IPL New Ball Wickets Analysis

Project Overview

This project analyzes the number of wickets taken with the new ball in IPL matches. The dataset includes details on matches, teams, venues, bowlers, and wickets taken within the first few overs using the new ball.

Dataset Information

The dataset (ipl_new_ball_wickets.csv) contains the following columns:

• Match_ID: Unique identifier for each match
• Team_1: First team playing the match
• Team_2: Second team playing the match
• Venue: Match venue
• Bowling_Team: Team that bowled first
• Bowler: Bowler who bowled the new ball
• Overs_Bowled: Number of overs bowled with the new ball
• New_Ball_Wickets: Number of wickets taken in the first few overs
• Match_Result: Outcome of the match

Files Included

• ipl_new_ball_wickets.csv: The dataset containing IPL match statistics.
• analysis.ipynb: A Jupyter Notebook for data visualization and insights.
• data_analysis.py: A Python script to perform analysis and generate graphs.
• histogram_new_ball_wickets.png: A histogram visualization of new ball wickets.

How to Use

Using Jupyter Notebook

1. Open analysis.ipynb in Jupyter Notebook.
2. Run the cells to analyze the dataset and generate visualizations.

Using Python Script

Run the following command to execute the Python script:

python data_analysis.py

This will generate various insights and graphs related to new ball wicket-taking trends.

Insights & Visualizations

• Distribution of wickets taken with the new ball per match.
• Top bowlers who have been most effective with the new ball.
• Comparison of wickets taken at different venues.

Dependencies

Install the required Python libraries using:

pip install pandas matplotlib seaborn jupyter

Conclusion

This project provides a detailed analysis of how effective different bowlers and teams are with the new ball in IPL matches. Further analysis can be performed by adding more historical data and exploring different factors affecting new ball wickets.