Блог Евгения Богачёва о грамотном и системном тренинге для атлетов и тренеров
▪️Обучение тренеров https://clck.ru/39LcZM
▪️Вебинары, мини-курсы, тренировочные планы: @evo_sales_bot
Задать вопрос - @evotra1ning
Created
11 December 2017 — measured — cross-checked against a third-party dataset (ext.tg_channel)
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 the other topics.
Growth
25 measurements spanning 96 days, net -44. 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 8,014–8,100 and does not start at zero.
Measurement log — every subscribers count we have recorded, most recent 20 of 25
Measured (UTC)
Subscribers
Change
10 Nov 2026, 14:49
8,042
+6
7 Nov 2026, 02:21
8,036
+5
4 Nov 2026, 03:56
8,031
+7
1 Nov 2026, 13:05
8,024
-3
29 Oct 2026, 08:41
8,027
+1
26 Oct 2026, 13:09
8,026
-7
23 Oct 2026, 22:17
8,033
-1
21 Oct 2026, 02:29
8,034
-3
17 Oct 2026, 23:30
8,037
+7
15 Oct 2026, 04:40
8,030
+6
11 Oct 2026, 22:16
8,024
-5
5 Oct 2026, 07:16
8,029
-14
27 Sept 2026, 00:17
8,043
-8
13 Sept 2026, 19:57
8,051
-2
10 Sept 2026, 06:17
8,053
-6
5 Sept 2026, 02:38
8,059
+1
1 Sept 2026, 14:46
8,058
-7
29 Aug 2026, 21:32
8,065
-3
26 Aug 2026, 23:44
8,068
-10
24 Aug 2026, 01:52
8,078
first reading
Engagement
41 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 35 pages of Telegram’s post history, 20 posts per page.
ERR · 30 days
23.4%
avg views ÷ 8,042 subscribers
Avg views / post
1,880
10 posts measured
Reaction rate
5.05%
reactions ÷ views · ER floor
Posts in window
10
of 41 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
Window
Rolling 30 days · latest post in window 9 November 2026
Posts held
41 (13 July 2026 – 9 November 2026)
Views total
18,825
Reactions total
951
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
11 Nov 2026, 01:07 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
Photos
796
Videos
354
Links
772
Lifetime counters from Telegram’s own channel header, read 11 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.
Video runtime
3m 24s
Average length
41s
Measured directly from 5 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
3,657 reactions across 39 posts, in 19 distinct kinds. The most used accounts for 39.9% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
❤
1,458
39.9%
🔥
930
25.4%
👍
864
23.6%
💯
158
4.32%
❤🔥
121
3.31%
🙏
37
1.01%
👏
21
0.574%
🤝
18
0.492%
✍
10
0.273%
🎉
7
0.191%
😭
7
0.191%
🏆
6
0.164%
😁
5
0.137%
🤔
4
0.109%
💔
3
0.082%
🤯
3
0.082%
🦄
3
0.082%
💊
1
0.027%
🫡
1
0.027%
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 40 of the 41 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 3,743 reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 41 most recent posts we hold, published 13 July 2026 to 9 November 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
11
across the posts below
Posts paid on
8
of 40 we hold a reading for · 20%
Most on one post
3
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 41 most recent posts we hold for this entry, published 13 July 2026 to 9 November 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
Telegram’s own ‘edited’ marker: 1 of 10 posts held from the last 30 days (10.0%) 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).
Вершины горы можно достигнуть разными путями – а в тренинге задачу можно решить разными методами и средствами. Это хорошие новости для нас, потому что мы можем быть эффективными в очень разнообразных условиях.
Например, мышечная гипертрофия. Мы знаем, что можем добиться роста мышечной массы, работая по 8-12 повторений на 60-80% от 1ПМ. Но также мы можем добиться этого, выполняя многоповторку с 30-40%, или работая с …
Один из важнейших принципов в физиологии – принцип размера Ханнемана.
Обнаружил, что не писал в блоге об этом принципе, а он прям очень важен. Понимание этого принципа помогает также понять:
- почему важно приближаться к отказу в гипертрофийной работе
- почему чтобы стать сильнее, требуется работать со значительным сопротивлением
- зачем нужна быстрая силовая работа
- как дольше выполнять работу на выносливость
- ка…
EVO_HYROX: новая программа тренировок
В одном из залов, где я тренируюсь, на доске написано задание для подготовки в Hyrox. Там буквально одна тренировка с пометкой «не стирать!», которая представляет собой просто обрезанную версию соревновательной программы. Так, конечно, можно тренироваться. Иногда.
Hyrox – это не методика тренировок. Прогонять соревновательную программу в каком-то виде в определенные моменты нуж…
С днём тренера!
