Emily Zacharias
Nicole Robak
Steven Passmore- Perceptual Motor Behaviour Laboratory, Faculty of Kinesiology & Recreation Management, University of Manitoba, Winnipeg, MB, Canada
Introduction: There has been growth in research in the sport of curling over the past few decades. The need for a scoping review is warranted. This study's purpose was to identify and synthesize research evidence regarding quantitative variables for a series of components within the sport of curling.
Methods: A scoping review of studies published and established within four databases was performed. One independent reviewer selected studies based on a systematic procedure. Inclusion criteria for studies were: (1) interventions that focused on the sport of curling; (2) quantitative in nature; (3) written in English; and (4) published within a peer-reviewed journal, a conference presentation, or a published thesis.
Results: Searching identified 8,467 articles and 94 met the inclusion criteria. Data were organized and synthesized based on the devised research variables from the sport of curling: The curl mechanism of the curling stone; the impact of sweeping on stone trajectory; curling delivery mechanics; wheelchair curling; technology analysis; strategy and tactics; psychological factors; injury occurrences; facility and arena infrastructure; and assessment of curling training and ability. The findings confirm the strong knowledge base that exists across game variables and unveil controversy between the underlying physics that produces curl, as well as the mechanisms of sweeping responsible for manipulating the stone trajectory.
Conclusions: Knowledge derived from this review can assist researchers, coaches, and curlers in addressing the specific variables of the sport that influence stone trajectory and game results. Such awareness will expose gaps in the current understanding and foster new research endeavors to further the knowledge of the sport.
Introduction
Curling is a target-directed winter sport with origins that date back to Scotland in 1530 (1). Today, the modern game is played with granite rocks on an indoor 42 m pebbled ice surface and is increasingly advancing in its rules and geographic popularity and is played at both a recreational and professional level (2). It has evolved into an Olympic and Paralympic sport with Women's, Men's, Mixed Doubles, and Mixed Wheelchair divisions (3). The traditional version of the sport consists of two teams, made up of four players per team, each throwing eight stones per end. The team with the advantage of throwing the last rock of the end has the “hammer”. By having the “hammer” the likelihood of winning an end is potentially increased. It is increased because the thrower can either knock out an opponent's stone or position their stone closer to the center pin. Each team member throws two consecutive stones per end alternating with the opposing team, translating the rock from the hack to the far house by releasing it at the near hog line (2). The rocks thrown with a linear and angular velocity travel down the ice while curling laterally across the sheet depending on the rotation applied to the handle. Team members not throwing act as sweepers, brushing in front of the rock in an attempt to influence the motion of the rock. The winning team of the end collect points at the completion of each end by having the stone closest to the center pin, and they receive additional points for each of their stones that rests in the house closer to the pin than the nearest opponent stone. The goal is to have the most points after the final end (3).
This sport, commonly known as “chess on ice”, is a combination of skill and tradition, with a unique set of physical demands (2). It comprises many variables including strategy and tactics, delivery biomechanics, sweeping techniques, emotional control, and team cohesion. The sport is highly variable, dependent on the state of the ice, the initial stone velocity, the ability to deliver the rock on target, and the number of rock rotations. Further, variability exists in stone trajectory due to the influence of sweepers brushing at varying speeds and positions (2). Technological advancements are constantly evolving the game while scientific data and field experience play an essential role in accumulating knowledge for each variable of the game, to allow for progression in competition and athleticism (4). The sport has many quantitative variables that determine the motion of the curling rock and the scoreboard result; thus, it appeared vital to review and summarize this published data. Through investigation, no comprehensive scoping review currently exists to examine all quantitative research conducted on the sport.
The purpose of this scoping review is (1) to consider all quantitative research that has been conducted in the sport of curling in order to understand the depth of our current knowledge in this field, (2) to establish the gaps in our understanding of the sport of curling, and (3) to determine future directions of study within the sport to inform athletes, coaches, as well as researchers on how to optimize play.
Methods
A scoping review of the literature was appropriate to meet the objectives of this study and answer the research question: what variables have been collected in curling studies to date, and are they meaningful to the multifaceted sport or prioritized as a scientific variable only?
The protocol was developed using the scoping review methodological framework adopted from Arksey and O'Malley (5). The draft protocol for the review was analyzed by research colleagues and implemented. The protocol consisted of a series of five stages, details of the search strategy and steps of the review process included:
(1) Identifying and collecting relevant studies: literature searches were conducted across four electronic bibliographic databases which include: PubMed, SPORTDiscus, Scopus, and Google Scholar. An initial search, using the search term “Curling” was conducted using Harzing's Publish or Perish software (6). This search established salient parameters and eight key search terms to carry out additional searches across the four databases. Those eight key terms included: (i) curling rock; (ii) sweeping effect in curling; (iii) curling team dynamics; (iv) curling delivery; (v) curling brush; (vi) cognitive imagery in curling; (vii) curling slide; and (viii) motion of curling rock. The collected literature was then screened for relevance in the sport of curling. After removing duplicates, studies were assessed for eligibility. Reference lists of eligible studies were further screened for additional, relevant studies.
(2) Selecting of studies: inclusion and exclusion criteria were established to filter and guide searches for relevant literature. In order to be included, literature from searches had to meet four inclusion criteria: (i) be from a peer-reviewed journal, a conference presentation, or a published thesis; (ii) published in the English language; (iii) include documented interventions or analysis in the sport of curling; and (iv) be quantitative in nature and/or describe quantitative research variables (mathematical modeling or statistical comparison). The literature was not restricted in time frame, study population, geographical publication, or type/design of journal article. Collected literature that did not meet all criteria was excluded, however, conflicting literature were analyzed by two colleagues to reach consensus for inclusion. By applying the eligibility criteria, two reviewers screened the articles for selection. Blinding was applied at this stage to ensure no bias between reviewers in the selection process. All conflicts between the two reviewers, generated through screening, were discussed to reach consensus. When conflict remained, the opinion of a third reviewer was sought to reach consensus. Initially, articles were selected from the title and abstract screening. A second, more in-depth selection, was then conducted through full-text screening. June 1, 2021 was the last date that the search was executed.
(3) Charting the data: once included articles were selected, data was extracted and charted according to author, title, journal, publication year, geographical location, purpose, sample size and type, methodology, intervention type, outcomes, key findings, and barriers. One author extracted and grouped the data, and another validated the data to ensure accuracy. Data were organized and grouped into subtopics according to the identified study purposes (i) the curl mechanism of the curling stone; (ii) the impact of sweeping on stone trajectory; (iii) curling delivery mechanics; (iv) wheelchair mechanics; (v) technology and tools; (vi) strategic/tactical analysis; (vii) psychological aspects; (viii) injury occurrences; (ix) impact of facility infrastructure on ice surfaces; and (x) assessment of curling training and ability.
(4) Summarizing and synthesis of the results: authors collectively compared and discussed the charted data. Descriptive statistics were performed to characterize the research literature and to identify the breadth and gaps. Trends across geographic location and decades of publication of included studies were evaluated. The study results were examined and discussed within each curling variable, to determine trends and commonalities. Barriers and gaps were identified within the literature to suggest future areas of study. Consensus between all three authors regarding the key items of information generated from the review was reached.
In addition to the scoping review methodological framework proposed by Arksey and O'Malley (5), we followed the PRISMA Extension for Scoping Reviews (PRISMA-ScR) checklist (7). No risk of bias assessment, summary measures, or additional analyses were conducted in this scoping review in accordance with the PRISMA-ScR (7). No formal review protocol exists.
