# An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality

Gilles Montagne, Nicolas Mascret, Martin Bossard, Loïc Chomienne, Simon Ledouit, Guillaume Rao, Nicolas Tordi, Eulalie Verhulst, Richard Kulpa

<figure><img src="image_1.png" /></figure>

## To cite this version:

Gilles Montagne, Nicolas Mascret, Martin Bossard, Loïc Chomienne, Simon Ledouit, et al.. An inter-disciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality. Frontiers in Sports and Active Living, 2024, Frontiers in Sports and Active Living, 6, pp.1324016. 10.3389/fspor.2024.1324016. hal-04479743

HAL Id: hal-04479743

https://hal.science/hal-04479743

Submitted on 24 May 2024

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<figure><img src="image_1.png" /></figure>

Check for updates

OPEN ACCESS

EDITED BY
Håvard Lorås,
Norwegian University of Science and
Technology, Norway

REVIEWED BY
Kerstin Witte,
Otto von Guericke University Magdeburg,
Germany

*CORRESPONDENCE
Gilles Montagne
gilles.montagne@univ-amu.fr

¹PRESENT ADDRESS
Martin Bossard,
Univ Gustave Eiffel, COSYS-PICS-L, Marne-la-
Vallée, France

¹These authors share first authorship

RECEIVED 19 October 2023

ACCEPTED 30 January 2024

PUBLISHED 12 February 2024

CITATION

Montagne G, Mascret N, Bossard M, Chomienne L, Ledouit S, Rao G, Tordi N, Verhulst E and Kulpa R (2024) An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality.

Front. Sports Act. Living 6:1324016.

doi: 10.3389/fspor.2024.1324016

COPYRIGHT

© 2024 Montagne, Mascret, Bossard, Chomienne, Ledouit, Rao, Tordi, Verhulst and Kulpa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality

Gilles Montagne¹*‡, Nicolas Mascret¹‡, Martin Bossard¹†, Loïc Chomienne¹, Simon Ledouit², Guillaume Rao¹, Nicolas Tordi³, Eulalie Verhulst² and Richard Kulpa²

¹Aix-Marseille Univ, CNRS, ISM, Marseille, France, ²Univ Rennes, Inria, M2S, Rennes, France, ³PEPITE EA4267, (EPSI), University Bourgogne Franche-Comté, Besançon, France

The ambition of our contribution is to show how an interdisciplinary framework can pave the way for the deployment of innovative virtual reality training sessions to improve anticipation skills in top-level athletes. This improvement is so challenging that some authors say it is like “training for the impossible”. This framework, currently being implemented as part of a project to prepare athletes for the 2024 Olympic Games in Paris, based on the ecological-dynamics approach to expertise, is innovative in its interdisciplinary nature, but also and above all because it overcomes the limitations of more traditional training methods in the field designed to optimize anticipation skills in top-level athletes. The ambition is to tackle successive challenges ranging from the design of virtual partners and opponents to the deployment of training programs in virtual reality, while ensuring the acceptability and acceptance of such innovative virtual reality training protocols and measuring associated workloads.

KEYWORDS

virtual reality, top level sport, interdisciplinary, anticipation skills, ecological-dynamics

## 1 Introduction

Improving anticipation skills in high-level athletes is so challenging under normal training conditions that some authors say it is like “training for the impossible” (1). In this contribution, we wish to demonstrate that this challenge can be achieved provided an interdisciplinary framework is implemented to design a new generation of virtual reality (VR) training tools. We would like to put the emphasis on highly time-constrained sports for which anticipation skills are of paramount importance. It is now clearly established that experts differ from non-experts in their ability to gather and use the appropriate information. They are therefore able to make the right decision at the right time, despite drastic time constraints (2, 3). Based on this observation, the central question that arises is how training should be organized for athletes, including experts, to optimize anticipation skills.

Although a lot of research (4) conducted in recent decades has brought to light the main principles that prevail when learning sport skills in general, the specific optimization of anticipation skills is still a very challenging issue. In addition to the fact that both perceptual-motor and decision-making processes that take place are task-specific, dynamically related to action, and moreover not always clearly identified, training carried out on field can hardly meet the specifications of rigorous anticipation training protocols.
<figure><img src="image_3.png" /></figure>

Check for updates

OPEN ACCESS

EDITED BY
Håvard Lorås,
Norwegian University of Science and
Technology, Norway

REVIEWED BY
Kerstin Witte,
Otto von Guericke University Magdeburg,
Germany

*CORRESPONDENCE
Gilles Montagne
gilles.montagne@univ-amu.fr

¹PRESENT ADDRESS
Martin Bossard,
Univ Gustave Eiffel, COSYS-PICS-L, Marne-la-
Vallée, France

¹These authors share first authorship

RECEIVED 19 October 2023

ACCEPTED 30 January 2024

PUBLISHED 12 February 2024

CITATION

Montagne G, Mascret N, Bossard M, Chomienne L, Ledouit S, Rao G, Tordi N, Verhulst E and Kulpa R (2024) An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality.

Front. Sports Act. Living 6:1324016.

doi: 10.3389/fspor.2024.1324016

COPYRIGHT

© 2024 Montagne, Mascret, Bossard, Chomienne, Ledouit, Rao, Tordi, Verhulst and Kulpa. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

# An interdisciplinary framework to optimize the anticipation skills of high-level athletes using virtual reality

Gilles Montagne¹*‡, Nicolas Mascret¹‡, Martin Bossard¹†, Loïc Chomienne¹, Simon Ledouit², Guillaume Rao¹, Nicolas Tordi³, Eulalie Verhulst² and Richard Kulpa²

¹Aix-Marseille Univ, CNRS, ISM, Marseille, France, ²Univ Rennes, Inria, M2S, Rennes, France, ³PEPITE EA4267, (EPSI), University Bourgogne Franche-Comté, Besançon, France

The ambition of our contribution is to show how an interdisciplinary framework can pave the way for the deployment of innovative virtual reality training sessions to improve anticipation skills in top-level athletes. This improvement is so challenging that some authors say it is like “training for the impossible”. This framework, currently being implemented as part of a project to prepare athletes for the 2024 Olympic Games in Paris, based on the ecological-dynamics approach to expertise, is innovative in its interdisciplinary nature, but also and above all because it overcomes the limitations of more traditional training methods in the field designed to optimize anticipation skills in top-level athletes. The ambition is to tackle successive challenges ranging from the design of virtual partners and opponents to the deployment of training programs in virtual reality, while ensuring the acceptability and acceptance of such innovative virtual reality training protocols and measuring associated workloads.

