Sports — 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 25 September 2026 and assigned it the closest of 31 fixed categories, at 99% 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.
Growth
6 measurements spanning 38 days, net +4. 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 152–158 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
14 Sept 2026, 06:18
157
+1
29 Aug 2026, 22:44
156
+2
22 Aug 2026, 19:37
154
-1
14 Aug 2026, 19:46
155
+2
8 Aug 2026, 19:16
153
no change
7 Aug 2026, 17:34
153
first reading
Engagement
20 posts held, back to 14 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 page of Telegram’s post history, 20 posts per page.
Nothing published in the last 30 days. ERR and ER are rolling 30-day measures, so there is nothing to compute — we hold 20 posts for this entry, the most recent from 3 August 2026. An engagement rate over an empty window would be a number about nothing.
What this channel posts
Video runtime
1m 49s
Average length
10s
Measured directly from 11 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.
Reaction mix
335 reactions across 20 posts, in 10 distinct kinds. The most used accounts for 31.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
🔥
105
31.3%
❤
89
26.6%
custom 5201889721185233476
84
25.1%
🏆
22
6.57%
😱
15
4.48%
⚡
7
2.09%
👍
5
1.49%
🤬
4
1.19%
💘
2
0.597%
🥰
2
0.597%
Custom emoji. One row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The count beside it is Telegram’s.
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 20 of the 20 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 335 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 20 most recent posts we hold, published 14 July 2026 to 3 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.
ФК «Немосква» объявляет просмотр в состав!
Мы — команда с победной культурой. За короткое время мы прошли путь от новичков до грозы турниров. Наши достижения — это результат работы и единства:
• Чемпионство в 3-й лиге.
• Победа в Серебряной лиге АЛФ.
• Бронза 2-й лиги.
• Звание Чемпионов главы Ленинского района.
Мы ищем усиление! Если ты чувствуешь в себе силы бороться за высшие места, если тебе тесно в любительск…
Showing the 12 most recent of 20 posts we hold for @nemoscowfc. 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.
Forward network
Republished by
Channels on the register that have forwarded this channel's posts into their own feed.
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.
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 14 September 2026 — this
entry's latest reading, not the date you are reading this.
“МФК «Немосква»” (@nemoscowfc), 157 subscribers as measured 14 September 2026. Telegram Register, tgregister.com/channel/nemoscowfc.
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.