Results
The initial search from the electronic databases using Harzing's Publish or Perish software yielded 1,367 results (PubMed: 167, Scopus: 200, Google Scholar: 1,000) (Figure 1). The thorough searches, using eight predetermined search terms, that followed the initial search, yielded 7,100 results (PubMed: 62, SPORTDiscus: 97, Google Scholar: 6,941, Scopus: 0). Therefore, a total of 8,467 results were retrieved through database searches. These records were screened to eliminate studies lacking relevance to the sport of curling, narrowing the results to 743. Duplicates were then filtered out leaving 227 records. The reference lists were screened for additional, relevant studies. Thirty-seven studies were added from reference searches to the existing 227, leaving 264 studies remaining. We obtained full-text access to 233 of these and after the initial screening of titles and abstracts 103 fit the inclusion protocol and remained. An additional nine articles were excluded after full-text assessment due to not fitting inclusion criteria (iv). Therefore, a total of 94 articles were included in the final data extraction, quality appraisal, and review in order to evaluate the quantitative variables in curling.
Figure 1. PRISMA 2020 flow diagram: overview of the study identification and selection process.
Study characteristics
Geographical location: when analyzing the geographic scope of the studies, two world regions accounted for a large sum (Figure 2). Forty-three of the ninety-four included studies (46%) have an origin in North America, with 36 of these studies emerging from Canada alone. A bias toward English speaking countries is possible due to one of the study inclusion criteria specifying that articles were to be written in English. Another possible bias is that curling is a sport that requires an indoor ice facility that may be cost prohibitive in some regions of the world. East Asia contributed 32% (30/94) of the studies respectively. Within this region, the studies are divided among three major countries, with Japan leading at 18, and then Korea and China close behind with eight and four. Up to nine European countries are also represented in the list of included studies ranging across the Nordic, Southern, and Western parts, which make up 16% (15/94). The remaining 6% (6/94) of studies are combinations of multiple world regions such as Korea and Germany collaborating or Canada collaborating with a variety of countries (Sweden, Scotland, Netherlands, or the United States of America).
Figure 2. Number of included studies by geographical location.
Decades of Publication: There has been a substantial increase in the number of articles published on the sport of curling in recent decades (Figure 3). The sport of curling was recognized as an Olympic sport in 1998 and the sport of Wheelchair curling as a Paralympic sport in 2002 (1). In 2007 the sport grew in popularity across Asia with the first World Women's Curling Championship taking place in Aomori, Japan (1). Among the included studies, 60% (n = 56) fell between 2011 and 2020, more than doubling the 23% (n = 22) of studies published between 2001 and 2010. From the months of January until July of 2021, an additional six studies (6%) had already been published. Conversely, only 9 (10%) studies were published between 1970 and 2000, and only one included study (1%) was published before 1970, in 1924.
Figure 3. Number of included studies by decade (1921–2021). The publications in 2021 only include search's since June 1 of 2021.
Themes
Through the outcomes assessed in the literature, multiple themes emerged. These themes were identified and categorized by one researcher with curling expertise and studies were grouped into 10 categories inspired by different domains in the sport of curling. Most studies evaluated one specific theme within the sport while acknowledging others to a lesser degree, however, some overlap of themes emerged in studies. Table 1 groups all studies by theme, variable, citation, and geographical region.
Table 1. Summary of all themes, the variable(s) assessed in each theme, and the studies that assessed the variable(s).
From the included literature: (1) the curl mechanism of the curling stone; (2) the impact of sweeping; (3) curling delivery biomechanics; (4) wheelchair curling; (5) technology and tools; (6) psychological; and (7) strategic variables, all occupied the primary purpose of the greatest number of studies. Other pertinent topics included: (8) injury analysis: (9) curling facility infrastructure; and (10) assessment of curling training, which were the secondary focus of some studies and integrated into studies with another primary focus.
Curl mechanism/physics of rock displacement
Twenty-seven studies addressed the curl phenomenon of the granite stone on a pebbled ice surface. The main focus of these studies was to comprehend the physics-based behavior of a curling rock via theoretical mechanisms and their mathematical models.
Numerous physical theories were introduced as mechanisms responsible for the observed curl of a curling rock. Six of these studies assessed lateral displacement of the stone according to asymmetrical models, based on the front-back and left-right asymmetrical distribution of friction force acting on the sliding stone (2, 74, 75, 81, 97, 98). Several additional studies discussed adjacent models, sharing the same front-back asymmetrical mechanism to explain lateral curl: (i) the “evaporation abrasion model”, which considers the evaporation of pebbles as responsible for the lower friction coefficient at the front of the running band (Figure 4) (86, 92, 96); (ii) the “snowplow model”, which explains curl according to the effect of ice fragments and debris on reducing the friction coefficient (81, 92); (iii) the “pressure difference model”; the only model with statistical evidence supporting its unreliability (92, 94, 95). Further front-back asymmetrical models include the “water layer model”, in which a thin water film produced by friction heat is dragged around by the rotation of the stone, lowering the coefficient of friction of the front running band (76–78, 91–93). Four studies described the “scratch-guide model”; this theoretical framework focuses on the lateral displacement of subsequent stones as proportional to the angle of cross-scratches produced by the leading and trailing running bands of preceding stones (73, 75, 89, 90). Several studies introduced the “pivot-slide model” which describes lateral displacement as a sequence of pivots about individual ice pebbles followed by slides (79, 85, 88). Finally, two studies evaluated “split friction/granular models”, describing factors of mixed lubrication (76, 87).
Figure 4. Curling stone features: front view, bottom-up view, top-down view.
Numerical models used to describe and validate the above theories were considered across studies (91, 92). Mathematical equations were presented to describe and predict: (1) the dynamic motion and trajectory of a curling stone (73, 82–86); (2) the relationship between the linear and angular velocity of the thrown stone (81); (3) the longitudinal and rotational deceleration of a stone (80); (4) the stone's kinetic energy (79); (5) the translational and rotational stone speeds (77, 78); (6) the torque due to dry and wet friction (76); (7) friction coefficients and the function of forces acting on the thrown stone (71, 74, 75, 97); (8) the surface profiles and cross-scratches of ice sheets (72, 73); and (9) thermodynamic analysis of ice friction when considering the interaction between individual ice pebbles and the stone running band (71). Two prominent mathematical analyses performed were: (1) numeric integration (74, 88), and (2) numeric differentiation (93, 96).
The common factor that all models try to account for is the coefficient of friction. Maeno (92) covers five different models that discuss the “front-back asymmetry” of frictional force in her review. Maeno does not discuss the “left-right asymmetry model” (98). Since Maeno's review, two new models were proposed bringing the total to eight. The five in Maeno's (92) review are the “Pressure Difference Model”, the “Water Layer Model”, the “Snowplow Model”, the “Evaporation Abrasion Model”, and the “Scratch Guide Model”. In order of novelty, the two newly proposed models are the “Pivot-Slide Model” (Shegelski, & Lozowski (79) and the “Split Friction Model with mixed lubrication” by Ziegler (87).
Impact of sweeping on the curl mechanism
Twelve studies solely explored the impact of sweeping in curling. Among these studies, variables of interest included: (1) muscle activity and force output alone and in tandem while performing the action (4); (2) stroke rate comparison between genders (4, 62); (3) rates of change in stone displacement according to sweeping (4, 70); (4) the effects of broom acceleration vs. force production on stone trajectory and heat transfer (2, 70); (5) the development of instruments to gauge quantitative sweeping effects (64, 66, 67); (7) observing the topography and thermodynamics of ice surface when comparing different broom head material (61, 65, 68); and (8) assessing different cases of sweeping (e.g., the ideal time to initiate sweeping) (69).
