The extend of my basketball knowledge is this: my local team, the Brose Baskets, are the German Champion and have won that trophy a few times over the years. I have been to exactly one of their games and while it was mad and exciting, basketball isn’t quite my thing.
Now of course I am always happy to learn something new, but to say I struggled with this week’s data is an understatement. It took me quite a while to figure out what I could do with it, what angle to take, etc.
Four Seed 1 teams in a single tournament? What???
And along the way I also had the pleasure to dial in to the Maine TUG hosted by Jonathan Drummey this morning, where Andy and I spoke to the audience about MakeoverMonday and they then went on to run a MakeoverMonday live session. Hope you guys enjoyed it 😉
So let’s get into this week’s data and the original viz…
What I like about it:
- all the years are included to show a timeline of results since 1985, from when the field was expanded to 64 teams (and even more teams later on)
- the text box highlighting percentages of lower seeds making the final four is interesting
What I don’t like about it:
- why would you sum up the seeds for the Final Four? How does that make sense? (now in relay triathlon races, the time for each participant is often summed up and the team with the shortest overall time wins. But that makes no sense for seeds in basketball tournaments…?)
- the heading tells me nothing. Could be about gardening for all I know…
- there is no colour legend. What do the colours mean?
- what do the numbers in the stacked bar charts stand for?
- why are there sometimes the same numbers in the stacked bar charts but the colours are different?
- how do they define ‘lower seeds’? Is it a number lower than 7, i.e. 1-6, which means they are better seeded teams? Or is it a number higher than 7, which would indicate a team playing at a ‘lower’ level?
- where does the data come from?
- the title ‘sports chart of the day’ and the logo take up unnecessary room, which could be used for all those explanations we’re missing
- what does it actually tell me? What insights can we gain? What seeds end up making the Final Four most often? Is there a regional difference (something I only stumbled across when looking at the data: there are four regions from which teams enter the competition)?
What I did:
- at first I struggled
- then I tried different vizzes just to get my head around the data. I tried time series, looked at regional clusters, different seeds, rounds, trends, bar charts, scatterplots, heat maps, highlight tables, box and whisker plots, bump charts, you name it, I tried them all. I looked at winning margins, upsets, number of wins by team, etc.
- I may have sent a few whingey messages to Andy, and I did try to read online about how this March Madness stuff actually works
- then I went back to square one and decided to just focus on one single round: the final.
- I did want to look at it over time, so I went for the years when an upset happened, i.e. a team that was seeded lower (a higher number) ended up winning
- but there wasn’t much on my dashboard by then, so I chose to call out a couple of highlights among the upsets:
- biggest upset by seed and
- biggest upset by winning margin
- finally ‘just’ a bit of formatting and I was done
(Click on the image for the Tableau Public version)