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Brainrot Clicker πŸ–±οΈ

Brainrot Clicker πŸ–±οΈ

A Roblox experience owned by Springlock Studio.

Clicker & idleENinternet meme cultureincremental/idle mechanicschaotic humor

Description (written by the developer; not a statement by this register)

πŸ”Š Tung tung tung... Tralalero tralala! The ultimate Italian Brainrot Clicker is back β€” now with even more ridiculous sounds and unhinged skins! πŸ§ πŸ’« Unlock new emotions and brainrot vibes: from lirili larila to Bobrito Bandito! πŸ–±οΈ Click your way into madness – each upgrade boosts your power, speed, and insanity. πŸ”₯ Become the Brainrot Clicker God. Leave your friends in the click dust! πŸŽ‰ Share your clicks, unlock every chaotic skin, and let Brr Brr Patapin take over the world. πŸ“ˆ Clicker. Brainrot. Mayhem. Simulator. Welcome to the madness.

Last updated by the developer 10 Nov 2025, 12:02 UTC.

0
playing (measured 11 Aug 2026, 07:49 UTC)
159,147
lifetime visits
67%
liked (82 πŸ‘ / 40 πŸ‘Ž)
200
favourites (1.3 per 1k visits)
21 November 2024
created (per Roblox)

Play on Roblox β†’

Live players over time

Growth

Growth history is still building. We hold one measurement for this entry. A trend needs at least two, taken days apart β€” so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log β€” every players count we have recorded
Measured (UTC)PlayersChange
11 Aug 2026, 07:490first reading

Concurrent players at each of our measurements (insert-on-change).

Monetization β€” game passes

Clicker God
175 R$
Lazy Clicker
150 R$
Auto Clicker
100 R$

Game passes for sale and their prices, measured from the Roblox passes API. Developer products bought inside the game aren’t publicly listable.

Badge funnel

Welcome Β· welcome94,378 Β· 0.00% win
Italien Β· other27,498 Β· 0.00% win

How many players have ever earned each badge β€” a proxy for how far players get before they stop. Steep drop-offs mark where a game loses people. Win rate is the past-day share of players who earned it; categories are assigned by a language model from each badge’s own name and description.