New feature

How to use Play areas

Explore our new feature

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We have welcomed another feature into our statistical bundle, called Play areas. It is a graphical, simple-to-read feature, but full of insight and useful information. You can observe Play areas as a standalone feature, but you can also complement it with our other similar graphics like Heatmaps or Player average positions graph for a wholesome and nuanced analysis. One thing is certain – it offers a new dimension of knowledge that can be useful to all of you interested in more.

The Play areas feature consists of three graphics. The first one shows the distribution of play of both teams combined, while the other two graphics represent the Play areas for each team, with three arrows indicating the side from which the team attacks. As the individual ones provide a different insight, Play areas can almost be considered as two features in one.

Areas are divided by color-coded sections. The more orange (or yellow in the dark theme) the section gets, the concentration of play in that area is higher. So one glimpse is enough to notice not only if a team dominates, but how much and in which areas too.

For example, in the Manchester City vs. Tottenham match in the screenshot, despite the final 2-2, you can see at a glance who ran the show. Almost half of the time was spent in front of Spurs’ goal, which is visible not only in the color, but in numbers too; 49% of playing time happened in front of Spurs’ goal, and only 11% in front of City’s. Just to point out, this insight cannot be read out from possession only, as it was, with 55% in City’s favor, only a bit lopsided.

In the other two graphs you can see the efforts of each side on the pitch. Again, you can see that Tottenham efforts consisted mostly of defending, as the sections are orange in front of their own goal, while almost no play happened in front of Man City’s goal. Or in the stats language: Spurs had three total shots on goal, and City had exactly ten times more than that.

Particularly interesting are the arrows showing on which side the play happens. The first screenshot below is Manchester City’s average Play area graph from the Premier League 2019/20. It is an aggregate of all matches City played this season, and in every single one of them the arrow was longer and sections more intense on the left side. Or in numbers, 42.2% of their play comes from the left side, 24.8% is in the middle, and 32.9% is on the right.

This obviously shows that, when it comes to attack, they mostly pressure from the left side and push really high in the goal area. You can clearly see why when you take a look at Raheem Sterling’s Heatmap (above), which is intensely red on the left and stretches all the way into the goal area. It perfectly reflects his style of play, marked exactly by this; deep entrances into the penalty area. On the right side, however, Bernardo Silva plays much differently, as seen in his season Heatmap too. He doesn’t enter the goal area that much, but rather turns to the the middle, switches sides and combines further away from the goal.

The general forward play by City can be supported by other numbers too. Out of total 10925 touches, City made 6564 or 60.1% of them in the opponent’s half. A reflection of the way City create their play on the opponent’s half and put the pressure really high.

Moving on to the next example, here we have Portugal vs Lithuania match from the Euro qualifiers, which ended with a 6-0 Portugal victory. You can see that Lithuania’s ineffectual attempts to score relied completely on one side. And even though they had very few shots on target, all of them were made from the right side, and Portugal’s defense had no job at all in the middle and on the left.

As you can see, the Play areas feature can give an indication of what happened in a match in which one side completely dominated, but you will here find some other interesting anomalies too on the level of a single match.


Play areas can also show just how much one team can be dependent on a single player. To show you this, we’ll move slightly east from Portugal and use the example from Catalonia.

Barcelona’s two matches in this season’s Champions League will do perfectly fine to show what Leo Messi means to them. The match against Borussia Dortmund that ended as a goalless draw will serve this purpose because Messi entered the game pretty late, in the 59th minute. In the other match, against Inter, he was in the starting lineups, and put on an amazing performance with an assist, 6 key passes and 2 big chances created, deserving this way the 9.1 SofaScore rating. The highest rating in the match that ended with 2:1 Barcelona victory. We will examine Barcelona’s structure of play in the opponent’s half with Messi and without him.

Barça started the match against Borussia in 4-3-3 formation with Griezmann, Suarez and Fati in Messi’s position. In this match 43% of active play happened in the middle of the pitch, and 32% in front of Borussia’s goal. Barcelona played through the flanks, and as the arrows show, they attacked mostly from the right side covered by Fati, together with Sergi Roberto who played quite offensively. Also, a large number of Barcelona’s pushes came from the left, while there was almost no play in the middle. The concentration of play was the scarcest in the ninths that should have been covered by an offensive midfielder; no wonder that Barcelona directed only one shot at the goal.

We come to the point where you see how crucial Messi is for Barcelona’s game. Except for scoring goals, he creates play and connects the middle with the attack. Here Barcelona had nobody to fill that space, so they tried to stretch the opponent thin and score. In this match they had the largest number of crosses in the season (19), but as they don’t have players to dominate aerial duels, nobody could capitalize on them.

Barça started the match against Inter with Messi on the right wing, but his position on the pitch was in reality much different. As opposed to the game with Borussia, Messi enabled Barcelona to concentrate the pushes through the middle of the pitch. Arrows show us that Barcelona had many more attacks in the middle, and the most important indicator are the last two ninths showing that the highest concentration of play happened in front of Inter’s goal. Messi stabilized Barcelona’s play and their number of crosses dropped to only 6, in comparison with the striking 19 against Dortmund.

From the statistical point of view, Barcelona’s play improved, and Messi finished the game with the 9.1 rating. Instead of forcing the play through wings and spreading the opponent thin, Messi contributed in depth and solved the match with his creativity.

As you can see, you can draw a ton of information from one single graph. And when you combine it with some of our other features, with that much information and insight, you really have a solid basis for a bulletproof football analysis.

For now, the Play areas feature is available on Android, but you will soon be able to find it on iPhones too.