[CHAPTER 4 PART 2] The Evil Revenge
A Roblox experience owned by Leo Hata Plays Studios.
HorrorENhorrorschooljumpscare
Description (written by the developer; not a statement by this register)
It's A Peaceful Day And You're Going To School, And The Day Was Normal Until On The Interval The Student Called "Dudia" Try One More Time To Separate Student Leo From Student Tutiro, And Leo Is Not Tolerating This Anymore, And He Decide To Have A Revenge, But At The Revenge... He Became An Evil Monster And You Need To Send Him Back To Reality, Can You Do It? Update 0.8 Update 0.8 log: Added Chapter 4 Part 2 Added more accessories to kay Added more details in injured Tutiro Added more details in a FBI Agent dead body Changed the name of Chapter 4 Part 1 badge Added Welcome back badge New Poop Texture New Pee Texture Added new scream to Leo.EXE when he hears something (Old scream was banned) Controls: Left Shift - Run F - Unlock Mouse E - Interact Backspace - Drop Item Y - Catch Item C - Crouch [Only Works In Chapter 2+] WARNING: This Game Contains Jumpscare And Loud Scream, Play At Your Own Risk Tags: TER, Evil, Revenge, Horror, Survival, Action, Adventure, EXE, School, Jumpscare
Last updated by the developer 25 Aug 2026, 01:28 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 We do not publish numbers we have not measured.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 |
|---|---|---|
| 25 Aug 2026, 17:01 | 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.