KEYWORDS

virtual reality, top level sport, interdisciplinary, anticipation skills, ecological-dynamics

## 1 Introduction

Improving anticipation skills in high-level athletes is so challenging under normal training conditions that some authors say it is like “training for the impossible” (1). In this contribution, we wish to demonstrate that this challenge can be achieved provided an interdisciplinary framework is implemented to design a new generation of virtual reality (VR) training tools. We would like to put the emphasis on highly time-constrained sports for which anticipation skills are of paramount importance. It is now clearly established that experts differ from non-experts in their ability to gather and use the appropriate information. They are therefore able to make the right decision at the right time, despite drastic time constraints (2, 3). Based on this observation, the central question that arises is how training should be organized for athletes, including experts, to optimize anticipation skills.

Although a lot of research (4) conducted in recent decades has brought to light the main principles that prevail when learning sport skills in general, the specific optimization of anticipation skills is still a very challenging issue. In addition to the fact that both perceptual-motor and decision-making processes that take place are task-specific, dynamically related to action, and moreover not always clearly identified, training carried out on field can hardly meet the specifications of rigorous anticipation training protocols.
Not only can the information content of a given task and the time
constraints not be controlled precisely on field, but also their
complexity is difficult to modulate, and the feedback given to
athletes usually lacks precision.

In recent years, the revolution of digital technologies in the field of sport has opened new perspectives from this point of view (5, 6). Virtual reality technologies, provide potentially very powerful tools which may exceed the limits previously described and allow a perfect control of the information available for the athlete. It is now possible to immerse athletes in interactive and realistic 3D digital environments including biologically realistic moving partners and/ or opponents while carrying out experimentally controlled tasks requiring anticipation, and to provide relevant feedback when needed. It is reasonable to consider that now is the time to “train for the impossible” and we posit that the conceptual, methodological, and technical solutions are readily available.

The rise of digital technologies this last decade, and more
precisely recent evolutions in the domain of VR, have led the
world of sport to take a close interest in the added value
associated with the use of VR technologies for the purpose of
optimizing performance. The large number of empirical works,
literature reviews, and meta-analyses focusing on the role of VR
in analyzing and optimizing the processes underlying sports
performance reflects this enthusiasm (7–11). Studies conducted
to date have revealed that VR is a tool of choice for
discriminating the anticipatory skills of experts and non-experts
in various sports such as baseball (12), golf (13), handball (14),
rugby (15), and soccer (16). Curiously, as previously mentioned
by some authors (7, 17), using VR in a training perspective to
transform and optimize the processes underlying anticipation
skills is much rarer. Moreover, very recent technological
developments in VR Head-Mounted Display (VR-HMD) allow
some limitations to be overcome (18).

Since many technological locks are being lifted, it is now
conceivable to bring VR-HMD into the training environments of
athletes and to deploy VR training sessions as part of a program
focused on optimizing anticipation skills. However, a number of
issues both methodological and theoretical still remain to be
addressed before the program can be useful for athletes and coaches.
These issues range from the design of animated digital twins of
either opponents or partners, to the elaboration of training protocols
in VR which are theoretically grounded and complementary to
traditional training sessions, passing through the assessment of both
the acceptance by athletes and coaches of technological solutions
and the new workloads related to the deployment of VR training
sessions. Only a dedicated interdisciplinary framework is likely to
provide answers to the above-mentioned issues.

2 The need for an interdisciplinary
framework

## 2.1 The example of an ongoing project

In order to give more meaning to our proposals we have
chosen, as the main thread of this article, to refer to a current

project which aims precisely to optimize the anticipation skills of
high-level athletes in the context of preparation for the Olympic
Games. The basic idea of this project is to improve the
anticipation skills of athletes by confronting them with the digital
twins of their opponents and/or their partners in a perfectly
controlled setting.

In the case of 4 × 100 m relay, the team performance is partly
based on the ability of athletes to synchronize their
displacements and therefore to initiate their race at the right
time, before the partner arrives in the relay transmission area,
despite the pressure exerted by the opponents. VR training
protocols will therefore have the function of training each athlete
to initiate their race at the appropriate time, with an avatar based
on motion capture of real sprinters and whose race features are
configurable. In addition, the user will be able to benefit from
precise feedback related to the timing errors produced.

In the case of boxing, the idea is to propose training protocols
in VR that allow the boxer to learn to extract the appropriate
information on the opposing fighter which should enable him/
her to anticipate attacks and adopt the appropriate parry and
counterattack. As mentioned previously in the relay example, the
behavior of the virtual opponent can be parametrized, according
to the boxers' needs. The use of VR will also allow online
recording of the evolution of performance.

## 2.2 The need for an interdisciplinary approach

In the sport domain, the high level of performance attained by
elite athletes is a perfect case for interdisciplinary research due to
the multidimensional explanations of the determinants of their
expertise (19, 20). But a recent review (21) asked the following
question: *Is sports science answering the call for interdisciplinary
research?* The authors concluded that this call is beginning to be
fulfilled by sport science research, and they also highlighted that
more individual analyses and more representative tasks are
needed to really achieve this goal. The use of VR could meet
these two expectations, but only if an interdisciplinary approach
is conducted at the interface of life sciences, human and social
sciences, engineering sciences, and computer sciences,
mobilizing different scientific fields such as neurosciences,
psychology, computer graphics, biomechanics, and physiology
(Figure 1). Indeed, each scientific discipline contributes to first
shed light on a particular field, for instance in the project
mentioned in the previous section, motion captures
(biomechanics), design of avatars with biological movements
(computer graphics), training anticipation skills in VR
(neurosciences), acceptance of the VR-HMD (psychology), and
workload (physiology and psychology). But each disciplinary
issue can positively or negatively influence the others (e.g., the
biological movement of an athlete's avatar can, from a
psychological point of view, be accepted or on the contrary be
refused by the VR-HMD user). It is thus the interdisciplinary
approach, at the interface of all these disciplines, that will ensure
the success of the project.
Not only can the information content of a given task and the time
constraints not be controlled precisely on field, but also their
complexity is difficult to modulate, and the feedback given to
athletes usually lacks precision.

In recent years, the revolution of digital technologies in the field of sport has opened new perspectives from this point of view (5, 6). Virtual reality technologies, provide potentially very powerful tools which may exceed the limits previously described and allow a perfect control of the information available for the athlete. It is now possible to immerse athletes in interactive and realistic 3D digital environments including biologically realistic moving partners and/ or opponents while carrying out experimentally controlled tasks requiring anticipation, and to provide relevant feedback when needed. It is reasonable to consider that now is the time to “train for the impossible” and we posit that the conceptual, methodological, and technical solutions are readily available.

