In precision Paralympic sports like wheelchair curling, visual attention is a paramount cognitive determinant of performance. While expertise-dependent differences in gaze behavior are documented in various sports, the specific cognitive mechanisms—particularly attentional selectivity and efficiency—underpinning elite performance in wheelchair curling remain unexplored. This study investigated the visual attention patterns of disabled curling athletes across skill levels to uncover the cognitive strategies associated with expertise.
Methods
Forty-eight disabled curling athletes were stratified into elite (Paralympic/World Champions, n = 16), general (National Champions, n = 16), and novice (Provincial Champions, n = 16) groups. Using Tobii Pro Glasses 3, eye movements were recorded during stone deliveries. Metrics included the number of fixations, fixation duration, and their distribution across predefined Areas of Interest (AOIs: Release Zone, Stone Path, Target/House, Other Areas). Performance was quantitatively assessed by international-level judges based on stone placement accuracy.
Results
A significant Group × AOI interaction was found for both number of fixations (p < 0.001,) and fixation duration (p < 0.001). Elite athletes allocated a significantly higher proportion of their fixations (54.3%) and viewing time (59.8%) to the Target, while minimizing attention to Other Areas (14.7% of fixations, 6.3% of duration). Novices displayed a dispersed attentional pattern, with more fixations on non-essential areas. Elites also demonstrated greater cognitive economy, evidenced by a lower total number of fixations and shorter total fixation duration than novices. Critically, fixation measures on the Target were positively correlated with performance scores (strongest in elites: r = 0.53, p < 0.01), whereas attention to Other Areas and the Stone Path was negatively correlated.
Conclusion
Elite performance in wheelchair curling is characterized by highly selective and efficient visual attention. Experts excel not only in focusing on task-critical information but also in actively suppressing distractions, a hallmark of automated cognitive processing. These findings extend the “Quiet Eye” and cognitive efficiency theories to wheelchair curling, highlighting the critical role of perceptual-cognitive skills. They provide a robust empirical basis for developing targeted attention training protocols to accelerate expertise development in precision sports for athletes with disabilities.
cognitive efficiencyeye-trackingParalympic sportquiet eyevisual attentionwheelchair curlingThe author(s) declared that financial support was received for this work and/or its publication. This research was supported by the Natural Science Foundation of Heilongjiang Province (Project No. LH2023C060).section-at-acceptanceSport PsychologyIntroduction
Wheelchair curling, a sport of precision and strategy within the Paralympic movement, presents a unique context to study the interplay of perception, cognition, and action under physical constraints (Laschowski et al., 2017; Li et al., 2022; World Curling Federation, 2025). The seated delivery position fundamentally alters the visual perspective and the process of gathering environmental information compared to standing athletes, placing a premium on efficient visual-attentional control as a cornerstone of expertise (Howard, 2010; Wang et al., 2022; Hua et al., 2025).
Eye-tracking research in sports sciences has consistently revealed that expert athletes possess a refined perceptual-cognitive architecture (Mann et al., 2007; Pojskic et al., 2020). They exhibit more economical visual search patterns, characterized by fewer but longer fixations on critical locations, culminating in the “Quiet Eye” (QE)—a final prolonged fixation on a relevant target before movement initiation, associated with optimal motor planning and performance under pressure (Vickers, 2007; González et al., 2017; Mizusaki et al., 2025). These superior gaze behaviors are theorized to reflect highly developed mental representations and cognitive processing efficiency, honed through years of deliberate practice (Ericsson and Lehmann, 1996; Zacharias et al., 2024).
Similar expertise-related visual strategies have been observed across various precision and aiming sports. For instance, in rifle shooting, experts exhibit longer and more stable QE periods compared to novices (Janelle et al., 2000; Williams et al., 2002). In air pistol shooting, elite performers demonstrate more efficient gaze behavior and attentional control linked to superior outcomes (Güler et al., 2023; Bayram et al., 2024). Furthermore, expertise in such tasks is also associated with enhanced executive functions, underscoring the intertwined nature of perceptual and cognitive processes (Shao et al., 2020).
