Effective use of Imagery Assisted Virtual Reality in Pitch Recognition and Sport Imagery Ability Development
Authors: Lindsay Ross-Stewart1, Landon Braun2, & Victoria Hardcastle3
1Department of Applied Health, Southern Illinois University Edwardsville
2College of Health Professions and Sciences, University of Wisconsin Milwaukee
3Department of Intercollegiate Athletics, Savannah State University
Corresponding Author:
Dr. Lindsay Ross-Stewart
Campus Box 1126
Southern Illinois University Edwardsville
Edwardsville, IL, 62026
lrossst@siue.edu
(618) 650-2410
Lindsay Ross-Stewart, PhD is an Associate Professor in the Department of Applied Health at Southern Illinois University Edwardsville. Dr. Ross-Stewart is a CMPC® and a Canadian Sport Psychology Association Mental Performance Consultant (MPC).
Landon Braun, M.S., is a Doctoral Student at the University of Wisconsin-Milwaukee in the College of Health Professions & Sciences. At UWM Landon works as a Teaching Assistant in the School of Rehabilitation Sciences & Technology where he teaches courses related sport and performance psychology to both undergraduate and graduate students.
Victoria Hardcastle, M.S., is an Assistant Softball Coach at Savannah State University.
Effective use of Imagery Assisted Virtual Reality in Pitch Recognition and Sport Imagery Ability Development
ABSTRACT
Abstract: Imagery can be described as experience that mimics real world experiences through the combination of using different sensory modalities in the absence of actual perceptions (43). One uses visual, auditory, kinesthetic (touch), smell, and taste to create a picture simulating real world environments and scenarios. Imagery can be used to enhance various aspects of performance by mentally preparing someone for an upcoming competition or helping an athlete focus specifically on a task (19). Virtual reality, understood in this study as a first-person filmed, computer presented, immersive simulation of a real environment (32), has become increasingly more utilized in sport performance settings (7, 37, 44). Combing these two elements, the purpose of this study was to investigate an applied Imagery Assisted Virtual Reality (IAVR) intervention on imagery ability and pitch recognition in a sample of eleven National Collegiate Athletic Association (NCAA) Division One softball players at a Midwestern University. This study’s results indicated a significant increase in global imagery ability as well as in four of the five functions of imagery (CS, CG, MG-A, MG-A) and in pitch type recognition. Practically, the results from this study suggest that the IAVR intervention can create an impactful experience to assist athletes in improving their performance and psychological skills.
Keywords: Psychological Skills, Pitching Ability, Softball, Virtual Reality, Collegiate Sport
Virtual reality technology has become an increasingly common tool used in sport (e.g., 3 – 4, 7, 14, 17, 24, 26; 28, 31, 37, 44) with application in areas such as injury rehabilitation (31), and performance enhancement (2, 27, Wood et al., 2020). In fact, virtual reality has been labeled the next step forward for athletic training (47) and has been the subject of several states of the field (e.g., 7, 26).
Virtual reality was originally defined as a computer-generated, artificial, or simulated environment created by technological software (38). Within sport, it has been defined as instances when individuals are engaged in a sport that is represented in a computer-simulated environment which aims to induce a sense of being mentally or physically present and enables interactivity with the environment (28). One important aspect that virtual reality training is lacking is a focus on how virtual reality can assist in increasing an athlete’s psychological skill development (32). While virtual reality can impressively replicate environments and simulate real-world reactions; it still lacks the ability to capture an emotional response to the environment (32). As we know that how one feels and their perceptions of the sporting environment are necessary for performance, past research has shown this to be a challenge in traditional VR interventions (11) Research on the incorporation of imagery into a virtual reality training program has shown it to be a promising way to gain the advantages of VR and to overcome this potential challenge (32, 33; 34).
In the context of sport, White and Hardy (45) defined mental imagery as: an experience that mimics real experience. We can be aware of “seeing” an image, feeling movements as an image, or experiencing an image of smell, tastes, or sounds without actually experiencing the real thing (23). One approach to the application of imagery in sport is the revised applied model of imagery, which states that athletes may use it to achieve different outcomes (10). To achieve desired outcomes, imagery type, what athlete’s images and imagery function, the why or the purpose of an athlete’s image should be considered (29). Imagery type is split into two categories, cognitive and motivational, with each operating at specific and general levels (43). Cognitive refers to performance enhancement while motivational focuses on confidence enhancement (5). Imagery types and functions have been defined as: Cognitive specific (CS) helps an athlete to work on skill learning, development, and execution. Cognitive general (CG) affords the athlete the ability to image different strategies and routines. Motivational specific (MS) imagery focuses on enhancing motivation through goal setting and goal achievement. Motivational general arousal (MGA) imagery focuses on somatic and emotional experiences such as regulating stress and arousal. Motivational general mastery (MGM) imagery concentrates on coping, gaining, and maintaining self-confidence, and staying focused (10, 18) identify. Athletes might use each of the imagery types alone or in combination with one another, depending on the meaning an athlete applies to the image (29). For example, an athlete can use cognitive specific imagery (CS type) to image themselves executing a skill successfully (CS function), but this image may also increase their confidence, which would be for the function type MG-M (10).
