DS28 Week 2 Project Day

Today was supposedly not a day for project however as our coach Carl got sick (get well soon Carl!). Our schedule was switched a bit with the original project Friday moved up to today (yay!). So let's get on with it.

So today we were asked to find an old dataset on MakeoverMonday website (https://www.makeovermonday.co.uk/data/) and to comment on the original viz, what's good and what's not so good about it and what we would have done to improve it. So the topic I have chosen is 2021 week 15: Fouls Called Game by NBA Referees (dataset with original viz: https://data.world/makeovermonday/2021w15). And below is the screen capture on the original viz:

So let's start with what is good about this viz:

  • I like the normalised per game value (even though I didn't know what it means in the first place, had to google that)
  • As sometimes we will come across some data with very different range, like a percentage value comparing to maybe an absolute number then the viz would be very messy as 2 values being compared together are hard to have a synchronised axis
  • So a normalised value could really tie all the different metrics together in order to better visualise them. BUT, there is a but, the normalised value is also something I feel bit iffy about which we would talk about that later

Now the no-nos(for me):

  • This chart is only showing 1 referee, as a basketball newbie (I do watch a bit of NBA but no idea what any of the foul means, nor the name Aaron Smith), I do not know why they were picking Aaron Smith to be in this visualisation
  • And as mentioned the normalised value is something I like and don't like at the same time. It is very statistically driven (not that it is bad), it could be bit difficult for some people without statistical knowledge to grasp the concept easily and hence they might need to google that in order to understand the chart fully (like I did)

So this is what I wanted to change on this graph:

  • Give users control on whose detail they want to see, instead of just having a particular referee by default
  • We can sort the ref by foul per game in order to get a bigger picture of which ref has most specific type of fouls called (maybe Aaron Smith is famous for calling a lot of fouls?)
  • Ditch the normalised value. As cool as it sounds and look, but if the chart cannot cater to the public then I believe it defeats the purpose
  • Provide options for users to compare the referees in different foul types

After hours of work, I have created a viz based on my own suggestion to myself (that doesn't sound good).

Tableau Public Link

I guess it's only fair too that I criticise my own work. In this chart I ditched the normalised value and gave user more control over what metrics they want to see, however when it comes to some metric with high number value the bubble chart will become very clunky, and all other metrics bubble will be a bit distorted or overlapped, as some of the refs do not have sufficient data or they never called such foul.

Also, the control for user to change ref comparison is a bit subtle. If you click on the bar chart above it will have a menu (see below) and then you can change the bubble chart below. However I believe I could have added more guidelines to the users. But due to time restriction of the project I failed to do so (another lesson: need better time management in project time/day).

So this is it, this is the viz I have created, tried to improve on the original viz. Working on a MakeoverMonday dataset is always fun (racing with the time limit is always the most "fun" part) . I guess time management is always a weakness of mine, I have spent too much time working on a percentile table calculation for the bubble chart (probably will run into such problem quite often in the future). However it was a great fun project, I am very much looking forward to our upcoming projects!

Author:
Alfred Chan
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