Footflix-LLM

Introduction

a Football LLM , This project aims to provide a comprehensive tool for scouting football players and comparing their statistics using data from an Excel file and external APIs.

Project Overview

The tool fetches player data from an Excel sheet, normalizes player names using a translation table, generates scouting reports using an external API (llama3), fetches live football scores from football-data.org, and compares player statistics using radar charts.

Tech Stack Used

• Python
• Flask (for backend)
• React (for frontend)
• Pandas (data handling)
• Requests (API calls)
• Plotly (for radar charts)
• Excel (for data storage)

Key Components and Functionality

Data Handling and Normalization

The project reads player data from an Excel file, normalizes player names using a translation table to handle special characters efficiently.

Scouting Report Generation

The generate_scouting_report function constructs prompts for strengths and weaknesses of a player and sends a POST request to an external API (llama3) to generate detailed scouting reports.

Live Football Scores

The fetch_football_scores function fetches live football scores for matches on a specified date using the football-data.org API.

Player Comparison with Radar Charts

The generate_radar_chart function generates radar charts comparing key statistics (goals, assists, etc.) between two players.

Commands

• score or match: Fetch live football scores for matches on a specific date.
• scout or player: Generate a scouting report and display statistics for a specific player.
• compare: Compare statistics between two players and visualize the comparison using radar charts.