⚽ FotMob Web Scraper

📌 Web Scraping Project using Python
This project scrapes football match data from FotMob, extracts key statistics, and stores them in a structured format for further data analysis.

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🚀 Features

• Automates data extraction from FotMob.
• Scrapes live & historical football match stats.
• Stores scraped data in CSV format for further processing.
• Uses Selenium & BeautifulSoup for dynamic and static content extraction.
• Error handling & robust scraping techniques implemented.

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🛠 Technologies Used

• Python 🐍
• Selenium (for handling dynamic content)
• BeautifulSoup (for parsing HTML data)
• Pandas (for data manipulation & storage)
• Requests (for sending HTTP requests)

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🔧 Setup & Installation

1️⃣ Clone the Repository

git clone https://github.com/your-username/scraper-project.git
cd scraper-project

2️⃣ Create & Activate Virtual Environment

# Create virtual environment
python3 -m venv env

# Activate (Windows PowerShell)
.\env\Scripts\Activate.ps1  

# Activate (Mac/Linux)
source env/bin/activate

3️⃣ Install Dependencies

pip install -r requirements.txt

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📊 How It Works

1. Launch the scraper:

   python index.py

2. Select leagues or teams (modify script if needed).
3. Scraped data is saved in the /data folder as CSV files.
4. Perform analysis using Jupyter Notebook (notebook.ipynb).

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📂 Project Structure

📦 Scraper-Project
 ┣ 📂 data              # Folder for scraped football data
 ┣ 📜 .gitignore        # Git ignore file
 ┣ 📜 README.md         # Project documentation
 ┣ 📜 async.py          # Async scraping script (if used)
 ┣ 📜 index.py          # Main script for scraping
 ┣ 📜 notebook.ipynb    # Jupyter Notebook for analysis
 ┣ 📜 requirements.txt   # List of dependencies
 ┣ 📜 test_pyetes.py     # Testing script
 ┗ 📜 testing.ipynb      # Additional tests

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📌 Future Enhancements

✔️ Automate scraping for multiple leagues
✔️ Store data in a SQL database for better querying
✔️ Build a Flask API to access scraped data

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🤝 Connect With Me

📧 Email: Idreesshoaib82@gmail.com
💼 LinkedIn: Mohammad Bahar
📂 GitHub: medrees-1000

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