Despite the acknowledged role of vision in curling strategy and execution (Bradley, 2009; Millet et al., 2021), scientific inquiry into the visual attention of athletes in this domain, particularly within the context of Paralympic sports, is scarce. Preliminary studies on able-bodied curlers suggest they employ specific visual strategies for “reading the ice” (Li et al., 2024; Song et al., 2022). Furthermore, studies in other team sports like soccer have highlighted how perceptual-cognitive processes, including visual search behavior, are affected by factors such as physiological demands and game contexts (Casanova et al., 2013, 2022), and how attentional effort varies across different player positions during real match play (Ballet et al., 2023). However, a significant gap exists in understanding the visual attention characteristics of elite wheelchair curling athletes and the underlying cognitive mechanisms that facilitate their superior performance. Understanding these mechanisms is not only of theoretical interest for expertise research but also holds profound practical value for designing evidence-based perceptual-cognitive training interventions for athletes with disabilities.
Therefore, this study aimed to bridge this gap by systematically investigating the visual attention characteristics of wheelchair curling athletes across a spectrum of expertise using portable eye-tracking. We recruited a unique cohort, including Paralympic and World Championship gold medalists, and compared them with national and provincial champions. The objectives were: (1) to compare the differences in the number of fixations, fixation duration, and their spatial distribution among elite, general, and novice athletes; and (2) to analyze the relationship between these visual attention metrics and sports performance. Grounded in theories of expert performance and attentional control, we hypothesized that elite athletes would exhibit more selective and efficient visual attention patterns, characterized by a dominant focus on the target and effective suppression of irrelevant areas, and that these specific patterns would be most strongly correlated with superior performance scores.
Materials and methodsParticipants
An a priori power analysis was conducted using G*Power 3.1.9.7 (Faul et al., 2007) for a one-way ANOVA with three groups. With an effect size f = 0.25, α = 0.05, and power (1-β) = 0.80 (Petway et al., 2020; López-Laval et al., 2016), the minimum required sample size was 42. We recruited 48 athletes to account for potential data attrition.
Forty-eight wheelchair curling athletes (24 male, 24 female; mean age = 28.6 ± 6.3 years) from the Heilongjiang Provincial Disabled Persons’ Federation participated. Participants had various physical disabilities eligible for Paralympic wheelchair curling classification, primarily including spinal cord injuries and lower limb amputations. All participants provided written informed consent. Based on competitive achievement, participants were divided into three groups:
Elite Athletes (n = 16): Paralympic and World Championship gold medalists (e.g., 2018 PyeongChang, 2022 Beijing, 2023 & 2025 World Championships). Mean training experience: 11.4 ± 3.2 years.
General Athletes (n = 16): Gold medalists of the National Games of China. Mean training experience: 7.2 ± 2.5 years.
Novice Athletes (n = 16): Gold medalists of provincial-level games in China. Mean training experience: 3.8 ± 1.7 years.
All participants had normal or corrected-to-normal vision and no diagnosed visual perception disorders.
Apparatus and AOI definition
Visual attention data were collected using the Tobii Pro Glasses 3 wireless portable eye-tracker (Tobii, Sweden). The device has a sampling rate of 100 Hz and allows for natural movement during the actual delivery. The eye-tracker was calibrated for each participant according to the manufacturer’s guidelines prior to testing (Zhao et al., 2024). The visual field was segmented into four dynamic Areas of Interest (AOIs) for analysis (Figure 1). These AOIs were selected based on the fundamental phases of the curling delivery and key visual information sources identified in prior curling research (Bradley, 2009; Li et al., 2024):
Release Zone: The immediate area of stone release (critical for initial motor control).
Stone Path: The anticipated trajectory from the hack to the house (relevant for trajectory prediction and online adjustment).
Target (House): The circular scoring area (the ultimate goal for action planning).
Other Areas: Fixations outside predefined AOIs, indicating potential distraction.
(AOIs were manually defined by a primary researcher and subsequently verified by a second independent researcher to ensure consistency).
Defined areas of interest (AOIs) for fixation analysis in curling.
Diagram of a curling rink showing a red-highlighted stone path connecting two circular targets labeled as Target (House); arrows label the Stone Path, Other Areas, and Release Zone with a curling stone shown in the release zone.Experimental design and procedure
A between-groups design was employed. The experiment was conducted on a standard international wheelchair curling sheet under competition-standard ice conditions (−5 °C ± 0.5 °C) at the Heilongjiang Curling Training Center.
