5 significant ways big data analytics is changing the world of soccer in Europe

The collection of big data in football is nothing new to the world’s most popular game. In fact, the collection and utilization of big data in football can be traced back to the 50’s where chartered accountant Charles Reep first used this form of analysis. Using statistical analysis has come a long way since then and today most of the major clubs in the world are using this method to gain that extra advantage over their competitors.

Big data refers to the mountains of data that is gathered using high tech software. However, this data is meaningless without the trained experts who have the ability to make sense of it all and present it in a way that managers and club owners can use to make informed decisions. Joaquim Cardona, former Digital Business Manager of Barcelona said in an interview that “Data is everywhere, what is very scarce are professionals capable of understanding it”.

 What we are seeing today is an increase in those individuals capable of understanding this data and as a result, it is being used in new and exciting ways that are revolutionizing the game in every aspect. In this article, we will be taking a look at 5 of these to illustrate how big data analytics is changing the world of soccer in Europe.

1. Allows punters to make informed decisions on which team they bet on

Sportsbetting is a big part of football which has been the case for many years. Today, punters are able to view the odds of a match long before game day. These odds are based on a number of complex factors that are formulated using big data and translated into a percentage that can be easily understood. For example, the Champions League odds this year has Bayern Munich as a favourite to win, with Manchester City coming second. These odds are very useful to punters and have a massive impact on the number of people who tune in to watch the game.

2. Creates new ways of assessing player performance

In a sport where millions are spent on purchasing players from across the globe, owners and managers need to know that their money is being well spent. The use and application of big data analytics is very important in this regard. During training sessions, clubs will have a team of data scientists, whose sole purpose is to gather data from the players. Using data captured from video footage, analysts are able to pick out in which areas players are weakest and formulate strategies to improve them.

Some clubs even take this one step further by using the raw data to develop algorithms using artificial intelligence. This is of course much quicker than using human analysts and is far more reliable long term. By analysing a player’s performance, both at training sessions and on match day, the coaching staff is able to make sound decisions with regards to the starting lineup, or even who the next transfer will be going forward.

3. Revolutionising advertising in football stadiums

One of the more creative ways that big data has been used in football has little to do with how the game itself is played, but more with marketers who advertise at live football games. During the 2018 FIFA World Cup, the stadiums were equipped with over a thousand cameras. These cameras are now being used to analyse fans’ behaviour whilst watching the matches by picking up the tiniest of details in their facial expressions, such as their eye movement and body language during the game.

Using artificial intelligence these systems pick up when the fans are most engaged and present this data to companies with big advertising budgets, say Coca-Cola, for example. Coca-Cola would then be able to advertise their product on the big screen at a time where it will receive the most engagement from fans.

4. Streamlining the recruitment and retention  process

Recruitment and retention of players is what makes and breaks teams.The big dogs in charge of overseeing the finances of the clubs take huge risks when spending millions on players to boost their chances of holding up a trophy. Equally as important is knowing when the best time is to transfer a player whose time at a club has come to an end. When recruiters go to the smaller clubs and look at players who show potential, they collect the data of these players which can be used to persuade the magers to go ahead with the purchase. On the other hand, data analytics can be used to translate the true value of a player to the team, and the organisation as a whole.

5. Using data collection to predict the moves of the opposition

Data analytics can be used to study the moves of the opposition, which in turn can be used to formulate strategies that give a team the upper hand on game day. Understanding the opposition’s playing dynamics down to the tiniest detail assists the coaching staff in formulating their tactics in a way that will give them that extra edge come game day.