Харламов не прошел кастинг на Гену Букина Можно подумать «Что за бред тут написан?». Но это реальный факт. В далеком в 2006 году Харламов ходил по кастингам и даже пробивался на роль Гены Букина. «Я пробовался на Букина в старый сериал, когда был молодым. Меня пробовали [на Гену], но потом поняли, что я слишком молодой, и взяли на [роль] соседа» 😭 Честно говоря, мне кажется если бы Харламов получил эту роль, сериа…

Channel
Канал слез актеров
@cryactors
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
10subscribers
+0 since we began measuring on 8 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
Register entry
| Telegram ID | -1001869581776 |
|---|---|
| Type | Channel |
| Username | @cryactors |
| Description | Сила в слезах наших! Ироничный канал об актерах кино и театра 😭 Рассказать и опубликовать ваши актерские истории можно автору канала @al_morozov |
| Created | 29 November 2022 — measured — dated from the channel’s first post |
| First recorded | 12 August 2026 |
| Last confirmed live | 12 August 2026 |
| Measurements held | 2 |
| On Telegram | t.me/cryactors |
Growth
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 12 Aug 2026, 10:32 | 10 | no change |
| 8 Aug 2026, 20:32 | 10 | first reading |
Engagement
15 posts held, back to 29 November 2022 — 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 pageof Telegram’s post history, 20 posts per page.
- ERR · 30 days
- 190.0%
- avg views ÷ 10 subscribers
- Avg views / post
- 19.0
- 4 posts measured
- Reaction rate
- 4.00%
- reactions ÷ views · ER floor
- Posts in window
- 5
- of 15 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. It is computed over the 1 of 4 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 20 July 2026 |
|---|---|
| Posts held | 15 (29 November 2022 – 20 July 2026) |
| Views total | 76 |
| Reactions total | 2 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 12 Aug 2026, 10:32 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
- 9
- Videos
- 1
- Links
- 3
Lifetime counters from Telegram’s own channel header, read 12 August 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
- 37s
- Average length
- 37s
Measured directly from 1 video 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
15 reactions across 8 posts, in 4 distinct kinds. The most used accounts for 73.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 11 | 73.3% | |
| 🔥 | 2 | 13.3% | |
| 😁 | 1 | 6.67% | |
| 🙈 | 1 | 6.67% |
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 8 of the 15 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 15reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 15 most recent posts we hold, published 29 November 2022 to 20 July 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.
Recent posts
Слезы футбола
Слезы Месси Аргентина 🇦🇷 0 - 1 🇪🇸 Испания Как вам финал? За кого болели?
Канал слез актеров pinned «Тут самые правдивые истории от непризнанных актеров современности 🫶🏻»
Alright, alright, alright… 😭 Факт, который перевернул бы историю кино: Мэттью МакКонахи - первый кандидат на роль Джека Доусона в «Титанике». Я прочитал сценарий и… не понял его. Слишком простая арка: бедный парень, богатая девушка, корабль, лёд, конец. Я искал сложность, излом, но не нашёл. Тогда я принял решение, которое до сих пор обсуждают в Голливуде. Камерон рассказывал, что МакКонахи попросту перестал выход…
🔥2
Скала в слезах 🪨 Американский актер Дуэйн Джонсон, известный своей мужественностью и харизмой, продемонстрировал свою уязвимость на Венецианском кинофестивале. На премьере фильма «Крушащая машина» зрители устроили 15-минутные овации, которые растрогали актера до слез. Ради роли бойца ММА Марка Керра Джонсон сбросил 27 килограммов, что стало настоящим подвигом. Его реакция на овации стала символом того, как важно пр…
❤2
«Я боялся этой сцены как огня, но провал случился не по моей вине» Реальная история со съемочной площадки от Александра: «Этим летом мне предстояло исполнить роль маньяка в одном из наших сериалов. Название пока не пишу, так как сериал в производстве. В начале по сценарию предполагалось показывать просто озабоченного мужика, но вдруг продюсер и режиссёр решают, что нужно всё-таки снять одну сцену насилия. Насилия! Я…
❤3
Слёзы «должны идти не из глаз, а из сердца» Александр Петров объяснял, что плакал во время съёмок фильма «Лёд-2» не по прямому указанию режиссёра, а из-за эмоциональной силы сюжета. Он подчёркивал, что слёзы «должны идти не из глаз, а из сердца». Актёр отмечал, что актёрский организм работает особым образом: слёзы либо появляются, либо нет - специально «наработать» их невозможно. При этом режиссёр Жора Крыжовников …
❤1
Мерил Стрип оказалась «недостаточно красивой» Удивительно, но в 1975 году итальянский продюсер Дино Де Лаурентис планировал снимать ремейк фильма 1933 года о гигантской горилле. Его сын приметил Мерил Стрип, тогда еще вполне начинающую актрису, в театральной пьесе и привел на кинопробы к отцу. Увидев ее, продюсер обратился к ребенку с вопросом на итальянском языке, не думая, что девушка их понимает: «Зачем ты притащ…
❤2🙈1
ДиКаприо тоже плачет! Помните фильм Квентина Тарантино «Однажды в Голливуде»? Там герой Ди Каприо плачет после того, как маленькая девочка говорит ему: «Ты — самый крутой актёр, которого я видела в жизни». 😭 Делитесь в комментариях, какие комплименты вы получали за свою актерскую игру? #кино #актеры #слезы #дикаприо
❤1
Все плачут и звезды не исключение 👇 Данила Козловский плакал, когда читал сценарий фильма «Легенда №17» о Валерии Харламове. Он признался в этом в интервью, отметив, что не считает себя сентиментальным человеком, и такое с ним случилось впервые. По словам актёра, история в сценарии была очень человечной и пронзительной. Его глубоко тронула линия становления героя, его путь к успеху, а также сложные отношения между …
❤2
Тут самые правдивые истории от непризнанных актеров современности 🫶🏻
😁1
Showing the 12 most recent of 15 posts we hold for @cryactors. 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.
Citation-graph rank
Citation-graph rank — 1,042,554 of 1,480,688entries in the measured graph. A weighted position computed from the forward and mention edges below — republished posts weigh more than named mentions — and recomputed periodically, over the whole graph. Published only as this ordinal position, never as a score: a position is a fact, and a score printed beside one channel’s name would read as a verdict this register does not make. The two counts beneath stay separate for the same reason mentions are never summed with forwards anywhere else on this page — a named-by count costs nothing to manufacture. The top 100 by this measure, or how it is computed.
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
Names
Channels on the register whose handles appear in this channel's posts.
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.
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 12 August 2026 — this entry's latest reading, not the date you are reading this.
“Канал слез актеров” (@cryactors), 10 subscribers as measured 12 August 2026. Telegram Register, tgregister.com/channel/cryactors.
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.