  Recording of events in National Hockey League rinks is done through the Real
Time Scoring System. This system records events such as hits, shots, faceoffs,
etc., as part of the play-by-play files that are made publicly available.
Several previous studies have found that there are inconsistencies in the
recording of these events from rink to rink. In this paper, we propose a
methodology for estimation of the rink effects for each of the rinks in the
National Hockey League. Our aim is to build a model which accounts for the
relative differences between rinks. We use log-linear regression to model
counts of events per game with several predictors including team factors and
average score differential. The estimated rink effects can be used to reweight
recorded events so that can have comparable counts of events across rinks.
Applying our methodology to data from six regular seasons, we find that there
are some rinks with rink effects that are significant and consistent across
these seasons for multiple events.
