Some call it football, some call it soccer but to many of us it is simply the Beautiful Game. Regardless of what you call it, football is a big business these days.
Well, that was the question I asked myself when Gareth Bale was transferred from Tottenham Hotspur to Real Madrid for a staggering sum of €91,000,000. That’s a lot of zeros for a single player! However, let’s not forget the thousands of other players moving between clubs every season.
That got me thinking…
How much money are we talking about?
Which countries are producing globally sought after players?
Which countries are spending exuberant amounts of money for top talent?
Here is my story of what happened next…
With all these questions curiosity took over and I started looking for data. Football transfer data is not easy to come by, there is no ‘data warehouse’ I could point Tableau at, well at least not one I could find. It seemed that the only approach was to roll up my sleeves and acquaint myself with the world of screens scraping. So I dusted off my Python skills and was quickly able to write a short script to feed my data addiction.
It took a while to collect all the data I needed, about 24 hours to be exact. Don’t you just love when your little bots are doing all the work while you are asleep? I hope your data addiction is a little easier to come by but there is always freelancer.com if you need help.
Do you need to know how to program to get started?
But according to President Obama, you should learn how to be a hacker anyway
So finally, armed with a glass of red and Tableau, I put my feet up and started to get intimate with my data.
After a few minutes of exploration some very interesting patterns started to emerge. One of these was the business of payment for players moving between clubs. This originated around 120 years ago, however almost 75% of all transfers happened only in the last 10 years. Thus my key intention became to show the global nature of football transfers over the last 100 years. It’s a no brainer that a map would be the best visualization to illustrate this, just add a timeline and presto, you end up with the following animation*. 113 years of football player transfer data compressed into a 60 second history lesson. It starts slowly but the growth in the last few decades is clear to see.
The animation told a great story. At the same time this only whet my apatite for more detailed analysis. As a result I started to peel the onion a little more, which allowed me to explore, taking this to the next level…
Make this an interactive experience with the hope that it would become personal. Give users the ability to quickly explore information that is important to them.
Is my country a source of football talent?
Has that changed over time?
In fact since the time it was uploaded, many international publications have indeed used this visualisation to tell their own stories from their country’s perspective. I was thrilled that this went beyond what I envisaged at the start!
This exercise showed the true power of collaboration that can be achieved using data visualization. A table of numbers would never create the same level of engagement.
Explore for yourself.
My other requirement, a more personal one, was for the visualization to be beautiful and intuitive, so that even a child could use it. Simplicity is not easy, I tend to approach my visual design challenges with this favourite quote in mind:
“Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.” by Antoine de Saint-Exupéry, Airman's Odyssey
In order to achieve this, the map had to take the centre stage and all other elements had to play a support role without distracting the viewer from the main act. In fact it’s the countries that are the main attraction, hence the map background is set to 50% transparency so as not to compete for attention.
I use minimal bold fonts, borrowing from the iOS 7’s minimalist design guides. The reason for this approach is to avoid “hijacking” the user’s attention from their focus on the story played out on the map.
A Colour pallet of orange and blue is also deliberate to cater for possible colour-blind viewers - which can be as high as 8% in male population.
And one last thing, the image of a football is there just in case someone was unsure about which football code we are talking about. This is a common challenge here in Australia where we have four football codes competing for attention.
When designing this player transfer visualization, the focus was to highlight the growing number of countries involved and the speed at which the transfers spread across the globe. The boys from the Baker and Kelly show summed it up perfectly by comparing the global and rapid spread of player transfers in this visualization to a fungus.
The visualization became a good example of how you can tell a great story with data.
I hope this post will inspire you to find some data and make it come alive. There is a story in every dataset; you just need to ask the right questions.
You can find more football visualisations on my blog eyeseedata.com
* I had to create a video from my workbook as Tableau animation is not yet available on the web. I am sure the product team is secretly working on it. The video was created using ScreenFlow on Mac OS X and an HD version published to Vimeo.