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[ORCHARDS] Fruit Picking Simulator

[ORCHARDS] Fruit Picking Simulator

A Roblox experience owned by Blue Farm Studios.

SimulatorENorchardrebirthstrading

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

Welcome to Fruit Picking Simulator! Now with your own orchard! Unlock new areas and biomes, sell collected items, level up your gameplay with accessories. - REBIRTHS AND TRADING NOW LIVE! ⭐ Support us with a thumbs up! 🆙 New areas! 📈 Leaderboards 💰 Get an extra 200 coins by joining the group: https://www.roblox.com/groups/5398182/Factor-Interactive Created and produced by Factor Interactive Logo design by Paze Fruit icons by @draxified Other icons by FlatIcon Updates coming soon

Last updated by the developer 1 Jul 2026, 19:47 UTC.

0
playing (measured 11 Aug 2026, 09:17 UTC)
157,634
lifetime visits
71%
liked (580 👍 / 239 👎)
2,371
favourites (15.0 per 1k visits)
23 October 2022
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 We do not publish numbers we have not measured.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
11 Aug 2026, 09:170first reading

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

Monetization — game passes

VIP
249 R$
Starter Pack
175 R$
2X Coins
149 R$
Super Equip
149 R$
2X XP
149 R$
2X Walkspeed
100 R$
Equip +2
99 R$
Sell Anywhere
69 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 Played · welcome128,182 · 0.00% win
Meet the Creator · welcome1,138 · 0.00% win
Fruit Ninja · other174 · 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.