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Quick Random Team Selector icon

How much does Quick Random Team Selector earn?

Android app from J. G. da Silva · Sports

ML forecast ★ 3.7 · 227 Free

~290/mo

ML revenue forecast. Calibrated against 24961 apps in this category.

Confidence band
±15%
High — many comparable apps with verified data

At a glance

What the app looks like

Live screenshots from the Play Store, captured by our snapshot worker. Tap any image to enlarge.

Quick Random Team Selector screenshot 1 Quick Random Team Selector screenshot 2 Quick Random Team Selector screenshot 3 Quick Random Team Selector screenshot 4

Quick Random Team Selector's revenue trajectory

Forecast revenue from snapshot history. Last 1 months.

Where Quick Random Team Selector sits in Sports

Revenue distribution of 24961 comparable apps. Quick Random Team Selector highlighted.

Quick Random Team Selector vs comparable apps

Revenue trajectory side-by-side. Bold = Quick Random Team Selector, ghosted = peers.

App spec

Version
Varies with device
Last update
Dec 13, 2025
Launched
Sep 18, 2014
Price
Free
Monetization
Free

What Quick Random Team Selector actually does (from store listing)

Randomly pick players and generate teams at the touch of the screen. Type the number of players and how many players on a team. The app will calculate the number of teams with color coding. The players will touch the phone screen and it will randomly reveal the color of the team that the player has been randomly selected for. Support for Android Wear OS.

Comparable Android apps

The five apps in Sports with the closest revenue to Quick Random Team Selector. Click any to see its detail page.

AppRevenueRatingRatings
Toronto Baseball Jays Edition icon Toronto Baseball Jays Edition 290 ★ 4.8 185
Kinesis Gym icon Kinesis Gym 290 — 0
Cliff Climbers icon Cliff Climbers 290 — 0
VfB Magazine icon VfB Magazine 290 — 0
Atlanta Baseball icon Atlanta Baseball 291 ★ 4.3 161
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How we calculated this

Each forecast combines App Store rating, ratings count, monetisation model, pricing tier, IAP signals and ad-supported flag. The base estimate is then multiplied by a per-category scaling factor learned from apps with founder-verified MRR. Every number on this page comes from public APIs and bumetric's own snapshot history.

Full methodology covers input variables, accuracy bands per category and how we treat apps without comparable anchors. See also the live data on Quick Random Team Selector's tracker page for current rating, reviews and snapshot timeline.

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