This project involves analyzing data from the T20 World Cup 2022 to build insights on the best XI players team that can be assembled. The process includes web scraping, data transformation, and dashboard creation.
- Web Scraping: For Data Collection Bright Data's web scraping capabilities from the ESPNcricinfo website
- Python: For data transformation and cleaning
- Power BI: For creating dashboards
Using data from the T20 World Cup 2022, the project aims to identify the best XI players. Data was collected using Bright Data's web scraping capabilities from the ESPNcricinfo website. After data collection, the following steps were performed:
The data transformation and cleaning process using Python and Pandas included:
- Removing duplicates
- Handling missing values
- Normalizing data formats
- Aggregating and summarizing relevant statistics
Dashboards were created using Power BI to visualize the players' insights and performance metrics. These dashboards help in identifying the best XI players based on various criteria such as:
- Batting average
- Strike rate
- Bowling economy
- Middle Order
- All Rounders
- Bowling and Batting Performances
The project provides a comprehensive analysis of player performance, allowing for assembling the best XI players team from the T20 World Cup 2022 data.