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Channel

🌔『体育电竞赛事滚球红单推单

@SJBhongdan

On this record: Topic · Observations · Also posting the same content · Growth · Engagement · Reactions · Posts · Citations · Cite this entry

9,897subscribers

-8,478 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-1003835275628
TypeChannel
Username@SJBhongdan
CreatedBetween 1 February 2026 and 31 July 2026 — estimated from Telegram’s id allocation, not measured. How this range is calculated.
First recorded7 August 2026
Last confirmed live16 September 2026
Measurements held30
Confirmed unchanged1 time, most recently 16 September 2026
On Telegramt.me/SJBhongdan

Topic

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 10 August 2026 and assigned it the closest of 31 fixed categories, at 92% 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.

Observations

These are measurements, not verdicts. Each one below states something we counted, alongside the evidence it was counted from, so you can check it rather than take it. None of them is graded: every observation this register holds is recorded at severity 0, because the precision of the detectors behind them has not been measured yet, and a rating we cannot support is worse than none. Read each as a fact about the data, not as a judgement about the channel. How we measure.

Content that also appears on other registered channels

Posts published here appear word for word on 1 other registered channel. They sit inside a group of 5 channels that share the same post bodies with each other. The matching is on the text itself, not on Telegram’s forward marker, so it finds a copy whether or not it was labelled as one.

Matching posts — open both and compare (5 of the pairs behind the counts below)
Posted firstThenOverlapGap
@ybgf9/140754 Aug 2026, 14:27 UTC@SJBhongdan/1157 · this entry4 Aug 2026, 14:53 UTC1.0026 minutes
@SJBhongdan/1163 · this entry5 Aug 2026, 14:59 UTC@ybgf9/140775 Aug 2026, 15:09 UTC1.0011 minutes
@ybgf9/140786 Aug 2026, 15:49 UTC@SJBhongdan/1169 · this entry6 Aug 2026, 16:52 UTC1.0063 minutes
@ybgf9/140827 Aug 2026, 10:21 UTC@SJBhongdan/1172 · this entry7 Aug 2026, 10:30 UTC1.008 minutes
@SJBhongdan/1175 · this entry7 Aug 2026, 16:13 UTC@ybgf9/140857 Aug 2026, 16:27 UTC1.0014 minutes
Every channel this entry shares post bodies with
ChannelMatching postsText overlapTypical gapPublished first
@ybgf95 (5/5 hand-verifiable sample passed)1.0014 minutes@ybgf9 (32)

Text overlap is the Jaccard coefficient over the set of distinct three-word phrases in the two bodies: 1.00 is identical wording, and the threshold for counting a pair at all is 0.70. Candidates are generated by simhash LSH (4 x 16-bit bands, exact Hamming <= 3) verified against the bodies with Jaccard over the SET of distinct 3-word shingles. Published first counts which side of each matching pair carries the earlier timestamp — in this corpus, which is the limitation directly below.

What this cannot establish

MEASURED, DOMINANT ERROR SOURCE: a post ingested before 2026-08-06 may have carried a forward header that was not recorded. A 45-pair hand-check against live t.me pages found 14 (31%) where the live page shows a forward header naming the other channel and the database has none, plus 4 more (9%) naming a third party. The text match itself was wrong 0 times out of 45. Read attribution_capture.items_in_trusted_window before treating the unattributed count as a claim.

Telegram lets a channel forward a post with a header naming the source, and we only began reliably recording that header on 2026-08-06. 2 of the 3 matches recorded here fall after that date and carried no header when we read them. The rest predate reliable capture and are not evidence either way.

“Published first” means first in this corpus. We hold 6 comparable posts for this entry, running 4 August 2026 to 7 August 2026. A channel we have read one page deep will look younger than a neighbour we have read in full, and the order would flip with no change in the underlying facts.

The detector’s own notes on this observation, as it recorded them. Names in this_style are fields of the underlying evidence record, which the plain-English paragraphs above read out for this entry.

