Athlete Monitoring: Data Analysis and Visualization
Normalizing Individuals
Some individuals might be high raters or low raters, or highly or low variable, particularly for subjective ratings such as wellness items (e.g., “how did you sleep; from 1 to 10” questions). This can also be applied, particularly high vs. low ratings, for training load, such as weekly distance run for novice vs. experienced runners. Continuous comparison between individuals done at absolute or raw scales might be missing these individual variations.
In this lecture I will explain the few techniques that can be used to make the comparison more “fair”, particularly for the purpose of figuring out the change in individual monitoring.
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