This project presents an Exploratory Data Analysis (EDA) of the ICC Men's T20 World Cup dataset.
The objective was to uncover patterns in match outcomes, team performance, scoring trends, venue influence, and external factors such as toss and weather impact.
Through structured analysis and visualizations, the project highlights how data-driven insights can enhance understanding of tournament dynamics.
- Analyze the impact of toss on match results
- Compare chasing vs defending performance
- Study first-innings score distribution
- Evaluate venue-wise scoring behavior
- Analyze team win percentages
- Examine rain-affected matches and their distribution
- Python
- Pandas
- NumPy
- Matplotlib
- Seaborn
- Jupyter Notebook
Teams winning the toss had a slight advantage (~56%), but toss alone did not guarantee match victory.
Defending teams won approximately 54.5% of matches, indicating a moderate advantage when Team batting first.
- Average first-innings score: ~134 runs
- Most matches had scores between 100–170 runs
- Suggests relatively balanced playing conditions
Scoring patterns varied significantly across venues, showing the importance of pitch conditions and ground characteristics.
Top-performing teams demonstrated consistency and adaptability throughout the tournament.
Rain-affected matches were evenly distributed among teams, indicating no major weather-related competitive bias.
The dataset includes match-level information such as:
- Teams
- Toss winner
- Match winner
- Venue
- First-innings score
- Match result
- Weather interruptions
- Data Cleaning
- Handling Missing Values
- Feature Exploration
- Data Visualization
- Insight Extraction
- Conclusion & Interpretation