Neo Soccer League
A Roblox experience owned by ANG - Neo Soccer League.
SportsENanimesoccerstats-upgrade
Neo Soccer League is a sports experience created on 2021-10-14. It has accumulated 72,730,024 lifetime visits and 142,846 favorites. The game holds an 86% like percentage. Currently, 7 users are playing. The description identifies it as an anime football game featuring character upgrades and leaderboards.
Description (written by the developer; not a statement by this register)
"The one who'll become the greatest striker in the world... is me!" Keep in mind this is a demo game, bugs may occur! Leaderboards and gamepasses will not be reset! [ INFO ] An anime football / soccer game. Play matches with other players and upgrade your character's stats, skills and flow state. Crush your opponents with your abilities as you rank up to become the best striker in the world. Triumph over everyone else as you become the true egoist. [ CREDITS ] Robuyasu - Project Director / Owner, Programmer, Game Designer, UI Designer, Sound Designer X_rnas - Lead Builder, 3D Modeler, Animator Orebloxx - Thumbnail Artist, UI Designer, Animator scronge_mCduk - Community Manager, Game Designer
Last updated by the developer 18 Mar 2026, 03:17 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 We do not publish numbers we have not measured.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, 15:33 | 11 | 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.