Perceptual-Motor Abilities of Professional Esports Gamers and Amateurs

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Haneol Kim Department of Kinesiology and Health, Georgia State University, Atlanta, GA, USA

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Seonjin Kim Department of Physical Education, Seoul National University, Seoul, Republic of Korea

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Jianhua Wu Department of Kinesiology and Health, Georgia State University, Atlanta, GA, USA

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Esports demands exceptionally fine motor skills. Perceptual-motor abilities such as anticipation, eye–hand coordination, and peripheral perception are essential for esports gamers to achieve high-level performance and win the game. However, the understanding of perceptual-motor ability in professional esports gamers is still limited. The aim of this study was to compare the perceptual-motor skills between professional esports gamers and amateurs. Eight male professional gamers and eight amateurs participated in this study voluntarily and completed three tasks: anticipation timing, eye–hand coordination, and peripheral perception. Results showed that the professional gamers had an earlier and more consistent anticipation timing in the anticipation-timing task than amateurs across four stimulus speeds. The professional gamers displayed a wider visual perception angle than the amateurs in the peripheral perception task. Our results demonstrate that long-time esports training advanced the development of anticipation timing and peripheral perception but might not affect the ability of eye–hand coordination.

Esports, also known as competitive video gaming, is a form of sports with real-life characteristics and has been a popular entertainment form among teenagers and young adults (Lee & Schoenstedt, 2011). Wack and Tantleff-Dunn (2009) reported that college-aged American men play electronic games for almost 10 hr a week, and 8.5% of them play as long as 35 hr per week. The local area networks connecting people around the world played an essential role in esports prevalence and accessibility (Lee & Schoenstedt, 2011). Esports can be connected over a network, not only from person to computer but also from person to person across different countries (Griffiths et al., 2003; Railsback & Caporusso, 2019). Based on its popularity, esports drew many researchers’ attention to the aspects of the fundamental perceptual-motor abilities in esports, which are essential for successful esports play but have not been studied systematically.

Esports is defined as a game facilitated by electronic systems with easily controllable human–computer interfaces such as a keyboard and a mouse (Hamari & Sjöblom, 2017; Pluss et al., 2019). Esports gamers must anticipate a stimulus from an opponent and react to it as quickly and accurately as possible by manipulating the human–computer interface. Advanced perceptual-motor abilities are necessary to succeed in esports, because successfully controlling a keyboard and a mouse is one of the critical factors in winning (Pluss et al., 2020). Playing computer games demands higher perceptual, attentional, cognitive, and fine motor skills (McDermott et al., 2014). For example, visual information displayed on a monitor and auditory information through headphones can be the stimuli in games. When these stimuli are exhibited, one needs to control their body movement by appropriately integrating and interpreting sensory input such as visual, auditory, and tactile information. Professional players in many sports often unleash their maximum capacity of perception to execute an efficient motor plan. They often show superior performance characterized by consistency, efficiency, stability, adaptability, and coordination. In fact, esports gamers make rapid decisions based on sensory input from a very competitive environment to execute an action (Pluss et al., 2019). However, it is not known to what extent professional esports gamers display better perceptual-motor skills than amateurs.

Among many perceptual-motor skills, anticipation timing, eye–hand coordination, and peripheral perception (field of vision) are critical for esports gamers. As more accurate and faster movements are required to play esports games, professional players often spend a significant amount of time training and competing for better performance. Previous research reported that perceptual-motor skills could be improved by experience and practice (Willingham, 1999). Ericsson and his colleague (Ericsson, 2008; Ericsson & Charness, 1994; Ericsson et al., 1993) defined a 10-year rule or 10,000 hr of deliberate practice to acquire expertise. Deliberate practice improves the skills and extends the range of skills. A recent study by Kim and Thomas (2015) reported that professional esports gamers practice at least 10 hr a day, consisting of game plans, strategy, and individual performances. In addition to cognitive skill training, physical requirements should not be underestimated either (Railsback & Caporusso, 2019). Some literature has revealed that practice improves anticipation timing accuracy in racket sports (Benguigui & Ripoll, 1998; Haywood, 1983; Wrisberg & Barbara, 1983). The visual field in various sports such as badminton (Poliszczuk & Mosakowska, 2009), handball (Zwierko et al., 2008), volleyball, and basketball was examined, but no study has investigated the visual field of esports gamers at a professional level. Griffith et al. (1983) found a significant difference between electronic video game users and nonusers in the rotary pursuit task in favor of game users. In contrast to numerous studies on perceptual-motor abilities of traditional sports (Mori et al., 2002), studies on perceptual-motor skills in professional esports gamers remain scarce.

