What Impact is Big Data Having on Soccer?

Throughout the last few years, big data has become an increasingly vital component of many different sports across the globe. One of the most prominent examples of its influence relates to the NFL's Big Data Bowl, which seeks to encourage the next generation within the analytics community. Moreover, the use of such data has also proved to be highly effective in the soccer world, with numerous teams utilizing the technology to increase their chances of both short- and long-term success.

As a result, we're going to look at how big data has affected soccer while also considering how further analysis has changed the outlook of the sport.

Big Data's Influence on Soccer

While the role of a side's coaching staff cannot be underestimated, the introduction of analytics and big data into soccer has significantly reduced the time spent on analyzing statistical patterns, as the role of the process is to computationally reveal patterns and trends which relate to human behavior. Because the analysis method can deal with such vast data sizes, it's therefore able to enhance the total number of results that can then be studied. In turn, from a coaching and management standpoint, this allows for tactical developments to be made around the strengths discovered through analysis of individual players' performance.

This numbers-driven influence has resulted in clear-cut differences to on-field performances over the last decade. The German national team, who won the 2014 World Cup, built a database that analyzed varying data points from both their team and their opponents. Crucially, this success can be attributed to data-related speed improvements, with the average time a player had on the ball falling from 3.4 seconds in 2010 to 1.1 just four years later.

The Sport's Wider Use of Data

Aside from noticeable on-the-field differences, big data is also having an impact on player transfers. Within soccer, the sudden abundance of player-level data has seen squad recruitment methods arguably go through the most significant transformation. Moneyball, which is a market value analysis theory, has long been utilized by Liverpool Football Club since Fenway Sports Group took over the reigning European Champions. As of January 2019, the Reds had the 12th-highest net spend in Europe and, despite that, have achieved back-to-back Champions League finals and a second-place finish in the Premier League, which highlights the noticeable improvement that analytics have had on their recent transfers.

Furthermore, data has also influenced supporter-focused elements of soccer, such as fantasy gaming sites and sports betting. Many of the existing fantasy soccer platforms, for example, provide selection advice based on acquired analytics and statistics to assist prospective gamers with their player picks. Moreover, users can also find soccer-related data to take into account at sports betting platforms such as NetBet, where you can browse data across a wide array of varying sports, leagues and players including finding first and last goal data, along with goals per match averages.

Soccer Isn't Looking Back After Embracing Big Data

Following its introduction, soccer has been late to the trend of utilizing data to its full potential but, having now accepted the analytical side of the game, the sport is thriving like never before. In addition to improving coaching methods and on-field performances, big data has also revolutionized fantasy gaming platforms and the sports betting market.