Channel
@baas_pro
On this record: Growth · Engagement · Reactions · Posts · Cite this entry
44subscribers
+1 since we began measuring on 7 August 2026
Risers and fallers across the register · movement among entries of Under 1,000.
| Telegram ID | -1002142708989 |
|---|---|
| Type | Channel |
| Username | @baas_pro |
| Created | Between 1 November 2023 and 31 May 2024— estimated from Telegram’s id allocation, not measured. How this range is calculated. |
| First recorded | 10 August 2026 |
| Last confirmed live | 24 August 2026 |
| Measurements held | 3 |
| Confirmed unchanged | 1 time, most recently 24 August 2026 |
| On Telegram | t.me/baas_pro |
| Measured (UTC) | Subscribers | Change |
|---|---|---|
| 24 Aug 2026, 06:37 | 44 | +1 |
| 10 Aug 2026, 17:01 | 43 | no change |
| 7 Aug 2026, 20:20 | 43 | first reading |
18 posts held, back to 8 June 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 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 2 measured posts that carry a reaction reading, and over those same posts' views.
| Window | Rolling 30 days · latest post in window 6 August 2026 |
|---|---|
| Posts held | 18 (8 June 2026 – 6 August 2026) |
| Views total | 31 |
| Reactions total | 1 |
| Forwards / comments | not exposed by the public surface — not measured, not estimated |
| Readings taken | 10 Aug 2026, 17:01 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.
22 reactions across 13 posts, in 8 distinct kinds. The most used accounts for 36.4% of them.
| Reaction | Count | Share | Share, drawn |
|---|---|---|---|
| 💯 | 8 | 36.4% | |
| 🔥 | 5 | 22.7% | |
| 👍 | 4 | 18.2% | |
| ✍ | 1 | 4.55% | |
| ❤ | 1 | 4.55% | |
| 🏆 | 1 | 4.55% | |
| 👌 | 1 | 4.55% | |
| 👏 | 1 | 4.55% |
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 13 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 22reactions 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 8 June 2026 to 6 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.
No match required A quiet day in the sports calendar does not mean a quiet day for attention. Elections, transfers, crypto, award shows, product launches and major news events already attract live interest. Prediction markets give operators a way to turn that attention into betting activity between matches and seasons. The opportunity is clear: more relevant events, more reasons to return, and less dependence on t…
✍1
Retention is not a department It is tempting to put retention somewhere inside CRM and pretend the job is done. Send the offer. Launch the bonus. Push the campaign. Wait for the player to return. The problem is that players do not leave because one message was missing. They leave when too many small things stop making sense at the same time: the lobby shows nothing relevant, the next step is unclear, withdrawals f…
One API, many trade-offs Game aggregation is usually sold as the clean route: one connection, many studios, faster launch, less pressure on the tech team. For many operators, that is exactly the right start. A new casino needs content quickly, and building separate integrations one by one can turn the launch plan into a beautiful spreadsheet of delays. But the integration model quietly shapes much more than speed.…
💯1
Page three problem A casino lobby can have thousands of titles and still make the user feel like there is nothing to play. That sounds ridiculous until you open a crowded lobby yourself. Slots, live games, crash titles, jackpots, “new”, “hot”, “top”, branded collections, seasonal banners, provider rows, promo rows, and somewhere inside that maze — the one game that actually fits the player. A large catalog solves …
💯1
Betting moves into the chat A player does not always want to open an app, search the lobby, filter markets and learn another interface just to place one bet. Sometimes the natural entry point is already open. Messaging apps are becoming more than support channels. For betting products, they can turn into a faster path from intent to action: asking for a match, checking odds, getting a relevant market, building a b…
🔥1
The second action Tournament traffic should be measured beyond FTD. A first deposit only proves that the event was strong enough to create urgency. The useful read starts after that: settled bet, return session, second stake, completed withdrawal, repeat deposit, CRM response, movement into another relevant event or market. Those signals should not be mixed into one “new users” number. A player who deposited, plac…
👍2
The empty full sportsbook A sportsbook can have thousands of events and still feel irrelevant in the wrong market. Coverage alone does not mean the product is useful. Players usually look for what matters to them first: local leagues, familiar teams, regional tournaments, popular formats, niche sports that actually have demand. If those options are buried under a global structure, the product may look rich in a dem…
👌1
Built for thumbs Mobile-first markets have a simple test: can a user open the product, understand the first screen, deposit with a familiar method and make the first action before attention disappears? The answer depends on small product decisions. What sits above the fold. How many fields registration asks for. Whether payment options look local. Whether a promo explains itself in one glance. Whether the sportsboo…
🏆1
Bonus rules are getting product-specific A bonus is no longer just a CRM idea with a nice headline. In regulated markets, the way an offer is built matters as much as the offer itself: what product the player uses, what reward they receive, how wagering works, what the terms say, and whether the system can track all of it clearly after launch. The UK is a good example of where this has already moved. Since January…
💯2🔥1
The almost-bettor Major tournaments bring a strange kind of traffic: people who are interested enough to open a sportsbook, but not interested enough to study it. They came for one match, not for a product tour. That user does not want to explore market depth, compare formats or understand the full logic behind the betslip. They need to find the match, understand the offer, deposit, place a bet and feel that nothi…
💯1
Back office decides more than UX Players see the interface. Teams live in the back office. That is where a product either stays manageable or slowly turns into manual work. Limits, player segments, bonus settings, risk notes, reports, permissions, payment statuses, support context — all of it affects how fast the team can react after launch. A weak back office does not always break the user experience directly. It…
AI won’t guess you AI search is changing what visibility means for B2B brands. A company can have a decent website, a few blog posts and still be easy to miss if the outside signal is weak. AI systems do not rely only on what a brand says about itself. They look for confirmation around it: third-party mentions, structured pages, reviews, compliance signals, clear product descriptions and consistent positioning acro…
Showing the 12 most recent of 18 posts we hold for @baas_pro. 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.
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 24 August 2026 — this entry's latest reading, not the date you are reading this.
“BAAS” (@baas_pro), 44 subscribers as measured 24 August 2026. Telegram Register, tgregister.com/channel/baas_pro.
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.