Two conditional theories of sweeping were assessed across studies: (1) the thermomechanical theory, outlining variables of the velocity of sweeping stroke, the downward force applied, and the pattern that is swept as having an effect on the coefficient of friction (64, 65, 68, 69); (2) the scratch mechanism of sweeping, measuring ice topography effects of sweeping; evaluating the brush head's effect on the ice surface, as well as the varying depth of scratches and the directional manipulation of the stone's trajectory (61).
Four of these studies reported using a sweep ergometer to collect force measurement and acceleration data along two axes while sweeping (64–67). Others used devices such as an inertial measurement unit (IMU) sensor attached to a broom, to measure kinematics and frequency of the sweeping activity as well as mechanical movements of a curling stone (4, 63), electromyography for muscle activity (4), cameras to collect visual data (62), and a non-contact optical profiler as well as an optical microscope to evaluate surface profiles of the ice after brush head contact (61).
Curling delivery mechanics
Curling delivery mechanics were the main topic of eight studies (12, 54–60). Delivery variables of flexibility, balance, and core strength were assessed in two studies (57, 58). This analysis occurred via an optotrak certus device (Northern Digital Instruments, Waterloo, ON) and a Curling-Specific Balance Test. Biomechanical force analysis was compared between flat-foot and toe sliding with toe sliding producing a larger moment arm than flat-foot sliding (12). Three of these studies assessed delivery variables according to movement phases (54, 55, 60). Phases of the slide (i.e., setup, pull-back, release, and after release) were compared in terms of attentional demands, kinematic correlations between trunk, hip, and knee movement, and directional accuracy of delivery.
Two studies considered force generation and weight control by (1) collecting data to understand the conversion of the timing of rock translation across different segments of the sheet into kick speed generated during delivery (56); (2) methods of force generation throughout the delivery includingincreased potential energy through a backswing, increased push-off from the stance leg in the hack, and earlier rock release to generate greater stone velocity (59). Comparison between elite and sub-elite curlers occurred in four studies regarding the execution and efficiency in delivery kinematics (58), movement qualities (i.e., flexibility and balance) (57, 58), timing intervals to estimate kick speed for delivery (56), and attentional demands (55). Flexibility and hip movement using hip goniometer measurements were compared across genders (54).
Wheelchair curling
Among the studies that investigated wheelchair curling, 50% of them assessed kinematic trajectories. These studies measured a biomechanical model of the curling delivery to quantify angular joint velocities and range of motion through the curling delivery in relation to the dynamics of stone translation (50–52). Trunk and motor control stability of the curling wheelchair athlete was assessed within four studies (50–53); this analysis concluded wheelchair curling as a beneficial method of rehabilitation for spinal cord injury (SCI) patients (53). Musculoskeletal modeling and body composition measurements effecting stone release, using dual-energy x-ray absorptiometry, were complimentary factors assessed in two studies (50, 51). The findings discuss how the distribution of fat mass in SCI athletes may be an advantage for trunk control through stone delivery and how body segment parameters influence the mass moment of inertia (50). Only one study analyzed the effects of psychological skill training on the performance of a national wheelchair team (20). A twelve-week individualized psychological skill training program was developed for each athlete. The program was informed and evaluated by in-depth interviews, numerous questionnaires (Psychological Skill Questionnaire in Sports, Questionnaire for Players' Self-Management, Korean Version of the Test of Performance Strategies, Profile of Mood States, Competitive State Anxiety Inventory [CSAI-2], and Questionnaire to Assess the Perception of Psychological Skill Training), the change in the performance outcome of the Wheelchair curling game, and EEG Inter-Hemispheric Asymmetry Index analysis. Positive psychological elements and increased competitiveness were found with improved in-game performance.
Integrated technology and artificial intelligence in curling
Twenty-one studies evaluated technological/artificially intelligent devices developed and implemented within the sport of curling. Thirty-eight percent (n = 8) of these studied the design and implementation of robotic machines across multifaceted aspects of curling (35, 39, 41, 44–49). Of the artificially intelligent (AI) curling robots, fabricated features included throwing controls to test precision and throwing accuracy, AI-based strategy simulators, vision technology to recognize the curling field and stone configuration/trajectory, and sweeping systems to deliver path planning strategies for sweeping (35, 47–49). Artificial agents were equipped with autonomous driving and friction feedback for traction control (45, 47). Of the studies that orchestrated curling matches, AI machines established a winning record while outperforming human counterparts (35, 45, 46). Other devices monitored musculoskeletal analysis of upper body kinematics and release velocity (44), as well as a digital curling system, used as a framework to compare curling strategies (33). Artificial infrastructure from four studies was evaluated with respect to their ability to monitor real-time position measurements and trajectory behavior of the curling stone, including an infrared camera (42), a prototype of a curling stone launcher (41), smart glasses (40), and a kernelized correlation filter tracker (39).
Statistical analysis and prediction of strategic curling outcomes were measured via AI algorithms in eleven studies. Three studies developed curling informatics via a digital scorebook system, intelligent Curling Elicitator (iCE) (Kitami Institute of Technology, Kitami, Japan) (31, 32, 38). Three studies focused on the neural networking of curling strategy from continuous action spaces using Monte Carlo Tree Search and kernel regression algorithms (23, 36, 37). Three of the studies implemented a deep reinforcement learning framework (22, 35, 36). Two studies evaluated continuous action spaces via the Markov process (33, 34). Single studies implemented game-tree searches of optimal shot selection via jiritsu-kun programming (22), and a server system “digital curling” to calculate turn-based curling strategy (43).
Strategic/tactical factors
Eleven studies considered strategic/tactical factors of the sport based on the notion of its cruciality to achieving winning outcomes. Four studies evaluated game information using the sequentially mentioned AI program iCE; a portable digital scorebook system within the novel field of curling informatics that effectively analyzes curling tactics and strategies in order to establish correlations between differences in shot accuracies and game scores (29–32).
Five studies assessed “hammer” scenarios to provide insight into tactical decisions. The importance of the “hammer” on game outcomes was considered by (1) modeling the “hammer” shot as a low-dimensional optimization problem with a continuous action space using Delaunay triangulation and sampling algorithms (26, 28); (2) applying binary logistic regression to statistics on possession of first stone or last stone per end (27); (3) appraising scenarios of being one up with the “hammer” vs. one down without, and whether to blank or take a single point (24, 25). Two studies evaluated the uncertainty of curling strategy via digital curling; AI-based programs including neural fictitious self-play (NFSP) methods (23), Kernel Regression-UCT (23), and jiritsu-kun (22) were acquired to propose strategic learning methods from expected scores distribution at the completion of ends through neural network models (22, 23).
Psychological aspects of curling
Seven studies focused on psychological determinants and results within the sport of curling. Psychological skill training of curling (wheelchair) athletes dominated 71% (n = 5) of these studies (17–21). Across the curling and wheelchair curling demographic, psychological variables of perfectionism, communication, pressure, self-management, anxiety, arousal, and interpersonal relationships were studied according to their impact on game performance (18–21). Implemented training techniques to optimize psychological state included routine training, attentional focus training, writing practice training, relation training, self-control training, positive self-talk training, and general imagery interventions, as methods of improving shot-making ability and game strategy (17, 20).
