A Taxonomy of Virtual Reality Sports Applications

doi:10.21203/rs.3.rs-4749691/v1

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Research Article

A Taxonomy of Virtual Reality Sports Applications

https://doi.org/10.21203/rs.3.rs-4749691/v1

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Although physical fitness is one of the most important factors regarding an individual’s health, many people perceive a lack of motivation. One promising solution is the usage of Virtual Reality (VR) sports applications. Studies showed that VR sport offers several advantages, ranging from a high enjoyment, the improvement of skill quality and motivation, to effectiveness in rehabilitation. The goal of this study is to obtain an overview of research VR sport applications through a systematic literature review and build a taxonomy based on this body of knowledge through an analysis of applications on the market. A comparison of both theory and practice reveals that while research applications often include specific sports movements for a well-defined target group, most market applications are designed for a wider audience and emphasize gamification. Further, market applications often include social experiences and competition that can motivate users significantly. Additionally, we identified whether current VR sports applications align with established learning theories and if their design can thereby facilitate sport skill learning. Our taxonomy offers valuable insights for both researchers and practitioners in the dynamic landscape of VR sports through describing trends and deriving gaps for future research.

Extended Reality

Physical activity has a wide range of positive impacts on humans, ranging from physiological effects, such as strength and stamina or lower obesity rates (Stodden et al. 2008), to psychological effects like higher well-being (Fox 1999) and lower consumption of alcohol (López Villalba et al. 2016; Malm et al. 2019). Besides, active individuals remain more active even in old age (Kjønniksen et al. 2009) and exhibit a higher knowledge of nutrition, exercise, and health (Khan et al. 2012). Despite various benefits, many individuals, especially high school students, perceive a lack of motivation (Papaioannou 1997; Deelen et al. 2018). One factor that contributes to the athletes’ motivation is the presence of competition (Frederick-Recascino, Christina and Schuster-Smith, Hana 2003). However, physical competition is not always feasible, for example due to long travel times, reduced mobility, or weather conditions. One promising solution to all these issues is the usage of virtual reality (VR) sports.

Virtual Reality is a technology characterized through four main attributes: immersion, interactivity, presence, and togetherness (Walsh and Pawlowski 2002). Immersion is the extent to which users can fade out the real world and are stimulated by the virtual world (Witmer and Singer 1998), while interactivity is the modification of elements in this virtual world (Steuer 1992). Presence refers to the feeling of being present in another environment (Witmer and Singer 1998) which can be shared with others (Durlach and Slater 2000). These attributes are usually accomplished through wearing so called head-mounted displays (HMDs). Prominent examples are the HTC Vive or Meta Quest (Steam 2024). Virtual reality, like augmented reality (AR), belongs to the spectrum of extended reality (XR) technologies. However, in contrast to VR, AR enriches the physical world with virtual elements (Milgram et al. 1995). The most prominent application areas of VR are gaming, travelling, and watching movies or videos (Statista 2023). Nearly 30% of the study participants of a survey in Germany declared that they have used VR for sport activities and 19% of thoses even participated in virtual sport events (Statista 2023). These results indicate an overall high interest in the combination of virtual reality and sports.

Existing studies in the field of VR sports highlight several advantages: increased fun, enjoyment and satisfaction (Hassandra et al. 2021; Caserman et al. 2022; Polechoński et al. 2024), the improvement of skill quality (Michalski et al. 2019; Mologne et al. 2022), and of motivation (Pu and Yang 2022; Keller et al. 2022; Gulec et al. 2023). Especially for individuals with reduced mobility and elderly persons, VR environments can be adjusted to meet their special needs (Kwan et al. 2021; Høeg et al. 2023; Yu et al. 2023). VR sport can also reduce the perceived exhaustion and increase the endurance (McMahon et al. 2020; McDonough et al. 2020; Saiz-Gonzalez et al. 2023). Similarly, for children, whose parents often call for more physical activity, VR sports can be a great opportunity (McMichael et al. 2020). However, some studies could not measure an enhancement of the training effect (Witte et al. 2022; Oagaz et al. 2022a; Rutkowski et al. 2022) or observed negative side effects, such as motion sickness (Rodrigues et al. 2020; Kwan et al. 2021). Some study participants also claimed that they missed social aspects of tested VR applications (Høeg et al. 2023; Karatas et al. 2023).

Research theories can help us to understand the potential benefits of VR sports. As VR has the potential to satisfy psychological needs, it raises the question if VR sports applications are designed to maximize intrinsic motivation, engagement, and the learning of new skills in physical activities. According to the cognitive load theory, learning and skill mastery are influenced by intrinsic cognitive load related to the complexity of the task, extrinsic cognitive load from the presentation of information, and germane cognitive load, which involves the processing and integration of new information (Sweller et al. 2011). VR applications can optimize cognitive load by presenting physical exercises in an interactive manner (Haryana et al. 2022). The situated learning theory says that such authentic contexts can enhance learning by providing experiences that mirror real-life settings and include social interaction (Lave and Wenger 1991). VR applications can simulate realistic sports scenarios and facilitate social engagement (Scavarelli et al. 2021). The self-determination theory emphasizes the role of intrinsic motivation in our behavior and learning. According to the self-determination theory, the fulfillment of basic psychological needs for autonomy, competence, and relatedness is essential for intrinsic motivation and optimal well-being (Ryan and Deci 2000). The immersive nature of VR applications can enhance the intrinsic motivation to engage in sport and fitness activities by presenting them as enjoyable and rewarding experiences (Huang et al. 2019; Reer et al. 2022).

The rising interest in VR sports is seen in bibliometric analysis that highlights the rising number of annual publications over the last two decades (Denche-Zamorano et al. 2023). It is also shown that the most important topic in the context of VR fitness is rehabilitation. Although the taxonomy approach in the field of information systems is not widespread, some taxonomies already exist for different VR fields. Examples include VR applications for the treatment of anxiety disorders (Korbel, Jakob et al. 2021), the use of VR in education (Motejlek and Alpay 2021), or VR for cultural heritage practices (Chong et al. 2022). However, we are not aware of such research for VR sports applications. Furthermore, first literature reviews summarize knowledge on VR sports, for example for non-immersive VR (Akbaş et al. 2019) or a small number of VR sports studies (Richlan et al. 2023). However, there is a lack of systematic reviews of VR sports environments, which is why a new literature review, focusing on the applications themselves, is necessary as a base for the taxonomy. By creating a taxonomy of research and commercial applications and comparing results, this study contributes to the research field of VR sports by structuring it and identifying trends and research gaps. Further we evaluate whether current VR sports applications are suitable to learn new skills based on established research theories. With our taxonomy, we want to close the knowledge gap regarding a structured overview of VR sports applications by answering the following research questions:

Which similarities and differences exist between research and commercial VR sports applications and which research gaps derive from that comparison?
Are current VR sports apps designed to effectively support learning?

The scope of our article includes VR sports applications running on HMDs, while excluding other forms of virtual reality, like Cave Automatic Virtual Environment (CAVE) or phone-based VR, with the intent of ensuring a high degree of immersion. In contrast, the differentiation between sporting applications and non-sporting applications is less clear-cut. One definition of sports includes all human activities that involve physical exertion, skill, and competition, governed by formal rules and organizations (Commonwealth of Australia 2011). However, especially in the field of virtual reality application where nearly all apps include human movements, it is challenging to draw a clear line between exergames and games without sports character. We define VR sports applications as applications that (1) can be assigned to a traditional sport, or (2) need to be executed while standing, or (3) can be executed while seated, but require strenuous movements. In edge cases, we discussed specific applications in a group of two researchers.

This paper starts with explaining the methods used in Sec. 2. Afterwards, we summarize literature in Sec. 3 and develop the taxonomy in Sec. 4. After discussing our results in Sec. 5, we conclude the article in Sec. 6.

A solid foundation of knowledge is required prior to developing a taxonomy which is the reason for first conducting a systematic literature review following the PRISMA guidelines (Page et al. 2021) and then creating the taxonomy based on the guidelines by Nickerson et al. (Nickerson et al. 2013).

2.1 Systematic literature review process

We queried two search interfaces: WebOfScience and Scopus. For both we applied the search string (“Virtual Reality” OR VR OR “Head-Mounted Display” OR HMD) AND (Sport OR Fitness) for Title/Abstract/Keywords. This search sting ensures that all articles include both VR devices and sports aspects. We decided to keep the search string very general to allow for a wide range of different kinds of sports. Our search resulted in 4,521 publications in total that were screened by two reviewers. As shown in Fig. 1, the literature screening process consisted of different phases. Before the screening, we removed duplicates from the dataset. Further we conducted a pre-screening where we removed non-English records, records without an available full text, and retracted articles. With the remaining 3,588 records sought for retrieval, we excluded records whose document type differs from an article and all articles older than 2012 since the first commercial HMD, the Oculus Rift, appeared on the market in that year. The remaining 1,951 records were assessed for eligibility. We applied five exclusion criteria in that step to exclude:

articles whose context is out of scope,
articles that include VR but have no focus on sport,
articles that focus on sports but do not utilize VR,
articles that utilized either non-immersive VR or did not specify the headset used, and
articles that did not implement individual applications since we want to compare research applications with apps on the market.

Finally, we conducted a forward and backward search resulting in 8 additional articles. From the final set of 59 studies, we extracted relevant data in the next step, such as headset, controllers, sport type, or avatar. Those categories were developed in an iterative process through analyzing the information provided in included publications. However, not all articles describe their offered application in detail. For some categories, a “not specified” label had to be used.

2.2 Application review process

To find suitable applications, we relied on the most prominent VR app stores, the Meta Quest store and the HTC Vive store (Vive Port). In both app stores, we searched for apps with the search strings “sport” and “fitness”. We decided for that search approach although both app stores have predefined sports categories. However, the text query led to a much higher number of results that also contained the apps from the predefined categories. The app selection process is shown in Fig. 2. First, we removed 124 duplicate applications. For the remaining 408 applications, we screened for eligibility where we applied four exclusion criteria. We removed:

apps whose content is out of scope,
apps that are downloadable content (DLC), i.e. game expansions,
gaming apps without a sports character, and
meditation apps without additional sports.

To reach a higher level of consistency in the app classification, two researchers screened all apps from the initial sample and labeled them. Differences in the classification were discussed for each application. The final 141 applications were used for the taxonomy creation. Because of the large size of the data set, we decided to group them based on the implemented sport and choose a representative application for each group that were screened in detail. To choose adequate representatives, we decided to select apps that are as heterogeneous as possible to achieve a taxonomy representing a wide range of potential VR sports applications. We also paid attention to the amount of information available for the representatives. An overview of the representative application for each sport can be found in Table 1. With the applications, we aimed to represent the most prominent commercially available sport categories for VR.

