Does the points table accurately depict where a team should finish at the end of the season? This is a question that many supporters and pundits alike ask, and for some, the answer is yes. Those who say yes would argue that through a season of 34-38 games, whoever wins the most points should win the league. This is true and would make sense for a league where everyone plays each other twice, whoever wins the most games should come out on top. The other side would argue that the table is not honest, and doesn’t depict the actual winner of that season.
In this data analysis, we will examine the Ligue 1 table compared to the teams’ xG and xGA. Based on the data and statistics, we will see which teams are underperforming, which ones are overperforming, and look to see overall how accurately the points table is represented in comparison to these statistics.
The league based on points
To begin with, we must first understand the table and how it stands during this international break. The table shown above shows matches played, wins, draws, losses, and overall points. Unsurprisingly, last year’s Champions League runner ups PSG are in first with 24 points. PSG are expected to be first, as they are the team with owners that have the ability to spend more on players than almost the rest of the league combined. This will also help show a trend that will be consistent throughout this analysis, showing PSG being the dominant team in the league.
Moving down the league, there aren’t too many surprises with the teams sitting in UEFA Champions League and Europa League places. Lyon would possibly be expected to be higher up due to their great run in last year’s Champions League and after beating Manchester City in the quarter-finals. Further down you will notice the newly-promoted Lens sitting much higher than many would except in 11th with two games to spare as well. Overall, the group with the opinion that the table is an accurate representation of the league would feel quite right based on this team. However, we will now dive deeper into the league and compare their league position to their xG.
League points compared to teams’ xG
Before we begin, xG is defined as expected goals, meaning how many goals a team is expected to score and, xGA being how many goals a team is expected to have allowed being scored against them. xG and xGA have been calculated including penalties.
The scatter plot above shows the number of points Ligue 1 teams have compared to their overall xG. The table on the right shows the same measures as the scatter plot but is sorted by the highest xG to lowest xG. PSG top this graph by leading the league with 24 points and an xG of 26.10. Looking at Lyon in this graph, you would think they would be second based on their xG of 24.2. However, they sit fifth in the league table with 17 points. Monaco have the same amount of points as Lyon but have 7.5 less xG with 16.7.
Based on this comparison alone, you can already see how it can be viewed that Lyon should be much higher in the league. It could be argued that they have been unlucky to not have scored more. A team that could also be deemed lucky in terms of the league position would be Marseille. They rank last in a table that is comprised solely of xG, as seen on the table above on the right. Marseille have the worst xG at only 8.8. That being said, they currently sit fourth in the table with 18 points. Marseille have managed to win five games so far this season. Compare that to Lyon who are fifth and have won one game fewer, but have an xG 24.2.
When we compare the expected goals to total goals scored, as seen above, we can draw similar conclusions about Lyon and Marseille. Lyon, even though they have not scored as many goals as expected, still have scored the third most amount of goals with 17. Lyon have also been given five penalties and have converted all of them.
Meanwhile, Marseille can be viewed as lucky as they have managed to score 12 goals while they were expected to score 8.8. That being said, they are still performing below the average of 13.80 xG and 13.41 goals scored. One other team that should be noted for exceeding their xG are Reims. They have scored 16 goals when they were expected to only score 11.
Expected goals allowed compared to goals allowed
Whilst scoring goals can help your team, it doesn’t necessarily win you games and yield more points. For teams to be successful they also need to be solid defensively. We will now compare their defensive capabilities by looking at their xGA and their goals allowed.
Above, we can see unsurprisingly that PSG lead this metric. They have the best defence in the league, only allowing three goals scored against them in 10 games and they’ve outperformed their xGA by 6.8. In large part, that’s thanks to their defence, but also Keylor Navas saving a penalty. Unfortunately, Brest lead the league in most goals allowed with 22 and they also have the largest difference between xGA and GA at 8.6.
Going back to our comparison of Lyon and Marseille, the data shows that Marseille had let in fewer goals than Lyon. Marseille have let in the third least amount of goals with eight and defended better than their xGA had predicted with 13.2. Meanwhile, Lyon have let in 10 goals, 0.7 more than expected. Both teams have only lost one game so far this season, and Marseille still have one game in hand.
Based on the information that has been explained above, we have established two teams that point-wise are close, but based on xG should be in very different positions. Now we will take a closer look at Lyon and Marseille and see how teams with such different xG can be so close in the table and what we can expect from them moving forward.
Are Marseille lucky and Lyon unlucky so far this season?
So far based on the statistics we have shown, you could argue “yes”, Marseille have been lucky with where they are in the table, and Lyon have been unlucky.
Taking a closer look at the two teams’ offensive actions, as shown above, you will notice that Lyon have been much more productive. The green highlights which team is better in that given statistic, and Lyon lead every statistic except one. However, from these stats we can gather that Lyon clearly shoot much more often than Marseille, but their efficiency is almost the same, with both of them having an on-target percentage of 26%.
From here, some could argue that Lyon are simply taking shots they shouldn’t be taking or deploy many long-range efforts. However, Lyon’s average distance for a shot on goal is closer than that of Marseille by almost a whole yard.
Before moving on to defensive actions, as seen above, we must first remember that Marseille had a better defensive record of only allowing eight goals with an xGA of 13.2, in comparison to Lyon who had let in 10 goals with an xGA of 9.3. Looking at the table for defensive actions, you will see this time that it is much more mixed with which team is more successful in these stats compared to the attacking actions. Marseille have been more involved in defensive actions within their own half as they lead in tackles in their defensive half by 21 and have 57 more clearances than Lyon. It should be remembered also that Marseille have played a game fewer than Lyon.
Overall, when comparing Lyon and Marseille this early in the season, the statistics have suggested that Lyon have been very unlucky so far with the number of goals they could have scored and they should over time move further up the table. Marseille, on the other hand, will be deemed lucky to be in the position they are in just now. They will have to realise that they will need to start producing more in front of the goal to stay within European places in the table.
To conclude our comparison of xG and xGA of teams and how it correlates to the Ligue 1 table, it can be inferred that these metrics do not necessarily give you a better understanding of who is the best team in the league. PSG rank first in points, xG, and xGA. A team that is so dominant in the league is unsurprisingly leading in these metrics as well. It can however show who is overperforming their metrics, like Marseille, and who is underperforming, such as Lyon. The data can provide insight to show where a team can be seen as lucky when they are exceeding their expected goals or expected goals against.
Lyon will understand that they should see improvements in points based on their strong xG. On the other hand, Marseille will see that to continue their strong start, they must improve in front of the goal. With that being said, whatever the data may say, that doesn’t always result in what happens on the pitch. Luck will always be a factor that contributes to parts of games thanks to human error, and the unexpected can arise at any moment, all of which ultimately affects the data.