Big data has long since found its way into match analysis in football. In their master’s thesis, two students at BFH Wirtschaft investigated how data can also be used for training. The term “sport” originally stood for having fun, distracting oneself or enjoying oneself. Today, sport has evolved, is marketed aggressively and interpreted in many different ways. It has long since ceased to be a purely recreational activity. Today we speak of the economisation of sport. Sporting leisure fun is now about intense experiences and the staging of events (Penz 2004, p. 5). It is almost impossible to separate competitive and elite sport from the economy. Recent developments have had an impact on athletes as well as many other actors, such as consultants, managers, coaches or even sponsors (Schützeneder 2019, p. 13-14)￼. Professional men’s football is symbolic of this. The financial value of football players has increased exponentially, so that their employers view them more as investments than as people. These circumstances are leading clubs to orient themselves more and more towards the processes and structures of commercial enterprises. Added to this is the optimisation in all areas through digital transformation.
Big Data influences training
Digitalisation has changed professional men’s football on and off the pitch. Technological progress is of great importance for this research work. Digitalisation is creating potential in both sporting and economic performance. So-called big data now also has football firmly in its grip. This opens up completely new possibilities in match analysis and the resulting coaching, but also expands the requirements profile for a coach (Memmert and Raabe 2019, pp. 1-2). Thanks to technological progress and data generation, pre-match and post-match preparations, analyses, scouting, medical care and marketing, for example, can be optimised. However, the full potential of the collected data has not yet been exhausted. Clubs and coaches are constantly trying to optimise the processes. The sports science models and methods have not yet met the needs of practice. Nevertheless, the data and technologies generated have already caused changes in the everyday life of professional men’s football. However, further development of the methods must take place so that the flood of data can be used optimally (Memmert et al. 2016, pp. 3-4). This research explored the changes to date and the future possibilities of coaching professional men’s football. The focus was on the data-based analysis of individual athletic as well as team tactical performance. The resulting changes in the everyday life of football coaches were included in the study. An outline of the digitalisation trends in professional men’s football was drawn up and the impact of the trends was analysed.
Game analysis needs more data use
Data science in professional men’s football is of much greater benefit in the physical and medical area than in the technical-tactical area. Today, mainly quantitative data-based indicators have an impact. The measured values provide great added value in injury prevention as well as in the development of physical performance. The various analytical methods have optimised load control and monitoring. The load limit of football players can be measured and analysed by combining different data-based methods with subjective treatments and surveys. Future technological possibilities could further optimise the load control. On the other hand, in the field of match analysis, the transfer from sports science to practice needs to be further advanced. Today’s mostly quantitative data-based measurements have little influence on the technical-tactical area. In this respect, qualitative analysis based on video data continues to dominate and is an integral part of pre-match and post-match preparation as well as individual tactical training. In quantitative data-based match analysis, key performance indicators (KPI) must find their way into practice. Based on positional data including ball tracking, combined with artificial intelligence and pattern recognition, data-based technical-tactical analysis will be able to make the difference between victory and defeat. Until these methods are implemented, coaches face the challenge of combining existing metrics with individual analytical skills to gain competitive advantage. In addition, the current realities in professional men’s football have changed the tasks and ways of working of coaches and their staff. Digitalisation and the increase in staff have turned them into interfaces analogous to a larger company. The staff of a team is now made up of experts in their respective fields. Video analysts, performance physiologists and data scientists are widespread. In addition, there is the scouting department, which has undergone a major change due to data science. Today, the analysis of video data and other data-based measurements are part of scouting. Nevertheless, subjective observations are irreplaceable. As long as the personality of football players cannot be measured, full automation of scouting will not be possible.
Data science for technical and tactical development
The practice requires that the methods of data science in professional men’s football have a direct influence on sporting success. Recommendations for action should be automatically suggested to the coaches without having to carry out an additional interpretation of the data. Sports science should create the transfer of knowledge into practice. This view must be viewed critically, especially in the field of professional men’s football. Clubs and associations should also see themselves as responsible. By integrating specialists such as data scientists or data analysts into the organisation, the practice could also take the initiative with regard to knowledge transfer. Another possibility would be cooperation with universities. Despite the difficulties of knowledge transfer, the topic of data science has already brought about major changes. Data-based analysis is particularly useful in the physical and medical fields. The technical-tactical benefits, on the other hand, are lagging behind. The longing for new key performance indicators from data-based game analysis is great. As long as artificial intelligence cannot be implemented, data-based match analysis will stagnate. Examples of open and data-savvy coaches like Gerardo Seoane show that certain indicators can be combined through personal analytical processes and subsequently serve as useful inputs for technical-tactical development. Technological skills and an affinity for data analysis are not yet fully part of the current job profile of professional football coaches. However, the digital transformation will not stop in professional football, analogous to the overall economic development. It would not be goal-oriented if all the positive effects of digitalisation were not applied. But this requires openness and interest on the part of the coach.
This is an excerpt from the master’s thesis “Digitalisation in professional men’s football – How is coaching and the economic perspective changing due to ongoing digitalisation?
1] Penz, Otto (2004): Praxis und Symbolik. On the Economisation of Sport. In: Kurswechsel: Zeitschrift für gesellschafts-, wirtschafts- und umweltpolitische Alternativen (2), pp. 7-14. 2] Schützeneder, Jonas (2019): Pro coaches between sports journalism and sports communication: Springer Fachmedien Wiesbaden.  Memmert, Daniel; Raabe, Dominik (2019): Revolution in Professional Football. Mit Big Data zur Spielanalyse 4.0. 2nd ed. 2019. Available online at https://doi.org/10.1007/978-3-662-59218-2. 4] Memmert, Daniel; Raabe, Dominik; Knyazev, Alexander; Franzen, Aljoscha; Zekas, Lukas; Rein, Robert et al. (2016a): Big Data in Professional Football. Analysis of positional data of the Bundesliga with new innovative key performance indicators. In: Leistungssport 46 (5), pp. 21-26. Available online at https://www.researchgate.net/profile/Daniel_Memmert/publication/309203092_Big_Data_im_Profi-Fussball/links/5804fbb008aef179365e5b3d.pdf, last checked 23.05.2020 .