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 is what the rules are. For example, the relevance of certain demographic characteristics and the potential variance between polling (conducted prior to the election) and actual election results.
There's a huge amount of assumptions, and forecasters disagree on those assumptions. We have very little historical data (polling is very recent) and even with complete historical data, future elections do not always conform to past elections.
