whoops in the excitement and enjoyment of the weekend, with such distractions as Groovin the Moo I forgot all about posting a blog. anyway enough blab here it is.
So i have collected all my data for my assignment (thank god) and I have come up with a way to visualise it. At first I was trying to work out a way in which I could visualise all my data on one page. I realized pretty quickly that this was either going to look very crap or it just wasn’t going to work. So I had a trawl through other datavisualisations for some inspiration and ideas. I remembered one of the examples that Michael Honey showed is in the datavis lecture which was the olympics one. where the medal data was visually displayed. My datavisualisation will be similar to the olympics datavis.
The viewer will be able to select a certain season such as the 2009 season or 1992 and select what data they want to see such as age. The age of the players will be added up to get one whole number and then this will be displayed in an oval shape similar to the ball, the older the team the larger the oval. The oval will have some kind of emblem design on it so it teams the viewer can distinguish between teams. the viewer can then click on the oval and it will come up a visualisation of the total age of that team throughout the years that team has been in the super 14, and a list of all the players in that team below the visualisation from the certain year that was selected and at the start and the stats for each individual player such as age weight height etc. This same principle of datavis will be used for weight, height. wins and losses etc. The only one that will be different will be the place of birth for each individual player. The viewer will be able to select the team or teams they want to view. A google map will pop up with pins showing where each player comes from. when the mouse is rolled over a pin the name of the player will pop up. You can click on the pin and the data of that player will show up below the google map. It is possible to view different teams at the same time. The pin markers will be different colours according to which team the player is from.
Hopefully the datavisualisation will show how important things such as age, weight, height etc in how well a team does.

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