One of the important background dimensions to comparative baseball statistics is known as “park adjustments,” a set of corrective factors applied to account for the physical differences (e.g., outfield wall depth) between each park. Among American sports today, only Major League Baseball and NASCAR (and golf, I suppose) permit such structural variation between the competitive arenas themselves.

Professional hockey used to be in that group too. More than merely adjusting, adding, and subtracting lines on the ice to affect the flow of play, as the NHL continues to do (cf. the NBA three-point line), the rinks themselves used to be different sizes. League rules mandate a uniform rink size, but so-called “small rinks” persisted in the NHL as late as the 1980s and 1990s in Boston, Chicago, and Buffalo.

While hockey does not face the structural differences present in baseball, there still is a need to apply rink-by-rink statistical adjustments. That’s because the compiling of basic hockey statistics (e.g., shots, hits, turnovers) requires statisticians to make judgment calls to a more significant degree than in a discrete-event sport like baseball.

By way of limited background, the NHL collects basic gameplay statistics through a computer system known as the Real Time Scoring System (RTSS). A benefit of RTSS is that it aggregates and organizes data for analysis by teams, players, and fans. A vulnerability of RTSS is the subjectivity alluded to above that comes when human scorers track a fluid, dynamic sport like hockey.

While others have noted certain biases among the RTSS scorers at different rinks, a paper by Michael Schuckers and Brian Macdonald published earlier this month analyzes those discrepancies across a spread of core statistics and proposes a “Rink Effects” model that aims to do for subjective rink-to-rink differences in hockey scoring what park adjustments do for structural differences between baseball parks.    Continue reading →