Sports League Management System

Overview

The Sports League Management System is a comprehensive tool designed to manage data associated with sports leagues, including teams, players, coaches, referees, matches, scores, and standings. This project leverages real-time data integration, ensuring accuracy and efficiency in managing sports league data.

Table of Contents

1. Project Description
2. Features
3. Technologies Used
4. Installation
5. Usage
6. Database Schema
7. ER Diagram
8. Screenshots
9. License

Project Description

The Sports League Management System aims to manage comprehensive data associated with sports leagues. The project utilizes real-time data from football-data.org, maintaining an updated database with minimal manual data entry, enhancing the system's efficiency and reliability.

Features

• Real-time data integration
• Management of teams, players, coaches, referees, matches, scores, and standings
• User-friendly interface for administrators and users
• Detailed search and filtering options
• Secure authentication and authorization
• Modular design for easy maintenance and scalability

Technologies Used

• Frontend: HTML, CSS (Bootstrap), JavaScript
• Backend: Flask (Python framework)
• Database: PostgreSQL
• Other Libraries: Requests, Gunicorn, Psycopg2, Python-Dotenv, Werkzeug

Installation

Prerequisites

• Docker and Docker Compose installed on your system
• Git for cloning the repository

Setup Steps

1. Clone the repository:

   git clone https://github.com/yourusername/sports-league-management.git
   cd sports-league-management

2. Set up the environment variables:

   # The setup script will automatically create .env from .env.example if it doesn't exist
   cp .env.example .env

   Edit the .env file and set your environment variables:

   • POSTGRES_USER: Database username
   • POSTGRES_PASSWORD: Database password
   • POSTGRES_DB: Database name
   • FOOTBALL_DATA_API_KEY: Your API token from football-data.org
   • Other configuration variables as needed

3. Run the setup script:

   chmod +x setup.sh
   ./setup.sh

   This will:

   • Check if Docker is running
   • Create necessary environment files
   • Build and start the Docker containers

The application will be available at http://localhost:5000

Manual Setup (Without Docker)

If you prefer to run the application without Docker:

1. Create and activate a virtual environment:

   python3 -m venv env
   source env/bin/activate

2. Install dependencies using Poetry:

   pip install poetry
   poetry install

   Or using pip:

   pip install -r requirements.txt

3. Set up PostgreSQL database and run the schema:

   psql -U your_username -d your_database -a -f schema.sql

4. Run the application:

   flask run

Usage

Admin Panel

• Manage Users: View and modify user privileges.
• Manage Teams: Add, update, or delete teams.
• Manage Players: Add, update, or delete players.
• Manage Matches: Schedule, update, or delete matches.

User Dashboard

• View Teams: Browse team profiles and their historical performance.
• View Players: View player profiles and performance statistics.
• View Leagues: Browse different leagues and their standings.
• View Matches: View upcoming and past matches with filtering options.
• Top Scorers: See the top scorers in various leagues.

Search Functionality

• Search: Find specific players, teams, stadiums, and coaches by name.

🎯 Kaggle Dataset

The data from this system is now available as a public dataset on Kaggle: European Football Leagues Database 2023-2024

Features of the dataset:

• Complete statistics for top 5 European leagues
• Weekly automated updates
• Available in both CSV and SQLite formats
• Comprehensive documentation and usage examples
• Clean, validated data with proper relationships

Database Schema

The database schema is designed to minimize redundancy and ensure data integrity by using foreign keys and transactions. The main entities include users, stadiums, leagues, seasons, teams, coaches, players, matches, scores, scorers, standings, referees, and match referees.

ER Diagram

The ER diagram illustrates the relationships between different entities in the Sports League Management System. Each table represents an entity, and the lines between them represent relationships. Primary keys are indicated by the underlined attributes, and foreign keys are shown as arrows pointing to the related primary keys.

Screenshots

Main Starting Screen

Login Screen

User Dashboard

Top Scorers Screen

Matches Screen

Teams Screen

Player Profiles Screen

League Profiles Screen

Manage Teams Screen

Match Profile Screen

League Profile Screen

Standings

Team Profile Screen

Player Profile Screen

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License

This project is licensed under the MIT License - see the LICENSE file for details.