Focusing on the way in which Imagery and Virtual Reality could be used together, Ross-Stewart and colleagues developed Imagery Assisted Virtual Reality (IAVR), a training protocol that involves an immersive virtual reality experience for users in which kinesthetic awareness is incorporated with users being able to see a first-person simulated scenario coupled with an individualized imagery script aimed at enhancing psychological skills and performance (32). IAVR entailed a first-person filmed batting environment from an on-deck position all the way up to batting and taking swings. This video was then followed by a blank screen with an individualized guided imagery script tailored to each individual player that was either audio recorded in the video itself or written down. In their initial study they found that participants who completed an IAVR intervention increased their skills imagery (CS), goal imagery (MS) and mastery imagery (MG-M) as measured by the Sport Imagery Ability Questionnaire (SIAQ; 43). Furthermore, results suggested an increase in overall imagery use, positive self-talk and automaticity in both practice and competition through the length of the study. Additionally, negative thinking during competition decreased, as measured by the Test of Performance Strategies (TOPS; 39). The finding that imagery and virtual reality used together can impact psychological constructs was supported by Frank et al (2022) who found self-efficacy to increase in a physical activity task using imagery and virtual reality. Furthering the support for IAVR, a recent study on the impact of VR on imagery ability and emotional affect found that VR can “induce emotional arousal and affect the mental imagery skills and positive affect of athletes” (46).
Baseball hall of famer Ted Williams referred to batting as “the hardest thing to do in sports” (35). If a softball pitcher throws a 60-mph fastball, it will reach Homeplate in .45 seconds. However, if she throws a changeup at 50 mph, it will reach Homeplate in .55 seconds. Batters have a brief window of opportunity in which they must recognize the pitch and decide to swing or not swing (20). Pitch recognition is the batter’s ability to recognize which way the seams on the ball are spinning/rotating and the trajectory of the ball (20). These two components can be categorized by pitch type (fastball, change-up, drop ball, rise ball) and prediction of eventual location of the pitch (strike, ball, inside, outside) (13). Being able to recognize pitches is an essential aspect of batting. However, there exists little agreement on what the skill of pitch recognition consists of and how to improve it (13).
Each pitch is comprised of different combinations of velocity, rotation, and trajectory cues. Outside of rotation and trajectory cues, there are other sources of information a batter might be receiving information from without being aware of it. These cues include knowledge of the pitcher, game situation, and batter’s count (20). A batter’s ability to recognize which pitch is being thrown will allow them to conduct their swing accordingly and increase performance. This recognition will allow a batter to make more solid hits and recognize the difference between a ball and strike. This recognition will also allow them to either look for pitches they want to hit or draw more walks. Therefore, pitch recognition is a pivotal skill for softball players to obtain if they want to achieve top performance.
The use of VR has been shown to be an effective tool for the increase of strike zone and pitch recognition (16). Virtual reality training has also been shown to lead to a greater sensitivity to visual information provided by the ball trajectory, seam rotation, and improved ability to use monocular cues to determine whether a pitch would cross the plate in the strike zone or not (16). Furthermore, Ranganathan and Carlton (30) found that VR was effective when baseball players had visual information of an entire pitch in their VR environment and ball trajectory yielded a higher prediction accuracy.
