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Ready for the Fight! (Beta 0.8)

Ready for the Fight! (Beta 0.8)

A Roblox experience owned by Animatronic_34s Studios (Roblox Edition)..

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

Welcome to a genetically altered fighting game! This game is made for the purpose of fighting, alliances, betrayals, among other things for the entertainment of the Robloxlian public. Your goal is to be the player with the most kills, playing time, and obtaining the emblems.

Last updated by the developer 23 May 2026, 17:46 UTC.

0
playing (measured 11 Sept 2026, 03:07 UTC)
327
lifetime visits
100%
liked (7 👍 / 0 👎)
2
favourites (6.1 per 1k visits)
8 March 2025
created (per Roblox)

Play on Roblox →

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 — so this will fill in on its own rather than being estimated. We do not publish numbers we have not measured.

Measurement log — every players count we have recorded
Measured (UTC)PlayersChange
11 Sept 2026, 03:070first reading

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

Badge funnel

Welcome to the Fight!!! · welcome36 · 0.00% win
Meet the creator. · welcome13 · 0.00% win
the princess´ s magic wand!!! · collection9 · 0.00% win
You Killed Animatronic_34´s Studios´s account!!! · other4 · 0.00% win
The Secret Lapis Lazuli Image. (TSLLI) · secret4 · 0.00% win
The Rocket Launcher!!! · collection4 · 0.00% win
The Secret Golden Image. (TSGI) · secret3 · 0.00% win
Electro Shock!!! · other3 · 0.00% win
The Secret Emerald Image. (TSEI) · secret3 · 0.00% win
The Secret Copper Image. (TSCI) · secret3 · 0.00% win
You killed Levi´s · progression2 · 0.00% win
You killed "Saul" · progression0 · 0.00% win
You killed "Mr. Marcus" · progression0 · 0.00% win

How many players have ever earned each badge — 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.