I (i.e., David Rothschild) live in constant regret for spending way too much time in 2016 worrying about who was going to win, and way too little about what information that I could produce that would actually be useful for a well-functioning democracy. That is why for 2018, I (along with my partner Tobias Konitzer) shifted the focus of PredictWise completely: less horse-race and more policy. 

I continue to enjoy exploring MSN‘s polling module, and we have done some very interesting work in 2018 learning how the polling data can enhance understanding of the MSN users. But, MSN polling also offers one simple and exciting attribute: the ability to do repeated, fast polling, at scale. 

We spent the last few cycles doing academic research on politics, pushing the boundaries of both methods (data collection, analytics, and consumption) and domain understanding (mapping public opinion, the effect of advertising, and news). And some of this work has had an impact on how actual practitioners create and use data around politics. 

As you have seen elsewhere, PredictWise’s track record when it comes to horse race predictions is, to say the least, very good. In general, there is a number of key cornerstones to successful predictions