🏏 Most Wickets - Cricket Bowling Analysis Project

Welcome to the Most Wickets project – a data analysis deep dive into the world of legendary cricket bowlers! 🧠📊
Using Python and powerful libraries like Pandas, NumPy, Matplotlib, and Seaborn, we explored performance metrics of some of the greatest bowlers in cricket history.

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🔍 Project Overview

This project focuses on answering key analytical questions about top bowlers by analyzing a dataset containing career stats such as:

• Matches Played (Mat)
• Innings Bowled (Inns)
• Balls Bowled
• Runs Conceded
• Wickets Taken (Wkts)
• Best Bowling Figures in Innings (BBI) & Match (BBM)
• Bowling Average (Ave)
• Economy Rate (Econ)
• Strike Rate (SR)
• 5 & 10 Wicket Hauls
• Career Span

We used pandas for data handling, seaborn & matplotlib for beautiful visualizations, and numpy for numerical operations.

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✅ Solved Questions

Here are the questions we explored and solved during the analysis:

1. 🥇 Which player has the best bowling average (Ave)?
2. 🎯 Who has the highest number of wickets in their career?
3. 💸 Which player has the best economy rate (Econ)?
4. 🧮 Comparison of strike rates (SR) of players with more than 100 matches.
5. 🔥 Who has the best bowling figures in an innings (BBI) and match (BBM)?
6. 🕰️ Which player has the longest career span?
7. 🏏 Who has bowled the most balls in their career?
8. 🎯 Who has the lowest average among players with at least 50 wickets?
9. 🖐️ Who has the most 5-wicket hauls in the dataset?
10. 🎯 Which players have taken more than 300 wickets?
11. ⭐ Who has the best bowling performance in a single match (BBM)?
12. 📈 How has economy rate (Econ) changed over different career spans?
13. 📊 What is the correlation between matches played and wickets taken?

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📁 Technologies Used

• 🐍 Python 3
• 🧮 Pandas & NumPy
• 📊 Matplotlib & Seaborn
• 💻 Jupyter Notebook

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📸 Sample Dataset Preview

| Player              | Span      | Mat | Balls | Runs  | Wkts | Ave   | Econ | SR   | BBI    | BBM    |
|---------------------|-----------|-----|-------|-------|------|-------|------|------|--------|--------|
| M Muralidaran       | 1992–2010 | 133 | 44039 | 18180 | 800  | 22.72 | 2.47 | 55.0 | 9/51   | 16/220 |
| SK Warne            | 1992–2007 | 145 | 40705 | 17995 | 708  | 25.41 | 2.65 | 57.4 | 8/71   | 12/128 |
| JM Anderson         | 2003–2022 | 169 | 36396 | 17014 | 640  | 26.58 | 2.80 | 56.8 | 7/42   | 11/71  |