Based on both past research in VR and IAVR, merging imagery and virtual reality may enhance the psychological skill and strategy development of athletes more than if they are used alone. Taken with recent suggestions for more research on the effectiveness of VR on both skill acquisition and psychological change in sport (e.g., 7 17, 26, 28 31, 41), specifically, Cotterill’s assertion that “there is also a need for more applied case studies that outline the procedures adopted and reflect on the outcomes obtained using VR in sport psychology–relevant ways”(7, p.22). The purpose of this paper is to highlight an applied Imagery Assisted Virtual Reality intervention that was used with a National Collegiate Athletic Association (NCAA) Division I softball team. Specifically, hitters were given the opportunity to participate in an intervention that designed individualized imagery assisted virtual reality video for them and then they were assessed to see how it impacted their imagery ability, and pitch recognition. Based on past research, it was hypothesized that both global imagery ability and pitch recognition would increase from baseline to post intervention. Furthermore, based on past research on IAVR (32) it was hypothesized that CS, CG, and MG-M imagery would significantly increase from baseline to post intervention. No hypothesis was made related to MS and MG-A imagery due to lack of past research, at the time of data collection, supporting the use of this imagery increasing using IAVR.
Materials and Methods
Methods
Participants
Participants were 11 NCAA Division One female softball players at a Midwestern University. Of the 11 participants five were right-handed batters and six were left-handed batters. Their ages ranged from 18-24 years old.
Measures
Sport Imagery Ability Questionnaire (43; SIAQ): The SIAQ was designed to measure an athlete’s ability to image different content (i.e., strategies, skills, feelings, and goals) and the frequency that an athlete images. The questionnaire has 15 questions rated from 1 (very hard to image) to 7 (very easy to image). The questions are divided into five different subscales; skill imagery ability (e.g., defining a specific skill), strategy imagery ability (e.g., making/executing strategies), goal imagery ability (e.g., winning the game), affect imagery ability (e.g., positive emotions connected with the sport), and mastery imagery ability (e.g., positive outlook when things are not going well). An overall sport imagery ability score and all subscales were calculated separately. To score each of the five subscales, questions for the subscale were summed and divided by the number of questions for each source. The SIAQ has been found to have good validity and reliability (43)
Pitch recognition test: A Pitch Recognition test was designed for this study to assess a participant’s ability to recognize a pitch type (fastball. change-up, etc.) and pitch location (strike/ball). Participants viewed twelve pitches via GoPro film from a pitcher. The film the participants viewed was from the same film they viewed in their IAVR. There were five seconds between each pitch allowing for the participants to circle both the pitch type and pitch location of the previously viewed pitch. The pitch recognition test had twelve different pitches for the baseline testing and the post intervention testing. The number of pitches they correctly identified for both type and location divided by twelve was their total pitch recognition scores. Both pitch type and pitch location were scored as subscale.
Procedure
Institution IRB was obtained. Players were recruited from an NCAA (National Collegiate Athletic Association) Division I softball team. Eleven players signed up to participate in the intervention. Participants who gave consent were assigned a time to film their first-person VR film. Filming was done both on the players’ field and in their indoor hitting facility to make sure it properly mimicked where they were currently practicing. During filming, participants wore dual mounted GoPro headsets on top of their batting helmets to gain first person filming perspectives. Participants were instructed to go through their whole routine starting with preparation for the on-deck circle by stepping into the batter’s box. Filming was also done to gain a third person perspective using a dual mounted GoPro headset strapped to a tripod and placed in the batter’s box. For this film day, three pitchers from the same team, who volunteered to help with the study were filmed pitching from the mound (one left-handed, two right-handed). All three of the pitchers threw their pitches (fastball, change-up, rise ball, etc.) for both right-handed batter and left-handed batter viewpoints. Ninety-six pitches were filmed to allow for a variety of options for the pitching videos.
After the filming was complete the research team used Shotcut to edit the film into two pitch recognition videos, and an individualized VR video for each participant. Videos of the pitches were made to assess pitch recognition at baseline and time 2. To make these videos, the third-person video was edited by clipping each pitcher’s pitch into its own. This allowed the researchers to integrate all three pitchers’ pitches into a specific order. Researchers then went through and selected twelve pitches out of the right-handed batter’s film and a separate twelve out of the left-handed batter’s film. These clips were arranged to simulate two full at bats, with a five second black screen between each pitch. This method was replicated to make the pitch recognition video that would be used for the post test.
To make the IAVR videos, first-person perspective film was edited to start when participants start their pre-at bat routine. The clip ended when the batter received a pitch from the pitcher while they were in the batter’s box. In these videos pitch clips were aligned to simulate a real world at bat, including timing between bats. To develop the guided imagery scripts that would be recorded as audio into the Virtual Reality videos, participants individually met with the research team to discuss their experiences at bat. The imagery scripts were written according to the guidelines suggested by (42) making sure to incorporate both stimulus and response propositions (8, 22) to the imagery scripts. The imagery scripts were broken down and recorded into two audio files. The first recording consisted of each participant’s rituals and routines starting when they are “in the hole” all the way to being in the batter’s box. This included getting equipment on (batting gloves, elbow guard, etc.), walking to the on-deck circle, on deck circle rituals, walking to the batter’s box, and pre at bat rituals. Some participants opted to have their walk-up song playing in the background during their imagery script when walking from the on-deck circle to the batter’s box.
