XG – LEVEL 1
A SIMPLE EXPECTED GOALS MODEL
Recently, I have depicted the value of using expected goals as an improvement of the shots statistic to gain a better understanding on the course of a match or the scoring abilities of players, which you can find here: Improving shot statistics. As described, the more criteria are used to weight a shot, the more precise a probability becomes to determine, to which degree a shot turns to a goal in average. However, the more criteria are used, the more complex the weighting of a shot becomes. A complex weighting may be interesting for prediction models and deep statistical analysis, but what if you just want to see which team has been better in a match by looking at some simple match statistics? That is what I want to do in this “Level 1 – Expected Goals” approach. I identified five different shot types and calculated the probabilities for them to turn into a goal. Important note: These five shot types exclude each other. For example, penalties are not included in the clear-cut chance calculation or a shot from the 6-yard box is not included in the calculation of shots from the 18-yard box.
Wrap-upLooking at the probabilities of these five different shot types, you can get a feeling on whether or not a shot was likely to be converted into a goal. With these five occasions, it should be possible to calculate your own expected goals value for a match by only knowing some additional information of the shots in a match. For example, the number of shots inside and outside the box can be found for many matches and whether there has been a penalty can be found anyways. The only more sophisticated occasion is the clear-cut chance, which cannot be found in every match statistic, but with football analysis advancing further, I expect it to be used more often.