通一顾，人间颜色如尘土，回眸一笑百媚生，六宫粉黛无颜色。这句话用来比喻果果则是再为恰当不过。早在上个月的时候，从榜单看到了果果。第一眼感觉这姑娘，还行。进了频道随便看看，直到看到一张穿着睡袍的照片，我楞住了，脑海里突然闪现出我去世的前女友。此时此刻，我不知道该用什么词语去表达我的心情。但是我的内心只有一个想法，即使我现在水泥封心，但是这个姑娘，我！约定了！ 但是本人因为在外地出差，只能和果果商量好日子再来怒战。从包时到夜课，再到包天。聊天中果果也没有因为我问东问西去敷衍，而是耐心的和我说着细节，最后敲定，包天计划，启动！ 但天有不测风云，从上个月…
💩3❤1
时间：2026.6 老师名字： 喵椰 老师电报号：@miaoye777 硬件： 颜值 3.75（颜值不惊艳但耐看，好笑，虎牙提升些可爱） 妆品 3.75（脸上粉将脸修饰得比较白，不卡粉.穿搭是温馨少妇风，感觉更适合走可爱路线，她本人想要成熟一点风格） 身高体重 165cm 45kg（） 皮肤 4（挺白的黄皮，身上没有色差，大部手感细腻，背面小有粗糙，背上有些许浅浅红点；锁骨附近有没及时刮的极淡的体毛；身上有多处纹身，手臂上多朵樱花，腿上的大面积纹身在一点点洗。） 胸 3.75（较小的B胸，不算饱满，乳头挺立而敏感，舔了后叫声连连；乳晕很小，颜色较浅） 腰 4（腰很细，腰线明显，腰光滑洁白） 臀 3.5（屁股较小，臀型微翘，没什么肉，比较紧实） 腿 3.75（比例正常，腿型不错；大小腿肉都比较松软，不够紧实） 足 4（37码白皙埃及脚，有和手指同款指甲油，脚背较高，肉不多，脚底有正常的些许粗糙，无死皮老茧） …
【时间】：2026.7 【艺名】：兜兜 【账号】： @dodo0826 【原价】：800p 【位置】：闵行 【硬件】：人照勉强，瘦瘦黑黑，皮肤很一般。胸不大，腿和屁股有些肉，还行。 【软件】：态度挺好，开朗能聊，服务基础 【过程】： 800的半价原本只是指望一个快餐，但是兜兜的女上给了我好大的惊喜。会用各种女上姿势摇，而且小穴越抽越紧，很爽啊。虽然我觉得这公寓房隔音很一般，但兜兜也是能放声浪叫。只是做着做着，套上一红，桩出姨妈了，就此作罢吧。做之前她就感觉会提前几天，还得是女生懂自己身体。 【总结】：硬件很一般，做爱体验不赖，半价可快餐 推荐星级：0.5⭐️ #快餐 #女桩机 #性价比 #兜兜
漂移的lcp乐乐已换账号： @manmanya123
Showing the 12 most recent of 19 posts we hold for @sapper_996. 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 — 445,817 of 1,151,006entries 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.
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
Republishes
Channels on the register whose posts this channel has forwarded.
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.
Named by 3 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.
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.
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 7 August 2026 — this entry's latest reading, not the date you are reading this.
“9拆盲盒” (@sapper_996), 517 subscribers as measured 7 August 2026. Telegram Register, tgregister.com/channel/sapper_996.
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.