I’ll have a longer post about this over at Primary Colors with examples of different types of news events our data will provide useful insight on for journalists, but here’s a quick example from my run-down of the 2014 primaries to watch.
In MI-14, you have the incumbent Congressman running for US Senate, and an open seat primary to replace him. Naturally, people are interested in the question of how liberal or conservative the next member will have to be to win the district.
Up until now, there hasn’t been a good basis for anchoring that discussion. But now the analysis can be contextualized in terms of the district, rather than the ideological preferences of the departing MOC:
The departing member’s information is included for reference, and their ideological data appears in the next three columns – their Primary Score (where 0 is a good liberal and 10 is too conservative), their Actual Score (how often they vote with progressives) and their Expected Score (how often we’d expect a MOC from a district like this to vote with progressives).
This is key because seeing the departing MOC’s scores can help anchor expectations for the new candidates running for the seat. Maybe the departing member was unusually conservative, as in the case of Gary Peters in MI-14. The candidates running to replace Peters might think they have to vote as conservatively as Peters did, but in reality, an MOC representing a D+29 district would be expected to vote with progressives about 92.2% of the time. Peters only voted with progressives 74.2% of the time: