Teams and front offices
Player evaluation, game-day preparation, role change monitoring, and no-lookahead replay validation.
Positioning
Built for buyers who need an analytics layer, not a stat table.
The strongest fit is a modular analytics API and reporting layer that can plug into existing dashboards, internal systems, scheduled feeds, and workflow tools.
Buyer paths
One engine. Multiple commercial surfaces.
Sportsbooks and DFS
Projection feeds, confidence and volatility, context-aware risk surfaces, and prop research support.
Fantasy, media, and builders
Auction values, player comps, archetype stories, and licensed research or content bundles.
What DelQuant is
A platform, not a stat table.
Player intelligence
Multi-season projections, context-aware variance, archetype classification, and historical comparables.
Decision surfaces
Outputs designed for fantasy drafts, prop research, player evaluation, roster construction, and media analysis.
Validation
No-lookahead replay, calibration logic, and a model stack built to be graded against actual outcomes.
What you can buy
DelQuant can be sold as a platform, a feed, or a research product.
Team pilots
Front-office style player evaluation, game-day insight, validation reports, and custom schemas for internal workflows.
Betting and DFS
Projection surfaces, confidence and risk layers, prop-adjacent research, and slate-ready feeds.
Fantasy and apps
Auction values, comparable-player logic, roster-fit views, and API-ready outputs for product integrations.
Content and research
Premium reports, methodology pieces, archetype stories, and comp-driven analysis sold through Substack, Gumroad, or Codezmart.
B2C hook
Historical comps are the consumer entry point.
Unlimited historical comps
One product, one price, one job: let NBA fans search a player and see the full historical family behind the line.
- Preview results for everyone
- Unlimited comps for subscribers
- Stripe-hosted checkout
- No card storage in DelQuant
How it fits the brand
The B2C product should feel adjacent to the B2B engine: explainable, stat-first, and built on the same comp system. It creates a consumer funnel without turning the homepage into a generic subscription page.
Methodologies
The landing page should point to the methods that make the outputs credible.
Core methods
- Weighted baselines across recent seasons and recent game windows
- Context-neutral player normalization for better comparability
- Archetype and comp mapping from public NBA box-score structure
- Risk and confidence surfaces instead of bare projections
- No-lookahead historical replay and grading
- Market and wins translations for downstream products
Why this matters
Buyers do not pay for a model just because it is statistical. They pay because it is explainable, repeatable, and packaged into something they can use. DelQuant should make that structure obvious from the first page.
The site should make it easy to move from public proof-of-work into private conversations about pilots, licensing, and research bundles.
Public proof
Keep the public work visible, but clearly downstream of the platform.
Basketball Ops demo
Context-neutral feed, FMV, FMVW, and the team comparison flow.
Team-facing study
Player projections, context-aware variance, role fit, and no-lookahead replay framed for a team buyer.
Roster identity study
Long-run roster identity, top-7 shape, and coaching/front-office fit packaged as a public-safe example.
Case studies
Use the public artifacts to prove the platform can speak team language.
Team pilot
Player-performance analytics layer
- Modular analytics API and reporting layer, not arena hardware replacement.
- Player projections, context-aware variance, confidence, historical comps, and replay validation.
- Best current examples are a transition-era roster sample and a post-change role readout.
Roster study
Roster identity and fit study
- 31-season roster identity study with era summaries and current top-7 role shape.
- Coaching prep, opponent fit, and front-office style roster construction framing.
- Useful as a warm-lead example of how DelQuant translates into decision support.
Next step
Request a pilot, a sample feed, or a research bundle.
The immediate goal is to turn this into a coherent front door for B2B outreach while the domain is being finalized. If you want direct intake, use the email below or route through the research surfaces.