中国超级联赛 滚球中 0 - 0 青岛西海岸 vs 重庆铜梁龙 上半场 大/小 (欧洲盘) 大(0.5) @ 1.99
🎉21❤19🔥15😁15👍9

Channel
@mknnnn
On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
108,829subscribers
-3,610 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 100,000–316,228.
| Telegram ID | -1001209637492 |
|---|---|
| Type | Channel |
| Usernames | @lanhuo98 @mknnnn |
| Description | 🏆赛事早知道|专业体育赛事资讯平台 聚焦全球热门体育与电竞赛事,提供欧冠、欧联、五大联赛、中超、NBA、CBA、FIBA、LOL、DOTA2 等热门赛事赛程、数据分析、即时资讯与精彩集锦,打造更全面的观赛体验。 致力于为广大体育与电竞爱好者提供及时、专业、全面的赛事内容服务。 商务合作|广告投放|内容投稿 联系: @TYVIP8bot |
| Created | Between 1 March 2018 and 30 June 2021— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 13 August 2026 |
| Measurements held | 7 |
| Confirmed unchanged | 1 time, most recently 13 August 2026 |
| On Telegram | t.me/mknnnn |
Gambling & betting — a classification, not a measurement. An on-box language model (Qwen3.6-35B-A3B-UD-Q6_K_XL, prompt version 1) read this channel’s own recent posts on 9 August 2026 and assigned it the closest of 31 fixed categories, at 85% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 13 Aug 2026, 05:07 | 108,829 | -246 |
| 12 Aug 2026, 05:22 | 109,075 | -913 |
| 11 Aug 2026, 02:13 | 109,988 | -799 |
| 10 Aug 2026, 04:00 | 110,787 | -437 |
| 9 Aug 2026, 00:52 | 111,224 | -1,000 |
| 8 Aug 2026, 03:11 | 112,224 | -215 |
| 7 Aug 2026, 17:17 | 112,439 | first reading |
139 posts held, back to 7 August 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 23 pagesof 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 92 of 139 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 14 August 2026 |
|---|---|
| Posts held | 139 (7 August 2026 – 14 August 2026) |
| Views total | 672,825 |
| Reactions total | 4,701 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 14 Aug 2026, 12:29 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.
Lifetime counters from Telegram’s own channel header, read 14 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.
Measured directly from 10 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.
4,701 reactions across 91 posts, in 8 distinct kinds. The most used accounts for 21.0% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 🎉 | 988 | 21.0% | |
| ❤ | 980 | 20.8% | |
| 👍 | 954 | 20.3% | |
| 😁 | 890 | 18.9% | |
| 🔥 | 885 | 18.8% | |
| 🤣 | 2 | 0.043% | |
| 👎 | 1 | 0.021% | |
| 🥱 | 1 | 0.021% |
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 92 of the 139 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 4,701reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 139 most recent posts we hold, published 7 August 2026 to 14 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.
中国超级联赛 滚球中 0 - 0 青岛西海岸 vs 重庆铜梁龙 上半场 大/小 (欧洲盘) 大(0.5) @ 1.99
🎉21❤19🔥15😁15👍9
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🎉15🔥14👍12😁11❤7
Signed TGBot
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😁9👍8🎉6🔥4❤3
⚽️⚽️⚽️足球推荐 002芬超 23.00 队伍:瓦萨 VS TPS图尔 推荐:瓦萨.0.5/1 主任:胜 分数:1-0 2-0 2-1 ——————————— 004德乙 00.30 队伍:不伦瑞克VS波鸿 推荐:不伦瑞克让0 竞猜:胜 比分:1-0 2-0 2-1 ——————————— 006瑞典超 01.00 队伍:艾夫斯堡VS韦斯特罗 推荐:艾夫斯堡-0.5 主任:胜 比分:1-0 2-0 2-1 ——————————— 007挪超 01.00 队伍:罗森博格VS维京 推荐:罗森博格让0 主任:胜 分数:1-0 2-1 3-2 ——————————— 009沙特联 02.00 队伍:利亚新月VS哈马费萨 推荐:利亚新月-2.5 主任:让胜 分数:4-0 4-1 5-1 ——————————— 017葡超 03.15 队伍:里斯本VS吉马良斯 推荐:里斯本-1.5/2 主任:让胜 分数:4-1 3-0 4-0 ————…
❤20🔥20😁20🎉12👍7
Signed 大螃蟹 (赌博找我)
俱乐部友谊赛 滚球中 0 - 1 卡洛华克 vs 特尔捷 上半场 大/小 (香港盘) 大(1.5) @ 1.66 高水第一关
👍25😁23🔥22🎉18❤14
日本J1联赛 队伍:东京绿茵 vs 柏雷素尔 推荐:东京绿茵 +0.5 赔率:0.99 中国超级联赛 队伍:武汉三镇 vs 上海海港 推荐:大 3 赔率:0.83 中国超级联赛 队伍:山东泰山 vs 青岛海牛 推荐:山东泰山 -1.5 赔率:0.97 中国超级联赛 队伍:青岛西海岸 vs 重庆铜梁龙 推荐:重庆铜梁龙 +0 / 0.5 赔率:1.04 挪威超级联赛 队伍:洛辛堡 vs 维京 推荐:大 3 / 3.5 赔率:0.88 葡萄牙超级联赛 队伍:里斯本竞技 vs 甘马雷斯 推荐:里斯本竞技 -1.5 赔率:0.83
❤22😁13👍11🎉9🔥9
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🎉29👍29🔥23❤19😁19
Signed TGBot
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😁10👍6🔥6❤5🎉5
沙特阿拉伯职业联赛 滚球中 0 - 1 艾伯哈 vs 哈森姆 上半场 大/小 (欧洲盘) 大(1.5) @ 1.86
❤20🎉16😁15👍9🔥8
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😁12👍9🎉8🔥7❤2
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❤32🎉28👍26🔥17😁9
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❤26🎉19👍19😁19🔥17
Showing the 12 most recent of 139 posts we hold for @mknnnn. 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 — 28,730 of 1,336,469entries 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.
Named by 107 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. The 24 listed below are the most frequent namers; the rest are counted above but not each listed.
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 13 August 2026 — this entry's latest reading, not the date you are reading this.
“体育推单|外围足球 |内幕红单|五大联赛预测” (@mknnnn), 108,829 subscribers as measured 13 August 2026. Telegram Register, tgregister.com/channel/mknnnn.
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.