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Local-first NBA prop research

PRISM

A daily scanner that pairs quantile estimates with local box-score history and a clear record of settled outcomes.

Role
Modeling · Local data · Product engineering
Year
2025
Repository
Private

01 / Interactive system slice

Inspect the workflow

Public sandbox · real engine with clearly labeled cached and preview states
PRISMNBA prop scanner
LIVE TOOL · PUBLIC SANDBOX
DETERMINISTIC PREVIEW

Starting the free-tier service…

Deterministic preview · estimates are distinct from settled outcomes

MIN EDGE (× MAE)1.00
3Evaluated
0Actionable
0Full value

TOP PLAYS

02 / Engineering evidence

Claims with boundaries

Derived from the local implementation and offline artifacts.

Runtime

Local firstThe development workflow runs without hosted dependencies.

Estimate

Quantile intervalLow, median, and high estimates remain visible together.

Review

Picks → recordPredictions stay distinct from subsequently settled results.

Problem

Why this exists

A ranked list can make model estimates look more certain than they are and blur the line between a prediction and a settled result.

System

How it is bounded

SQLite-backed history feeds quantile models and a local API. The interface preserves prediction intervals, source context, and outcome status across the daily workflow.

Outcome

What the demo proves

A compact research loop for scanning candidates, inspecting player context, and auditing what actually settled.

Implementation surface

PythonLightGBMFastAPIReactSQLite

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