The rise of digital technologies this last decade, and more
precisely recent evolutions in the domain of VR, have led the
world of sport to take a close interest in the added value
associated with the use of VR technologies for the purpose of
optimizing performance. The large number of empirical works,
literature reviews, and meta-analyses focusing on the role of VR
in analyzing and optimizing the processes underlying sports
performance reflects this enthusiasm (7–11). Studies conducted
to date have revealed that VR is a tool of choice for
discriminating the anticipatory skills of experts and non-experts
in various sports such as baseball (12), golf (13), handball (14),
rugby (15), and soccer (16). Curiously, as previously mentioned
by some authors (7, 17), using VR in a training perspective to
transform and optimize the processes underlying anticipation
skills is much rarer. Moreover, very recent technological
developments in VR Head-Mounted Display (VR-HMD) allow
some limitations to be overcome (18).

Since many technological locks are being lifted, it is now
conceivable to bring VR-HMD into the training environments of
athletes and to deploy VR training sessions as part of a program
focused on optimizing anticipation skills. However, a number of
issues both methodological and theoretical still remain to be
addressed before the program can be useful for athletes and coaches.
These issues range from the design of animated digital twins of
either opponents or partners, to the elaboration of training protocols
in VR which are theoretically grounded and complementary to
traditional training sessions, passing through the assessment of both
the acceptance by athletes and coaches of technological solutions
and the new workloads related to the deployment of VR training
sessions. Only a dedicated interdisciplinary framework is likely to
provide answers to the above-mentioned issues.

2 The need for an interdisciplinary
framework

2.1 The example of an ongoing project

In order to give more meaning to our proposals we have
chosen, as the main thread of this article, to refer to a current

project which aims precisely to optimize the anticipation skills of
high-level athletes in the context of preparation for the Olympic
Games. The basic idea of this project is to improve the
anticipation skills of athletes by confronting them with the digital
twins of their opponents and/or their partners in a perfectly
controlled setting.

In the case of 4 × 100 m relay, the team performance is partly
based on the ability of athletes to synchronize their
displacements and therefore to initiate their race at the right
time, before the partner arrives in the relay transmission area,
despite the pressure exerted by the opponents. VR training
protocols will therefore have the function of training each athlete
to initiate their race at the appropriate time, with an avatar based
on motion capture of real sprinters and whose race features are
configurable. In addition, the user will be able to benefit from
precise feedback related to the timing errors produced.

In the case of boxing, the idea is to propose training protocols
in VR that allow the boxer to learn to extract the appropriate
information on the opposing fighter which should enable him/
her to anticipate attacks and adopt the appropriate parry and
counterattack. As mentioned previously in the relay example, the
behavior of the virtual opponent can be parametrized, according
to the boxers' needs. The use of VR will also allow online
recording of the evolution of performance.

## 2.2 The need for an interdisciplinary approach

In the sport domain, the high level of performance attained by
elite athletes is a perfect case for interdisciplinary research due to
the multidimensional explanations of the determinants of their
expertise (19, 20). But a recent review (21) asked the following
question: *Is sports science answering the call for interdisciplinary
research?* The authors concluded that this call is beginning to be
fulfilled by sport science research, and they also highlighted that
more individual analyses and more representative tasks are
needed to really achieve this goal. The use of VR could meet
these two expectations, but only if an interdisciplinary approach
is conducted at the interface of life sciences, human and social
sciences, engineering sciences, and computer sciences,
mobilizing different scientific fields such as neurosciences,
psychology, computer graphics, biomechanics, and physiology
(Figure 1). Indeed, each scientific discipline contributes to first
shed light on a particular field, for instance in the project
mentioned in the previous section, motion captures
(biomechanics), design of avatars with biological movements
(computer graphics), training anticipation skills in VR
(neurosciences), acceptance of the VR-HMD (psychology), and
workload (physiology and psychology). But each disciplinary
issue can positively or negatively influence the others (e.g., the
biological movement of an athlete's avatar can, from a
psychological point of view, be accepted or on the contrary be
refused by the VR-HMD user). It is thus the interdisciplinary
approach, at the interface of all these disciplines, that will ensure
the success of the project.
<figure><img src="image_2.png" /></figure>

# 3 Toward the optimization of anticipation skills

## 3.1 A prerequisite: a theoretical conception of the processes to optimize

Although an interdisciplinary consortium is mandatory to lift all the locks associated with the implementation of training protocols in VR designed to optimize anticipation skills in top athletes, it may not be sufficient to succeed. The whole project must be based on a clear conception of the anticipation processes implemented by athletes that one wishes to train and optimize. Distinct theoretical frameworks account for the processes

underlying anticipation skills (22, 23). For example, the project mentioned previously (§ 2.1) is backed on the ecological-dynamics vision of expertise in sport (24). According to this theoretical framework, expertise relies on the “athlete’s capacity to functionally adapt his/her movements to the dynamics of complex-performance environments by continuously perceiving information to regulate goal-directed actions” (24, p. 130). This framework has its origin in the work of Gibson (25) which proposed to break with the traditional cognitivist-inspired approaches to perception, by proposing a new ecological approach to perception and action based on the inseparable nature of the links between the agent and his/her environment and between perception and action (26). According to the
<figure><img src="image_4.png" /></figure>

# 3 Toward the optimization of anticipation skills

## 3.1 A prerequisite: a theoretical conception of the processes to optimize

Although an interdisciplinary consortium is mandatory to lift all the locks associated with the implementation of training protocols in VR designed to optimize anticipation skills in top athletes, it may not be sufficient to succeed. The whole project must be based on a clear conception of the anticipation processes implemented by athletes that one wishes to train and optimize. Distinct theoretical frameworks account for the processes

underlying anticipation skills (22, 23). For example, the project mentioned previously (§ 2.1) is backed on the ecological-dynamics vision of expertise in sport (24). According to this theoretical framework, expertise relies on the “athlete’s capacity to functionally adapt his/her movements to the dynamics of complex-performance environments by continuously perceiving information to regulate goal-directed actions” (24, p. 130). This framework has its origin in the work of Gibson (25) which proposed to break with the traditional cognitivist-inspired approaches to perception, by proposing a new ecological approach to perception and action based on the inseparable nature of the links between the agent and his/her environment and between perception and action (26). According to the
ecological-dynamics framework, athletes would actively perceive opportunities for action in the perceptual flow produced by moving partners and/or opponents, provided they are attuned to the relevant high-order perceptual variable. The optimization of perceptual-motor and decision-making processes is a question of actively discovering these variables through repetitions in various contexts in the presence of feedback.

In the light of these considerations, VR training sessions should preserve the natural links between perception and action insofar as the anticipation skills of experts cannot be optimized when the natural links between perception and action are disrupted. Training sessions should also preserve as much as possible both the task and environment constraints encountered by the athlete on field in such a way as to facilitate the transfer of the optimized skills to the field (27). With these specifications in mind a research project can be designed to overcome intertwined challenges (Figure 1).

