Since Diego Simeone took charge of Atlético Madrid, among other features, their team is widely regarded for their strong defense. In the current season they have conceded 12 goals in 29 games, recording a very low average of goals conceded per game (0.414).

In order to give some perspective, I plotted three charts containing goals scored per game vs goals conceded per game considering the last 17 seasons of the Europe Top 5 Leagues (starting from the 1999/2000 season; 1632 data points).

As we can see from Chart 1, the Chelsea team of the 2004/2005 season are the only team to have a lower goals conceded per game ratio (0.395) than the current Atlético Madrid team (0.414). No other team have a ratio lower than 0.500.

atleti-1

Chart 1 – Goals for/game vs goals against/game in the Top 5 Leagues in the last 17 seasons.

More over, 4 out if 12 goals that Atlético Madrid have conceded in the Liga 2015/2016 have been against Barcelona. If for a moment we exclude these goals conceded against Barcelona (Chart 2), Atlético Madrid’s ratio drops incredibly to 0.276.

atleti-2

Chart 2 – Goals fro/game vs goals against/game in the Top 5 Leagues in the last 17 seasons (added Atletico Madrid of 2015/16 excluding games vs Barcelona).

It may also be interesting to see how Atlético Madrid’s goals conceded per game ratio has changed during seasons (Chart 3). The 2015/2016 ratio is very low even when compared to the the 2013/2014 season (when Atlético Madrid won the Liga and reached the Champions League Final).

atleti-3

Chart 3 – Goals for/game vs goals against/game in the Top 5 Leagues in the last 17 seasons (Atletico Madrid seasons in red)

Maybe, Atlético Madrid are the best (or the second best) defensive team of the century.

Barcelona’s 2015/16 season is being characterized by a large number of missed penalties, obvious to everyone. Now, this is clearly unusual for Barcelona, since they have missed 8 penalties in the Liga for the 2015/16 season, while missing just 5 in the previous six seasons (from 2009/10 to 2014/15). What about compared to other European teams? Is such a poor performance so unusual? If we consider just the last seven seasons, we find out that there are other examples just as bad, or even worse.

Let’s consider the ongoing 2015/16 season in the European top five leagues. Chart 1 shows the plot of taken vs scored penalties by the 98 teams of these five leagues. The two lines of 100% and 50% conversion rate can help us compare the conversion rate of different teams, since the different number of taken penalties can be misleading. Barcelona are placed relatively bad here, below the 50% conversion line, but they are not the only team below this line. What makes them look ‘that bad’ is the fact they they have taken a lot of penalties (15), much more than the rest (no other team has more than 10).

penalties-t5l

Chart 1 – Penalties taken vs scored in the Top 5 Leagues for the 2015/16 season (98 data points).

Chart 2 shows the same type of graph considering the last seven seasons in the Liga (140 data points). Barcelona’s seasons are represented by the red dots. Here it is more visible that Barcelona’s penalty conversion is much worse than in the previous six seasons (all red dots are above the best fit line). As we can see, a considerable number of teams are placed in or below the 50% conversion line, showing similar performance to Barcelona’s. Obviously, the worst example here is Racing Santander, since during the 2011/12 season they managed to score just 1 out of 6 penalties.

penalties-liga

Chart 2 – Penalties taken vs scored in the Liga during the last 7 seasons, from 2009/10 to 2015/16 (140 data points).

A much more comprehensive plot is shown in Chart 3, where are plotted the last seven seasons of Europen top five leagues and Champions League (878 data points). As we can see here, Barcelona are bad, but we have seen worse (and this just considering the last seven seasons).

penalties-last-7-seasons

Chart 3 – Penalties taken vs scored in the Top 5 Leagues and in the Champions League during the last 7 seasons,from 2009/10 to 2015/16 (878 data points).

Lionel Messi has scored 6 free kick goals with Barcelona during the ongoing 2015/2016 season, setting a new personal record for most free kick goals within a single season. He has undoubtedly improved his free kick shooting technique and currently he is one of the best free kick takers in the world.