Table 1. Representative applications used for the taxonomy creation

Sport category	Representative application	Appstore
Baseball	WIN Reality Baseball (P1)	Quest
Cricket	Ib Cricket (P2)	Quest, Valve, Vive
Basketball	Gym Class - Basketball VR (P3)	Quest
Football	CleanSheet Soccer (P4)	Quest
American Football	2MD: VR Football (P5)	Quest, Valve, Vive
Boxing	The Thrill of Fight (P6)	Quest, Valve
Golf	Golf+ (P7)	Quest
Sailing	VR Regatta (P8)	Quest, Valve, Vive
Winter sports	Carve Snowboarding (P9)	Quest
Tennis	First Person Tennis (P10)	Quest, Valve, Vive, Pico
Table Tennis	Eleven Table Tennis (P11)	Quest, Valve, Pico
Racket	Racket: Club (P12)	Quest, Valve, Pico
Dancing	Dance Dash (P13)	Quest, Valve, Vive
Music Games	Synth Riders (P14)	Quest, Valve, Vive, Vision Pro
Exergames	LES MILLS BODYCOMBAT (H15) Holofit by Holodia (P16)	Quest, Vive Quest
Climbing	The Climb ½ (P17)	Quest
Mind-body-practices	Xponential+ (P18)	Quest

2.3 Taxonomy creation process

A taxonomy is a categorization of objects within a domain based on shared characteristics. The taxonomy creation process is based on the method of (Nickerson et al. 2013). They define it as a set of one or more dimensions with several characteristics each. The taxonomy creation process consists of three phases. First, determining meta-characteristics based on the purpose of the taxonomy. Second, determining ending conditions which we adopt from (Nickerson et al. 2013). And finally, iterating until all ending conditions are met. Iterations can be either empirical-to-conceptual starting with object subsets and moving them to dimensions and characteristics, or conceptual-to-empirical, beginning with conceptualizing characteristics and dimensions before examining objects. We added new characteristics in each iteration if (1) the regarded VR sports applications do not fit into the current taxonomy or (2) new dimensions appear that are needed to distinguish between different VR sports apps. Finally both approaches, conceptual and empirical, converge into the last step where the ending conditions are checked. If all ending conditions are fulfilled, the taxonomy creation process is finished. Otherwise, a new iteration needs to be performed (Nickerson et al. 2013). Unlike in the original definition of a taxonomy by Nickerson et al., we decided to allow the classification of VR sports applications into several characteristics of one dimension, if needed. This allows us to waive the listing of all combinatorial possibilities if applications for instance implement several sceneries. Since our literature review delivers first insights into possible VR sports applications, we derived the first version of the taxonomy from the categories and features from the literature review. We analyzed the commercial applications in the following iterations to refine the taxonomy.

The systematic literature review, based on the PRISMA guidelines (Page et al. 2021), intends to depict a knowledge body for the taxonomy.

3.1 Sport categories

In the selected articles, we encountered a wide range of sports, as shown in Table 2. One of the most prominent categories of the regarded studies were exergames, encompassing active applications characterized by playfulness while diverging from traditional kinds of sports. However, conventional sports that include gamification elements belong to separate categories. Examples of exergame applications in the literature are a game where users need to hit viruses (Yang et al. 2022), a game where players need to squat to avoid obstacles while standing on a moving train (Ou et al. 2020), or punching spiders and monster attacking the users (Graf et al. 2023). The most prominent conventional sport in the literature is cycling, where users typically sit on ergometers while the HMD shows an environment that moves during the ride. Other frequently examined sports are soccer, either from the perspective of a player or a goalkeeper, weight training, and boxing. However, we could also identify a wide range of sports with only one or two publications each.

Table 2. Frequency of sport categories in the analyzed literature

Sport category	Quantity	Articles
Cycling	8	(McMahon et al. 2020; Wender et al. 2022; Touloudi et al. 2022; Rutkowski et al. 2022; Mahalil et al. 2023; Rojo et al. 2023; Stavrou et al. 2023; Finnegan et al. 2023)
Exergame	8	(Xu et al. 2020; Ou et al. 2020; Farič et al. 2021; Cao et al. 2021; Naito et al. 2022; Yang et al. 2022; Graf et al. 2023; Ju et al. 2023)
Soccer	6	(Gulec et al. 2019; Rojas Ferrer et al. 2020; Valkanidis et al. 2020; Vu et al. 2022; Krupitzer et al. 2022; Höner et al. 2023)
Weight training	5	(Xiao et al. 2017; Lee et al. 2022; Mologne et al. 2022; Gulec et al. 2023; Wang et al. 2023)
Boxing	4	(Xu et al. 2020; Kwan et al. 2021; Cao et al. 2021; Wender et al. 2022)
Basketball	3	(Panchuk et al. 2018; Tsai et al. 2022; Liu et al. 2024)
Differs	3	(Lin et al. 2021; Wu et al. 2023; Lemmens 2023)
Karate	3	(Petri et al. 2019; Witte et al. 2022; Pastel et al. 2023)
Table Tennis	3	(Wu et al. 2021; Oagaz et al. 2022b; Oagaz et al. 2022a)
Golf	2	(Harris 2019; Harris et al. 2024)
Tai Chi	2	(Banakou et al. 2016; Liang et al. 2018)
Tennis	2	(Le Noury et al. 2021; Gaugne et al. 2022)
Aerobic	1	(Karkar et al. 2018)
Baseball	1	(Nasu et al. 2022)
Climbing	1	(Zhang et al. 2022)
Cricket	1	(Kelly et al. 2022)
Gymnastics	1	(Bürger et al. 2022)
Ice Hockey	1	(Polikanova et al. 2022)
Pilates	1	(Park and Lee 2023)
Skiing	1	(Li et al. 2023)
Volleyball	1	(Bai et al. 2021)
Yoga	1	(Caserman et al. 2022)
Total	59

3.2 Hardware

The category of hardware splits into technical output and input devices, while some studies applied additional external devices. An overview of used headsets can be found in Table 3. The most prominent headsets in the considered studies are HTC Vive and Oculus Rift. Both are wired headsets that need to be connected to computers for the computations. However, according to a statistic by Steam, the market share of those headsets is decreasing while wireless models, such as the Meta Quest are gaining more attention (Steam 2024). Quest headsets are the third most frequently encountered option in the examined literature. Some studies also applied different devices.

Table 3. Headsets in the regarded literature

Headset	Quantity	Articles
HTC Vive	27	(Xiao et al. 2017; Harris 2019; McMahon et al. 2020; Xu et al. 2020; Ou et al. 2020; Valkanidis et al. 2020; Farič et al. 2021; Le Noury et al. 2021; Lin et al. 2021; Oagaz et al. 2022b; Bürger et al. 2022; Zhang et al. 2022; Vu et al. 2022; Caserman et al. 2022; Wender et al. 2022; Naito et al. 2022; Polikanova et al. 2022; Tsai et al. 2022; Limballe et al. 2022; Witte et al. 2022; Kelly et al. 2022; Oagaz et al. 2022a; Mologne et al. 2022; Gulec et al. 2023; Pastel et al. 2023; Höner et al. 2023; Graf et al. 2023)
Oculus Rift	9	(Panchuk et al. 2018; Karkar et al. 2018; Petri et al. 2019; Gulec et al. 2019; Rojas Ferrer et al. 2020; Cao et al. 2021; Krupitzer et al. 2022; Lee et al. 2022; Finnegan et al. 2023)
Meta / Oculus Quest	7	(Bai et al. 2021; Nasu et al. 2022; Touloudi et al. 2022; Mahalil et al. 2023; Rojo et al. 2023; Stavrou et al. 2023; Wu et al. 2023)
Differs	3	(Liang et al. 2018; Gaugne et al. 2022; Li et al. 2023)
HTC Vive Pro	3	(Yang et al. 2022; Ju et al. 2023; Harris et al. 2024)
Pico Neo	2	(Wang et al. 2023; Loiseau Taupin et al. 2023)
Valve Index	2	(Wu et al. 2021; Lemmens 2023)
HP Reverb	1	(Yu et al. 2023)
Microsoft Holo Lens 2	1	(Nekar et al. 2023)
NVIS nVisor SX111	1	(Banakou et al. 2016)
Star VR	1	(Liu et al. 2024)
Tier One	1	(Rutkowski et al. 2022)
Vive Cosmos Elite	1	(Park and Lee 2023)
Total	59

Regarding the user input, which is shown in Table 4, most of the articles specified that they applied controllers, either handheld or attached to an external device, such as a tennis racket (Gaugne et al. 2022) or on an ice hockey stick (Polikanova et al. 2022). Another large number of studies did not specify the usage of controllers whereby it can be assumed that controllers were used due to the inability of some HMDs to track hand movements. Finally, a minority of studies specified that they directly tracked the users’ hands.

Table 4. Input devices in the regarded literature

Input device	Quantity	Articles
Controller	29
Not specified	25
Hands	4
Mouse and keyboard	1	(Gulec et al. 2019)
Total	59

As Table 5 shows, beside controllers, some of the studies included additional devices that are often related to the examined sport. All studies examining VR cycling include either an ergometer or at least pedals for incapacitated individuals that need to sit on a chair. The Xbox Kinect is a device that can track players’ movements and is thus used in some studies. The movements are then displayed in the VR environments to mirror the current body position. The studies on (table) tennis included rackets to make the experiences more realistically while other studies included basketballs, batters, or weights.

Table 5. External devices besides controllers applied in the literature

External devices	Quantity	Articles
Ergometer or pedals	8	(McMahon et al. 2020; Wender et al. 2022; Touloudi et al. 2022; Rutkowski et al. 2022; Mahalil et al. 2023; Rojo et al. 2023; Stavrou et al. 2023; Finnegan et al. 2023)
Xbox Kinect	6	(Liang et al. 2018; Karkar et al. 2018; Rojas Ferrer et al. 2020; Bai et al. 2021; Lin et al. 2021; Oagaz et al. 2022a)
(Table) tennis racket	5	(Le Noury et al. 2021; Wu et al. 2021; Gaugne et al. 2022; Oagaz et al. 2022a; Wu et al. 2023)
Basketball	2	(Panchuk et al. 2018; Liu et al. 2024)
Batter / bat	2	(Nasu et al. 2022; Kelly et al. 2022)
Weights	2	(Lee et al. 2022; Gulec et al. 2023)
Balance beam	1	(Bürger et al. 2022)
Black box VR	1	(Mologne et al. 2022)
Golf putter	1	(Harris 2019)
Ice hockey stick	1	(Polikanova et al. 2022)
Training machine	1	(Lemmens 2023)
Mobile phone	1	(Tsai et al. 2022)
Paddle	1	(Oagaz et al. 2022b)
Thera bands	1	(Park and Lee 2023)
Treadmill	1	(Wang et al. 2023)
Total	32

3.3 Target group

The target groups of our considered studies are shown in Table 6. Most of the studies did not specifically mention a target group and hence have very heterogeneous samples. Studies that did focus on a specific target group were most commonly tested with (professional) athletes, e.g., football applications for football players or goal keepers. However, some experiments were conducted with beginners in specific sports and tried to teach them basic movements rather than refining their technique. While the majority of publications focus on healthy participants or did not specify a focus, some studies explicitly target individuals with reduced mobility, COVID-19 patients, or overweight individuals. Only a small number of publications directly target children or elderly people.