## 3.2 The main challenges

**Challenge #1:** Designing realistic partners' and opponents' avatars immersed in representative environments.

The first challenge lies in the design of avatars of either partners and/or opponents that athletes will face during VR training sessions but also to integrate these avatars into representative virtual environments identically reproducing the sporting environments. This ambition requires the realization of a series of operations described in Figure 1. The first one concerns the collection of in-situ motion datasets representative of consistent motor performances with respect to the levels of expertise and individual movement patterns of the athletes. It is crucially important to carry out such motion capture in real field conditions while preserving as much as possible the biological accuracy of the collected movement pattern. The second step is to transfer these motion datasets into virtual character animation. The challenge is to apply these movements to fully reconfigurable avatars while preserving the biological properties of these motions. This requires morphological retargeting approaches.

The needs concerning the characteristics of the avatars (e.g., adaptive vs., non-adaptive) will depend on the sporting situation considered. Concerning the project described in section 2.1, the use of adaptive avatars is unnecessary in the context of the 4 × 100 m relay as virtual reality is only used to optimize the initiation of the race of the athlete who will receive the stick. Conversely, in boxing, the use of adaptive avatars is crucial to maintain the dynamics of the sport and ensure that the virtual boxer is at the right position and orientation for a successful attack. Its performance is also automatically adjusted to match the real boxer's capabilities, preventing it from being placed in a situation of failure and allowing an individual adaptation to the boxer's progress.

As a corollary to the previous point, the selection of athletes for motion captures can be important. For 4 × 100 m relay, which constitutes a collaborative task, it is logical for example that the motion captures are carried out on the partners. For boxing, the

confrontation with opponents, whoever they may be, allows boxers to optimize their anticipation skills, especially when attacks are selected to mimic opponents' preferred ones.

**Challenge #2:** Designing a user-centric app.

The in-situ motion datasets previously mentioned will serve as the basis for creating a library of scenarios that will be used during the VR training sessions. For example, in the case of 4 × 100 m relay, these scenarios take the form of sprinters approaching the transmission zone, either alone or in the presence of opponents, at fully configurable speeds and places on the track. In the case of boxing, these scenarios immerse a real boxer, in a virtual ring, facing a virtual opponent who will produce a series of attacks that challenge the defensive skills to be trained. The scenario library mentioned previously can be stored in an application whose specifications has to be designed in close connection with end users. The basic idea is to allow each coach to easily program the VR training sessions in advance or at the last moment by selecting the appropriate scenarios. In return the application is intended to record a number of variables to characterize the athlete's behavior in order to be able to give feedback to the athlete and/or the coaches online or in a delayed way as required.

**Challenge #3:** Designing theoretically grounded VR training sessions.

The third challenge is to identify the best way to organize the training of athletes to optimize their anticipatory skills. The use of VR finds its full expression by allowing a great number of repetitions in a fully controlled environment and by providing precise feedback about the choices and actions made by the athletes. The ambition here is to create individualized training sessions allowing the athlete to develop adaptive behaviors; for example, the variability of the conditions of practice at the service of the development of perceptual-motor workspaces within which experts can search for functional coordination solutions (24). Importantly, VR allows the implementation of training methods that would not have been possible otherwise. The action capacities of either partners and opponents can be easily manipulated, so as approach biological limits or even exceed them, in order to develop athletes' adaptive capacities and prepare them as much as possible for the imponderables that characterize very high performance. Importantly, to preserve the ecological validity of training protocols, the sensory modalities generally used (in addition to the visual modality) must also be stimulated as part of Virtual Reality training. For example, in the case of the 4 × 100 m relay, stadium noise has been integrated to contextualize the training as much as possible. However, no haptic feedback is needed. For the boxing task, acoustic feedback is added on impacts, and spectators' noise can be set from hostile to friendly.

**Challenge #4:** Overcoming the limitations of VR.

VR is a hardware- and software-based system and therefore has some intrinsic limitations. First, it has been widely demonstrated that depth perception is underestimated in virtual environments (28). This problem can be overcome by immersing free-moving athletes in rich and structured virtual environments providing them with a large amount of motion parallax and other sources
ecological-dynamics framework, athletes would actively perceive opportunities for action in the perceptual flow produced by moving partners and/or opponents, provided they are attuned to the relevant high-order perceptual variable. The optimization of perceptual-motor and decision-making processes is a question of actively discovering these variables through repetitions in various contexts in the presence of feedback.

In the light of these considerations, VR training sessions should preserve the natural links between perception and action insofar as the anticipation skills of experts cannot be optimized when the natural links between perception and action are disrupted. Training sessions should also preserve as much as possible both the task and environment constraints encountered by the athlete on field in such a way as to facilitate the transfer of the optimized skills to the field (27). With these specifications in mind a research project can be designed to overcome intertwined challenges (Figure 1).

## 3.2 The main challenges

**Challenge #1:** Designing realistic partners' and opponents' avatars immersed in representative environments.

The first challenge lies in the design of avatars of either partners and/or opponents that athletes will face during VR training sessions but also to integrate these avatars into representative virtual environments identically reproducing the sporting environments. This ambition requires the realization of a series of operations described in Figure 1. The first one concerns the collection of in-situ motion datasets representative of consistent motor performances with respect to the levels of expertise and individual movement patterns of the athletes. It is crucially important to carry out such motion capture in real field conditions while preserving as much as possible the biological accuracy of the collected movement pattern. The second step is to transfer these motion datasets into virtual character animation. The challenge is to apply these movements to fully reconfigurable avatars while preserving the biological properties of these motions. This requires morphological retargeting approaches.

The needs concerning the characteristics of the avatars (e.g., adaptive vs., non-adaptive) will depend on the sporting situation considered. Concerning the project described in section 2.1, the use of adaptive avatars is unnecessary in the context of the 4 × 100 m relay as virtual reality is only used to optimize the initiation of the race of the athlete who will receive the stick. Conversely, in boxing, the use of adaptive avatars is crucial to maintain the dynamics of the sport and ensure that the virtual boxer is at the right position and orientation for a successful attack. Its performance is also automatically adjusted to match the real boxer's capabilities, preventing it from being placed in a situation of failure and allowing an individual adaptation to the boxer's progress.

As a corollary to the previous point, the selection of athletes for motion captures can be important. For 4 × 100 m relay, which constitutes a collaborative task, it is logical for example that the motion captures are carried out on the partners. For boxing, the

confrontation with opponents, whoever they may be, allows boxers to optimize their anticipation skills, especially when attacks are selected to mimic opponents' preferred ones.

