Best 11" - Crafting Cricket Excellence through Data Analytics

Goal: Assembling a team poised to triumph over any adversary, meticulously curated using the power of Data Analytics

Project Steps:

• Data Collection: ESPNCRICinfo data gathered in JSON format.

• Data Cleaning and Transformation: Loaded into pandas for initial cleaning, converted to CSVs, and further refined using Power Query. DAX measures are employed for data aggregations.

• Data Modeling: Utilized a star schema format with dimension and fact tables.

• Data Visualization: Engaged in visualization to extract valuable insights.

Solution Overview:

Pages showcasing filtered players for each role with respective stats.
The last page displays the final 11 with the team's combined strength. Players can be added/removed, and team strength adjusts accordingly.

Interesting Finding:

Big players like Babar Azam, Ben Stokes, and Mitchell Starc missed inclusion due to role-specific requirements.

Skills: Microsoft Power BI · SQL · Pandas · Data Analysis · Web Scraping