  • Verbatim republication has three causes and the text separates only two: a clone/mirror, unattributed copy-paste, or BOTH channels copying a common third source that neither attributes. The spread filter (content held by at most 8 channels) reduces the third and does not remove it.
  • 'Earliest' means earliest IN THIS CORPUS. A channel ingested one page deep will look younger than a neighbour ingested in full; corpus_coverage above is there to be checked before the direction is believed.
  • shared_verified_est extrapolates the sampled pass rate over the full narrow match count; sampled/passed are the numbers actually measured.
  • Absence of a forward header is not proof of intent: Telegram lets a channel disable forward attribution, and a credit written in the body is not parsed as attribution here (mention_edge_either_way above is the closest available signal).

Across the whole group of 5, the earliest publisher we hold is @cftiyu. That is a statement about our reading window, not a claim of authorship.

Recorded under the key clone_mutual, last confirmed 8 August 2026. An observation that a later pass no longer finds is cleared, and a cleared observation is removed from this page rather than being shown struck through — we do not keep publishing a claim we have withdrawn. Dispute an observation.

Also posting the same content

This channel’s posts match, word for word or near enough, posts on 4 other registered channels, found by comparing text fingerprints across every channel on the register. That matching has been checked by hand against the live Telegram pages and found reliable — 0 wrong of 45 pairs re-read.

Which channel, if either, published first is deliberately not shown. The same hand-check found that reading wrong 18 of 45 times — 60%, no better than a coin flip — because it depends on how deep our own crawl happened to reach into each channel’s history, not on when the content was actually first posted. This list is ordered by subscriber count, the same as every other listing on this site, never by which channel we think came first. Word-for-word matching has several ordinary explanations besides copying — a channel mirroring itself, an unattributed repost, or two channels independently repeating the same wire story — and this measurement cannot tell those apart. How this is measured.

Growth

9,89718,37514,1367 August 2026 — 18,375 subscribers8 August 2026 — 18,342 subscribers9 August 2026 — 18,333 subscribers10 August 2026 — 18,291 subscribers11 August 2026 — 18,206 subscribers12 August 2026 — 10,636 subscribers13 August 2026 — 10,599 subscribers15 August 2026 — 10,568 subscribers16 August 2026 — 10,524 subscribers17 August 2026 — 10,464 subscribers18 August 2026 — 10,441 subscribers19 August 2026 — 10,430 subscribers20 August 2026 — 10,410 subscribers21 August 2026 — 10,394 subscribers23 August 2026 — 10,383 subscribers25 August 2026 — 10,363 subscribers25 August 2026 — 10,340 subscribers27 August 2026 — 10,334 subscribers27 August 2026 — 10,325 subscribers28 August 2026 — 10,314 subscribers29 August 2026 — 10,254 subscribers30 August 2026 — 10,238 subscribers31 August 2026 — 10,214 subscribers1 September 2026 — 10,190 subscribers2 September 2026 — 10,177 subscribers4 September 2026 — 10,156 subscribers7 September 2026 — 10,116 subscribers10 September 2026 — 10,066 subscribers12 September 2026 — 9,976 subscribers16 September 2026 — 9,897 subscribers7 August 202616 September 2026
30 measurements spanning 40 days, net -8,478. 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 8,625–19,647 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 30
Measured (UTC)SubscribersChange
16 Sept 2026, 01:209,897-79
12 Sept 2026, 14:579,976-90
10 Sept 2026, 10:0110,066-50
7 Sept 2026, 02:3710,116-40
4 Sept 2026, 09:2210,156-21
2 Sept 2026, 20:2510,177-13
1 Sept 2026, 16:5510,190-24
31 Aug 2026, 18:5410,214-24
30 Aug 2026, 19:5610,238-16
29 Aug 2026, 22:5510,254-60
28 Aug 2026, 20:0210,314-11
27 Aug 2026, 21:1310,325-9
27 Aug 2026, 00:2710,334-6
25 Aug 2026, 21:4310,340-23
25 Aug 2026, 00:5510,363-20
23 Aug 2026, 14:0710,383-11
21 Aug 2026, 23:1710,394-16
20 Aug 2026, 15:4810,410-20
19 Aug 2026, 17:4210,430-11
18 Aug 2026, 20:0710,441first reading

