The current European football season is coming to its end. Last week there was the UEFA Champions League semi-final draw and, in case you don’t know, Juventus will face Monaco while Real Madrid will play against Atletico Madrid. I decided use data STRATABET gave me regarding the European clubs and make an analysis on the highly anticipated Champions League matches. I will write an article analyzing each matchup, today I will talk about Juventus vs. Monaco and soon to write about Real x Atletico.
Assumptions:
In previous texts, I have shown that data regarding the quality of the shots (a metric also known as expected goals, abbreviated to exG) reveals a lot about a team’s performance. Today, I’ll add the shot “location” as another important factor, you will be able to see not only the quality but also the region in which the shot occurred.
Another important assumption is that as the football season in Europe is nearing its end, I believe that there is already an interesting statistical sample to make an analysis of the offensive and defensive performance of a team.
Methodology:
First, I grouped the data provided by Stratabet, and made a subset with only the shots made and conceded by Juventus and Monaco during the current season. I applied a statistical technique called clustering to that data (if you want to know more read the notes at the end of the text) and calculated the average shots made and conceded by each of the teams. The concept is very simple; the shots are grouped per their similarity and form a cluster.
After that, I used Plotly, a tool that allows you to create interactive graphics, and prepared 2 graphs. The idea is to be able to see and analyze the shots (and average shots) for and against involving Monaco and Juventus.
For each chart, I inserted the offensive data of one team and the defensive data of another. That is, a graph with the title “Monaco Attacking vs Juventus Defending” includes all the shots made by Monaco and all the shots conceded by Juventus.
The size of each point in the graph indicates the quality of the chance created/suffered by the team. The bigger the point, the more likely that chance will result in a goal. In addition, by moving the mouse through the points you can see who the team was playing against, which player made the shot, the play type and the outcome of that chance (if it was defended, saved or ended in a goal). You can choose whether you want to visualize all the chances, the average chances (clusters) or only those that have ended in goals.
Results:
In the chart below we can see the performance of the Juve’s attack and Monaco’s defense simultaneously (in other words, the chances created by Juventus and the chances conceded by Monaco throughout this season):
For a better reading of the chart, I suggest that you first display only the data regarding the Italian team. Note that there is a large black “stain” inside the center of the box, which indicates a huge number of chances with a high probability of scoring in that region. By hovering over a few points the Higuain’s is the most frequently seen inside the box, but it is also possible to see a good amount of dangerous shots made by Dybala, Mandzukic, Cuadrado, Pjanic and Bonucci. People who believe Juve is a traditional Italian team that focus 100% of its efforts to defend itself are being deceived. Those who watched the game against Barcelona know that the Old Lady creates a lot of quality chances and the above chart illustrates this fact.
Now leave only the Monaco data on the graph. One notices a big red “stain” within the box, which should be a concern for the principality team. This is a sign that the team in general gives enough freedom for the opponent to shoot in locations and conditions in which the probability of scoring a goal is high, in other words, the team’s defense has been having a questionable performance. It important to remember that in the last 4 Champions League matches Monaco have conceded 9 goals, which is certainly something to be worried about.
To further illustrate the analysis, click the “Clusters” option and direct your attention to the points within the box. Note that there are four relatively large red dots, which further underscores the need for Monaco to urgently improve its defense. This graph indicates a great scenario for Juve’s attack, since its opponent usually allows chances in a region in which the Italian team is lethal.
Next, we’ll look at Monaco’s attack and Juventus’ defense (i.e. the chances created by Monaco and the chances conceded by Juventus in the current season):
Put only Monaco’s data on the chart and you can see why the team is one of the most exciting to watch this season. There are several relatively large spots within the area, forming a red “stain” that extends significantly. Also, hovering over a few points is difficult to find a prevailing name. Falcao appears quite a few times, but the names of Germain, Mbappe and Bernardo Silva are frequent as well. The club clearly has a great offensive momentum, which has charmed many football fans.
After that, display only Juve’s data and you’ll see what it means to be Europe’s best defense. It is possible to note that the black “stain” within the area is neither extensive nor continuous. Juventus’ defensive system simply prevents the opponent from having significant chances in most of their matches. In addition, Juve opponents’ lives become even more complicated since Buffon does not seem to feel aging effects and has impeccable performances constantly. Click on the “Only Goals” option and you will see that only a few chances with relatively high exG could hit the back of the Italian club’s net.
Clicking on the “Clusters” option Monaco’s offensive DNA and Juventus’ defensive solidity will be further highlighted. Notice that the average finishes made by the principality team happen within the area with a high exG, and the average finishes suffered by Juve happen a little further away from the goal and with a relatively lower exG.
Therefore, from the two charts and their respective analyzes it is possible to say Juventus has an advantage in this matchup, especially because of its balance between attack and defense. Monaco are likely to face defensive difficulties in both games, the question is whether their attack will be able to surprise the experienced Italian defense and repeat what they did against Manchester City, compensating for their own defensive deficiencies with many goals.
Observations:
- Stratabet provides data on shots and dangerous moments (attacks with a high chance of scoring but that ended without a shot), I used the two types of data in the charts.
- For the clustering analysis, I used the “kmeans” function of R, considering the location and the quality of each chance. There are several ways to determine the number of clusters to be extracted, I chose the number 6 after doing an empirical analysis on the dendogram of the completions of each team.
- I highly recommend the plotly library for R and Python, the tool is excellent
This article was written with the aid of StrataData, which is property of Stratagem Technologies. StrataData powers the StrataBet Sports Trading Platform, in addition to StrataBet Premium Recommendations.
Algolritmo's founder. I have a bachelor's in Computer Science and a master's in Analytics. My goal is to bring a new perspective into Brazilian football. I'm particularly interested in communicating complex ideas through simple data visualizations.
I graduated in Computer Science and Business Administration at the University of Southern California and got a masters degree in Analytics at the same institution. I have worked as a Data Science intern at companies such as Facebook, Itaú and Looqbox.