The second recording started when each participant was in the batter’s box. Depending on how the participant wanted their imagery script written, they might receive a ball or strike first. Then, hitting to a designated spot of their choosing. Participants then had a choice of running through first, running to second, or sliding into second. The scenarios and cues they picked up from the first base coach were all individualized to each participant. These individual imagery scripts were turned into audio files and then embedded into the participants corresponding virtual reality film to make the Imagery Assisted Virtual Reality interventions for each participant. The IAVR was set up as the following: imagery script of preparation for an at bat, 3rd person pitch film, first person film from the dugout to the batter’s box, and then imagery script of hitting the ball and making it to a base safe.
Before being given their IAVR film, participants watched the baseline pitch recognition video and marked the pitch type and location of each video. Each player was provided with a pair of virtual reality goggles and a locked cell phone loaded with their individualized video. Instructions were also provided to participants on how to download the videos onto their personal phone if they preferred to have it on their own phone. Participants were instructed to watch their IAVR video at least once a day using virtual reality goggles. Participants were also informed that if they requested any changes to their IAVR (i.e., imagery speed, tone, pitch order) the research team would make the changes at any time during the intervention.
After participants had the IAVR video for six weeks they completed a post intervention pitch recognition test where they watched the second pitching video that had been made and once again recorded what type and location, they believed they saw for each pitch. They also completed the SIAQ at this time.
Results
Review of the data indicated that two participants had missed one question each. The means for each question were used as a replacement so the participants data could still be used in the analysis, as deemed appropriate in inferential statistics (21). Next descriptive statistics for baseline and post intervention were calculated for each of the five imagery ability subscales and global imagery ability score, as well as total pitch recognition, pitch type and pitch location. Paired samples t-tests were run to assess mean changes from baseline to post intervention for all imagery ability subscales and total imagery score as well as for the three pitch assessments. As the data were expected to increase from baseline to post intervention across all variables a one tailed test was employed with an alpha level of 0.05. Cohens d were calculated for all pairs with 0.21 – 0.59 considered a small effect .60 – .79 a medium effect and 0.80 to 100 a large effect (6).
Imagery
Participants’ global imagery ability was higher at post-testing (m = 5.69, sd = 0.79) as opposed to baseline (m = 5.02, sd = 0.69), which was found to be a statistically significant difference, t(10) = -2.70, p = .01, d = 0.91). Skill imagery ability change from baseline to post intervention was also significant (t(10) = -2.51, p = 0.02, d = 0.73), indicating that the participants increased their skill imagery ability from baseline (m = 4.79, sd = 1.12) to post intervention (m = 5.63, sd = 1.20). Strategy imagery ability was found to have a statistically significant change (t(10) = -2.05, p = .03, d = 0.63). Means indicated an increase from 4.73 (sd =0.94) at baseline to 5.30 (sd =0.88) at post intervention. The affect imagery ability increase was statistically significant (t(10) = -2.07 p = 0.03, d = 0.81). Means indicated a change from 5.55 (sd = 0.83) at baseline to 6.22 at post intervention (sd = 0.79). Mastery imagery ability from baseline (m = 4.88, sd = 0.86) to post test (m = 5.60, sd = 0.79) was also statistically significant (t(10) = -2.05, p = 0.02, d = 0.88). Goal imagery did not have a statistically significant change from baseline (m = 5.15, sd = 1.02) to post intervention (m = 5.70, sd = 1.03, (p = 0.07, d = 0.53).
Pitch Statistics
Pitch type recognition was found to be statistically significant from baseline (m = 6.60, sd = 3.13) to post intervention (m = 9.10, sd = 2.08), t(10) = -2.28, p = .04) with a large effect size (d = 0.94). Pitch location recognition and total pitch recognition both increased, however neither were statistically significant changes (p >0.05). Percentage change was also recorded for pitch type as that is the common way to assess these statistics in applied softball scenarios. See Table 1 for full statistics for Pitch.
