Sports blogs are an amazing place. While we can't be bothered to have an informed debate on the financial wellbeing of our communities, we can create vast mountains of statistical data suggesting the best possible pitching rotation. Here is my contribution to that beautiful distraction from reality we call sports.
While trying to explain my choice of starting lineups, I developed a MEL script which creates a graphical representation of any statistical data set. Below is a visualization of the Seattle Sounders 2010 season statistics for league play.
In the first image (Salary Analysis), circle size (area) is dictated by player salary while the circle brightness is a function of age. The green ring is their total minutes played divided by their eligible minutes under contract. The blue ring is their player rating. For example, a young cheap player like Nyassi is a small white dot. An older player with a large salary like Keller is a large black dot. Players are arranged left to right on the x axis based on starts and games played.
In this second image I went a little stat crazy and invented my own metrics, with great names like OOP.
An early test render.
Here is what it looks like in Maya.
MEL code snippet.
I'm going to translate this over to Action Script for a more interactive website experience. Too bad there is no direct web port, Maya is a much more fun development environment.
