How to Create Contextualised Data Visualisation for Football

By Salvo Tudisco

21-October-2022 on Users

7 minute read

In this blog, we’d like to introduce you to Salvo Tudisco, a business professional with a passion for football. Salvo combines his expertise with a love of football in order to create contextualised data of the game using data visualisation tools such as PowerBI. But what does this mean exactly?

 

We’ll let him explain in this must-read article…

 

The Data Context

 

Hello! My name is Salvo Tudisco. I’m a 33 year-old Italian who currently lives in Barcelona. Like you, I’m a football freak. I love the game, and strongly believe that contextualised data can provide football clubs of any level with useful insights that can help them improve the performance of the team, individual players and day-to-day work at the club.



To this end, I recently created a Twitter account called TheDataContext which promotes this. Let me explain what all of this means.



Data in the right context can tell amazing stories, and my aim is to collect and analyse data, mainly from academies and amateur teams, in order to provide an advanced analysis with dynamic visualisation.

 

I want to stress the word “dynamic” here, because, for me, it’s extremely important that the people who actually use the data can “play” with it. 

 

For this type of visualisation I recommend PowerBI, a business intelligence tool that allows us to create data models and comprehensive visualisations.

 

For example, check out this Power BI report on xG I made recently, along with the explanation of what you’re seeing on my Youtube channel.

 

Heatmap Nacsport Power BI

 

I chose academies and amateur teams because I’m a grassroots football coach and this is an environment where I feel comfortable. In addition, I strongly believe that data and dynamic analysis should support every club, including those that don’t have the budget for expensive equipment.

 

It’s my firm belief that putting data at the service of academies can provide a powerful tool which can aid the development of young players.

 

The Process of Creating Contextualised Data

 

Before we get to data visualisation, there are two important steps that must come first:

 

Filming

 

In the photo below, you can see me setting up my camera to film a match. While it’s certainly a bonus to have it, you don’t need fancy, professional equipment to film a game. A simple smartphone can do a decent job.

 

Filming a football game

 

Collecting Data

 

Ok, let’s talk a little bit about the video analysis tool which allows me to collect my data…Nacsport Scout.

 

This photo shows me in the middle of the data collection process using Nacsport.

 

 

Using a detailed button template, it’s possible to register any part of the game you’d like to analyse, such as passes, shots and interceptions. In Nacsport, these main events are called Categories.

 

But more than this, you can also add contextual data to each category. In Nacsport, you do this using buttons called Descriptors. For example, XY coordinate data can be added to the data set. You do this by using the Nacsport graphic descriptor tool. Simply click where the action happened on the field to register it.

 

Nacsport Graphic Descriptor Contexualised Data Football

 

As I said before, context is key, and this is why Descriptors are so important to the analysis. You can add as much information to the Categories as you want.

For example:

 

Imagine you want to register the moment when a pass is released. In our analysis template, would would first click the Category “Pass”. After this, we click the descriptor buttons to add the context. For passes, standard descriptors might include:

 

1. Long / short pass

2. The player who made the pass

3. The area of the field the pass was made (using the graphic descriptor)  

 

But we don’t have to stop there. We can add even more context using other descriptors. We might want to know, for example.

 

1. In which phase of the game the pass occurred? Defensive transition / offensive transition / set piece?

2. The game situation at the moment of the pass. Where we winning, losing or drawing?

3. Did the pass break through the defensive line of the opponent?

 

One of the best things about using Nacsport is that the limit of the data you can collect really is your imagination. Because the analysis templates are completely customisable, you can add as much, or as little, data as you want or need.

 

Data Visualisation with Context

 

In the following images, you can see some examples of data visualisation, created with Python and PowerBI in Context.

 

If you want to know more, please visit my Twitter account and Youtube channel where I’ll be posting weekly analyses. At the moment, they are mostly in Spanish but, rest assured, there will be more content added soon in English.

 

If you made it this far, then clearly you are football freak for me, and I can’t wait to speak to you over on Twitter! Thanks for reading this article. 

 

And from all of us here at Nacsport, we’d like to thank Salvo for taking the time out from his busy schedule to write this article for us. We look forward to seeing much more football analysis content from him in the future.

 

If you would like more information about Nacsport or creating sports data visualisation, get in contact with us and we’d be happy to give you more information and free 30-day trial.

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