Big Data in Football Sports

Big Data in Football Sports has become a highly efficient tool thanks to the multiple possibilities that offers in a field in which it was still untapped. As in other economic and social sectors, the sports industry has not wanted to stay behind and has signed up for this technological revolution , incorporating it as a really valued utility for the technical stuff’s tasks. In this post, we will find out what is Big Data about, how can it be obtained, why is it that interesting and some of its uses, specially in football sports, as big clubs and elite academics are already doing,

What is Big Data?

bigdata en el deporte del fútbolBig Data are these data which are on the net, the cloud or in files and are accumulated in big quantities, user’s information of any system who in a specific moment, they’ve incorporated in a file. They may have been obtained on the Internet, phones, through polls, etc; and they can refer to anything we can imagine where do we live, what do we eat, what do we buy, our habits, our hobbies, our health… The thing that makes Big Data different from any other file is its size, as it requires specialized technology, but especially the possibility to analyse its content, for example, establishing relations or statistics in a way in which a use can be made of all this accumulate information.

Big Data in Football Sport

For a normal user, if he thinks about Big Data the first thing that comes to their mind are marketing campaigns, market studies or sociological studies. Maybe he is not that this utility arrived at the sport’s world many years ago. And, again, American major leagues (football, hockey, basketball, baseball…) have gone ahead implementing this utility, not only to study the performance of their teams and the statistics of the players but also to analyse the signing market. Like this, from a certain level, there is no longer a coach or a coaching staff that does not use and take advantage of the benefits this tech apps offer.

As every business will use one analysis program or app, or another; it is true that they actually exist some KPIs and variables that can be repeated when considering the different parameters:

  • Generics: ball possession, percentages, effective time of game, possessions duration.
  • In attack: passes, shots, centres, lost balls, dribbles, win position with or without ball, corner, action when stopped ball, direct free kicks, counter attacks, climbs on the left football lane, right, central, etc.
  • In defence: won and lost duels, entrances, football fouls, cards, ball recoveries.
  • KPIs winners: goal, shots at goals, passes goals, opportunities…

Recording all this data is not a new thing, the new part is its precision and the programmes capacity to cross them between them automatically, so the technic staff will have more information which will help them making decisions.

Big Data in scouting

big data en el futbolScouting actually consists in collecting data about the players, teams, strategies and any other interesting aspect for a technic so, once this data is processed and analysed, it can support the coach or the sportive director.

We cannot forget that football clubs are still business, for what they will always be looking for the necessary tools and instruments and the newest informatic apps and make them available to the coaches. Like this, they can optimise their task.

Scout’s work of observing, evaluating, creating statistics tables and other documents which save time and help preparing them, have found powerful help in terms of analysing to justify and to support their observations in Big Data. However, Big Data in football has gone even further, as it has found lots of applicable areas in this sector. For this reason, especially in the last two years, independent specialized in sportive analysis businesses have been emerging. Considering that only a single football game can extract almost eight million data, of which only a 30% could have been collected manually, we can conclude that traditional scouting has achieved a qualitative improvement.

Scouting and its evolution

The scout is an essential figure inside the sportive team as the biggest coaches have always had big scouts by their side

When elaborating a precise report quickly and in profundity was necessary, this helper who had big knowledge and references of all the other players, own and rivals, could make a dossier or support and assess his coach, but always being based on his memory, notes and also intuition.

But Big Data in Football Sports, have also contributed to the evolution of this task: Business Intelligence (BI) allows them to analyse data and develop strategies considering even more data, helping in the making decisions process. Knowing this mechanisms and knowing how to perfectionate a professional dossier based in data mark the difference between the past and the future of scouting.

We already know that Real Madrid is working on a regular basis with their own app, Bernabéu Digital, even though they exist other even more generic apps that can be equally effective: InStat Scout, WyScout, MediaCoach, OptSport

Big Data in signing footballers

bigdata en el deporteNowadays, Big Data is more than advisable when it comes to signing footballers: is essential. Thanks to globalisation and Big Data in football, any club can sign any football player, no matter in where the club is or even the player.

The candidates who will participate in the most important leagues of the world are thousands and not all of them are that famous, even though they can be excellent options, something we will be able to know based on their data and statistics.

When a club comes out on the market searching for a specific player profile, it already knows what it needs, the place he has to cover in the squad, the money it can spend and, again, this tools will be helpful to narrow the search and guide it to names which adjust more to their needs.

If we also include that, nowadays, there is many more data about any signing of the ones that have never been completed, including their medical history, we could conclude that the club’s bet for this new football player will be safer and less risky as when they were done only considering some parameters and relying a lot on the intuition.

So, there is no doubt in the fact that the use of Big Data in signing players increases its efficacy, helps creating a better squad and refine investments, avoiding errors, that specially in modest teams, can be lethal.


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