Lane changes are an important aspect of freeway flow. Most lane change models are microscopic, describing whether individual vehicles/drives will change lanes, and hence are calibrated microscopically. Macroscopic validation often is restricted to the distribution of vehicles across lanes. To the best of our knowledge, no systematic analysis has been made of the number of lane changes as function of the operational characteristics of the origin and target lane. This paper fills that gap, by analyzing the number of lane changes as function of several incentives. Based on data availability, two 'simple' sites are selected, i.e. as close as possible to a straight continuous freeway. Statistically, we find that on the selected sites, drivers change lanes on average once per two kilometer driven. Furthermore, analyzing the number of lane changes (per kilometer per hour) as function of the density in the origin lane and in the target lane, we find, as expected, this increases with the density in the origin lane for a fixed density in the target lane. Surprisingly, it also increases with the density in the target lane for a fixed density in the origin lane. The underlying mechanism is therefore different than gap acceptance theory. The analyses presented in this paper can be used to qualitatively verify (microscopic and macroscopic) lane change models, and to propose better lane change models.