8 measurements spanning 22 days, net -14. 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 1,473–1,491 and does not start at zero.
Measurement log — every subscribers count we have recorded
Measured (UTC)
Subscribers
Change
30 Aug 2026, 01:46
1,475
-2
26 Aug 2026, 15:12
1,477
+1
23 Aug 2026, 23:29
1,476
-4
20 Aug 2026, 15:34
1,480
-6
14 Aug 2026, 09:15
1,486
+1
11 Aug 2026, 11:32
1,485
-4
7 Aug 2026, 21:47
1,489
no change
7 Aug 2026, 21:38
1,489
first reading
Engagement
5 posts held, back to 8 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 1 pageof Telegram’s post history, 20 posts per page.
ERR · 30 days
16.3%
avg views ÷ 1,475 subscribers
Avg views / post
241
1 post measured
Reaction rate
7.05%
reactions ÷ views · ER floor
Posts in window
1
of 5 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 7 August 2026
Posts held
5 (8 July 2026 – 7 August 2026)
Views total
241
Reactions total
17
Forwards / comments
not exposed by the public surface — not measured, not estimated
Readings taken
7 Aug 2026, 21:47 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.
Reaction mix
102 reactions across 5 posts, in 10 distinct kinds. The most used accounts for 34.3% of them.
Every reaction kind recorded on the sample, most used first
Reaction
Count
Share
Share, drawn
custom 5350702035819833989
35
34.3%
custom 5256047523620995497
25
24.5%
custom 5409125874651903587
9
8.82%
custom 5326037211164978005
8
7.84%
custom 5370869711888194012
7
6.86%
custom 5258203794772085854
6
5.88%
custom 5467642076755685102
6
5.88%
custom 5310184100328385996
4
3.92%
custom 5357593469760059395
1
0.98%
custom 5361597788029204378
1
0.98%
Custom emoji. Every row above is a Telegram custom emoji, which the public preview renders as an element carrying only a numeric id — no character, and no image we can reach. The id is printed as-is rather than substituted with a look-alike glyph, because a stand-in would be our invention showing where a measurement should be. The counts beside them areTelegram’s.
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 5 of the 5 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 102reactions in total: the kind of figure the paragraph above means by “a reaction total printed elsewhere on the page”.
Measured over the 5 most recent posts we hold, published 8 July 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.
Одни проекты необходимо покупать, другие работают по подписке, а третьи привлекают бесплатным входом, но получают доход за счет микротранзакций. За каждым из этих форматов стоит экономика со своими плюсами и рисками.
Запускаем цикл постов про 3 основные модели монетизации игр:
• Часть 1. Платная модель
• Часть 2. Free-to-Play
• Часть 3. Подписочная модель
Начинаем с платной модели. Разберем ее плюсы и минусы, а так…
Один из главных вызовов при проработке NPC – сделать их поведение живым и убедительным.
Разбираем 4 основных архитектурных паттерна, на которых строятся мозги неписей 🧠
В комментарии закинули полезные ресурсы для тех, кто хочет погрузиться в тему глубже.
Инкрементальные игры – жанр, который со стороны кажется абсурдом: монотонно кликать мышкой ради добычи ресурсов, а затем покупать улучшения, которые делают клики за вас. Тем не менее, это один из самых аддиктивных феноменов в геймдизайне.
Разбираемся, как устроены инкременталки и почему они так затягивают😵💫
#игры_dev
Один вовремя найденный инструмент способен сэкономить десятки часов рутины 👨💻
Делитесь в комментариях ресурсами, тулзами или плагинами, которые облегчили вам работу над проектами.
Направление не имеет значения, но уточняйте, чем именно они полезны.
Задачи, с которыми неожиданно хорошо справилась нейронка, тоже приветствуются 🛠
🎮🎮🎮🎮🎮🎮
Мрачные космические приключения, средневековые стратегии и олдскульные шутеры – собрали подборку игр, к которым стоит присмотреться на летней распродаже.
Ссылки на проекты оставили в комментариях 🎮
#игры_dev
Showing the 5 most recent of 5 posts we hold for @kefirdevscool. 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.
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 30 August 2026 — this
entry's latest reading, not the date you are reading this.
“KEFIR DEV'S COOL” (@kefirdevscool), 1,475 subscribers as measured 30 August 2026. Telegram Register, tgregister.com/channel/kefirdevscool.
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.