Messi has now 22 free kick goals in official club competitions. This is a very high figure but not particularly mind blowing, considering the number of games and seasons he has played at the club. Maybe interesting and spectacular is what we find out when we classify Messi’s free kick goals according to the result of the game when they occurred (Chart 1).

free-kicks-messi

Chart 1

As we can see in the above chart, the wast majority (19 out of 22) of Messi’s free kick goals have arrived when the team needed the most, when they were losing (3 goals) and drawing (16 goals). This data highlights once again Messi’s particularity of being relevant and influential in the most important moments of the match.

They say “imitation is the greatest form of flattery,” but when you’re a sports journal that wants to be taken seriously, imitation is not just wrong, it is also a crime called plagiarism.

Last Tuesday (February 23rd, 2016), after the Arsenal vs Barcelona Champions League match, I posted two stats (involving Messi and ter Stegen respectively) on my Twitter account:

 

The next day (Wednesday, February 24th, 2016), the Spain-based sports journal Sport published in their website two articles talking about the stats in my tweets, exactly those stats, but just in a narrative way:

http://www.sport.es/es/noticias/barca/ter-stegen-mas-decisivo-que-buffon-cech-neuer-4923143

http://www.sport.es/es/noticias/barca/messi-siempre-acude-rescate-4923153

In both pieces, they didn’t mention me as the source of those data. I find this very unfair and offensive, especially considering the time I spent in working on those stats. Such a pity.

When I became aware of the ter Stegen article, I got in touch with the author through Twitter. He claimed he didn’t write that piece (although his name was listed as the author). He said he got the data from my Twitter account and that he forwarded them to his colleague who wrote the article.

He promised to make the necessary correction on the article and to credit my Twitter account as the source. Though he did it later, my Twitter handle was misspelled.

A few hours later, I read the article about Messi and thought it would be pointless if I have to go after them one by one. The Messi article had a different author.

Then I decided to write this, as a constructive way to avoid this. It is really a pleasure and a huge consideration to be mentioned and for my work to appear in big media but not referencing other people’s work is something I don’t find tolerable.

Barcelona are not as solid defensively as they were last season. In 44 games they have already conceded the same number of goals (38) they did in the entire 2014/2015 season (60 games).

In order to further explore this, we made 3 charts comparing defensive parameters of Barcelona with all the other teams of the five main European leagues. For comparison reasons, we added Barcelona’s performance last season (2014/2015).

A short summary of the charts below is that this season, Barcelona allow opponents to have more shots and chances than during the 2014/2015 season. As a direct consequence we have more goals against and Barcelona’s keepers are forced to make much more saves.

defense-1

Chart 1 – Shots against/game vs. % of shots against that were goals.

defense-2

Chart 2 – Shots against/game vs. goals against/game.

defense-3

Chart 3 – Shots against/game vs. goalkeeper saves/game.

We analyzed the passing game of 26 Liga goalkeepers (500+ played minutes) in terms of passing typology, frequency and accuracy. Although he has played just 4 games in the 2015/2016 Liga season, Marc-André ter Stegen has been also included, with the aim to serve as a point of reference. As we’ll see in the further 4 charts, the passing game of both Barcelona’s goalkeepers is similar, and very different from all the other goalkeepers in the Liga.

gk-1

Chart 1

Chart 1 shows the typology of passes (per 90 minutes) of Liga goalkeepers. Both ter Stegen and Bravo play considerably more short passes and less long passes than other goalkeepers. A high number of short passes is also typical of Rayo Vallecano’s goalkeepers (Juan Carlos, Toño and Yoel), a team which plays in a similar way as Barcelona, in terms of high possession. The high number of short passes is a consequence of these goalkeepers attempt to combine a lot with defenders or defensive midfielders who position themselves close to the penalty box when the goalkeeper has the ball.

