The clean-sheet rate ranking
Serie A is the clear leader in the covered sample, with 100 clean sheets from 312 covered team-matches. Its resulting rate of 32.05% is higher than every other league in the comparison.
| Rank | League | Teams | Covered team-matches | Goals for (GF) | Clean sheets (CS) | Failed to score (FTS) | Clean-sheet rate |
|---|---|---|---|---|---|---|---|
| 1 | Serie A | 20 | 312 | 365 | 100 | 100 | 32.05% |
| 2 | Ligue 1 | 18 | 288 | 411 | 82 | 82 | 28.47% |
| 3 | La Liga | 20 | 342 | 437 | 94 | 94 | 27.49% |
| 4 | Premier League | 20 | 348 | 487 | 90 | 93 | 25.86% |
| 5 | Bundesliga | 18 | 270 | 426 | 69 | 69 | 25.56% |
What separates the five leagues
Serie A leads on both rate and total clean sheets
Serie A recorded the highest clean-sheet total as well as the highest rate: 100 clean sheets at 32.05%. The denominator matters, however. A raw total cannot be compared fairly with another league’s total without considering how many covered team-matches produced it.
Ligue 1 followed at 82 clean sheets in 288 team-matches, while La Liga recorded 94 in 342. The Premier League had 90 clean sheets in 348 team-matches, and the Bundesliga had 69 in 270. Those figures produce the ranking shown above.
Goals for are separate context
The table also reports goals for and failed-to-score counts as aggregate league figures. The clean-sheet rate itself uses only clean sheets and covered team-matches; the goals-for and failed-to-score columns do not enter that calculation.
Method and coverage
Calculation
The rate is calculated as:
Clean-sheet rate = clean sheets ÷ covered team-matches × 100
For example, Serie A’s figure is 100 ÷ 312 × 100 = 32.05%, rounded to two decimal places. The underlying numerator and denominator are shown in the table so the percentage remains transparent.
Sample boundaries
The dataset covers 96 teams and 1,560 team-matches across the Premier League, Ligue 1, Bundesliga, Serie A and La Liga. The sample includes completed matches only. The denominator is explicitly a team-match count, not a fixture count.
What the observed numbers show
Across the five league rows, there were 435 clean sheets in 1,560 covered team-matches, an overall arithmetic rate of 27.88%. Serie A’s 32.05% therefore sits above the combined five-league benchmark, while all four other individual league rates are lower.
The ordering is close at the bottom: the Premier League recorded 25.86% and the Bundesliga 25.56%. At the top, Serie A was followed by Ligue 1 and La Liga. These are observed differences in aggregate rates, not explanations of why those differences occurred.
Limitations
This analysis applies only to the covered 2025-26 sample. It should not be read as a claim about matches outside that coverage, and the completed-match convention means the figures are limited to matches included under that rule.
Because the denominator is team-matches rather than fixtures, the percentages should not be compared with a fixture-based rate without recalculation. The figures are also league-level aggregates. They show which league had the highest observed rate, but they do not establish a causal relationship or identify any factor that made one league lead another.
Frequently asked questions
Which Big Five league had the highest clean-sheet rate?
Serie A had the highest rate in the covered sample, with 100 clean sheets from 312 covered team-matches, equal to 32.05%.
How is the clean-sheet rate calculated?
It is calculated by dividing aggregate clean sheets by covered team-matches and multiplying by 100. The calculation is 100 clean sheets divided by 312 team-matches for Serie A, for example.
Why is the denominator team-matches rather than fixtures?
The stated convention is to use covered team-matches, not fixtures. Each league’s rate in the table follows that denominator.
How large is the covered sample?
The comparison covers 96 teams and 1,560 covered team-matches across the five leagues. Completed matches only are included.
Does the ranking explain why Serie A led?
No. The ranking is a descriptive comparison of aggregate observed rates. It does not prove causation or identify why the rates differ.