🐰Bullseye Simulator
A Roblox experience owned by Flashy Games.
SimulatorENsimulatorknivespets
Bullseye Simulator is a simulator experience created on 2019-12-18. It has recorded 1,130,781 lifetime visits and 10,924 favorites. The game holds an 86% like percentage. Currently, zero users are playing. The description highlights features such as multi-delete, pet merging, and new zones.
Description (written by the developer; not a statement by this register)
🎯 [UPDATE 2] 🎯 What's new? : - Multi-Delete - Pet Merging - Leaderboards - Better deals with coins purchase - Music in zones - 2 New Zones - 2 New Eggs - 24 New Knifes - 12 New Pets - 12 New Headbands - 10 New Ranks - Many bugs Fixed! Welcome to Bullseye Simulator! A quality game unique in its genre where you upgrade your powerful knives to demolish targets and players in the hope to become the most OVERPOWERED player of all time! HOW TO PLAY: ⚡ Gain fragments by throwing your knife 💪🏻 Use your powerful items to fight other players in the arena 💰 Sell fragments for coins 🎯 Destroy targets and dummies for more coins! ⭐ Unlock new items, pets, and zones 👑 DOMINATE! ROBLOX Premium Perks: 💎 Auto Hatch for all eggs 💎 Auto Clicker for all items
Last updated by the developer 15 Aug 2021, 18:31 UTC.
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 We do not publish numbers we have not measured.
| Measured (UTC) | Players | Change |
|---|---|---|
| 10 Aug 2026, 21:21 | 0 | first reading |
Concurrent players at each of our measurements (insert-on-change).
Monetization — game passes
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
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.