College of Kinesiology
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Item Estimating is not measuring: the use of non-invasive estimations of maturity in youth football(Taylor and Francis, 2021) Baxter-Jones, Adam; Fransen, Job; Skorski, SteveItem The Sport Performance Perceptions Scale (SPPS) Manual(2023) Adam, Margo E. K.; Ferguson, Leah J.; Mosewich, Amber D.; Kowalski, Kent C.Item Are There Sensitive Periods for Skill Development in Male Adolescent Basketball Players?(Lippincott, Williams & Wilkins [Commercial Publisher]; American College of Sports Medicine (ACSM) [University Publisher], 2024) GUIMARÃES, EDUARDO; BAXTER-JONES, ADAM D. G.; WILLIAMS, A. MARK; ANDERSON, DAVID I.; JANEIRA, MANUEL A.; GARBELOTO, FERNANDO; PEREIRA, SARA; MAIA, JOSÉAbstract Purpose Although spurts in physical capacities during adolescence are well known, little is known about the existence of such spurts in sport-specific skill development, especially during the period of rapid growth in stature. Our aims were to examine the timing, intensity, and sequence of basketball-specific skill spurts aligned with biological (years from peak height velocity (PHV)) rather than chronological age. We then defined putative sensitive periods (windows of optimal development) for each skill aligned to the adolescent growth spurt. Methods Altogether, 160 adolescent male basketballers aged 11–15 yr were tested biannually over 3 consecutive years. The years from attainment of PHV was estimated, and six skill tests were aligned to each year from PHV in 3-month intervals. Skill velocities were estimated using a nonsmooth polynomial model. Results Maximal gains in slalom dribble occurred 12 months before PHV attainment (intensity, 0.18 m·s−1·yr−1), whereas in speed shot shooting (intensity, 9.91 pts·yr−1), passing (intensity, 19.13 pts·yr−1), and slalom sprint (intensity, 0.19 m·s−1·yr−1), these skill spurts were attained 6 months before PHV attainment. The mean gains in control dribble (intensity, 0.10 m·s−1·yr−1) and defensive movement (intensity, 0.12 m·s−1·yr−1) peaks coincided with attainment of PHV. We identified different sized windows for optimal development for each skill. Conclusions Peak spurts in skill development, for most basketball skills, were attained at the same time as PHV. The multiple peaks observed within the defined windows of optimal development suggest that there is room for skill improvement even if gains might be greater earlier rather than later in practice. Our findings highlight the need to make coaches aware of where their players are relative to the attainment of PHV because different skills appear to develop differently relative to PHV. Such knowledge may help in designing more relevant training regimes that incorporate the athlete’s current growth status so that skill development can be maximized.Item Enhancement of a Mathematical Model for Predicting Puberty Stage in Boys: A Cross-Sectional Study(Wiley, 2024-11-25) de Almeida-Neto, Paulo Francisco; Baxter-Jones, Adam Dominic George; Arrais, Ricardo Fernando; de Azevedo, Jenner Christian Veríssimo; Dantas, Paulo Moreira Silva; Cabral, Breno Guilherme de Araújo Tinôco; Medeiros, Radamés Maciel VitorBackground Previously, we developed a mathematical model capable of predicting pubertal development (PD) through seven anthropometric variables, with an accuracy of 75%. We believe that it is possible to develop a similar model that uses fewer anthropometric measurements and provides greater precision. Objective Develop a mathematical model capable of predicting PD through anthropometric variables. Methods We evaluated the anthropometric profile and PD by medical analysis in 203 boys (Age = 12.6 ± 2.6). Subsequently, we divided the boys into groups: development (n = 121) and cross-validation (n = 82). Data from the development group were subjected to discriminant analysis to identify which anthropometric indicators would be potential predictors of PD. We subsequently developed an equation based on the indicated indicators and tested its validation using data from the cross-validation group. Results Discriminant analyses showed that age and sitting-height were the variables with the greatest power to predict PD (p < 0.05). Consequently, the mathematical model was developed: Puberty-score = −17.357 + (0.603 × Age [years]) + (0.127 × Sitting-height [cm]). Based on the scores generated, we classified PD into stage-I (score ≤ −1.815), stage-II (score = −1.816 to −0.605), stage-III (score = −0.606 to 0.695), stage-IV (score = 0.696–3.410), and stage-V (score > 3.410). No differences were found between PD assessments performed by doctors and assessments using the mathematical model (p > 0.5). The prediction model showed high agreement (R 2 = 0.867; CCC = 0.899; ICC = 0.900; Kappa = 0.922; α-Krippendorff = 0.885; Bland–Altman LoAs = −2.0, 2.0; pure error = 0.0009) with accuracy of 82.8% and precision of 82%. Analyses in the cross-validation group confirmed the reliability of the prediction model. Conclusion The developed mathematical model presents high reliability, validity and accuracy and precision above 80% for determining PD in boys.