![[DISCONTINUED] Undertale AU Monster Battles](https://tr.rbxcdn.com/180DAY-f5ab0efc05a435f2c6d892b066e9f5b6/256/256/Image/Png/noFilter)
[DISCONTINUED] Undertale AU Monster Battles
A Roblox experience owned by Bikuta 'n Foxer Studios.
Fighting & PvPENUndertaleAUfighting
[DISCONTINUED] Undertale AU Monster Battles is a fighting-pvp experience created on 2020-05-30. The game has recorded 1,465,847 lifetime visits and 9,994 favorites. Currently, zero users are playing. The experience holds a 72% like percentage. Players engage in character-based combat within the Undertale universe.
Description (written by the developer; not a statement by this register)
[WARNING! THIS GAME IS DISCONTINUED! ANYTHING YOU DO AT THIS GAME IS AT YOUR OWN RISK! GAMEPASSES AND SUCH WILL NOT BE REFUNDED!] For more information, join the game and read the text signs at the lobby This is a undertale AUs fight game, where you get Level by afk farming or killing players and get stronger characters for help you be better when fighting players, you can choose your favorite undertale characters too! for example, Sans, Papyrus and more! Credits to Toby and Temmie for creating Undertale
Last updated by the developer 5 Jan 2026, 17:47 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 We do not publish numbers we have not measured.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, 22:21 | 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.