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His model has always been closer state to state, election to election than anyone else’s, which is why people use his models. He is basically using the same model and tweaking it each time, you make it sound like he’s starting over from scratch. When Trump won, none of the prediction models were predicting he would win, but his at least showed a fairly reasonable chance he could. His competitors were forecasting a much more likely Hillary win while he was showing that trump would win basically 3 out of 10 times. In terms of probability that’s not a blowout prediction. His model was working better than competitors. Additionally, he basically predicted the battleground states within a half percentage iirc, that happened to be the difference between a win/loss in some states.
So he has exactly one chance to get it right.
You’re saying it hitting one of those 3 of 10 is “getting it wrong”, that’s the problem with your understanding of probability. By saying that you’re showing that you don’t actually internalize the purpose of a predictive model forecast. It’s not a magic wand, it’s just a predictive tool. That tool is useful if you understand what it’s really saying, instead of extrapolating something it absolutely is not saying. If something says something will happen 3 of 10 times, it happening is not evidence of an issue with the model. A flawless model with ideal inputs can still show a 3 of 10 chance and should hit in 30% of scenarios. Certainly because we have a limited number of elections it’s hard to prove the model, but considering he has come closer than competitors, it certainly seems he knows what he is doing.
I think you’re missing the point of predictive modeling. It’s probability of separate outcomes is built in. This isn’t fortune telling, there is no crystal ball. Two predictive models can have different predictions and they both may have value. Just like separate meteorologists can have different forecasts, but predict accurately the same amount over time, all be it at different intervals. IIRC, the average meteorologist correctly predicts rain over 80% of the time. They are far over predicting by chance. But if you look at the forecast in more than one place you often get slightly different forecasts. They have different models and yet arrive at similar conclusions usually getting it mostly accurate. It’s the same with political forecasts, they are only as valuable as your understanding of predictive modeling. If you think they are intended to mirror reality flawlessly, you will be sorely disappointed. That doesn’t make the models “wrong”, it doesn’t make them “right” either. They are just models that usually predict a probable outcome.