If late-campaign polls are to be used as forecasts, it is important to ask, how well do the polls do and why are some polls better forecasts than others? We analytically compare alternative methods for estimating the systematic bias in the election trial heat polls of the individual polling houses and of the polling industry as a whole. We put each technique to the test using data from the 2004 US Presidential election. From the collection of evidence we are able to identify the approach that produces the most efficient unbiased estimates and answer the question of how the polls did in 2004. A third of the houses exhibited large and significant biases, but the industry as a whole converged on the truth.