Over the past two decades, data analytics emerged as a key in every aspect of our world, business, media, sports. It is the process of obtaining raw data and interpreting it to improve decision-making. Football has been collecting the most data for the longest time: however, it is the most complex in the sports world. Plenty of money is being spent on developing data collection, and more importantly, improving the ability to interpret it. From here, the role of data analysts is becoming increasingly important.
With the rise of technology and the growth of datasets nowadays, football analytics is evolving rapidly and emerging in many fields in the game. As we follow, we will briefly talk about the main areas of applications.
In scouting, data is the heart of this process. It can help you generate options in making better deals, saving time and money. For instance, Liverpool made a great signing in 2012, not a playing star but a data analyst, Michaels Edwards. Working with a group, including a four-man research team, realized as a football analytics dream team, they could analyze performance data to scout for players that fit in Jurgen Klopp’s playing style. With higher quality and quantity of data, Liverpool made excellent purchases such as Mohamed Salah, Alisson, Virgil Van Dijk, and Andrew Robertson forming a bedrock in winning the Champions League Trophy followed by the Premier League, ending a 30-year wait for the title.
Data analysis is translating a match into numbers and stats to interpret how the team and the players performed. Statistics like ball possession, number of shots, shots on target offer a guide of how the team has played: moreover, there are some new indicators like expected goals, expected assists, number of passes, pass completion rate, etc. These measures and indicators provide a framework for achieving goals and monitoring strengths and weaknesses to improve in the attack, defense, and build-up phases of the game.
Youth and player development is a field where data has an essential role. Smaller teams depend on data analytics as a tool to predict players’ abilities and potential. This creates a cycle: developing prospects, improving hidden talents, and selling them for a profit. Teams like Ajax have emerged as a great example of developing excellent prospects like Frenkie De Jong, Matthijs de Ligt and made about $190 million profit from their sale. Interpreting the data and reports formed of your players gives you the quality in making success, not buying it.
In conclusion, data is growing in importance in all life areas including the complex world of football, and money is invested in this world to make the most profit. The question is how will data influence the football game more in the future?