The Impact of Data Science on Modern Day Football

According to a study executed by World Atlas in 2020, football was the most popular sport worldwide with a fanbase of approximately 4 billion people. This huge following has significantly impacted the football industry from a financial perspective, with the sport becoming an industry that is capable of generating large amounts of revenue. Consequently, many of the world's wealthiest individuals and groups have invested into football with the aim of growing their wealth further.

Despite football appearing to be a profitable opportunity for investors, the increase of competition within the market has made it extremely challenging for investors to make these aspired profits. Therefore, investors have needed to explore a variety of opportunities in order to gain a competitive advantage within the market. This explains the introduction of data science in football, with many football club owners investing into developing technologies in order to gain an advantage against competitors.

The history of data science in football

The first account of data science being used in football was during the 1958 FIFA World Cup in Sweden. This involved the Brazilian national team using psychometric tests to measure the teams football performance, however results were not fool-proof due to this approach being in its infancy. These test results suggested that the "world's greatest player", Pele, should be omitted from the squad for being deemed to be "infantile" and "lacking fighting spirit". The results were proven to be inaccurate as Pele was kept in the squad and proceeded to score 6 goals in the tournament, including 2 goals in the final which saw Brazil win the trophy. This concluded that more research into the implementation of data science in football was required to better understand how it could be used more effectively in the sport.

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The next major development in the use of data science in football occurred in the late 1980's with the introduction of AC Milan's "Mind Room" unit which was lead by Dr Bruno Demichelis, the first ever sport psychologist in Serie A. The "Mind Room" involved AC Milan building a psychology department which used a combination of stress relief therapy with cognitive training and neuroscience driven by player data. This approach proved to be very effective with AC Milan winning 21 major trophies between 1986 and 2009. The success of the "Mind Room" was the first major breakthrough for the use of data science in football and encouraged many other football clubs to follow this approach and build on it.

In more recent times, football clubs have began implementing data science beyond their own team and player performances, with clubs now using data analysis in their recruitment processes and to analyse the tactics of competing clubs. An example of this is the 2015/16 Leicester City team who successfully used data analytics to recruit players that fitted the clubs tactical approach, which, in turn, resulted in the club defying 5000-to-1 odds to win the Premier League title. Following this outcome, many clubs adopted Leicester City's data science approach in their recruitment processes by analysing player performance metrics, such as 'pass completion rates', 'goal probability added' and 'successful aerial duels'. These metrics represent only a minority of metrics that are analysed by data science specialists at football clubs worldwide.

What next for data science in football?

The revolution of data science in football observingly is almost at its peak, with most of the world's professional football clubs growing their data science teams and acquiring new data technologies to use at their clubs.

At present, a technology that is making advancements at a rapid rate is artificial intelligence (AI), especially in the world of football. These advancements include football clubs being able to use new tools that can automatically collect real-time data from video recordings of games and training sessions, which can "track" players, the ball and the team's performance. Additionally, these tools can "track" key factors, such as abnormal ball possession and frequent areas of ball loss, which, in turn, opens up new opportunities for more data-driven decisions. Overall, these AI tools benefit the whole structure of the club, from coaches who can gain a better understanding of their team and opposition teams, to the players who can understand more ways that they can improve their performances. Meanwhile, these tools can also benefit the recruitment team who can better understand the qualities required for players to successfully fit in at the club; these include a variety of sociological, psychological and physiological qualities.

Summary

Data science has been involved in the world of football for decades. However, it has recently become more in demand amongst football clubs worldwide, due to the constant development of technology and the reputation it's built for having a huge influence on success within football. This demand has encouraged an increase of football clubs investing towards data science teams, technologies and research. Consequently, it could be forecasted that data science will continue playing a huge role in football for decades to come. Additionally, it could even be argued that data science might take over the world of football and become a necessity for football clubs to remain competitive at the highest level. Nevertheless, it is evidently an very exciting time for everyone involved in data science and football.