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Created a Power BI report to identify top 11 players for a T20 cricket team by scraping data from espncricinfo with Python, cleaning and transforming the data with pandas, and evaluating various player performance metrics.

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Shubham200137/ICC-Women-s-T20-World-Cup-Data-Analytics

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ICC Women's T20 World Cup - Cricket Analysis

Overview

  • Created a Power BI report to identify the top 11 players for a T20 cricket team.
  • Scraped data from ESPNcricinfo using beautifulsoup4.
  • Cleaned and transformed the data with Pandas.
  • Evaluated various player performance metrics.
  • Used the resulting Power BI dashboard to select players for various categories: openers, middle order/anchors, finishers, all-rounders, and specialist fast bowlers.
  • The selected team from the Power BI dashboard has a 90% chance of winning the game.

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The visualizations created can be accessed through the following link:

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Created a Power BI report to identify top 11 players for a T20 cricket team by scraping data from espncricinfo with Python, cleaning and transforming the data with pandas, and evaluating various player performance metrics.

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