This will be the last post summiarizing this years Superettan and Allsvenskan. The previous ones can be found here. Continue reading Superettan 2015 Season Summary #2
A while back I listened to the Analytics FC podcast, episode 4 and now recently the episode 14. Among other things they talked about womens football and the lack of available (open) data. When I heard it I thought I’d give a try with the data I have gathered for the Swedish League – Damallsvenskan. So here is the summary of Damallsvenskan 2015!
This post turned out to become quite a lot related to programming. As I mentioned in the last post my idea was make my predictive table positions/points model more accurate by adding more data to it. I wanted to use my own football-data parser in order to add shots data, including TSR to all teams included in the model.
With the Swedish leagues slowly coming to an end I wanted to look at creating a method for making a qualified, statistically based projection of how football leagues will end up. As the name of this blog now implies, I have approached the problem with machine learning and the results look really promising!
Some time ago I got a question from Tom Worville, at http://analyticsfc.co.uk/ if I could share how I create my plots. As I have mentioned before I use Plotly. In my opinion a superb visualization tool with a great api and a sound user policy. Being a Python programmer their eminent python library is of course extra appreciated.
Here is how I create a football pitch with Plotly. Meet footballpitchplot!
So, I got some great feedback on my first blog post! Now I feel that I have to explain the model in-depth and make some validations. One thing first, I will try to never write long blog posts, Google Analytics tells me that the average visitor reads my blog for 3 minutes so the posts I write will all be readable in that time.
So this is my first blog post. There will be a lot more to come! I’ll probably mix stories and insights from my ongoing projects regarding football analytics, predictions and betting with Team/Player/Match-Analysis. The latter actually has sprung from the projects so all off a sudden I sat with what I think is a world premiere of projecting Expected Goals for the top Swedish divisions.