Skip to content

harshitha1201/ICC-Mens-T20-World-Cup-2022-Insights

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

3 Commits
 
 
 
 

Repository files navigation

ICC-Mens-T20-World-Cup-2022-Insights

Overview

The ICC Men's T20 World Cup is a cricket tournament played among multiple teams. In this project, I developed a Microsoft Power BI dashboard to gather insights for team formation and the creation of winning strategies.

Link to Interactive dashboard

Key Highlights

Data Gathering: I performed web scraping to collect extensive data on players' information and stored it in a json file.

Data Cleaning: I cleaned and preprocessed the acquired data, ensuring accuracy and consistency.

Data Transformation & Data Modeling: I transformed the raw data into a structured format, as well as I created relationships between various tables in order to connect them with each other making it ready for in-depth analysis.

Dashboard Creation: I created dashboards that effectively communicated critical insights to stakeholders. These dashboards were designed to be user-friendly, allowing for easy interpretation of complex cricket statistics.

Insights Derived

Top Power Hitters/Openers : Identified the most explosive batsmen in the tournament, crucial for setting high run targets.

Top Anchors/Middle Order: Recognized players who provided stability and maintained the innings during crucial phases.

Top Finishers/Lower Order : Highlighted batsmen with a knack for finishing games effectively under pressure.

Top All-rounders: Identified versatile players who excelled both with the bat and ball, adding a dynamic dimension to the team.

Top Fast Bowlers: Recognized the leading wicket-takers and most economical bowlers, pivotal for restricting the opposition's scoring.

Playing 11 Selection

One of the project's key outcomes was the creation of a formidable Playing 11 team. This selection was meticulously crafted, taking into account the top-performing players from the aforementioned categories. The aim was to assemble a balanced team capable of both setting competitive totals and successfully defending them.

Tools/Libraries Used

• BrightData (For Web Scraping)

• Python Pandas (Data Cleaning)

• Microsoft Power Query (Data Cleaning, Transformation and Modeling)

• Microsoft Power BI (For Dashboard Creation)

• DAX Measures (To create Calculated Columns)

About

No description, website, or topics provided.

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published