Engagement

131 posts held, back to 4 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 39 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
0.124%
avg views ÷ 9,897 subscribers
Avg views / post
12.2
51 posts measured
Reaction rate
11.1%
reactions ÷ views · ER floor
Posts in window
51
of 131 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 1 of 51 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 29 August 2026
Posts held131 (4 August 202629 August 2026)
Views total624
Reactions total1
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken29 Aug 2026, 17:20 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

3 reactions across 3 posts, in 2 distinct kinds. The most used accounts for 66.7% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
266.7%
👏133.3%

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 131 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 3 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.

Measured over the 131 most recent posts we hold, published 4 August 2026 to 29 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.

Recent posts

29 Aug 2026, 12:43 UTC8 viewsread 29 August 2026
Photo

---同路上车 跟反自由--- ---赛事无神 红黑勿怪--- 德甲 21:30 队伍:艾禾斯堡-勒沃库森 推荐:艾禾斯堡(+1) 德甲 21:30 队伍:科隆-霍芬海姆 推荐:科隆(+0/0.5) 德甲 21:30 队伍:美因茨05-帕德博恩 推荐:美因茨05(-1) 德甲 21:30 队伍:RB莱比锡-门兴格拉德巴赫 推荐:RB莱比锡(-1) 德甲 21:30 队伍:柏林联-法兰克福 推荐:法兰克福 (0) 英超 22:00 队伍:考文垂-赫尔城 推荐:双进(是)

29 Aug 2026, 12:01 UTC9 viewsread 29 August 2026
Photo

---同路上车 跟反自由--- ---赛事无神 红黑勿怪--- 英超 19:30 队伍:利物浦-诺丁汉森林 推荐:诺丁汉森林(+1/1.5) 英冠 19:30 队伍:米德尔斯堡-西布朗 推荐:全场大(2.5/3) 英冠 19:30 队伍:狼队-斯托克城 推荐:斯托克城(+0.5/1) 英冠 19:30 队伍:德比郡-斯旺西 推荐:总进球(2/3球) 中超 19:30 队伍:成都蓉城-辽宁铁人 推荐:辽宁铁人(+1/1.5) 中超 20:00 队伍:河南-重庆铜梁龙 推荐:河南(-1.5)

29 Aug 2026, 08:23 UTC7 viewsread 29 August 2026

日本J1联赛 清水心跳 VS 柏太阳神 08-29 17:30 (GMT+8) 全场让球 [欧洲盘] 柏太阳神 -0.5 @ 1.90 日本J2联赛 大宫松鼠 VS 湘南海洋 08-29 18:00 (GMT+8) 全场让球 [欧洲盘] 湘南海洋 +0/0.5 @ 1.87 烤肉串走起!

28 Aug 2026, 14:18 UTC9 viewsread 29 August 2026

德国乙级联赛 布伦瑞克 VS 柏林赫塔 08-29 00:30 (GMT+8) 全场让球 [欧洲盘] 布伦瑞克 +0/0.5 @ 1.83 法国甲级联赛 里尔 VS 巴黎圣日耳曼 08-29 02:45 (GMT+8) 全场让球 [欧洲盘] 巴黎圣日耳曼 -1 @ 2.12 吃肉2串1 干! 剁屌担保!

