Before revision:  Our results for the 2012 and 2016 U.S. races are largely in agreement with those of popular forecasters, and we use our new model to explore how subjective choices about uncertainty impact results. Our goals are to open new avenues for improving how elections are forecast, to increase understanding of the results that are reported by popular news sources, and to illustrate the value of data-driven forecasting using dynamical systems  .
After revision:  Our results for the 2012 and 2016 U.S. races for president, Senate, and governor. Although contagion and voting dynamics differ, our work suggests a new approach to elucidate how elections are related across states. It also illustrates the effect of accounting for uncertainty in different ways, provides an illuminating example of data-driven forecasting using dynamical systems .