GLOSSARY
Adjusted Save Percentage (AdSv%):6
Defined here, it is the weighting of a goaltender’s save percentage in each danger level by the fraction of shots that would be expected from the league-wide distribution
Different goaltenders face different distributions of shots from across the ice due to the offenses they face and the defenses in front of them. We adjust save percentage by re-weighing the components according to the league-wide distribution of shots, so that the value better translates between different goaltenders. This is similar to stratified sampling in survey methodology, and also goes by the name benchmarking.
With our danger breakdown, standard save percentage of Saves/(Saves + Goals) is expressed as
Sv% = (Saves_low + Saves_med + Saves_high)/(Saves_low + Goals_low + Saves_med + Goals_med + Saves_high + Goals_high)
ZONE START EFFECTS ON SV%
Basically you can fully account for zone start effects by ignoring the first 10 seconds after an offensive or defensive zone face off
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%)
Thus, I think it is extremely important to factor out shots faced immediately after a face off when evaluating goaltender performance
EVALUATING GOALIES IN CONTEXT
Adjusted Save Percentage, or SV%+. It does the same thing as ERA+, in the sense that someone with a SV%+ of 100 is league average and anyone above that is better while anyone below that is worse.
SV%+ = [(1 – League-average save %) / (1 – Goalie SV%)] * 100
the spread in overall goalie talent is just not that big anymore. Unless you hit the jackpot with one of the guys at the very top of the list, chances are that the guy you’re getting isn’t going to be THAT much better than an average goalie.
ADJUSTING SV% FOR TEAM EFFECTS
As teams can generally control where their opponents’ shots are coming from (positionally, at least) it naturally makes sense to adjust our goalie statistics.
adjSv% = adjSv% Rel + lgSv%
Where adjSv% Rel = Sv% – xSv%
The way to interpret the delta is this: a positive delta means that a goalie’s adjusted save percentage is greater than his observed save percentage, or in other words that his defense cost him points by allowing more shots from forwards than we’d expect.
As you can see, the deltas aren’t huge, but there are goalies for whom it does seem to make a difference in our evaluation.
While these are still relatively small differences for many goalies, over the course of a career these can start to add up.
SHOT DANGER BINS
(March 2015)
High Danger Save % correlates highest (R^2 of .6) with Traditional Save %. This means that of the 3 bins, a goalie’s High Danger Save % is the most integral to Traditional Save %.
DO NHL GM’S OVERVALUE GOALIES
(Mar 2015)
The difference between the average elite starter and the average replacement-level goaltender is almost entirely based on HD SV%. There is literally no distinction in terms of average ability for each group on other shots. Most telling is the fact that league average SV% is essentially replacement level, so goaltending should be far cheaper to obtain than most teams seem willing to accept.
By comparing a goaltender’s HD SV% to that of the average replacement level goaltender (.812), we can identify how many goals saved above replacement (GSAR) they have provided
DANGER ZONES AND SHOT VOLUMES
a goalie’s performance on high danger shots was most closely correlated with overall success, with medium shots having slightly less influence, and low danger shots showing almost no relationship.
A useful extension would be to look at how well the danger zone save percentages predicted future overall save percentages. After all, if performance on high danger shots is most critical for a goalie in determining his current season save percentage, it stands to reason that this would also be a key predictor of future success
We’re essentially just as good at guessing his save percentage using High Danger Save Percentage as we are with total Save Percentage.
the medium and low danger data often has too much noise to find a netminder’s talent in.
The other take away message here is that shots against do matter when we’re evaluating goaltending, because all things being equal, a goalie who faced more shots likely faced easier shots to save.
REGRESSING SV% BY DANGER ZONE
Low-Danger is almost all noise, Mid-Danger has a signal but it’s weak, and High-Danger is the best and has a fair signal.
So not only does the observed spread increase as we move to High-Danger but we can attribute more of that to talent (the standard deviation due to talent is higher).
I think this is important in showing why we should be mainly focusing on High Danger sv% when it comes to evaluating goalies (obviously not only focus on it, just mostly) as it has the biggest spread in talent.
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