This project aims to perform a proper analysis on the 2022 T20 WC to find the best possible team from that World Cup. The analysis is carried out using data scraping, preprocessing, and visualization techniques.
The project can be accessed online here!
The following tools were used to perform the analysis:
JavaScript for data scraping Python for preprocessing the data Power BI for dashboarding and visualization
The data for the analysis was scraped from the following sources:
The data was scraped using JavaScript and Bright Data. The data scraped from ESPN Cricinfo includes:
Match details (date, venue, result, etc.) Batting and bowling statistics of players The data was stored in json and CSV files for further analysis.
The data was preprocessed using Python and the pandas library. The preprocessing steps included:
Merging the data from different CSV files Cleaning and transforming the data Calculating team-wise and player-wise statistics The preprocessed data was then stored in a separate CSV file.
The preprocessed data was visualized and dashboarded using Power BI. The dashboard includes:
Overview of the tournament Team-wise statistics (batting, bowling, and fielding) Player-wise statistics (batting, bowling, and fielding) The dashboard also includes interactive visualizations such as filters, slicers, and drill-downs.
The analysis provides insights into the performance of teams and players in the 2022 T20 WC. The dashboard helps in identifying the best possible team from the tournament. All the details are avaiable in this repository.
This project was carried out by @JanMayhem.