Running Performance can be Predicted by Log v-Log t-Models based on Non-Exhaustive Tests and Rating of Perceived Exertion

Brückner, Jan-Peter ORCID

Individual running performances at different distances can be described by log v-log t-models. The study tests, if rating of perceived exertion while submaximal graded exercise (GXT) and constant load test (CLT) can be used for parameter estimation of log-log-models so that running performance can be predicted. Under laboratory and field conditions 13 and 12 subjects performed a submaximal GXT and CLT, where RPE was measured using RPE15-Scale (Borg, 2004) to calculate 3000m running-performance. Finally, maximal 3000m track runs were done for model verification. Predicted and measured running speed were highly correlated (r = .92 vs. r = .96, p < .001). In the laboratory study predicted speeds were significant lower than measured speeds, whereas by field tests predicted values didnĀ“t differ from measured ones. It is concluded that the presented approach offers an accurate, economic and non-exhaustive possibility of performance prediction in running.

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Brückner, Jan-Peter: Running Performance can be Predicted by Log v-Log t-Models based on Non-Exhaustive Tests and Rating of Perceived Exertion. 2018.

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