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Dashboard Week, Day 3 – ICC Cricket World Cup Data

This post was originally published on The Data School blog between 2018 and July 2025, before our program was renamed to MIP’s Analytics Career Accelerator. References throughout this article to “The Data School” or “DS” all refer to what is now MIP’s Analytics Career Accelerator. The program, its people, and its commitment to launching outstanding analytics careers remain the same – just under a new name.

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Today we worked on making dashboards using the cricket data Craig has been working on recently. I thought I’d use this opportunity to make a dashboard showcasing some radar charts. I have been meaning to write a blog on these charts for a while, I think they are great at compressing many measures into an intuitive shape and giving insights as to the strengths and weaknesses of a sporting team/player.

That said I have yet to figure out how to best visualize them using Tableau, here’s my method so far…

First step for making radar charts is to decide how many factors you want to use, as this affects the number of sides/corners of the polygon, and the calculations required to make them. For the team cricket data I elected my factors to be Fielding, Batting, Bowling, Experience and Team Cohesion. I calculated these 5 measures by combining multiple measure pertaining to each factor, and then ranking them 1 to 10 (10 being the best score for each factor).

I also has to assign each factor an, I have 5 factors, so I used the numbers (0, 2, 4, 6, 8). I then treated these assigned integers and ranks as angles and radii, and made my Cartesian coordinates using these formulas.

 

In Tableau this gave me a set of points like this…

 

 

To make these polygons, change the marks types to polygon, make sure Team Name is on detail (or color) and put the angle integers on “Path”. Putting team name on rows will also separate the teams out to their own

I then blended to Cricket Game data to get wins and losses, to make a dashboard that explores (for a selected team), the teams they have won and lost to, and any possible characteristic patterns.

 

 

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