There is really only 1 stat I care about. Wins.
Would it be more accurate or informative to filter out the goalies who only play 10 games? 20 games?
If you want to compare the tops in the league, goalies who play all the time, why have the crappy save %s from goalies who rarely play lowering the mean.
So the 129%SV+ for BOBROVSKY!! would probably go down some, but still it's all relative.
I would like to see the numbers for just the top 50 goalies, or even the top goalies who faced a certain number of shots(say 500) or games played.
edit: I now see that Hockeys Reference says "Min. 4 shots faced per team game needed to qualify", which filters out some, I suppose.
I've been doing exactly this for quite some time now. For instance:
http://hockeygoalies.org/bio/nhl/toronto.html
(scroll down to where save percentage has been calculated)
Z-Score tells how many standard deviations above (or below) league average a goaltender's performance was during the season.
GD tells how many goals a goaltender prevented during the season, above and beyond the league average (looking at the link above, it appears that H-R is doing this now, calling it GSAA).
GAR is the same as above, but comparing against a "replacement-level" goaltender (since GD would assign a value of zero to a league-average goaltender, but there's definite value in being average).
SNW% gives what the goaltender's winning percentage would be if he were on a team that (a) faces a league-average number of shots, and (b) scores a league-average number of goals. (SNW and SNL are then a goaltender's support-neutral wins and losses).
For more recent seasons, I also calculate a goaltender's game-to-game variance (as a measure of consistency) as well as the strength of schedule faced by the goaltender.
I describe these all in a bit more detail here: http://hockeygoalies.org/stats/glossary.html
You can filter the numbers any which way you want using their "Play Index" up a the top left of the page.
I wish there was a stat kept for quality scoring chance save percentage. Maybe there is and I don't know that?
That is insane! Is there a way to see how many hundreds of thousands of years it will take someone to be as bad as Fleury was in the playoffs against the Flyers 2 seasons ago?Bringing a few things to the table to help show why save percentage translations are important.
Here's a list of all Vezina Trophy winners:
http://hockeygoalies.org/awards/vezina.html
Over time, you can see the raw (unadjusted) save percentages fluctuate, as periods of offense dominated, and periods of defense dominated. Did all of the goaltenders in the 1980s suck? Maybe, but unlikely.
If you look at the adjusted metrics (Z-Score, Goal Differential, and Goals Above Replacement), you can still see some outliers - this is purportedly the list of each year's best goalie, after all - but the pattern evens out a bit.
It's also easier to pick out the truly remarkable performances. Note Dominik Hasek's 93% (raw) save percentage in 1993-94 - if you look at his z-score, you can see that his performance was 4.6 standard deviations above the league average. What "z score" measures is the likelihood that an average goaltender would put together a season like the one in question (since we've all seen average goaltenders put together stretches of great play). A z-score of 4.6 means that an average goaltender would reproduce Hasek's 1993-94 season about once every 475,000 years.
If you click through (on the above page), you can see the individual goaltenders' careers evolve (under REGULAR SEASON STATISTICS or POSTSEASON STATISTICS). It helps to compare (for instance) Patrick Roy's career with Dominik Hasek's career with Martin Brodeur's career (and you can see that each was remarkable in his own way).
That is insane! Is there a way to see how many hundreds of thousands of years it will take someone to be as bad as Fleury was in the playoffs against the Flyers 2 seasons ago?
Good question - taking from here:
http://hockeygoalies.org/bio/fleury.html
(under POSTSEASON STATISTICS)
Fleury's 83.4% save percentage was 4.2 standard deviations lower than the average performance in the 2012 Stanley Cup playoffs, as a league-average save percentage in the 2012 playoffs was a beefy 92.1%. A goaltender with a long-term 92.1% save percentage will put together a stretch like Fleury's about every 75,000 seasons.
However...
It's also important to consider the opponents that Fleury was facing (it's less important in the regular season, when teams essentially all play each other, and no one plays a single opponent an inordinate amount of times). Fleury faced only the Flyers, and if you look all the way to the right on Fleury's 2012 postseason line, you can see that his opponent-weighted expected save percentage was 0.900. Stated differently, the Flyers had a 10% shooting percentage last year (other than empty-net goals), which is quite high for this era.
So it's perhaps not fair to expect Fleury to average 92.1% in his playoffs year, but a more modest 90.0%. Against that benchmark, he was still about 2.7 standard deviations below average, which would put his performance at about once in 288 postseasons (still bad but not horrendous).
Good question - taking from here:
http://hockeygoalies.org/bio/fleury.html
(under POSTSEASON STATISTICS)
Fleury's 83.4% save percentage was 4.2 standard deviations lower than the average performance in the 2012 Stanley Cup playoffs, as a league-average save percentage in the 2012 playoffs was a beefy 92.1%. A goaltender with a long-term 92.1% save percentage will put together a stretch like Fleury's about every 75,000 seasons.
However...
It's also important to consider the opponents that Fleury was facing (it's less important in the regular season, when teams essentially all play each other, and no one plays a single opponent an inordinate amount of times). Fleury faced only the Flyers, and if you look all the way to the right on Fleury's 2012 postseason line, you can see that his opponent-weighted expected save percentage was 0.900. Stated differently, the Flyers had a 10% shooting percentage last year (other than empty-net goals), which is quite high for this era.
So it's perhaps not fair to expect Fleury to average 92.1% in his playoffs year, but a more modest 90.0%. Against that benchmark, he was still about 2.7 standard deviations below average, which would put his performance at about once in 288 postseasons (still bad but not horrendous).
Just being curious on how you get your numbers like" one every 75000 seasons" from your standard deviation?
Good question. If we assume that shots on net follow a binomial distribution (admittedly a stretch), then as the number of shots faced increases, the distribution can be approximated by a normal distribution.
At that point, and with a z-score, it's just a matter of measuring the area to the right (in the case of a positive z-score) or to the left (in the case of a negative z-score).
For instance, consider a goaltender with a z-score of -1.48 (since that's an image that I was able to swipe online ):
There is 6.94% of the curve to the left of the goaltender's performance, so we would expect a goaltender to do as poorly as he did (or worse) 6.94% of the time. So it would happen about every 14.4 seasons (since 1/6.94% = 14.4).
Does that make sense? Once we assume a binomial distribution (which isn't perfect, but it's not horrible), then it's just probability theory.
So 1.15SV+ = 15% above average?
I'll watch the games
No, it merely means that the goalie was 1.15 standard deviations above the mean, as calculated with whatever metrics the statician decided to utilize. Z-Score of 1.0 is equal to 1 standard deviation above the mean, which correlates to a goaltender playing in the 84.13th percentile.
If that 1.15 is equal to a z-score, that means that the goaltender played in the 87.49th percentile.