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Sieve | NBA Analytics

Overview

Sieve is an analytics dashboard that evaluates NBA player contracts relative to on-court performance. By combining salary data with advanced impact metrics (LEBRON), it identifies market inefficiencies—highlighting players who are significantly underpaid or overpaid. Check out the Code Documentation here: Link to Sieve Code Documentation

Key Features

  • Value Analysis: Automatically calculates a "Value Gap" for every player.
  • Team Efficiency: Visualizes how well front offices convert payroll into wins.
  • Interactive Dashboard: Filter by salary, age, and impact to explore the market.
  • Data Integration: Merges contract data from Basketball Reference with advanced performance stats.

Check out the Statistical Data used: Link to Sieve Statistics Documentation

Live Demo

View Dashboard

About

Sieve is a Python project that analyzes NBA player salaries relative to their on-court impact based on archetype classifications. It combines statistical performance metrics (LEBRON and WAR metrics) with contract data scraped from Basketball Reference to identify value gaps players who may be overpaid or underpaid compared to their impact.

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