🏏 Asia Cup Bowler Analysis

This project analyzes bowling performance in the Asia Cup, using Python, Pandas, Matplotlib, and other data-science tools. The notebook explores player statistics, visualizations, and insights that help understand bowler effectiveness.

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📂 Project Structure

Asia-Cup-Bowler-Analysis/
│
├── Asia Cup.ipynb          # Main analysis notebook
├── dataset/                # (optional) Raw / cleaned datasets
├── README.md               # Project documentation

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📊 Features & Analysis Performed

• ✔️ Data cleaning and preprocessing

• ✔️ Loading and exploring Asia Cup bowling dataset

• ✔️ Calculating key bowling metrics:

  • Economy rate
  • Strike rate
  • Wickets taken
  • Overs bowled
  • Average

• ✔️ Visualizations using Matplotlib / Seaborn

  • Top wicket-takers
  • Best economy bowlers
  • Performance comparisons

• ✔️ Insights and summary of top-performing bowlers

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🛠️ Technologies Used

• Python
• Jupyter Notebook
• Pandas
• NumPy
• Matplotlib
• Seaborn

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🚀 How to Run

1. Clone the repository:

   git clone https://github.com/Parthiban-web/Asia-Cup-Bowler-Analysis
   

2. Install required libraries:

   pip install pandas numpy matplotlib seaborn notebook
   

3. Open the notebook:

   jupyter notebook "Asia Cup.ipynb"
   

4. Run all cells to view the analysis.

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📈 Results & Insights

The notebook provides:

• Ranking of bowlers based on wickets, economy, strike rate
• Visual comparison charts
• Identification of best and consistent bowlers
• Statistical breakdown of Asia Cup bowling performances

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🙌 Author

Parthiban Machine Learning & Data Science Enthusiast GitHub: https://github.com/Parthiban-web

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⭐ Contributions

Feel free to fork the project and submit pull requests! Suggestions and improvements are always welcome.

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📜 License

This project is for learning and analysis purposes. You may modify and use it freely.