Table 1. Average Number and percentage of pitches accurately identified at baseline and Post Intervention
# Correct Baseline | # Correct Post Intervention | # Correct Pitch Type Baseline | # Correct Pitch Type Post Intervention | # Correct Pitch Location Baseline | # Correct Pitch Location Post Intervention | ||||||
# | % | # | % | # | % | # | % | # | % | # | % |
4.1 | 34.17 | 5.9 | 49.17 | 6.6 | 55 | 9.1 | 75.83 | 7 | 58.33 | 7.2 | 60 |
Discussion
This study investigated the effect of an applied Imagery Assisted Virtual Reality intervention on NCAA Division I softball players’ imagery ability and pitch recognition. This study hypothesized an increase in global imagery ability, pitch recognition as well as increases in skill (CS), strategy (CG), and Confidence (MG-M) imagery. Overall, the hypotheses were supported by the findings of this study.
This study’s results indicated a significant increase in the participants’ global imagery ability with this change indicating a large effect size. Furthermore, of the five imagery subscales all showed increases from baseline to post intervention, with Skill, Strategy, Mastery and Affect imagery ability increasing from baseline to post intervention. The increase in global imagery ability and subscale increases equates to the athlete’s ability to image being easier in real sport situations (49). This is of applied significance as this increase in global imagery could assist athletes in mental preparation before engaging in sport specific performance endeavors. It is also of importance as we have few studies demonstrating how to increase imagery ability even though we know the ability to image is important for athletes who want to use imagery to increase their sport performance. As imagery has been shown over and over again to increase sport performance (e.g., 9), knowing how to increase imagery ability is an important step in pursuit of maximizing the benefits of this psychological strategy.
This study demonstrates how virtual reality can assist a person’s imagery ability when showing real world video in correlation to their imagery script. We can postulate that global imagery ability increased in part due to the IAVR increasing the functional equivalency of the intervention (32). These results align with research on functional equivalence (22 and the PETTLEP model of imagery which states that all senses need to be engaged to be fully immersed in an imagery script (e.g., 1, 19; 36, 40).
The results indicated significant increases in confidence (MG-M) and affect (MG-A) imagery ability which equates to an athlete’s ability to image and be in control and cope during difficult sporting situations, and image positive content withing their sport (43). It may be that these motivational imagery subscales had a significant increase due to cue words (e.g., calm, focus, confidently) that were inserted into each participants imagery script to stimulate an emotional response. These cue words, chosen by each participant, were combined with repeated phrases such as “take a deep breath,” “feel yourself,” and “you are confident” were also used to stimulate an emotional response from participants. Some participants also opted to have their walk-up song play during their imagery assisted virtual reality. This auditory connection between virtual reality film and real-world stimulus may have allowed participants to emotionally connect to the IAVR and use it to regulate arousal. It should be noted that although it was not hypothesized that affect imagery (MG-A) would increase due to lack of research at the time of study, this finding is supported by recent research that has come out since data was collected for this study (46). The increase in MG-A imagery ability indicates that athletes experienced some type of realistic emotion within the imagery experience. This finding coincides with previous research (25, 27) that posits increases in affect imagery within virtual reality films may be attributed to social presence within these virtual reality films. Lee and colleagues (25) believed that responses to social presence within virtual environments may be due to the players’ expectations of interactions during an actual game. Within this study, social presence was maintained throughout virtual reality film by incorporating the presence of teammates in the videos. Finally, there were significant increases in skill (CS), and strategy (CG) imagery ability, which supported the hypothesis and is in line with past research (32). This makes sense as the IAVR gave the players extra opportunities to see themselves engaging in the skill of hitting and through imagery incorporated their individual strategies for how they were going to hit the ball.
Pitch Statistics
The hypothesis that pitch recognition would increase was partially supported. Pitch type recognition was found to be significantly increased from pre to post intervention. However, although pitch location recognition and total pitch recognition both increased, neither change was statistically significant. Percentage change was also recorded for pitch type as that is the common way to assess these statistics in applied softball scenarios and gave real world application information when it came to pitch recognition change. Of particular importance in this study was the finding that pitch type recognition increased by over 20% (from recognizing 6.6/12 – 9.1/12) from baseline to post intervention. Although not statistically significant the change in total pitch recognition increased by two pitches (4.1/12 to 5.9/12, 15%) which in an applied setting is a noteworthy performance increase. As the IAVR in this study was not filmed with 360-degree cameras it may be that this affected the batter’s sense of where the pitch was over the base, leading to a lack of pitch location increase. However, the IAVR focus on first person perspective of the pitch coming at them just as it would in a real game essentially gave them more reps “reading” the pitch where they did not have to think about anything else (what they were going to do), which may be part of why their pitch type recognition increased. These findings are important for those within the softball world as we know that recognizing a pitch can predict accuracy of an at bat (e.g., 30, 16). Although it is noted that pitch recognition is an essential aspect to batting, there is little agreement on how to improve it (13). This study’s results demonstrate the effectiveness of IAVR on increasing pitch type recognition and could therefore be a low-cost tool used by teams to increase the skill of pitch recognition, and therefore batting percentages.
