I enjoy working with statistics, and data, and spreadsheets. So, after all the recent talk of a “blue wave” this fall, I wanted to see just how much of a swing we would need across Kentucky to take back the Kentucky House. In this post, I’ll share what I found, as well as the spreadsheet I used, so you can run your own scenarios.
First, some caveats:
- I used the 2016 results as a starting point. This means that if there was no Dem opponent in a district, then the Repub will always win, no matter what swing percentage you set. And by the same token, if there was no Repub opponent, then the Dem will always win, no matter how much negative swing you put in. (Yes, you can model a Republican wave as well.)
- The percentage swing you enter is applied to every race; you don’t model races individually. I could have set it up that way, but I wanted just a simple state-wide model that would be easy to grasp.
- The model is based on straight percentages, and doesn’t take into account factors like turnout, funding, or anything else. It just answers a simple question: What statewide swing percentage, if applied evenly, would flip the House?
The spreadsheet for you to view
Here is the Google Sheets version of the spreadsheet, in a view-only mode. As you can see, a 15% Dem swing in each district results in a 51-49 Dem majority in the House.
Specifically, it flips these districts: 8, 11, 13, 15, 24, 33 (my district!), 48, 49 (already flipped), 74, 78, 81, 91, 92, 95, 98
What’s striking about many of these districts is how small the Repub winning margin was in 2016. Scan down that list and you’ll see seats where the Repub won by less than 10% of the vote.
Try your own models
I’ve not tried this before with a large group, so if this doesn’t work well, my apologies.
Below is a link to the Google Sheet, with one limitation: the only cell you can edit is the swing percentage number at the top. You don’t have to type the percentage sign; just put in the percentage of state-wide swing, and see what happens.
And let me know if you found this interesting, or helpful, in the comments. AND, if you have other analysis you’d like to see, throw those ideas in the comments as well. Enjoy!
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