Two studies addressed psychological performance regarding other demographics (i.e., older adults and coaches) (15, 16). Both studies generated a regression model in their analysis. The psychological context within curling was evaluated using psychological skills training as a variable of coaching behavior and beliefs (15). This curling context also was assessed as a tool/leisure activity to improve older adults' psychophysical properties of functionality, balance confidence, and perceptions of aging (16). Across all seven studies, questionnaires were the most frequent form of data collection, occurring in 100% of studies (15–21). Kim and colleagues (21) utilized the Group Cohesion Questionnaire [GCQ; (99)], the Group Efficacy Questionnaire [GEQ; (100)], and the Effective Communication Questionnaire [SETECTS-2; (101)] to assess teambuilding. Kim and colleagues (20) evaluated psychological skills via the Psychological Skill Questionnaire in Sports [PSQS; (102)], the Questionnaire for Players' Self [QSF-M; (103)], the Korean Version of the Test of Performance Strategies [TOPS; (104)] the Profile of Mood States (POMS), Competitive State Anxiety Inventory (CSAI-2), and a Questionnaire to Assess the Perception of Psychological Skill Training (QAPPSK). Lizmore (19) investigated perfectionism with an abbreviated and modified version of the Sport-Multidimensional Perfectionism Scale-2 [Sport-MPS-2; (105)], and reactions to mistakes with the Sport Emotion and Cognition Questionnaire (SECQ). Paquette (15) used a revised version of the Sport-Psychology Attitudes-Revised Coaches Questionnaire [SPA-RCQ; (106)], a revised version of the Mental Skills Questionnaire [MSQ; (107)], the Coaching Competence Scale [CCS; (108)], and the Sport-Confidence Inventory [SCI; (109)]. Pezer and Brown (18) investigated personality traits by using the Will To Win Questionnaire [WTWQ; (110)]. Stewart investigated imagery ability, use, and assessment with the Movement Imagery Questionnaire-Revised [MIQ-R; (111)], and the Sport Imagery Questionnaire [SIQ; (112)]. Stone and colleagues (16) assessed perceptions of aging with the Attitude Towards Own Aging Sub-Scale [ATOA; (113)], and the Stigma Consciousness Questionnaire [SCQ; (114, 115)].
Injury analysis
Two studies solely addressed curling-related injuries placing this subtopic as a secondary finding (13, 14). Both acquired a reportive methodology to assess information on the demographics, site of injury, type of injury, and curling-specific aggravated conditions. A supplemental article (cross-referenced from delivery mechanics) addressed injury in terms of biomechanical delivery measurements according to force vector analysis of delivery positions (12). Studies concluded that curling is a safe winter sport compared to its Winter Olympic sports counterparts (13, 14).
Curling arena infrastructure
Another secondary finding was the subtopic of “Curling arena infrastructure” which contained two studies that discussed the construction and transformation of non-curling fields into curling ice rinks (10, 11). A novel ice arena and the National Aquatics Center located in China were venues prefabricated into curling arenas with curling ice installation (10, 11). These venues were analyzed to determine how the requirements of the curling ice and air differ from those of other arenas as well as traditional curling rinks (11). They reviewed the procedures and tests applicable to the design and operation of ice competition surfaces. Factors considered include the refrigeration load, graded static load, dynamic tests, vertical and horizontal deformation characteristics, and analytical frequency of buildings as a method of determining the infrastructure's effects on the playing surface and the development of a novel curling ice rink using detachable and prefabricated structures (10, 11).
Assessment of curling training and ability
The final secondary finding subtopic evaluated curling ability and training tactics. Two studies were assessed (8, 9). The primary assessment of curling ability was on-ice technical, strategic, and shot-making skills (8, 9). This constituted proficiency in accurately delivering the stone to the target, proficiency in producing desired shot outcomes for various types of shots, and a multiple-choice strategy test (8, 9). Secondary assessment of curling ability was determined via off-ice athletic ability by measuring curlers' muscular endurance, trunk strength, aerobic capacity, and flexibility, correlating the physiological tests to on-ice performance (8). Studies published prior to the completion of the literature search, had not made any consideration of gender differences within the sport of curling with the exception of sweeping and delivery mechanics (4, 62, 64).
Discussion
This is the first scoping review aimed at defining and evaluating the quantitative knowledge that exists in the sport of curling. It was conducted through standard methods outlined by Arksey and O'Malley (5) to identify, select, and synthesize the findings from 94 studies. The current knowledge of the sport was documented by analyzing the geographic scope of studies, year of publication, and by the specific subdivisions of themes that make up the sport. Provided below are important results of this review that can be relevant for future researchers, coaches, and curling athletes.
The results from the included quantitative studies revealed substantial evidence of the controversy that exists in the curl mechanisms of the curling stone. To date, no unanimous theory exists to explain the lateral displacement of the curling stone (72, 75). Various physical models present conflicting proposals including: (1) the “front-back” and “right-left asymmetrical models” (2, 74, 75, 81, 97, 98); (2) the “evaporation-abrasion model” (86, 92, 96); (3) the “snowplow model” (81, 92); (4) the “pressure difference model” (92); (5) the “scratch-guide model” (73, 75, 89, 90); (6) the “pivot-slide model” (79, 85, 88); (7) the “split friction model” (87); and (8) the “water layer model” (76–78, 91–93). There is also a large variation in the different mathematical equations used in analysis across studies, as currently no numerical model of curling stone dynamics can satisfactorily predict all observed stone translations (80). Further controversy remains on the influence of the stone running band (72), speed of rotation (76, 87), and pebbled ice surface on the lateral displacement. Many studies have considered this domain of the sport, but few have observed the mechanisms experimentally or been able to provide concrete data. More research is needed in this area to develop statistical and relevant data for curlers, physicists, and ice makers to broaden comprehension of stone trajectories.
In addition, controversy still remains regarding the mechanisms of sweeping. Some studies support the thermodynamic theory, proposing that increased ice surface temperature produced through a combination of force and stroke speed lowers the coefficient of friction between the stone and ice (65, 68). Others support the scratch mechanism of sweeping, proposing that the combination of sweeping force and sweeping rate manipulates rock trajectory through the production of topographic scratches as opposed to surface heat (61). More research is needed to determine what influence each theory contributes to manipulating the longitudinal and lateral trajectory of the rock down the sheet of ice.
Technology is becoming a substantial factor in curling and its training tactics. The integration of AI agents and devices into curling formed its own theme in the results section, as the second most common focus. Across all variables of curling, AI programming has been most developed in terms of fabricating agents to learn and play the game, developing devices to enhance on-ice technical training of athletes, as well as for efficiency in statistical analysis and prediction of strategic curling outcomes (22, 23, 31–38, 43). Many studies with a focus on tactics and AI introduced computer algorithms into the continuous action spaces as a method of improving shot selection in curling. Technological devices were also present across sweeping studies, used to track force and acceleration measurements of the sweep stroke (64–67), as well as muscle activity of sweepers (4), and ice profiles after sweeping (61). Delivery mechanics literature further introduced technological devices. Online programs were utilized in terms of measuring kinematic motion (58), pressure and force vectors (12), as well as the stone position relative to the line of delivery (60). From the findings that robotic agents can outperform human curlers in game scenarios, we can accurately store digital curling informatics, and can greatly enhance accuracy in the training and testing of elite-level curlers. It appears that AI devices are an important factor in progressing the game and should continue to be developed, tested, and implemented in more areas specific to the sport of curling. Future directions in technological curling research are endless and should further investigate quantitative motions of the players and the stone according to specific game states by developing more adaptable IMU sensors. Another future direction is to develop instrumented “hacks” with built-in force plates that automatically generate feedback on the force produced. The “hack” is what curlers kick off of with their feet to begin sliding down the ice. This technological advancement could be used as a method of training memory in which curlers can learn kick speed and engagement of leg muscles in their takeoff of delivery for varying called weights.
