[Oblarg]

Originally Posted by wgardner

The second is the error in measuring the actual, underlying OPR value (if you buy into the linear model). If teams actually had an underlying OPR value, then as teams play 10, 100, 1000 matches the error in computing this value will go to zero.

Unfortunately, this is tenuous - there's no real reason to believe that each team contributes linearly to score by some flat amount per match, and that variance beyond that is a random variable whose distribution does not change match-to-match.

If one were to assume that this is actually the case, though, then one would just take the error from the first part and divide it by sqrt(n) to find the error in the estimation of the mean.