Exploring La Liga Through the Lens of xT Metric: Barcelona and Real Madrid’s Dominance, De Paul’s Passing Mastery, and Vinicius’s Dribbling Magic
In the previous article, we analyzed the Premier League. Today it’s La Liga’s turn. Still ahead are at least the Bundesliga, Serie A, and Ligue 1 with similar reviews. If you are interested in the format and would like to see a similar analysis of other leagues, please write about it in the comments.
The analysis in this article is based entirely on the use of the xT metric. Why should this metric be given attention?
- It allows evaluating the effectiveness of players’ actions with the ball on the field in possessions that did not end in shots.
- In attacks that ended in shots, we can only operate with basic metrics like xG, xA, and try to translate the final value to all participants (this is how metrics such as xGChain and xGBuildup were calculated). xT allows for a much more flexible assessment of actions compared to the mentioned indicators. (for details here)
- Among its conditional competitors, xT is the easiest to implement and interpret. Undoubtedly, this metric has a number of limitations and is unquestionably inferior to other machine learning-based tools (metrics like VAEP, OBV, PV), but it still provides a deeper optics for analyzing football data.
Here we go.
A brief reminder that xT, or “expected threat,” indicates how much the probability of scoring a goal changes when the ball moves from one area of the football field to another. For each point on the football field, a certain value is preliminarily calculated. The difference between two such points during a pass or carrying of the ball is the final xT score. It is these scores that we will be using in this article.
First of all, let’s look at the Top 25 La Liga players by xT for passes and ball carrying on dribbles.
This ranking features players from eight teams, with Real Madrid and Barcelona completely dominating, occupying half of all the spots.
- Real Madrid is represented by eight players: Vinicius, Rodrigo, Modric, Diaz, Kroos, Bellingham, Vazquez, and Valverde.
- Barcelona secures six spots thanks to Raphinha, Yamal, De Jong, Pedri, Canselo, and Felix.
- Atletico Madrid has four players in the list with Riquelme, De Paul, Lino, and Correa.
- Real Betis, currently sixth in the league standings, earns three positions in the ranking for Isco, Rodri, and Ezzalzouli.
- Girona, like the remaining Athletic Bilbao, Las Palmas, and Sevilla, is represented by only one player.
The same ranking can be plotted on two axes to get a clearer picture of how the analyzed players are distributed relative to the league average and other footballers.
It’s evident that, aside from Kroos, all 24 players fall into the top-right quadrant. This area of green dots corresponds to higher xT metric values compared to the La Liga average. The German is slightly below the average level in terms of moments created through dribbling but ranks fourth in the league for passing effectiveness.
Below is a ranking that corresponds only to the horizontal axis of the previous graph. Here, the top Spanish league players are ranked by the danger created through passes.
The top four spots are very closely distributed. De Paul is in the lead, followed by De Jong, with Real Madrid veterans Modric and Kroos trailing closely behind.
A similar ranking exists for players who frequently carry the ball from less dangerous areas into zones with a higher probability of scoring.
Vinicius leads with a clear margin. Rodrigo creates 25% less on average per match. Next comes Riquelme, whom we’ll see again in our article in an unexpected position. Rounding out the top 5, Raphinha and Yamal create almost twice as less as the leader of the ranking.
Below is a map of the most effective creators in LaLiga in relation to specific locations on the football field from which a player passes or dribbles with the ball into more dangerous areas in terms of the probability of scoring a goal within the next few actions.
A third of the zones on the map are occupied by Real Madrid players. There’s complete dominance on the left flank and half space in the attacking third and the central part of the field.
Vini creates moments better than anyone else in the league from four different zones. On the left of the picture, all passes and carries with positive xT values are displayed. In the central part, only actions performed from zones where the Brazilian dominates are presented. On the right, the most dangerous actions by xT are highlighted separately.
It’s evident that the main threat is created through carries, as previously shown in the general league rankings. On average, per match, the Brazilian creates 0.61 xT through dribbling, accounting for almost 80% of all moments.
On the right flank and half space of the attack, Barcelona’s rising star Lamine Yamal stands out. For comparison, below is his map of passes and carries. His actions are more balanced — approximately 50% of the moments are created by the Spanish footballer both through passing and dribbling.
Now let’s look at two players who are the best in two central field zones. Let’s start with De Paul.
