Little Secrets about #DataScience and Basketball

One of the coolest experiences we've had as #DataExplorers was the pleasure of collaborating with FC Barcelona and their Sports Performance super-team, especially Franc García , Xavi Reche Royo and Jairo Vázquez Guerrero .

Well... today I'm going to tell you a few little secrets...

1. The network of trust

All this began thanks to the network of trust that we have been building, personally and professionally, for so many years.

Our esteemed Joan Guàrdia Olmos connected us with Alfons Freixes , who gave us the opportunity to join EUNCET , which in turn allowed us to meet Franc García , who introduced us to his colleagues...

In #DataScience too, take care of your network.

2. Crystal clear

Imagine a senior unit director saying so precisely...

"We come here to win everything, Ray. The objective is to discover competitive advantages that allow us to win more. Can we find out what factors of weekly training have an impact on match day?".

Apart from the classic characteristics of any set of objectives, in #DataScience we need them to be very specific, quantifiable and connectable with data.

Straight to the point.

3. Balanced admiration

The basis of this project was a good dose of mutual admiration among all team members. Nothing to add about how well FC Barcelona does it, but we Butler Scientifics do it great too.

We all respected each other for our know-how (and for accepting what we DON'T know) and that made the road very easy.

4. Creativity

I recently read that...

"Creativity is intelligence having fun".

Surprising as it may seem to you, #DataScience also gains a lot from it. We came up with the idea of adding new data to the existing one that contributed a lot to its automated exploration.

For example, did you know that the important thing is not to sleep well or badly, but to be regular during the week?

That nuance of stability or variability of health emerged from our neurons as a potential source of competitive advantage.

5. We did it!

Ok. It can always be done better but, after hundreds of hours preparing data, some more reviewing progress together and only a few minutes of our #AutoDiscovery, we managed to find some of those competitive advantages, especially that...

The HEALTH of the player during the week gives more clues about his performance in the match than the training.

Something like this was already known, but here we added the STABILITY approach: you can have stress or not; it's okay. The problem is when sometimes you do and sometimes you don't!

The whole process, the results and their interpretation by professional basketball coaches are available in an article that was published a few months ago here:

Of course, If you want to have a copy just let me know! :)

Oh, one more thing ...

Any #DataScience project is meaningless if there are no CALLS TO ACTION.

FC Barcelona Performance Team (and other sports clubs) now have new tools to gain those vital split points in the performance of their players.

It's time to put them into action.

I'm in.