# A Systematic Literature Review of Intelligent Data Analysis Methods for Smart Sport Training
## 1 Introduction  
The rapid development of Information Technologies (IT) has had an impact on almost all areas of our lives. Computers, smartphones, smart watches, and other mobile and pervasive technologies change the way we work and how we perceive the outer world. Furthermore, robots are replacing human workers in various industries, especially in the era of Industry 4.0 [1]. There is no doubt that our civilization has to adapt to the many changes that are the consequence of modern technology [2].  
Sport training is not an exception, and is also an interesting area, where modern technology is revolutionizing the way athletes maximize their performance and compete on a higher level than ever before. By the same token, with the increase of participation trends in mass sporting events [3], as well as the involvement of people in sporting activities, there is a need for systems/applications that can guide, help, and support people in enjoying their activities [4]. For instance, many people all over the world cannot hire a professional sports trainer due to the many barriers, e.g., financial. On the other hand, extensive research that links intelligent data analysis tools/methods with sport science is building new intelligent solutions that support all phases of sports training. Smart Sport Training (SST) is a type of sports training, which utilizes the use of wearables, sensors, and Internet of Things (IoT) devices, and or intelligent data analysis methods and tools to improve training performance and/or reduce workload, while maintaining the same or better training performance. This means that SST implementations range from simple tasks, such as introducing wearable devices [5] in a sports training session, performing intelligent data analysis of a session, to much more complex artificial trainer implementations, where a coach is replaced by a smart agent which manages all the aspects of training, except for actually performing the proposed exercises for the trainee [6]. The workloadreduction can apply either to the athlete or his trainer. For an athlete, an improved training plan means he can achieve better results with the same, or even less, amount of training, and for his trainer, this means the assistance of IT technologies can automate parts of his coaching routine.  
The research area that represents the intelligent data analysis methods in the domain of sport training is now becoming very popular. Despite the popularity of this research area, literature on this subject is expanding quickly. In this paper, we compile the latest advancements in this domain. We review the intelligent data analysis methods that are applied in different sports, either individual or team sports. Moreover, we study how mature the studies in the field are when measured according to the technology readiness level [7].  
The remainder of this paper is structured as follows. Section 2 outlines the fundamentals of sports training. Section 3 presents a description of the research methodology used to conduct a systematic literature review, Section 4 identifies and classifies the intelligent data methods used in the field. Section 5 presents all the reviewed studies, sorted by the sports in which they were conducted. Section 6 analyzes the findings, and provides answers to the proposed research questions, together with future challenges. The paper is wrapped up in Section 7, where conclusions are drawn.