Ecological momentary assessment (EMA) and accelerometer-based devices can be used concurrently to better understand dimensions of physical activity. This study presents procedures for analyzing data derived from both methods to examine exercise-related walking and running, as well as determine evidence for alignment between these methods. The participants (N = 29) wore an ActiGraph GT3X+ and completed four EMA surveys/day across 2 weeks to report exercise (mode and duration). GT3X+ counts per 10 s were processed using the Crouter two-regression model to identify periods of walking/running (coefficient of variation in activity counts ≤10% and >0%). Two reviewers visually inspected Crouter two-regression model data and recorded durations of walking/running in time blocks corresponding to EMA reports of exercise. The data were classified as “aligned” if the duration of walking/running between methods were within 20% of one another. Frequency analyses determined the proportion of aligned versus nonaligned exercise durations. Reviewer reliability was examined by calculating interobserver agreement (classification of aligned vs. nonaligned) and intraclass correlation coefficients (ICC; duration based on coefficient of variation). Of the 139 self-reported bouts of walking and running exercise, 25% were classified as aligned with the Crouter two-regression model coefficient of variation. Initial interobserver agreement was 91, and ICCs across data classified as aligned (ICC = .992) and nonaligned (ICC = .960) were excellent. These novel procedures offer a means of isolating exercise-related physical activity for further analysis. Due to the inability to align evidence in most cases, we discuss key considerations for optimizing EMA survey questions, choice in accelerometer-based device, and future directions for visual analysis procedures.