In this summer’s look at sabermetrics and hockey, I have recently introduced the concept of zone starts. This is the tabulation of the number of times a player is on the ice for a faceoff in a given zone on the ice (offensive, neutral or defensive) over the course of the season. In order to see the correlation of these numbers with Corsi Numbers, these zone start numbers are restricted to 5 on 5 situations. The raw data has been tabulated by Vic Ferrari at Irreverent Oiler Fans.
Today I will present the list of the 20 players who were most preferentially used in defensive situations. These are the twenty players who were on the ice for the most defensive zone faceoffs minus offensive faceoffs.
In this summer’s look at sabermetrics and hockey, I have been looking at the Corsi Number. I have published top 20 and worst 20 adjusted Corsi lists with Corsi Number treated as both a counting stat and a rate stat. Here are the top 20 and worst 20 adjusted Corsi numbers as a counting stat and the top 20 and worst 20 adjusted Corsi numbers as a rate stat. It is clear that the players who made the top 20 lists were players who excelled in the situations that they played and those who were on the worst 20 lists failed in their situation. However, it is not clear how tough the role they played on their team was. One piece of the context, which helps to interpret if the player failed because they are not NHL calibre players or because they played in a tough role in which it would be hard for any player to excel is important to try to make sense of Corsi Numbers, is which zone they tended to take faceoffs in.
In this summer’s look at sabermetrics and hockey, I have been looking at the Corsi Number. The Corsi Number is the difference in the number of shots directed at the net (shots on goal, blocked shots and missed shots) taken by a team while a given player is on the ice and those taken by his opponents in five on five situations. I recently gave the top 20 adjusted Corsi rates. This is a list of players who excelled in the roles that they played last season. Today, I am listing the worst 20 adjusted Corsi rates. The adjustment method involves calculating a player’s Corsi rate while he is on and off the ice and subtracting them to get the adjusted rate attributed to a given player. This is similar to the adjustment that behind the net does with on/off ice adjusted +/- ratings.
Here are the 20 worst adjusted Corsi rates from 2008/09 among players with 50 or more games played:
In this summer’s look at sabermerics and hockey, I have been looking at the Corsi Number. The Corsi Number is the difference in the number of shots directed at the net (shots on goal, blocked shots and missed shots) taken by a team while a given player is on the ice and those taken by his opponents in five on five situations. I have given the top 20 and worst 20 adjusted Corsi Numbers found when treating Corsi as a counting number (total over the entire season). A similar adjustment can be done as a rate stat (per minute of ice time). The main difference between these adjustments is that players who succeed, but in lesser roles on teams are more likely to be found at the extremes of the ratings.
Here are the top 20 adjusted Corsi rates from the 2008/09 season among players with 50 or more games played:
The New York Rangers were the third lowest scoring team in the NHL last season. They averaged 2.44 goals per game, finishing barely ahead of the Colorado Avalanche and New York Islanders. Improving the offence in New York should be a priority. The highest scoring player who finished the 2008/09 season as a Ranger was Nik Antropov, who was acquired on trade deadline day from the Toronto Maple Leafs. His 59 points led the Rangers. Antropov left the team as a free agent when he signed with the Atlanta Thrashers.
Among players who spent the entire 2008/09 with the Rangers, Scott Gomez and Nikolai Zherdev led the team in scoring with 58 points. Both of them are gone. Gomez was traded to the Montreal Canadiens. The biggest scorer from last season acquired in return was Chris Higgins, who is coming off a 23 point year. Zherdev won’t be back with the Rangers either. They have walked away from his $3.9 salary arbitration award to allow him to become an unrestricted free agent. Last year’s three top point scorers on the lowest scoring playoff team will not be back. How can that be a step forward?
This summer in my look at sabermetrics and hockey, I have been looking at the Corsi Number. They are a good judge of puck possession that is much like +/-, although it comes with different strengths and different weaknesses.
I have ranked the best 20 and worst 20 player adjusted Corsi Numbers. This ranking is done treating Corsi as a counting stat accumulated over the season. It can also be looked at as a rate stat and ranked per minute of 5 on 5 ice time played. To that effect, I have listed the top 20 Corsi rates from 2008/09. Today, I look at the worst 20.
This summer in my look at sabermetrics and hockey, I have been looking at the Corsi Number. They are much like +/- ratings, except since they include all shots directed at the goal (including missed shots and blocked shots) they give much larger numbers with less random fluctuations in them, They show who is driving puck possession (those players with good Corsis) and remove the element of goaltending from +/-. When players play defensive roles that do not drive puck possession, their Corsi is not always a good method of rating their play (with the best example of this being Jan Hejda). Thus far, I have only looked at Corsi Numbers treated as counting numbers and not as rates (per minute). This is how they are treated at behind the net.
Here are the top twenty players (with 50 games played or more last year) ranked by Corsi per minute of 5 on 5 play:
Probably the least logical results I have found in this summer’s look at sabermetrics and hockey surround Jan Hejda of the Columbus Blue Jacket. Hejda was among the Columbus Blue Jackets leaders in ice time with over 22 minutes played per game. He is not an offensive star as he contributed only 21 points last season. Most of his value is defensive.
If we look at the top 20 adjusted +/- ratings from last season, we find Hejda’s +19.4 is good for sixteenth best in the league. That is a clear sign that he has been a good player. However, if we look at the worst 20 adjusted Corsi Numbers from last season, we find Hejda’s -155.8 is nineteenth worst in the league. That suggests he has been a bad player and clearly contradicts his +/-. How can that be?
In this summer’s look at sabermetrics and hockey, I have been looking at the Corsi Number as an alternative to +/- ratings. Today, I am listing the worst 20 adjusted Corsi ratings from 2008/09. The adjustment is done in the same manner developed for +/- ratings in The Hockey Compendium by Jeff Klein and Carl-Eric Reif. I discuss this adjustment method here. In this method, a team adjustment is calculated from team Corsi Numbers. Since five players are on the ice, team Corsi Numbers are divided by five to give a baseline team value that is treated as a “zero” for that team. All individual player Corsi Numbers have the team adjustment subtracted off.
Here are the worst 20 adjusted Corsi Numbers from the 2008/09 season among players who played at least 50 games and with only one team:
When I listed the players with the worst 20 Corsi Numbers last season, the list included a lot of defencemen who play on bad teams against top competition and usually start their shifts in the defensive zone. This of course is a contributing factor to their poor Corsi numbers. Copper N Blue notices this and points it out. He criticizes me for listing the players with the worst Corsi Numbers, suggesting that it will provide ammunition to the “anti-numbers” crowd. There are people who do not want to believe that statistics and math can be used to understand hockey and would just like it all to go away. It is obvious that statistical analysis has made significant in roads to hockey, so it isn’t going away. It also isn’t clear that hockey can ever be solved on the level of baseball, but that is a goal - even if it is unattainable. This aspect of the game has little effect upon your viewing of a game, unless you want it to. There is no reason you have to know anything about statistics to view a game.
About The Puck Stops Here
Who am I? A diehard hockey fan.
Why am I blogging? I want to.
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