Categoria: Football Analytics
-
Data-driven scouting for Liverpool: replacing Fabinho
This summer, Liverpool are undergoing a full-fledged revolution in their midfield. The simultaneous departures of Fabinho, Henderson, Milner, Keita and Oxlade-Chamberlain mean that the Reds are seeking to rejuvenate the squad, adding fresh legs able to keep up with Klopp’s demanding play style. The arrivals of Szoboszlai and Mac Allister for a combined fee in…
-
AERO: a new aerial skill metric
In this blog post, we introduce our new Aerial Elo Rating Optimization (AERO) index, a new metric focused on aerial skill. Aerial skill metrics and the case for an Elo rating Aerial duels can be a key event in football on both ends of the pitch, and the relative skill between defenders and forwards in…
-
One-twos: a new metric for associative ball progression and chance creation
Ball progression and chance creation are key phases of play in football, which can be achieved in several ways. In this article, we introduce a new metric which quantifies a specific mode of associative ball progression and chance creation: one-twos. We describe our empirical definition of one-two in event data and characterize the resulting data…
-
Introducing Gegenpressing Intensity (GPI)
Gegenpressing, or counterpressing, is now a well-established strategy in many possession-based teams. To capture this aspect of the game, we introduce a new metric, called Gegenpressing Intensity (GPI), which measures the fraction of times a team immediately attempts to regain the ball after losing possession in attacking areas, rather than falling back. We find that…
-
Midseason reviews 2022/23: Serie A
A stellar start to the season has seen Napoli gain an edge over the rest of the field. Our advanced metrics show that the top spot is well deserved, while Roma are the side with the largest underperformance compared to Expected Points. The two sides show the largest improvement in xG difference compared to 2021/22,…
-
Shot quality and results in football
We investigate the link between shot quality, as measured by the team average xG per shot, and both results (in terms of wins) and performance (measured with our Expected Points model), for the top 5 European leagues. We find a strong link between xG per shot difference (xG per shot minus xG per shot conceded,…
-
The Very Exclusive xOVA Club
We introduced Expected Offensive Value Added, or ‘xOVA’, to facilitate scouting for creative and skilled players, who are able to have a great impact in the final third of the pitch. Therefore, forwards, wingers and attacking midfielders top our xOVA charts. For example, in our database, the highest seasonal xOVA (22.27) was produced by Lionel…
-
Measuring pressing success: Buildup Disruption Percentage (BDP)
Pressing is a fundamental part of many teams’ game plan in modern football. At the same time, it is difficult to measure it accurately using event data. While PPDA is certainly a very useful metric, in our view it would be advisable to complement it with different, indirect measurements of how teams are able to…
-
Data-driven scouting for Newcastle
After the takeover from PIF, Newcastle United was set to become one of the main players in January’s transfer market. This has indeed been the case, with the Magpies already completing two important signings. In this piece, we use our extensive dataset to scout for interesting players in the positions where Newcastle seems to be…
-
Soccerment's Expected Points model
Expected Goals (xG) models allow us to quantify the chance quality of individual shots. This gives us the chance to quantify the probability of a team winning, losing or drawing the match, based on the two team’s total xG during the match. In turn, this can be translated into an expectation value for points gained…
Italian 
English