Sunday, August 9, 2009

Corsi corrected for Starting Shift Location

As a general rule, a player's Corsi number is a reasonably good indicator of his ability to drive territorial play at even strength.

Having said that, it's easier for some players to accrue a good corsi number than others.

For example, a player that plays on a good team, shares the ice with good linemates, and plays against weak competition is greatly advantaged over a player that plays on a poor team, shares the ice with poor linemates, and plays tough minutes.

Another factor that influences Corsi is starting zone location at even strength. That is, a player that starts his shifts more frequently in the offensive zone will, on average, have a better Corsi number than a player that starts his shifts more frequently in the defensive zone.

The purpose of this post is to attempt to correct for this.

As reported by Vic Ferrari in this post, each extra starting Offensive Zone Faceoff a player takes at even strength is worth approximately 0.6 Fenwick, where Fenwick is equivalent to [SHOTS FOR + MISSED SHOTS FOR] - [SHOTS AGAINST + MISSED SHOTS AGAINST].

Of course, the correction factor for Corsi will necessarily be larger due to the inclusion of blocked shots.

A brief analysis indicates that, at the level of individual players, the ratio of Fenwick to Corsi is approximately 0.75.

Considering that 0.6/0.75=0.8, the appropriate correction factor in respect of corsi would be about 0.8.

Thus, in adjusting each player's corsi to reflect starting zone location, I applied the following formula.

{CORSI + [(STARTING D-ZONE SHIFTS - STARTING O-ZONE SHIFTS)* 0.8]}

However, in order to give a more accurate representation of each player's abilities, I thought it necessary to control for ice-time as well.

Not having the EV ice-time handy, I merely used each player's starting EV shift total as a proxy for EV ice-time.

I then multiplied the resulting figure by 1000 in order to make the data more presentable.

Thus, the complete correction formula used was as follows:

{CORSI + [(STARTING D-ZONE SHIFTS - STARTING O-ZONE SHIFTS)* 0.8]}*1000
____________________________________________
[D-ZONE STARTING FACEOFFS+O-ZONE STARTING FACEOFFS+NEUTRAL ZONE STARTING FACEOFFS]

So, essentially, it's corsi adjusted for zone location, divided by total starting EV shifts, multiplied by 1000.

I then sorted the results by team and have presented below the five best and five worst players on each team.

And for the Eastern Conference:

Overall, I'm pretty satisfied with the results of this exercise. The numbers are pretty reasonable and basically accord with my subjective sense of which players are good and which players are not.

Some observations:

• some of the more unusual results are explainable through quality of competition (see: Columbus, Anaheim)
• a lot of the players that fare poorly are young players or 4th line forwards
• Colby Armstrong is a very good and very underrated player; likewise for Tyler Kennedy
• Paul Ranger might be his team's best all-around player
• some players that changed teams mid-season show up on multiple lists (Vermette, Kunitz, Wisniewski, Kalinin, Ja.Williams)
• one Kostitsyn brother is apparently much better than the other

EDIT: It appears that Matt at BattleofAlberta did a similar exercise for the Flames mid-way through the 2008-09 NHL season.

Sunny Mehta said...

"Not having the EV ice-time handy, I merely used each player's starting EV shift total as a proxy for EV ice-time."

i think Behind the Net has individual player corsis listed per 60 min.

JLikens said...

Yeah, that's a good point.

I'd just have to aggregate the 5-on-5 data with the 4-on-4 and 3-on-3 data.

Olivier said...

Behindthenet is troublesome when it comes to players on multiple teams tough.

Kent W. said...

Thanks for this. Really good stuff.

Anonymous said...

Great analysis. I was wondering if you have data for all the players on each team, and if so could you send it to me? thrashersrecaps@gmail.com

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JLikens said...

Thrashers Recaps:

I just realized that I used 0.75 instead of 0.8 as the correction factor.

After I've corrected the data, I will send you the spreadsheet.

Anonymous said...

Awesome! Thank you. This data could be very valuable to people looking to do their own analysis, have you thought about posting it to download from your blog?

Olivier said...

I was tinkering those data, and I was wondering if shots wouldn't be a better proxy than faceoffs for icetime?

I guess it all comes down to the fact that I'm too lazy to run some correlation test...

JLikens said...

"I was tinkering those data, and I was wondering if shots wouldn't be a better proxy than faceoffs for icetime?

I guess it all comes down to the fact that I'm too lazy to run some correlation test..."

They'd both be fairly good, I'd imagine.

Come to think of it, nhl.com actually has even strength icetime data for individual players. I probably should have just used that.

Anonymous said...

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Host Pay Per Head said...

I didn't know that Cursi can be that effective to know all that. I expected that it has its flaws.