  Existing approaches for estimating home-field advantage (HFA) include
modeling the difference between home and away scores as a function of the
difference between home and away team ratings that are treated either as fixed
or random effects. We uncover an upward bias in the mixed model HFA estimates
that is due to the nonrandom structure of the schedule -- and thus the random
effect design matrix -- and explore why the fixed effects model is not subject
to the same bias. Intraconference HFAs and standard errors are calculated for
each of 3 college sports and 3 professional sports over 18 seasons and then
fitted with conference-specific slopes and intercepts to measure the potential
linear population trend in HFA.
