In sport and exercise research, examining both within- and between-individual variation is crucial. The ability to investigate change both within competitive events and across a competitive season is a priority for many sport researchers. The aim of this article is to demonstrate an approach to analyzing intensive longitudinal data collected through time-scale-dependent longitudinal designs. Following didactic presentation of the approach, two illustrations from secondary data analysis are used to describe the modeling process in detail. Illustration 1 includes affective response data from an exercise intervention randomized pilot study. Illustration 2 uses referee and player distance data collected during professional soccer games in the English Premier League. Each illustration describes a process for testing and comparing multiple time scale models based on the three-level multilevel model, and results are interpreted. In the discussion, advantages and limitations of the approach are highlighted.