Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test
Background: The exhaustive series of tests undergone by young athletes of Olympic rowing prior to important competitions imply loads of physical stress that can ultimately impact on mood and motivation, with negative consequences for their training and performance. Thus, it is necessary to develop a...
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MDPI AG
2021
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oai:doaj.org-article:ecd0b63f318240d1b6025010ab31082f2021-11-25T16:46:51ZPerformance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test10.3390/biology101110822079-7737https://doaj.org/article/ecd0b63f318240d1b6025010ab31082f2021-10-01T00:00:00Zhttps://www.mdpi.com/2079-7737/10/11/1082https://doaj.org/toc/2079-7737Background: The exhaustive series of tests undergone by young athletes of Olympic rowing prior to important competitions imply loads of physical stress that can ultimately impact on mood and motivation, with negative consequences for their training and performance. Thus, it is necessary to develop a tool that uses only the performance of short distances but is highly predictive, offering a time expectancy with high reliability. Such a test must use variables that are easy to collect with high practical applicability in the daily routine of coaches. Objective: The objective of the present study was to develop a mathematical model capable of predicting 2000 m rowing performance from a maximum effort 100 m indoor rowing ergometer (IRE) test in young rowers. Methods: The sample consisted of 12 male rowing athletes in the junior category (15.9 ± 1.0 years). A 100 m time trial was performed on the IRE, followed by a 2000 m time trial 24-h later. Results: The 2000 m mathematical model to predict performance in minutes based on the maximum 100 m test demonstrated a high correlation (r = 0.734; <i>p</i> = 0.006), strong reliability index (ICC: 0.978; IC95%: [0.960; 0.980]; <i>p</i> = 0.001) and was within usable agreement limits (Bland -Altman Agreement: −0.60 to 0.60; 95% CI [−0.65; 0.67]). Conclusion: The mathematical model developed to predict 2000 m performance is effective and has a statistically significant reliability index while being easy to implement with low cost.Luiz Felipe da SilvaPaulo Francisco de Almeida-NetoDihogo Gama de MatosSteven E. RiechmanVictor de QueirosJoseane Barbosa de JesusVictor Machado ReisFilipe Manuel ClementeBianca MiarkaFelipe J. AidarPaulo Moreira Silva DantasBreno Guilherme de Araújo Tinoco CabralMDPI AGarticleathletic performancerowingsportyoung athletemathematical modelBiology (General)QH301-705.5ENBiology, Vol 10, Iss 1082, p 1082 (2021) |
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DOAJ |
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DOAJ |
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EN |
| topic |
athletic performance rowing sport young athlete mathematical model Biology (General) QH301-705.5 |
| spellingShingle |
athletic performance rowing sport young athlete mathematical model Biology (General) QH301-705.5 Luiz Felipe da Silva Paulo Francisco de Almeida-Neto Dihogo Gama de Matos Steven E. Riechman Victor de Queiros Joseane Barbosa de Jesus Victor Machado Reis Filipe Manuel Clemente Bianca Miarka Felipe J. Aidar Paulo Moreira Silva Dantas Breno Guilherme de Araújo Tinoco Cabral Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| description |
Background: The exhaustive series of tests undergone by young athletes of Olympic rowing prior to important competitions imply loads of physical stress that can ultimately impact on mood and motivation, with negative consequences for their training and performance. Thus, it is necessary to develop a tool that uses only the performance of short distances but is highly predictive, offering a time expectancy with high reliability. Such a test must use variables that are easy to collect with high practical applicability in the daily routine of coaches. Objective: The objective of the present study was to develop a mathematical model capable of predicting 2000 m rowing performance from a maximum effort 100 m indoor rowing ergometer (IRE) test in young rowers. Methods: The sample consisted of 12 male rowing athletes in the junior category (15.9 ± 1.0 years). A 100 m time trial was performed on the IRE, followed by a 2000 m time trial 24-h later. Results: The 2000 m mathematical model to predict performance in minutes based on the maximum 100 m test demonstrated a high correlation (r = 0.734; <i>p</i> = 0.006), strong reliability index (ICC: 0.978; IC95%: [0.960; 0.980]; <i>p</i> = 0.001) and was within usable agreement limits (Bland -Altman Agreement: −0.60 to 0.60; 95% CI [−0.65; 0.67]). Conclusion: The mathematical model developed to predict 2000 m performance is effective and has a statistically significant reliability index while being easy to implement with low cost. |
| format |
article |
| author |
Luiz Felipe da Silva Paulo Francisco de Almeida-Neto Dihogo Gama de Matos Steven E. Riechman Victor de Queiros Joseane Barbosa de Jesus Victor Machado Reis Filipe Manuel Clemente Bianca Miarka Felipe J. Aidar Paulo Moreira Silva Dantas Breno Guilherme de Araújo Tinoco Cabral |
| author_facet |
Luiz Felipe da Silva Paulo Francisco de Almeida-Neto Dihogo Gama de Matos Steven E. Riechman Victor de Queiros Joseane Barbosa de Jesus Victor Machado Reis Filipe Manuel Clemente Bianca Miarka Felipe J. Aidar Paulo Moreira Silva Dantas Breno Guilherme de Araújo Tinoco Cabral |
| author_sort |
Luiz Felipe da Silva |
| title |
Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| title_short |
Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| title_full |
Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| title_fullStr |
Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| title_full_unstemmed |
Performance Prediction Equation for 2000 m Youth Indoor Rowing Using a 100 m Maximal Test |
| title_sort |
performance prediction equation for 2000 m youth indoor rowing using a 100 m maximal test |
| publisher |
MDPI AG |
| publishDate |
2021 |
| url |
https://doaj.org/article/ecd0b63f318240d1b6025010ab31082f |
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