I guess there could also be a split-the-ticket effect, though McCain (perhaps generously) hasn’t made that case. In any event, this is easy enough to model.

I think this is the first time your projected electoral vote (364 vs. 174) has given Obama a better than 2:1 ratio (359 vs. 179). I’ve seen 350 used as the “landslide” threshold, but a 2:1 ratio would seem to be a cleaner definition for a landslide…

There is also this “coattail” effect you claim, but Democrats’ median expectation is a gain of 7 Senate seats based on polls alone. I haven’t looked into whether there is good evidence for a Presidential campaign drawing a result away from empirical polls.

In predicting the Senate, one question is whether the coattail effect is fully captured by the Senate polls or whether the Senate poll result should be adjusted in the direction of the Presidential poll result of that state.

MEV is probably most useful as a predictive metric; it is certainly the right thing to look at the day before the election. However, as Sam wisely pointed out at the start, this is a descriptive analysis, not a predictive one. This discussion convinces me that MM is the right metric for tracking.

I am currently developing an interest in Senate and House predictions. As of today it’s 3:1 in favor of a 58-42 split in the Senate, with most of the remaining probability in 57-43. For now, a 60-40 split is about 90000:1 against. I have not yet tackled the large task of sifting through House race data.

If your EV distribution on election eve were similar to the one at noon today, what would your prediction be? The lower median with low prob, or the higher mode with much higher prob?

(1) and (2) are especially helpful considering the challenges of the coming few years. (3) is hard in the Senate because Obama/Biden trail the Democratic candidate in close races in Georgia, Mississippi, and Kentucky. I’ll guess that the closing moves will involve winning marginal House races in blue states.