Comparison of different measures to monitor week-to-week changes in training load in high school runners

Training load is commonly used to monitor training stress and is the product of external and internal physiological loads experienced by an athlete. With emerging wearable technology, it is possible to evolve existing external load measurement from duration or distance to runner-specific biomechanic...

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Veröffentlicht in:International journal of sports science & coaching 2021-04, Vol.16 (2), p.370-379
Hauptverfasser: Ryan, Megan R, Napier, Christopher, Greenwood, Daniel, Paquette, Max R
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Napier, Christopher
Greenwood, Daniel
Paquette, Max R
description Training load is commonly used to monitor training stress and is the product of external and internal physiological loads experienced by an athlete. With emerging wearable technology, it is possible to evolve existing external load measurement from duration or distance to runner-specific biomechanical data, which when combined with existing measures of internal load such as session rating of perceived exertion (sRPE), may improve the quantification of training stress. This study compared week-to-week changes in training duration with different training loads obtained from common and more individualized measures of external load. The training of nine male high school cross-country runners from the same team undertaking the same training program was monitored for two consecutive weeks. This two-week cycle included a “coach-prescribed” low and high training load week. Training loads were calculated with sRPE and external load measures including: duration (minutes), Step Count, “Bone Stimulus” (IMeasureU), and cumulative vertical force. Weekly distances (in miles) were also measured. Between-week percent change (%Δ) was compared among training loads and minutes using paired t-tests and Cohen’s d effect size. Different %Δ were found between sRPExMinutes (%Δ=65 ± 25%; p = 0.002, d = 1.83), sRPExStep Count (%Δ=66 ± 31%; p = 0.006, d = 2.06), sRPExForce (%Δ=66 ± 29%; p = 0.002, d = 1.91), and miles (%Δ=28 ± 13%; p = 0.019, d = 0.71) compared to minutes (%Δ=20 ± 8%). These findings highlight that only using weekly volume can greatly misrepresent changes in training stress in runners. We therefore encourage coaches and practitioners to consider training monitoring approaches beyond just weekly distance or duration. Simple measures of training load that include duration and sRPE might be sufficient.
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Between-week percent change (%Δ) was compared among training loads and minutes using paired t-tests and Cohen’s d effect size. Different %Δ were found between sRPExMinutes (%Δ=65 ± 25%; p = 0.002, d = 1.83), sRPExStep Count (%Δ=66 ± 31%; p = 0.006, d = 2.06), sRPExForce (%Δ=66 ± 29%; p = 0.002, d = 1.91), and miles (%Δ=28 ± 13%; p = 0.019, d = 0.71) compared to minutes (%Δ=20 ± 8%). These findings highlight that only using weekly volume can greatly misrepresent changes in training stress in runners. We therefore encourage coaches and practitioners to consider training monitoring approaches beyond just weekly distance or duration. 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title Comparison of different measures to monitor week-to-week changes in training load in high school runners
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