Coaches and players desire and would benefit greatly from easy access to performance data of matches and training sessions (Koekoek, van der Mars, van der Kamp, Walinga, & van Hilvoorde, 2018). They use this information not only to monitor performance but also to plan training programs and game strategy. According to the assessment of volleyball coaches in The Netherlands,1 the two areas which can substantially improve sports training are as follows: (a)Interactive exercises and enhanced instructions, and (b)Providing the trainer with information from live data on player behavior. It is because performance in sports depends on training programs designed by team staff, with a regime of physical, technical, tactical, and perceptual-cognitive exercises. Depending on how athletes perform, exercises are adapted or the program may be redesigned. State of the art data science methods have led to groundbreaking changes. The data are from sources such as tracking position and motion of athletes in basketball (Thomas, Gade, Moeslund, Carr, & Hilton, 2017) and baseball and football match statistics (Stensland et al., 2014). Furthermore, new hardware platforms appear, such as LED displays integrated into a sports court (Kajastila & Hämäläinen, 2015) or custom tangible sports interfaces (Ludvigsen, Fogtmann, & Grønbæk, 2010). These offer possibilities for hybrid training with a mix of technological and nontechnological elements (Kajastila & Hämäläinen, 2015). This has led to novel kinds of exercises (Jensen, Rasmussen, Mueller, & Grønbæk, 2015; Ludvigsen et al., 2010) including real-time feedback, that can be tailored to the specifics of athletes in a highly controlled way. These developments are not limited to elite sport. Interaction technologies are also used for youth sports (e.g., the widely used player development system of Dotcomsport.nl) and school sports and physical education (Koekoek et al., 2018).
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