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This infographic was submitted by AFL.com, who said this:
“All you need to know about the AFL’s Brownlow Medal is contained in this infographic: Find out how many Brownlows your club has won, what the most prevalent guernsey number for the winners is, triple Brownlow winners and more.”
This IG looks pretty sharp. The design is clean and everything is pretty easy to interpret (with the exception of the logos, which I’ll get to in a bit). It seems to have all the stats someone might want to know about the Brownlow. I love that the background is dark, mainly because of the black cat–I think it’s an awesome effect that the cat almost fades into the background.
There are a few issues with the data viz here. In the first graph, Number of Brownlows Won Per Club, we see that the club with the most Brownlows, South Melbourne/Sydney Swans, won 14. Then there are some bar values for the other clubs… but there are no axes or labels or anything to show how many the other clubs won! All we really know is, it’s less than 14. For the most prevalent guernsey numbers, it would’ve been cool to stretch out the uniforms on a modified bar graph to represent the number of times they’ve been used, instead of just writing it out. The very bottom statistic (the first Brownlow winner received 7 votes) does a great job of taking something that might’ve just been a number and turning it into data viz–but there are so many other spots where that isn’t done. The Club Brownlow Total Votes bar graph is excellent, though.
On a general note, maybe it’s just my unfamiliarity with the club logos, but even still I think the logos could’ve been a little larger throughout. It does present a design problem because there are up to 18 logos on one graph, so maybe if they were large enough at the top to be read, it could serve as sort of a key for the smaller logos throughout.
Overall, I’d give this infographic a B-. It’s got a good design, good dimensions and good flow, as well as some excellent models for data viz, but there are many places where data viz should’ve been employed and it wasn’t. Adding more of that will turn this into a great infographic!
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