Posted without readable text
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Channel
@freeslotpodcast
On this record: Growth · Engagement · What this channel posts · Reactions · Posts · Citations · Cite this entry
1,626subscribers
+25 since we began measuring on 6 August 2026
Risers and fallers across the register · movement among entries of 1,000–3,162.
| Telegram ID | -1002046216529 |
|---|---|
| Type | Channel |
| Username | @freeslotpodcast |
| Created | Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 6 August 2026 |
| Last confirmed live | 15 August 2026 |
| Measurements held | 6 |
| Confirmed unchanged | 1 time, most recently 15 August 2026 |
| On Telegram | t.me/freeslotpodcast |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 15 Aug 2026, 16:27 | 1,626 | +19 |
| 12 Aug 2026, 01:33 | 1,607 | -2 |
| 9 Aug 2026, 08:06 | 1,609 | +7 |
| 6 Aug 2026, 12:11 | 1,602 | +1 |
| 6 Aug 2026, 07:32 | 1,601 | no change |
| 6 Aug 2026, 03:18 | 1,601 | first reading |
17 posts held, back to 28 May 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 pagesof Telegram’s post history, 20 posts per page.
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.
| Window | Rolling 30 days · latest post in window 7 August 2026 |
|---|---|
| Posts held | 17 (28 May 2026 – 7 August 2026) |
| Views total | 1,700 |
| Reactions total | 40 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 7 Aug 2026, 17:57 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.
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.
175 reactions across 14 posts, in 10 distinct kinds. The most used accounts for 38.3% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| ❤ | 67 | 38.3% | |
| 🔥 | 45 | 25.7% | |
| 👍 | 28 | 16.0% | |
| 😱 | 11 | 6.29% | |
| 🤝 | 9 | 5.14% | |
| 🤡 | 6 | 3.43% | |
| ⚡ | 3 | 1.71% | |
| 💘 | 3 | 1.71% | |
| 👀 | 2 | 1.14% | |
| 💯 | 1 | 0.571% |
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 16 of the 17 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 176reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 17 most recent posts we hold, published 28 May 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.
Posted without readable text
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Почему некоторым коллегам путь по карьерному треку даётся проще? Кажется, мы нашли формулу успеха в любом деле 🤓 Лера, наш технический писатель, прочитала «Гениев и аутсайдеров» Малкольма Гладвелла и собрала статью об успехе, где рассказала: ✨Что больше всего влияет на практике: талант, удача, среда или всё сразу; ✨Что такое эффект накопленного преимущества; ✨Как работает знаменитое правило 10 000 часов; ✨Как связан…
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🏃♀️Коллеги, мы не договорили! Мы тут поняли, что показали не всё, что отсняли на South Hub — исправляемся. Предлагаем вам послушать тех, кто согласился ответить на наши каверзные вопросы. МТС, Вконтакте, Т-Банк, X5 Tech, Авито — кого узнали и с кем согласны? Пишите внизу ⬇️ #tl
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Коллеги возвращаются с уже легендарной Avito.Tech.Conf 🚀 По-классике, собираемся нашим огромным комьюнити руководителей, тим- и техлидов и всех тех, кто управляет сложным в IT. 🔸Будут и классика формата — доклады, вокршопы, мастермайнды. Здесь совсем скоро вернемся с деталями. И максимально продуманные зоны, чтобы переключиться, узнать новое и пообщаться. Подробнее про каждую рассказали здесь. И, самое главное, ко…
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Мы так часто и много говорим про процесс онбординга сотрудников, тем временем более болезненный оффбординг (да, такое слово существует) всегда остаётся в стороне 😭 Но не в нашем новом выпуске! В этот раз собрались все втроём, чтобы честно и открыто поговорить про процесс увольнения с обеих сторон, а также обсудить: ✨ Что команда знает об уходе человека и что команда на самом деле знает об уходе человека; ✨ Какие ри…
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Сейчас будет больно … Какое у вас было самое неприятное увольнение в роли тимлида? #tl
Несём вам выпуск, который вы точно посмотрите🔥 Новый эпизод — честный разговор в кулуарах недавнего SouthHub в Сочи. Саша Афёнов и Саша Прокшина собрали топов из Cloud.ru, HeadHunter, Авито, Альфа-Банка, Звука и других IT. Без розовых очков и аккуратных выражений поговорили о: — миссиях и ошибках на вершине карьеры; — бюджетах на AI; — роли CTO в «кровавом энтерпрайзе» и роли продактов; — культуре в командах. Слуш…
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«Пора перфа!» Эту фразу знает каждый в Авито — и она про performance review, который проходит два раза в год. Алина Бабенко, тимлид команды Auction Efficiency, рассказала, как устроен этот: что происходит до ревью, как собирается обратная связь, зачем нужны калибровки и почему итоговая оценка — это не только про грейд, но и про доверие к системе. А как прочитаете, возвращайтесь в комментарии и рассказывайте, как оц…
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🏃♀️ Кажется, без Леонида Каневского теперь причину багов не разгадать! Новый LSR превратился в настоящее расследование — на этот раз под прицелом endpoint аватарок и его внезапная любовь к ошибке 404 😭 Подозреваемых много, зацепок — еще больше. Удастся ли довести дело до конца? Смотрим вместе по ссылкам: 📱 YouTube 📱 ВК Видео 📱 Rutube А в комментариях делимся любимыми мемами с отцом русского тру-крайма ⬇️ #tl
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Low-code personas уже среди нас И это новая реальность, которая меняет многие процессы в продуктах и командах. Если раньше написание кода было чисто инженерским хард-скиллом, то теперь ИИ сделал этот навык обязательным для всех профессий. Есть уже в ваших командах low-code personas? Как они поменяли процесс? ⬇️ А весь выпуск про AI, производительность и здравый смысл можно посмотреть тут. #tl
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Какой бы дорогой порой не была ошибка, если делаешь её сам — учиться на чужих кейсах гораздо сложнее 🧑💻 Но, раскроем вам секрет — никакого индивидуального опыта не существует 👀 Все мы совершаем одни и те же ошибки. И самые частые мы собрали в новом выпуске! Например, факапы при донесении обратной связи и способы всё исправить. Слушаем и смотрит по ссылкам: 📱 YouTube 📱 VK ⚡️ Яндекс Музыка #tl
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👀 Что эффективнее для лида: учиться на своих или чужих ошибках?
Showing the 12 most recent of 17 posts we hold for @freeslotpodcast. 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 — 39,490 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.
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.
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.
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 15 August 2026 — this entry's latest reading, not the date you are reading this.
“Свободный слот” (@freeslotpodcast), 1,626 subscribers as measured 15 August 2026. Telegram Register, tgregister.com/channel/freeslotpodcast.
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.