Background: To examine whether individual differences in intensive longitudinal data-derived affective dynamics (i.e. positive and negative affect variability and inertia and positive affect-negative affect bipolarity) – posited to be indicative of emotion dysregulation – are uniquely related to drinking level and affect-regulation drinking motives after controlling for mean levels of affective states. Method: We used a large sample of college student drinkers (N = 1640, 54% women) who reported on their affective states, drinking levels and drinking motives daily for 30 days using a web-based daily diary. We then calculated from the daily data positive and negative affect variability, inertia, affect bipolarity and mean levels of affect and used these as predictors of average drinking level and affect-regulation drinking motives (assessed using both retrospective and daily reporting methods). Results: Findings from dynamic structural equation models indicated that mean levels of affect were uniquely related to drinking motives, but not drinking level. Few dynamic affect predictors were uniquely related to outcomes in the predicted direction after controlling for mean affect levels. Conclusion: Our results add to the inconsistent literature regarding the associations between affective dynamics and alcohol-related outcomes, suggesting that any effects of these indicators, after controlling for mean affect levels, might be more complex than can be detected with simple linear models.