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Channel

Эволюция тренировки

@evotraining

On this record: Topic · Growth · Engagement · What this channel posts · Reactions · Stars · Posts · Citations · Telegram's recommendations · Cite this entry

8,043subscribers

-43 since we began measuring on 6 August 2026

Risers and fallers across the register · movement among entries of 3,162–10,000.

Register entry

Telegram ID-1001342661439
TypeChannel
Username@evotraining
Created11 December 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel)
First recorded6 August 2026
Last confirmed live27 September 2026
Measurements held13
Confirmed unchanged1 time, most recently 27 September 2026
On Telegramt.me/evotraining

Topic

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 12 September 2026 and assigned it the closest of 31 fixed categories, at 59% 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

8,0438,0908,066.56 August 2026 — 8,086 subscribers6 August 2026 — 8,086 subscribers12 August 2026 — 8,090 subscribers16 August 2026 — 8,083 subscribers20 August 2026 — 8,081 subscribers24 August 2026 — 8,078 subscribers26 August 2026 — 8,068 subscribers29 August 2026 — 8,065 subscribers1 September 2026 — 8,058 subscribers5 September 2026 — 8,059 subscribers10 September 2026 — 8,053 subscribers13 September 2026 — 8,051 subscribers27 September 2026 — 8,043 subscribers6 August 202627 September 2026
13 measurements spanning 52 days, net -43. 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 8,036–8,097 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)SubscribersChange
27 Sept 2026, 00:178,043-8
13 Sept 2026, 19:578,051-2
10 Sept 2026, 06:178,053-6
5 Sept 2026, 02:388,059+1
1 Sept 2026, 14:468,058-7
29 Aug 2026, 21:328,065-3
26 Aug 2026, 23:448,068-10
24 Aug 2026, 01:528,078-3
20 Aug 2026, 04:228,081-2
16 Aug 2026, 19:388,083-7
12 Aug 2026, 22:248,090+4
6 Aug 2026, 07:158,086no change
6 Aug 2026, 07:078,086first reading

Engagement

18 posts held, back to 13 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 19 pages of Telegram’s post history, 20 posts per page.

ERR · 30 days
8.94%
avg views ÷ 8,043 subscribers
Avg views / post
719
1 post measured
Reaction rate
7.23%
reactions ÷ views · ER floor
Posts in window
1
of 18 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
WindowRolling 30 days · latest post in window 28 August 2026
Posts held18 (13 July 2026 – 28 August 2026)
Views total719
Reactions total52
Forwards / commentsnot exposed by the public surface — not measured, not estimated
Readings taken28 Aug 2026, 19:04 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
1m 11s
Average length
24s

Measured directly from 3 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

1,459 reactions across 17 posts, in 11 distinct kinds. The most used accounts for 41.1% of them.

Every reaction kind recorded on the sample, most used first
ReactionCountShareShare, drawn
❤59941.1%
🔥38726.5%
👍33623.0%
❤‍🔥634.32%
💯382.60%
🤝171.17%
✍100.685%
🤔40.274%
😁30.206%
👏10.069%
🫡10.069%

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 18 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 1,545 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 13 July 2026 to 28 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
6
across the posts below
Posts paid on
5
of 18 we hold a reading for · 28%
Most on one post
2
single highest reading

A paid reaction is a reader spending Telegram Stars — bought with money — on a post by @evotraining. 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 18 most recent posts we hold for this entry, published 13 July 2026 to 28 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.