**Challenge #2:** Designing a user-centric app.

The in-situ motion datasets previously mentioned will serve as the basis for creating a library of scenarios that will be used during the VR training sessions. For example, in the case of 4 × 100 m relay, these scenarios take the form of sprinters approaching the transmission zone, either alone or in the presence of opponents, at fully configurable speeds and places on the track. In the case of boxing, these scenarios immerse a real boxer, in a virtual ring, facing a virtual opponent who will produce a series of attacks that challenge the defensive skills to be trained. The scenario library mentioned previously can be stored in an application whose specifications has to be designed in close connection with end users. The basic idea is to allow each coach to easily program the VR training sessions in advance or at the last moment by selecting the appropriate scenarios. In return the application is intended to record a number of variables to characterize the athlete's behavior in order to be able to give feedback to the athlete and/or the coaches online or in a delayed way as required.

**Challenge #3:** Designing theoretically grounded VR training sessions.

The third challenge is to identify the best way to organize the training of athletes to optimize their anticipatory skills. The use of VR finds its full expression by allowing a great number of repetitions in a fully controlled environment and by providing precise feedback about the choices and actions made by the athletes. The ambition here is to create individualized training sessions allowing the athlete to develop adaptive behaviors; for example, the variability of the conditions of practice at the service of the development of perceptual-motor workspaces within which experts can search for functional coordination solutions (24). Importantly, VR allows the implementation of training methods that would not have been possible otherwise. The action capacities of either partners and opponents can be easily manipulated, so as approach biological limits or even exceed them, in order to develop athletes' adaptive capacities and prepare them as much as possible for the imponderables that characterize very high performance. Importantly, to preserve the ecological validity of training protocols, the sensory modalities generally used (in addition to the visual modality) must also be stimulated as part of Virtual Reality training. For example, in the case of the 4 × 100 m relay, stadium noise has been integrated to contextualize the training as much as possible. However, no haptic feedback is needed. For the boxing task, acoustic feedback is added on impacts, and spectators' noise can be set from hostile to friendly.

**Challenge #4:** Overcoming the limitations of VR.

VR is a hardware- and software-based system and therefore has some intrinsic limitations. First, it has been widely demonstrated that depth perception is underestimated in virtual environments (28). This problem can be overcome by immersing free-moving athletes in rich and structured virtual environments providing them with a large amount of motion parallax and other sources
of information which is well documented to greatly attenuate
virtual misperception (29). Secondly, VR can lead to
cybersickness, a user discomfort that can result in
discontinuation of use. Its main causes are hardware, content,
and human factors (30). To avoid cybersickness, the type and
duration of training sessions can be balanced based on the
athlete's personal characteristics and habits with VR. Thirdly, the
main challenge raised by the use of VR for training concerns
skills transfer. Does improvement in VR entail improvement in
real life? This is a very complex issue as performance is by
nature multifactorial, and assessment must be carried out using
protocols that are both close to competition conditions and
quantifiable. Importantly, some recent work reveals that
anticipation skills optimized through virtual reality training
protocols can be effectively transferred to the field (8).

4 Two risk mitigation strategies

Two risk mitigation strategies have to be conducted simultaneously, namely evaluation of acceptance and workloads of VR sessions. The objective is to be sure that the benefits on the optimization of anticipation skills are not degraded by other factors that are not controlled.

4.1 Assessing acceptance of the VR-HMD

If the VR-HMD is not accepted by coaches and athletes
before a first use, it would ultimately never be used. Therefore,
based on the Technology Acceptance Model (TAM, 31), it is of
paramount importance to identify which variables influence
coaches' and athletes' acceptance of the VR-HMD and thus
lead, before a first use, to initial blockages regarding its use for
sports performance improvement. For example, in the project
mentioned previously (see § 2.1) it has been shown (32) that
elite athletes intended to use this VR-HMD, found it quite
useful and quite easy and pleasant to use, even though they
have not really used it yet. It also highlighted that elite athletes
wonder if those around them would advise them to use it.
Therefore, initial blockages do not seem to appear in elite
athletes. The issue of acceptance is not limited to acceptance
before first use. If the VR-HMD is not accepted once it has
been tested, its effective use quickly declines. Therefore, it is
necessary to regularly measure coaches' and athletes' acceptance
of the VR-HMD to identify to what extent specific stages of
software development led to changes in perceived usefulness,
perceived ease of use, perceived enjoyment, and intention to
use the VR-HMD. Finally, once the VR-HMD is in its final
version and delivered to coaches and athletes, the same
variables should be regularly measured throughout the training
process to identify whether acceptance of the device still
remains at a high level and whether specific interventions are
ever needed if acceptance decreases.

4.2 Assessing workloads

Adding VR-based training protocols to the athletes' training program would change the total training load. The primary goal is indeed to allow athletes to train more without high-intensity work or risk of injury, but training may also add an attentional, cognitive, and physiological workload. Therefore, it is necessary to monitor and prevent any possible negative effect on the training load induced by using VR in training when the athlete is not accustomed to this technological device. An Athlete Management System can be used to collect and analyze data related to the training program and to the athletes' responses to this program. Different types of information related to exertion, fitness level, motivation as well as pain perceived, and sleep quality and duration can be collected and analyzed. Questionnaires are also a way of reporting subjective experience of workload. The simulation task load index (SIM-TLX, 33) was specifically designed for its self-reported assessment in virtual environments. Combined with the Athlete Management System and with external loads (e.g., heart rate), these measures will help in identifying potential overload but also in individually adapting and enhancing VR training (34). All these variables can be analyzed to examine how the athletes used VR. In this way it is possible to prevent all negative effects related to RV added to the training program and determine which type of use is the most beneficial.

5 Conclusion and perspectives

Despite the growing interest of the sports world in new
technologies, and XR technologies in particular, they are little
adopted by top coaches and top athletes as part of training
procedures. This article aims to show how an interdisciplinary
framework can pave the way for the deployment of innovative
virtual reality training sessions to improve anticipation skills in
top-level athletes. VR is particularly attractive because it offers
the opportunity to overcome the limitations of traditional
training protocols by allowing athletes to optimally develop their
adaptive capacities. The DNA of this framework is based on its
interdisciplinary nature, but also on a precise knowledge of the
processes we wish to optimize which guides the technological
choices and the use made of them. We believe that the approach
could enable new generations of studies to be carried out to draw
out the quintessence of XR tools in the context of optimizing the
performance of high-level athletes.

Data availability statement

The original contributions presented in the study are included
in the article/Supplementary Material, further inquiries can be
directed to the corresponding author.
of information which is well documented to greatly attenuate
virtual misperception (29). Secondly, VR can lead to
cybersickness, a user discomfort that can result in
discontinuation of use. Its main causes are hardware, content,
and human factors (30). To avoid cybersickness, the type and
duration of training sessions can be balanced based on the
athlete's personal characteristics and habits with VR. Thirdly, the
main challenge raised by the use of VR for training concerns
skills transfer. Does improvement in VR entail improvement in
real life? This is a very complex issue as performance is by
nature multifactorial, and assessment must be carried out using
protocols that are both close to competition conditions and
quantifiable. Importantly, some recent work reveals that
anticipation skills optimized through virtual reality training
protocols can be effectively transferred to the field (8).