The experiment was conducted at the Heilongjiang Curling Training Center under experimenter supervision from March 6 to March 9, 2024. Prior to formal testing, participants completed a standardized warm-up. The warm-up protocol consisted of 5 min of light upper-body mobility exercises (arm circles, shoulder rolls) followed by 5 practice deliveries with a stationary stone to re-familiarize with the delivery motion without performance pressure. The formal delivery sequence was randomized to control for order effects. Before testing, participants were fitted with the eye tracker, which was calibrated according to manufacturer specifications. Once successful calibration was confirmed, data recording commenced under the supervision of the equipment operator.
Performance was designed to simulate competitive conditions, assessing participants’ ability to accurately deliver stones to specific target zones. The target (a specific circle within the house) was verbally communicated to the athlete before each delivery attempt. The procedure adhered to official competition rules, with all deliveries initiated from the starting line. Each participant was permitted two practice throws followed by three consecutive formal delivery attempts using the same stone, delivered in a clockwise direction. Data from the three formal trials were averaged for each participant for statistical analysis. Sweeping was prohibited throughout the testing session (Li et al., 2024; Yamamoto et al., 2018).
Performance was evaluated by five internationally-certified judges, blinded to participant identity and sequence. Scoring was based on the final stone position relative to the house’s concentric circles (Figure 2): 5 points for the button (center circle), 4 for the one-foot ring, 3 for the four-foot ring, 2 for the eight-foot ring, and 1 for the twelve-foot ring. Stones on a boundary were awarded the higher score (Li et al., 2024; Yamamoto et al., 2018).
Curling rink and scoring zones in the curling performance.
Bar chart comparing percentage of total fixations across skill levels—Elite, General, and Novice—for four areas: Release Zone, Stone Path, Target, and Other Areas. Target receives the highest fixation percentage in all groups, while fixation on Other Areas increases as skill decreases.Data analysis
Eye-tracking data were processed in Tobii Pro Lab (v1.19) using the I-VT fixation filter (velocity threshold: 30°/s; minimum duration: 160 ms). For each trial, we extracted the number of fixations, fixation duration, and their distribution across AOIs. These specific gaze metrics—number of fixations and fixation duration—are widely used in sports eye-tracking research to quantify visual search efficiency and attentional allocation (Casanova et al., 2022).
Statistical analyses were performed in SPSS 26.0. After confirming normality and homogeneity of variance, two-way mixed ANOVAs (Group × AOI) were conducted for number of fixations and fixation duration, with AOI as the within-subjects factor and Group (Elite, General, Novice) as the between-subjects factor. One-way ANOVAs assessed group differences in total fixation metrics. Post-hoc tests used Bonferroni corrections. Pearson correlation analyses were performed separately for each group to examine the relationship between AOI-specific metrics and performance scores. Significance was set at p < 0.05. Effect sizes are reported as partial eta-squared (ηp2).
ResultsNumber of fixations across AOIs
A two-way mixed ANOVA revealed significant main effects of Group (F(2,150) = 8.65, p < 0.001, ηp2 = 0.12) and AOI (F(3,150) = 282.15, p < 0.001, ηp2 = 0.86), and a significant Group × AOI interaction (F(6,150) = 5.17, p < 0.001, ηp2 = 0.17). Post-hoc tests showed that elite athletes made significantly fewer fixations on “Other Areas” than both general (p = 0.028) and novice athletes (p < 0.001). No other significant between-group differences were found for specific AOIs (Table 1).
Descriptive statistics and group comparisons for the number of fixations across AOIs (unit: times).
