NBA Prediction Engine

Analyze game data and predict outcomes in real-time

Advanced Basketball Analytics Platform

This comprehensive NBA analytics platform uses statistical models, machine learning, and Monte Carlo simulations to analyze games, predict outcomes, and compare player matchups. Powered by WebAssembly and DuckDB, it performs complex calculations entirely in your browser without requiring server-side processing. Explore the different tabs below to access various analytics tools.

Game Winner

Predict the winner of upcoming NBA games based on team statistics and historical matchup data

Matchup Analysis

Compare head-to-head player statistics and analyze performance trends across different seasons

Win Probability

Calculate win probabilities based on current game state using historical NBA data

Game Simulation

Run Monte Carlo simulations to predict final scores and point differentials

Season Simulation

Simulate NBA seasons to forecast playoff odds and championship probabilities

Data Source

Sample data successfully loaded!

This is a small sample dataset for demonstration purposes. For larger datasets, consider loading from S3.

How It Works

This application demonstrates the power of thick client architecture using:

  • 1
    Rust + WebAssembly: Running our statistical model at near-native speed with memory safety
  • 2
    DuckDB-WASM: Processing historical NBA data right in your browser
  • 3
    NLP.js: Enabling natural language queries about game data
  • 4
    Next.js: Providing a smooth, reactive UI experience

Key Features

  • Real-time win probability calculations
  • Natural language queries about game statistics
  • SQL-based data exploration
  • Monte Carlo game simulations
  • Season-level Monte Carlo simulations
  • 100% client-side computation

Technical Note:

All computations happen directly in your browser - no server calls needed for data processing!