How much does Quick Random Team Selector make per month?

Based on our ML-calibrated revenue forecast, Quick Random Team Selector earns approximately $290/mo. This is a US-storefront-equivalent estimate; global revenue can be several times larger for internationally-distributed apps. See the methodology page for the full formula and confidence bands.

What apps are like Quick Random Team Selector?

Browse the full Sports category catalog to find similar apps with revenue, build cost, audience and tech stack data. Each /p/{slug} page also shows a Compare side-by-side widget with three peer apps from the same niche.

Who makes Quick Random Team Selector?

Quick Random Team Selector is published by J. G. da Silva on the Google Play Store. See the full publisher portfolio (other apps by the same developer) via the More by developer block on the product page above.

What is Quick Random Team Selector's BU Score?

Quick Random Team Selector has a BU Score of 48/100 (Emerging). The score combines App Store rating, ratings count, monetization model and revenue signals calibrated against founder-verified MRR anchors. See the BU Score formula.

Quick Random Team Selector

Quality Score

Emerging

Quick Random Team Selector

Name: Quick Random Team Selector — app revenue, audience, build cost & risk profile
Creator: bumetric
License: https://creativecommons.org/licenses/by/4.0/
Keywords: Quick Random Team Selector revenue, Quick Random Team Selector app analytics, mobile app revenue estimate, Sports revenue, Android app revenue

by J. G. da Silva

Medium confidence

3.7 ✍️ Editor

✍️ bumetric analysis

“

Quick Random Team Selector is an Android app from J. G. da Silva in the Sports category, currently rated 3.7★ across 227 ratings. Initial signal reads as mixed reviews: supporters praise core features while critics cite stability and value gaps.

Quality Score is 48: Emerging (early traction worth watching). For a Sports app, that means early traction worth watching. The full BU Investment Matrix below scores 8 dimensions including monetisation, growth, and operational risk.

Track changes month-over-month in the Performance section below: live snapshot history and revenue forecast included.

💰 Monthly revenue · now vs forecast

● Right now

$500

per month

→

12-mo forecast

$437 – $1575

per month

→

24-mo forecast

$405 – $3644

per month

INDIE tier

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Description hook & conversion structure
Screenshots, ratings, reviews strategy

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Typical impact: +2-5× organic installs

📊 Performance Tracking LIVE

Loading…

idle

Rating

—

Reviews

—

Forecast Revenue / mo

—

Snapshots tracked

since first record

ONE-TIME · BUILD 💰 Estimated build cost

$150K

↳ What it cost to build · not monthly revenue

Likely range $110K – $200K

$25K · MVP floor $100K · indie scale $500K+ · studio build

📈 Slow ROI — current MRR is well below build cost

Synthetic estimate. Inputs: category complexity, file size, screen count, monetization layer, platform reach, age × team-size proxy. Calibrated against 2024-2026 indie-agency rate surveys. Full math + source list on /methodology.

Where the money goes

🧱 MVP baseline (design + 1-store ship)	+$28K
📱 5 unique screens × $4.5K	+$22K
⚙ Sports complexity ×1.90	+$45K
🌐 Cross-platform reach (iOS + Android)	+$52K

Total estimate $150K

👥 Estimated audience size

40K

Lifetime downloads (US-equivalent)

Monthly active

4.0K

Daily active

1.2K

Synthetic estimate from ratings × category benchmarks. Calibrated against 2024-2026 mobile-attribution retention + DAU/MAU reports. Numbers are US-storefront-equivalent — true global audience can be 5-10× larger for international apps. Full math + source list on /methodology.

How we sized it

📲 Sports engagement	~180 installs / rating
🔁 Sports D30 retention	10%
📍 DAU / MAU stickiness	0.30

DAU / MAU 30% sticky

🛠 Estimated tech stack

🤖

Native Android (Kotlin)

Medium confidence · 55%

Also possible

Flutter

Heuristic guess from app bundle size, category, store description signals, and release-date stack era. Bumetric does not disassemble binaries — for binary-level certainty you would need an SDK intelligence tool or the manifest itself. Reasoning chain on the right. Full ruleset on /methodology.

