An artificial intelligence (AI) predicts the best strategies of football players |

Scientists from the Alan Turing Institute in the UK have developed an AI algorithm to predict which team has the best chance of winning the World Cup in Qatar. It mainly takes into account the results of previous championships.

However, important factors such as the performance of individual players are left out. It would therefore be interesting for it to be supplemented by another algorithm, developed in 2020 by data scientist Carter Bouley. He analyzes the different types of passes that players can make, in order to calculate the best strategies.

It should be noted that this algorithm was not made for the World Cup in Qatar, nor for a specific championship. It is simply a way of using statistics and computer science to develop the best game strategies for football players.

It’s mainly passing-based, so it could be very useful for teams like the Spanish national team, whose passing game is often one of the keys to their success. The ideal is to optimize them, so that they involve the minimum expenditure of energy and that they can also be chained with precision until they end up in the goal. There is no magic formula, but at least this algorithm can help design the best possible strategies.

The algorithm of the perfect pass, even beyond Qatar

Of course, not all football players are the same. They are more or less qualified and more or less trained. However, optimizing their passing strategies can help them all.

That’s the goal of this algorithm, which was trained using data from 358,753 passes, made in 380 games, involving 20 teams. Several factors were taken into account. First of all, it must be determined whether the players are in their own half or that of the opposing team. For another, minute-by-minute results and full match results. In addition, the passes were drawn graphically, with the ends of the field being the X and Y axes. Finally, the type of pass was taken into account: normal, header, cross, corner, throw-in, goal kick or free kick.

With all this data, artificial intelligence was put into action to search for patterns that linked a specific type of player pass with better results. They discovered data that a large proportion of passes are missed at a very short distance, less than 5m. Furthermore, between 15 and 30 m, “ there are far more successful passes than missed passes, and after 30m the proportion of successful passes drops dramatically, while missed passes begin to level off“.

Another key factor turned out to be where on the pitch the pass is made. For example, the closer they get to the opponent’s goal, the more missed passes they make. Logically, this is a very important area, so it is important to know which strategies work best in this location.

Special attention for footballers

In this algorithm, the individual role of the players is taken into account. As Bouley himself explained at the time, ” if the model predicts that a pass will occur with a probability of 0.8 and it is made, 0.2 is added to the players pass score“. In contrast, ” if the pass has not been made, minus 0.8 for the passing rating of the players”. The average is then calculated on the number of passes made by the player, in order to define an average pass risk score. “This score makes it possible to compare the players through the risk taken and passed in the pass“.

Because, logically, it is not only a question of knowing which are the best passes. You also need good players who can execute them. It also means that they must be able to take risks, but without being too bold. There is virtue in the middle ground. This also applies to winning a football match. It doesn’t matter if you are at the World Cup in Qatar or in a local championship.

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