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Super Fat Simulator 2

Super Fat Simulator 2

A Roblox experience owned by Grinch Studios™.

Super Fat Simulator 2 is a Roblox experience created on December 18, 2017. The game has accumulated 25,616,070 lifetime visits and 158,605 favorites. Currently, zero users are playing. The title holds a 75% like percentage. No specific genre classification is recorded in the available data.

Last updated by the developer 4 Oct 2018, 20:34 UTC.

0
playing (measured 10 Aug 2026, 15:34 UTC)
25,616,070
lifetime visits
75%
liked (29,128 👍 / 9,893 👎)
158,597
favourites (6.2 per 1k visits)
18 December 2017
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 We do not publish numbers we have not measured.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
10 Aug 2026, 15:340first reading

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

Monetization — game passes

x2 Fatness
145 R$
Giant Whopper
65 R$
VIP Access
45 R$
Milkshake Machine Access
35 R$
Popcorn Machine Access
25 R$

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

You got Hotdog! · collection7,310,743 · 0.00% win
You got Chocolate Milk! · collection4,258,375 · 0.00% win
You got Pizza! · other2,946,270 · 0.00% win
You got Taco! · collection2,161,358 · 53.3% win
You got Ice Cream! · other1,673,306 · 0.00% win
You got Burrito! · collection1,343,374 · 0.00% win
You got Big Whopper! · collection736,652 · 0.00% win
You entered Fatty Land! · welcome374,132 · 0.00% win
You caught the Flying Taco! · collection3 · 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.