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Jožef Šimenko and Vedran Hadžić

Purpose: This study investigates bilateral performance with the Special Judo Fitness Test (SJFT) and its associations with competition performance (CP) and competition volume (CV) in judo. Methods: The SJFT compared movement patterns of the dominant (D) and nondominant (ND) sides on a sample of 27 youth judoka. Repeated-measures analysis of variance was used to determine differences in SJFT execution to the D and ND side, and for associations, the Pearson correlation was used (P < .05). Results: The total number of throws is significantly higher on the D side, with better performance in the final SJFT index. The CP showed positive correlations with the D side of SJFT executions in the second part of SJFT (P = .042) and the total number of throws (P = .036). On the ND side, the CP showed a positive correlation with the second part of the SJFT (P = .014), a negative correlation with the third part of the SJFT (P = .035), and a positive correlation in the total number of throws (P = .027). CV shows significant correlations with all parameters of the SJFT in the D and ND sides, with stronger correlations on the ND side. Conclusions: The study presents significantly better performance in judokas’ D side in SJFT. Associations between CP and CV with the SJFT were significant in connection to both body sides. It highlights the importance of bilateral movement development and good execution of the throwing techniques for the D and ND body sides of youth judoka to achieve greater CP all year round.

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Felipe Guimarães Teixeira, Paulo Tadeu Cardozo Ribeiro Rosa, Roger Gomes Tavares Mello, and Jurandir Nadal

Purpose: The study aimed to identify the variables that differentiate judo athletes at national and regional levels. Multivariable analysis was applied to biomechanical, anthropometric, and Special Judo Fitness Test (SJFT) data. Method: Forty-two male judo athletes from 2 competitive groups (14 national and 28 state levels) performed the following measurements and tests: (1) skinfold thickness, (2) circumference, (3) bone width, (4) longitudinal length, (5) stabilometric tests, (6) dynamometric tests, and (7) SJFT. The variables with significant differences in the Wilcoxon rank-sum test were used in stepwise logistic regression to select those that better separate the groups. The authors considered models with a maximum of 3 variables to avoid overfitting. They used 7-fold cross validation to calculate optimism-corrected measures of model performance. Results: The 3 variables that best differentiated the groups were the epicondylar humerus width, the total number of throws on the SJFT, and the stabilometric mean velocity of the center of pressure in the mediolateral direction. The area under the receiver-operating-characteristic curve for the model (based on 7-fold cross validation) was 0.95. Conclusion: This study suggests that a reduced set of anthropometric, biomechanical, and SJFT variables can differentiate judo athlete’s levels.

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Alannah K.A. McKay, Trent Stellingwerff, Ella S. Smith, David T. Martin, Iñigo Mujika, Vicky L. Goosey-Tolfrey, Jeremy Sheppard, and Louise M. Burke

Throughout the sport-science and sports-medicine literature, the term “elite” subjects might be one of the most overused and ill-defined terms. Currently, there is no common perspective or terminology to characterize the caliber and training status of an individual or cohort. This paper presents a 6-tiered Participant Classification Framework whereby all individuals across a spectrum of exercise backgrounds and athletic abilities can be classified. The Participant Classification Framework uses training volume and performance metrics to classify a participant to one of the following: Tier 0: Sedentary; Tier 1: Recreationally Active; Tier 2: Trained/Developmental; Tier 3: Highly Trained/National Level; Tier 4: Elite/International Level; or Tier 5: World Class. We suggest the Participant Classification Framework can be used to classify participants both prospectively (as part of study participant recruitment) and retrospectively (during systematic reviews and/or meta-analyses). Discussion around how the Participant Classification Framework can be tailored toward different sports, athletes, and/or events has occurred, and sport-specific examples provided. Additional nuances such as depth of sport participation, nationality differences, and gender parity within a sport are all discussed. Finally, chronological age with reference to the junior and masters athlete, as well as the Paralympic athlete, and their inclusion within the Participant Classification Framework has also been considered. It is our intention that this framework be widely implemented to systematically classify participants in research featuring exercise, sport, performance, health, and/or fitness outcomes going forward, providing the much-needed uniformity to classification practices.

