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⚽ Analyze football strikers’ performance using Python. Includes data cleaning, visualizations, and ML models like KMeans and Regression. Built with pandas, seaborn, scikit-learn, and more. Ideal for sports analytics and performance clustering.

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🏟️ Best Strikes – Striker Performance Analytics

This project analyzes the performance of football strikers using Python.


📦 Requirements

bash pip install pandas numpy matplotlib seaborn scikit-learn scipy openpyxl

📊 Features

  • Clean and preprocess Excel striker data
  • Visualize stats: goals, assists, accuracy, etc.
  • Handle missing data
  • Apply ML models (KMeans, Regression, etc.)
  • Create performance plots

📁 Files Football Strikes Analysis/ → Jupyter notebook (.ipynb or .txt) Strikers_performance.xlsx → Dataset

🛠️ Tech Stack

  • pandas
  • numpy
  • matplotlib
  • seaborn
  • scikit-learn
  • scipy
  • openpyxl

🚀 How to Run Use Google Colab (recommended) or run locally using Jupyter Notebook.

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⚽ Analyze football strikers’ performance using Python. Includes data cleaning, visualizations, and ML models like KMeans and Regression. Built with pandas, seaborn, scikit-learn, and more. Ideal for sports analytics and performance clustering.

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