AI Artificial Intelligence: Football against the enemy

Artificial intelligence in football, through big data, has made it possible to reduce uncertainty in many of the industry's own processes: analysing performance and spotting talent.

The human-machine relationship has become standardised in all professional, social and recreational processes, changing the collective mindset of people and, therefore, their attitude and behaviour in their interaction with the world, something that has transcended all industries and businesses, including sport. The terms artificial intelligence and big data are fully standardised in the analysis of the game and the performance of the footballer and his team, as well as in the reduction of uncertainty in the search and acquisition of talent in the transfer markets.

Data and artificial intelligence soccer

From probability models to distributional models, advanced statistics channel behaviours based on the different game situations that can be measured. Humans, with their judgement and experience with the game over time, have managed to open a way for the machine to adapt to it in an attempt to reduce chance, trying to model when a player performs and responds based on the needs and events of the game previously chosen.

From the selection and observation of situations and realities that have already happened before and frequently, artificial intelligence and advanced statistics articulate functions and mathematical models to measure reality, helping to complement the work of the human being; a complement that streamlines processes, reduces doubts and helps to make better decisions. At Driblab we believe that this whole process has become one of the most useful for football professionals.

How does AI football work?

For example, if the functions of a winger within the team are standardised as much as possible by the spirit and evolution of the game, we will be able to measure it automatically if the machine understands and stores all the events within a match that correspond to all the left wingers. In that way, we are knowing how a player should perform in that position and we will know when he is doing well and when he is not.

As in all processes, and even more so in a sport like football, where one of its greatest enemies, chance, has a powerful influence, refining these processes and making them more complex will be the basis of advanced statistics applied to football, as well as other sectors that try to prevent injuries or measure physical performance in each training session. We will only have to know the variables better in order to teach them to the machine as keys in its subsequent work. This is the motive and objective of the data industry in football, which is why Driblab was born and continues to grow, becoming one of the references in the consultancy sector supported by big data and artificial intelligence.

We are Driblab, a consultancy specialized in the statistical analysis of players and teams; our work is focused on advising and minimizing risk in professional football decision-making in areas related to talent detection and footballer evaluations. Our database has more than 180,000 players from more than 180 competitions, covering information from all over the world. Here you can learn more about how we work and what we offer.

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