Table 6. Target groups of the considered applications

Target group	Quantity	Articles
Not specified	21	(Banakou et al. 2016; Karkar et al. 2018; Xu et al. 2020; Bai et al. 2021; Cao et al. 2021; Oagaz et al. 2022b; Bürger et al. 2022; Wender et al. 2022; Touloudi et al. 2022; Naito et al. 2022; Gaugne et al. 2022; Yang et al. 2022; Oagaz et al. 2022a; Lee et al. 2022; Finnegan et al. 2023; Pastel et al. 2023; Wang et al. 2023; Nekar et al. 2023; Graf et al. 2023; Park and Lee 2023; Lemmens 2023)
Athletes	17	(Panchuk et al. 2018; Petri et al. 2019; Rojas Ferrer et al. 2020; Valkanidis et al. 2020; Le Noury et al. 2021; Nasu et al. 2022; Vu et al. 2022; Polikanova et al. 2022; Tsai et al. 2022; Krupitzer et al. 2022; Limballe et al. 2022; Witte et al. 2022; Kelly et al. 2022; Mahalil et al. 2023; Gulec et al. 2023; Höner et al. 2023; Liu et al. 2024)
Beginners	8	(Xiao et al. 2017; Harris 2019; Wu et al. 2021; Lin et al. 2021; Caserman et al. 2022; Li et al. 2023; Loiseau Taupin et al. 2023; Harris et al. 2024)
Individuals with reduced mobility	3	(Liang et al. 2018; McMahon et al. 2020; Zhang et al. 2022)
COVID-19 patients	2	(Rutkowski et al. 2022; Stavrou et al. 2023)
Diseased children	2	(Ou et al. 2020; Ju et al. 2023)
Elderly	2	(Rojo et al. 2023; Yu et al. 2023)
Adolescents	1	(Farič et al. 2021)
Individuals with non-regular workouts	1	(Mologne et al. 2022)
Overweight individuals	1	(Wu et al. 2023)
Referees	1	(Gulec et al. 2019)
Total	59

3.4 Characters and avatars

As a representation of the player, some applications implemented avatars. All different kinds of avatars are listed in Table 7. Most studies that applied avatars designed them in a way that represents the considered sport e.g., football players, ice hockey players, or karate athletes. However, some studies relied on minimalistic avatars, meaning that there is a form of a body but without complex textures. Often these avatars are monochrome, e.g., blue and red, depending on the team in the game (Vu et al. 2022). While some studies did not specify how their applied avatars appear, one study implemented a referee avatar.

Table 7. Players’ avatars in the considered applications

Avatar	Quantity	Articles
Athlete	12	(Banakou et al. 2016; Rojas Ferrer et al. 2020; Valkanidis et al. 2020; Lin et al. 2021; Caserman et al. 2022; Polikanova et al. 2022; Krupitzer et al. 2022; Mahalil et al. 2023; Li et al. 2023; Wang et al. 2023; Yu et al. 2023; Nekar et al. 2023)
Minimalistic	5	(Liang et al. 2018; Vu et al. 2022; Naito et al. 2022; Finnegan et al. 2023; Pastel et al. 2023)
Not specified	3	(Bai et al. 2021; Oagaz et al. 2022b; Kelly et al. 2022)
Referee	1	(Gulec et al. 2019)
Total	21

In addition to the player’s avatar, many studies also included other characters, as shown in Table 8. Most prominent are instructors or assistants, i.e. a person guiding the execution of specific movements. These instructors are mostly pre-recorded. Further, some studies implemented one or several opponents. However, these opponents were always controlled by a computer. The same number of research applications implements teammates. Spectators and referees on the other hand were rather rare in the literature.

Table 8. Other avatars or characters in the considered applications

Avatar	Quantity	Articles
Opponent(s)	16	(Petri et al. 2019; Rojas Ferrer et al. 2020; Valkanidis et al. 2020; Wu et al. 2021; Bai et al. 2021; Vu et al. 2022; Tsai et al. 2022; Gaugne et al. 2022; Limballe et al. 2022; Witte et al. 2022; Kelly et al. 2022; Höner et al. 2023; Wang et al. 2023; Loiseau Taupin et al. 2023; Yu et al. 2023; Wu et al. 2023)
Instructor	12	(Banakou et al. 2016; Liang et al. 2018; Karkar et al. 2018; Xu et al. 2020; Cao et al. 2021; Lin et al. 2021; Oagaz et al. 2022b; Oagaz et al. 2022a; Gulec et al. 2023; Pastel et al. 2023; Nekar et al. 2023; Graf et al. 2023)
Teammates	11	(Panchuk et al. 2018; Gulec et al. 2019; Rojas Ferrer et al. 2020; Bai et al. 2021; Vu et al. 2022; Naito et al. 2022; Tsai et al. 2022; Kelly et al. 2022; Höner et al. 2023; Wu et al. 2023; Liu et al. 2024)
Spectators	5	(Rojas Ferrer et al. 2020; Le Noury et al. 2021; Gaugne et al. 2022; Gulec et al. 2023; Yu et al. 2023)
Referee	2	(Le Noury et al. 2021; Gulec et al. 2023)
Total	46

3.5 Application design

The applications in the literature exhibit miscellaneous application designs, ranging from the gameplay variation to the implemented scenery. An overview is listed in Table 9. The levels of the applications in the literature target mostly different tasks, e.g., emergency situations, hazardous environments and high-risk job tasks without being exposed to real danger or injuries in the case of VR skiing (Li et al. 2023). Free kick scenarios are another example in a goalkeeping simulation (Valkanidis et al. 2020). Those applications are summarized in the category of level diversity. Some applications designed levels with increasing difficulty. In the case of tennis, the tennis ball was played with increasing distance to the player (Gaugne et al. 2022).

Table 9. Gameplay variation in the considered applications

Gameplay variation	Quantity	Articles
Level diversity	27	(Xiao et al. 2017; Panchuk et al. 2018; Karkar et al. 2018; Rojas Ferrer et al. 2020; McMahon et al. 2020; Xu et al. 2020; Valkanidis et al. 2020; Farič et al. 2021; Wu et al. 2021; Cao et al. 2021; Zhang et al. 2022; Wender et al. 2022; Krupitzer et al. 2022; Yang et al. 2022; Limballe et al. 2022; Kelly et al. 2022; Lee et al. 2022; Rojo et al. 2023; Stavrou et al. 2023; Finnegan et al. 2023; Pastel et al. 2023; Höner et al. 2023; Li et al. 2023; Wu et al. 2023; Lemmens 2023; Liu et al. 2024; Harris et al. 2024)
Difficulty scaling	4	(Ou et al. 2020; Touloudi et al. 2022; Polikanova et al. 2022; Gaugne et al. 2022)
Total	31

To train different sports, the research applications relied on gameplay sceneries, as presented in Table 10. The most prominent sceneries in the applications are stadiums with spectator stands surrounding the area. Gym environments are similarly popular, displaying either a room with fitness equipment or a larger sports hall. However, some of the studies also relied on natural environments or implemented a range of different environments. Exergame applications are one example that applied different environments to their games, depending on their context (Ou et al. 2020; Wu et al. 2023). Other environments we encountered frequently are sport courts, e.g., tennis courts (Le Noury et al. 2021; Gaugne et al. 2022) or a golf court (Harris 2019), and natural environments, like lakes (Cao et al. 2021) or forests (Liang et al. 2018; Ju et al. 2023). Rather uncommon are environments, such as streets, empty rooms, or boxing rings.

Table 10. Gameplay scenery in the considered applications

Gameplay scenery	Quantity	Articles
Stadium	12	(Gulec et al. 2019; Rojas Ferrer et al. 2020; Valkanidis et al. 2020; Bai et al. 2021; Nasu et al. 2022; Vu et al. 2022; Polikanova et al. 2022; Krupitzer et al. 2022; Kelly et al. 2022; Gulec et al. 2023; Höner et al. 2023; Yu et al. 2023)
Gym	10	(Banakou et al. 2016; Xiao et al. 2017; Karkar et al. 2018; Petri et al. 2019; Lin et al. 2021; Bürger et al. 2022; Witte et al. 2022; Lee et al. 2022; Pastel et al. 2023; Nekar et al. 2023)
Differs	8	(McMahon et al. 2020; Ou et al. 2020; Zhang et al. 2022; Yang et al. 2022; Rojo et al. 2023; Stavrou et al. 2023; Wu et al. 2023; Lemmens 2023)
Court	6	(Panchuk et al. 2018; Harris 2019; Le Noury et al. 2021; Tsai et al. 2022; Gaugne et al. 2022; Liu et al. 2024)
Nature	6	(Liang et al. 2018; Cao et al. 2021; Rutkowski et al. 2022; Park and Lee 2023; Ju et al. 2023; Harris et al. 2024)
Street or road	4	(Wender et al. 2022; Touloudi et al. 2022; Mahalil et al. 2023; Finnegan et al. 2023)
(Empty) room	4	(Xu et al. 2020; Farič et al. 2021; Caserman et al. 2022; Naito et al. 2022)
Boxing ring	3	(Limballe et al. 2022; Wang et al. 2023; Loiseau Taupin et al. 2023)
Table tennis room	3	(Wu et al. 2021; Oagaz et al. 2022b; Oagaz et al. 2022a)
Castle	1	(Graf et al. 2023)
City	1	(Mologne et al. 2022)
Ski resort	1	(Li et al. 2023)
Total	59

The taxonomy creation consists of the taxonomy preparation – determining meta-characteristics and ending conditions - and the iterations themselves until all ending conditions are fulfilled. Finally, we present the resulting taxonomy.

4.1 Taxonomy preparation

For the first step of the taxonomy preparation, determining the meta-characteristics for the taxonomy, we choose “virtual reality sports applications available in the most popular virtual reality app stores”. Further, we apply the ending conditions by (Nickerson et al. 2013). The whole taxonomy creation process is shown in Fig. 3.

4.2 Iterations

Iteration 1. In the first iteration, we follow a conceptual-to-empirical approach, with the literature review providing a strong knowledge base. We directly derive the dimensions from the literature categories in Sec. 3 and convert their features into characteristics. As we have added new dimensions and characteristics in this iteration, another iteration is necessary.

