I created this because I believe that shooting accuracy is a skill (how much of a skill compared to luck or random variation ¯\_(ツ)_/¯) and also I way to get a rough measure of goalkeepers. The next xG model is looking at Shots on Target which uses the same variable as above but it is based on only shots on target (for this it is very simply saved shots or goals no blocks). Overall I have found that this pretty accurately reflects the work done by others and gives numbers that are very reasonable. Was it set or open play, how was it assisted and was it a fast break or big chance.
It is in the simplest taking a look at where a shot was taken based on fairly large sized buckets. The first and most used is what I started out calling Chance Quality last season and then gave up and realized that name will never catch on and switched to following everyone else calling it xG. They are all derived using a logistic regression based on Premier League Data from 2015-16 and the big 5 European leagues + Champions League from 2016-17. I have already written about where I get my data from (although that doesn't include StrataBet data but that isn't in the xG model right now or any of the stuff on Tableau) and wanted to go into depth on how these numbers are derived.įirst is that I have 4 different xG models, they each vary slightly and are dependent on the information at hand. I as re-start my weekly updates of the stats that I post on Tableau I wanted to get around to writing about my different xG models.
0 kommentar(er)
