This article is the second of a two part series evaluating 2011 baseball player forecasts. The first looks at hitters and found that forecast averages outperform any particular forecasting system. For pitchers, it appears as though the results are somewhat reversed. Structural forecasts that are computed using “deep” statistics (k/9, hr/fb%, etc.) seem to have done particularly well.
As with the other article, I will look at two main bases of comparison: Root Mean Squared Error both with and without bias. Bias is important to consider because it is easily removed from a forecast and it can mask an otherwise good forecasting approach. For example Fangraphs Fan hitter projections are often quite biased, but are very good at predicting numbers when this bias is removed.