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on March 11, 2019

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Summer of Tennis - Heat Maps

Heat Maps for some reason often invoke a 'wow!' Some research needs to be done on the why that is the case. But, if you check the topic on Google Trends, you can see the following: I've also been really fascinated on the single visual that explains so much spatially. I had an opportunity to create one, when I was tasked with plotting all hits and bounces for each player in a match on the tennis court. For the ease of understanding, I aligned all hits to one side of the court and shots to the other. This allowed the user to compare among different players with ease too. Since the points are a lot, it made sense to convert these short charts into hex density charts. A very useful resource in this case was the below Tableau article on Hex bin Density Map . Since this data is proprietary to the USTA, I cannot post the actual visualization to the public domain, so attaching pictures of my work, below: Here you can see the following salient features: Selectio

Summer of Tennis - Mapping the Tennis Court

Through a detailed analysis of all 200 odd variables which define a player winning a point, two of the most significant are the player's average position on the point and the ball's average bounce position on the opponent's court. That is the hit and bounce position on the tennis court. If we chart the tennis court on an XY plane, we find that these average positions can be defined as points on the plane. To define these points in tennis language, we have to look at them in reference to tennis lines, i.e. width from the centerline of the court to the depth from the baseline. These positions are possible via the on-court Electronic Line call system in the US Open, which tracks the ball positions and player positions 20+ times every second. So, we ended up creating new telling tennis stats named Shot Width, Shot Depth, Player Width and Player Depth, which could help describe a player's game. A big challenge was how to display these numbers, which could make sense to

#MakeoverMonday - Dietary Preferences / Restrictions

This was my first Makeover Monday (apologetically) I have been following Andy Kriebel for a long time now, but didn't somehow go down to googling Makover Monday ! I really liked the concept of it, since it is just one story, which you can play with, rework and present with no strings attached. This Monday was about a not-so-great visualization from the Neilson group, about survey results from the Ingredient and Dining-Out trends for 2016 report about the Dietary Preferences / Restrictions of people around the world. I say, not-so-great, since I dislike pie charts, circular bar charts, etc, as they don't really do justice to any comparison you want to showcase. The initial visual is as below: My take on the visual was as below: Would love to read your thoughts or shares.

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