Apr 262012
 

While doing my earlier post on Luongo’s value I noticed that Luongo’s 5v5close zone start adjusted save percentage relative to the rest of the league is much more mediocre than his 5v5 save percentage.  I decide to look into this further and realized that this is in large part due to zone start effects, and not score effects.  This got me to look into zone start effects on a goalies save percentage further.

I previously wrote an article where I described a simple and straight forward for adjusting for zone starts.  Basically you can fully account for zone start effects by ignoring the first 10 seconds after an offensive or defensive zone face off so this is what I have been doing ever since.  I hadn’t yet considered the effect on a goalies save percentage though so here it is.  In the table below you will find all goalies who played 3000 5v5 minutes over the previous 3 seasons.  There are 46 such goalies.

Goalie 5v5 Sv% ZS Adj. Sv% Diff. 10Sec Sv% 10Sec SA%
MICHAL NEUVIRTH 91.8% 90.5% 1.4% 96.0% 24.6%
JIMMY HOWARD 92.3% 90.6% 1.7% 98.2% 22.0%
ROBERTO LUONGO 93.0% 91.5% 1.5% 98.4% 21.6%
TIM THOMAS 93.1% 92.0% 1.1% 97.4% 21.0%
HENRIK LUNDQVIST 93.1% 92.0% 1.1% 97.4% 20.5%
TUUKKA RASK 93.0% 91.8% 1.2% 97.9% 20.3%
COREY CRAWFORD 92.2% 90.7% 1.4% 97.9% 20.1%
TOMAS VOKOUN 92.9% 91.7% 1.2% 97.7% 19.7%
EVGENI NABOKOV 92.6% 91.4% 1.2% 97.4% 19.5%
DWAYNE ROLOSON 91.4% 90.0% 1.4% 97.3% 19.1%
BRIAN BOUCHER 91.8% 90.4% 1.4% 97.9% 18.8%
SCOTT CLEMMENSEN 92.1% 90.7% 1.3% 97.9% 18.5%
JOSE THEODORE 92.6% 91.6% 1.0% 97.0% 18.4%
SERGEI BOBROVSKY 92.3% 91.0% 1.3% 97.8% 18.4%
SEMYON VARLAMOV 92.9% 91.9% 1.0% 97.4% 18.2%
JAMES REIMER 92.7% 91.7% 0.9% 96.9% 17.9%
RAY EMERY 91.8% 90.9% 0.9% 96.1% 17.8%
JOHAN HEDBERG 92.1% 91.1% 0.9% 96.5% 17.6%
MIIKKA KIPRUSOFF 92.5% 91.5% 1.0% 97.4% 17.5%
CRAIG ANDERSON 92.3% 91.2% 1.0% 97.2% 17.1%
JEAN-SEBASTIEN GIGUERE 91.7% 91.1% 0.6% 94.8% 17.0%
DEVAN DUBNYK 92.1% 91.0% 1.1% 97.4% 16.7%
PETER BUDAJ 92.1% 91.1% 0.9% 96.7% 16.6%
ANTTI NIEMI 92.7% 91.7% 1.0% 98.1% 16.1%
MARTY TURCO 91.8% 90.7% 1.1% 97.3% 16.0%
MARTIN BRODEUR 91.7% 90.5% 1.1% 97.7% 15.8%
JONATHAN QUICK 92.6% 91.9% 0.6% 96.1% 15.2%
BRIAN ELLIOTT 91.2% 90.3% 0.9% 96.2% 15.2%
CAREY PRICE 92.5% 91.9% 0.5% 95.6% 14.8%
JONAS GUSTAVSSON 90.9% 89.8% 1.1% 97.3% 14.7%
DAN ELLIS 91.3% 90.5% 0.8% 96.1% 14.3%
KARI LEHTONEN 92.6% 92.2% 0.5% 95.4% 14.2%
CAM WARD 92.6% 91.9% 0.7% 97.0% 13.5%
PEKKA RINNE 93.0% 92.5% 0.5% 96.1% 13.5%
CHRIS MASON 91.0% 90.7% 0.4% 93.3% 13.4%
MARC-ANDRE FLEURY 91.6% 90.9% 0.7% 96.4% 13.4%
ILYA BRYZGALOV 92.8% 92.3% 0.5% 96.2% 13.3%
NIKOLAI KHABIBULIN 91.0% 90.0% 1.0% 97.7% 13.3%
RYAN MILLER 92.7% 92.2% 0.5% 96.3% 13.2%
NIKLAS BACKSTROM 92.6% 92.2% 0.4% 95.2% 12.9%
ONDREJ PAVELEC 92.1% 91.5% 0.6% 96.0% 12.8%
STEVE MASON 91.2% 90.5% 0.8% 96.5% 12.6%
JONAS HILLER 92.6% 91.9% 0.7% 97.3% 12.5%
MIKE SMITH 92.4% 91.9% 0.6% 96.4% 12.4%
JAROSLAV HALAK 92.9% 92.4% 0.5% 96.8% 11.8%
MATHIEU GARON 91.0% 90.5% 0.5% 95.2% 11.4%
Average 92.3% 91.4% 0.9% 96.9% 16.2%

