Over the past decade or so, numerous websites have popped up attempting to quantify player and team performances and player value through statistics. Whoscored, FotMob, Opta, Fbref, and I’m sure many others have been tracking numbers to give soccer fans, journalists, and possibly coaches and scouts more concrete player and team analysis. 

Stats are more associated with sports like baseball, basketball, and American football. Given that soccer is a more fluid sport than baseball, has less possession control than basketball, and has less definable stop-start plays than football, it may be difficult to apply stats in the same way. That’s not to say advanced statistics don’t matter in soccer, or that they can’t be helpful for certain purposes. But how much can they tell you? 

It’s complicated, but we’ll break down whether or not advanced statistics matter in soccer.

What were we doing before these analyses?

Not too long ago, people were only keeping track of goals, assists, shutouts (a.k.a. clean sheets), possession, and saves. 

Goals were obviously the most important stat. Goals win games, especially in a low scoring sport like soccer. Players who can score them are valuable, and people who can stop them are also valuable, although not quite as much so (as a former goalkeeper, I can tell you it’s harder to score than to stop people from scoring). 

Basic goal scoring statistics

Assists were next on the list, as setting up goals is a pretty important part of scoring them. Then you would look at goalkeepers and defenders who were part of a defense that weren’t giving up a lot of goals. 

Other than these basic numbers, people just used subjective judgment to determine which players and teams were better than others. You’d watch the game (or a bunch of games), recognize certain patterns that were difficult to quantify (this defensive midfielder is great at closing down space and winning tackles), and argue with your friends about who was better. 

Why did stats in soccer evolve?

Slowly you started to see more in-depth stats evolve from the basic numbers mentioned above. For example, this forward scores a lot of goals, but is he really a good finisher? Let’s see how many shots he takes per game, and how many of those he converts. Ok, a shot percentage is good, but how easy are the chances he’s scoring? Does he get many easy chances, is he creating most of his own shots, or does he need a lot of chances to score? How can you even determine these factors with any sort of concrete numbers?

This rabbit hole led to what is now known as “expected goals,” which quantifies how often you would expect an average player to score a given shot. You add up all of these shots, and you get a number of goals a player should score in a given game or season. You then compare them to his or her number of actual goals, and this tells you whether or not this player is a good goal scorer or not. 

While it’s not perfect, as someone has to define how often a goal should be scored from a given shot (which, while based on some data, is still subject to one’s judgment), it does give you a general idea of whether a player is a good finisher, and whether or not a team creates quality chances to score. 

At the end of the day, goals are what really matter, but this underlying stat can tell fans, journalists, and coaches more than just a simple score line or a number of goals and assists next to a player’s name for the season. 

Now every area of the game has seen continual granularization of statistical analysis in the same way. For instance, you can see how many of a particular kind of pass a player makes in a game – short, medium, long, progressive, shot-creating, and goal-creating (and probably more types). This seems like a lot to take in for the average fan, but it can be interesting for the die-hard fan in addition to those directly involved in the game (coaches, scouts, executives, analysts, commentators, etc…).   

Why are people using stats in soccer?

To a self-professed soccer nerd and former professional player (who was not measured in such a way), these numbers seem pretty cool. They can give you an easier understanding of what to expect in a given game or over a season. 

Writers, analysts, and commentators can come up with talking points based on stats. They can more easily compare player performances using actual data, and they can try to better predict the outcomes of games. They can analyze hundreds of categories to tell a story. 

Fans can use these numbers to (try to) win debates with their friends about which player is better. They can also use them to better understand why their favorite teams or players are performing or not performing up to expectations. On the flip side, stats can also be a source of frustration if the numbers are telling you something, but the coaches or players keep seemingly ignoring it (“why are they playing that guy at defensive midfield, his short passing percentage is terrible”)?

As for coaching and scouting, I assume modern coaches use them extensively. In the old days if you saw a certain player was scoring a lot of goals, this would cause a coach or scout to have a look at the player. Today, if you need a commanding defender, you can see if someone’s aerial duel percentage, number of clearances, and tackles won percentage, and you could now have a better idea of whether or not to scout this player in person. And I’m sure you could use the same principles to scout your opponents. 

Stats only tell a part of the story

At its heart, soccer is a simple game. Sometimes such advanced statistics can overcomplicate things. They also don’t tell the whole story. 

For one, you can miss the forest for the trees. Looking at so many advanced metrics for a midfielder, for instance, you might miss the fact that he holds on to the ball too long, killing the momentum of a build-up or attack (something stats can’t measure). You could miss this fact if you focused on measurable stats like progressive pass percentage, pass completion percentage, tackles won rate, interceptions, and other numbers make him look like a good midfielder. A midfielder who plays slowly can override all these other metrics. 

The same goes for a defender. It’s hard to measure good positioning or how well they close down space, for instance. But anyone who knows the game understands the importance of reading the game and getting in the right spot before your opponent does. Oftentimes the best defenders diffuse a play without having to make a tackle. You cannot measure this part of the game. 

As a fan, sometimes when analysts, commentators, or writers rely too much on stats for their point of view, it can overcomplicate a simple game. This overreliance on stats can also keep those involved in the game from really seeing what is happening. It’s easier to fall back on numbers to make a point, but harder to rely on your own subjective analysis. You can miss valuable insights this way.

I remember watching Christian Pulisic play in a preseason game for Dortmund a few years back, and the biggest thing I noticed was his movement. It was very intelligent. He knew how to find space and when to move into it, either getting himself open to receive the ball in a dangerous area or opening up space for a teammate. You cannot measure this either, yet such actions are vital in a team sport.

With an overemphasis on stats, you can lose the simple conclusions you gain from just watching a game or a player. It can make analysis too robotic and not as insightful as it could be.

Statistics are a guide, the trained eye still knows best

Anyone working in a corporate job has probably heard the term “what you can measure, you can manage.” That’s why I think the importance of statistics in soccer has increased so much. With technology we can measure a lot more than we used to in soccer. And the powers that be can manage things more easily. For players, coaches, fans, and analysts, this can certainly help. 

And many high level professional teams are taking a data-driven approach to scouting and buying players, making coaching decisions, and determining playing style and strategy. 

I do think that numbers can guide you in the right direction for all of these purposes. And advanced stats can certainly help the decision-making process for high level teams. But stats are not everything in soccer. 

Because soccer is such a fluid game, numbers will never be able to quantify everything as it does in other sports. Baseball has very static plays involving a few actions. Football has well-defined plays that last 10 seconds or so before stopping. Basketball, while as fluid as soccer in many regards, has much more control of the ball in a given possession due to the use of hands as the primary control agent of the ball. 

All of these factors make it easier to use statistics to measure things in these sports, as they are more controlled environments. Soccer is more fluid (other than set plays, you don’t have a chance to reset at regular intervals), more chaotic (due to having to use the feet to control the ball), and a lower scoring game (meaning good plays don’t lead to a definable outcome as often), meaning stats will have a harder time measuring what helps win and lose a game. 

A well-trained eye will complete the picture, giving you insight into areas that cannot be measured. That’s why the best teams still have some kind of subjective input into player scouting, and why the data can still be wrong.

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