AOI
Elite
General
Novice
F
p
Partial η2
Release zone
4.31 ± 0.79
4.63 ± 0.89
5.44 ± 1.21
Stone path
5.19 ± 1.33
5.94 ± 1.06
6.31 ± 1.08
Target (House)
16.38 ± 1.96
15.31 ± 1.40
14.56 ± 1.75
Other areas
4.44 ± 1.41
6.69 ± 1.20
8.06 ± 1.06
Main effect: group
8.65
** < 0.001
0.115
Main effect: AOI
282.15
** < 0.001
0.862
Interaction: group × AOI
5.17
** < 0.001
0.171
** < 0.001.
Fixation duration across AOIs
A two-way mixed ANOVA revealed significant main effects of Group (F(2,150) = 25.71, p < 0.001, ηp2 = 0.26) and AOI (F(3,150) = 1442.10, p < 0.001, ηp2 = 0.97), and a significant Group × AOI interaction (F(6,150) = 24.71, p < 0.001, ηp2 = 0.50). Post-hoc tests revealed a clear expertise gradient (Table 2): elite athletes had significantly longer fixation durations on the Target than novices, and on the Release Zone than novices. Conversely, novices exhibited significantly longer fixation durations on the Stone Path and Other Areas than both elite and general athletes. General athletes also fixated longer on the Stone Path and Other Areas than elite athletes.
Descriptive statistics and group comparisons for the fixation duration across AOIs (unit: ms).
AOI
Elite
General
Novice
F
p
Partial η2
Release zone
6,646 ± 344
6,093 ± 367
5,423 ± 346
Stone path
3,082 ± 592
3,728 ± 521
5,100 ± 682
Target (house)
16,956 ± 1,377
16,256 ± 629
15,531 ± 1,191
Other areas
1883 ± 571
3,648 ± 483
4,937 ± 1,295
Main effect: group
25.71
** < 0.001
0.255
Main effect: AOI
1442.10
** < 0.001
0.966
Interaction: group × AOI
24.71
** < 0.001
0.497
** < 0.001.
Total visual attention metrics and distribution
One-way ANOVAs revealed significant group effects on the total number of fixations (F (2,45) = 6.24, p = 0.004, ηp2 = 0.21) and total fixation duration (F(2,45) = 4.56, p = 0.016, ηp2 = 0.17). Novice athletes had a significantly higher total number of fixations than elites (p = 0.003), and a longer total fixation duration than elites (p = 0.013) (Table 3).
Descriptive statistics and group comparisons for the total visual attention metrics.
Dependent variable
Group
Mean ± SD
F
p
Partial η2
Total number of fixations (times)
Elite
30.19 ± 2.26
6.24
**0.004
0.214
General
32.31 ± 1.74
Novice
34.13 ± 1.82
Total fixation duration (ms)
Elite
28,438 ± 1,440
4.56
*0.016
0.166
General
29,715 ± 673
Novice
30,976 ± 1,560
* < 0.05, ** < 0.01.
The distribution of visual attention (Figures 3, 4) highlighted stark expertise differences. Elite athletes allocated the majority of fixations (54.3%) and viewing time (59.8%) to the Target, with minimal allocation to Other Areas (14.7% of fixations, 6.3% of duration). Novices showed a dispersed pattern (Target: 42.6% of fixations, 49.2% of duration; Other Areas: 25.1% of fixations, 16.1% of duration). General athletes displayed an intermediate profile.
Distribution of number of fixations across AOIs by expertise level.
Bar chart comparing eye fixation percentages on Release Zone, Stone Path, Target, and Other Areas among Elite, General, and Novice groups. Target fixation exceeds 48 percent for all groups, highest in Elite at 54 percent.
Distribution of fixation duration across AOIs by expertise level.
Four scatterplots display the relationship between fixation duration in different zones and performance score for elite, general, and novice groups, with trendlines and overall correlation coefficients labeled for each zone.Relationship between fixation patterns and performance scores
Separate correlation analyses for each group revealed that number of fixations and fixation duration on the Target were positively correlated with performance scores (strongest in elites: r = 0.53, p < 0.01 for number of fixations; r = 0.50, p < 0.01 for fixation duration). Conversely, fixations on Other Areas (strongest negative in elites: r = −0.48, p < 0.01 for number of fixations; r = − 0.46, p < 0.01 for fixation duration) and the Stone Path were negatively correlated with performance (Figures 5, 6).
Relationships between fixation counts in different AOIs and performance scores for each group (Elite, General, Novice).
Diagram of a curling sheet showing two circular targets with colored rings, labeled lines including tee line, hog line, centre line, and hack, and a scoring system from 1 to 5 points based on proximity to the center.
