新台催收 #宜享花 苹果ios, 25年上线出货 金额3000以上 已测试,下款流水没问题 ,新货懂的来 数量22w+
Signed 法海

Channel
@fahai717
On this record: Topic · Growth · Engagement · What this channel posts · Posts · Citations · Cite this entry
8,411subscribers
+3,911 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of 3,162–10,000.
| Telegram ID | -1001773175491 |
|---|---|
| Type | Channel |
| Username | @fahai717 |
| Description | 出售全行业各类精准数据 ✈️:@fahai818 |
| Created | Between 1 December 2021 and 30 April 2023 — estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 7 August 2026 |
| Last confirmed live | 14 November 2026 |
| Measurements held | 42 |
| Confirmed unchanged | 1 time, most recently 14 November 2026 |
| On Telegram | t.me/fahai717 |
Gambling & betting — 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 11 September 2026 and assigned it the closest of 31 fixed categories, at 97% 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.
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 14 Nov 2026, 10:58 | 8,411 | -48 |
| 9 Nov 2026, 09:46 | 8,459 | -40 |
| 5 Nov 2026, 16:45 | 8,499 | -41 |
| 2 Nov 2026, 19:01 | 8,540 | -63 |
| 30 Oct 2026, 11:19 | 8,603 | -66 |
| 27 Oct 2026, 11:46 | 8,669 | -54 |
| 24 Oct 2026, 18:09 | 8,723 | +2,112 |
| 21 Oct 2026, 21:56 | 6,611 | -57 |
| 18 Oct 2026, 11:56 | 6,668 | -30 |
| 15 Oct 2026, 18:21 | 6,698 | -148 |
| 12 Oct 2026, 23:20 | 6,846 | -195 |
| 6 Oct 2026, 08:39 | 7,041 | -191 |
| 29 Sept 2026, 10:40 | 7,232 | -403 |
| 19 Sept 2026, 07:17 | 7,635 | -181 |
| 15 Sept 2026, 03:17 | 7,816 | -2,194 |
| 13 Sept 2026, 15:37 | 10,010 | -2,235 |
| 11 Sept 2026, 17:58 | 12,245 | -277 |
| 9 Sept 2026, 02:20 | 12,522 | -98 |
| 5 Sept 2026, 19:56 | 12,620 | -1 |
| 3 Sept 2026, 17:16 | 12,621 | first reading |
52 posts held, back to 1 January 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 63 pages of 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.
| Window | Rolling 30 days · latest post in window 12 November 2026 |
|---|---|
| Posts held | 52 (1 January 2026 – 12 November 2026) |
| Views total | 10,226 |
| Reactions total | — |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 15 Nov 2026, 02:15 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 15 November 2026 — not the date at the top of this page, which is when the subscriber count was last read. Below Telegram’s rounding threshold, so these counts are exact.
Telegram’s own ‘edited’ marker: 1 of 9 posts held from the last 30 days (11.1%) carried it when this register last read them. The marker says a post was changed after publishing, not what it said before — this register holds the earlier wording only where an edit fell between two of its own reads (see the edit ledger and how it is measured).
新台催收 #宜享花 苹果ios, 25年上线出货 金额3000以上 已测试,下款流水没问题 ,新货懂的来 数量22w+
Signed 法海
各行业实时提取出货中... 需要的咨询 @fahai818
Signed 法海
台湾购物数据 25年5.4W左右 26年12.6W左右 一手未出 数量有限来 打包选手
Signed 法海
现如今数据市场鱼龙混水,选择对一个数据商变得至为重要,能够为你节省很多渠道消耗费用,以最小的成本达到最佳的效果,毕竟底料才是 引流的核心 @fahai818
Signed 法海
南美洲老牌BC博彩:http://67n.com/ 会员数据已全部脱库🔥 全库数据500万+🗡 @fahai818
Signed 法海
全网最精准装修数据 覆盖了全国地级市,内鬼来源 目前市面上最精准的装修数据,没有之一 可出实时,周内,月内,三个月内,历史 包省,包市,包地区的优先!!! 带上你的量来,有量有价!@fahai818
Signed 法海
#台湾 菠菜带银行 联系 @fahai818
Signed 法海
现在的灰产类是独有通道,自有的模型每天都是再跑的,不要再纠结随时出单的问题
Signed 法海
六合收单,精准论坛劫持数据,百分百六合老彩民数据,适合各类型渠道消耗,效果好,留存高。 @fahai818
Signed 法海
长话短说⚠️⚠️⚠️ 注意:所有格式均可以手动编辑操作,真假难辨,有人咨询很多奇奇怪怪的模版不做过多的解释,一手保真,一分钱一分货,是什么就是什么,做生意只为长久,不做一次性生意,垃圾东西不做,你有效果我才有收入,行业水深,鱼龙混杂,追求一个目的:共赢! 欢迎咨询: @fahai818
Signed 法海
国家补贴中心 383750条 储藏工程 254225条 数贸会 23898条 大梦初心 26577条 共信中华 363402条 脱库完成!开始出货!@fahai818
Signed 法海
共信中华
Signed 法海
Showing the 12 most recent of 52 posts we hold for @fahai717. 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.
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.
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 14 November 2026 — this entry's latest reading, not the date you are reading this.
“🌈🌈法海数据直营💥海内外全行业抓取” (@fahai717), 8,411 subscribers as measured 14 November 2026. Telegram Register, tgregister.com/channel/fahai717.
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.