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Artificial Intelligence (AI) Machine Learning (ML) Natural Language Processing (NLP)
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AI in Football: A Disruptive Innovation?

  • Marwen Hjiri
  • Author Marwen Hjiri
  • Published October 14, 2022

From aiding in navigation to performing surgeries, it is fascinating how Artificial Intelligence (AI) is transforming our everyday lives. It is no longer a futuristic vision but a technology that is currently being deployed in a variety of sectors including transportation, finance, criminal justice, and healthcare. The increasing penetration of AI has helped in augmenting human capabilities in multiple ways; improving decision-making, risk mitigation, leveraging systems performance, and optimizing business models (West & Allen, 2018). Such developments have aided in enhancing efficiency along with generating substantial economic and social benefits. Sports is one of those domains in which AI is being increasingly leveraged nowadays. In this blog post will introduce and examine how AI is being integrated into the sports fields notably in Football.

AI in Sports

A decade back, it would have been impossible for us to imagine that American sports drama Moneyball would become a reality someday. But with the advancement of technology, the application of AI in the sports sector is becoming increasingly common nowadays. Although the application of statistics in sports has been around since the beginning, the use of AI in the field has had a great impact on the level of audience engagement, in creating strategies, and in determining the way sports are played today (How is AI used in sports, 2020).

In the last few years, AI with its real-time statistics has made the world a lot smarter for the sports community including the athletes, broadcasters, and viewers. The AI sports market is estimated to reach USD 19.9 billion by 2030 (Srivastava, 2022). Many factors are identified as contributors to this growth-increased demand for real-time data analytics, tracking and monitoring of players, AI forecasts and predictions, and virtual assistants to interact with and optimize fans’ experience (Srivastava, 2022). In addition to this, AI and Machine Learning (ML) play a crucial role when it comes to talent recruitment, game analytics such as umpire assistance, and training and coaching. So it is safe to say that the adoption of AI-based technologies in the sports industry would ensure improved decision-making processes facilitated by data-driven analysis.

This effective use of AI in sports prompts us to consider the possibility of employing it in the physical education arena. Using AI in this domain would aid in resolving the problems associated with traditional physical education models while also facilitating greater efficiency in terms of both teaching as well as learning (Yu, 2021). The manifestations of AI in this field can be promptly visible in process monitoring and accurate diagnosis which in turn leads to personalized services and intelligent decision-making (Yuan, 2021). As AI functions on data, the more data it gathers the more accurate would be its analysis. In terms of physical education, AI can track the emotion and reflections of the students, while learning, along with their performances i.e. the extent to which they have mastered the motor skills. Such process monitoring would enable the teachers to alter their methodologies in accordance with the requirements of the student. It also helps the students in receiving personalized training that is in accordance with their skills and aptitude. Overall, it, therefore, helps in improving the learning performance of the students.

AI in Football

Football is one of the sports in which the introduction of AI-enabled technology has brought about countless possibilities. Such technology is already impacting football; goal-line technology and video-assisted replays that assist the referees are already in use. Semi-automated offside technology will be used at FIFA World Cup, 2022 in Qatar to track the movements of the players to ensure precise decision-making (FIFA.com, 2022).

Primarily, AI helps in facilitating individualized/behavioral training for the players (Wang & Feng, 2022). Football is a game that mandates targeted training as the physical stamina and attributes of each player are different. Introduction of the AI technology in training would help in capturing the players’ performances on which a quantitative, as well as qualitative analysis, can be performed so that the decisions are not made by purely relying on the experience of the coaches (Qiao, 2022). With the help of AI-assisted wearables and high-speed cameras, large amounts of data such as the player’s heart rate, speed, distance covered, forward pass, penalty kick, and many other similar actions are recorded. Such datasets can help the coaches to gain valuable insights regarding the strengths and weaknesses of each player/ team and accordingly tailor the training strategies (Mirza, 2020). Even the players will get to know their potential and the areas in which they need to improve and thereby optimize their movements to ensure maximum hit rate of kicks (How is AI used in sports, 2020). Thus integrating AI technology ensures augmented coaching while improving the players performances.

Injury prediction is another front on which AI technology would be of immense use in football. In fact, injury prevention is accorded one of the highest priorities due to the associated physical, mental, and economical strain it imposes upon the players, coaches, and clubs. As per recent estimates, the English Premier League clubs incur approximately USD 19-26 million for injury treatments of players (Tedesco et al., 2022). This demands the need for technology that would objectively and systematically monitor and evaluate the player’s performance so that it can be improved while minimizing the risk of injury (Tedesco et al., 2022). AI and ML which have already made disruptive influences in various contexts in clinical medicine such as in disease diagnosis and mortality prediction could come in aid here with their ability to gather and analyze vast amounts of heterogeneous data and identify hidden patterns which otherwise would have gone unnoticed to the human eyes. Many top-level teams have already adopted the technology wherein players are monitored using wearable sensors and smart sensors attached to the training locations, which function using intelligent wireless networking (Qiao, 2022). The data it gathers is used to identify the player’s current physical status and play patterns. Based on this, the AI would predict if a player is susceptible to an injury in the near future and accordingly prescribe the actions to be taken. Thus, AI can play the role of a teammate to the players while also being an assistant to the coach (Qiao, 2022).

The advantages that come with the integration of AI into sports are too vast to be discussed here. It definitely has the potential to serve the interests of many including sports trainers, players, sports companies, advertisers, and spectators.

What the future holds

It is truly fascinating to see how the use of AI in sports has redefined it in the most efficient manner both in terms of playing it as well as watching it. AI has deeply penetrated the domain; there is no going back from drones and big sports monitors. And now with it making a mark in sports analytics, it can be said with certainty that it will shape the way sports are played, viewed, and even marketed.

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