I see the statistic XFIP being thrown around a lot on the boards, as a "true" measure of what a pitchers ERA should be. Statements like " with an ERA of 2 and an XFIP of 4, Pitcher x is due for a regression".
Up front, I don't like the idea of XFIP at all. Ground balls count as hits too, I don't think walks matter as much, and I don't think strikeouts are as important as people make them out to be.
I am open-minded, so I wanted to test how well XFIP was at predicted next month's ERA as a way to test.
The formula I used for XFIP was the one listed here : http://www.fangraphs.com/library/pitching/xfip/
xFIP = ((13*(Fly balls * lgHR/FB%))+(3*(BB+HBP))-(2*K))/IP + constant
I used the 2014 constant for Lghr/fb% of 9.50%. I used 3.10 as the constant in the second part of the equation. Using a sample size of 64 starting pitchers, selected based on having pitched over twenty innings per month from April to September, using 2014 season as the data for the test.
I tested two ways, termed short term reversion and long term reversion.
Short term reversion would be last months XFIP compared to this months ERA. So for June, it would be June ERA-May XFIP = Prediction Error
Long Term Reversion= Average of monthly values up to that point, so for June it would be June ERA-(April XFIP+MayXFIP)/2
Short Term Reversion Results
XFIP ERA
Average 1.325 1.444
Std Deviation .44 .589
Count 38 26
Average is average error. Std Deviation is the standard deviation of total average errors between pitchers, count if the number of pitchers that XFIP was more accurate on.
Technically, based on this data, they are not incorrect when they say it is more accurate at predicting future era. However, it only outperforms last months ERA by an average of .12, which is less then the deviation of errors between pitchers. I would be cautious relying on this to predict future era results, because the results of this test show it to be inconclusive.
Long Term Reversion
XFIP ERA
Average 1.25 1.30
Std Deviation .387 .43
Count 37 27
Again, technically, it is slightly better than ERA. However, it is the same situation, the gain is approximately .05 runs more accurate. The difference is even less in magnitude using the cumulative average.
Based on these results, I would be cautious about drawing conclusions of a pitchers future performance based on XFIP.