Iteration 2. In this iteration, we adopt an empirical-to-conceptual approach, deriving dimensions and characteristics from VR applications focusing on team-oriented sports, as these show great popularity. They are traditional team-oriented disciplines that have a wide appeal and are well-established in both physical and virtual formats. We examined five different VR sports applications in our database: P1 (WIN Reality Baseball), P2 (ib Cricket), P3 (Gym Glass - Basketball VR), P4 (CleanSheet Soccer), and P5 (2MD: VR Football). Since bat-and-ball sports as well as team ball sports without a bat contain a wide range of possible sports, we decided to summarize related sports to super-category characteristics instead of listing all possible sports. All products operate on the Meta Quest headset. However, two applications are also compatible with HTC Vive and Valve Index (P2 and P5). We decided to limit the “hardware” dimension to the most three prominent HMDs as apps are usually created for popular devices. However, we additionally introduced a characteristic for other headsets. In addition, all five products use controllers for input, with each providing an athlete avatar for the player. In terms of gameplay, all applications involve interaction with other avatars, such as teammates and opponents, and are set in sports venues. We decided to summarize the various venues specific to the respective sport as a single characteristic. Furthermore, P1, P2, P3, and P4 offer a diversity of levels while P2 additionally offers narrative progression which we added as a new characteristic. We also retrieved key facts from the app stores. We noticed that all applications support multiplayer, allowing users to engage with other players. The games can be played in various positions – either seated (P1, P5) or standing (P1, P2, P3, P4). In terms of in-app purchases, P1, P3, and P4 offer this feature, allowing users to buy additional content or features within the game, while P2 and P5 do not. This information requires new dimensions for the multiplayer functionality, the gaming positions to play the applications, and for the possibility to purchase in-app items. As we have identified specific characteristics of these five products in this iteration and added new dimensions, we need to perform another iteration to further refine and expand our taxonomy.

Iteration 3. For the third iteration, we continue with the empirical-to-conceptual approach, examining various sport applications that, contrary to team oriented disciplines, are played individually. They provide a contrast with respect to their unique environments, intensity, and activities. We examined four distinct VR sports applications: P6 (The Thrill of Fight), P7 (Golf+), P8 (VR Regatta), and P9 (Carve Snowboard). Since those applications represent different sports, boxing, golf, sailing, and skiing respectively, we needed to update the “sport category” dimension. All applications, except for P6 and P9, support multiplayer, allowing users to engage with other players. In terms of in-app purchases, P7 and P8 offer new content, while P9 does not specify the type of in-app purchases. As previous applications offer cosmetics while P7 and P8 offer new content only, this observation led to the refinement of the “in-app purchases” dimension, splitting it into “cosmetics”, “content”, and “not specified” to differentiate the type of purchases properly. As we have identified specific characteristics of these applications in this iteration, we need to perform another iteration to further refine and expand our taxonomy.

Iteration 4. For the fourth iteration, we continue with the empirical-to-conceptual approach, examining racket sports and rhythm games. Racket sports and rhythm games add another layer of interaction and skill requirements, both using intense and immersive controller movements and showcasing the diversity of gameplay possible in VR applications. We examined five additional VR sports applications: P10 (First Person Tennis), P11 (Eleven Table Tennis), P12 (Racket: Club), P13 (Dance Dash), and P14 (Synth Riders). These applications show the need for further refinement in our taxonomy. Specifically, we observe that P10, P11, and P12 are better classified under a shared characteristic ("racket sport") within the sport category dimension. Furthermore, we identify P13 and P14 as rhythm games, necessitating the addition of a new characteristic ("rhythm game") under the sport category dimension. This addition accounts for games that involve music and dancing as their central element of gameplay. In terms of external devices, P13 introduces a new method of control by using track straps strapped under one of the player’s legs leading to the addition of a new characteristic. While both P13 and P14, being less traditional sports games, are played in futuristic environments, P11 further offers an urban scenery. Finally, we noticed that P14 offers a multiplayer mode where two players compete on separate maps, with the player with the highest score declared as the winner. This indirect competition differs from the direct competition observed in games like P10, P11, and P12 and previous team sports where players directly interact with each other. Therefore, we refine the “multiplayer” dimension to include specific types of competition, introducing “direct competition” and “indirect competition” in cases where games provide no direct competition but leaderboards to compare their high score with other players around the world as new characteristics as well as “single-player only”. As we've identified specific characteristics of these five products in this iteration, we need to perform another iteration to further refine and expand our taxonomy.

Iteration 5. For the fifth iteration, we continue with the empirical-to-conceptual approach, examining VR applications usually categorized as exergames. Exergames focus on physical fitness and exercise, blending elements of gaming with workout routines. This combination is unique to virtual applications, and they highlight how VR can be used not only for entertainment but also for promoting health and fitness. We examined four distinct VR sports applications: P15 (LES MILLS BODYCOMBAT), P16 (Holofit by Holodia), P17 (The Climb 1/2), and finally P18 (Xponential+). P15 and P16 are identified as exergames, P16 additionally contains cycling, and P17 represents climbing, reinforcing the existing characteristics within the “sport category” dimension, and finally P18 represents an application for different mind-body practices such as Pilates. P16 highlights the need for further refinement in our taxonomy. Instead of relying on controllers, P16 can also utilize hand tracking, introducing a new method of interaction. This observation leads to the creation of a new dimension, "tracking", with characteristics including “roomscale”, “hand tracking”, and “none”. In terms of payment models, most of the previously examined applications followed a pay-to-play model, with one exception that was free-to-play (P3). However, P16 and P18 introduce a subscription model, adding a new type of payment model to our taxonomy. This observation leads to the introduction of a new dimension, the "payment model", with characteristics including "pay-to-play", "free-to-play", and "subscription". As we have identified specific characteristics of these three products in this iteration, we need to perform another iteration to further refine and expand our taxonomy.

Iteration 6. Although all representative applications were examined in the last iterations, our database contains many further applications that have not been screened in detail yet and therefore need to be classified in our taxonomy. Thus, we stick with the empirical-to-conceptual approach. During the classification phase of the remaining applications, we recognized some dimensions that require further characteristics. Therefore, a “miscellaneous” characteristic was added for the “sport category” and “animal”, “casual”, and “torso-only” characteristics were added for the “avatar” dimension. Some of the remaining applications did not specify their gameplay variation or implemented miscellaneous or fantasy/sci-fi environments. One of the research applications uses the gaming position lying, leading to a new characteristic. Further, we could identify applications that allow for song package purchases inside the apps. Finally, we summarized the two dimensions “external devices” and “target group” where we created summarizing categories for their characteristics. Since new dimensions were added, we need another iteration.

Iteration 7. Having examined all applications from the database in the previous iterations, the approach in this iteration transitions to conceptual-to-empirical while maintaining consistency in all dimensions. Since nothing changed in this iteration and all dimensions and characteristics are unique, all objective ending conditions are met. Further the final taxonomy achieves a balance between conciseness and robustness as well as being comprehensive. Together with the explanations given in this article and the possibility to add new dimensions and characteristics, the taxonomy also meets the subjective ending conditions. Hence, the development process concludes.

4.3 Final taxonomy

The final taxonomy consists of 15 dimensions, as shown in Fig. 4. Our classification includes the 18 applications that were screened in detail for the taxonomy creation as well as the total number of appearances of specific characteristics amongst all 141 sports apps from two app stores and all 59 research apps.

Hardware. During our app store screening we observed that most apps run on HTC Vive, followed by Meta Quest while only a minority is available for other headsets. While most of the apps allowed controller input, only a few enabled hand tracking. External devices, such as sports or fitness equipment, were rather rare. Most of the apps tracked the whole room, called roomscale, while some applications tracked the users’ hands.

Application purpose. The identified applications cover a wide range of sports. Most popular are team ball sport that do not include the usage of bats, rhythm games, racket sport, bat-and-ball sport, and exergames. Overall, most of the remaining popular sports are also covered by VR applications. While commercial applications did not specify a target group, research applications targeted different age, fitness, and health levels. For those applications explicitly mentioning a gaming position, standing is encountered most often while a minority of applications allow sitting. The gameplay variation that is most popular is level diversity, meaning that the user can choose between different levels, e.g., different songs in rhythm games. However, in some applications the users can follow a story or career, which we call narrative progression. Only a few applications apps offer difficulty scaling within their levels.

Application design. Most of the applications apply training facilities or nature environments as gameplay sceneries. The third most common scenery we encountered were sport venues. Aside from those natural sports environments, other applications implemented futuristic, fantasy, or sci-fi environments. Urban and empty sceneries were rather rare. While most of the commercial applications include gamification, research applications do not.

Game entities. Those applications implementing avatars mostly relied on athletes. However, some applications also implemented torso-only, minimalistic, animal, or casually dressed avatars. In the category of other avatars, opponent(s), spectators, and teammates are popular while a minority of applications implemented instructors or animals.

Payment. Most of the commercial applications need to be purchased once to play them, which we call pay-to-play. Only a small number of apps are either free-to-play or require a subscription. Some commercial applications additionally offer in-app purchases, either for content, cosmetics, or song packages.

Social interaction. A minority of applications allow multiple players to interact during the games. However, some of the commercial applications included direct competition, meaning that players are within the same environment and can see each other. Some commercial applications also implemented indirect competition, e.g., score boards where players can compare themselves to others despite competing on their own.

In the following section, we critically examine our findings from the literature review and compare them with our final taxonomy. This comparison allows us to identify differences and similarities between research and commercial VR sports applications, providing a differentiated understanding of the current approaches. Further we evaluate whether current VR sports applications are designed in a way which supports learning. We then explore potential future research avenues and reflect on the limitations of our study.

5.1 Comparison of theory and practice

Our investigation into VR sports applications reveals that VR sports applications in the literature and in the app stores share several similar characteristics while also showing a range of differences which are depicted in Fig. 5. Our criteria for the comparison of theory and practice derive from the final taxonomy and the occurrence of different characteristics. Both literature and actual applications run on mainly two HMDs, the HTC Vive and Oculus/Meta devices like the newer Meta Quest which are prevalent due to their technological advancements and market penetration. This is congruent to headset statistics, e.g. by Steam. These devices are favored for their high-resolution displays, precise tracking, and large developer ecosystems making them the devices of choice for delivering immersive VR experiences.

Further, the usage of handheld controllers is very popular in theory and practice and a demonstration to the maturity of this input method. Controllers offer haptic feedback, which is essential for the tactile sensations that improve the VR experience, especially in sports applications where physical engagement is a key factor. Hand tracking, while promising, has yet to achieve the same level of precision and reliability, although it shows a possibility for future innovation in VR interactivity. Note that some HMDs are limited to controller input only and do not support hand tracking, such as the HTC Vive. Studies also showed that users feel a higher arousal and dominance when using controllers in comparison to hand tracking (Voigt-Antons et al. 2020).