Included in the table are 5v5 save percentage, 5v5 zone start adjusted save percentage, the difference between 5v5 save percentage and zone start adjusted save percentage, the goalies save percentage on shots within 10 seconds of an offensive/defensive zone face off, and the percentage of shots that the goalie faced that were within 10 seconds of an offensive/defensive zone face off.

As you can see, the average within 10 seconds of a face off save percentage is significantly higher than the average face off adjusted save percentage (97.9% vs 91.4%) and the variation of the percentage of shots faced within 10 seconds if a face off across goalies is very significant (average 16.2%, low of 11.4%, high of 24.6%).  Furthermore, this average seems to be team driven (i.e. Rask/Thomas have quite similar/high percentages, S. Mason/Garon, Pavelec/C. Mason quite low).  This can introduce a significant bias into a goalies save percentage.  If we calculate an expected save percentage based on the number of ‘within 10 second’ and ‘during normal play’ shots and the average save percentages for those situations, the expected save percentage of Neuvirth would be 92.7% while the expected save percentage of Mathieu Garon would be 92.0%.  Now that is just a 0.7% difference which you may not think is huge, but the lowest 5v5 save percentage is 90.9% and the highest is 93.1% for a range of 2.3%.  That means a 0.7% variation due to within 10 seconds of a face off vs normal play could account for 30% of all variation in goaltender save percentage.  I am too lazy to look into it, but I wonder if variation in number of power play shots faced has as much impact on overall save percentage.  I am certain that this is a far more significant factor than score effects.

Thus, I think it is extremely important to factor out shots faced immediately after a face off when evaluating goaltender performance (and any players performance for that matter).  Furthermore, I fully stand by my previous Luongo post where I suggest he is a mere middle of the pack goalie.

 

  2 Responses to “Zone Start effects on Goalie Save Percentage”

  1.  

    “I think it is extremely important to factor out shots faced immediately after a face off when evaluating goaltender performance (and any players performance for that matter). ”

    And this sort of thing is why people don’t take stats only analysis of players seriously. You completely discount a viable hockey play to change the numbers to prove your point.

    I have a lower opinion of Luongo than you so I am not even saying this to defend him.

    •  

      I am not doing it to prove a point. The zone start thing arose out of my Luongo article, not created for it.

      The reality is shots within 10 seconds of a face off are easier to save. Every goalie in the league has a higher save percentage on these shots than shots that occur more than 10 seconds after the face off.

      The other reality is that there is a huge discrepancy among goalies in the percentage of shots they face that occur within 10 seconds of a face off. So, for a goalie that faces a high percentage of such shots they will have a higher percentage of easy shots faced and for those goalies that face a low percentage of such shots will have a higher percentage of tough shots faced. This will have an impact on a goalies save percentage that has nothing to do with the goalies individual talent level.

      Those are the facts. There are a number of ways to deal with those facts and one such way is to not consider the type of shots that results in the bias or unfairness as I have done. Hockey stats guys do this all the time when they consider even strength save percentage instead of overall save percentage because it has been shown that shots faced while short handed (i.e. shots taken by the team on the power play) are tougher to save. My goal is to do the best I can to compare goalies under similar circumstances the best I can and to do so I need to some how eliminate the 10 seconds after face off shot difficulty bias.

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