While this study is an important addition to the new area of Imagery Assisted Virtual Reality, there are limitations to consider. The first limitation of this study was the sample size. Although the small sample size is acknowledged as a limitation it should be noted that even with this small sample size, the effect sizes in this study were medium to high indicating that with a larger sample these findings may be even more pronounced. As this was an applied study using players who were in season, it was considered unethical to make some of them a control group. Specifically, having some players given an advantage over others, an advantage that is not shown to disappear over time, would be unfair to those in the control group, impacting both individual athletes and the team as a whole. Therefore, not having a control group, although a deliberate decision, does lead to the lack of knowledge as to whether another unexpected variable may have impacted these results.
As IAVR is a new strategy for increasing imagery ability and sport performance, there are several areas future researchers should consider. Current research on IAVR has focused on the effect of IAVR on imagery ability it may be useful to focus on imagery use (facilitative and debilitative) as the ability to image is of importance only in that it effects imagery use effectiveness (12). Therefore, future research should focus specifically on the effect of IAVR on amount of deliberate imagery use both during and after they complete the IAVR protocol. To that point, future applied research on IAVR would benefit from tracking season performance post intervention, or by athletes who use IAVR throughout a season. Additionally, the impact of IAVR on pitch recognition during in game would be a worthy pursuit. At this time, we do not know what the optimal length of an IAVR protocol would be for athlete imagery, psychological skill, or athletic performance. All these areas are ripe for future research to investigate.
Conclusion
Overall, the results of this study further support the value of an Imagery Assisted Virtual Reality protocol being used in sport. Specifically, this study showed that IAVR can increase performance statistics (pitch recognition) and imagery ability.
Applications in Sport
These findings have practical significance as they lend support for IAVR to be used by softball players to further both their in-game skills and psychological skills development. Furthermore, these findings add to the existing literature that indicates IAVR may be a cost effective and impactful tool for athletes in various sports.
References
- Anuar, N., Cumming, J., & Williams, S. E. (2015). Effects of applying the PETTLEP model on vividness and ease of imaging movement. Journal of Applied Sport Psychology, 28(2), 185-198. doi:10.1080/10413200.2015.1099122
- Bedir, D., & Erhan, S. E. (2021). The effect of virtual reality technology on the imagery skills and performance of target-based sports athletes. Frontiers in Psychology, 11, 2073. doi.org/10.3389/fpsyg.2020.02073
- Bideau, B., Multon, F., Kulpa, R., Fradet, L., Arnaldi, B. & Delamarche, P. (2004). Using virtual reality to analyze links between handball thrower kinematics and goalkeeper’s reactions. Neuroscience Letters, 372(1-2), pp.119-122. https://doi.org/10.1016/j.neulet.2004.09.023
- Bird, J. M. (2020). The use of virtual reality head-mounted displays within applied sport psychology. Journal of Sport Psychology in Action, 11(2), 115-128. https://doi.org/10.1080/21520704.2018.1563573
- Callow, N., & Hardy, L. (2001). Types of imagery associated with sport confidence in netball players of varying skill levels. Journal of Applied Sport Psychology, 13(1), 1-17. doi:10.1080/104132001753155921
- Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ:
- Cotterill, S. (2018). Virtual reality and sport performance: Implications for applied practice. Case Studies in Sport and Exercise Psychology, 2, 21-22. doi:10.1123/cssep.2018-0002
- Cumming, J., Cooley, S. J., Anuar, N., Kosteli, M.-C., Quinton, M. L., Weibull, F., & Williams, S. E. (2016). Developing imagery ability effectively: A guide to layered stimulus response training. Journal of Sport Psychology in Action, 8(1), 23–33. doi: 10.1080/21520704.2016.1205698
- Cumming, J., & Ramsey, R. (2008). Imagery interventions in sport. In Advances in applied sport psychology (pp. 15-46). Routledge. doi: 10.13140/2.1.2619.2322.