Another similarity is the implementation of avatars for the users themselves and other entities, such as teammates, opponents, spectators, and trainers. Avatars play a crucial role in both research and commercial applications enhancing the sense of presence in the virtual environment. In research applications, avatars are often designed to replicate the real-world movements of the users. This is particularly important for applications focused on skill acquisition or rehabilitation, where accurate movement replication is essential for immersion. Commercial applications, in addition, may often employ avatars for their motivational and engagement value, offering options to customize their avatars allowing users to personalize their virtual representation. This can lead to increased user attachment to the VR application and a more enjoyable experience which is crucial for keeping long-term engagement. Additionally, sharing virtual environments with other people is a key characteristic that classifies virtual reality (Walsh and Pawlowski 2002). As such, sports such as soccer, basketball, or table tennis rely on other players each with their own avatar. However, even for sports that do not require the usage of other players, additional characters can enhance the VR experience. For instance, the presence and feedback from an audience increases motivation and leads to better performance (Yu et al. 2023).

Aside from these similarities, we could also identify various differences. The first aspect only present in research applications is the definition of target groups. Research applications target specific user groups in their studies, such as athletes, the elderly, or individuals with mobility impairments, and tailor their VR experience accordingly. This targeting allows for controlled experimentation and the collection of specific data to assess the effectiveness of VR experiences for these particular groups. Commercial applications, by contrast, aim to attract a broader audience, offering VR experiences that are accessible and enjoyable for users of different fitness levels, seniority, and interests. This could be due to the playful character as well as various difficulty levels and a variety of activities that allows users from any age and fitness to use these apps. From a business perspective, designing for a broad audience could increase the number of downloads and hence the revenue generated of actual applications.

Furthermore, research applications often applied external devices alongside controllers, such as ergometers, Xbox Kinect, or sports equipment like rackets and bats. The integration of external devices in research applications is often motivated by the desire to simulate real-world conditions or enhance the precision of data collection in their studies. Those devices help users to realistically reproduce the feeling of conventional sport providing valuable feedback on the user's performance and helping the translation of VR training into real-world improvements. However, commercial sports apps are limited in their adoption of additional devices, possibly due to the additional costs for potential users in addition to the hardware expenses for the headset and the application. Commercial applications focus on a seamless user experience that minimizes the entry barriers. Requiring additional devices could deter potential users from downloading. Hence the additional effort may not be worth the implementation expense (Caserman et al. 2022). By removing external devices as a requirement, developers can simplify the setup process, lower the expenses for user, and potentially increase the marketability of their application. The trade-off is a less specialized VR experience, but one that is more accessible to the average consumer.

Another aspect of commercial VR sports applications is the kind of training. In the literature, specific skills are usually trained. They focus more on the competitive aspects of sports, aligning with the research-driven nature of these implementations. The goal is to use the capabilities of VR to improve particular aspects of fitness or rehabilitation in a controlled and measurable way. On the other hand, fun is the main aspect of commercial applications. Their objective is to provide an engaging and enjoyable fitness experience that encourages regular use and promotes well-being. Commercial applications often apply the concept of gamification, which might be due to the popularity of gaming in VR (Metamandrill 2023). Gamification in sports apps can fulfill users’ needs for competence, autonomy, and relatedness (Bitrián et al. 2020) and can directly impact behavioral intentions (Habachi et al. 2024) and users’ mood (Huang et al. 2017). By integrating gamified elements such as point scoring, achievements, and progress tracking, these applications motivate the users intrinsically and provide a sense of accomplishment.

The last literature feature that stands out compared to commercial applications is the concept of social experiences, e.g., sharing the environments with other players which is one of the main characteristics of virtual reality (Walsh and Pawlowski 2002). Recent studies showed that making sports apps social can be effective to integrate sports routines in users’ daily life (Tu et al. 2019). The concept of social experiences in VR fitness applications is particularly promoted in commercial implementations. These applications often feature multiplayer modes, leaderboards, and other social sharing capabilities. The addition of these social elements to VR applications not only reflects the community aspects of team sports, but also serves the human desire for social interaction. However, for applications in literature that focus on the training of athletic skills, the additional implementation effort of making the VR apps social could be unnecessary for their specific research questions. Research applications may include other avatars, such as coaches or opponents, but these are usually controlled by AI or are pre-recorded, and they lack the social interaction that human players provide. While this can be sufficient for the purposes of a controlled study, it does not utilize the full potential of VR to create social, and interactive VR environments that goes beyond the individual experience. Regarding commercial applications, VR sports applications often include competition, either directly or indirectly. This is linked to the inclusion of social aspects since the contact with other players within the VR applications often leads to rivalry. These competitive features are not only fun but also provide players with ambitious goals and benchmarks for success. Interindividual rivalry can lead to higher sports performance and motivation (Kilduff 2014) and could hence encourage users to purchase and download VR sports apps. Research applications may include competitive elements, but these are usually secondary to the main research objectives.

5.2 Accordance of VR applications with learning theories

The taxonomy developed in our study provides a structured overview of the characteristics of VR sports applications, which can be analyzed based on the cognitive load theory, the situated learning theory, and the self-determination theory.

The findings from our taxonomy show that both research-based and commercially available VR sports applications often use immersive and interactive environments to display physical exercises. According to the cognitive load theory, the immersive presentation inside VR can reduce extrinsic cognitive load and enhance germane cognitive load by allowing users to focus on the task at hand (Sweller et al. 2011). The taxonomy reveals that applications vary in complexity, from various difficulty settings in simple rhythm games to diverse gameplay modes in more complex team sports simulations, meaning that developers implicitly address the intrinsic cognitive load by designing tasks to different skill levels. This finding aligns with the theory on handling cognitive load to improve learning and skill development on an optimal level (Haryana et al. 2022).

Our taxonomy also highlights the diverse range of realistic scenarios and contexts that VR sports applications offer, from sport venues to natural environments. The situated learning theory says that such authentic contexts can enhance learning by providing experiences that mirror real-life settings (Lave & Wenger, 1991). The inclusion of multiplayer and competitive elements like leaderboards supports situated learning by facilitating social interaction within the learning environment. This is consistent with our taxonomy's findings where multiplayer is a key component of many commercial VR sports applications, improving the training of skills through cooperation and competition (Scavarelli et al. 2021). However, in contrast, most VR research applications are single-player only which could limit the learning possibilities based on the situated learning theory.

The taxonomy's insights support the principles of self-determination, particularly the basic needs theory. Research-based and commercially available VR sports applications offer autonomy through various gameplay options and customizable experiences in cosmetics or difficulty. By addressing the need for autonomy, VR sports applications can promote intrinsic motivation and encourage users to engage in physical activities (Ryan and Deci 2000). The taxonomy also shows that applications provide feedback and track progress by collecting points for various actions, which supports the need of competence. Moreover, the social interaction facilitated by multiplayer game modes in commercial applications addresses the need for relatedness.

5.3 Future research avenues

Since our taxonomy revealed specific characteristics with limited research applications, we could identify future research avenues to potential research fields.

Effectiveness of VR rhythm games. Current research focusses mostly on cycling, soccer, and exergames. However, within the app stores, rhythm games are very popular. Since the market share of these kinds of applications is relatively high, a deeper understanding of the effectiveness of such games on the users’ health is necessary.

Theoretical validation of VR water and winter sports. Although a range of VR water and winter sports applications are available on the market, the existing research base remains sparse. We could only identify one study examining skiing and ice-skating. Given the popularity of both sports, alongside with other winter and water sports, these areas present a great research opportunity.

Effect of gamification. Several studies showed the positive impact of gamification in sports apps (Huang et al. 2017; Bitrián et al. 2020; Habachi et al. 2024). However, the research on gamified VR sports apps is rather limited. Although there are some research applications that are exergames, a direct comparison of VR sports apps that are either gamified or serious could increase the understanding whether insights from conventional sports apps can be transferred to VR apps.

Influence of social aspects on user experience. Additionally, the integration of social aspects, i.e., playing with or against other users, represents a significant area for future research. Although many research applications include other avatars, such as teammates, opponents, or spectators, those avatars are computer controlled and do not represent actual users. The potential for real time human-to-human interaction within VR sports applications is yet to be explored. Since togetherness is a key features of virtual realities (Walsh and Pawlowski 2002) and can be motivating for conventional sports applications (Tu et al. 2019), studies could combine the exploration of social effects in multiplayer to investigate how social features such as cooperative or competitive multiplayer modes affect the users in motivation and overall fitness. The application of togetherness in VR sports apps is therefore an important future research avenue.

5.4 Limitations

We want to acknowledge the limitations encountered in our study. The first limitation is related to the focus we set on peer-reviewed articles while excluding all other document types. While this focus ensures a high quality of the results, other literature, that might implement further interesting VR sports applications, is omitted. This approach may have excluded valuable insights from conference proceedings and grey literature, which could provide a more comprehensive picture of the current state of VR sports applications. Further, we only included studies that specified the use of immersive HMDs potentially overlooking applications developed for other output devices which might provide valuable insight as well. As VR continues to evolve, future research should consider a broader range of devices to fully understand the diversity of VR sports experiences. Our third limitation refers to the literature search. We decided to keep the search string as general as possible to include a wide range of sports. While intentionally broad to capture a wide range of sports, this may have missed studies that used more specific approaches or focused on niche applications. Refining the search string through adding specific kinds of sport or expanding the search to include additional databases might have led to more results. To compensate that, we included a detailed forward and backward search to gather further articles in the considered sports. Finally, we needed to exclude some promising articles due to unavailability despite a full text request. It highlights the challenges of accessing relevant literature, which may have impacted the comprehensiveness of our literature review. Ensuring a better access to publications could reduce this limitation in future studies.

This study has made several significant contributions to the field of VR sports. First, we created a taxonomy in an iterative process which is based on results of a systematic literature review regarding VR sports applications. Building upon this knowledge, we conducted a comprehensive comparison between research applications portrayed in the literature and the actual landscape of VR sports apps available in commercial markets. Our analysis revealed both similarities and differences, shedding light on the evolution of VR technology within the sports domain. We revealed that the differences between research and commercial VR sports applications highlight the distinct priorities and constraints of each domain. While literature applications mostly focus on specific skills of defined groups in order to conduct scientific research under controlled conditions, commercial apps operate in a market-driven environment where user engagement and the viability of monetization are crucial. Therefore, they are designed for a wide range of people and designed in a fun, motivating and competitive way. Both contribute valuable insights to VR sports, with research applications improving our understanding of the potential usage of VR for health and fitness and commercial applications driving user approval and user adoption. Derived from this comparison, we could identify several areas that require further research. Another contribution of this study is related to learning theories. We showed that many VR sports applications are designed in a way which supports learning. However, social aspects have been neglected in research so far.

