Mark Rieke, a Data Scientist at Game Data Pros, recently launched an exciting side project that merges his professional expertise with a passion for political analysis. Rieke has developed a comprehensive forecast model for the upcoming presidential election, which will provide valuable insights into potential outcomes based on current data.

Rieke’s model, which builds upon The Economist’s 2020 election model, offers a nuanced analysis by mixing polling data with economic and approval metrics to generate state-level forecasts. This approach ensures a more granular understanding of the political landscape, especially in states with sparse polling data. The comparison point is a national popular vote forecast. State-level forecasts are preferred because the electoral map is biased toward Republicans, so they can win without winning the popular vote.

As Rieke explains, “Polling data is partially pooled across states such that we detect changes even in states with few polls.”

Rieke’s election forecast model is a fascinating example of how data science can be applied to real-world scenarios. To explore the project in detail, including national and state-level outputs, visit his original post: https://lnkd.in/gbxTGycu.

For those interested in delving deeper, Rieke provides a full breakdown of the methodology and access to the source code on his blog.