10.13130/RD_UNIMI/ZSCGJ7Giuliani, MarcoMarcoGiuliani0000-0002-6927-7177University of MilanoUNIMI Dataverse2023Social SciencesEuropean electionPollsAccuracyPrediction errorGiuliani, MarcoMarcoGiulianiUniversity of Milano2023-02-072023-02-073137346776456071application/x-stata-syntaxtext/tab-separated-valuesapplication/pdf1.0CC0 WaiverPollsters have been recently accused of delivering poor electoral predictions. We argue that one of the reasons for their failures lies in the difficulty of including an updated deep understanding of electoral behaviour. Even if pollsters’ predictions are not forecasts produced by models, the set of choices needed to produce their estimates is not indifferent to a theoretical comprehension of electoral dynamics. We exemplify this lack of theory by using an original dataset consisting of 1057 party*poll observations in the case of the last European election. Pollsters failed to account for what we know about second-order elections, thus overestimating government and big parties, which normally obtain poor results in European elections, and underestimating new and Eurosceptic ones, which usually perform well.