Welcome to my T20 World Cup Cricket Data Analytics project! This project aims to perform comprehensive analyses on T20 World Cup cricket data using Python, Pandas, and Power BI. Below, I outline the steps and methodologies I employed to achieve this.
- Bright Data is used for web scraping
- Data Cleaning and Transformation in python pandas
- Data Modeling and building Parameters using DAX
- Build Dashboard in Power BI
The T20 World Cup is one of the most exciting cricket tournaments, featuring the best teams from around the world. The goal of this project is to analyze various aspects of the tournament, such as player performance, team statistics, and match outcomes, and to gain insights that can help in selecting the best players and strategies.
- Understanding the T20 World Cup Data Gained an overview of the T20 World Cup, including its format, key statistics, and relevant parameters. Identified the problem statement and defined the scope of the project.
- Data Collection Utilized web scraping techniques to collect data from the ESPN Cricinfo website. Extracted various datasets including player statistics, match results, and team performances.
- Data Cleaning and Transformation in Python Employed Python and Pandas to clean and preprocess the data. Handled missing values, standardized formats, and performed necessary transformations to prepare the data for analysis.
- Data Transformation in Power Query Imported the cleaned data into Power BI. Further transformed the data using Power Query to optimize it for modeling and analysis.
- Data Modeling and Building Parameters using DAX Created data models in Power BI to establish relationships between different datasets. Utilized Data Analysis Expressions (DAX) to build parameters and perform complex calculations.
- Building Dashboard in Power BI Designed and developed interactive dashboards in Power BI to visualize the data. Incorporated various visual elements such as charts, graphs, and tables to present the insights clearly.
- Insights and Final Player Selection Analyzed the dashboards to extract meaningful insights about player performances, team strengths, and match trends. Based on these insights, selected the final 11 players who would form the ideal team for the T20 World Cup.
- Power Hitters/Openers : These are the best players to hit the boundaries.
- New Anchors/Middle Order : These are the middle order players.
- Finisher/Lower Order Anchors : These are the Lower order Anchors.
- All Rounders : These are the all rounder players both in batting and bowling.
- New Specialist Fast Bowlers : These are the new fast bowlers.
- Final 12 : These are the players we choose to play the final match.
This project showcases the integration of data collection, cleaning, transformation, modeling, and visualization techniques to perform an in-depth analysis of T20 World Cup cricket data.