Так сложилось, что о праздниках я вспоминаю обычно с запозданием: о национальных праздниках, когда утром при прогулке с собакой вижу пустые улицы; о профессиональных – когда кто-нибудь кого-нибудь с ними поздравляет.
День физкультурника и день тренера всегда приходят неожиданно! Но это всегда приятный сюрприз и возможность немного порефлексировать.
Когда-то давно, в прошлой жизни, когда я только-то…
Отдых внутри подхода: когда, зачем, в каком формате?
В силовой тренировке отдых может применяться не только между подходами, но и внутри подхода. Делается это с несколько отличными целями, в зависимости от решаемых задач. Но физиология всегда одна: отдых внутри подхода создает условия для снижения окклюзии и лучшего кровоснабжения мышц, лучшего ресинтеза креатинфосфата и его доступности в каждом повторе, и меньшей а…
Сверхобобщение как ошибка тренерского мышления
Нередко встречаюсь с ошибками мышления, когда какая-то переменная в тренинге признается одинаково важной (или неважной) вне зависимости от контекста.
Например, объем в рабочих подходах. В гипертрофийном тренинге результаты во многом завязаны на объем тяжелых подходов в неделю. 10 лучше 5, 15 лучше 10, 20 лучше 15. Ну и иногда начинают рассуждать в русле, что такая же з…
31 октября - 01 ноября пройдет очный практический семинар по планированию тренировочного процесса для реабилитологов и физических терапевтов.
На примере актуальных протоколов, которые повсеместно используются в реабилитации, мы разберем:
▪️как управлять тренировочным воздействием и направлять адаптацию необходимых структур и функций
▪️как подбирать и регулировать нагрузку на разных этапах
▪️как выстроить микроцикл …
Новые навыки, повторы и подходы
Недавно студентка задала вопрос, который звучит примерно так:
Как при обучении новым навыкам определить оптимальное количество повторений и подходов?
Как всегда, хочется конкретики типа «3*8». Но двигательное обучение – процесс нелинейный и сильно варьирует в зависимости от того, кто, чему и у кого учится.
Потому вместо однозначного «совета быстрого приготовления» поделюсь, как я обы…
В субботу провел мастер-класс в рамках конвенции MFITNESS, посвященный изометрическим методам тренировки.
Изометрика интересна тем, что может эффективно применяться для очень разных задач:
- максимальная сила в специфичных углах
- скорость нарастания силы в преодолевающем и стопорящем действиях
- гипертрофия, укрепление соединительных тканей
- повышение жесткости сухожилий
- развитие гибкости
- двигательный контроль…
«Хитрость жизни в том, чтобы умереть молодым, но как можно позже» - такую фразу увидел вчера, и она прям зацепила.
Когда ее увидел, сразу вспомнил недавний разговор с другом, который сказал примерно так:
«Я вот думал, зачем я вообще тренируюсь? Зачем делаю тяжелые приседы и тяги, если это все избыточно для повседневной жизни? И я понял – для того, чтобы прожить подольше и успеть увидеть побольше. Меня прям заворажив…
Долгое время говорили, что для гипертрофии надо работать в диапазоне от 8 до 12 повторений, и это считалось самодостаточным по важности фактором. Но исследования (1, 2) снова и снова подтверждают: важно не конкретное количество повторений, а приближение к мышечному отказу в подходе (создающее достаточное механическое напряжение в волокнах целевых мышечных групп) и суммарный объем тяжелых подходов в неделю (10-20 подх…
❤72🔥46💯17👍11
Showing the 12 most recent of 41 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
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.
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.
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.
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 · 148,367 Telegram ranks this channel #5 of 95 here — alongside 94 others — read 12 August 2026
Александр Семенов @trenersemenov · 22,682 Telegram ranks this channel #36 of 96 here — alongside 95 others — read 19 September 2026
ЛиндоВерный @lindover · 20,113 Telegram ranks this channel #37 of 85 here — alongside 84 others — read 27 September 2026
Доктор Епифанов | Невролог| Все о позвоночнике @epifanovnews · 49,258 Telegram ranks this channel #44 of 93 here — alongside 92 others — read 26 August 2026
Скоромный @Skoromnyy · 22,001 Telegram ranks this channel #53 of 79 here — alongside 78 others — read 21 September 2026
Павел Баранов. Эндокринология/диетология. @pavelbaranov_md · 31,082 Telegram ranks this channel #66 of 96 here — alongside 95 others — read 6 September 2026
Мудрость Фитнеса (тренер Кабуров) @fitness_mayatnik · 25,555 Telegram ranks this channel #75 of 93 here — alongside 92 others — read 13 September 2026
This channel appears in 7 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 10 November 2026 — this
entry's latest reading, not the date you are reading this.
“Эволюция тренировки” (@evotraining), 8,042 subscribers as measured 10 November 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.