Recent posts

28 Aug 2026, 11:18 UTC719 views52 reactions1 Starread 28 August 2026

Вопрос о наболевшем от подписчика: Евгений добрый день. Работаю тренером в Училище олимпийского резерва по Боксу. Тренерский стаж работы 20 лет. Возраст моих учащихся 14-18лет. Что касается специализации по виду спорта, то здесь у меня вопросов нет, ну или по крайней мере ответы я могу найти общаясь с коллегами и специалистами по виду спорта. А вот теперь причина моей головной боли уже не первый год. Когда я был спор…

🔥27👍12❤8✍3😁2

25 Aug 2026, 11:10 UTC≈1,280 views115 reactions1 Starread 28 August 2026
Photo

Как мы оказались в горах Год назад мы с племянником Максом (15 лет на тот момент) поднимались на гору в Геленджике на скорость. Это была его инициатива, которую я с удовольствием поддержал. Там невысоко, перепад высоты был всего около 400 м, но прямой путь вверх и темп сделали свое дело. В процессе он быстро устал, приуныл, всячески изображал страдание. Но мы поднялись. Если честно, я думал, что он больше не захоче…

❤56👍32🔥26👏1

24 Aug 2026, 14:35 UTC≈1,450 views140 reactions2 Starsread 28 August 2026
Photo

Только вернулся из отпуска в Ташкенте. Был там всего 5 дней, программа супер плотная, главное событие – восхождение на Большой Чимган. О восхождении расскажу отдельно, есть несколько интересных моментов, которыми хочу поделиться. Сейчас о другом. Пару лет назад мне довелось поработать с узбекской паралимпийской легкоатлеткой Сафией Бурхановой, выступающей в толкании ядра. Мы работали дистанционно, я выступал в качес…

❤83🔥43👍11❤‍🔥3

19 Aug 2026, 12:55 UTC≈2,160 views116 reactions1 Starread 28 August 2026

"Клиентам ничего не нужно и не интересно" Снова и снова в общении с тренерами на тему подходов к тренингу слышу, что заморачиваться смысла нет, потому что «людям с фитнес-целями ничего не интересно, только похудеть/подкачаться». И меня это немного злит. Слушайте, ну да, так и есть! Люди часто воспринимают тренировки как необходимое зло, чтобы нормально выглядеть. Это может позвучать для кого-то неприятно, но в сред…

❤66👍31🔥19

11 Aug 2026, 08:30 UTC≈2,310 views44 reactionsread 28 August 2026
Photo

Запись вебинара "Планирование межсезонной подготовки для профессиональных спортсменов" на примере плана для Арсена Захаряна теперь доступна в закрытом клубе тренеров Evotraining Team по этой ссылке. Те, кто не успел поучаствовать в вебинаре, но хотели бы ознакомиться с материалом, теперь имеют эту возможность. Запись вебинара по планированию для фитнес-клиента с учетом занятий паделом тоже будет там. В ведении клу…

❤20👍13🔥10❤‍🔥1

10 Aug 2026, 14:57 UTC≈2,170 views61 reactionsread 28 August 2026
Photo

Сегодня завершили сборы тренеров, посвященные обучению клиентов сложным двигательным навыкам. 8 дней по 4 часа интенсивной работы. Разбирали двигательный состав разнообразных навыков, от приседа до рывка штанги, от отжиманий до ходьбы на руках, от прыжков до ускорений. Изучали вариации, ошибки, коррекции, команды. Учились учить друг на друге. Традиционно на таких сборах мы используем компактный формат с небольшим кол…

🔥29❤19👍12❤‍🔥1

7 Aug 2026, 07:36 UTC≈2,390 views88 reactionsread 28 August 2026

Стать лучшим тренером по физподготовке в России – когда-то у меня, начинающего специалиста, была такая мечта. Как бы наивно не звучала эта установка, она добавляла мотивации учиться, повышать квалификацию, браться за сложные задачи. Со временем (а также знаниями и опытом) пришло понимание, что такая установка не имеет практического смысла. Лучший тренер – в чем? По сравнению с кем? Каковы критерии? Кто в жюри? Мир ф…