Playing computer games may facilitate the development of cognitive skills and increase attentional capacity (Dobrowolski et al., 2015). Different genres of esports might have different enhancing effects. However, still, there was a significant decrease in reaction time for correct responses after playing action video games for 10 weeks (Chiappe et al., 2013), probably due to a better ability to distinguish stimuli from noise (Donohue et al., 2010). A 10-hr training of playing video games demonstrated an improvement in spatial attention tasks and mental rotation tasks (Feng et al., 2007). Green and Bavelier (2003, 2006) showed that action video game training enhanced visual attentional capacity and accuracy in detecting squares from a briefly flashed display. Anticipation timing is widely used to test perceptual-motor ability, especially in racket sports, and the performance is improved through practice in the anticipation timing accuracy task (Akpinar et al., 2012). However, Akpinar et al. (2012) reported that tennis players demonstrated less absolute error than badminton and table tennis players at the low-stimulus velocity (1 m/s), badminton players in the moderate-stimulus velocity (3 m/s), and tennis players in the high-stimulus velocity (5 m/s), suggesting that different sports can affect perceptual-motor performance in a different manner. In contrast, little is known about how esports gaming activities improve anticipation timing, eye–hand coordination, and peripheral perception in perceptual-motor abilities.

This study aimed to examine differences between professional esports gamers and amateurs in perceptual-motor abilities. Specifically, we assessed perceptual-motor skills in anticipation timing, eye–hand coordination, and peripheral perception that are closely related to esports performance. We hypothesized that professional gamers would perform better than amateurs in each of three perceptual-motor tasks due to their long-time intensive training and competition.

Methods

Participants

Participants consisted of eight male professional esports players (age, 23.8 ± 1.9 years) and eight male amateurs (age, 24.7 ± 2.1 years) in South Korea. We contacted one of the professional esports teams to recruit professional players, and amateurs were recruited from the hosting university. All the participants were right-handed without any known physical and neurological deficits and volunteered to participate in the study. The professional group was part of an esports team mainly playing a strategy simulation game named StarCraft, which is a multiuser real-time strategy game developed by Blizzard Entertainment. The professional gamers were members of the Korea e-Sports Association at the time of data collection. They had been playing esports in a professional team for between 3 and 10 years, in addition to the years paying esports as amateurs. Amateurs had never registered in the Korea e-Sports Association or had any experience playing strategic simulation games. Upon arrival at the laboratory, all participants signed an informed consent form.

Apparatus and Procedure

Anticipation Timing

We used a Bassin anticipation timer (model 50–575, Lafayette Instrument) to measure the anticipation timing (Figure 1a). The LED light stimuli moved from left to right on a runway (9.23 × 9.23 × 228.60 cm) at various speeds (0.45, 1.35, 2.69, and 4.03 m/s). Akpinar et al. (2012) used 1 m/s (low), 3 m/s (moderate), and 5 m/s (high) for the stimulus velocities, and their pilot study showed the velocity of 6 m/s was too fast and unreliable. The distance between the participant and the equipment was 1.5 m. Participants pressed a button in front of them when they determined that the light stimulus arrived at the end of the runway. One trial was demonstrated to the subject for each speed condition, and then five practice trials were collected to give the subject feedback on their anticipation timing. A positive timing means that the button was pressed after the light stimulus arrived at the end of the runway, whereas a negative timing means that the button was pressed before the light stimulus arrived at the end of the runway (Figure 1a). Thereafter, every participant completed 20 trials for each speed condition without feedback. The order of speed conditions was randomized across the participants.

