The 2017-2018 La Liga season is now seven matches into the season. Málaga CF is winless. Deportivo Alavés broke their losing streak with a win in their last match. Sevilla FC is playing well and trying to stay close to the leader, FC Barcelona. As an Oracle employee and soccer fan, I enjoy looking at the statistics for numerous fútbol organizations. In this blog, my focus is La Liga, the top professional association football division of the Spanish football league system. I am planning posts around other leagues and a series of blogs building up to the World Cup this summer.
Being a numbers guy, I find data visualization enjoyable. This is especially true within the world of sports. With regard to soccer specifically, I like to look at statistics and find the stories behind the numbers. For instance, which teams are ranked high but have a low percentage of clean sheets? This would either imply their strikers are the ones most responsible for the team's success or their defensive players are the ones holding them back. How about teams that are ranked high but have a low number of 'goals for'? This suggests either that the keepers are the ones that are having the larger impact on the team or their strikers really need to step up. These are the kinds of questions that sports fans love to ponder!
However, the time-consuming analysis it takes to answer these kinds of questions can be frustrating. This is where data visualization comes in. Instead of creating multiple tabs in a spreadsheet and picking/pulling/editing numbers, you simply point/click/drag variables in a DV tool and you quickly see the answers to your most complex questions.
As in my previous fútbol post, I will use the statistics found on the Footystats website. From this site, I copied and pasted the data I wanted. You can download the spreadsheet here. Next, I imported my work into Oracle Data Visualization and began to visualize specific stats around the La Liga season. Below are my findings.
Above is a graphic that shows all the teams with at least 10 points. The darker, wider colors indicate teams with the higher percentage of clean sheets. Real Sociedad de Fútbol either has a problem with their defense allowing too many goals or they have really great strikers that are keeping the team ranked well. Honestly, it's probably both.
This is the value of using data visualization to analyze your numbers. It provides visual insight into the weight and importance of the variables impacting your business and helps you find the story behind the story.
Next, let's look at the relationship between a high ranking and the number of 'goals for'.
In the above graph, the teams with the higher number of 'goals for' are represented by the darker, wider columns. CD Leganés has managed to remain one of the better teams without scoring a lot of goals. This suggests that either the keepers are really good and are keeping the team afloat or their strikers need to improve. Just like in the previous graph, it's probably a combination of both.
Again, this is why data visualization is so useful. Finding hidden gems in your data that otherwise may not have been discovered and therefore—making your data more relevant.
Let's switch the focus to teams without many points.
This is called a 'Treemap' graph. All of these teams have less than 10 points. The larger the box, the more 'goals for'. The darker the box, the more 'goals against'. So... we are looking for teams with big boxes and lighter colors. Getafe Club de Fútbol is the team that stands out. This is a team that is not living up to it's potential. They are on the cusp of being a good team and competing with the better teams in La Liga.
This is the value of data visualization. It is easier to find the hidden gems in your data when you leverage DV tools. Oracle Data Visualization makes your information more useful than ever.
If you like what you see, visit www.oracle.com/goto/datavisualization to learn more about Oracle Data Visualization and get your free trial.
If you already have Oracle Data Visualization, here is the "dva" file for this analysis. The password is "LALIGA" (without quotes), all uppercase.
Also, for current Oracle Data Visualization customers, be sure to visit the new Oracle Analytics Library and download sample files to take your analytics to a new level.
Lastly, don't take our word for it, see what analysts are saying about Oracle Analytics Cloud here.