❤41🔥27👍19❤‍🔥1

3 Aug 2026, 06:45 UTC≈3,380 views49 reactionsread 28 August 2026
Photo

Photo, posted without a caption

🔥41👍7❤1

2 Aug 2026, 13:45 UTC≈2,640 views65 reactionsread 28 August 2026

Конкурентные тренировки В тренировке комплексной направленности мы одновременно развиваем несколько физических качеств. Например, скоростную силу в начале тренировки, затем силу и в конце выносливость. Вопрос, который часто при этом возникает: как подбирать упражнения так, чтобы свести к минимуму конкуренцию стимулов (на уровне сигнальных путей, расхода гликогена, ударной нагрузки, доступной энергии и т.д.)? Причем о…

❤35👍26🔥3😁1

31 Jul 2026, 07:03 UTC≈1,970 views38 reactionsread 28 August 2026

Бесплатный вебинар 4 августа: "Планирование межсезонья для профессиональных спортсменов" Нередко слышу от тренеров: вот классно было бы работать с профессиональными спортсменами! Вот с ними бы я смог использовать весь свой арсенал методов и инструментарий! У профи совсем другое отношение к ОФП – не то, что в фитнесе, где люди ничего не хотят, кроме похудеть/подкачаться. В работе со спортсменами, действительно, треб…

👍16🔥12❤10

30 Jul 2026, 09:34 UTC≈2,080 views52 reactionsread 28 August 2026

Регуляция объема силовой через % падения скорости Когда нам требуется развивать максимальную силу, обычно силовая работа выполняется в диапазоне от 1 до 5 повторений на интенсивности 80% от 1ПМ и выше. Но помимо интенсивности и количества повторений хорошо бы еще понимать, сколько повторений в подходе делать. Вот, например, на 85% от 1ПМ сколько делать, 1, 3 или 5 повторов? Ответ важен потому, что мы хотим решать за…

👍23❤15🔥10🤔4

29 Jul 2026, 14:30 UTC≈1,880 views89 reactionsread 28 August 2026

Сейчас настраиваюсь на сборы по обучению сложным двигательным навыкам для тренеров, которые начнутся на следующей неделе, и освежаю теоретический материал. Одна из важных концепций в двигательном обучении – разделение внутреннего и внешнего фокуса внимания при формулировании инструкций и команд. В любом произвольном движении или упражнении можно фокусироваться на внутренних ощущениях, а можно – на внешних факторах и…

👍45❤26🔥14✍4

Showing the 12 most recent of 18 posts we hold for @evotraining. 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

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.

Mentions

Named by 4 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.

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.

Appears in Telegram’s recommendations for other channels

The reverse of the list above, and a different kind of signal. This does not require this channel to have ever been asked about directly — each row below is a channel we DID ask Telegram about, whose Telegram-generated list happened to include this one. A channel can appear here with an empty list above it, because being named by someone else’s query is independent of having been queried itself.

Физикл | Олег Зингилевский
@fiztransform · 149,098
Telegram ranks this channel #5 of 95 here — alongside 94 others — read 12 August 2026
Александр Семенов
@trenersemenov · 22,844
Telegram ranks this channel #36 of 96 here — alongside 95 others — read 19 September 2026
Доктор Епифанов | Невролог| Все о позвоночнике
@epifanovnews · 49,123
Telegram ranks this channel #44 of 93 here — alongside 92 others — read 26 August 2026
Скоромный
@Skoromnyy · 22,173
Telegram ranks this channel #53 of 79 here — alongside 78 others — read 21 September 2026
Павел Баранов. Эндокринология/диетология.
@pavelbaranov_md · 31,179
Telegram ranks this channel #66 of 96 here — alongside 95 others — read 6 September 2026
Мудрость Фитнеса (тренер Кабуров)
@fitness_mayatnik · 25,728
Telegram ranks this channel #75 of 93 here — alongside 92 others — read 13 September 2026

This channel appears in 6 seed channels' Telegram-generated recommendation lists in total. Each is Telegram’s list for THAT channel, not this one — see how this is measured.

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 27 September 2026 — this entry's latest reading, not the date you are reading this.

“Эволюция тренировки” (@evotraining), 8,043 subscribers as measured 27 September 2026. Telegram Register, tgregister.com/channel/evotraining.

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.