Academic Journal - Journal of Business Strategy - 2020
Lichtenthaler, Ulrich
prematch & post match
This article offers evidence from a best-practice case study. It examines how Liverpool Football Club integrates data analytics and artificial intelligence with human knowledge to attempt to help give teams a competitive advantage during games. It shows that adopting ai solely is not enough but the way it is combined with an analytics team can help enhance game analytics.
One of the key findings of this article is that AI is not a standalone replacement for football analytics, instead they help enhance the managers/coaches/analysts expertise and intuition. Emotional intelligence such as Jürgen Klopps in this article is important for interpreting data, motivating players, making decisions under uncertainty. This allows coaches to make informed tactical decisions and match preparation and adjustments during the season
Using standard AI analytic tools may give short-term gains to a team but these can easily be implemented by their competition. The competitive edge for teams is when they use AI alongside existing data is used to make club decisions. In this article Liverpool say that their football success is not related to solely the data they collect or the tool they are using but more on how they implement them in to their day to day such as tactics, training, preparation or match management.
One good use of using Ai for analysis in football when coaching has to deal with uncertainty, unexpected events, human variability as football is a dynamic game. The analytics can inform coaches of the possibilities and predictions and then they can decide what to accept, ignore or adapt for their team. This provides them with predictive insights or simulations of how their changes may affect outcomes and how different decisions they may make such as formation, substitutions, training loads affect the team and helps keep them better information.
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Summary - Pre match Analysis
In a pre-match setting, ai analysis can be used to hep with studying opponents, their patterns and their tendencies such as pressing, passing structures and set piece routines. It also helps coaches and analysts to make more informed decisions for their match plans based on statistical tendencies and predictive models.
This emphasises how data driven insights can further aid a teams preparation and ensure data is used collaberatively to plan strategy and select players
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Summary - Post Match Setting
Ai analysis can be used to help review the performance data after a match. This could be data such as player movement, tactical success or physical metrics. Ai can then help to create a summary of what worked or failed in the players strategy and decision making. They can then feed this evaluated outcome back into their long term learning, allowing them to refine tactics and players training.
In this article they outline how Liverpool has been using AI analysis for continuous learning and improvements and to help close the loop between data, intuition, and team management, building a strong system.
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