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Dajo Sanders, David J. Spindler, and Jamie Stanley

Purpose: This case study aims to describe the multidisciplinary preparation of a multiple medal-winning Paralympic cyclist active in the C5 class. Specifically, it describes the 12-month preparation period toward the Tokyo 2020 Paralympic Games. Method: The participant (height 173 cm; weight approximately 63 kg) is active in the C5 para-cycling class (right arm impairment) and was preparing for the individual pursuit, road time trial, and mass-start race in the Tokyo Paralympic Games. The participant was supported by a multidisciplinary practitioner team focusing on multiple facets of athletic preparation. Morning resting heart rate (HR) and HR variability, as well as daily training data, were collected during the 12 months prior to Tokyo. Weekly and monthly trends in training, performance, and morning measures were analyzed. Training intensity zones were divided into zone 1 (<lactate threshold), zone 2(>lactate threshold, <critical power), and zone 3 (>critical power). Results: The participant won a silver (individual pursuit) and a bronze (time trial) medal at the Paralympic Games. Annual sums of volume and total work (in kilojoules) were, respectively, 1039 hours and 620,715 kJ. Analyzing all road sessions, 85% was spent in zone 1, 9% in zone 2, and 6% in zone 3. Physiological (eg, high training loads, hypoxic stimuli) and psychological stressors (ie, significant life events) were clearly reflected in morning HR and HR-variability responses. Conclusions: This case study demonstrates how a multidisciplinary team of specialist practitioners successfully prepared an elite Paralympic cyclist utilizing a holistic approach to training and health using data to manage allostatic load.

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Tim Newans, Phillip Bellinger, Christopher Drovandi, Simon Buxton, and Clare Minahan

Purpose: Sport-science research consistently contains repeated measures and imbalanced data sets. This study calls for further adoption of mixed models when analyzing longitudinal sport-science data sets. Mixed models were used to understand whether the level of competition affected the intensity of women’s rugby league match play. Methods: A total of 472 observations were used to compare the mean speed of female rugby league athletes recorded during club-, state-, and international-level competition. As athletes featured in all 3 levels of competition and there were multiple matches within each competition (ie, repeated measures), the authors demonstrated that mixed models are the appropriate statistical approach for these data. Results: The authors determined that if a repeated-measures analysis of variance (ANOVA) were used for the statistical analysis in the present study, at least 48.7% of the data would have been omitted to meet ANOVA assumptions. Using a mixed model, the authors determined that mean speed recorded during Trans-Tasman Test matches was 73.4 m·min−1, while the mean speeds for National Rugby League Women and State of Origin matches were 77.6 and 81.6 m·min−1, respectively. Random effects of team, athlete, and match all accounted for variations in mean speed, which otherwise could have concealed the main effects of position and level of competition had less flexible ANOVAs been used. Conclusion: These data clearly demonstrate the appropriateness of applying mixed models to typical data sets acquired in the professional sport setting. Mixed models should be more readily used within sport science, especially in observational, longitudinal data sets such as movement pattern analyses.

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Juan A. Escobar-Álvarez, Pedro Jiménez-Reyes, Filipe A. Da Conceição, and Juan P. Fuentes-García

Dancers require many specific dance skills of a ballistic nature. The design of supplementary training to improve the strength of the lower limbs and jump height is a relevant area of research. The purpose of this study was (1) to compare the effect of plyometric training versus combined training on countermovement jump (CMJ), squat jump (SJ), and sauté in first position (sauté) height and (2) to observe whether changes in CMJ and SJ were associated with changes in sauté in female and male dancers. Eighty-one classical professional ballet dancers (41 women and 40 men, age = 22.9 [3.7] y, body mass = 59.7 [8.6] kg, height = 167.4 [7.3] cm) were divided into a control group and 2 experimental groups: plyometric training and combined training. All groups followed their common routine of training regarding classes and rehearsal practice, whereas the experimental groups added 2 sessions (1 h per session) for 9 weeks of supplementary training. Significant increases (medium to large effect size) in CMJ, SJ, and sauté height were found in the pretest versus posttest comparisons for both experimental groups. Significant, very large correlations were found between the magnitude of improvement in sauté and the magnitude of improvement in CMJ and SJ. Plyometric and combined training programs are effective ways to improve jumping ability in professional dancers. The improvement in CMJ and SJ has a good transference on sauté `performance. These findings support the use of traditional training methods to improve jump height in specific and nonspecific ballet jumping ability.