When the day started we were given data on the UEFA Women’s Euros from 2022. This data included many different tables. This caused me to immediately start thinking about all the possibilities of dashboards and analysis. I started off by thinking about ranking the players by position in this tournament using a multitude of metrics.
As I started to get to work on this idea I took a step back and realised that it would likely not be feasible in the short time span we had. This is a roadblock that would have caused me to get stressed at the start of the data school, but now it is just a small hurdle on the path of the overall project. I took a step back and reassessed what would be possible in the time span, and what I would be interested in creating.
This led me to looking at the data on Shots taken and something I have wanted to create is a map of where shots took place and this gave me the opportunity to do that.
I then started planning this project and really getting into the detail about what could be shown. With a sketch on excalidraw.
This was my finished sketch when getting into dashboarding. With the map being the focal point. I then went about making all of these charts, and started dashboarding the charts.
When I was finished with the dashboard I was not happy with the outcome as I thought it was very basic which led me to diving back into the data which is where I found data on the xG (Chance of each expected shot) of each shot. This made me think that instead of just the goal scorers I could compare that to their xG.
Creating this chart then made the analysis feel a lot more complete to me, and with some interactivity I was happy with where the dashboard was after the 6 hours we spent on it.
https://public.tableau.com/app/profile/alfie.king/viz/WhohastheBestxGtoActualGoals/Dashboard1