Stat AI
⭐MRRdeals Score · 56/100Stat AI is a sports analysis app that uses AI to provide data-driven decisions and insights.
What this SaaS is
Stat AI provides AI-driven sports analysis for data-driven decisions and insights.
- AI-driven insights
- Sports analysis
- Data-driven decisions
- No active customers— Zero customers reported. Hard to model retention or growth.
- Founded <12mo ago— Less than 12 months of operating history. Retention is unproven.
- Single acquisition channel— All customers come from one acquisition channel. Pull the plug and revenue dies.
Numbers that matter
Tech stack
Score breakdown
How the composite score above splits across seven independent signals. Each axis is graded 0-100. Hover for details.
Payback period, asking price vs category median multiple, and 30-day profit margin.
30-day MRR delta, with a small bonus when historical snapshots confirm a sustained climb.
Revenue per visitor, customer count, plus live-site UX signals (pricing reachability, core pages, copyright freshness).
AI-disruption risk, presence on review platforms (G2, ProductHunt, AppSumo…), penalty when built on no-code rails.
Diversity of marketing channels, Merchant-of-Record status, cofounder count. Solo founders and no-code stacks get docked.
Listing freshness, payment provider trust, business age, customer concentration. Higher score = less risky.
Structured market read across TAM, saturation, 3-year trend, and hype cycle, blended with our category momentum signal.
Market read
- TAMmid
The app targets a broad audience but is limited to sports analysis, indicating a mid-sized market.
- Saturationgrowing
The market for sports analysis apps is growing with increasing interest in data-driven insights, but not yet saturated.
- 3y trendgrowing
The trend for AI applications in sports is growing as more consumers seek personalized insights.
- AI disruptionvulnerable
The reliance on AI for insights makes it vulnerable to competitors who can replicate the technology quickly.
- Hype cycleearly
AI in sports analysis is still in the early stages, with potential for mainstream adoption in the coming years.
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