Relative Importance of a Players Impact on Teammate Shooting Percentage

A month and a half ago Eric T at NHLNumbers.com had a good post on quantifying the impact on teammate shooting percentage.  I wanted to take a second look at the relative importance the impact on teammate shooting percentage can have because I disagreed somewhat with Eric’s conclusions. For a very small number of elite playmakers, the ability to drive shooting percentage can be a major component of their value. For the vast majority of the league, driving possession is a more significant and more reproducible path to success. It is my belief that it is important to consider impact

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Quality of Competition in 5v5 Close Situations

I have been wondering about the benefits of using 5v5 close data instead of 5v5 when we do player analysis and player comparisons.  The rationale for comparing players in 5v5close situations is that we are comparing players under similar situations.  When teams have a comfortable lead they go into a defensive shell resulting in fewer shots for but with a higher shooting percentage and more shots against, but a lower shooting percentage.  The opposite of course is true when a team is trailing.  But what I have been thinking about recently is whether there is a quality of competition impact

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On-ice shooting percentage is sustainable…

Prior to the season Gabe Desjardins and I had a conversation over at MC79hockey.com where I predicted several players would combine for a 5v5 on-ice shooting percentage above 10.0% while league average is just shy of 8.0%.  I documented this in a post prior to the season.  In short, I predicted the following: Crosby, Gaborik, Ryan, St. Louis, H. Sedin, Toews, Heatley, Tanguay, Datsyuk, and Nathan Horton will have a combined on-ice shooting percentage above 10.0% Only two of those 10 players will have an on-ice shooting percentage below 9.5% So, how did my prediction fair?  The following table tells all. Player

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Lupul’s always been this good.

A lot has been made about Joffrey Lupul’s “career year” this year and some Leaf fans are even suggesting that now is the time to trade him while his value is at an all-time high.  While it is true that he is on pace for career high in goals and points I would like to suggest that this is not because he is having a ‘career year’ but that he is being given greater opportunity.  He has always been this good and there is no reason to expect that he cannot repeat this years performance next season. When I analyze

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What is Rick Nash?

So word has come out over the last day that Rick Nash is, at least on some level, available in a trade from the Blue Jackets.  So, the question is, who is Rick Nash and would you want him on your team? Nash has been a Blue Jacket from the day he was drafted first overall in 2002.  He has played 648 regular season games and has scored 277 goals and 527 points.  Since the lockout he is 10th in goals (only Ovechkin, Kovalchuk, Heatley, Iginla, Staal, Lecavalier, Marleau, Vanek and Hossa) and 25 in points.  He has a pair

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Defenders effect on Save %

It has been shown on numerous occasions that players can influence their own teams on-ice shooting percentage be that through their talents or their style of play.  An example is the PDO vs Luck article I posted the other day.  In that article there is a table that clearly shows that shooting percentage varies across players and that players who are given more ice time (presumably because they are better players) have higher shooting percentages.  The same was not true for on-ice save percentage though.  On-ice save percentages were not ‘stratified’ according to ice time. That study looked at forwards and I

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Thoughts on PDO and Luck

One of my beefs in the analysis and evaluation of hockey players is the notion that PDO (on-ice shooting percentage plus on-ice save percentage) can be used as a proxy for luck.  A perfect example of how PDO is used as a proxy for luck is this article by Neil Greenberg about the Washington Capitals. For example, when Alex Ovechkin has been on the ice during even strength this season, the team has a shooting percentage of 8.2 percent and has saved shots at a rate of .917. So that makes his PDO value 999 (.082+.917=.999), which is almost exactly

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Zone Start Effects on Stats

Over the past week or so I have talked about a simple and straight forward method for taking into account variations in zone starts.  The method is to simply ignore the 10 seconds following an offensive or defensive face off.  By adjusting for zone starts in this manner we can see a fairly significant impact on stats and today I’ll take a look at what gets impacted and how. To do this I took a look at 3 year data using the 2008-09, 2009-10 and 2010-11 seasons.  Using 5v5 data for players with at least 1000 minutes of ice time

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Evaluating the Leafs Defensemen

With the re-signing of John-Michael Liles the Leafs now have an abundance of defensemen signed under control for a number of years, many with big dollar contracts too.  We all have our varying opinions on the relative values of each of these defensemen but I thought it would be an appropriate time to take a closer look at them statistically. Offensively 2011-12 HARO+ 2010-11 HARO+ 2010-12 HARO+ 2011-12 FenHARO+ 2010-11 FenHARO+ 2010-12 FenHARO+ JOHN-MICHAEL LILES 1.23 1.03 1.11 0.96 0.99 1.00 CODY FRANSON 1.20 1.06 1.10 1.05 1.05 1.03 LUKE SCHENN 1.10 1.08 1.08 0.85 1.02 0.99 DION PHANEUF 1.01

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Importance of Quality of Competition/Teammates

Whenever I get into a statistical debate over which player might be better than another the inevitable argument that comes up is “yeah, but player A plays against tougher competition and gets tougher assignments” which is a valid argument to make.  But how valid?  The other day I looked at a simple, straight forward method for accounting for zone start differences (which can be significant) and today I thought I’d take a look at quality of teammates and quality of competition. Whenever I browse through my stats.hockeyanalysis.com site or in my own database I have always been curious about the general lack

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