- Cumming, J., & Williams, S. E. (2013). Introducing the revised applied model of deliberate imagery use for sport, dance, exercise, and rehabilitation. Movement & Sport Sciences-Science & Motricité, (82), 69-81. https://doi.org/10.1051/sm/2013098
- Cuperus, A. & Van der Ham, I. (2016). Virtual reality replays of sports performance: Effects on memory, feeling of competence, and performance. Learning and Motivation, 56, pp.48-52. https://doi.org/10.1016/j.lmot.2016.09.005
- Di Corrado, D., Guarnera, M., Vitali, F., Quartiroli, A., & Coco, M. (2019). Imagery ability of elite level athletes from individual vs. team and contact vs. no-contact sports. Brain, Cognition, and Mental Health, 7, e6940. doi: https://doi.org/10.7717/peerj.6940
- Fadde, P. J. (2006). Interactive video training of perceptual decision-making in the sport of baseball. Retrieved from http://peterfadde.com/Research/Baseball.pdf
- Fink, P., Foo, P., & Warren, W. (2009). Catching fly balls in virtual reality: A critical test of the outfielder problem. Journal of Vision, 9(13), pp.14-14. doi: https://doi.org/10.1167/9.13.14
- Frank, C., Hülsmann, F., Waltemate, T., Wright, D. J., Eaves, D. L., Bruton, A., Botsch, M., & Schack, T. (2022). Motor imagery during action observation in virtual reality: the impact of watching myself performing at a level I have not yet achieved. International Journal of Sport and Exercise Psychology, 1-27. https://doi.org/10.1080/1612197x.2022.2057570
- Gray, R. (2017). Transfer of training from virtual to real baseball batting. Frontiers in Psychology, 2183. https://doi.org/10.3389/fpsyg.2017.02183
- Harrison, K., Potts, E., King, A. C., & Braun-Trocchio, R. (2021). The effectiveness of virtual reality on anxiety and performance in female soccer players. Sports, 9(12), 167. https://doi.org/10.3390/sports9120167
- Hall, C. R., Mack, D. E., Paivio, A., & Hausenblas, H. A. (1998). Imagery use by athletes: Development of the Sport Imagery Questionnaire. International Journal of Sport Psychology, 29(1), 73–89.
- Holmes, P. S. & Collins, D. J. (2001). The PETTLEP approach to motor imagery: A functional equivalence model for sport psychologists. Journal of Applied Sport Psychology, 13(1), 60-83. doi:10.1080/104132001753155958
- Hyllegard, R. (1991). The role of the baseball seam pattern in pitch recognition. Journal of Sport and Exercise Psychology, 13(1), pp.80-84. https://doi.org/10.1123/jsep.13.1.80
- Huck, S. W. (2014). Reading statistics and research (7th ed.). Pearson Education Limited.
- Lawrence Erlbaum Associates. https://doi.org/10.2307/2290095
- Jeannerod, M. (1981) Intersegmental coordination during reaching at natural visual objects. Attention and performance IX, ed. Long, J. & Baddeley, A., & Erlbaum.
- Jones, L., & Stuth, G. (1997). The uses of mental imagery in athletics: An overview. Applied and Preventive Psychology, 6(2), 101–115. doi: 10.1016/s0962-1849(05)80016-2
- Kehoe, R. & Rice, M. (2016). Reality, virtual reality, and imagery: Quality of movement in novice dart players. British Journal of Occupational Therapy, 79(4), pp.244-251. https://doi.org/10.1177/0308022615616820
- Lee, H., Chung, S., & Lee, W. (2012). Presence in virtual golf simulators: The effects of presence on perceived enjoyment, perceived value, and behavioral intention. New Media & Society, 15(6), pp.930-946. https://doi.org/10.1177/1461444812464033
- Malachi, E.G., Tunggara, R., Cahyadi, Y., Meiliana, Fajar. M. (2023). A systematic literature review of virtual reality implementation in sports. International Conference on Artificial Intelligence in Information and Communication (ICAIIC) Conference Program. doi 10.1109/ICAIIC57133.2023.10067095
- Murray, E., Neumann, D., Moffitt, R. and Thomas, P. (2016). The effects of the presence of others during a rowing exercise in a virtual reality environment. Psychology of Sport and Exercise, 22, pp.328-336.
- Neumann, D. L., Moffitt, R. L., Thomas, P. R., Loveday, K., Watling, D. P., Lombard, C. L., Antonova, S., & Tremeer, M. A. (2018). A systematic review of the application of interactive virtual reality to sport. Virtual Reality, 22(3), 183-198.
