You could reasonably conclude someone has 80% chance to win by using a large amount of slightly lopsided data, or you could reasonably conclude the same thing with a smaller amount of highly lopsided data.
As such there is a relationship involving the probability of the outcome, the quantity of the polling data, the quality of the polling data, and the margins of the polling data.
At the time I wasn't aware that Nate had published his predicted margins. So, seeing he had a high probability for Obama in Virginia, which turned out to be close, I concluded that one of three things was true:
1. Virginia was very heavily polled and there was just a ton of good and consistent data, justifying a prediction of 80%.
OR 2. Virginia had a normal amount of good and consistent data, but it was all very lopsided.
OR 3. There was an error with Nate's model or with the data.
Had I known that I could have easily accessed his predicted margins I could have easily seen that it was 1. But without knowing that, I was ruling out 2 because it turned out the state was very close.
My point was that it's not easy to just look at Nate's map and score it against the result map. That's a very shallow and fairly uninteresting way to look at it.
My secondary point was that even if you understand that he had predicted some percentage chance to win in each state, it's not even easy to look at that percentage chance and score it against the result map, because, given a prediction like "80% chance Obama wins", there are many different ways he could have arrived at his conclusion, and it would be more accurate to inspect the method by which he arrived at the conclusion compared to the margins in the state.
I've put up a text file comparing the two here: http://pastebin.com/0RB5GRjQ and it turns out the results were within Nate's given interval in 49 of 50 states. It's not the shallow and misleading "50/50" you get by just comparing the color of Nate's map with the results map -- but I think it's much more interesting, more accurate, and more impressive.
As such there is a relationship involving the probability of the outcome, the quantity of the polling data, the quality of the polling data, and the margins of the polling data.
At the time I wasn't aware that Nate had published his predicted margins. So, seeing he had a high probability for Obama in Virginia, which turned out to be close, I concluded that one of three things was true:
1. Virginia was very heavily polled and there was just a ton of good and consistent data, justifying a prediction of 80%. OR 2. Virginia had a normal amount of good and consistent data, but it was all very lopsided. OR 3. There was an error with Nate's model or with the data.
Had I known that I could have easily accessed his predicted margins I could have easily seen that it was 1. But without knowing that, I was ruling out 2 because it turned out the state was very close.
My point was that it's not easy to just look at Nate's map and score it against the result map. That's a very shallow and fairly uninteresting way to look at it.
My secondary point was that even if you understand that he had predicted some percentage chance to win in each state, it's not even easy to look at that percentage chance and score it against the result map, because, given a prediction like "80% chance Obama wins", there are many different ways he could have arrived at his conclusion, and it would be more accurate to inspect the method by which he arrived at the conclusion compared to the margins in the state.
I've put up a text file comparing the two here: http://pastebin.com/0RB5GRjQ and it turns out the results were within Nate's given interval in 49 of 50 states. It's not the shallow and misleading "50/50" you get by just comparing the color of Nate's map with the results map -- but I think it's much more interesting, more accurate, and more impressive.