Signals we read

🏷 Category context	Sports
📦 Tiny game bundle	→ Native 2D engine

🔬

How we forecast this revenue

LOW CONFIDENCE

Baseline

$500/mo · ML-estimated from 234 triggers

Growth rate

+6.0% MoM · INDIE tier baseline (compound monthly)

6 months

$426 – $993

12 months

$437 – $1.6K

24 months

$405 – $3.6K

Compound growth at +6.0% MoM (tier baseline for INDIE). Range widens with horizon — typical noise band ±40% at 6mo.. Ranges widen with horizon — distant futures carry more uncertainty.

📊

BU Investment Matrix

Pre-traction · 38/100INDIE TIERlimited signal

Growth Velocity

5.0

Founder Strength

2.8

Product Quality

5.1

Revenue Strength

2.7

Monetization Maturity

1.0

Defensibility

4.5

Market Position

0.0

Operational Safety

9.0

💰 Revenue: Marginal — $200 - $1250/mo · INDIE tier · medium confidence, trajectory unclear.
⭐ Quality: 3.67★ across 227 reviews — below category median.
📍 Market: Not yet charting in any of the 9 monitored markets.
📈 Growth: last update 226d ago — slow cadence.
⚠️ Risk: Low — no material risk signals detected.

🎯 For competitors: Mixed picture. Worth competing if you have a clear UX or pricing edge — otherwise crowded segment.

💵 For acquirers: Estimated asking range 18-32× monthly = $9K-$16K.

Composite of 8 dimensions computed deterministically from public signals — no LLM, every score traces back to a measurable input. Default weights shown; "compete" / "acquire" / "invest" lenses re-weight without re-fetching.

Range:

💰 Forecast Revenue / mo

MODEL

Revenue forecast computed from BU's 234 trigger model on each snapshot. Calibrated against ground-truth from 58 verified-revenue apps.

🔬Forecast Breakdown — Why This Estimate?Top 3 of 3 triggers

Our ML model uses 200+ signals from public data. These are the most influential for this app:

Mature app (11y old)METRIC		+$1,500
Ad-supported / freemiumMETRIC		+$600
Early-stage install base (227 ratings)METRIC		+$400

METRIC = structural app data · REVIEW = mined from user reviews · ✓ VERIFIED = Stripe-verified anchor (TrustMRR)

📥 Estimated Downloads / week

PROXY · ratings × 50/wk —

Industry-rule estimate (Sensor Tower / data.ai): one weekly install ≈ 50 new ratings. Solid points = tracked snapshots · faded line = pre-tracking model backfill.

📈 Reviews Growth

LIVE

Cumulative review count from first BU snapshot. Each point = a tracked update.

⭐ Rating Trend

LIVE

Average rating evolution. Updates with each new review batch.

🗓️ Snapshot Timeline

HISTORY

Each bar shows a tracked update and the metric delta from the previous snapshot.

Profile & Insights

Everything we know — and don't — about this app and its company.

Identification

App name: Quick Random Team Selector
Developer: J. G. da Silva
Bundle ID: com.jotage.sorteiatimes
App Store URL: Open in App Store
Category: Sports
Content rating: Not found
Languages: Not found

Company

Website: Not found
Tagline: Not found
Description: Not found
Founded: Not found
HQ / Address: Not found
Employees: Not found
Logo: Not found

Revenue

Verified revenue / mo: Not found
AI revenue estimate / mo: Not found
AI annual estimate: Not found
ML model estimate / mo: $57/mo
Top-grossing rank: Not found
All-time revenue: Not found
Pricing: Not found

Founder

Founder data not yet collected for this app.

Funding

Funding data not yet collected for this app.

Press & Links

Press & Links data not yet collected for this app.

Contacts & Socials

Contacts & Socials data not yet collected for this app.

📈Ratings growth227 ratings+47% lifetimeShow 3-year history estimate ▾

Tracked (1 weeks) Pre-tracking estimate (36 weeks) · model-based, ±5% noise · anchored to release date and current value

Profile is built from iTunes Lookup + developer site scrape + ML revenue model. Empty fields show "Not found" — additional sources (Crunchbase, X, IndieHackers, Acquire.com) coming.

📝 About this app

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.

App Specs

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🔖 vVaries with device🔄 updated 0d ago📂 Sports💰 Free

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📝 Description

BU Score · Transcendent

Full revenue analysis

Read the article-style breakdown for Quick Random Team Selector: category rank, percentile, growth signal, comparable apps, and how the forecast is calibrated against verified-MRR anchors in this niche.

Read deep-dive →