- Nordin, S. M., & Cumming, J. (2008). Types and functions of athletes’ imagery: Testing predictions from the applied model of imagery use by examining effectiveness. International Journal of Sport and Exercise Psychology, 6(2), 189-206. doi:10.1080/1612197x.2008.9671861
- Ranganathan, R. & Carlton, L. (2007). Perception-action coupling and anticipatory performance in baseball batting. Journal of Motor Behavior, 39(5), pp.369-380.doi: 10.3200/JMBR.39.5.369-380.
- Richlan, F., M Weiß, M., Kastner, P., & Braid, J. (2022). Virtual training, real effects: A systematic literature review on sports performance enhancement through interventions in virtual reality. PsyArXiv. psyarxiv.com. doi.org/10.31234/osf.io/ckgm2
- Ross-Stewart, L., Price, J., Jackson, D., & Hawkins, C. (2018). A preliminary investigation into the use of an imagery assisted virtual reality intervention in sport. Journal of Sports Science, 6(1).
- Ross-Stewart, L & Lee, R. (2023). VR training and imagery training in esports. Journal of Imagery Research in Sport and Physical Activity, 18. doi.org/10.1515/jirspa-2023-0003
- Sai Raam, S. V., Santhosh Gopi, S., Santhosh, K., Aravind Subramanian, N., & Babiyon Clement, A. (2022). A preliminary investigation on sports-based VR technology with the influence of psychological skill training. International Journal of Creative Research Thought, 10, 7.
- Sherwin, J., Muraskin, J., & Sajda, P. (2012). You can’t think and hit at the same time: Neural correlates of baseball pitch classification. Frontiers in Neuroscience, 6. doi: 10.3389/fins.2012.00177
- Smith, D., Wright, C., Allsopp, A., & Westhead, H. (2007). It’s all in the mind: PETTLEP-based imagery and sports performance. Journal of Applied Sport Psychology, 19(1), 80-92. doi:10.1080/10413200600944132
- Sohail, Z., Firdos, A., Ikram, S., & Talha, M. (2022). The impact of virtual reality and augmented reality on sport psychology. Revista de Psicología del Deporte (Journal of Sport Psychology), 31(1), 217-226. Retrieved from https://www.rpd-online.com/index.php/rpd/article/view/667
- Steuer, J. (1992). Defining virtual reality: Dimensions determining telepresence. Journal of Communication, 42(4), 73-93. doi:10.1111/j.1460-2466.1992.tb00812.x
- Thomas, P.R. Murphy, S.M., & Hardy, L. (1999) Test of performance strategies: Development and preliminary validation of a comprehensive measure of athletes’ psychological skills, Journal of Sports Sciences, 17, 697 -711. doi: 10.1080/026404199365560
- Wakefield, C., & Smith, D. (2012). Perfecting practice: Applying the PETTLEP model of motor imagery. Journal of Sport Psychology in Action, 3(1), 1-11. doi:10.1080/21520704.2011.639853
- Wang, J. (2012). Research on application of virtual reality technology in competitive sports. Procedia Engineering, 29, pp.3659-3662.
- Williams, S. E., Cooley, S. J., Newell, E., Weibull, F., & Cumming, J. (2013). Seeing the difference: Developing effective imagery scripts for athletes. Journal of Sport Psychology in Action, 4(2), 109–121. doi: 10.1080/21520704.2013.781560
- Williams, S. E., & Cumming, J. (2014). Sport imagery ability questionnaire. ResearchGate. doi:10.13140/RG.2.1.1608.6565
- Wood, G., Wright, D. J., Harris, D., Pal, A., Franklin, Z. C., & Vine, S. J. (2021). Testing the construct validity of a soccer-specific virtual reality simulator using novice, academy, and professional soccer players. Virtual Reality, 25(1), 43-51. doi.org/10.1007/s10055-020-00441
- White, A. & Hardy, L. (1998). An in-depth analysis of the uses of imagery by high-level slalom canoeists and artistic gymnasts. The Sport Psychologist, 12(4), 387–403. doi.org/10.1123/tsp.12.4.387
- Wu Y, Lukosch S, Lukosch H, Lindeman RW, McKee RD, Fukuden S, Ross C and Collins D (2023), Training mental imagery skills of elite athletes in virtual reality. Frontiers in Virtual Reality, 1189717. doi: 10.3389/frvir.2023.1189717
- Zorowitz, J. (2018, December 4). It Just Got Real. Retrieved from https://www.nbcsports.com/newsletters