Another important aspect observed from our review is the comparison across gender over the multifactorial variables of the game. Differences across gender were considered in terms of sweeping and delivery mechanics. Men and women were compared with respect to muscle activity and force output when sweeping, as well as their sweeping effect on the lateral and longitudinal trajectory of the stone (4, 62, 64). Studies across the variable of sweeping concluded that both genders produce similar muscle activation patterns when sweeping and that men have a more significant sweeping impact, carrying the rock a further distance and extending the stone's deceleration (4, 62). Differences in delivery mechanics between men and women were also of concern to some studies. The main finding established that women have greater hip flexibility and extension in a slide than their male counterparts (54). Gender comparisons failed to be considered in the evaluation of on-ice strategy calls, precision in shot-making ability, and psychological responses during gameplay. Future studies should consider expanding the differences according to gender in these game variables in order to develop a more comprehensive understanding of the difference between men's and women's play.
Substantial evidence of the differences between elite and sub-elite curling athletes was common across some themes. This comparison was most prevalent in studies regarding delivery biomechanics, in which elite and sub-elite curlers were contrasted in terms of core strength, flexibility, and balance with elite curlers outperforming their sub-elite counterparts (57). Comparisons also occurred for the center of mass, plantar pressure, and joint angles of elite and sub-elite curling deliveries (12). Timing methods used to estimate rock displacement were established to be reliable for elite athletes to vary stone delivery velocity, but not for sub-elite (56). Finally, skill level was compared according to attentional demands between sub-elite and elite curlers, showing that reaction time is distributed similarly across all skill levels, with elite-level curlers producing a slower delivery time overall (55). Comparison between skill levels was also assessed in sweeping; comparing force applied vertically, with elite athletes outperforming sub-elite (67).
There was a substantial difference in the magnitude of studies composed on the traditional format of curling as opposed to wheelchair curling. Wheelchair curling was only considered a subset of the sport, occupying six of the ninety-two included studies. Wheelchair studies primarily covered topics of the biomechanics of stone delivery (51, 52, 116), body composition of wheelchair curling athletes (50), and psychological skill training (20). It would be important to expand wheelchair curling knowledge to other areas of the game (ex, strategy variations from the traditional format), in order to optimize athlete development and performance by understanding variables specific to this format.
Although many aspects of sweeping were assessed through the literature, there is a dearth of current research assessing widely debated sweeping strategies. Corner sweeping, snow plowing, backward sweeping, and horizontal vs. vertical broom head stroke angles (Table 2) are all hotly debated concepts within the current curling world and clarification of their impact on rock trajectory needs to emerge via research.
Table 2. Newly debated sweeping techniques.
Future research
We feel that each variable discussed has relevance to curling athletes and/or future curling studies. There is undeniable value in understanding the physical mechanisms responsible for the generation of curl in a thrown stone; this game variable is prioritized as both a foundation of knowledge for the sport and a scientific variable of scholarly interest. Continued research may lead to new breakthroughs and continued advancement in how curling is conducted. There is also value in placing more emphasis on adaptable variables (e.g., technique, equipment, the focus of attention, rotation, etc.). Knowledge of game variables that an athlete has control over will be impactful to improving curling performance. Therefore, we believe future attention should be directed toward applied aspects of the game while continuing to seek concrete evidence for the underlying mechanisms.
It is notable that investigations of the mixed-doubles format of curling are absent from the extant literature. This novel format of curling was introduced in the Olympic Games in 2018 (117), was absent from all collected literature. With the variations in the rules, strategy, the number of players, gender, and length of the game, this format of curling requires attention in the research domain in order to develop a statistical understanding of its unique quantitative variables.
Strengths and limitations of this scoping review
This review applied a systematic and rigorous search strategy that retrieved many articles to answer the research question. Each sub-factor in the sport of curling was searched with eight key search terms established in order to capture the depth of curling literature. However, due to limited access to study retrieval by the head researcher, some studies were unintentionally omitted and labeled as missing. In producing the review, both published journal articles and also grey literature (i.e., published thesis' and/or conference presentations) were considered. The consideration of grey literature, which met inclusion criteria, prevented the restriction of findings and served as a method of including all cases relevant to this sport. Further, the inclusion of thesis dissertations were a reliable source for collecting older variations of published articles that otherwise were unobtainable due to access restrictions. Several other relevant published studies written in other languages were omitted based on criteria precluding all but English; thus, it is important to point out that this may skew the geographic analysis of studies in favor of North America and Europe and limit accumulated global knowledge.
Conclusion
This study sought to review the literature on the quantitative variables present in the sport of curling. It answers our research question and illustrates the current knowledge that exists in the sport for each devised variable, providing openings for future research. This review will aid in building a more comprehensive understanding of the game mechanisms, as well as add significantly to the understanding of the modern game techniques being applied to optimize athletes' gameplay. There is an influx of research being generated within the scope of curling in the most recent years, with research being conducted globally. The current body of literature reviewed reveals varying mechanisms underlying the curl trajectory of the stone and optimal dynamics of sweeping. The varying proposed explanations of the included studies are proof that more rigorous studies are needed to demonstrate the complex physics of the game. This review provides an impetus for further assessment on the variables of curling delivery biomechanics, wheelchair curling, psychological and strategic variables, and technology and tools. Studies included in this scoping review only scratched the surface of these variables and their impact on game performance.
Author contributions
EZ: Conceptualization, Data curation, Formal Analysis, Investigation, Methodology, Project administration, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing, Software. NR: Data curation, Formal Analysis, Investigation, Methodology, Resources, Validation, Visualization, Writing – original draft, Writing – review & editing, Software. SP: Conceptualization, Formal Analysis, Investigation, Methodology, Resources, Supervision, Visualization, Writing – review & editing.
Funding
The author(s) declare that no financial support was received for the research, authorship, and/or publication of this article.
Acknowledgments
We would like to thank Morris Curling Club curling rink for access to their rink to facilitate photographing commonly debated sweeping techniques.
Conflict of interest
The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.
Publisher's note
All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article, or claim that may be made by its manufacturer, is not guaranteed or endorsed by the publisher.
References
1. Maxwell D. Canada Curls: The Illustrated History of Curling in Canada. North Vancouver, BC: Whitecap Books (2003).
2. Bradley JL. The sports science of curling: a practical review. J Sports Sci Med. (2009) 8(1):495–500.24149588
3. World Curling Federation. What is curling? (2020). Available online at: https://worldcurling.org/about/curling/ (accessed May 4, 2022).
4. Kim TW, Lee SC, Kil SK, Choi SH, Song YG. A case study on curling stone and sweeping effect according to sweeping conditions. Int J Environ Res Public Health. (2021) 18(1):833. doi: 10.3390/ijerph18020833
5. Arksey H, O'Malley O. Scoping studies: towards a methodological framework. Int J Soc Res Methodol. (2005) 8(1):19–32. doi: 10.1080/1364557032000119616
6. Harzing AW. Publish or Perish (8.2.3944) [Computer Software]. Tarma Software Research Ltd., Windows GUI Edition (2007). Available online at: http://www.harzing.com/pop.htm
7. Tricco AC, Lillie E, Zarin W, O’Brien KK, Colquhoun H, Levac D, et al. PRISMA extension for scoping reviews (PRISMA-ScR): checklist and explanation. Ann Intern Med. (2018) 169(7):467–73. doi: 10.7326/M18-0850
8. Kivi D, Auld T, Leon-Carlyle C, Witluk D. Physical and Physiological Assessment of Competitive Junior Curlers. Thunder Bay, ON: Noca (2013). Available online at: https://curlnoca.ca/wp-content/uploads/2013/06/Curling-Fitness-Assessment-Study.pdf
9. McNeil MA. Measurement of curling ability through a knowledge and skills test (Master’s thesis). McGill University (1975). eScholarship.
