Gambling & betting — a classification, not a measurement. An on-box language model (qwen3.6:35b-a3b, prompt version 1) read this channel’s own recent posts on 3 November 2026 and assigned it the closest of 31 fixed categories, at 98% 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 the other topics.
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.
Views per post sit far below this size band
1.4 average views per post against 10,126 subscribers — an engagement rate of 0.014%. Across the 1,944 registered channels in the same cohort — 10,012–31,612 subscribers, posting mainly in Chinese — the middle half sit between 1.80% and 11.6%, with a median of 4.90%.
What this was computed from
Window
30 days (4 October 2026 – 3 November 2026)
Posts measured
23 of 23 published in the window (23 exact, 0 rounded by Telegram)
Views totalled
32
Mature posts only
0.014% over 17 posts read at least 24h after publication
When this is recorded. A channel is listed here only when its engagement rate sits at or below the 1st percentile of its cohort and is at least 3× away from that cohort’s median — below it — on both the all-readings figure and the mature-only figure. The percentile alone would be circular: a percentile cut puts the same share of every cohort in the tail whatever the data looks like. The distance from the median is what makes it a statement about this channel.
This is not a verdict, and the direction is not a quality signal. A low rate has many innocent causes — audiences that read in the Telegram app without opening the channel, a subscriber base built long before the current output, an audience in a different timezone from our reading. A high rate has innocent causes too: a post that travelled far beyond the channel’s own subscribers will do it. We publish the measurement and the distribution it sits in. The full cohort baselines are downloadable, so this comparison can be reproduced rather than trusted.
Recorded under the key err_low, last confirmed 4 November 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.
Growth
2 measurements taken within a single day. 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 10,116–10,136 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
4 Nov 2026, 01:49
10,126
no change
3 Nov 2026, 05:22
10,126
first reading
Engagement
23 posts held, back to 31 October 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 3 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
0.014%
avg views ÷ 10,126 subscribers
Avg views / post
1.4
23 posts measured
Reaction rate
—
this channel exposes no reaction counts
Posts in window
23
of 23 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
Window
Rolling 30 days · latest post in window 3 November 2026
Posts held
23 (31 October 2026 – 3 November 2026)
Views total
32
Reactions total
—
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
3 Nov 2026, 21:22 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
10s
Average length
5s
Measured directly from 2 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.
1⃣1⃣月1⃣日 😍😀 于谦结算
❤❤❤❤❤❤❤❤
澳超 珀斯光荣 vs 阿德莱德联（阿德莱德联-0/0.5 / 大2.5/3）⭐️重点
赛果：4-0 ✖️（让球未中 / 大球命中）
德乙 菲尔特 vs 荷尔斯泰因基尔（荷尔斯泰因基尔+0/0.5 / 大2.5）
赛果：1-0 ✖️（让球未中 / 大球未中）
德乙 汉诺威96 vs 德累斯顿迪纳摩（汉诺威96-0.5 / 大2.5）⭐️重点
赛果：2-1 ✅（让球命中 / 大球命中）
德乙 圣保利 vs 纽伦堡（圣保利-0/0.5 / 大2.5/3）
赛果：1-3 ✖️（让球未中 / 大球命中）
意甲 科莫 vs 威尼斯（科莫-0.5/1 / 大2.5）⭐️重点
赛果：1-0 ✅（让球半赢 / 大球未中）
德甲 柏林联合 vs 科隆（柏林联合-0/0.5 / 小2.5/3）
赛果：1-1 ✖️（让球半输 / 小球命中）
意甲 弗罗西诺内 vs 都灵（都灵+0/0.5 / 小2.5…
Showing the 12 most recent of 23 posts we hold for @T1tiyubot. 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 recorded as deleted after publishing
We recorded 1 post on @T1tiyubot as deleted — posts this register held that were missing from the channel’s public page on two separate reads, taken from different network addresses at least an hour apart.
A deletion is not wrongdoing. This register can see that a post it held is no longer on the channel’s public page, and when — not why. Expired ad placements, reposts, rotating links and corrections all look the same. This is a count of recorded detections, not an exact total: it misses deletions we could not see, because only a post we held and later re-read inside the page can be seen to go, and it may include a small number of wrong records. How this is measured.
First seen missing
3 November 2026
Most recent seen missing
3 November 2026
Median time before seen missing
37 hours
Seen missing in the last 30 days
1
Mentions
Named by 10 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.
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 4 November 2026 — this
entry's latest reading, not the date you are reading this.
“🥇T1体育🅥招商代理🅥官网” (@T1tiyubot), 10,126 subscribers as measured 4 November 2026. Telegram Register, tgregister.com/channel/T1tiyubot.
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.