Relationships between fixation duration in different AOIs and performance scores for each group (Elite, General, Novice). Figures 5, 6 have been revised to improve readability by increasing font sizes and reducing visual clutter, while Figure 6 is presented here as an example of the improved format.
Four scatterplots compare number of fixations versus performance score for three groups: elite (blue circles), general (purple diamonds), and novice (yellow triangles), showing regression lines and overall correlation values (r) for Release Zone, Stone Path (negative correlations), Target, and Other Areas (positive correlations).Discussion
This study provides a novel investigation into the cognitive mechanisms of visual attention in wheelchair curling athletes, revealing systematic expertise-related differences that align with and extend established theories of perceptual-cognitive expertise.
Our central finding is the superior attentional selectivity and cognitive efficiency of elite athletes. Elites allocated over half of their visual resources (number of fixations and fixation duration) to the task-critical Target area, while simultaneously exhibiting the most effective suppression of irrelevant information, as evidenced by minimal attention to Other Areas. This pattern signifies a highly refined “knowledge-driven” attentional control system (Vickers, 2007; Klatt and Smeeton, 2022), where cognitive resources are deployed based on the paramount requirements of the task. The significant Group × AOI interaction underscores that expertise is defined not by a general increase in looking, but by a qualitative shift in what is attended to and what is ignored. This finding resonates with the Attentional Control Theory (Eysenck et al., 2007), which posits that anxiety and expertise influence the balance between goal-directed (top-down) and stimulus-driven (bottom-up) attentional systems. The elite athletes’ pattern suggests a stronger top-down control, efficiently prioritizing task-relevant cues while inhibiting distractors.
The fixation duration patterns offer strong support for the application of the Quiet Eye (QE) theory to wheelchair curling. The elites’ prolonged fixations on the Target and Release Zone are indicative of an extended QE period, facilitating optimal motor parameterization and online control during critical movement phases (Vickers, 2007; González et al., 2017). Conversely, the novices’ longer dwell time on the Stone Path suggests a “reactive” or “feedback-dependent” strategy, potentially attempting to track an anticipated path rather than trusting a pre-programmed action—a hallmark of less automated skill (Mann et al., 2007; Babiloni et al., 2009).
Furthermore, the finding that elite athletes achieved superior performance with a lower total number of fixations and shorter total fixation duration is a clear marker of cognitive economy. This efficiency suggests that experts extract the necessary information more rapidly and with fewer samples, relying on rich internal models built through extensive practice (Presta et al., 2021; Ericsson and Lehmann, 1996). Novices, with less refined cognitive representations, appear to engage in more effortful and extensive visual searching, implying a less efficient and more capacity-consuming processing style (Slagter et al., 2018; Burris et al., 2020).
The correlation results powerfully link these gaze behaviors to performance outcomes. The strong positive correlation between Target-looking and performance, most pronounced in elites, confirms the functional value of this focus. More critically, the strong negative correlations for Other Areas and the Stone Path in elites indicate that for experts, the ability to inhibit distracting or non-essential information is as crucial as the ability to focus (Hülsdünker et al., 2018; Harrison et al., 2023). This highlights a dual mechanism of expert attention: enhanced facilitation of relevant stimuli coupled with active suppression of irrelevant stimuli (Cui et al., 2025; Pusenjak et al., 2015). This finding moves beyond simply identifying “where experts look” to explaining “how” their cognitive system achieves superior performance through efficient resource management.
An alternative explanation for the observed efficiency could be attributed to greater task familiarity and movement automatization among elites, which inherently reduces the need for conscious visual monitoring of the action itself (Stone Path) or the environment (Other Areas). While our design cannot fully disentangle automatization from active inhibition, the strong negative correlations specifically for elites suggest that superior performance is associated not just with less looking elsewhere, but with an active, strategic avoidance of non-critical information—a skill that likely develops alongside automatization.
From an applied perspective, these findings have direct implications for training in Paralympic sports. Developing perceptual-cognitive training protocols for wheelchair curling athletes should emphasize cultivating both selective focus (e.g., through QE training) and distraction inhibition. This could involve gaze-contingent feedback systems that alert athletes when their focus drifts from the target, or simulated training environments with controlled visual distractors. Such interventions would be particularly valuable for athletes with disabilities, as they offer a pathway to enhance performance that complements physical training and adapts to individual functional profiles.