## 4 Two risk mitigation strategies

Two risk mitigation strategies have to be conducted simultaneously, namely evaluation of acceptance and workloads of VR sessions. The objective is to be sure that the benefits on the optimization of anticipation skills are not degraded by other factors that are not controlled.

### 4.1 Assessing acceptance of the VR-HMD

If the VR-HMD is not accepted by coaches and athletes
before a first use, it would ultimately never be used. Therefore,
based on the Technology Acceptance Model (TAM, 31), it is of
paramount importance to identify which variables influence
coaches' and athletes' acceptance of the VR-HMD and thus
lead, before a first use, to initial blockages regarding its use for
sports performance improvement. For example, in the project
mentioned previously (see § 2.1) it has been shown (32) that
elite athletes intended to use this VR-HMD, found it quite
useful and quite easy and pleasant to use, even though they
have not really used it yet. It also highlighted that elite athletes
wonder if those around them would advise them to use it.
Therefore, initial blockages do not seem to appear in elite
athletes. The issue of acceptance is not limited to acceptance
before first use. If the VR-HMD is not accepted once it has
been tested, its effective use quickly declines. Therefore, it is
necessary to regularly measure coaches' and athletes' acceptance
of the VR-HMD to identify to what extent specific stages of
software development led to changes in perceived usefulness,
perceived ease of use, perceived enjoyment, and intention to
use the VR-HMD. Finally, once the VR-HMD is in its final
version and delivered to coaches and athletes, the same
variables should be regularly measured throughout the training
process to identify whether acceptance of the device still
remains at a high level and whether specific interventions are
ever needed if acceptance decreases.

### 4.2 Assessing workloads

Adding VR-based training protocols to the athletes' training
program would change the total training load. The primary goal
is indeed to allow athletes to train more without high-intensity
work or risk of injury, but training may also add an attentional,
cognitive, and physiological workload. Therefore, it is necessary
to monitor and prevent any possible negative effect on the
training load induced by using VR in training when the athlete
is not accustomed to this technological device. An Athlete
Management System can be used to collect and analyze data
related to the training program and to the athletes' responses to
this program. Different types of information related to exertion,
fitness level, motivation as well as pain perceived, and sleep
quality and duration can be collected and analyzed.
Questionnaires are also a way of reporting subjective experience
of workload. The simulation task load index (SIM-TLX, 33) was
specifically designed for its self-reported assessment in virtual
environments. Combined with the Athlete Management System
and with external loads (e.g., heart rate), these measures will
help in identifying potential overload but also in individually
adapting and enhancing VR training (34). All these variables can
be analyzed to examine how the athletes used VR. In this way it
is possible to prevent all negative effects related to RV added to
the training program and determine which type of use is the
most beneficial.

## 5 Conclusion and perspectives

Despite the growing interest of the sports world in new
technologies, and XR technologies in particular, they are little
adopted by top coaches and top athletes as part of training
procedures. This article aims to show how an interdisciplinary
framework can pave the way for the deployment of innovative
virtual reality training sessions to improve anticipation skills in
top-level athletes. VR is particularly attractive because it offers
the opportunity to overcome the limitations of traditional
training protocols by allowing athletes to optimally develop their
adaptive capacities. The DNA of this framework is based on its
interdisciplinary nature, but also on a precise knowledge of the
processes we wish to optimize which guides the technological
choices and the use made of them. We believe that the approach
could enable new generations of studies to be carried out to draw
out the quintessence of XR tools in the context of optimizing the
performance of high-level athletes.

## Data availability statement

The original contributions presented in the study are included
in the article/Supplementary Material, further inquiries can be
directed to the corresponding author.
## Author contributions

GM: Writing – original draft. NM: Writing – original draft.
MB: Writing – review & editing. LC: Writing – review & editing.
SL: Writing – review & editing. GR: Writing – review & editing.
NT: Writing – review & editing. EV: Writing – review & editing.
RK: Writing – original draft.

## Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article.

This work is part of the REVEA project supported by a government grant managed by the French National Research Agency (ANR) as part of the "France 2030" program (20-STHP-0004).

## References

1. Drew L. Training for the impossible. *Nature*. (2021) 592:S4-6. doi: 10.1038/d41586-021-00816-3

2. Beek PJ, Jacobs DM, Daffertshofer A, Huys R. Expert performance in sport: views from the joint perspective of ecological psychology and dynamical systems theory. In: Starkes JL, Ericsson KA, editors. *Expert Performance in Sports: Advances in Research on Sport Expertise*. Champaign, IL: Human Kinetics (2003). p. 321-44.

3. Mann DTY, Williams AM, Ward P, Janelle CM. Perceptual-cognitive expertise in sport: a meta-analysis. *J Sport Exerc Psychol*. (2007) 29:457-78. doi: 10.1123/jsep.29.4.457

4. Hendry DT, Ford PR, Williams AM, Hodges NJ. Five evidence-based principles of effective practice and instruction. In: Baker J, Farrow D, editors. *Handbook of Sport Expertise*. New York, NY: Routledge (2015). p. 414-29.

5. Appelbaum LG, Erickson G. Sports vision training: a review of the state-of-the-art in digital training techniques. *Int Rev Sport Exerc Psychol*. (2018) 11:160-89. doi: 10.1080/1750984X.2016.1266376

6. Harris DJ, Wilson MR, Vine SJ. A systematic review of commercial cognitive training devices: implications for use in sport. *Front Psychol*. (2018) 9:709. doi: 10.3389/fψysg.2018.00709

7. Miles HC, Pop SR, Watt SJ, Lawrence GP, John NW. A review of virtual environment for training in ball sports. *Comput Graph*. (2012) 36:714-26. doi: 10.1016/j.cag.2012.04.007

8. Gray R. Transfer of training from virtual to real baseball batting. *Front Psychol*. (2017) 8:2183. doi: 10.3389/fψysg.2017.02183

9. Neumann DL, Moffitt RL, Thomas PR, Loveday K, Watling DP, Lombard CM, et al. A systematic review of the application of interactive VR to sport. *Virtual Real*. (2018) 22:183-98. doi: 10.1007/s10055-017-0320-5

10. Michalski SC, Szpak A, Loetscher T. Using virtual environments to improve real-world motor skills in sports: a systematic review. *Front Psychol*. (2019) 10. doi: 10.3389/fψysg.2019.02159

11. Faure C, Limballe A, Bideau B, Kulpa R. Virtual reality to assess and train team ball sports performance: a scoping review. *J Sports Sci*. (2020) 38:192-205. doi: 10.1080/02640414.2019.1689807

