05 Jun Real Madrid Got More Points Than Expected
Not traditional xPoints: a clearer way to see which LALIGA teams got the most — and the least — from the danger they created and conceded
The league table tells us who collected the most points.
But it does not always tell us how much each team got from the danger it created and conceded.
That is the idea behind this analysis.
We are not talking here about traditional expected points. That distinction matters.
Traditional expected points, or xPoints, are usually calculated match by match. They estimate the probability of winning, drawing or losing based on the chances created by both teams in a specific game.
This analysis is different.
Here, we built a season-level comparison based on a simpler football question:
When a team creates and concedes a certain level of danger, how many points do teams with that profile usually get?
Then we compared that number with the points the team actually won.
The difference is what we call the points gap.
xG: putting a number on the “almost goal”
Expected goals, or xG, can be understood as a way of putting a number on the football “almost goal”.
Every coach knows the feeling.
A team arrives in the box. The chance looks clear. The bench reacts. The crowd feels that the goal is close. The ball does not go in, but everyone knows the team has created danger.
xG tries to measure how dangerous those moments were.
Not every shot is the same. A long-range shot under pressure is not equal to a clear chance inside the six-yard box. xG helps us distinguish between low-quality and high-quality chances.
But xG is not the scoreboard.
It tells us about the quality of the chances. It does not tell us whether the striker finished, whether the goalkeeper made the save, whether the shot hit the post, or whether the team managed the final minutes well.
That is why the interesting question is not only:
Who created more danger?
But also:
Who turned that danger into points?
Why we used the balance of danger in dynamic play
We did not choose the metric randomly.
First, we tested which xG indicators were most strongly related to points in LALIGA EA SPORTS 2025/26.
The strongest relationship came from dynamic-play xG difference.
That means:Dynamic-play xG difference=xG created in dynamic play−xG conceded in dynamic play
In football language:
The danger a team generated when the ball was in play, minus the danger it allowed the opponent to generate.
This is important because it is not just an attacking measure.
A team can create many chances, but if it also concedes many, the overall picture changes. What matters most is the balance between creating and conceding.
The correlation with points was very high:
| Metric | Correlation with points |
|---|---|
| Dynamic-play xG difference | 0.926 |
| Total xG difference | 0.923 |
| Dynamic-play xG for | 0.896 |
| xGOT | 0.889 |
| Total xG for | 0.883 |
| Total xG against | -0.620 |
This does not mean dynamic-play xG difference is a magic metric.
The total xG difference was almost identical, with a correlation of 0.923. So the message is not that dynamic play completely changes the analysis.
The stronger and more practical message is this:
Points were best explained by the balance between danger created and danger conceded, not by attacking or defensive numbers alone.
In this dataset, the dynamic-play version gave the slightly strongest relationship, so we used it as the reference.
How the points gap was calculated
Using dynamic-play xG difference, we built this simple model:Estimated points=52.35+1.06×Dynamic-play xG difference
Then we calculated:Points gap=Actual points−Estimated points
The interpretation is the key.
If the gap is close to 0, the team got roughly the number of points teams usually get with that balance of danger.
If the gap is positive, the team got more points than teams usually get with a similar balance of danger.
If the gap is negative, the team got fewer points than teams usually get with a similar balance of danger.
This does not measure luck directly.
It does not say who deserved more or less.
It measures something more specific:
How efficiently each team turned its balance of danger into points.
Real Madrid: the biggest positive points gap
Real Madrid were the clearest positive case.
| Team | Actual points | Estimated points | Points gap |
|---|---|---|---|
| Real Madrid | 86 | 75.5 | +10.5 |
Real Madrid finished with 86 points.
Based on their balance of danger in dynamic play, the model estimated 75.5 points.
That means Real Madrid finished 10.5 points above the model.
In simple football terms:
Real Madrid collected around ten more points than teams usually collect with a similar balance between danger created and danger conceded in dynamic play.
That does not mean Real Madrid were lucky.
It means they converted their balance of chances into points more efficiently than any other team in the competition.
That extra return may come from many football factors:
- finishing efficiency;
- strong goalkeeping;
- winning close matches;
- set-piece impact;
- defensive actions in key moments;
- game management;
- individual quality;
- the ability to turn small advantages into wins.
The model does not tell us which factor explains everything. But it clearly shows that Real Madrid obtained the highest points return from their balance of danger.
Getafe and Elche also got more from their chance balance
Real Madrid were followed by Getafe CF and Elche CF.
| Team | Actual points | Estimated points | Points gap |
|---|---|---|---|
| Real Madrid | 86 | 75.5 | +10.5 |
| Getafe CF | 51 | 42.3 | +8.7 |
| Elche CF | 43 | 35.4 | +7.6 |
These three teams did not have the same season profile.
Real Madrid competed at the top of the table. Getafe and Elche were in very different competitive contexts.
But they share one thing:
They collected more points than teams usually collect with a similar balance of danger in dynamic play.
For Getafe and Elche, this does not mean they dominated the league in chance creation.
It means they extracted more points from their chance balance than the model suggested.
In coaching terms, that may point to efficiency in small margins: defending the box, set pieces, goalkeeping, finishing at the right time, or managing tight games.