In conclusion, this study contributes to the understanding of VR sports applications by synthesizing theoretical knowledge with real-world observations. By identifying aspects of convergence and disparity, we provide valuable insights for researchers, developers and practitioners aiming to leverage VR technology for sports-related experiences.

Data availability

The extracted data that support the findings of this study are not openly available due to reasons of sensitivity and are available from the corresponding authors upon reasonable request.

Authors contributions

Conceptualization: Sophia Elsholz; Methodology: Sophia Elsholz; Formal analysis and investigation: Sophia Elsholz and Kevin Pham; Writing - original draft preparation: Sophia Elsholz, Kevin Pham; Writing - review and editing: Sophia Elsholz, Kevin Pham, Rüdiger Zarnekow; Resources: Sophia Elsholz, Kevin Pham; Supervision: Rüdiger Zarnekow

Competing interests

The authors declare that there are no conflicts of interest regarding the publication of this paper.

Funding

No funding was received to assist with the preparation of this manuscript.

Akbaş A, Marszałek W, Kamieniarz A, Polechoński J, Słomka KJ, Juras G (2019) Application of Virtual Reality in Competitive Athletes – A Review. Journal of Human Kinetics 69:5–16. https://doi.org/10.2478/hukin-2019-0023
Bai Z, Yao N, Mishra N, Chen H, Wang H, Magnenat Thalmann N (2021) Enhancing Emotional Experience by Building Emotional Virtual Characters in VR Volleyball Games. Computer Animation & Virtual 32:e2008. https://doi.org/10.1002/cav.2008
Banakou D, Hanumanthu PD, Slater M (2016) Virtual Embodiment of White People in a Black Virtual Body Leads to a Sustained Reduction in Their Implicit Racial Bias. Front Hum Neurosci 10. https://doi.org/10.3389/fnhum.2016.00601
Bitrián P, Buil I, Catalán S (2020) Gamification in sport apps: the determinants of users’ motivation. EJMBE 29:365–381. https://doi.org/10.1108/EJMBE-09-2019-0163
Bürger D, Ritter Y, Pastel S, Sprich M, Lück T, Hacke M, Stucke C, Witte K (2022) The Impact of Virtual Reality Training on Learning Gymnastic Elements on a Balance Beam with Simulated Height. International Journal of Computer Science in Sport 21:93–110. https://doi.org/10.2478/ijcss-2022-0005
Cao L, Peng C, Dong Y (2021) Ellic’s Exercise Class: promoting physical activities during exergaming with immersive virtual reality. Virtual Reality 25:597–612. https://doi.org/10.1007/s10055-020-00477-z
Caserman P, Liu S, Gobel S (2022) Full-Body Motion Recognition in Immersive- Virtual-Reality-Based Exergame. IEEE Trans Games 14:243–252. https://doi.org/10.1109/TG.2021.3064749
Chong HT, Lim CK, Rafi A, Tan KL, Mokhtar M (2022) Comprehensive systematic review on virtual reality for cultural heritage practices: coherent taxonomy and motivations. Multimedia Systems 28:711–726. https://doi.org/10.1007/s00530-021-00869-4
Commonwealth of Australia (2011) National Sport and Active Recreation Policy Framework. https://parksleisure.com.au/wp-content/uploads/parc-library/569-0-National%20Sport%20and%20Active%20Recreation%20Policy.pdf. Accessed 10 Jun 2024
Deelen I, Ettema D, Kamphuis CBM (2018) Sports participation in sport clubs, gyms or public spaces: How users of different sports settings differ in their motivations, goals, and sports frequency. PLoS ONE 13:e0205198. https://doi.org/10.1371/journal.pone.0205198
Denche-Zamorano A, Rodriguez-Redondo Y, Barrios-Fernandez S, Mendoza-Muñoz M, Castillo-Paredes A, Rojo-Ramos J, Garcia-Gordillo MA, Adsuar JC (2023) Rehabilitation Is the Main Topic in Virtual and Augmented Reality and Physical Activity Research: A Bibliometric Analysis. Sensors 23:2987. https://doi.org/10.3390/s23062987
Durlach N, Slater M (2000) Presence in Shared Virtual Environments and Virtual Togetherness. Presence: Teleoperators & Virtual Environments 9:214–217. https://doi.org/10.1162/105474600566736
Farič N, Smith L, Hon A, Potts HWW, Newby K, Steptoe A, Fisher A (2021) A Virtual Reality Exergame to Engage Adolescents in Physical Activity: Mixed Methods Study Describing the Formative Intervention Development Process. J Med Internet Res 23:e18161. https://doi.org/10.2196/18161
Finnegan SL, Dearlove DJ, Morris P, Freeman D, Sergeant M, Taylor S, Pattinson KTS (2023) Breathlessness in a virtual world: An experimental paradigm testing how discrepancy between VR visual gradients and pedal resistance during stationary cycling affects breathlessness perception. PLoS ONE 18:e0270721. https://doi.org/10.1371/journal.pone.0270721
Fox KR (1999) The influence of physical activity on mental well-being. Public Health Nutr 2:411–418. https://doi.org/10.1017/S1368980099000567
Frederick-Recascino, Christina, Schuster-Smith, Hana (2003) Competition and intrinsic motivation in physical activity: A comparison of two groups.
Gaugne R, Barreau J-B, Duc-Martin P, Esnault E, Gouranton V (2022) Sport heritage in VR: Real tennis case study. Front Virtual Real 3:922415. https://doi.org/10.3389/frvir.2022.922415
Graf L, Abramowski S, Born F, Masuch M (2023) Emotional Virtual Characters for Improving Motivation and Performance in VR Exergames. Proc ACM Hum-Comput Interact 7:1115–1135. https://doi.org/10.1145/3611063
Gulec U, Isler IS, Doganay MH, Gokcen M, Gozcu MA, Nazligul MD (2023) Power‐VR: Interactive 3D virtual environment to increase motivation levels of powerlifters during training sessions. Computer Animation & Virtual 34:e2045. https://doi.org/10.1002/cav.2045
Gulec U, Yilmaz M, Isler V, O’Connor RV, Clarke PM (2019) A 3D virtual environment for training soccer referees. Computer Standards & Interfaces 64:1–10. https://doi.org/10.1016/j.csi.2018.11.004
Habachi S, Matute J, Palau-Saumell R (2024) Gamify, engage, build loyalty: exploring the benefits of gameful experience for branded sports apps. JPBM 33:57–75. https://doi.org/10.1108/JPBM-07-2022-4070
Harris D (2019) Exploring sensorimotor performance and user experience within a virtual reality golf putting simulator. PsyArXiv
Harris D, Donaldson R, Bray M, Arthur T, Wilson M, Vine S (2024) Attention computing for enhanced visuomotor skill performance: Testing the effectiveness of gaze-adaptive cues in virtual reality golf putting. Multimed Tools Appl. https://doi.org/10.1007/s11042-023-17973-4
Haryana MRA, Warsono S, Achjari D, Nahartyo E (2022) Virtual reality learning media with innovative learning materials to enhance individual learning outcomes based on cognitive load theory. The International Journal of Management Education 20:100657. https://doi.org/10.1016/j.ijme.2022.100657
Hassandra M, Galanis E, Hatzigeorgiadis A, Goudas M, Mouzakidis C, Karathanasi EM, Petridou N, Tsolaki M, Zikas P, Evangelou G, Papagiannakis G, Bellis G, Kokkotis C, Panagiotopoulos SR, Giakas G, Theodorakis Y (2021) Α Virtual Reality App for Physical and Cognitive Training of Older People With Mild Cognitive Impairment: Mixed Methods Feasibility Study. JMIR Serious Games 9:e24170. https://doi.org/10.2196/24170
Høeg ER, Andersen NB, Malmkjær N, Vaaben AH, Uth J (2023) Hospitalized older adults’ experiences of virtual reality-based group exercise therapy with cycle ergometers: An early feasibility study. Computers in Human Behavior Reports 11:100301. https://doi.org/10.1016/j.chbr.2023.100301
Höner O, Dugandzic D, Hauser T, Stügelmaier M, Willig N, Schultz F (2023) Do you have a good all-around view? Evaluation of a decision-making skills diagnostic tool using 360° videos and head-mounted displays in elite youth soccer. Front Sports Act Living 5:1171262. https://doi.org/10.3389/fspor.2023.1171262
Huang H-C, Wong M-K, Yang Y-H, Chiu H-Y, Teng C-I (2017) Impact of Playing Exergames on Mood States: A Randomized Controlled Trial. Cyberpsychology, Behavior, and Social Networking 20:246–250. https://doi.org/10.1089/cyber.2016.0322
Huang Y-C, Backman SJ, Backman KF, McGuire FA, Moore D (2019) An investigation of motivation and experience in virtual learning environments: a self-determination theory. Educ Inf Technol 24:591–611. https://doi.org/10.1007/s10639-018-9784-5
Ju Y-J, Du Y-C, Huang H-C, Hu Kao P-S, Cherng R-J (2023) Development and feasibility of a virtual reality-based exergaming program to enhance cardiopulmonary fitness in children with developmental coordination disorder. Front Pediatr 11:1238471. https://doi.org/10.3389/fped.2023.1238471
Karatas E, Sunday K, Apak SE, Li Y, Sun J, Batmaz AU, Barrera Machuca MD (2023) “\”I consider VR Table Tennis to be my secret weapon!\": An Analysis of the VR Table Tennis Players’ Experiences Outside the Lab". In: Proceedings of the 2023 ACM Symposium on Spatial User Interaction. ACM, Sydney NSW Australia, pp 1–12
Karkar A, AlMaadeed S, Salem R, AbdelHady M, Abou-Aggour S, Samea H (2018) KinFit: A Factual Aerobic Sport Game with Stimulation Support. Int J Emerg Technol Learn 13:50. https://doi.org/10.3991/ijet.v13i12.8626
Keller N, Whittle RS, McHenry N, Johnston A, Duncan C, Ploutz-Snyder L, Torre GGDL, Sheffield-Moore M, Chamitoff G, Diaz-Artiles A (2022) Virtual Reality “exergames”: A promising countermeasure to improve motivation and restorative effects during long duration spaceflight missions. Front Physiol 13:932425. https://doi.org/10.3389/fphys.2022.932425
Kelly N, Stafford J, Craig C, Herring MP, Campbell M (2022) Using a virtual reality cricket simulator to explore the effects of pressure, competition anxiety on batting performance in cricket. Psychology of Sport and Exercise 63:102244. https://doi.org/10.1016/j.psychsport.2022.102244