gk-2

Chart 2

Chart 2 shows the total passes per 90 minutes and the percentage of those that are long passes. Here, the tendency that Bravo and ter Stegen have to play less long passes than the rest of the goalkeepers is more visible. Bravo has 35% of his passes classified as long passes (ter Stegen has 36%) while all other goalkeepers have more than 55% of their passes classified as long passes (the average Liga goalkeeper has 76% of passes as long ones). Here it has to be noted that the number of total (attempted) passes per 90 minutes doesn’t seem to be a ‘special’ indicator of ‘passing game’, as a goalkeeper may be ‘forced’ to distribute a lot when his team allows many shots against.

gk-3

Chart 3

gk-4

Chart 4

Chart 3 shows the overall pass accuracy in relationship to total passes. Bravo and ter Stegen are very close to each other, having a considerably higher pass accuracy (respectively 84% and 82%) than other Liga goalkeepers (all less than 67%). As it can be observed in Chart 4, Barcelona’s goalkeepers are superior in both long and short pass accuracy, with ter Stegen being a bit more accurate in long passes (a typical feature of the young German goalkeeper).

Messi is not scoring as much as in his peak goal-scoring form but he is currently scoring the ‘most decisive’ goals of his career at Barcelona.

This is the conclusion we arrived at based on what the scoreboard says before Messi scores in a particular game.

We will show how we arrived at this conclusion based on a series of charts below.

seasonal-2

Chart 1

The first chart (Chart 1) shows the distribution (in %) of Messi’s career goals at Barcelona according to what the score was when his goals occurred, calculated separately for each season. As we can see, the % of goals of each category are highly scattered.

In the current season, Messi has 62% of his goals in those moments of the game when Barcelona have been losing or held to a draw. This is a higher % than in any of his previous seasons (since 2008/2009, when he was a regular starter).

This is a much higher % than during the last season (36%), for example, where he had a high percentage of goals (38%) scored when Barcelona were already 2+ goals up in the scoreboard.

The same argument can be made for the 2011/2012 season, in which Messi scored 73 goals for Barcelona, but 38% of which was scored when the team was already leading by 2+ goals.

The second chart below (Chart 2) shows the same distribution of Messi’s goals scored in La Liga and in the Champions League. His % of goals scored when the team is losing or held to a draw in the CL (52%) is considerably higher than in La Liga (42%).

competition

Chart 2

Analyzing Messi’s goals like this presents us an interesting set of data: his goals against Real Madrid.

With 21 goals, Messi is El Clásico’s all-time highest goalscorer, but the most stunning fact is that he has scored 17 or 81% of these goals in the most crucial moments of the game when Barcelona have been losing (8 goals) or held to a draw (9 goals).

el-clasico

Chart 3

Is Messi “finished”? He’s only just started.

 

It is hardly a secret that not all goals in football have the same importance. Their relative importance depends on many factors, such as the opponent, competition, etc. Quantitatively measuring (giving numerical value) the relative importance of goals scored is not easy, since any logic used might have its natural dose of bias and subjectivity. Here we show a way that probably is not some new or innovative idea but maybe presented in a different way. As it will be explained and illustrated further, it represents a way of dividing or categorizing goals and assists in terms of their relative importance.

The main and simple logic here is valuing goals/assists according to the result of the game prior to the moment when the goal/assist occurred. Simply put, one goal/assist has not the same importance scored/assisted when the game is in equilibrium and when the team is winning by 2 or 3 goals. To achieve this categorization, goals/assists for individual players (just goals for teams) have been classified, as the following images show.

g-dist-player

g-dist-team

Here, we have distributed (in percentages) each player’s goals/assists and each team’s goals according to the result of the game in the moment prior to the goal/assist occurrence. For example, Benzema has zero goals/assists when his team is behind in the score, he has 43% of his goals/assists when the result is in equilibrium (0-0; 1-1; etc) and so on. For teams, Barcelona scores 10% of their goals when they are losing, 32% when the result is in equilibrium, 24% when they are winning by 1 goal, 18% when they are winning by 2 goals, and 16% when they are winning by 3 or more goals.

