My favorite Javy Baez moments in no particular order and other fun El Mago moments, a thread 🧵 Go ahead homer in Game 1 of the 2016 NLDS.

do you readers a favour and make a table like this in methodology papers

Re-reading Lundberg et al. which I always assign in the first week of intro methods. It's so polite, but its core point amounts to the most savage of critiques: studies should be very precise about the question they are trying to answer, but that usually doesn't happen.

I enjoyed this interview and discussion about my work at Tufts in support of ideological diversity.

I wonder what part of the argument you agree or disagree with? Our arguments about calibration are directly applicable to your "bet" standard. Regardless of who won that bet we still wouldn't know who was a better forecaster, which is our point!

Justin Grimmer Nate Silver My go-to example: coin is tossed one time, and while in the air, one modeler says the probability of heads is 0.99. The other says it is 0.95. It comes down heads. What information do you have to make the decision as to who is better at modeling?

Does the private sector have more presidential elections than academics?

We engage with some of these points in the blog post, but some very interesting points here.

In POLITICO, Hoover Institution senior fellow Justin Grimmer challenges the reliability of current #election forecasting models and highlights potential negative impacts they may cause in #voter behavior. politico.com/news/magazine/…