The left image is cluttered and doesn’t carry much meaning. The central and right images are of the greatest interest in the context of comparison with Kroos. It’s evident that the Argentine midfielder creates the greatest danger with almost vertical passes into the penalty area.
Tony Kroos’ playstyle is distinctively different. The German plays slightly deeper and acts as a kind of conductor, achieving high efficiency in passing through a large number of medium and long balls to the flanks, while almost not using vertical passes directly into the opponent’s penalty area.
I would also like to note that when analyzing midfielders, the threshold for the right graph was changed (from 0.05 to 0.03), where the most dangerous passes by xT are displayed. This is because the closer the zone is to the penalty and goal area, the higher the xT scores obtained when moving the ball into them. On average, attacking players have slightly higher scores than players in the central part of the field. Therefore, to not overly filter out the most dangerous passes, the threshold should be made softer.
In the initial third of the field, Rayo’s central defender, Florian Lejeune, stands out. The Frenchman ranks in the top for two zones, and along the line outside the penalty area, he scores higher than any other presented players — 0.36 xT on average per game. Below is his map of passes and carries. For the right graph, the set threshold is 0.02 xT per action.
It’s evident that Lejeune predictably scores high on xT due to successful long passes to the flanks in the final third.
Unfortunately, the provided ranking also features unexpected heroes in terms of their association with specific areas of the football field. Rodrigo Riquelme takes the first place for the area in the central part of the penalty box.
The Spaniard is having an excellent season and ranks in the top 3 for danger created through carrying. All his actions are predominantly focused on the left flank. However, with just three episodic actions in the penalty area, he managed to achieve the best indicators in the League.
The reason for this is the low frequency of successful ball carrying actions in this area of the football field. From this area, shots are often taken, or attempts to sharpen through position improvement after receiving fail.
The image below shows Riquelme’s closest competitors who scored slightly less by xT. It’s evident that to rank in the top, it’s enough to make just a few passes or ball carries. This position is very volatile in terms of final ratings and is not informative. We’ll keep this in mind for the future.
The image below considers a team ranking. For each team, the xT of all players was summed up and divided by the number of matches played.
- Barcelona and Real Madrid lead by a significant margin, far ahead of their closest competitor, Atletico.
- Villarreal and Celta are ranked 9 places higher in the ranking of created moments than their current positions in the league table. This fact may serve as an indicator for further examination of other metrics and a closer evaluation of the quality of moment realization. The xT metric indicates good potential, which is hampered by insufficient efficiency in the final stages of attacks.
- A symmetrical conclusion can be drawn regarding Real Sociedad and Getafe, which, in terms of created moments, rank significantly lower in the overall team ranking by xT compared to their positions in the league table. Again, this is just a marker for additional verification and greater attention to assessing the quality of the teams’ play in the final third.
The discussed ranking can also be transferred to a coordinate grid in terms of xT metrics for passes and carries.
The gap between Real Madrid and Barcelona from the rest of the teams becomes even more evident. Villarreal, which has entered the top right quadrant, deserves a special mention. This indicates that the danger created through passes and dribbling exceeds the league’s average metrics. Thus, Villarreal is in the Top 6 of such clubs, while actually being in 13th place.
The final graph in the review demonstrates how effectively teams create danger at the opponent’s goal and how many moments they allow at their own goal.
Four distinct areas can be identified on the proposed visualization.
The top right quadrant — high efficiency area (create a lot, allow few).
- Barcelona and Real Madrid are the most efficient in the league (xT diff: 2.18 and 1.91)
- Athletic Bilbao is in third place with an xT diff = 0.84
- Girona is another team in the “Efficient Teams” right top square with an xT diff = 0.57
The bottom right quadrant — high risk area (create a lot and allow a lot at their own goal)
- Atletico Madrid falls into this area
The top left quadrant — conservative area (create few, allow few)
- Real Sociedad is the most defensive team in La Liga.
The bottom left quadrant — low efficiency area (create few, allow a lot)
- Valencia is the best team in terms of league standings among those that allow more moments at their own goal on average per match than they create at the opponent’s goal.
Also read:
Exploring the Best EPL Creators by xT: A Zone-by-Zone Analysis
Behind the EPL Scenes: Quick Analysis Using xT Metric and Football Event Data
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