10. Zhang W, Li J, Yang Q, Mu L. Practical application of a novel prefabricated curling ice rink supported by steel-concrete composite floors: in situ measurements of static and dynamic response. Structures. (2021) 32(1):1888–906. doi: 10.1016/j.istruc.2021.04.011
11. Li L, Lin W, Zhang T, Liu X. On-site measurement of thermal environment and heat transfer analysis in a curling arena. J Build Eng. (2021) 34(1):101691. doi: 10.1016/j.jobe.2020.101691
12. Robertson I, Arnold GP, Wang W, Drew TS, Nasir S, MacDonald C, et al. A pilot biomechanical assessment of curling deliveries: is toe sliding more likely to cause knee injury than flatfoot sliding? BMJ Open Sport Exerc Med. (2017) 3(1):1–8. doi: 10.1136/bmjsem-2017-000221
13. Reeser JC, Berg RL. Self reported injury patterns among competitive curlers in the United States: a preliminary investigation into the epidemiology of curling injuries. J Sports Med. (2004) 38(29):E29. doi: 10.1136/bjsm.2003.010298
14. Berry JW, Romanick MA, Koerber SM. Injury type and incidence among elite level curlers during world championship competition. Res Sports Med. (2013) 21(2):159–63. doi: 10.1080/15438627.2012.757229
15. Paquette KJ. Canadian Curling coaches’ use of psychological skills training (Master’s thesis). Brock University (2009). Brock University Open Repository.
16. Stone RC, Rakhamilova Z, Gage WH, Baker J. Curling for confidence: psychophysical benefits of curling for older adults. J Aging Phys Act. (2018) 26(1):267–75. doi: 10.1123/japa.2016-0279
17. Stewart NW. The effects of cognitive general imagery use on tactical decision-making in curling (Doctoral thesis). University of Western Ontario (2016). Electronic Thesis and Dissertation Repository. Available online at: https://ir.lib.uwo.ca/etd/3863
18. Pezer V, Brown M. Some psychological determinants of curling performance. Percept Mot Skills. (1982) 55(1):1115–27. doi: 10.2466/pms.1982.55.3f.1115
19. Lizmore MR. Perfectionism and reactions to mistakes in competitive curling (Master’s thesis). University of Alberta (2013). Education Research Archive.
20. Kim SW, Choi SL, Kim HC. Development and practical application of a psychological skill training program for national wheelchair curling players. J Korea Converg Soc. (2019) 10(3):275–90. doi: 10.15207/JKCS.2019.10.3.275
21. Kim Y, Park S, Kim T. The development of a team building program for Korean curling team. Int J Appl Sports Sci. (2017) 29(2):155–68. doi: 10.24985/ijass.2017.29.2.155
22. Yamamoto M, Kato S, Iizuka H. Learning of expected scores distribution for positions of digital curling. Workshop on Curling Informatics (2018).
23. Han Y, Zhou Q, Duan F. A game strategy model in the digital curling system based on NFSP. Complex Intell Syst. (2021) 8(3):1857–63. doi: 10.1007/s40747-021-00345-6
24. Willoughby KA, Kostuk KJ. An analysis of a strategic decision in the sport of curling. Decis Anal. (2005) 2(1):58–63. doi: 10.1287/deca.1050.0032
25. Willoughby KA, Kostuk KJ. Preferred scenarios in the sport of curling. Interfaces (Providence). (2004) 34(2):117–22. doi: 10.1287/inte.1030.0049
26. Ahmad ZF, Holte RC, Bowling M. Action selection for hammer shots in curling. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (2016).
27. Park SG, Lee S. Curling analysis based on the possession of the last stone per end. Procedia Eng. (2013) 60(1):391–6. doi: 10.1016/j.proeng.2013.07.028
28. Ahmad ZF. Action selection for hammer shots in curling: optimization of non-convex continuous actions with stochastic action outcomes (Master’s thesis). University of Alberta (2017). Education and Research Archive.
29. Otani H, Masui F, Yanagi H, Ptaszynski M. Advances in curling game information analysis by considering starting position. Proceedings of the 5th International Congress on Sport Sciences Research and Technology Support (2017). p. 89–95. doi: 10.5220/0006498800890095
30. Otani H, Masui F, Hirata K, Yanagi H, Ptaszynski M. Analysis of curling team strategy and tactics using curling informatics. Proceedings of the 4th International Congress on Sport Sciences Research and Technology Support (2016). p. 182–7. doi: 10.5220/0006044601820187
31. Masui F, Otani H, Yanagi H, Ptaszynski M. Study on game information analysis for support to tactics and strategies in curling. Ic Sports 2016/2017. (2019) 975(1):128–49. doi: 10.1007/978-3-030-14526-2_9
32. Masui F, Hirata K, Otani H, Yanagi H, Praszynski M. Informatics to support tactics and strategies in curling. Int. J. Autom Technol. (2016) 10(2):244–52. doi: 10.20965/ijat.2016.p0244
33. Ohti K, Tanaka T. A curling agent based on the monte-carlo tree search considering the similarity of the best action among similar states. Adv Comput Games. (2017) 10664(1):151–64. doi: 10.1007/978-3-319-71649-7_13
34. Kostuk KJ, Willoughby KA, Saedt APH. Modelling curling as a markov process. Eur J Oper Res. (2001) 133(1):557–65. doi: 10.1016/S0377-2217(00)00202-2
35. Won D-O, Müller K-R, Lee S-W. An adaptive deep reinforcement learning framework enables curling robots with human-like performance in real-world conditions. Sci Robot. (2020) 5(46):1–14. doi: 10.1126/scirobotics.abb9764
36. Lee S, Park S, Kim T, Kil S. Development of speed/trajectory measurement system using smart glasses for beginning or unskilled curlers. J Sports Eng Technol. (2019) 233(1):145–59. doi: 10.1177/1754337118809864
37. Yee T, Lisy V, Bowling M. Monte carlo tree search in continuous action spaces with execution uncertainty. Proceedings of the Twenty-Fifth International Joint Conference on Artificial Intelligence (2016). p. 690–6
38. Masui F, Ueno H, Yanagi H, Ptaszynski M. Toward curling informatics—digital scorebook development and game information analysis. IEEE Conference on compUtational Intelligence and Games (2015). p. 481–8. doi: 10.1109/CIG.2015.7317911
39. Takahashi M, Yokozawa S, Mitsumine H, Mishina T, Matsuhisa Y, Muramatsu S. Visualization of stone trajectories in live curling broadcasts using online machine learning. Proceedings of the 25th ACM International Conference on Multimedia (2017). p. 1390–7
40. Lee K, Kim S, Choi J, Lee S. Deep reinforcement learning in continuous action spaces: a case study in the game of simulated curling. Proceedings of the 35th International Conference on Machine Learning (2018). Vol. 80(1), p. 2937–46
41. Ravanbod A. A machine design for launching curling stones and an initial evaluation of its efficiency (Doctoral thesis). University of Saskatchewan (2021). Harvest.
42. Takegawa Y. Proposal of a real-time position measurement system for curling stones. Workshop on Curling Informatics (2018).
