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Goalies: Adjusted Playoff Save Percentage

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05-07-2012, 11:51 PM
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Goalies: Adjusted Playoff Save Percentage

I don’t think that anybody has done a comprehensive study about playoff save percentage. I thought it was an important enough topic to spend a couple of hours analyzing the data.

To adjust playoff save percentage, two adjustments are required. First, saves are normalized to a 90.5% save percentage environment. This is calculated for each goalie each year, and the goalie’s shots and saves are removed from the league for the purpose of that calculation. Second, these numbers are adjusted to an environment where goalies face 28.6 shots per game. This won’t impact save percentage in any year (as shots and saves are adjusted by the same amount), but it ensures that a goalie’s performance in a year that features many shots per game (such as 2011) is not weighed more than a goalie’s performance in a year that features few shots per game (such as 2001) when calculating career averages.

I haven't attempted to account for the fact that a goalie on a strong team will be able to play more games due to having better teammates, facing an easier first round opponent, having home ice advantage, etc. These are important things to consider, but I can't quantify them.

I’ve used data from 1984 to 2011. All numbers are taken from hockey-reference.com. I realize that playoff save percentage exists going back to the 1950s, but this is the only usable data that I have. If someone wants to continue this project going farther back, I’d welcome it.

I’ve stated before that save percentage is, in my opinion, the single best statistic to measure goalie performance. That being said, I think that save percentage is more reliable in the regular season than in the playoffs for a few reasons. First, the sample sizes are much larger, which means that one can have more confidence in the numbers. Second, the strength of opponents varies widely in the playoffs (a goalie can play 300 minutes of hockey entirely against the best team in the NHL). Third, many teams play more defensively in the playoffs – on average, I think that many teams surrender less dangerous shots, which would, all things being equal, overstate save percentage in the playoffs. Still, to the extent that save percentage is used, it should be adjusted for era.

My purpose isn’t to present one number which is a perfect representation of a goalie’s performance. Rather, I want to improve on what has already been quantified in conventional statistics.


Last edited by Hockey Outsider: 05-07-2012 at 11:58 PM.
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05-07-2012, 11:51 PM
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Career Save Percentage - minimum 1,000 adjusted shots

* This table is now updated for 2014

GoalieShotsSavesSP%
Tim Thomas 1526 1409 92.4%
Olaf Kolzig 1446 1330 92%
Tuukka Rask 1459 1342 92%
Patrick Roy* 7218 6638 92%
John Vanbiesbrouck 2030 1865 91.9%
Ken Wregget 1767 1622 91.8%
Dominik Hasek 3422 3140 91.7%
Ed Belfour* 4641 4256 91.7%
Jean-Sebastien Giguere 1546 1416 91.6%
Kirk McLean 2099 1918 91.4%
Patrick Lalime 1105 1010 91.4%
Cam Ward 1137 1038 91.3%
Dwayne Roloson 1478 1348 91.2%
Jonathan Quick 2192 1999 91.2%
Henrik Lundqvist 2687 2449 91.1%
Felix Potvin 2186 1992 91.1%
Curtis Joseph 4044 3685 91.1%
Martin Brodeur 5439 4953 91.1%
Grant Fuhr* 3966 3610 91%
Mike Liut 1064 968 91%
Mike Richter 2182 1985 91%
Miikka Kiprusoff 1679 1527 90.9%
Bill Ranford 1536 1396 90.9%
Tom Barrasso 3521 3197 90.8%
Ryan Miller 1631 1481 90.8%
Jimmy Howard 1349 1225 90.8%
Corey Crawford 1597 1449 90.7%
Chris Osgood 3246 2943 90.7%
Roberto Luongo 1864 1689 90.6%
Nikolai Khabibulin 2155 1951 90.5%
Ron Hextall 2632 2382 90.5%
Reggie Lemelin 1147 1036 90.3%
Marty Turco 1345 1215 90.3%
Kelly Hrudey 2531 2286 90.3%
Sean Burke 1101 993 90.2%
Greg Millen 1336 1205 90.2%
Brian Boucher 1069 964 90.2%
Don Beaupre 1538 1386 90.1%
Mike Vernon 3493 3146 90.1%
Jose Theodore 1730 1559 90.1%
Jon Casey 1789 1611 90.1%
Carey Price 1184 1066 90%
Andy Moog 2655 2385 89.8%
Evgeni Nabokov 2314 2077 89.7%
Antti Niemi 1714 1538 89.7%
Ilya Bryzgalov 1304 1169 89.7%
Arturs Irbe 1513 1357 89.6%
Marc-Andre Fleury 2559 2291 89.5%
Ray Emery 1051 937 89.2%

