Athletic Play Surfaces and Injury Risk

Yurgil, Jacqueline L; Meredith, T. Jason; Martin, Peter Mitchell

doi:10.1249/jsr.0000000000000828

Cited by 3 publications

(3 citation statements)

References 36 publications

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“…Injury risk in relation to competition and training surfaces has been extensively evaluated in equine and human medicine ( 3 , 39 , 40 ). Relationships between surface type and risk of injury have been minimally evaluated in canine sports, with one study suggesting a correlation between track surface and injury in racing greyhounds ( 41 ).…”

Section: Discussionmentioning

confidence: 99%

Internet Survey of Risk Factors Associated With Training and Competition in Dogs Competing in Agility Competitions

2022

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Objective: To describe risk factors associated with training and competition in relation to frequency and severity of injuries experienced by agility dogs.Procedures: An internet-based survey collected data on competition level variables and training level variables. The primary outcome was history of any injury and a secondary outcome considered history of severe injury (injury lasting > 3 months). Logistic regression was used to estimate associations and final models were obtained via backward selection to identify the strongest associations within variables.Results: There were 4,197 dogs included in this analysis. Injury was reported for 1,737 (41.4%) dogs and severe injury was reported for 629 (15.0%). In the model with competition level factors, jumping 4” (OR: 1.50) or 2–4” (OR: 1.31) over shoulder height compared to jumping 0–2” lower and competing at national events was associated with increased injury risk, while competing 6+ times on rubber matting was associated with lower risk (OR: 0.62). Training level variables associated with injury risk were age starting jump, teeter, and weave training, with the highest risk observed for dogs starting jump training between 3 and 18 months but starting weave and teeter training after 18 months of age.Conclusion and Clinical Relevance: Many variables thought to be associated with injury risk were not significant in the final model. Starting jump training at an earlier age was associated with greater risk of injury relative to starting after 18 months. It is possible that the high impact of jump training before skeletal maturity may increase the risk of injuries or musculoskeletal conditions. The increased risk of injury in dogs that jump 2–4, or 4+ inches higher than shoulder height may be due to increased biomechanical forces during takeoff and landing. Faster dogs may be at higher risk of injury; handlers planning competition around big events or competing at the national level are likely to have faster dogs, and may be less likely to compete on rubber matting. These data provide valuable current insight into the possible effects that training and competition variables may have on injury risk in agility dogs.

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Section: Discussionmentioning

confidence: 99%

Internet Survey of Risk Factors Associated With Training and Competition in Dogs Competing in Agility Competitions

2022

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“…Relaxation exercise is carried out at the end of each training to relieve the stress of exercise and promote the recovery of body functions from exercise [5]. Muscles are in a tight state after exercise, and if not timely relaxed, it will not only lead to muscle soreness but with time, it will also make the muscles lose elasticity, and movement coordination will be greatly reduced; hence, appropriate postpractice relaxation is needed to relieve exercise fatigue and to meet psychological pressure requirements [6].…”

Section: Introductionmentioning

confidence: 99%

Artificial Intelligence and Big Data-Based Injury Risk Assessment System for Sports Training

Zhang

2022

Mobile Information Systems

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Sports training is an important part of daily life, and various injuries are prone to occur during the training process. If they are not dealt promptly, they are bound to affect daily life. Although our nationals are becoming more and more aware of participating in physical exercise, they are performing numerous sports activities at the time of unexpected events, and sports injuries are becoming more and more frequent. To realize the evaluation and automatic prediction of sports training injury risk factors, a sports training injury risk evaluation algorithm using big data analysis is proposed. Establish a training injury risk analysis model, analyze the relevant parameters of training injury risk assessment through statistical and quantitative analyses, extract the entropy characteristics of training injury risk big data, optimize the decision-making and assessment process of injury risk through stable result assessment and fuzzy decision-making, and establish an expert system analysis model of sports training injury risk assessment. The hierarchical analysis method is applied to evaluate the training injury risk, and the adaptive fuzzy control is optimized to realize the optimal design of training injury risk assessment. Results show that this method has good adaptive characteristics and high certainty.

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“…favoring shorter rally durations and more points concluded with high-speed shots, which may potentially lead to a higher incidence of abrupt movements and an increased risk of injuries, although it is worth noting that certain characteristics of grass courts, such as shorter points and a higher frequency of serves and net play, may mitigate the risk of injuries for players [9,19,79,80].…”

Section: Plos Onementioning

confidence: 99%

Retirements of professional tennis players in second- and third-tier tournaments on the ATP and WTA tours

Palau,

Baiget,

Cortés

et al. 2024

PLoS ONE

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The demands of professional tennis, including physical and psychological aspects, contribute to the frequency of retirements at elite levels of the sport. The aim of this study was to analyze epidemiological patterns and risk factors associated with retirements in previous ATP and WTA Tour tournaments. A retrospective cohort study was conducted. This study focused on previous ATP and WTA Tour tournaments. The ATP database encompassed 584,806 matches, while the WTA database included 267,380 matches. To assess retirements, potential risk factors such as playing surface, tournament category, match round, and player age were analyzed. Incidence rates were calculated for the period between 1978–2019 for men and 1994–2018 for women. The overall incidence rate was 1.56 (95%CI: 1.54, 1.59) and 1.36 (95%CI: 1.33, 1.39) retirements per 1000 games played in male and female competitions, respectively. Retirements increased over the years. Higher incidence rates were observed on hard (1.59 [95%CI: 1.56, 1.63] and 1.39 [95%CI: 1.34, 1.44]) and clay (1.60 [95%CI: 1.57, 1.63] and 1.36 [95%CI: 1.32, 1.41]) compared to grass courts (0.79 [95%CI: 0.65, 0.94] and 1.06 [95%CI: 0.88, 1.27]). Risk factors differed by gender, with tournament category significant in males (IRR: 1.23 [95%CI: 1.19, 1.28] in ITF vs ATP) and match round in females (IRR: 0.92 [95%CI: 0.88, 0.98] in preliminary vs final). This study provides valuable insights for coaches, players, support teams, and epidemiologists regarding retirements and associated risk factors in previous ATP and WTA Tour tournaments, contributing to injury prevention strategies.

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Athletic Play Surfaces and Injury Risk

Cited by 3 publications

References 36 publications

Internet Survey of Risk Factors Associated With Training and Competition in Dogs Competing in Agility Competitions

Internet Survey of Risk Factors Associated With Training and Competition in Dogs Competing in Agility Competitions

Artificial Intelligence and Big Data-Based Injury Risk Assessment System for Sports Training

Retirements of professional tennis players in second- and third-tier tournaments on the ATP and WTA tours

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