In this paper we introduce a novel approach for query performance prediction based on ranking list scores dispersion. Starting from the premise that different score distributions appear for good and poor performance queries, we introduce a set of measures that capture these differences between both types of distributions. The proposed measures will employ the ranking list, output of a search system, as an information source to predict query performance in terms of MAP. The obtained results reveal a significant correlation degree with MAP and are very similar to those achieved with more complex methods. Finally some generic open questions that could guide further research on query prediction methods are introduced.