## 1 Introduction  
In recent years, virtual reality (VR) technologies have emerged as relevant tools for perceptual-motor training in sports [1, 2, 3, 4]. Indeed, the use of virtual environments (VEs) allows for complete control over the training condition, which is not possible in the real-world environment (RWE). In addition, VEs offer the possibility of implementing training principles that are relevant for learning but rather hard to apply on the field [5]. These principles include, for example, manipulating task constraints [6], providing task-relevant feedback [7], and shaping individualized adaptive training programs [8]. Recently, a 4 \(\times\) 100 m athletics relay simulator including VE technologies was created with a view to the 2024 Olympic Games, specifically to train athletes' anticipation skills, i.e., the ability of athletes to initiate their runs at the right time to minimize speed loss during baton transmission [9]. In relays, the first runner carries a relay baton that has to be passed to the next athlete in a 30 m passing zone. The goal of the receiving runner is to optimize their start in order to catch the baton at maximum speed in the passing zone. To achieve this, the receiving athlete has a simple task, which is to initiate their run when the incoming partner passes over a reference go-mark on the ground. This transmission phase can be difficult to train on the track for several reasons. First, the repetition of the task for receiver athletes is necessarily associated with the sprints of other athletes, and repetitions of many runs at maximum speed is physiologically impossible for them to carry out and could lead to injuries. Secondly, there is no integrated measurement system on the field that allows athletes to precisely measure their performance and/or product behavior. And finally, training on a track does not allow for precise control over training conditions. The simulator was therefore created in collaboration with the French Athletics Federation in order to overcome these limitations and be able to implement the learning principles identified previously [5]. It was specially designed with the two main objectives of realistically recreating the informational context of the task while allowing the athlete to behave as if they were on the track. From our point of view, the preservation of functional relationships between perception and action is fundamental in order to optimize the anticipation capacities of high-level athletes [10; 11; 12]. This simulator has already been used as a tool to characterize the anticipation skills of athletes of the French national team [13], and high acceptance scores were recorded before and after using the simulator [14]. However, although this simulator is both well accepted and offers the possibility of characterizing the behavior of athletes, it is necessary to assess its efficacy as a training tool before incorporating it into athletes' training routines as part of the next Olympiad. In VR training, the first criterion of efficacy concerns the transfer of improvements acquired through the VE into the real world [15]. According to the review by [PERSON] et al. [3], despite the growing number of sports training simulators which integrate VR technologies, only four of them have demonstrated a real-world transfer--in darts [16], table tennis [17], juggling [6], and baseball batting [8]. However, many others have already used VE in sports training without any assurance as to their efficacy, thereby running the risk of wasting valuable training time and, in the worst-case scenario, even reducing the athlete's performance. The lack of transferable training protocols in VE is probably linked to the absence of precautions taken in most studies to ensure the validity and fidelity of simulators before using them to train athletes, which represent the secondary criterion for VE evaluation and is a good predictor of transferability [15].