[wgardner]

And now for the data where the single testing point was removed from the training data, then the model was computed, then the single testing point was evaluated, and this was repeated 80 times. So the results below are for separate training and testing data.

Stdev of prediction residual of the winning margins:
OPR: 34.6
CCWM: 30.5
WMPR: 30.4

(note that on the testing data from a few posts ago, WMPR had a Stdev of 15.9, so this is an argument that WMPR is "overfitting" the small amount of data available and that it could benefit from having more matches per team)

# of matches predicted correctly (out of 79 possible)
OPR: 63
CCWM: 55
WMPR: 58

So here, the WM-based measures are both better at predicting the winning margin itself but not at predicting match outcomes. CCWM and WMPR have almost identical prediction residual standard deviations but WMPR is slightly better at match outcome prediction in this particular example for some reason.

Again, it would be great to test this on some 2014 data where there was more defense.