We are very fortunate a paper that I wrote with a former student, Jim Curro, accepted to the MIT Sloan Sports Analytics Conference Research Paper Competition.  The paper presents a  new ratings system which we think is an improvement over the current approaches.  It creates a two-way (offense and defense combined) rating that isolates the impact of an individual player by adjusting for home ice, the quality of competition, the quality of teammates and where a player starts their shifts.  We assess the impact of a player on every play the NHL records in a season using a statistical method called ridge regression to account for the factors listed above.  The resulting ratings for a specific player tell us how many wins above or below an average NHL player they are.

Here is the abstract of that paper:

Hockey is a fluid sport with players frequently coming on and off the ice without the stoppage of play.  It is also a relatively low scoring sport compared to other sports such as basketball.  Both of these features make evaluation of players difficult.  Recently, there have been some attempts to get at the value of National Hockey League (NHL) players including Macdonald [1], Ferrari [2], and Awad [3].  Here we present a new comprehensive rating that accounts for other players on the ice will a give player as well as the impact of where a shift starts, often called zone starts, and of every non-shooting events such as turnovers and hits that occur when a player is on the ice.  The impact of each play is determined by the probability that it leads to a goal for a player’s team (or their opponent) in the subsequent 20 seconds.  The primary outcome of this work is a reliable methodology that can quantify the impact of players in creating and preventing goals for both forwards and defenseman.  We present results based on all events from the 2010-11 and 2011-12 NHL regular seasons. 

 The full paper is available here.