Khan KM, Thompson AM, Blair SN, Sallis JF, Powell KE, Bull FC, Bauman AE (2012) Sport and exercise as contributors to the health of nations. The Lancet 380:59–64. https://doi.org/10.1016/S0140-6736(12)60865-4
Kilduff GJ (2014) Driven to Win: Rivalry, Motivation, and Performance. Social Psychological and Personality Science 5:944–952. https://doi.org/10.1177/1948550614539770
Kjønniksen L, Anderssen N, Wold B (2009) Organized youth sport as a predictor of physical activity in adulthood. Scandinavian Med Sci Sports 19:646–654. https://doi.org/10.1111/j.1600-0838.2008.00850.x
Korbel, Jakob, Meywirth, Sophia, Zarnekow, Rüdiger (2021) A Taxonomy of Virtual Reality Applications for the Treatment of Anxiety Disorders. ECIS 2021 Proceedings
Krupitzer C, Naber J, Stauffert J-P, Mayer J, Spielmann J, Ehmann P, Boci N, Bürkle M, Ho A, Komorek C, Heinickel F, Kounev S, Becker C, Latoschik ME (2022) CortexVR: Immersive analysis and training of cognitive executive functions of soccer players using virtual reality and machine learning. Front Psychol 13:754732. https://doi.org/10.3389/fpsyg.2022.754732
Kwan RYC, Liu JYW, Fong KNK, Qin J, Leung PK-Y, Sin OSK, Hon PY, Suen LW, Tse M-K, Lai CK (2021) Feasibility and Effects of Virtual Reality Motor-Cognitive Training in Community-Dwelling Older People With Cognitive Frailty: Pilot Randomized Controlled Trial. JMIR Serious Games 9:e28400. https://doi.org/10.2196/28400
Lave J, Wenger E (1991) Situated Learning: Legitimate Peripheral Participation, 1st edn. Cambridge University Press
Le Noury P, Buszard T, Reid M, Farrow D (2021) Examining the representativeness of a virtual reality environment for simulation of tennis performance. Journal of Sports Sciences 39:412–420. https://doi.org/10.1080/02640414.2020.1823618
Lee J, Lee Y, Park S (2022) Virtual Gymnasium: Personalized Weight Perception Interface in Lifting Virtual Objects. Applied Sciences 12:12414. https://doi.org/10.3390/app122312414
Lemmens JS (2023) Persistence and pleasure in VR: Enhancing Exercise Endurance and Enjoyment through Virtual Environments. Psychology of Sport and Exercise 69:102494. https://doi.org/10.1016/j.psychsport.2023.102494
Li T, Wang H, Zhou B, Li Z, Chen Z, Lan Q, Fan D (2023) Design and feasibility study of a HCPS framework-based VR alpine skiing decision-making training system. Computers & Graphics 114:138–149. https://doi.org/10.1016/j.cag.2023.06.007
Liang Y, Wu D, Ledesma D, Davis C, Slaughter R, Guo Z (2018) Virtual Tai-Chi System: A smart-connected modality for rehabilitation. Smart Health 9–10:232–249. https://doi.org/10.1016/j.smhl.2018.07.021
Limballe A, Kulpa R, Vu A, Mavromatis M, Bennett SJ (2022) Virtual reality boxing: Gaze-contingent manipulation of stimulus properties using blur. Front Psychol 13:902043. https://doi.org/10.3389/fpsyg.2022.902043
Lin J-HT, Wu D-Y, Yang J-W (2021) Exercising With a Six Pack in Virtual Reality: Examining the Proteus Effect of Avatar Body Shape and Sex on Self-Efficacy for Core-Muscle Exercise, Self-Concept of Body Shape, and Actual Physical Activity. Front Psychol 12:693543. https://doi.org/10.3389/fpsyg.2021.693543
Liu P-X, Pan T-Y, Lin H-S, Chu H-K, Hu M-C (2024) VisionCoach: Design and Effectiveness Study on VR Vision Training for Basketball Passing. IEEE Trans Visual Comput Graphics 1–14. https://doi.org/10.1109/TVCG.2023.3335312
Loiseau Taupin M, Romeas T, Juste L, Labbé DR (2023) Exploring the effects of 3D-360°VR and 2D viewing modes on gaze behavior, head excursion, and workload during a boxing specific anticipation task. Front Psychol 14:1235984. https://doi.org/10.3389/fpsyg.2023.1235984
López Villalba F, Rodríguez García P, García Cantó E, Pérez Soto J (2016) Relationship between sport and physical activity and alcohol consumption among adolescents students in Murcia (Spain). Arch Argent Pediat. https://doi.org/10.5546/aap.2016.eng.101
Mahalil IB, Yusof ABM, Ibrahim NB, Mahidin EMBM, Hwa NH (2023) A Fully Immersive Virtual Reality Cycling Training (vProCycle) and its Findings. IJACSA 14. https://doi.org/10.14569/IJACSA.2023.0140242
Malm C, Jakobsson J, Isaksson A (2019) Physical Activity and Sports—Real Health Benefits: A Review with Insight into the Public Health of Sweden. Sports 7:127. https://doi.org/10.3390/sports7050127
McDonough DJ, Pope ZC, Zeng N, Liu W, Gao Z (2020) Comparison of College Students’ Blood Pressure, Perceived Exertion, and Psychosocial Outcomes During Virtual Reality, Exergaming, and Traditional Exercise: An Exploratory Study. Games for Health Journal 9:290–296. https://doi.org/10.1089/g4h.2019.0196
McMahon DD, Barrio B, McMahon AK, Tutt K, Firestone J (2020) Virtual Reality Exercise Games for High School Students With Intellectual and Developmental Disabilities. J Spec Educ Technol 35:87–96. https://doi.org/10.1177/0162643419836416
McMichael L, Farič N, Newby K, Potts HWW, Hon A, Smith L, Steptoe A, Fisher A (2020) Parents of Adolescents Perspectives of Physical Activity, Gaming and Virtual Reality: Qualitative Study. JMIR Serious Games 8:e14920. https://doi.org/10.2196/14920
Metamandrill (2023) Virtual Reality in the Gaming Industry; Biggest Players & Use Case Examples. https://metamandrill.com/virtual-reality-in-the-gaming-industry. Accessed 4 Apr 2024
Michalski SC, Szpak A, Saredakis D, Ross TJ, Billinghurst M, Loetscher T (2019) Getting your game on: Using virtual reality to improve real table tennis skills. PLoS ONE 14:e0222351. https://doi.org/10.1371/journal.pone.0222351
Milgram P, Takemura H, Utsumi A, Kishino F (1995) Augmented reality: a class of displays on the reality-virtuality continuum. In: Das H (ed). Boston, MA, pp 282–292
Mologne MS, Hu J, Carrillo E, Gomez D, Yamamoto T, Lu S, Browne JD, Dolezal BA (2022) The Efficacy of an Immersive Virtual Reality Exergame Incorporating an Adaptive Cable Resistance System on Fitness and Cardiometabolic Measures: A 12-Week Randomized Controlled Trial. IJERPH 20:210. https://doi.org/10.3390/ijerph20010210
Motejlek J, Alpay E (2021) Taxonomy of Virtual and Augmented Reality Applications in Education. IEEE Trans Learning Technol 14:415–429. https://doi.org/10.1109/TLT.2021.3092964
Naito A, Go K, Shima H, Kijima A (2022) Synchrony in triadic jumping performance under the constraints of virtual reality. Sci Rep 12:12417. https://doi.org/10.1038/s41598-022-16703-4
Nasu D, Baba T, Imamura T, Yamaguchi M, Kitanishi Y, Kashino M (2022) Simplified Virtual Reality System Can Be Used to Evaluate the Temporal Discrimination Ability in Softball Batting as in the Real Environment. Front Sports Act Living 4:843896. https://doi.org/10.3389/fspor.2022.843896
Nekar DM, Lee D-Y, Hong J-H, Kim J-S, Kim S-G, Nam Y-G, Yu J-H (2023) Effects of Pseudo-Weight Resistance Training Using Mixed-Reality Technology on Muscle Activation in Healthy Adults: A Preliminary Study. Applied Sciences 13:10021. https://doi.org/10.3390/app131810021
Nickerson RC, Varshney U, Muntermann J (2013) A method for taxonomy development and its application in information systems. European Journal of Information Systems 22:336–359. https://doi.org/10.1057/ejis.2012.26
Oagaz H, Schoun B, Choi M-H (2022a) Performance Improvement and Skill Transfer in Table Tennis Through Training in Virtual Reality. IEEE Trans Visual Comput Graphics 28:4332–4343. https://doi.org/10.1109/TVCG.2021.3086403
Oagaz H, Schoun B, Choi M-H (2022b) Real-time posture feedback for effective motor learning in table tennis in virtual reality. International Journal of Human-Computer Studies 158:102731. https://doi.org/10.1016/j.ijhcs.2021.102731
Ou Y-K, Wang Y-L, Chang H-C, Yen S-Y, Zheng Y-H, Lee B-O (2020) Development of virtual reality rehabilitation games for children with attention-deficit hyperactivity disorder. J Ambient Intell Human Comput 11:5713–5720. https://doi.org/10.1007/s12652-020-01945-9
Page MJ, McKenzie JE, Bossuyt PM, Boutron I, Hoffmann TC, Mulrow CD, Shamseer L, Tetzlaff JM, Akl EA, Brennan SE, Chou R, Glanville J, Grimshaw JM, Hróbjartsson A, Lalu MM, Li T, Loder EW, Mayo-Wilson E, McDonald S, McGuinness LA, Stewart LA, Thomas J, Tricco AC, Welch VA, Whiting P, Moher D (2021) The PRISMA 2020 statement: an updated guideline for reporting systematic reviews. BMJ n71. https://doi.org/10.1136/bmj.n71
Panchuk D, Klusemann MJ, Hadlow SM (2018) Exploring the Effectiveness of Immersive Video for Training Decision-Making Capability in Elite, Youth Basketball Players. Front Psychol 9:2315. https://doi.org/10.3389/fpsyg.2018.02315
Papaioannou A (1997) Perceptions of Motivational Climate, Perceived Competence, and Motivation of Students of Varying Age and Sport Experience. Percept Mot Skills 85:419–430. https://doi.org/10.2466/pms.1997.85.2.419
Park SJ, Lee JW (2023) Effects of Virtual Reality Pilates Training on Duration of Posture Maintenance and Flow in Young, Healthy Individuals: Randomized Crossover Trial. JMIR Serious Games 11:e49080. https://doi.org/10.2196/49080
Pastel S, Petri K, Chen CH, Wiegand Cáceres AM, Stirnatis M, Nübel C, Schlotter L, Witte K (2023) Training in virtual reality enables learning of a complex sports movement. Virtual Reality 27:523–540. https://doi.org/10.1007/s10055-022-00679-7
Petri K, Emmermacher P, Danneberg M, Masik S, Eckardt F, Weichelt S, Bandow N, Witte K (2019) Training using virtual reality improves response behavior in karate kumite. Sports Eng 22:2. https://doi.org/10.1007/s12283-019-0299-0
