IPL Match Analysis Project

Overview

Comprehensive IPL Match Analysis Using Historical Data

This project analyzes Indian Premier League (IPL) matches using detailed datasets from 2008–2022. The analysis involves exploring match-level as well as ball-by-ball data to uncover patterns, trends, and key insights into player performances, team strategies, and overall match dynamics.

Project Objectives

• Analyze IPL history for patterns and insights.
• Identify top teams, players (batsmen, bowlers), best venues, and key match moments.
• Understand how tactics like toss decisions, venue choices, and innings order influence match results.
• Visualize data using graphs, charts, and dashboards for easy interpretation.

Features/Analyses

• Venue statistics: Most matches hosted, highest scoring venues, etc.
• Team performance: Most wins, win distribution over years, influence of toss, super overs, etc.
• Player performance: Top scorers, top wicket-takers, their strike/economy rates.
• Over-wise and segment-wise (Powerplay, Middle, Death) run distributions.
• Dismissal type distributions.
• Boundaries and scoring rates by teams and players.
• Winning margins across seasons.
• Many more insights packaged as dashboards.

Data Sources

The following data files are used (provided in project repository):

• IPL_Matches_2008_2022.csv — Match-level summary (date, teams, venue, toss, result, player of match, etc.).
• IPL_Ball_by_Ball_2008_2022.csv — Ball-by-ball details (batsman, bowler, runs, wickets, extras, etc.).

Setup and Usage

1. Clone the Repository

git clone 
cd IPL-Analysis-Project

Install with:

pip install -r requirements.txt

3. Usage

• Jupyter Notebooks:
  Open in Jupyter/Colab and run cell by cell to reproduce all explorations and visualizations.

• Dashboards:
  View presentation and dashboard files in the dashboards/ folder for summary insights.

• Scripts:
  Run data cleaning and analysis scripts in src/ for batch processing.

Key Questions Addressed

This project answers multiple IPL-centric analytical questions, including but not limited to:

• Which venues and teams have dominated IPL history?
• Who are the top 10 run scorers and top 10 wicket takers, and what are their strike/economy rates?
• How are runs and wickets distributed across different phases (Powerplay, Middle, Death overs)?
• What are the common types of dismissals? How does toss affect outcomes?
• Which matches were the highest-scoring, and what were the biggest wins (margin)?
• Boundary counts for teams, and more!

See the IPL_Analysis_Dashboard.pptx for visual answers to each key question.

Data Preparation

• All datasets have been checked for consistency (e.g., missing values, team names, dates).
• "No result" and abandoned matches have been removed for accurate statistics.
• Feature engineering performed for phase-by-phase analysis (segmenting runs/wickets by overs).

Results and Visualizations

• Graphs, charts, and dashboards summarize all findings.
• Dominant teams: Mumbai Indians, Chennai Super Kings, etc.
• Star batsmen: Virat Kohli, David Warner, etc.
• Star bowlers: Lasith Malinga, Yuzvendra Chahal, etc.
• Venue and toss impact, scoring patterns, and more.

How to Contribute

Contributions are welcome. Create a pull request or submit issues for bugs or suggestions.

Authors

• Kedar Mahajan (BT23CSA033)
• Koustubh Gadekar (BT23CSA039)
• Prakhar Kothari (BT23CSA052)
• Under guidance of Mr. Santosh K Sahu

Happy IPL analyzing!