ShotCaller

Live Site: ShotCaller

Table of Contents

• Overview
• Technologies
• Libraries & Methodologies
• Features
• TODOS/Features to Implement
• Author Info

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Overview

Welcome to ShotCaller, a predictive webapp designed for basketball enthusiasts and fantasy league players. Using NBA player and match data, the app provides highly accurate predictions for NBA games and fantasy matchups.

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Technologies

• Backend: Flask, Python
• Frontend: Vite, TypeScript
• Data Processing: Pandas, Beautiful Soup
• Database: PostgreSQL
• Machine Learning: Scikit-learn

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Libraries & Methodologies

• Web Scraping: Beautiful Soup for extracting NBA data.
• Data Processing: Pandas for cleaning and preparing datasets.
• Machine Learning: Random forest algorithm for predictions.

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Features

• Match Outcome Predictions: Predict match outcomes of NBA or fantasy league games based on user input of teams or players!

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TODOS/Features to Implement

• Integrate authentication to allow users to save their teams.
• Expand dataset to include additional leagues and seasons.
• Improve app design for easier usability.

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Author Info

Created by:
Azim Rahat - Portfolio | LinkedIn

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