Abstract: Human Trajectory Prediction (HTP) having gained much momentum in the last years, this paper addresses the question of evaluating how complex is a given dataset with respect to the prediction problem. For assessing a dataset complexity, we define a series of indicators around three concepts: Trajectory predictability; Trajectory regularity; Context complexity. We compare the most common datasets used in HTP at the light of these indicators and discuss what this may imply on benchmarking of HTP algorithms.