43. Ito T, Kitasei Y. Proposal and implementation of “digital curling”. IEEE Conference on Computational Intelligence and Games (2015). p. 469–73. doi: 10.1109/CIG.2015.7317945
44. Tanaka Y, Matsushita K, Tsuji T, Imamura N. Human hand movements in skilled motor performance of a virtual curling task. International Conference on Complex Medical Engineering. IEEE (2007). p. 1338–43. doi: 10.1109/ICCME.2007.4381957
45. Choi JH, Song C, Kim K, Oh S. Development of stone throwing robot and high precision driving control for curling. IEEE International Conference on Intelligent Robots and Systems (2018). p. 2434–40. doi: 10.1109/IROS.2018.8594026
46. Aannevik F, Robertsen JE. Skippy: agents learning how to play curling (Master’s thesis). Norwegian University of Science and Technology (2009). NTNU Open. Available online at: http://urn.kb.se/resolve?urn=urn:nbn:no:ntnu:diva-9010
47. Won D-O, Kim B-D, Kim H-J, Eom T-S, Müller K-R, Lee S-W. Curly: an AI-based curling robot successfully competing in the Olympic discipline of curling. Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (2018). p. 5883–5
48. Kawamura T, Kamimura R, Suzuki S, Iizuka K. A study on the curling robot will match with human: result of one end game with one human. IEEE Conference on Computational Intelligence and Games (2015). p. 489–95. doi: 10.1109/CIG.2015.7317934
49. Gwon J, Kim H, Bae H, Lee S. Path planning of a sweeping robot based on path estimation of a curling stone using sensor fusion. Electronics (Basel). (2020) 9(3):457. doi: 10.3390/electronics9030457
50. Laschowski B, McPhee J. Quantifying body segment parameters using dual-energy x-ray absorptiometry: a paralympic wheelchair curler case report. Procedia Eng. (2016) 147(1):163–7. doi: 10.1016/j.proeng.2016.06.207
51. Laschowski B. Biomechanical modeling of paralympic wheelchair curling (Master’s thesis). University of Waterloo (2016). Waterloo’s Institutional Repository.
52. Laschowski B, Mehrabi N, McPhee J. Optimization-based motor control of a paralympic wheelchair athlete. Sports Eng. (2018) 21(3):207–15. doi: 10.1007/s12283-018-0265-2
53. Herzog T, Swanenburg J, Hupp M, Hager AGM. Effect of indoor wheelchair curling training on trunk control of person with chronic spinal cord injury: a randomised controlled trial. Spinal Cord Series and Cases. (2018) 4:26. doi: 10.1038/s41394-018-0057-8
54. Kraemer EF. Hip and knee positions during the curling delivery (Master’s thesis). University of Wisconsin-LA Crosse (2009). College of Science and Health.
55. Shank V, Lajoie Y. Attentional demands in the execution phase of curling. Int J Kinesiol Sports Sci. (2013) 1(1):1–8. doi: 10.7575/aiac.ijkss.v.1n.1p.1
56. Kivi D, Auld T. Temporal methods to estimate the displacement of a curling rock: comparison between competitive and recreational curlers. Conference: International Society of Biomechanics in Sports (2010).
57. Pojskic H, McGawley K, Gustafsson A, Behm DG. The reliability and validity of a novel sport-specific balance test to differentiate performance levels in elite curling players. J Sports Sci Med. (2020) 19(1):337–46.32390727
58. Bernier K, Segler E, Hessler E. Changes in the Fluidity of Coordination with Curling Experience. Retrieved from the University of Minnesota Digital Conservancy (2016). Available online at: https://hdl.handle.net/11299/193365 (accessed June 17, 2021).
59. Harms S. A motion analysis study describing the kinematics of the curling delivery (publication No. 194) (Master’s thesis). University of North Dakota (2000). Physical Therapy Scholarly Projects. Available online at: https://commons.und.edu/pt-grad/194
60. Kivi D, Auld T. Directional accuracy of the delivery in competitive curlers. 30th Annual Conference of Biomechanics in Sports (2012), Vol. 164(1), p. 350–3.
61. Balsdon M, Wood J. Comparing broom conditions in curling: measurements using ice topography. Proc AMIA Annu Fall Symp. (2020) 49(1):82. doi: 10.3390/proceedings2020049082
62. Kivi D, Auld T, Zerpa C. Sweep length vs sweep rate analysis in competitive male and female curlers. Conference: International Society of Biomechanics in Sports (2014). p. 606–9
63. Dzikowski B, Pachwicwicz M, Weremczuk J. Inertial measurements of curling stone movement. XV International Scientific Conference on Optoelectronic and Electronic Sensors (2018). doi: 10.1109/COE.2018.8435175
64. Yanagi H, Miyakoshi K, Fukuoka M, Yamamoto N. Development of curling brush for measuring force exerted during sweeping. 30th Annual Conference of Biomechanics in Sports (2012). Vol. 175(1), p. 354–6
65. Marmo BA, Farrow IS, Buckingham MP, Blackford JR. Frictional heat generated by sweeping in curling and its effect on ice friction. Proc. IMechE. (2006) 220(1):189–97. doi: 10.1243/14644207JMDA93
66. Buckingham M-P, Marmo BA, Blackford JR. Design and use of an instrumented curling brush. Proc Inst Mech Eng. (2005) 220(4):199–205. doi: 10.1243/14644207JMDA70
67. Buckingham M-P. Acquisition systems for in situ monitoring of athletes and equipment in curling and snowboarding (Doctoral thesis). University of Edinburgh (2006). Edinburgh Research Archive.
68. Yanagi H, Miyakoshi K, Yamamoto N. Force measurement of sweeping on ice in curling. J Sci Med Sport. (2013) 16(1):59–83. doi: 10.1016/j.jsams.2013.10.183
69. Lawson J, Rave M. Sweeping gestures: a control theory model for curling. Coll Math J. (2019) 51(2):132–40. doi: 10.1080/07468342.2020.1707044
70. Yanagi H, Miyakoshi K, Fukuoka M, Yamamoto N, Isaka T. Measurement of forces exerted during sweeping in curling. International Society of Biomechanics in Sports Conference (2008).
71. Lozowski E, Maw S, Kleiner B, Szilder K, Shegelski M, Musilek P, et al. Comparison of IMU measurements of curling stone dynamics with a numerical model. Proceedia Eng. (2016) 147(1):596–601. doi: 10.1016/j.proeng.2016.06.246
72. Kameda T, Shikano D, Harada Y, Yanagi S, Sado K. The importance of the surface roughness and running band area on the bottom of a stone for the curling phenomenon. Sci Rep. (2020) 10(20637):1–9. doi: 10.1038/s41598-020-76660-8
73. Honkanen V, Ovaska M, Alava MJ, Laurson L, Tuononem AJ. A surface topography analysis of the curling stone curl mechanism. Sci Rep. (2018) 8:8123. doi: 10.1038/s41598-018-26595-y
74. Penner AR. The physics of sliding cylinders and curling rocks. Am J Phys. (2001) 69(3):332–9. doi: 10.1119/1.1309519
75. Nyberg H, Alfredson S, Hogmark S, Jacobson S. The asymmetrical friction mechanism that puts the curl in the curling stone. Wear. (2013) 301(1–2):583–9. doi: 10.1016/j.wear.2013.01.051
76. Shegelski MRA, Niebergall R, Walton MA. The motion of a curling rock. Can J Phys. (1996) 74(1):663–70. doi: 10.1139/p96-095
77. Shegelski MRA, Reid M, Niebergall R. The motion of rotating cylinders sliding on pebbled ice. Can J Phys. (1999) 77(11):847–62. doi: 10.1139/p99-074
78. Shegelski MRA, Niebergall R. The motion of rapidly rotating curling rocks. Aust J Phys. (1999) 52(1):1025–938. doi: 10.1071/PH98064
79. Shegelski MRA, Lozowski E. Pivot-slide model of the motion of a curling rock. Can J Phys. (2016) 94(1):1305–9. doi: 10.1139/cjp-2016-0466
80. Lozowski EP, Szilder K, Maw S, Morris A, Poirier L, Kleiner B. Towards a first-principles model of curling ice friction and curling stone dynamics. Proceedings of the Twenty-Fifth International Ocean and Polar Engineering Conference (2015). p. 1730–8
81. Denny M. Curling rock dynamics: towards a realistic model. Can J Phys. (2002) 80(1):1005–14. doi: 10.1139/P02-072
82. Shegelski MRA. The motion of rapidly rotating cylinders sliding on smooth surfaces. Can J Phys. (2001) 79(1):841–6. doi: 10.1139/cjp-79-5-841
83. Shegelski MRA. Maximizing the lateral motion of a curling rock. Can J Phys. (2001) 79:1117–20. doi: 10.1139/cjp-79-8-1117
84. Shegelski MRA. The motion of a curling rock: analytical approach. Can J Phys. (2000) 78(9):857–64. doi: 10.1139/cjp-78-9-857
85. Shegelski MRA, Lozowski E. First principles pivot-slide model of the motion of a curling rock: qualitative and quantitative predictions. Cold Reg Sci Technol. (2018) 146(1):182–6. doi: 10.1016/j.coldregions.2017.10.021
86. Maeno N. Dynamics and curl ratio of a curling stone. J Sports Eng. (2014) 17(1):33–41. doi: 10.1007/s12283-013-0129-8
87. Ziegler M. The split friction model—introducing mixed lubrication to curling. Creative Commons Attribution 4.0 International License (2021). doi: 10.21203/rs.3.rs-367477/v1 (accessed June 16, 2021).
