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Using the Acute:Chronic Workload Rat...

Saylor, Hannah Elizabeth.

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Using the Acute:Chronic Workload Ratio to Predict Peak Performance in Elite NCAA Track and Field Sprinters.

Record Type:	Electronic resources : Monograph/item
Title/Author:	Using the Acute:Chronic Workload Ratio to Predict Peak Performance in Elite NCAA Track and Field Sprinters./
Author:	Saylor, Hannah Elizabeth.
Published:	Ann Arbor : ProQuest Dissertations & Theses, : 2019,
Description:	91 p.
Notes:	Source: Masters Abstracts International, Volume: 81-04.
Contained By:	Masters Abstracts International81-04.
Subject:	Nutrition. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=13897573
ISBN:	9781088300275

Using the Acute:Chronic Workload Ratio to Predict Peak Performance in Elite NCAA Track and Field Sprinters.
Saylor, Hannah Elizabeth.

Using the Acute:Chronic Workload Ratio to Predict Peak Performance in Elite NCAA Track and Field Sprinters. - Ann Arbor : ProQuest Dissertations & Theses, 2019 - 91 p.

Source: Masters Abstracts International, Volume: 81-04.

Thesis (M.S.)--The Florida State University, 2019.

This item must not be sold to any third party vendors.

Purpose: To establish the relationship between the acute:chronic workload ratio and peak performance in division 1 NCAA track and field sprinters over the course of the 2018 outdoor season. Methods: The acute:chronic workload ratio was determined by calculating the sum of the week before the competition's session rating of perceived exertion of training load (acute load) and dividing it by the average weekly session rating of perceived exertion of training load over the previous four weeks (chronic workload). All ratings of perceived exertion were self-reported through an Athlete Management System (AMS) no later than one hour after the training session or competition. The sprinters' race times were recorded through an online data base and, in the primary statistical analysis, were analyzed for confounding variables. Once the confound variables were established, Pearson correlations were used covarying for the confounding variables. Our hypothesis was that there would be a positive relationship between the acute:chronic workload ratio and the 100m and 200m race times. In a secondary analysis, violating the statistical assumption of independence, the acute:chronic workload ratio was correlated to the sum of all data points for male and female 100m and 200m race times and the male and female 100m and 200m Z-scores for each sprinter. Bins were created with the hypothesis that having an acute:chronic workload ratio between 0.8 and 1.3 would be correlated with lower race times in the 100m and 200m races and more negative Z-scores for the 100m and 200m races. Results: A lower acute:chronic workload ratio resulted in a moderate positive correlation with lower race times in the 100m (R= 0.542) and 200m (R= 0.711) races. Conclusions: Maintaining an acute:chronic workload ratio between 0.8 and 1.3 may be optimal for elite division 1 NCAA track and field sprinters to reach their peak performance in the 100m and 200m races. An individualized approach to training load using the acute:chronic workload ratio should help coaches and performance staff with individualized training-load planning and prescription for the sprinters to reach peak performance.

ISBN: 9781088300275Subjects--Topical Terms:

517777
Nutrition.
Subjects--Index Terms:

Sprinters

Using the Acute:Chronic Workload Ratio to Predict Peak Performance in Elite NCAA Track and Field Sprinters.
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520 $a Purpose: To establish the relationship between the acute:chronic workload ratio and peak performance in division 1 NCAA track and field sprinters over the course of the 2018 outdoor season. Methods: The acute:chronic workload ratio was determined by calculating the sum of the week before the competition's session rating of perceived exertion of training load (acute load) and dividing it by the average weekly session rating of perceived exertion of training load over the previous four weeks (chronic workload). All ratings of perceived exertion were self-reported through an Athlete Management System (AMS) no later than one hour after the training session or competition. The sprinters' race times were recorded through an online data base and, in the primary statistical analysis, were analyzed for confounding variables. Once the confound variables were established, Pearson correlations were used covarying for the confounding variables. Our hypothesis was that there would be a positive relationship between the acute:chronic workload ratio and the 100m and 200m race times. In a secondary analysis, violating the statistical assumption of independence, the acute:chronic workload ratio was correlated to the sum of all data points for male and female 100m and 200m race times and the male and female 100m and 200m Z-scores for each sprinter. Bins were created with the hypothesis that having an acute:chronic workload ratio between 0.8 and 1.3 would be correlated with lower race times in the 100m and 200m races and more negative Z-scores for the 100m and 200m races. Results: A lower acute:chronic workload ratio resulted in a moderate positive correlation with lower race times in the 100m (R= 0.542) and 200m (R= 0.711) races. Conclusions: Maintaining an acute:chronic workload ratio between 0.8 and 1.3 may be optimal for elite division 1 NCAA track and field sprinters to reach their peak performance in the 100m and 200m races. An individualized approach to training load using the acute:chronic workload ratio should help coaches and performance staff with individualized training-load planning and prescription for the sprinters to reach peak performance.
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