Coach Diego Alonso arrived at the Uruguay National Team replacing Oscar Washington Tabárez who had left them in a very tight spot as they were showing poor results and they only had a few games left to get their ticket to the 2022 World.

He proved everyone wrong

However, his arrival was a complete success and they won their last four games and Uruguay got a direct ticket to Qatar 2022. This is no coincidence, Alonso's working method is completely different from Tabarez's, as it is based on a much more modern working method than that of his predecessor, based on an exhaustive statistical analysis using big data.

They will have to beat Korea, Portugal, and Ghana

In fact, to prepare for their group stage matches against Korea, Portugal, and Ghana, Alonso reviewed more than 200 metrics for each opponent where he can review issues such as shots on goal, expected danger, the areas where the rivals attack more, where they are vulnerable, among others, just to anticipate as best as possible everything that could happen in each advance, each individual duel.

Looking for predictability in an uncertain game

"We are generating metrics that try to measure merit and analyze performance from a statistical perspective. The game is a bit unpredictable, but in the end, advanced statistics and big data generate probability models and what we do with Uruguay is try to visualize through the data everything that could have happened even if it doesn't happen," explained Alejandro Arroyo, spokesman for the Spanish consulting firm Driblab, which provides advanced statistics to the Uruguayan national team.

"If a player is performing well, but in certain metrics, his teammates are not helping him, we play with those probabilities in areas such as expected goals, expected assists, and expected danger. We see how he is performing beyond the result because in soccer there are many variables that we try to isolate," he adds.

Why so much data to plan a match?

This trend is already common in major professional sports in the United States, mainly baseball, but in soccer this tendency is just growing, to focus much more on the probabilities that the numbers yield.

Uruguay, therefore, took the risk of having as detailed an analysis as possible of how their opponents perform, including individual performances. This leads them to predict under what conditions a goalkeeper is most likely to catch a cross into the box, depending on the thousands and thousands of crosses that have been delivered and the area where the ball lands.

Relevant analysis

"The data allows for very relevant analysis. In the area of video analysis, it complements a lot of what we do during video production. The data is the support for a lot of information, the backup. It helps us confirm a lot of patterns that we can identify through the image. It is a very good complement to the image," explained Andrés Paysee, a member of Uruguay's technical staff and coordinator of the AUF's video analysis area.

They looked for patterns

"During the match, they can confirm a lot of patterns that are being repeated based on what you saw previously of your own team and your opponent's team. It can awaken some conclusion that, suddenly, through visualization you don't see so clearly," he added.