Quote:
Originally Posted by Citrus Dad
It's been known that OPR doesn't reflect actual scoring ability. It's a regression analysis that computes the implied "contribution" to scores. Unfortunately no one ever posts the estimates' standard errors (which I imagine to be enormous with 10 or so observations.)
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Quote:
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I'm thinking of the parameter standard errors, i.e., the error estimate around the OPR parameter itself for each team. That can be computed from the matrix--it's a primary output of any statistical software package.
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The second quote above is from a dialog I've been having with Citrus Dad, and I have his permission to post it here.
I'd like to hear what others have to say.
Do you think the concept of standard error applies to the individual computed values of OPR, given the way OPR is computed and the data from which it is computed?
Why or why not?
If yes: explain how you would propose to compute the standard error for each OPR value, what assumptions would need to be made about the model and the data in order for said computed standard error values to be meaningful, and how the standard error values should be interpreted.