Figure 1
Figure 1

Experimental setup. (a) The Bassin Anticipation Timer: A light travels down the 2.28-m runway from the start to the end at different speeds (i.e., 0.45, 1.35, 2.69, and 4.03 m/s). Subjects pressed a pushbutton in front of them when they anticipated the timing of light arriving at the end. (b) The photoelectric rotary pursuit: The rotary pursuit test was performed at the rotating speed of 30 revolutions per minute under the conditions of rotating directions (i.e., clockwise and counterclockwise) and rotating shape (i.e., circle, triangle, and square). Time on target duration was measured in a 30-s test under each condition. (c) The Vienna Test System: The test involved a central tracking task and a peripheral perception task. Light stimuli were displayed randomly on both panels (Item i). Strip of the light stimulus was presented repeatedly at random order. The subject responded by stepping on a foot pedal under the Vienna Test System as soon as the subject detected the strip while focusing on a central tracking task. Moving target on the monitor (Item ii) is given to fix head movement, and the subject was required to track the moving target by control knobs with two hands (Item iii). Hand–hand coordination was necessary to continue tracking: The left knob controlled tracking from left to right (or from right to left), and the right knob controlled tracking from up to down (or from down to up). The peripheral vision angle was measured in degrees while the subject continued tracking. The warning sound was generated when the subject failed to track the moving target; however, the accuracy was not measured in this test.

Citation: Journal of Electronic Gaming and Esports 1, 1; 10.1123/jege.2022-0001

Eye–Hand Coordination

A Photoelectric Rotary Pursuit (Model 2203E, Lafayette Instrument), known as a useful device to study coordination and limb control (Jeon, 2005), was used to measure eye–hand coordination (Figure 1b). Participants pursued the target as accurately as possible with the electric stylus for 30 s. All participants performed direction effect testing and then task effect testing in order. First, to study the direction effect, we used the rotary pursuit tasks with a circular disk in a clockwise or a counterclockwise direction at a rate of 30 revolution per minute. Participants performed nine trials for each direction without feedback. Second, to study the task effect, we randomly used a rotating target consisting of several types of disks (such as triangle, circle, and square) rotating clockwise at a rate of 30 revolution per minute. One trial was demonstrated for each type of disk. Then, participants practiced every kind of disk five times, and feedback was provided on their performance. Next, participants performed six trials for each task.

Peripheral Perception

The Vienna Test System (SCHUHFRIED GmbH) was used to measure the peripheral visual perception of professional gamers and amateurs (Figure 1c). The panels on both sides of the system contained continuous light stimulations, which kept blinking at random locations. When a straight line of the stimulus light appeared among the random blinking lights, participants responded by immediately stepping on a foot pedal while performing a tracking task on a monitor in front of them, which limited head movements during the testing. The range of angle was obtained if the participant responded to the stimulus appropriately before the stimulus disappeared. The total angle in degrees was calculated by adding the left and right visual fields. We mainly focused on the visual field, excluding results such as foot reaction time and the number of corrections.

Statistical Analyses

A two-way (2 group × 4 speed) mixed analysis of variance (ANOVA) with repeated measures on speed was conducted on the anticipation timing. A two-way (2 group × 2 direction) mixed ANOVA with repeated measures on direction was conducted on time on target duration of rotary pursuit for the eye–hand coordination task. A two-way (2 group × 3 task) mixed ANOVA with repeated measures on task was conducted on time on target duration of rotary pursuit. An independent t test was conducted to compare the peripheral perception angle between the two groups. For all the ANOVA tests, post hoc pairwise comparisons were completed with Bonferroni adjustments when necessary. The Shapiro–Wilk test was used to test the normality of the data. The log transformation was applied if the data were not normally distributed. Statistical analyses were performed using the SAS (version 9.4) statistical software. A significant level was set at α = .05.

Results

The professional gamers showed a negative anticipation timing in all speed conditions, whereas the amateurs displayed a negative anticipation timing in the 1.35, 2.69, and 4.03 m/s speed conditions and a positive anticipation timing in the 0.45 m/s speed condition (Figure 2). Statistical analysis showed the normality of the data and demonstrated that there was a group-by-speed interaction, F(3, 42) = 3.52; p = .023; η2 = .20. Post hoc analysis indicated that there was a difference between the two groups only at 0.45 m/s. Also, there was a speed effect within amateurs between 0.45, 1.35, and 2.69 m/s, whereas no significant difference between speeds was found in professionals.

Figure 2
Figure 2

Means and SDs of the anticipation timing. A positive timing means that the button was pressed after the light stimulus arrived at the end of the runway, while a negative timing means that the button was pressed before the light stimulus arrived at the end of the runway. For statistical analysis, group difference and *speed difference at p < .05.

