Abstract — The T20 World Cup Cricket Data Analysis project, titled "T20 World Cup Cricket Data Analysis (ESPN)", aims to extract and analyze data from ESPN Cricinfo to gain insights into team and player performance in the T20 World Cup. The project's objectives include extracting player and team data, analyzing batting, bowling, and fielding statistics, identifying trends and patterns, and developing predictive models to forecast future match outcomes. To achieve these objectives, the project employs web scraping using Python and BeautifulSoup, data cleaning and preprocessing using Pandas and NumPy, data analysis using statistical and machine learning techniques, and data visualization using Matplotlib and Seaborn. The expected outcomes include insights into team and player performance, identification of key factors influencing match outcomes, development of predictive models, and recommendations for team selection and strategy. The project utilizes Python, BeautifulSoup, Pandas, NumPy. .Conclusion This work has implications for cricket experts, not only fans, but also readers, analysts, or coaches to have a deeper insight into the player's performance, strategy effectiveness, and making of betterinformed decisions.