12. Gray R, Beilock S, Carr TH. "As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players. *Psychon Bull Rev*. (2017) 14:669-75. doi: 10.3758/BF03196819

13. Campbell MJ, Moran AP. There is more to green reading than meets the eye! exploring the gaze behaviours of expert golfers on a virtual golf putting task. *Cogn Process*. (2014) 15:363-72. doi: DPI: 10.1007/s10339-014-0608-2

14. Vignais N, Bideau B, Craig C, Brault S, Multon F, Delamarche P, et al. Does the level of graphical detail of a virtual handball thrower influence a goalkeeper's motor response? *J Sports Sci Med*. (2014) 8:501-8. PMID: 24149589

15. Brault S, Bideau B, Kulpa R, Craig CM. Detecting deception in movement: the case of the side-step in rugby. *PLoS One*. (2012) e37494. doi: 10.1371/journal.pone.0037494

16. Craig CM, Berton E, Rao G, Fernandez L, Bootsma RJ. Judging where the ball will go: the case of curved free kicks in football. *Naturwissenschaften*. (2006) 93:97-101. doi: 10.1007/s00114-005-0071-0

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

17. Akbas A, Marszatek W, Kamieniarz A, Polechonski J, Stomka K, Juras G. Application of virtual reality in competitive athletes – a review. *J Hum Kinet*. (2019) 69:5-16. doi: 10.2478/hukin-2019-0023

18. Düking P, Holmberg HC, Sperlich B. The potential usefulness of virtual reality systems for athletes: a short SWOT analysis. *Front Physiol*. (2018) 9:128. doi: 10.3389/fphys.2018.00128

19. Buekers M, Ibáñez-Gijón J, Morice AHP, Rao G, Mascret N, Laurin J, et al. Interdisciplinary research: a promising approach to investigate elite performance in sports. *Quest*. (2017) 69:65-79. doi: 10.1080/00336297.2016.1152982

20. Ibáñez-Gijón J, Buekers M, Morice A, Rao G, Mascret N, Laurin J, et al. A scale-based approach to interdisciplinary research and expertise in sports. *J Sports Sci*. (2017) 35:290-301. doi: 10.1080/02640414.2016.1164330

21. Piggott B, Müller S, Chivers P, Papaluca C, Hoyne G. Is sports science answering the call for interdisciplinary research? a systematic review. *Europ J Sport Sci*. (2019) 19:267-86. doi: 10.1080/17461391.2018.1508506

22. Montagne G, Bastin J, Jacobs DM. What is visual anticipation and how much does it rely on dorsal stream? *Int J Sport Psychol*. (2008) 39:149-56.

23. Craig CM. Understanding perception and action in sport: how can virtual reality technology help? *Sports Technology*. (2014) 6:161-9. doi: 10.1080/19346182.2013.855224

24. Davids K, Araujo D, Seifert L, Orth D. Expert performance in sport: an ecological dynamics perspective. In: Baker J, Farrow D, editors. *Handbook of Sport Expertise*. New-York, NY: Routledge (2015). p. 130-44.

25. Gibson JJ. *The Ecological Approach to Visual Perception*. Boston, MA: Houghton, Mifflin (1979).

26. Montagne G. Prospective control in sport. *Int J Sport Psychol*. (2005) 36:127-50.

27. Le Noury P, Polman R, Maloney M, Gorman A. A narrative review of the current state of extended reality technology and how it can be utilized in sport. *Sports Med*. (2022) 52:1473-89. doi: 10.1007/s40279-022-01669-0

28. Plumert JM, Kearney JK, Cremer J, Recker K. Distance perception in real and virtual environments. *ACM Trans Appl Percept (TAP)*. (2005) 2:216-23. doi: 10.1145/1077399.1077402

29. Vienne C, Masfrand S, Bourdin C, Vercher JL. Depth perception in virtual reality systems: effect of screen distance, environment richness and display factors. *IEEE Access*. (2020) 8:29099-110. doi: 10.1109/ACCESS.2020.2972122

30. Chang E, Kim HT, Yoo B. Virtual reality sickness: a review of causes and measurements. *Int J Human-Computer Interact*. (2020) 36:1658-82. doi: 10.1080/10447318.2020.1778351

31. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. *Manag Sc*. (2000) 46:186-204. doi: 10.1287/mnsc.46.2.186.11926

32. Mascret N, Montagne G, Devrièse-Sence A, Vu A, Kulpa R. Acceptance by athletes of a virtual reality head-mounted display intended to enhance sport performance. *Psychol Sport Exerc*. (2022) 61:102201. doi: 10.1016/j.psychsport.2022.102201

33. Harris DJ, Wilson MR, Vine SJ. Development and validation of a simulation workload measure: the simulation task load index (SIM-TLX). *Virt Reality*. (2020) 24:557-66. doi: 10.1007/s10055-019-00422-9

34. Legrand FD, Joly PM, Bertucci WM, Soudain-Pineau MA, Marcel J. Interactive-virtual reality (IVR) exercise: an examination of in-task and pre-to-post exercise affective changes. *J Appl Sport Psychol*. (2011) 23:65-75. doi: 10.1080/10413200.2010.523754
## Author contributions

GM: Writing – original draft. NM: Writing – original draft.
MB: Writing – review & editing. LC: Writing – review & editing.
SL: Writing – review & editing. GR: Writing – review & editing.
NT: Writing – review & editing. EV: Writing – review & editing.
RK: Writing – original draft.

## Funding

The author(s) declare financial support was received for the research, authorship, and/or publication of this article.

This work is part of the REVEA project supported by a government grant managed by the French National Research Agency (ANR) as part of the "France 2030" program (20-STHP-0004).

## References

1. Drew L. Training for the impossible. *Nature*. (2021) 592:S4-6. doi: 10.1038/d41586-021-00816-3

2. Beek PJ, Jacobs DM, Daffertshofer A, Huys R. Expert performance in sport: views from the joint perspective of ecological psychology and dynamical systems theory. In: Starkes JL, Ericsson KA, editors. *Expert Performance in Sports: Advances in Research on Sport Expertise*. Champaign, IL: Human Kinetics (2003). p. 321-44.

3. Mann DTY, Williams AM, Ward P, Janelle CM. Perceptual-cognitive expertise in sport: a meta-analysis. *J Sport Exerc Psychol*. (2007) 29:457-78. doi: 10.1123/jsep.29.4.457

4. Hendry DT, Ford PR, Williams AM, Hodges NJ. Five evidence-based principles of effective practice and instruction. In: Baker J, Farrow D, editors. *Handbook of Sport Expertise*. New York, NY: Routledge (2015). p. 414-29.