Citation: Journal of Electronic Gaming and Esports 1, 1; 10.1123/jege.2022-0001

The professional gamers demonstrated similar time on target durations between clockwise and counterclockwise and among three types of disks during the rotary pursuit task (Table 1). Furthermore, the professional gamers displayed similar time on target durations as the amateurs in all the eye–hand coordination tasks. Statistical analysis showed the normality of the data and found neither a main effect nor an interaction for assessing task and direction effects in eye–hand coordination.

Table 1

Mean (SD) of Eye–Hand Coordination Duration and Peripheral Perception Angle and the Statistical Results

ProfessionalAmateurStatistical results
Eye–hand coordination
 Direction
  Clockwise28.92 (1.33)28.11 (0.83)n.s.
  Counterclockwise28.93 (0.97)27.74 (1.10)
 Task
  Triangle28.90 (1.49)27.55 (1.65)n.s.
  Circle28.67 (1.19)27.56 (1.10)
  Square29.20 (1.10)28.66 (1.02)
Vision field
 Peripheral perception165.76 (10.17)151.34 (12.92)t14 = 2.48, p = .026

Note. For statistical results, n.s. at p < .05. n.s. = nonsignificance.

The professional showed a wider range of peripheral perception by almost 15° than the amateurs (Table 1). On average, the mean peripheral perception was 165.76° for the professionals and 151.34° for the amateurs. A statistical analysis showed the normality of the data and reported that there was a significant difference between the two groups in favor of the professional gamers (t14 = 2.48, p = .026).

Discussion

We investigated whether professional esports gamers present better perceptual-motor abilities than amateurs through tasks of anticipation timing, eye–hand coordination, and peripheral perception. There was a difference between professional gamers and amateurs in anticipation timing and peripheral perception, but not in eye–hand coordination. The professional gamers had an earlier anticipation timing regardless of stimulus velocity and a wider range of visual perception than amateurs.

Our results indicated that in all speed conditions ranging from slow to fast (0.45 1.35, 2.69, and 4.03 m/s), the professional gamers showed earlier responses (about 30 ms) to the stimulus than amateurs. Instead of waiting until the stimulus (opponent) arrives at the target, professional gamers produced a more offensive manner by reacting to the stimulus before it arrived. Furthermore, a 15° wider visual field might help professional gamers detect the stimulus earlier and thus respond to it earlier.

Anticipation timing has been shown to be sport specific. Experienced players were more accurate and used to the ball trajectories in that sport, indicating a better matching response with the stimulus (Benguigui & Ripoll, 1998). For instance, Ak and Kocak (2010) reported that junior tennis players had a mean of 50.9 ms of anticipation timing compared with 59.4 ms of table tennis players. Also, they found male junior table tennis players showed a mean of 53.0 ms, and females displayed a mean of 57.4 ms of anticipation timing. It seems that the anticipation timing accuracy of males might be better than that of females. Esports gamers in this study were all male adults. They had better anticipation timing accuracy than junior tennis players and junior table tennis players, suggesting that esports play may have a higher demand on anticipation in shorter time windows. Long-time training might facilitate professional gamers to develop even better anticipation timing. However, this certainly warrants further investigation. Age and gender should be carefully considered in anticipation timing.

Contrary to our hypothesis on rotary pursuit tasks, the result of professionals did not differ from amateurs. This may suggest that the rotary pursuit task is more difficult to improve even with a great deal of intensive esport experience. Previously, Griffith et al. (1983) found no correlation between the amount of time spent and performance in a rotary pursuit task in college students who played video games for approximately 5 hr per week. In addition, Ericsson and Lehmann (1996) found that experts perform excellent tasks in their trained domain but do not always exhibit similar excellence in other untrained domains. In other words, training has its specificity and transferability (Causer & Ford, 2014). When some skills can be transferred from one domain to another, transferability is defined. For example, when tennis swing is enhanced, it helps improve badminton swing positively, and overhand throwing drills are moderately correlated with tennis serve speed (O’Keeffe et al., 2007; Reid et al., 2015). In this context, the rotary pursuit task in our study might not be an appropriate task to assess the transferability of perceptual-motor training in professional esports gamers. However, as professional gamers showed a trend of a longer time on target duration than amateurs, it may be warranted to test various stimulus speeds in future studies.