These distribution charts give us the possibility to do many analysis. For example, we can see that Atlético Madrid are an extremely efficient team. They have concentrated 87% of their goals when the game is in equilibrium or when they are winning by 1 goal. They have 0 goals scored in those moments of the game when they are winning by 3 or more goals. The same can be said for their main forward, Griezmann. He has 86% of his goals/assists in the most crucial moments of the game.

In contrast, Real Madrid and their main forwards (Cristiano, Bale and Benzema) have ‘inflated’ their numbers with goals/assists in moments of the game where the winner is practically decided. For example, Cristiano has 35% of his goals/assists when Real Madrid is winning by 3 or more goals and he has 0 goals/assists when his team is losing.  Similar numbers are displayed for Bale and Benzema, although not at such a high contrast.

Barcelona and their main forwards (Messi, Suárez and Neymar) are situated in a middle ground between Atlético Madrid and Real Madrid, showing a good balance. Messi, yet scores the most important goals and gives the most important assists, having 57% of them when the team is losing or the game is in equilibrium.

Maybe a final note would be that this way of categorizing goals/assists is more representative than doing it taking into account the ‘quality’ of the opponent, based on opponent’s ‘name’ or ‘ranking’. Simply because the name or ranking of a team might not coincide with the specific difficulty a match might have. For example, one late winning goal against a very low ranked team is more important than the 4th goal scored in a 4-0 win vs Real Madrid (or any highly ranked team). From the other hand, these charts should not be read ‘literally’ and some context is needed when being analyzed. For example, we can’t exclude the possibility (as it has happened in various precedents) that games with 3+ goals differences might turn around, hence, goals scored in those moments gain a big value.

Last Wednesday, in the Copa del Rey match against Espanyol, Lionel Messi scored his fourth seasonal goal coming directly from a free kick. This was Barcelona’s fifth seasonal free kick goal, if we add Neymar’s equalizer against Atlético Madrid.

In the below image you can find a schematic visualization of these free kick goals, along with some free kicks that hit the goal post and/or cross bar.

free-kicks

So, thinking about fouling Barcelona’s players close to the penalty area and preventing their run? Maybe that is not a great idea.

The importance that Sergio Busquets has in the Barcelona team is crucial in many aspects, one of them being his ability to effectively press in the attacking third of the pitch, when Barcelona is attacking and lose the ball. Here is where Busquets excels his game. Considering all Barcelona’s players, he has the most balls won back during this season, exactly 145 balls won back in 23 appearances in Liga, Champions League, and FIFA Club World Cup (Rakitic is second with 122).

Busquets’ ball recovery in the attacking third of the pitch has two very positive and straightforward consequences for Barcelona:

  • Prevents the opposition team from starting a counter attack.
  • Enables Barcelona to build a very fast attack when the opposition team is not well positioned (since they expected to start their own counter attack after they recovered the ball). Actually, Barcelona can score in less than 2-3 seconds, starting from when Busquets intercepts the ball.

During this season we have been able to witness a large manifestation of the second point expressed above. Actually, Barcelona have scored 5 goals which are directly a consequence of Busquets’ ball recovery (interception), the last one being Suárez’s first goal vs Real Betis during the 16th round of the Liga. These goals and their respective sequences are listed as below:

1 – European Super Cup, vs Sevilla: interception by Busquets – Suárez – Goal

2 – Liga, round 8, vs Rayo Vallecano: interception by Busquets – Suárez – Neymar – Goal

3 – Champions League, game 3, vs BATE Borisov: interception by Busquets – Alba – Neymar – Rakitic – Goal

4 – Liga, round 11, vs Villarreal: interception by Busquets – Neymar – Goal

5 – Liga, round 16, vs Real Betis: interception by Busquets – Suárez – Goal

A graphical representation of these 5 goals can be seen in the below image:

busi-int

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