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Cart Ride To Lunchly!

A Roblox experience owned by Wafflingz.

OtherENendurancecart rideno obstacles

Description (written by the developer; not a statement by this register)

Game Title : Cart Ride To Lunchly! Embark on an epic journey of endurance and patience as you ride the cart to the legendary Lunchly! In this calm yet challenging adventure, you’ll need persistence and focus to make it to the finish. No obstacles, no racing—just you, your cart, and the ride ahead. Can you make it all the way? Tags : Patience, Lunchy, Ksi, Prime, Freakbob, KSI, Paul, PRIME, Ride, CartRide, Long Ride, Brainrot, Mr beast, DanTDM, dantdm, mrbeast, feastables, Thick of it, Trippie redd, NLE, Cold.

Last updated by the developer 19 Nov 2024, 15:15 UTC.

0
playing (measured 18 Aug 2026, 18:16 UTC)
2,674
lifetime visits
24%
liked (6 👍 / 19 👎)
14
favourites (5.2 per 1k visits)
7 October 2024
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 We do not publish numbers we have not measured.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
18 Aug 2026, 18:160first reading

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

Monetization — game passes

Skip To Finish (INSANELY OP!!!!)
799 R$
Hyper Lazer Gun
300 R$
KILL ALL
250 R$
Magic Carpet (OP!!!)
249 R$
Speed Coil
89 R$
Gravity Coil
89 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

Welcome! · welcome2,213 · 0.00% win
Completed!! · progression42 · 0.00% win
Met The Creator! · welcome16 · 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.