Education — 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 24 September 2026 and assigned it the closest of 31 fixed categories, at 70% 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
7 measurements spanning 62 days, net +42. 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 170–228 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
8 Oct 2026, 21:16
221
+6
27 Sept 2026, 14:19
215
+18
14 Sept 2026, 09:21
197
+13
6 Sept 2026, 10:21
184
+7
28 Aug 2026, 15:47
177
-2
8 Aug 2026, 13:15
179
no change
7 Aug 2026, 17:37
179
first reading
Engagement
18 posts held, back to 27 August 2025 — 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 18 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
34m 31s
Average length
2m 18s
Measured directly from 15 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
171 reactions across 17 posts, in 7 distinct kinds. The most used accounts for 34.5% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
59
34.5%
🔥
44
25.7%
👍
41
24.0%
👏
11
6.43%
❤🔥
10
5.85%
🏆
4
2.34%
🙏
2
1.17%
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 17 of the 18 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 171 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 18 most recent posts we hold, published 27 August 2025 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.
Друзья, наконец-то готов представить результат полугодовой работы — мой новый авторский сайт boriskrasnov.ru.
Это не просто визитка, а полноценная платформа, которую я собирал вручную от первой строчки кода до финального монтажа видеоуроков.
Что внутри: 📚 Два авторских курса. Курс «Стопы» (10 подробных часовых уроков) создавался целый год. Каждый урок снят и смонтирован лично мной.
Второй курс — «Функциональные до…
В этом видео я рассказываю о важных деталях во время работы на мышцы живота.
О которых многие забывают или вовсе не знают и потом имеют проблемы с вываливающимся низом живота и дисфункцией мышц тазового дня.
Работа с группами это мой социальный проект. Это единственный в Москве, в таком формате, который я создавал с начала 2018.
Все придумывал сам, нет никаких стандартных протоколов групповых программ. Все очень гибко, в зависимости от физических данных занимающихся.
В нем я собрал все свои знания и опыт, которые я постоянно пополняю. Сколько продлится еще этот проект я не знаю, пока веду..
Я собрал здесь множество т…
Иногда наша нервная система бывает излишне перенапряжена. И выстреливает зажатыми регионами мышц - шейный отдел, плечи, поясница и тд. В этом видео я рассказываю как с помощью теста на гипертонус можно выявить это.
Showing the 12 most recent of 18 posts we hold for @krasnovfitness. 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.
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 8 October 2026 — this
entry's latest reading, not the date you are reading this.
“KrasnovFitness” (@krasnovfitness), 221 subscribers as measured 8 October 2026. Telegram Register, tgregister.com/channel/krasnovfitness.
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.