Getting a Bang for Your Buck: 2022 State Legislative Elections

Hello, once again! During the Virginia elections last year, we introduced a feature called the “Bang For Your Buck” model, identifying which districts in the Virginia House of Delegates are the best ones to donate to. This is exclusive content only available to our paid Substack subscribers. For 2022, we are delighted to announce that we are expanding this model to include races nationwide, which will also contain mini-models or “focuses” for individual states. This new and improved version of Bang For Your Buck utilizes 5 primary input metrics for the calculation of the investment value for an individual district, with a modifier value for the number of competitive seats in a chamber applied at the end. In this article I’ll go over these metrics, why we’ve chosen them, and what weight is assigned to them.

Chamber Rating 

The chamber rating modifier is an essential variable, and as such it is weighted at 27.5%. The logic to this metric is simple: if a chamber isn’t highly competitive, a heavy investment is unlikely to affect the odds and this variable will lower the overall investment value as a result. This variable ranges from a value of 57 to 200, with 200 being the maximum value set within the 45-55% win chance region.

District Rating

The next essential variable is the district rating, which is also weighted at 27.5%. “Toss-Up” districts will be given the maximum value of 200 for this metric, going down to 37.5 for “Very Likely” districts. Competitive districts are more worthwhile to invest in, especially compared to a district that has a history of being relatively “safe”. 

District Rating Tipping Point

Another metric we use that is similar to the district rating modifier is the district rating tipping point modifier. This metric looks at the median district in a state and compares the rating of the indicated district to the aforementioned median. For example, if the tipping point for control in a certain chamber is “Lean R,” this metric will give the highest weight to districts in that chamber which are also “Lean R.” We’ve included this metric because the tipping point district is ultimately what will determine which party controls a chamber, and knowing how close a district is to changing hands is important information when it comes to making investments. We give this metric a weight of 20%.


Fundraising metrics are often excluded from consideration when it comes to determining which districts are the most and least important to invest in. If a district is overinvested, it’s unlikely that throwing more money at a campaign will impact the outcome as much as a district that is underinvested. As a result, this metric ends up being the only “input” metric which will generally contribute a negative value towards the overall investment value (in some cases, however, it can be positive for severely underinvested races). Since different states have different district sizes, this metric is performed on an individual basis. We then compare this metric to the median money raised per person for all of the ~330 districts in this model. This metric is, however, somewhat in flux. There aren’t many fundraising metrics to refer to as of right now, and as a result, this variable will likely change in form and weight over time. Currently, this metric is weighted at 15%. 

Presidential Tipping Point

We know what you’re thinking– why would we include presidential results in a metric such as this? However, given the fact that these will all be new district lines, normal incumbency effects are more difficult to account for. Including how close a district is to the tipping point based on the 2020 Presidential election is a way to get somewhat of a partisanship baseline relative to the rest of the state, which we feel is important to consider. However, since this metric cannot account for the differences between federal and state legislative elections, this metric is only weighted at 10%.  

Competitiveness Modifier

This last modifier is applied to the overall investment value in a state after the above 5 values are calculated and weighted. While developing this model, we realized that Maine’s House of Representatives dominated the top ~20 districts for overall investment value. This was because of Maine’s rating as a “Toss-Up” chamber and numerous “Toss-Up” districts. Any single Maine State House seat is arguably not the most important district in the nation to invest in because of all the other options for competitive races in the chamber. As a result, we included a modifier that ranges from 0.6 to 1.0, effectively lowering the rating if there are a large number of competitive seats in a given chamber. It’s a way of saying, “Sure these are all ‘Toss-Up’ races in a ‘Toss-Up’ chamber, but there’s 30 of them and they have 10,000 people each!”. None of these seats on their own are essential to the overall chance of control for a chamber.