28 Aug 2026, 14:12 UTC9 views1 reactionsread 29 August 2026
Photo

2026-08-29 02:00 沙特超级联赛 卡赫利塞哈特 v 希拉尔 足球 球队进球数: 希拉尔 - 大 / 小 - 上半场 大 1 2026-08-29 02:30 德国甲组联赛 拜仁慕尼黑 v 斯图加特 足球 大 / 小 - 上半场 大 1.5 / 2 2026-08-29 02:45 意大利甲组联赛 AC米兰 v 威尼斯 足球 角球数 - 让球 AC米兰 -2.5 2026-08-29 02:45 法国甲组联赛 里尔 v 巴黎圣日耳曼 足球 让球 巴黎圣日耳曼 -0.5 / 1 2026-08-29 03:00 英格兰超级联赛 水晶宫 v 曼城 足球 球队进球数: 曼城 - 大 / 小 大 1.5 / 2 五串四

1

28 Aug 2026, 11:37 UTC7 viewsread 29 August 2026
Photo

---同路上车 跟反自由--- ---赛事无神 红黑勿怪--- 马来超 19:30 队伍:沙巴-檳城 推荐:沙巴(-0.5/1) 中超 19:35 队伍:大连英博-北京国安 推荐:全场小(3) 中超 19:35 队伍:上海申花-山东泰山 推荐:上海申花(-1) 中超 20:00 队伍:深圳新鹏城-上海海港 推荐:深圳新鹏城(+0.5)

28 Aug 2026, 11:10 UTC7 viewsread 29 August 2026

2026-08-28 19:35 中国超级联赛 大连英博 v 北京国安 足球 让球 北京国安 -0 / 0.5 2026-08-28 19:35 中国超级联赛 上海申花 v 山东泰山 足球 让球 上海申花 -1 2026-08-28 19:35 中国超级联赛 深圳新鹏城 v 上海海港 足球 大 / 小 大 2.5 / 3

28 Aug 2026, 10:35 UTC7 viewsread 29 August 2026

澳大利亚新南威尔士联赛二 悉尼大学 VS 保尼白鹰 08-28 18:00 (GMT+8) [滚球] 上半场大小 [欧洲盘] 大 0.5 @ 2.11

28 Aug 2026, 08:41 UTC8 viewsread 29 August 2026
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韩国女子K联赛 仁川现代制铁(女) VS 庆州 KHNP(女) 08-28 18:00 (GMT+8) 全场让球 [欧洲盘] 仁川现代制铁(女) +0.5 @ 1.88 兄弟们开户单 剁屌担保!

27 Aug 2026, 15:43 UTC11 viewsread 29 August 2026

2026-08-28 01:00 欧洲联赛外围赛-附加赛 萨尔茨堡红牛 v 米亚尔比 足球 让球 萨尔茨堡红牛 -2 ------------------------- 2026-08-28 02:30 西班牙甲组联赛 维戈塞尔塔 v 奥萨苏纳 足球 角球数 - 大 / 小 大 8.5 ------------------------- 2026-08-28 02:30 英格兰联赛杯 切尔西 v 卢顿 足球 大 / 小 - 上半场 大 1.5 ------------------------- 2026-08-28 03:00 西班牙甲组联赛 巴塞罗那 v 毕尔巴鄂竞技 足球 让球 巴塞罗那 -1.5 / 2 ------------------------- 2026-08-28 01:00 欧洲协会联赛外围赛-附加赛 贺拉戴克 v 帕纳辛奈科斯 足球 让球 帕纳辛奈科斯 -0 / 0.5 ------------------

27 Aug 2026, 12:51 UTC10 viewsread 29 August 2026

澳大利亚北部特区超级联赛 海伦斯 VS 加鲁达FC 08-27 19:00 (GMT+8) [滚球] 全场大小 [欧洲盘] 大 3.5 @ 2.03

27 Aug 2026, 12:15 UTC9 viewsread 29 August 2026

俄罗斯杯资格赛 巴尔瑙尔戴拿模 VS 艾立叙欧斯克 08-27 18:30 (GMT+8) [滚球] 全场大小 [欧洲盘] 大 5.5 @ 2.01

Showing the 12 most recent of 131 posts we hold for @SJBhongdan. 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.

Mentions

Named by 2 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 16 September 2026 — this entry's latest reading, not the date you are reading this.

“🌔『体育电竞赛事滚球红单推单” (@SJBhongdan), 9,897 subscribers as measured 16 September 2026. Telegram Register, tgregister.com/channel/SJBhongdan.

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.