In addition, we found professional gamers had a broader visual perception field. The human visual system plays a major role in processing visual information, and professional players must have superior ability in peripheral perception. The peripheral perception of the visual field was found to be 170° in handball athletes (Zwierko, 2007) and 174° in female basketball athletes (Mańkowska et al., 2015), both of which are similar to 165° in our professional esports gamers. This suggests that intensive esports training can expand the visual field and result in a wider peripheral perception of the visual field.

Our study provided insight on perceptual-motor ability in professional esports gamers, which may help design esports-specific practice routines and training drills. The years of playing esports as professional gamers are correlated with cortical volume in the right superior frontal gyrus, right superior parietal gyrus, and right precentral gyrus in functional magnetic resonance imaging (fMRI) studies (Campbell et al., 2018). The brain receives the signals through perception and processes the signals to transmit to muscles to make a movement appropriately. Thus, playing esports may involve many different brain areas related to perceptual-motor abilities. It is plausible that playing esports games may have strong potential in rehabilitation for children who have problems in perceptual-motor development.

There were a few limitations in this study. First, professional esports gamers and amateurs in this study were limited to male gamers and esports gamers from various games need to be recruited to generalize the results. Due to the limited access to professional esports gamers, our participants were recruited regardless of the years they played as professional gamers. Second, this study was conducted in a laboratory-based situation, and it may not represent esports gamers’ performance in a real-time esports competition. Third, due to the limited equipment in the laboratory, we were able to assess perceptual motor-abilities using three tasks. Other perceptual-motor tasks, for example, spatial perception assessment and visual memory test, might further reveal differences in perceptual-motor skills between professional gamers and amateurs. Fourth, differences in perceptual-motor skills between professionals and amateurs might be that professionals might have had better perceptual-motor skills than amateurs before professional gamers started intensive professional training. This may contribute to further differences between the two groups reported in this study.

Future studies may include a variety of perceptual-motor test to comprehensively understand perceptual-motor ability between professional gamers and amateurs. Also, future studies may use a longitudinal design and brain imaging to understand the effect of training period on the development of perceptual-motor skills and the pattern of brain activities during esports play.

Conclusion

Esports professional gamers demonstrated better performance in anticipation timing and peripheral perception (a wider field of vision in degrees) when compared with amateurs. Professional esports gamers consistently pressed the button before the stimulus arrived, but similar eye–hand coordination performance as amateurs. These findings suggest that playing esports may elicit further perceptual-motor skill development and result in a higher level of certain perceptual-motor skills.

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  • Zwierko, T., Głowacki, T., & Osiński, W. (2008). The effect of specific anaerobic exercises on peripheral perception in handball players. Kinesiologia Slovenica, 14(1), 6876.

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H. Kim (hkim162@gsu.edu) is corresponding author, https://orcid.org/0000-0003-0952-6474

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  • Figure 1

    Experimental setup. (a) The Bassin Anticipation Timer: A light travels down the 2.28-m runway from the start to the end at different speeds (i.e., 0.45, 1.35, 2.69, and 4.03 m/s). Subjects pressed a pushbutton in front of them when they anticipated the timing of light arriving at the end. (b) The photoelectric rotary pursuit: The rotary pursuit test was performed at the rotating speed of 30 revolutions per minute under the conditions of rotating directions (i.e., clockwise and counterclockwise) and rotating shape (i.e., circle, triangle, and square). Time on target duration was measured in a 30-s test under each condition. (c) The Vienna Test System: The test involved a central tracking task and a peripheral perception task. Light stimuli were displayed randomly on both panels (Item i). Strip of the light stimulus was presented repeatedly at random order. The subject responded by stepping on a foot pedal under the Vienna Test System as soon as the subject detected the strip while focusing on a central tracking task. Moving target on the monitor (Item ii) is given to fix head movement, and the subject was required to track the moving target by control knobs with two hands (Item iii). Hand–hand coordination was necessary to continue tracking: The left knob controlled tracking from left to right (or from right to left), and the right knob controlled tracking from up to down (or from down to up). The peripheral vision angle was measured in degrees while the subject continued tracking. The warning sound was generated when the subject failed to track the moving target; however, the accuracy was not measured in this test.

  • Figure 2

    Means and SDs of the anticipation timing. A positive timing means that the button was pressed after the light stimulus arrived at the end of the runway, while a negative timing means that the button was pressed before the light stimulus arrived at the end of the runway. For statistical analysis, group difference and *speed difference at p < .05.

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