You never did much statistics, did you? Certainly your definition of "accurate" seems to me to mean something like "spot on or worthless", which seems incredibly restrictive.
Apariah - the final prediction for the 2016 US election, from fivethirtyeight.com, was that Hillary Clinton would win 48.5% of the popular vote, and Trump 44.9%. In the event, Clinton got 48.2% and Trump 46.1%. By most standards that's not a bad prediction. Unfortunately, the small miss had huge consequences in terms of the Electoral College, as Trumps "extra" votes were concentrated in a few states -- notably Wisconsin, Pennsylvania and Michigan.
As misses go, a small error has had huge consequences. But such is the nature of probabilistic methods. There is always the chance that you'll end up wrong, but that doesn't mean that your approach was flawed.