Conclusion
This study demonstrates that expertise in wheelchair curling is underpinned by distinct and highly efficient visual-attentional strategies. Elite athletes exhibit a sophisticated cognitive profile characterized by:
Superior Attentional Selectivity: A dominant focus on the task-critical target area (House).
Effective Cognitive Inhibition: The ability to actively suppress attention to irrelevant and distracting areas.
Enhanced Cognitive Economy: Achieving superior performance with less overall visual sampling, indicative of automated processing.
These findings robustly extend theories of attentional control and the Quiet Eye to the domain of precision Paralympic sports. They also suggest potential applicability of similar perceptual-cognitive training principles to other precision Paralympic disciplines, such as shooting or archery. They underscore that perceptual-cognitive skills are a critical component of expertise in wheelchair curling. Consequently, training interventions should be designed to cultivate not just the physical skill of delivery, but also the cognitive skills of focused attention and distraction inhibition, potentially through gaze-contingent feedback and video-based simulation training.
Limitations and future research
While this study was conducted in an ecologically valid setting, some limitations warrant mention. The sample was drawn from a single province; future multi-regional studies would enhance generalizability. Secondly, incorporating neurophysiological measures like EEG or fNIRS could directly probe the neural mechanisms of the observed attentional control and inhibition. Third, this study was conducted in a controlled environment; future research should examine how these fixation patterns hold under the heightened psychological pressure of actual competition. It is also important to note that eye-tracking captures overt attention (where one is looking), but not necessarily covert attention (where one is attending mentally without moving the eyes). Finally, a primary applied direction is the development and rigorous testing of perceptual-cognitive training protocols, based on these findings, to enhance both the visual-attentional skills and on-ice performance of developing athletes. Future longitudinal intervention studies are needed to establish a causal link between training-induced changes in gaze behavior and performance improvements.
Data availability statement
The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.
Ethics statement
The studies involving humans were approved by the Ethics Committee of the Heilongjiang Provincial Disabled Persons’ Federation (No. 20240126, Approval Date: January 26, 2024). The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.
The author(s) declared that this work was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Generative AI statement
The author(s) declared that Generative AI was not used in the creation of this manuscript.
Any alternative text (alt text) provided alongside figures in this article has been generated by Frontiers with the support of artificial intelligence and reasonable efforts have been made to ensure accuracy, including review by the authors wherever possible. If you identify any issues, please contact us.
Publisher’s note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
ReferencesBabiloniC.Del PercioC.RossiniP. M.MarzanoN.IacoboniM.InfarinatoF.. (2009). Judgment of actions in experts: ahigh-resolution EEG study in elite athletes. NeuroImage45, 512–521. doi: 10.1016/j.neuroimage.2008.11.035, 19111623BalletC.BarretoJ.HopeE.CasanovaF. (2023). What is the visual behaviour and attentional effort of football players in different positions during a real 11v11 game? A pilot study. F1000Res12:679. doi: 10.12688/f1000research.134231.4, 38076296Bayramİ.KanatE. A.