5. Appelbaum LG, Erickson G. Sports vision training: a review of the state-of-the-art in digital training techniques. *Int Rev Sport Exerc Psychol*. (2018) 11:160-89. doi: 10.1080/1750984X.2016.1266376

6. Harris DJ, Wilson MR, Vine SJ. A systematic review of commercial cognitive training devices: implications for use in sport. *Front Psychol*. (2018) 9:709. doi: 10.3389/fpsyg.2018.00709

7. Miles HC, Pop SR, Watt SJ, Lawrence GP, John NW. A review of virtual environment for training in ball sports. *Comput Graph*. (2012) 36:714-26. doi: 10.1016/j.cag.2012.04.007

8. Gray R. Transfer of training from virtual to real baseball batting. *Front Psychol*. (2017) 8:2183. doi: 10.3389/fpsyg.2017.02183

9. Neumann DL, Moffitt RL, Thomas PR, Loveday K, Watling DP, Lombard CM, et al. A systematic review of the application of interactive VR to sport. *Virtual Real*. (2018) 22:183-98. doi: 10.1007/s10055-017-0320-5

10. Michalski SC, Szpak A, Loetscher T. Using virtual environments to improve real-world motor skills in sports: a systematic review. *Front Psychol*. (2019) 10. doi: 10.3389/fpsyg.2019.02159

11. Faure C, Limballe A, Bideau B, Kulpa R. Virtual reality to assess and train team ball sports performance: a scoping review. *J Sports Sci*. (2020) 38:192-205. doi: 10.1080/02640414.2019.1689807

12. Gray R, Beilock S, Carr TH. "As soon as the bat met the ball, I knew it was gone": outcome prediction, hindsight bias, and the representation and control of action in expert and novice baseball players. *Psychon Bull Rev*. (2017) 14:669-75. doi: 10.3758/BF03196819

13. Campbell MJ, Moran AP. There is more to green reading than meets the eye! exploring the gaze behaviours of expert golfers on a virtual golf putting task. *Cogn Process*. (2014) 15:363-72. doi: DPI: 10.1007/s10339-014-0608-2

14. Vignais N, Bideau B, Craig C, Brault S, Multon F, Delamarche P, et al. Does the level of graphical detail of a virtual handball thrower influence a goalkeeper's motor response? *J Sports Sci Med*. (2014) 8:501-8. PMID: 24149589

15. Brault S, Bideau B, Kulpa R, Craig CM. Detecting deception in movement: the case of the side-step in rugby. *PLoS One*. (2012) e37494. doi: 10.1371/journal.pone.0037494

16. Craig CM, Berton E, Rao G, Fernandez L, Bootsma RJ. Judging where the ball will go: the case of curved free kicks in football. *Naturwissenschaften*. (2006) 93:97-101. doi: 10.1007/s00114-005-0071-0

## Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

## Publisher's note

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.

17. Akbas A, Marszatek W, Kamieniarz A, Polechonski J, Stomka K, Juras G. Application of virtual reality in competitive athletes – a review. *J Hum Kinet*. (2019) 69:5-16. doi: 10.2478/hukin-2019-0023

18. Dücking P, Holmberg HC, Sperlich B. The potential usefulness of virtual reality systems for athletes: a short SWOT analysis. *Front Physiol*. (2018) 9:128. doi: 10.3389/fphys.2018.00128

19. Buekers M, Ibáñez-Gijón J, Morice AHP, Rao G, Mascret N, Laurin J, et al. Interdisciplinary research: a promising approach to investigate elite performance in sports. *Quest*. (2017) 69:65-79. doi: 10.1080/00336297.2016.1152982

20. Ibáñez-Gijón J, Buekers M, Morice A, Rao G, Mascret N, Laurin J, et al. A scale-based approach to interdisciplinary research and expertise in sports. *J Sports Sci*. (2017) 35:290-301. doi: 10.1080/02640414.2016.1164330

21. Piggott B, Müller S, Chivers P, Papaluca C, Hoyne G. Is sports science answering the call for interdisciplinary research? a systematic review. *Europ J Sport Sci*. (2019) 19:267-86. doi: 10.1080/17461391.2018.1508506

22. Montagne G, Bastin J, Jacobs DM. What is visual anticipation and how much does it rely on dorsal stream? *Int J Sport Psychol*. (2008) 39:149-56.

23. Craig CM. Understanding perception and action in sport: how can virtual reality technology help? *Sports Technology*. (2014) 6:161-9. doi: 10.1080/19346182.2013.855224

24. Davids K, Araujo D, Seifert L, Orth D. Expert performance in sport: an ecological dynamics perspective. In: Baker J, Farrow D, editors. *Handbook of Sport Expertise*. New-York, NY: Routledge (2015). p. 130-44.

25. Gibson JJ. *The Ecological Approach to Visual Perception*. Boston, MA: Houghton, Mifflin (1979).

26. Montagne G. Prospective control in sport. *Int J Sport Psychol*. (2005) 36:127-50.

27. Le Noury P, Polman R, Maloney M, Gorman A. A narrative review of the current state of extended reality technology and how it can be utilized in sport. *Sports Med*. (2022) 52:1473-89. doi: 10.1007/s40279-022-01669-0

28. Plumert JM, Kearney JK, Cremer J, Recker K. Distance perception in real and virtual environments. *ACM Trans Appl Percept (TAP)*. (2005) 2:216-23. doi: 10.1145/1077399.1077402

29. Vienne C, Masfrand S, Bourdin C, Vercher JL. Depth perception in virtual reality systems: effect of screen distance, environment richness and display factors. *IEEE Access*. (2020) 8:29099-110. doi: 10.1109/ACCESS.2020.2972122

30. Chang E, Kim HT, Yoo B. Virtual reality sickness: a review of causes and measurements. *Int J Human-Computer Interact*. (2020) 36:1658-82. doi: 10.1080/10447318.2020.1778351

31. Venkatesh V, Davis FD. A theoretical extension of the technology acceptance model: four longitudinal field studies. *Manag Sc*. (2000) 46:186-204. doi: 10.1287/mnsc.46.2.186.11926

32. Mascret N, Montagne G, Devrièse-Sence A, Vu A, Kulpa R. Acceptance by athletes of a virtual reality head-mounted display intended to enhance sport performance. *Psychol Sport Exerc*. (2022) 61:102201. doi: 10.1016/j.psychsport.2022.102201

33. Harris DJ, Wilson MR, Vine SJ. Development and validation of a simulation workload measure: the simulation task load index (SIM-TLX). *Virt Reality*. (2020) 24:557-66. doi: 10.1007/s10055-019-00422-9

34. Legrand FD, Joly PM, Bertucci WM, Soudain-Pineau MA, Marcel J. Interactive-virtual reality (IVR) exercise: an examination of in-task and pre-to-post exercise affective changes. *J Appl Sport Psychol*. (2011) 23:65-75. doi: 10.1080/10413200.2010.523754