In the previous blog post (Shot Location Part 1) we presented “The Pitch” as a visualization of shot location data collected from more than 10.000 matches in the best European leagues. By this model we are able to communicate shot location data to football players in a way, which promote intuitive understanding.
Now, as we promised, we will explain how we work with this tool to make players score more goals. Basically, what we do is comparing the model of the general distribution of goals in open play (visualized above) to the shot location data from a specific player (visualized below). Take for example Philippe Coutinho (his full stats for the season 2019/20).
The first number in every cell indicates the number of goals in open play from that area. The second number shows the number of shots in open play from the same area. Please notice that shots after set pieces are not included.
What we can see is that Coutinho has a tendency to take a lot of shots from outside the penalty box (40/83 = 48 %). In other words, Coutinho is taking almost half of his shots, where only 1 % of goals usually gets scored. Finishing from these positions is most often equivalent to handing possession to the opponents.
If we, in TSA, were working with Coutinho, we would encourage him to take fewer shots from outside the penalty box. Instead, he should consider to pass from these positions and then run into the areas of the penalty box, where more goals are usually scored. Of course, we can also design training sessions aiming to facilitate creating this kind of chances.
His primary cell (8 shots and 1 goal) is (3.3-). Only 2 % of goals normally gets scored from here. Moving some of these shots just a few meters to the right (into cell (3.2-)) would increase chance of scoring (4 % of goals are scored from here).
Furthermore, based on the shot location data we make several calculations, which can provide knowledge regarding from which areas the player is most effective. These calculations we will elaborate in a future blog post.