Lire le football à travers les données depuis 2017.
Quand la football analytics n'était encore qu'une niche, nous la publiions déjà. Ici, nos data scientists partagent des métriques originales comme la Gegenpressing Intensity et l'AERO, des analyses d'avant-saison, des rapports de scouting et les études de validation derrière XSEED : l'histoire de la football intelligence, racontée au moment où elle s'écrivait.
Ball possession in European football (part 3)
Final part of our trilogy of posts dedicated to ball possession in European football. We look into the recurring build-up patterns of four top European teams: Barcelona, Man City, Napoli and Bayern Munich. Third part of a trilogy The FIRST PART OF THE TRILOGY (LINK) was an introduction to ball possession. How it is calculated and […]
Ball possession in European football (part 2)
In this second post of our trilogy on ball possession, we expand the analysis we started in the first part, digging into the build-up habits of the top European teams. We propose the ratio of passes on total touches, as an indicator of “good football”. Napoli are topping the tables on this measure. Man City […]
Ball possession in European football (part 1)
This is part one of a trilogy of posts dedicated to the role of ball possession in football. In this post, we look at how ball possession is calculated and how the focus on ball possession is often (not always) a synonym of success. We also start digging into the bidirectional causation problem: do the teams play […]
Crossing: An effective strategy?
Crossing is still very much used by the top European teams (18.6 per match, on average). However, we doubt the efficiency of such an attacking strategy. We calculate that only 1 every 64 crosses is directly translated into a goal. Is it worth trying? We conclude it is not, unless you have someone like Mauro […]