ŞimşekD. (2024). Comparison of quiet eye duration of three different performance level athletes in air pistol shooting: a preliminary research report. Europ. J. Phys. Educ. Sport Sci.11:81. doi: 10.46827/ejpe.v11i8.5730BradleyJ. L. (2009). The sports science of curling: a practical review. J. Sports Sci. Med.8, 495–500. doi: 10.2519/jospt.2009.0415, 24149588BurrisK.LiuS.AppelbaumL. (2020). Visual-motor expertise in athletes: insights from semiparametric modelling of 2317 athletes tested on the Nike SPARQ Sensory Station. J. Sports Sci.38, 320–329. doi: 10.1080/02640414.2019.1698090, 31782684CasanovaF.EstevesP. T.PadilhaM. B.RibeiroJ.WilliamsA. M.GargantaJ. (2022). The effects of physiological demands on visual search behaviours during 2 vs. 1 + GK game situations in football: an in-situ approach. Front. Psychol.13:885765. doi: 10.3389/fpsyg.2022.885765, 35712138CasanovaF.GargantaJ.SilvaG.AlvesA.OliveiraJ.WilliamsA. M. (2013). The effects of prolonged intermittent exercise on perceptual-cognitive processes in soccer players. Med. Sci. Sport Exer.45, 1610–1617. doi: 10.1249/MSS.0b013e31828b2ce9, 23470295CuiJ.ZhouH.ChenR.LiD.MaiW.PengW.. (2025). Improvement strategies of athlete's concentration level based on visual attention model. Sci. Rep.15:20580. doi: 10.1038/s41598-025-06556-y, 40595101EricssonK. A.LehmannA. C. (1996). Expert and exceptional performance: evidence of maximal adaptation to task constraints. Annu. Rev. Psychol.47, 273–305. doi: 10.1146/annurev.psych.47.1.273, 15012483EysenckM. W.DerakshanN.SantosR.CalvoM. G. (2007). Anxiety and cognitive performance: attentional control theory. Emotion7, 336–353. doi: 10.1037/1528-3542.7.2.336, 17516812FaulF.ErdfelderE.LangA.-G.BuchnerA. (2007). G*power 3: a flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Beha Res Methods39, 175–191. doi: 10.3758/bf03193146, 17695343GonzálezC. C.CauserJ.MiallR. C.GreyM. J.HumphreysG.WilliamsA. M. (2017). Identifying the causal mechanisms of the quiet eye. Eur. J. Sport Sci.17, 74–84. doi: 10.1080/17461391.2015.1075595, 26356536GülerG.ŞimşekD.TuncerS.Mon-LópezD. (2023). Evaluation of physiological parameters and gaze behaviour of air pistol shooters related to performance outcomes. Int. J. Perf. Anal. Sport23, 309–320. doi: 10.1080/24748668.2023.2261072HarrisonR. E.GieselM.HesseC. (2023). Action perception in athletes: expertise facilitates perceptual discrimination. Percept. Mot. Skills130, 1472–1494. doi: 10.1177/00315125231182046, 37277916HowardB. (2010). Curl to win: Expert advice to improve your game. New York, NY: HarperCollins.HuaL.ZhuY.BiG.ZhuM.DiaoY. (2025). Effects of sliding techniques on lower limb biomechanics and muscle synergy during curling delivery: a focus on joint kinetics and muscle coordination. Front. Hum. Neurosci.19:1587118. doi: 10.3389/fnhum.2025.1587118, 40654565HülsdünkerT.StrüderH. K.MierauA. (2018). The athletes' visuomotor system - cortical processes contributing to faster visuomotor reactions. Eur. J. Sport Sci.18, 955–964. doi: 10.1080/17461391.2018.1468484, 29738678JanelleC. M.HillmanC. H.AppariesR. J.MurrayN. P.MeiliL.FallonE. A.. (2000). Expertise differences in cortical activation and gaze behavior during rifle shooting. J. Sport Exerc. Psychol.22, 167–182. doi: 10.1123/jsep.22.2.167KlattS.SmeetonN. J. (2022). Processing visual information in elite junior soccer players: effects of chronological age and training experience on visual perception, attention, and decision making. Eur. J. Sport Sci.22, 600–609. doi: 10.1080/17461391.2021.1887366, 33554775LaschowskiB.MehrabiN.McPheeJ. (2017). Inverse dynamics Modeling of Paralympic wheelchair curling. J. Appl. Biomech.33, 294–299. doi: 10.1123/jab.2016-0143, 28084864LiY.ShiL.YangR.HuW. F.RuX.GaoP. (2022). Research progress on the competitive ability characteristics and training strategies of elite wheelchair curlers. China Sport Sci. Technol.58, 3–8. doi: 10.16470/j.csst.2022010LiT.WangX.WuZ.LiangY. (2024). The effect of stroboscopic vision training on the performance of elite curling athletes. Sci. Rep.14:31730. doi: 10.1038/s41598-024-82685-0, 39738499López-LavalI.Legaz-ArreseA.GeorgeK.Serveto-GalindoO.González-RaveJ. M.Reverter-MasiaJ.. (2016). Cardiac