It’s been a bit since my last blog post and my last #makeovermonday entry. I had a little extra time this morning so I thought I’d get back into the routine. 

This week, Andy’s challenged us with a very small data set (3 columns by 6 rows). Some of the hardest datasets are the smallest but we enjoy a good challenge, right? The dataset is taken from a Guardian article back in 2019 taking a look at the bonus-earning potential of players from the US men’s and women’s national soccer teams during world cup cycles. I highly encourage you to check out the original article. The authors do a great job of employing scroll-telling with the data. It’s very interactive but “looks” nice but the choice of using circles or bubbles to encode the data was a miss because we know that our eyes are not great (terrible, actually) at estimating differences in surface area and angles. It’s on of the reason we tend to avoid using packed bubbles or pie/donut charts to show differences in values.

During my exploration of different ideas, I tried out a vertical version similar to the original but it just didn’t work. I also tried stacked bars but that really didn’t look right because we aren’t trying to add the bonuses together. In another view, I attempted making a side-by-side bar chart but  I really wanted to show the ‘x’ multiplier but the side-by-side chart was showing absolute variance and that wasn’t what I was going for. That’s the best thing about #MakeoverMonday, we get to try lots of things and iterate through various designs with very little risk

In my makeover, since the same data storytelling technique isn’t possible in Tableau, opted for a single horizontal view of the bonuses at each stage of the World Cup cycle. Another thing I did was add the multiplier to the men’s bar to illustrate further how much more earning potential they have over the women. 

GO FORTH AND VIZ