Introdução: O desempenho de remadores no remoergômetro é motivo de curiosidade entre os cientistas. Os modelos de predição podem medir o desempenho no remoergômetro. Neste sentido, as variáveis estudadas foram analisadas como possíveis preditores de desempenho. Objetivo: Desenvolver diferentes modelos de regressão a fim de predizer o desempenho com o uso das variáveis antropométricas composição corporal, consumo máximo de oxigênio e força. Métodos: Vinte remadores participaram do estudo (21,35 ± 0,98 anos). Foram aplicados os testes de consumo máximo de oxigênio, força, 500 m e o exame de absorciometria radiológica de dupla energia. A regressão linear múltipla foi realizada no SPSS 16 para os quatro diferentes modelos de regressão. A confiabilidade dos modelos foi indicada pelo coeficiente de determinação R2 e pelo erro padrão da estimativa (SEE). Resultados: Os modelos de antropometria-potência (R2 = 0,92; SEE = 0,06), VO 2 Pico (R2 = 0,88; SEE = 0,07), força-potência (R2 = 0,93; SEE = 0,06) apresentaram predição confiável para o desempenho nos 500 m em remoergômetro, assim como a combinação de todas as variáveis (R2 = 0,94; SEE = 0,08). Conclusão: Feitas essas análises, pode-se assegurar a necessidade desses modelos com o objetivo de complementar a identificação, seleção de talentos e, sobretudo, melhora no desempenho.Descritores: desempenho atlético; força muscular; antropometria; análise de variância; análise de regressão. ABSTRACTIntroduction: The performance of rowers in the rowing ergometer is a matter of curiosity among scientists. Prediction models can measure performance on the rowing ergometer. In this sense, the studied variables were analyzed as possible predictors of performance. Objective: To develop different regression models in order to predict performance using the anthropometric variables body composition, maximal oxygen consumption, and strength. Methods: Twenty rowers participated in the study (21.35±0.98 (R2=0.92, SEE=0.06), VO2 peak (R2=0.88, SEE=0.07), SEE=0.06) 92; SEE = 0,06), VO 2 pico (R2 = 0,88; SEE = 0,07),93; SEE = 0,06) presentaron predicción confiable para el rendimiento en los 500 m en remoergómetro, así como la combinación de todas las variables (R2 = 0,94; SEE = 0,08 . Com a avaliação individual do remador, os técnicos são capazes de avaliar o ranking de cada atleta na equipe em ambiente controlado 1 . Assim, os resultados das avaliações de potência e força máxima são preditores de desempenho no remoergômetro no teste máximo de 2000 metros [8][9][10][11] . Além disso, o comportamento físico está relacionado com a composição e dimensão corporal do remador de alto nível, por serem fatores determinantes da força muscular e amplitude de movimento nas fases da remada 12,13 . Enfim, um perfil favorável pode ser considerado como um fator importante para o desenvolvimento do remador em adição a técnica e experiência. Esse perfil identificado, pode ser utilizado para identificação de talentos e desenvolver avaliações específicas. Atualmente, os estudos analisam as variáveis que...
Introduction: High-performance training should focus on motor capability determinants in competition to make physical preparation effective. Objective: To analyze and draw up an elite model based on competitive activity, to guide the theory and practice of female rowers, using data on the 42 finalists of the 2010-2018 world championships. Methods: Forty-two rowers from 2010-2018 world championships participated in the study, final A, women's single scull without weight restrictions. The statistical comparison was performed and differences between 500 meter splits analyzed for each variable were discussed. Results: Strong correlation was observed between time (r=-0.99, p<0.01), power (r=0.99, p<0.01), technical level (r=0.99, p<0.01) and speed. In the competitive model, the relationship between speed at 2000 meters and time (r=-0.96, p<0.01), speed (r=0.94, p<0.01) and power (r=0.96, p<0.01) showed a strong correlation with speed in the splits of the third 500 meters of the race. In terms of stroke rate (r=-0.56, p<0.01) and stroke length (r=0.54, p<0.01), the strongest correlation occurs at the start, in the first 100 meters of competition. Conclusion: Having performed these analyses, it is possible to confirm the need to investigate competitive activity in order to supplement the rower's fitness preparation system. Level of evidence I; Diagnostic studies-Investigating a diagnostic test.
Introduction: The National Rower Evaluation System [Sistema Nacional de Avaliação do Remador] (SNAR), adopted by the Brazilian Rowing Confederation, aims to establish a national ranking, and is a prerequisite to participation in National Championships and Selective Games, in its different categories, as well as for joining the Brazilian Rowing Team. Objective: This study aimed to analyze the relationship and the prediction of the SNAR results with competitors’ times in a Brazilian Rowing Championship (CBR). Methods: The investigation involved 11 female rowers (18.00 ± 0.89 years) and 16 male rowers (18.18 ± 0.91 years), participants in a CBR, in the junior category. The research was qualitative, with content analysis of the data available on the Confederation's website. Results: In the junior female category, of the ten variables studied, three showed a correlation r≥0.50; in the junior male category, nine showed a correlation r≥0.50. The multiple linear regression equation, with all the variables studied, showed R2 = 0.86 and SEE = 5.30, in the female category; and R2 = 0.90 and SEE = 3.56, in the male category. Conclusion: Based on our results, the tests indicated by SNAR can be an important source of information, offering significant support for managers, athletes and coaching staff, for use in performance diagnosis and in particular, competition prognosis. It can also be used to adapt training schedule where necessary. Level of evidence I; Diagnostic studies-Investigation of a diagnostic test.
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