PropTrack Verified

Subscription sports prop research bot with public accuracy ledger for underserved leagues (WNBA, NCAA, tennis), charging handicappers $19/mo to build trust through transparent performance tracking. · Sports Betting Analytics

DEAD SLOW · CAUTIOUS

5.6 ShipScore / 10

Strongest: time-freedom automation. Weakest: entry — ledger wedge already copied by many.

Condition: Only build if the WNBA/NCAA/tennis prop data edge is real and measurable — a 60+ day public ledger beating market lines on leagues Steamnote and PropGPT ignore, sourced from a licensed feed you can afford at $19/mo pricing.

Part I — The Verdict what the instruments read

01 — The ShipScore breakdown

Control

C5 — depends on odds/player-prop data feeds and betting-ad platform rules

Entry barriers

E3 — Steamnote, TrueSharp, Olympus Bets all shipping the same public-ledger hook

Need

N6 — PropGPT $76k MRR proves spend, but it's eroding -11%/mo

Time-freedom

T8 — automated bot plus $19 self-serve subscription, no per-client labor

Scale

S6 — global digital, but niche leagues and betting-regulated geographies cap reach

What the five commandments measure

C — Control	Do you own the customer, or does a gatekeeper stand between you and revenue?
E — Entry	How hard is this to copy once it works? A rival's existence isn't the question — the durability of their advantage is.
N — Need	Is demand proven with money rather than vibes?
T — Time	Can income detach from your hours, or did you buy yourself a job?
S — Scale	How far does it reach without linear cost?

Scored on the evidence below, against CENTS as we've adapted it plus a Buffett-style moat reading of every rival — the same referee for every idea, including the ones we generate ourselves. The verdict follows the arithmetic: we never relabel a score to make it read better, and the weakest commandment is always named. The exact rubric stays in-house so the scale can't be written for.

02 — The pace test — $1M/yr

At $19/mo (assumed category price), you need 4,386 subscribers for a $1M/yr pace.

Nearest tracked rivals on that curve:

PropGPT: AI Props Analysis

$76k 91%

↓↓ moat eroding · -11%/moX · quiet

DunkMax

$4k 5%

A rival's moat trend is its verified-revenue trajectory, not its rating — a 4.9★ incumbent with eroding revenue is a different opponent than a widening one. How it's computed →

Part II — The Evidence the receipts, good and bad

03 — Rival scan — corpus tracks 2 similar

PropGPT: AI Props Analysis	verified MRR $76k · revenue trend: eroding (-11%/mo) · X-chatter: low (trustmrr)	↓↓ moat eroding · -11%/mo X · quiet
DunkMax	verified MRR $4k (trustmrr)

PropGPT: AI Props Analysis — $76k verified MRR and brand recognition; even eroding, it owns the AI-props category default.
Steamnote — Launching with the exact same pitch — public auditable ledger, ROI/hit rate upfront, subscription coming.
TrueSharp — Verified auto-tracked picks marketplace; network effects from many tipsters beat one solo bot.

04 — Demand evidence

PropGPT verified $76k MRR — real, sizeable paid spend in AI prop analysis.
DunkMax at $4k MRR shows smaller niche entrants can also monetize.
X complaints confirm the pain: tipsters hide losses, cherry-pick, few independently verified.
Negative signal: PropGPT eroding -11%/mo; zero Reddit signal; launch chatter mostly self-promo under 100 views.

05 — Risks

The 'public accuracy ledger' wedge is already claimed by at least three concurrent launches.
Honest tracking is a liability — one bad month of published ROI kills conversions.
PropGPT's -11%/mo erosion may mean the whole AI-props subscription category is churning out.
Underserved leagues have thinner, pricier, less reliable data — WNBA/NCAA prop coverage is spotty.

06 — Kill switches — what kills this with one decision

Sports data licensor (player-prop feeds for NCAA/WNBA/tennis) — Price hike or terms change makes $19/mo unit economics impossible overnight.
Sportsbook anti-scraping / odds API terms — Blocking line access removes the core comparison signal the ledger depends on.
App store and ad-platform gambling policies — Betting-adjacent classification bans paid acquisition and mobile distribution simultaneously.

Part III — The Plan if you insist on proceeding

07 — What this scan can't tell you

Cannot tell whether you actually have a predictive edge in WNBA/NCAA/tennis props.
Cannot see PropGPT's churn cause — pricing, accuracy, or category-wide fatigue.
Cannot verify whether Steamnote/TrueSharp have shipped paying subscribers or are vapor.

Scores judge the market and business model — not your ability to execute. Verified MRR = independently tracked revenue; reviews/upvotes = platform-reported. Judged 2026-08-09.

08 — The wedge & the next step

Own the leagues the incumbents skip: be the only auditable prop engine with deep WNBA, women's tennis and mid-major NCAA coverage, where books post softer lines and no tracked rival competes.

Cheapest next step: Publish 30 days of timestamped WNBA/tennis prop calls free on X with closing-line value shown, and count how many DM asking for paid access before writing product code.

Not quite it? Spin the model

Business-model variations of this idea, engineered to beat 5.6 — different vertical, audience, model, or wedge. Same harsh scale. Pro feature.

One evidence-backed gap a day, free

Close — but conditional. Every morning the engine files one mined gap, scored on the same harsh scale as this one. Free at 7am AEST, unedited.

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Monitor this idea

Weekly re-scan against the live corpus. If the market moves this ShipScore by a point, or flips the verdict, you hear about it. Free while we're small.