Polechoński J, Szczechowicz B, Ryśnik J, Tomik R (2024) Recreational cycling provides greater satisfaction and flow in an immersive virtual environment than in real life. BMC Sports Sci Med Rehabil 16:31. https://doi.org/10.1186/s13102-024-00818-4
Polikanova I, Yakushina A, Leonov S, Kruchinina A, Chertopolokhov V, Liutsko L (2022) What Differences Exist in Professional Ice Hockey Performance Using Virtual Reality (VR) Technology between Professional Hockey Players and Freestyle Wrestlers? (a Pilot Study). Sports 10:116. https://doi.org/10.3390/sports10080116
Pu Y, Yang Y (2022) Application of Virtual Reality Technology in Martial Arts Situational Teaching. Mobile Information Systems 2022:1–13. https://doi.org/10.1155/2022/6497310
Reer F, Wehden L-O, Janzik R, Tang WY, Quandt T (2022) Virtual reality technology and game enjoyment: The contributions of natural mapping and need satisfaction. Computers in Human Behavior 132:107242. https://doi.org/10.1016/j.chb.2022.107242
Richlan F, Weiß M, Kastner P, Braid J (2023) Virtual training, real effects: a narrative review on sports performance enhancement through interventions in virtual reality. Front Psychol 14:1240790. https://doi.org/10.3389/fpsyg.2023.1240790
Rodrigues J, Coelho T, Menezes P, Restivo MT (2020) Immersive Environment for Occupational Therapy: Pilot Study. Information 11:405. https://doi.org/10.3390/info11090405
Rojas Ferrer CD, Shishido H, Kitahara I, Kameda Y (2020) Read-the-game: System for skill-based visual exploratory activity assessment with a full body virtual reality soccer simulation. PLoS ONE 15:e0230042. https://doi.org/10.1371/journal.pone.0230042
Rojo A, Castrillo A, López C, Perea L, Alnajjar F, Moreno JC, Raya R (2023) PedaleoVR: Usability study of a virtual reality application for cycling exercise in patients with lower limb disorders and elderly people. PLoS ONE 18:e0280743. https://doi.org/10.1371/journal.pone.0280743
Rutkowski S, Bogacz K, Czech O, Rutkowska A, Szczegielniak J (2022) Effectiveness of an Inpatient Virtual Reality-Based Pulmonary Rehabilitation Program among COVID-19 Patients on Symptoms of Anxiety, Depression and Quality of Life: Preliminary Results from a Randomized Controlled Trial. IJERPH 19:16980. https://doi.org/10.3390/ijerph192416980
Ryan RM, Deci EL (2000) Self-determination theory and the facilitation of intrinsic motivation, social development, and well-being. American Psychologist 55:68–78. https://doi.org/10.1037/0003-066X.55.1.68
Saiz-Gonzalez P, J. McDonough D, Liu W, Gao Z (2023) Acute Effects of Virtual Reality Exercise on Young Adults’ Blood Pressure and Feelings. International Journal of Mental Health Promotion 25:711–719. https://doi.org/10.32604/ijmhp.2023.027530
Scavarelli A, Arya A, Teather RJ (2021) Virtual reality and augmented reality in social learning spaces: a literature review. Virtual Reality 25:257–277. https://doi.org/10.1007/s10055-020-00444-8
Statista (2023) Für welche Inhalte haben Sie Virtual Reality bereits genutzt? https://de.statista.com/statistik/daten/studie/1247695/umfrage/umfrage-zu-beliebten-einsatzszenarien-fuer-virtual-reality-in-deutschland. Accessed 4 Oct 2024
Stavrou VT, Vavougios GD, Kalogiannis P, Tachoulas K, Touloudi E, Astara K, Mysiris DS, Tsirimona G, Papayianni E, Boutlas S, Hassandra M, Daniil Z, Theodorakis Y, Gourgoulianis KI (2023) Breathlessness and exercise with virtual reality system in long-post-coronavirus disease 2019 patients. Front Public Health 11:1115393. https://doi.org/10.3389/fpubh.2023.1115393
Steam (2024) Steam Hardware & Software Survey. https://store.steampowered.com/hwsurvey/Steam-Hardware-Software-Survey-Welcome-to-Steam. Accessed 10 Jun 2024
Steuer J (1992) Defining Virtual Reality: Dimensions Determining Telepresence. Journal of Communication 42:73–93. https://doi.org/10.1111/j.1460-2466.1992.tb00812.x
Stodden DF, Goodway JD, Langendorfer SJ, Roberton MA, Rudisill ME, Garcia C, Garcia LE (2008) A Developmental Perspective on the Role of Motor Skill Competence in Physical Activity: An Emergent Relationship. Quest 60:290–306. https://doi.org/10.1080/00336297.2008.10483582
Sweller J, Ayres P, Kalyuga S (2011) Cognitive Load Theory. Springer New York, New York, NY
Touloudi E, Hassandra M, Galanis E, Goudas M, Theodorakis Y (2022) Applicability of an Immersive Virtual Reality Exercise Training System for Office Workers during Working Hours. Sports 10:104. https://doi.org/10.3390/sports10070104
Tsai W-L, Pan T-Y, Hu M-C (2022) Feasibility Study on Virtual Reality Based Basketball Tactic Training. IEEE Trans Visual Comput Graphics 28:2970–2982. https://doi.org/10.1109/TVCG.2020.3046326
Tu R, Hsieh P, Feng W (2019) Walking for fun or for “likes”? The impacts of different gamification orientations of fitness apps on consumers’ physical activities. Sport Management Review 22:682–693. https://doi.org/10.1016/j.smr.2018.10.005
Valkanidis TCh, Craig CM, Cummins A, Dessing JC (2020) A goalkeeper’s performance in stopping free kicks reduces when the defensive wall blocks their initial view of the ball. PLoS ONE 15:e0243287. https://doi.org/10.1371/journal.pone.0243287
Voigt-Antons J-N, Kojić T, Ali D, Möller S (2020) Influence of Hand Tracking as a way of Interaction in Virtual Reality on User Experience
Vu A, Sorel A, Limballe A, Bideau B, Kulpa R (2022) Multiple Players Tracking in Virtual Reality: Influence of Soccer Specific Trajectories and Relationship With Gaze Activity. Front Psychol 13:901438. https://doi.org/10.3389/fpsyg.2022.901438
Walsh KR, Pawlowski SD (2002) Virtual Reality: A Technology in Need of IS Research. CAIS 8. https://doi.org/10.17705/1CAIS.00820
Wang Y, Chen Q, Liu L, He Q, Cheung JC-W, Wong DW-C, Liu Y, Lam W-K (2023) Training effects of set- and repetition-interval rest time on recumbent-boxing exercise: Could virtual reality improve further? iScience 26:107399. https://doi.org/10.1016/j.isci.2023.107399
Wender CLA, Tomporowski PD, Ahn SJ (Grace), O’Connor PJ (2022) Virtual reality-based distraction on pain, performance, and anxiety during and after moderate-vigorous intensity cycling. Physiology & Behavior 250:113779. https://doi.org/10.1016/j.physbeh.2022.113779
Witmer BG, Singer MJ (1998) Measuring Presence in Virtual Environments: A Presence Questionnaire. Presence 7:225–240. https://doi.org/10.1162/105474698565686
Witte K, Droste M, Ritter Y, Emmermacher P, Masik S, Bürger D, Petri K (2022) Sports training in virtual reality to improve response behavior in karate kumite with transfer to real world. Front Virtual Real 3:903021. https://doi.org/10.3389/frvir.2022.903021
Wu E, Piekenbrock M, Nakumura T, Koike H (2021) SPinPong - Virtual Reality Table Tennis Skill Acquisition using Visual, Haptic and Temporal Cues. IEEE Trans Visual Comput Graphics 27:2566–2576. https://doi.org/10.1109/tvcg.2021.3067761
Wu Q, Han R, Li Z, Huang X, Cheng D, Ni J, Zhang S, Tan X, Kang P, Yu S, Chen A, Lu Y, Yao F, Jin Z, Qin Y, Guo J, Liu D, Zhang Y, Song Y, Zhu L, Lu Q, Chen Q, Lin C, Fang Q, Maimaitikasimu M, Wu J, Jia W, Sheng B, Wang J, Li H (2023) Effect of virtual reality-based exercise and physical exercise on adolescents with overweight and obesity: study protocol for a randomised controlled trial. BMJ Open 13:e075332. https://doi.org/10.1136/bmjopen-2023-075332
Xiao P-W, Fan K-K, Xu S, Su C-H (2017) A Preliminary Study on the Learning Satisfaction and Effectiveness of VR Weight Training Assisting Learning System for Beginners. EURASIA J MATH SCI T 13. https://doi.org/10.12973/eurasia.2017.01061a
Xu W, Liang H-N, He Q, Li X, Yu K, Chen Y (2020) Results and Guidelines From a Repeated-Measures Design Experiment Comparing Standing and Seated Full-Body Gesture-Based Immersive Virtual Reality Exergames: Within-Subjects Evaluation. JMIR Serious Games 8:e17972. https://doi.org/10.2196/17972
Yang H, Li J, Liu J, Bian Y, Liu J (2022) Development of an Indoor Exergame Based on Moving-Target Hitting Task for COVID-19 Epidemic: A Comparison Between AR and VR Mode. IEEE Trans Games 14:511–521. https://doi.org/10.1109/TG.2021.3118035
Yu K, Wen S, Xu W, Caon M, Baghaei N, Liang H-N (2023) Cheer for me: effect of non-player character audience feedback on older adult users of virtual reality exergames. Virtual Reality 27:1887–1903. https://doi.org/10.1007/s10055-023-00780-5
Zhang X, Hui L, Li M, Huang J, Chen C, Yang Y, Song F, Hu F, Luh D-B (2022) Design to Assist Better Youthhood for Adolescents with Lower-Limb Disability through Virtual Reality Sports. IJERPH 19:3985. https://doi.org/10.3390/ijerph19073985

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A Taxonomy of Virtual Reality Sports Applications

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Abstract

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1. Introduction

2. Methods and material

2.1 Systematic literature review process

2.2 Application review process

2.3 Taxonomy creation process

3. Systematic Literature Review

3.1 Sport categories

3.2 Hardware

3.3 Target group

3.4 Characters and avatars

3.5 Application design

4. Taxonomy

4.1 Taxonomy preparation

4.2 Iterations

4.3 Final taxonomy

5. Discussion

5.1 Comparison of theory and practice

5.2 Accordance of VR applications with learning theories

5.3 Future research avenues

5.4 Limitations

Conclusions

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References

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