The amplitude, frequency and number of oscillating movements have a significant impact on the possible damage modes of rolling bearings. Changes in amplitude change both the fatigue and wear risk of the raceways. In order to properly calculate the fatigue lifetime of an oscillating bearing, estimate the risk of surface-induced damage modes and design test programs for such bearings, it is necessary to understand the characteristics of the oscillating movements. This paper presents a comprehensive method for the analysis of time series data including position and loads. The method is applied to the simulated time-series data of the IWT 7.5-164 reference wind turbine. Wind turbine blades typically experience wide-band dynamic loads due to stochastic wind conditions. Therefore, it is important to use time series based cycle counting methods.