The other side: Rayo, Athletic and Alavés
At the opposite end were Rayo Vallecano, Athletic Club and Deportivo Alavés.
| Team | Actual points | Estimated points | Points gap |
|---|---|---|---|
| Rayo Vallecano | 50 | 60.3 | -10.3 |
| Athletic Club | 45 | 55.0 | -10.0 |
| Deportivo Alavés | 43 | 51.8 | -8.8 |
Rayo Vallecano finished with 50 points, but their balance of danger in dynamic play was associated with 60.3 points.
Athletic Club finished with 45 points, while the model estimated 55.0.
Alavés finished with 43 points, compared with an estimated 51.8.
This does not mean these teams deserved those extra points.
It means something more precise:
Their balance between danger created and danger conceded in dynamic play was stronger than their final points total suggested.
In football terms, they did not convert their chance balance into points as efficiently as the league trend would suggest.
That can happen for many reasons:
- missed clear chances;
- conceding goals from low-probability situations;
- defensive errors at decisive moments;
- poor results in close matches;
- difficulty protecting leads;
- set-piece problems;
- goalkeeper performance;
- timing of goals;
- winning some games comfortably but losing too many tight matches.
The data does not replace football analysis. It tells us where to start looking.
How to read the graph
The graph compares two things:
- Actual points, on the vertical axis.
- Points gap, on the horizontal axis.
Teams on the right got more points than teams usually get with a similar balance of danger.
Teams on the left got fewer points than teams usually get with a similar balance of danger.
The horizontal reference line is set at 46 points, the points level of the team in the middle of the table.
This creates four football profiles.
1. High points, extra return
These are teams that finished high in the table and also got more points than the model estimated.
This is the strongest competitive profile.
It includes:
- FC Barcelona
- Real Madrid
- Villarreal CF
- Atlético de Madrid
Real Madrid are the standout case because they had the largest positive points gap in the league: +10.5.
They were not only high in the table. They also turned their balance of danger into more points than any other team.
2. High points, points left behind
These teams finished with relatively strong points totals, but fewer points than their chance balance suggested.
This group includes:
- Rayo Vallecano
- RC Celta
- Real Betis
- Valencia CF
- Athletic Club
This is not necessarily a negative comment on how they played.
In fact, for teams like Rayo and Athletic, the data suggests that their balance of danger in dynamic play was stronger than their final points return.
The question is not:
Did they play badly?
The better question is:
Why did that balance not become more points?
That is where a coaching staff may want to look deeper: finishing, defensive errors, set pieces, goalkeeper performance, game states or the management of close matches.
3. Lower points, strong return
These teams did not finish near the top of the table, but they got more points than expected from their balance of danger.
This group includes:
- Getafe CF
- Elche CF
- RCD Espanyol de Barcelona
- Levante UD
- RCD Mallorca
- Sevilla FC
- Real Sociedad
Getafe and Elche are the clearest examples.
This profile is useful because it highlights teams that competed well without necessarily dominating the chance balance.
They may have been strong in:
- defending key moments;
- set pieces;
- low-margin games;
- compactness;
- emotional control;
- finishing efficiency;
- protecting advantages.
In simple terms:
They got more out of their balance of danger than most teams.
4. Lower points, weak return
These teams finished with fewer points and also got fewer points than their balance of danger suggested.
This group includes:
- Deportivo Alavés
- Girona FC
- CA Osasuna
- Real Oviedo
Alavés are the most notable case in this area, with a points gap of -8.8.
This profile invites a deeper football question:
Was the issue chance conversion, defensive errors, set pieces, game management, or something else?
The data does not replace the coach’s eye. It gives the coach a clearer place to start looking.
Why the bottom of the table changes more than the top
At the top, the picture does not change dramatically.
Barcelona, Real Madrid, Villarreal and Atlético still appear as strong teams. The analysis mainly tells us how they converted their balance of danger into points.
But at the bottom, the picture becomes more interesting.
If teams were ranked only by the points estimated from their dynamic-play xG difference:
- Real Oviedo would still be in the bottom three.
- Elche CF and Levante UD would fall into the relegation zone.
- Girona FC and RCD Mallorca would move out of it.
This does not mean Elche or Levante deserved to go down.
It means they got more points than teams usually get with their balance of danger in dynamic play.
And it means Girona and Mallorca had a chance balance that looked more competitive than the final table alone suggests.
This is why the analysis is useful: it does not rewrite the table, but it helps explain where the table may hide different performance stories.
The key idea
The league table tells us the outcome.
This analysis tells us something different:
How well each team transformed its balance of danger into points.
A positive gap should not be read simply as luck.
A negative gap should not be read simply as injustice.
A positive gap means the team extracted more points than usual from its chance balance.
A negative gap means the team extracted fewer.
That is all — but it is a very useful football signal.
Final takeaway
Real Madrid finished with the biggest positive points gap in LALIGA EA SPORTS 2025/26.
They got 10.5 points more than the model estimated from their balance of danger in dynamic play.
Getafe CF and Elche CF also stood out as teams that extracted more points than usual from their chance balance.
At the other end, Rayo Vallecano, Athletic Club and Deportivo Alavés collected far fewer points than their balance of danger suggested.
The conclusion is simple:
xG tells us how dangerous the chances were.
The league table tells us what actually happened.
The points gap tells us who turned danger into points — and who left points behind.