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 15 September 2026 and assigned it the closest of 31 fixed categories, at 53% 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
14 measurements spanning 38 days, net +9. 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 2,545–2,561 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
13 Sept 2026, 22:41
2,557
-2
10 Sept 2026, 05:17
2,559
+5
4 Sept 2026, 16:15
2,554
+2
1 Sept 2026, 10:05
2,552
-1
29 Aug 2026, 13:24
2,553
-3
26 Aug 2026, 14:23
2,556
-1
23 Aug 2026, 15:47
2,557
+2
20 Aug 2026, 10:13
2,555
+3
17 Aug 2026, 11:13
2,552
+2
13 Aug 2026, 18:18
2,550
+2
10 Aug 2026, 16:17
2,548
+1
7 Aug 2026, 09:57
2,547
-1
6 Aug 2026, 18:45
2,548
no change
6 Aug 2026, 18:34
2,548
first reading
Engagement
9 posts held, back to 2 August 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 2 pages 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 9 posts for this entry, the most recent from 7 August 2026. An engagement rate over an empty window would be a number about nothing.
Reaction mix
236 reactions across 9 posts, in 4 distinct kinds. The most used accounts for 42.4% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
100
42.4%
👍
74
31.4%
🔥
61
25.8%
💯
1
0.424%
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 9 of the 9 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 236 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 9 most recent posts we hold, published 2 August 2026 to 7 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.
Telegram Stars
Stars received
1
across the posts below
Posts paid on
1
of 9 we hold a reading for · 11%
Most on one post
1
single highest reading
A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @evotrens. Telegram publishes the count on the public post preview alongside ordinary reactions, and this register reads it there. It is the only figure on this site that measures money moving rather than attention.
Stars are not reactions, and the two are never added. They are rendered in the same strip on Telegram and counted in the same shape, but one is a tap and the other is a purchase. The reaction totals and the engagement rate elsewhere on this page exclude every figure in this section, and no rate here is computed against a reaction count.
This is not revenue, and we publish no currency figure. What a Star costs a reader and what it pays a channel are different numbers, Telegram takes a share we cannot observe, and the terms have changed. Converting a Star count into money would be an estimate dressed as a measurement, so the count is where we stop.
Counted over the 9 most recent posts we hold for this entry, published 2 August 2026 to 7 August 2026. Star counts above 1,000 reach us in Telegram’s short form and carry the same three-significant-figure rounding as everything else on this page.
🔥 Лопатка работает на стене, которая дышит
⠀
Рубрика Анны Мацкевич
⠀
Лопатку часто пытаются «зафиксировать», будто это кронштейн, который однажды прикрутили к стене и забыли.
Но анатомия собрана интереснее. У лопатки нет настоящего сустава с рёбрами. Она скользит по поверхности грудной клетки и удерживается мышцами.
⠀
🏗 Грудная клетка - фасад здания. Лопатка - подвижная рабочая платформа. Передняя зубчатая и трапеция…
Отзыв Мария А.
"После вебинара по протракции решила взять у вас еще и курс по дыханию. И вот тут я прям в восторге.
Все очень понятно, без воды, а дополнения под видео вообще отдельная любовь. Уже начала понемногу использовать материал с клиентами и наконец поняла, на что именно смотреть, а не просто давать всем подряд «подышать животом».
Спасибо огромное Дмитрию и всей вашей команде! Точно буду рекомендовать коллег…
Вы продаете не на тренировке. Вы продаете тренировкой.
Можно знать техники продаж, красиво объяснять ценность и владеть «секретными формулировками». Но если само занятие слабое, все это работает как дорогая упаковка пустой коробки.
Клиент оценивает не только то, что вы говорите. Он чувствует, насколько точно подобраны упражнения, понимаете ли вы его состояние, умеете ли менять нагрузку и есть ли у происходящего ясна…
Начинаю серию интервью с различными специалистами.
За ребятами из Physiotutors я слежу давно и признателен им за многие варианты, которые они публикуют.
Поэтому Андреас, являющийся сооснователем, и стал первым героем этой серии.
https://evotren.ru/blog/tpost/physiotutors
✅ Друзья, в приложении появился вебинар Максима Оборина с разбором упражнения «Джампинг джек».
Кажется, что проще уже некуда: прыжок, ноги в стороны, руки вверх. Но именно в таких знакомых движениях особенно хорошо видно, умеет ли клиент сохранять ритм, управлять приземлением и распределять нагрузку без лишнего удара по стопам, коленям и пояснице.
Для тренера джампинг джек - это быстрый способ заметить, где человек…
Коллеги! Кто регулярно рекомендует наши курсы и имеет неплохую аудиторию тренеров (или тех, кто хочет стать тренером), то пишите на [email protected] с темой письма - хочу промокод.
Сделаем персональный промокод и те, кому вы рекомендовали курс, смогут оформить его по скидке, а вы получите бонус.
🔥 “Я всё потерял за эту неделю”
Рубрика Анны Мацкевич
Клиент пропустил несколько тренировок и возвращается с ощущением, будто всё придется начинать заново.
“Я совсем выпал”.
“Наверное, форма уже ушла”.
“Теперь опять месяц восстанавливаться”.
И здесь тренеру легко либо слишком бодро сказать: “Да ничего страшного”, либо устроить человеку наказание за отсутствие.
Ни то ни другое не помогает.
За одну сложную неделю ч…
Showing the 9 most recent of 9 posts we hold for @evotrens. 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.
Stars beside a post are paid reactions — Telegram Stars, bought with money and spent on that post. They are a different unit from reactions and are never added to them, here or anywhere else on this page.
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.
Cross-platform identity — Wikidata
A Wikidata item names this Telegram handle as belonging to the entity it describes. This is Wikidata’s claim, not a verification made by this register — nobody here confirmed that the account is genuinely operated by the entity named. Wikidata content is CC0; every fact below is dated to when it was read from Wikidata, not to when the association was first made there.
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 13 September 2026 — this
entry's latest reading, not the date you are reading this.
“Evotren | Сообщество думающих тренеров” (@evotrens), 2,557 subscribers as measured 13 September 2026. Telegram Register, tgregister.com/channel/evotrens.
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.