88. Mancini G, de Schoulepnikoff L. Improved pivot-slide model of the motion of a curling rock. Can J Phys. (2018) 97(12):1301–8. doi: 10.1139/cjp-2018-0356
89. Shegelski MRA, Lozowski E. Null effect of scratches made by curling rocks. J Sports Eng Technol. (2019) 233(3):1–5. doi: 10.1177/1754337118821575
90. Penner AR. A scratch-guide model for the motion of a curling rock. Tribol Lett. (2019) 67(35):1–13. doi: 10.1007/s11249-019-1144-0
91. Summers AE, Montgomery PJ. Investigation of the motion of a fixed rotating solid body over ice with a thin fluid interface. Adv Fluid Mech V. (2004) 45(1):247–56.
92. Maeno N. Assignments and progress of curling stone dynamics. J Sports Eng Technol. (2016) 237(2):1–6. doi: 10.1177/1754337116647241
93. Jensen ET, Shegelski RA. The motion of curling rocks: experimental investigation and semi-phenomenological description. Can J Phys. (2004) 82(10):791–809. doi: 10.1139/P04-020
95. Harrington EL. An experimental study of the motion of curling stones. Proc Trans Can. (1924) 3(18):247–59.
96. Maeno N. Curl mechanism of a curling stone on ice pebbles. Bull Glaciol Res. (2010) 28(1):1–6. doi: 10.5331/bgr.28.1
97. Nyberg H, Jacobson S, Hogmark S. Calculated trajectories of curling stones sliding under asymmetrical friction: validation of published models. Tribol Lett. (2013) 50(3):379–85. doi: 10.1007/s11249-013-0135-9
99. Lee HG, Kim BH. Development of group cohesion test for sports teams (II). J Sport Sci. (1995) 6:15–26.
100. Short SE, Sullivan P, Feltz DL. Development and preliminary validation of the collective efficacy questionnaire for sport. Meas Phys Educ Exerc Sci. (2005) 9:181–202. doi: 10.1207/s15327841mpee0903_3
101. Sullivan PJ, Felts DL. The preliminary development of the scale for effective communication in team sports (SECTS). J Appl Sport Psychol. (2003) 33:1693–715.
102. Yoo J, Hur YH. Development and validation of the psychological skill questionnaire in sport. Korean J Phys Educ. (2002) 41(3):41–50.
103. Kim BJ. Measuring self-management practices in Korea athletes. Korean J Sport Sci. (2003) 14(4):125–40.
104. Kim BJ, Ho S. Preliminary validation of the Korean version of the test of performance strategies (TOPS): item development and factor structure. Korean J Meas Eval Phys Educ Sport Sci. (2002) 4(1):13–29.
105. Gotwals JK, Dunn JGH. A multi-method multi-analytic approach to establishing internal construct validity evidence: the sport multidimensional perfectionism scale 2. Meas Phys Educ Exerc Sci. (2009) 13:71–92. doi: 10.1080/1091367090281266
106. Zakrajsek R, Zizzi S. Factors influencing track and swimming coaches’ intentions to use sport psychology services. Athl Insight Online J Sport Psychol. (2007) 9(2):1–22. Available online at: https://researchrepository.wvu.edu/faculty_publications/2922
107. Bull SJ, Albinnson JG, Shambrook CJ. The mental game plan: getting psyched for sport. Cheltenham: Sports Dynamics (1996).
108. Myers ND, Vargas-Tonsing TM, Feltz DL. Coaching efficacay in intercollegiate coaches: sources, coaching behaviour, and team variables. Psychol Sport Exerc. (2005) 6:129–43. doi: 10.1016/j.psychsport.2003.10.007
109. Vealey RS. Mental skills training in sport. In: Tenenbaum G, Eklund RC, editors. Handbook of sport psychology. 3rd ed. Hoboken, NJ: John Wiley & Sons (2007). p. 287–309. doi: 10.1002/9781118270011.ch13
111. Hall CR, Martin KA. Measuring movement imagery abilities: a revision of the movement imagery questionnaire. J Mental Imagery. (1997) 21:143154.
112. Hall CR, Mack DE, Paivio A, Hausenblas HA. Imagery use by athletes: development of the sport imagery questionnaire. Int J Sport Psychol. (1998) 29:73–89.
113. Lawton MP. The Philadelphia geriatric center morale scale: a revision. J Gerontol. (1975) 30:85–9. doi: 10.1093/geronj/30.1.85
114. Hess TM, Hinson JT, Hodges EA. Moderators of and mechanisms underlying stereotype threat effects on older adults’ memory performance. Exp Aging Res. (2009) 35:153–77. doi: 10.1080/03610730802716413
115. Pinel EC. Stigma consciousness: the psychological legacy of social stereotypes. J Pers Soc Psychol. (1999) 76:114–28. doi: 10.1037/0022-3514.76.1.114
116. Laschowski B, Mehrabi N, McPhee J. Inverse dynamics modelling of paralympic wheelchair curling. J Appl Biomech. (2017) 33(4):294–9. doi: 10.1123/jab.2016-0143
117. Vieira S. Everything you need to know about the curling mixed doubles event at Beijing 2022. Olympics.com (2022). Available online at: https://olympics.com/en/news/everything-you-need-to-know-curling-mixed-doubles-event (retrieved May 16, 2022).
Keywords: sport of curling, wheelchair curling, curl mechanism, sport technology, quantitative measures, curling strategy
Citation: Zacharias E, Robak N and Passmore S (2024) An examination of studies related to the sport of curling: a scoping review. Front. Sports Act. Living 6:1291241. doi: 10.3389/fspor.2024.1291241
Received: 8 September 2023; Accepted: 22 January 2024;
Published: 13 February 2024.
Edited by:
Gavin L. Moir, East Stroudsburg University, United StatesReviewed by:
Brandon Snyder, East Stroudsburg University, United StatesConnor Saker, East Stroudsburg University, United States
Matthew Miltenberger, East Stroudsburg University, United States
© 2024 Zacharias, Robak and Passmore. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
*Correspondence: Nicole Robak cm9iYWtuQG15dW1hbml0b2JhLmNh
†These authors have contributed equally to this work
‡This author is the senior author