Open AccessAssociation between 1-mile run times in training and selected predictors: A case study
Author(s) -
John Hart,
MHSc Dc
Publication year - 2020
Publication title -
international journal of sport, exercise and health research
Language(s) - English
Resource type - Journals
ISSN - 2581-4923
DOI - 10.31254/sportmed.4109
Subject(s) - mile , linear regression , regression analysis , regression toward the mean , medicine , demography , regression , statistics , mathematics , geography , geodesy , sociology
Runners have an interest in what variables might help them achieve faster run times. In this case study of an individual runner, six predictors are compared to his 1-mile run times over a 1-year period. The six predictors consisted of run sessions (1, 2, etc), outdoor temperature, outdoor humidity, time of day that run began, resting heart rate (HR) on day of run, and heart rate variability also on day of run. Predictors that showed statistically significant correlations were included in multiple linear regression to compare relative strength of association with run times. Two predictors qualified for regression analysis: run session and HR. Both continued to show statistically significant associations in regression.