The accuracy of model output increases with a decreasing support size of the input data, due to the increase of detail. This paper examines whether this is true for various spatial models developed for simulating rockfall. We analyze the effect of the support size on the accuracy of a set of models and their parameters. Both calibration and validation data were obtained from real-size rockfall experiments in France, where high-speed video cameras recorded the trajectories and velocities of more than 200 individual falling rocks with diameters between 0.8 and 1.5 meter. The second validation set was obtained in the Austrian Alps. Here we mapped rockfall impacts on trees to obtain the spatial distribution of rockfall impacts throughout the study site. These observed data are thoroughly compared with the output of a rockfall simulation model. One of the main findings is that a larger support size can be a more important cause of a larger model error than poor data quality.