Sampling errors are random, and expected. Other types of misses are not simple "errors" but polling flaws, like sampling a non-representative group, ignoring non-responders or assuming they break the same as the responders, asking poorly-worded questions, etc.
Occasional flaws in polling is understandable and tolerated. But when those misses repeatedly line up the same way, and are rather sizeable, that's evidence of either systematic flaws, or outright bias.
I'm not sure what a "sampling error" is. To echo the sibling poster, per-state sentiment is not normally distributed. For example, we know Trump is more popular among white men than other demographics. This means that if we were to create a random variable that reflected the sentiment of white men throughout the US, we would (probably though I'd have to dig deeper into the data) presume to see a higher median vote count in this demographic. However, we cannot say that Trump's popularity in Massachusetts is independent from his popularity in New York, because his popularity in the white male demographic is the dependent variable between both random variables.
I was discussing in good faith, so I'm not sure why you chose to be snarky. Let's clarify here, I'm not sure what "sampling error" in this case would be, such that it is distinct from electoral trends at large. The random variables in question _are_ demographic groups. How is it meaningful to discuss sampling error if your assumption is that state and county data is independently distributed? The poll data that Gelman et al used is public data, I urge you to take a look and work with it.
Occasional flaws in polling is understandable and tolerated. But when those misses repeatedly line up the same way, and are rather sizeable, that's evidence of either systematic flaws, or outright bias.