Earlier quoted context omitted.
You're comparing two scenarios, one in which you know all the facts, and one in which you don't. In the dice toss scenario, we know everything relevant. In the election scenario, we don't. A model like this is attempting to say "these are the rules we think exist. Based on the rules, and assuming the data is off by some random distribution, here's what we think could happen". What different forecasters disagree about…
I will veer this off into the dreaded political territory even though this is mostly a technical discussion. The Democratic Party proved it was not as progressive as they thought as Sanders lost the primary. The reality is, the country as a whole is also not as liberal either, regardless of what these pollsters are asking people. You think the party is youthful, and ready for progressive ideas, but alas, the party wh…
Well Nate Silver wrote a full critically acclaimed book about why these types of forecast are more useful (and accurate) in reality because they account for uncertainty - he has been doing this for years, ever since he used to write similar algorithms to help bookies pick odds for sporting events, so I think your hot take isn’t based in any world of facts or knowledge on this.
Don’t trust a forecaster that says with certainty that a certain candidate will win, unless they have also bet their life’s earnings on it. Showing your statistical confidence level isn’t a bad thing.