## 4 Discussion  
Given the current growth of interest in the use of VR technologies for perceptual-motor training in sport, there is an urge to take a number of methodological precautions with regard to their effectiveness before using them to characterize and/or optimize the underlying (perceptual-motor) processes. In this regard, the notions of validity and fidelity are emerging in the literature as relevant predictive criteria. Consequently, the aim of this study was to assess the validity and fidelity of a relay simulator in the most exhaustive way. The overall results suggest that the simulator is, on the one hand, an accurate tool for the measurement of athletes' behavior (validity) and, on the other hand, allows athletes to behave in the virtual task as if they were on the real track (fidelity). This assertion is based on several complementary measures carried out in this study and discussed below. First, the results concerning the sense of presence and the comparison of workload are discussed. The results concerning the perceptual-motor behavior of the athletes at different scales are then analyzed. Every participant reported a high level of presence in the environment. In comparison with previous uses of this scale in the literature, these results suggest that the virtual task is immersive and that the physical fidelity is sufficient (16.4 \(\pm\) 2.1 in this study; 12.7 \(\pm\) 4.5 in [PERSON]'s study [21]). A high level of presence could lead to user engagement, which is a benefit to training efficacy. However, while a high sense of presence is desirable for the take-up of the technology, it is not necessarily a good predictor of training efficacy. High physical fidelity is often associated with high graphical realism, which is not necessarily linked to the key perceptual features of the task [25]. This emphasizes the need to conduct an exhaustive fidelity assessment with complementary measures. Next, the perceptual-cognitive demands of the VE were compared with those of the RWE using self-report scales of task load in each condition. Among the nine workload dimensions measured using  
Figure 6: The individual-scale average timings of each key event (wave initiation shown in blue, gaze release in red, and foot lift in green) in the real-world environment (RWE) and the virtual environment (VE) relative to the moment the partner passes over the mark for each participant. The error bars represent the within-participant variability of the initiation timings for each event in each condition. The clouds of points represent the initiation timing of each trial in each condition for each event. the SIM-TLX, only the \"mental demands\" differed significantly between conditions: the measures of mental demands were significantly higher in the VE. This result is consistent with those obtained by [PERSON] et al. (2016), which show that good immersion in a VR task was positively correlated with additional mental demands. Another possibility concerning this result could be related to environmental conditions during VE trials: the VE running initiations were conducted in a closed room, and participants could potentially experience higher mental demands when running toward a wall. This result can also be discussed in the context of the Cognitive Load Theory. Studies in the literature on Cognitive Load Theory consider three different types of load ([PERSON], 2015; [PERSON], 2016): the intrinsic load of the learner, which is inherent in the complexity of the task; the extraneous load, which is linked to the way the task is presented; and the germane load, which is directly associated with the learning process. The absolute cognitive load is considered as the sum of the three types of load. So, if this theory is applied to this study, the difference in mental demand between the two conditions could be explained by a difference in one of the three load types. However, the context of the task differs greatly between the two conditions.