The model showed promising results, demonstrating an R2 value of .82 – indicating that it explained about 82% of the variance in electoral vote totals. This value is only slightly lower than the sophisticated model developed by researchers at Facebook and Google.
The model can be used to estimate vote totals in swing districts and to help determine the potential impact of funding on election results. The same methodology could be adapted for use in state or local voter models.
Code for the model can be found at Dr. Brodsky’s GitHub repository here.