troponin I release after a basketball match in elite, amateur and junior players. Clin. Chem. Lab. Med.54, 333–338. doi: 10.1515/cclm-2015-0304, 26136302MannD. T. Y.WilliamsA. M.WardP.JanelleC. M. (2007). Perceptual-cognitive expertise in sport: a meta-analysis. J. Sport Exerc. Psychol.29, 457–478. doi: 10.1123/jsep.29.4.457, 17968048MilletG. P.BrocherieF.BurtscherJ. (2021). Olympic sports science-bibliometric analysis of all summer and winter Olympic sports research. Front Sports Act Living3:772140. doi: 10.3389/fspor.2021.772140, 34746779MizusakiY.KameiM.IkudomeS.MurataM.MannD. L.NakamotoH. (2025). Success in basketball shooting is better explained by less variability in quiet eye duration than the average quiet eye duration itself. Psychol. Sport Exerc.79:102853. doi: 10.1016/j.psychsport.2025.102853, 40194673PetwayA. J.FreitasT. T.Calleja-GonzálezJ.Medina LealD.AlcarazP. E. (2020). Training load and match-play demands in basketball based on competition level: a systematic review. PLoS One15:e0229212. doi: 10.1371/journal.pone.0229212, 32134965PojskicH.McGawleyK.GustafssonA.BehmD. G. (2020). The reliability and validity of a novel sport-specific balance test to differentiate performance levels in elite curling players. J. Sports Sci. Med.19, 337–346. doi: 10.1101/2024.05.11.24307223, 32390727PrestaV.VitaleC.AmbrosiniL.GobbiG. (2021). Stereopsis in sports: visual skills and Visuomotor integration models in professional and non-professional athletes. Int. J. Environ. Res. Public Health18:11281. doi: 10.3390/ijerph182111281, 34769799PusenjakN.GradA.TusakM.LeskovsekM.SchwarzlinR. (2015). Can biofeedback training of psychophysiological responses enhance athletes' sport performance? A practitioner's perspective. Phys. Sportsmed.43, 287–299. doi: 10.1080/00913847.2015.1069169, 26200172ShaoM.LaiY.GongA.YangY.ChenT.JiangC. (2020). Effect of shooting experience on executive function: differences between experts and novices. PeerJ8:e9802. doi: 10.7717/peerj.9802, 32983637SlagterH. A.AlilovicJ.Van GaalS. (2018). How early does attention modulate visual information processing? The importance of experimental protocol and data analysis approach. Cogn. Neurosci.9, 26–28. doi: 10.1080/17588928.2017.1372405, 28845741SongM.ZhaoQ.DuC.ZhouC.LiR. (2022). The relationship between the accuracy of curling athletes' duration judgment and delivery performance. PeerJ10:e13541. doi: 10.7717/peerj.13541, 35722254VickersJ. N. (2007). Perception, cognition, and decision training: The quiet eye in action. Champaign, IL: Human Kinetics.WangX.LiuR.ZhangT.ShanG. (2022). The proper motor control model revealed by wheelchair curling quantification of elite athletes. Biology11:176. doi: 10.3390/biology11020176, 35205043WilliamsA. M.SingerR. N.FrehlichS. G. (2002). Quiet eye duration, expertise, and task complexity in near and far aiming tasks. J. Motor Behav.34, 197–207. doi: 10.1080/00222890209601941, 12057892World Curling Federation (2025) The rules of curling and rules of competition. Available online at: https://worldcurling.org/wp-content/uploads/2025/08/Rules-2025.pdf (Accessed August 15, 2025).YamamotoMKatoSIizukaH. (2018). Learning of expected scores distribution for positions of digital curling. Workshop on curling informatics. The 23rd game programming workshop (GPW-2018), Shonan, Japan.ZachariasE.RobakN.PassmoreS. (2024). An examination of studies related to the sport of curling: a scoping review. Front. Sports Act Liv.6:1291241. doi: 10.3389/fspor.2024.1291241, 38414637ZhaoX.ZhaoC.LiuN.LiS. (2024). Investigating the eye movement characteristics of basketball players executing 3-point shot at varied intensities and their correlation with shot accuracy. PeerJ12:e17634. doi: 10.1371/journal.pone.0299938, 39172908
Edited by: Thiago Ribeiro Lopes, Federal University of São Paulo, Brazil
Reviewed by: Filipe Casanova, Universidade Lusófona do Porto, Portugal
Ismail Bayram, Technical University Dresden, Germany