For the longest time, statistics in football were heavily skewed towards end product. Goals and assists were the only tangibles available to the regular viewer of football. Over the past few years, however, the statistical landscape within football has undergone a revolution. Companies such as Opta, Statsbomb and Wyscout have led the charge in this regard, utilising events data to create advanced metrics that shine a light on aspects of the game that are easy to miss otherwise. Metrics such as xG, xA, key passes, etc have as a consequence become a part of common football discourse and occupy an important space in player analysis.
With the availability of these metrics, analysts have attempted to find ways to reward deeper players for their contributions to earlier parts of play. Enter xGBuildup; as the name suggests, this metric rewards players by tracing xG back to the first link in that chain of possession and dividing the end xG value equitably. In other words, xGBuildup is the total xG a player is involved in minus shots and key passes. Sounds confusing? Well, just a minute. When put into action, the metric begins to make a lot more sense. “Contextualise”, as they say.
Here’s a look at Barça’s xGBuildup distribution in 2014/15, 2015/16 and 2019/20.
Here, you can clearly see the playmakers stand out. Busquets, Xavi and Iniesta expectedly, but Mascherano, Alba and Alves too. This statistic helps map out a team’s build-up patterns. For instance, Barça became more reliant on the full-backs for ball-progression in 15/16 as compared to the previous season. Moreover, Neymar’s heightened deep contributions in 15/16 really stand out in this map.
In both graphics, Barça’s xGBuildup distribution isn’t too lopsided. That indicates a well-rounded arsenal in terms of build-up options. A quick look at the 2019/20 graphic indicates that things have changed.
Here, things look slightly more grim. Most of Barça’s xGBuildup is split between Busquets and Alba, who are the focal points of ball progression. Arthur and de Jong don’t rank very highly here, which is in line with the way they’ve been deployed. In contrast to his role at Ajax, Frenkie has not been in charge of progression at Barcelona and has instead been played in a variety of more advanced roles. Arthur too has been taking up higher positions on the field than he did last season. Consequently, his xGBuildup per 90 has come down to 0.4 from 0.65.
Currently, Barça are dealing with a rapidly declining full-back and one who is inept in the opposite half. Therefore their progression through wider channels has been massively curtailed. This leads to balance problems, especially since Barça practically play with three central attackers. This is an area that needs work.
So, xGBuildup. As a stat it has several upsides. However it is lacking in some ways. For one, it merely divides the xG equally between all those involved beforehand instead of weighing specific contributions differently. For instance, a pass by Busquets may have carried more value to the run of play than an earlier one by Lenglet yet the xGBuildup model would reward them equally. This is why other metrics such as xT (expected threat) are being developed. They seek to proportionally reward players for their contribution to build-up.
In all, statistics tend to be somewhat divisive in the football world. Critics point to the fact that they take away pleasure from the game and reduce it to numbers. Perhaps a better way to look at them is as an enhancement to that very viewing experience, a method of solidifying opinion, of ascertaining and challenging one’s own beliefs. After all, credible statistics are seldom misleading.