Football is a game of goals, tactics, and individual performances, but numbers can tell us much more about what happens during a match. Football stats are used to measure player performance, team performance, attacking actions, defensive work, possession, passing, and many other aspects of the game.
Whether you are a football fan, content creator, analyst, or simply want to understand the game better, learning how to read football statistics can help you look beyond the final score.
What Are Football Stats?
Football stats are numerical measurements collected during football matches and across competitions. They describe what players and teams do on the pitch.
Some of the most common football stats include:
- Goals
- Assists
- Shots
- Shots on target
- Possession
- Passes
- Passing accuracy
- Tackles
- Interceptions
- Clearances
- Saves
- Fouls
- Cards
- Clean sheets
Statistics can be presented as totals, averages, rankings, percentages, or normalized figures such as statistics per 90 minutes. FIFA’s football-data framework uses these different approaches to make comparisons between players and teams more meaningful.
Why Are Football Stats Important?
The final score only tells you the result. Football stats provide additional information about how the match was played.
For example, imagine a team wins 2–0. Looking at the statistics could reveal that the team had:
- 45% possession
- 8 shots
- 5 shots on target
- 1.7 expected goals
Meanwhile, its opponent might have had more possession but created fewer quality chances.
This shows why statistics should be used together rather than relying on a single number.
The Most Important Football Stats
1. Goals
Goals are the most basic attacking statistic.
For teams, goals show how many times they scored during a match or competition. For players, they provide a simple measure of scoring output.
You can also look at:
- Goals per match
- Goals per 90 minutes
- Goals in home matches
- Goals in away matches
2. Assists
An assist generally refers to the player’s contribution immediately before a teammate scores.
Assists are particularly useful when analyzing creative players such as midfielders and wingers.
However, definitions can vary between data providers, so it is important to understand the methodology being used. Opta, for example, has detailed definitions for assists, key passes, shots, passes, and other football events.
3. Shots
Shots measure attempts to score.
A player taking 5 shots has more shooting volume than a player taking 1 shot, but volume alone does not tell us the quality of those chances.
That’s why analysts often combine shots with shots on target and expected goals (xG).
4. Shots on Target
Shots on target measure attempts that are considered on target according to the specific provider’s definition.
Different football-data companies can use slightly different definitions. For example, Opta and other providers have detailed rules for determining whether a shot counts as being on target.
5. Possession
Possession represents the percentage of time a team controls the ball.
A team might have 65% possession while its opponent has 35%.
But possession alone doesn’t determine which team created the better chances. It should be considered alongside shots, chances, passing, and other metrics.
6. Passing Statistics
Passing stats can tell us how teams and players move the ball.
Common passing statistics include:
- Total passes
- Completed passes
- Passing accuracy
- Key passes
- Progressive passes
- Long passes
- Crosses
Passing accuracy is generally calculated by comparing successful passes with attempted passes. FIFA describes completion rate as the percentage of successful actions compared with attempted actions.
Advanced Football Stats
Modern football analysis goes beyond traditional statistics.
Some important advanced metrics include:
Expected Goals (xG)
xG, or expected goals, estimates the quality of goal-scoring opportunities.
Instead of simply counting shots, xG attempts to measure how likely those chances were to become goals.
Expected Assists (xA)
xA estimates the likelihood that a pass or chance-creating action will lead to an assist.
It can help identify players who consistently create good opportunities, even when their teammates do not finish them.
PPDA
PPDA is commonly used as a measure related to pressing intensity.
It can help analysts examine how frequently a team allows passes in certain areas before attempting defensive actions.
Progressive Passes
Progressive passes measure passes that move the ball significantly closer to the opponent’s goal according to the definition used by the data provider.
These metrics are part of the growing vocabulary of modern football analytics.
What Does “Per 90” Mean in Football Stats?
One of the most useful concepts in football statistics is per 90 minutes.
Imagine Player A has scored 10 goals after playing 2,000 minutes, while Player B has scored 8 goals after playing only 1,000 minutes.
Looking only at total goals doesn’t provide the full picture.
Per-90 statistics normalize performance to a standard 90-minute period:
Per 90 = Statistic ÷ Minutes Played × 90
This makes it easier to compare players who have played different amounts of time. FIFA also uses per-90 normalization in its football data framework.
How to Compare Football Players Using Stats
When comparing two players, avoid looking at only one statistic.
For example, when comparing two forwards, you could examine:
| Statistic | Player A | Player B |
|---|---|---|
| Goals | 15 | 12 |
| Assists | 7 | 10 |
| Shots | 70 | 55 |
| xG | 13.5 | 11.2 |
| Goals per 90 | 0.65 | 0.72 |
The numbers provide different pieces of information. A good comparison should also consider the players’ positions, roles, minutes, teammates, and tactical systems.
How to Read Football Stats Correctly
The biggest mistake when using football statistics is treating one number as the complete story.
For example:
More possession ≠ automatically better performance
More shots ≠ automatically better chances
More passes ≠ automatically better football
More tackles ≠ automatically better defending
Statistics become more useful when several metrics are combined with context.
You should consider:
- The opponent
- The player’s position
- Minutes played
- Home or away context
- Match situation
- Team tactics
- Competition level
- Sample size
Football Stats vs Football Analytics
There is a small but important difference.
Football stats generally refer to the numbers themselves: goals, assists, shots, passes, tackles, possession, and so on.
Football analytics involves analyzing those numbers to identify patterns, relationships, and insights.
For example:
Stats: A team had 60% possession.
Analytics: The team had 60% possession but created relatively few high-quality chances.
The first statement describes a number. The second puts that number into context.
Where Can Football Stats Be Used?
Football statistics are useful in many areas of the sport.
For Fans
Fans can use statistics to understand player and team performances more deeply.
For Coaches
Coaches can use data to analyze tactical performance and identify areas that may need improvement.
For Scouts
Player statistics can help scouts identify players whose performances fit particular roles or playing styles.
For Football Websites
Football statistics websites can organize data into player profiles, team pages, league tables, match reports, historical records, and analytical articles.
Conclusion
Football stats provide a powerful way to understand the game beyond the final score. From basic numbers such as goals and assists to advanced metrics such as xG, xA, PPDA, and progressive passes, football data can reveal different aspects of player and team performance.
The most important thing is to understand what each statistic actually measures and to avoid judging a player or team based on a single number.
When combined with context, football stats can turn a simple match result into a much deeper analysis of what happened on the pitch.