This table shows why it's critically important to take the era into consideration when evaluating goalies' playoff performances. For example, Grant Fuhr posted a seemingly unimpressive 89.9% save percentage between 1984 and 1988, when he helped the Oilers win four Stanley Cups in five years. Adjusted for era, Fuhr stopped 91.8% of the shots he faced during those four seasons. That's not quite elite, but it's a very strong performance over a large sample size (79). That doesn't even take into account the strong likelihood that Fuhr faced tougher quality shots than average due to playing on a run-and-gun team.

Keep in mind that career save percentage is, by definition, a career average. Tom Barrasso had a few rough playoffs at the start and end of his career, and that dragged down his average. His career average of 90.8% is barely above average; if one focuses on his prime from 1988 to 1996, Barrasso's save percentage rises to a very strong 91.6%.

Patrick Roy is tied for the second highest career save percentage out of any goalie who faced at least 1,000 shots (Roy faced nearly five times as many shots as Thomas). He's also faced 33% more shots than the next closest goalie (Brodeur). No goalie during the past thirty years has surpassed (or even approached) Roy's combination of an extremely high level of performance, and longevity.

Osgood is slightly above average at stopping the puck. I think the Hall of Fame should be a balance between ability and accomplishments. Osgood has is consistent and durable, but is only slightly above average ability. In my opinion, he shouldn’t get a spot in the Hall due to having the fortune of spending most of his career playing behind the best franchise of the past two decades.

Update for 2012: Fleury has the second-worst adjusted save percentage after a number of horrific games in the spring. Thomas' save percentage drops slightly, but he still has the highest adjusted playoff save percentage 1983-present (minimum 1,000 shots).

Update for 2013: We all know how game six of the Stanley Cup finals ended, but Rask still had a phenomenal postseason. He has the 4th best playoff save percentage of all-time. Quick has now faced enough shots to qualify for the list and based on the threshold (minimum 1,000 shots), he has the T-8th best save percentage of all-time. Lundqvist moves up slightly but is still well below his regular season performance. Fleury drops further and now has the worst adjusted save percentage of all-time.

Update for 2014: Quick and Lundqvist duelled in the Stanley Cup finals and now rank 14th and 15th in career adjusted save percentage. If we increase the threshold to 2,000 adjusted shots, they rank 6th and 7th. Fleury has a decent spring, but still ranks last (minimum 2,000 adjusted shots).


Last edited by Hockey Outsider: 06-15-2014 at 06:52 PM.
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05-07-2012, 11:52 PM
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Top Thirty Playoffs – minimum 1,000 minutes

* updated for 2014

PlayerCup?Smythe?YearTeamGPWinLossMinsSASvSv%
Martin Brodeur Yes 1995 NJD 20 16 4 1222 475 448 94.4%
Patrick Roy* Yes Yes 1993 MTL 20 16 4 1293 611 577 94.3%
Pelle Lindbergh 1985 PHI 18 12 6 1008 468 441 94.3%
Ed Belfour* 1995 CHI 16 9 7 1014 491 462 93.9%
Patrick Roy* Yes Yes 1986 MTL 20 15 5 1218 489 458 93.7%
Jean-Sebastien Giguere Yes 2003 MDA 21 15 6 1407 760 711 93.6%
Patrick Roy* 1989 MTL 19 13 6 1206 521 488 93.6%
Reggie Lemelin 1988 BOS 17 11 6 1027 442 414 93.5%
Olaf Kolzig 1998 WSH 21 12 9 1351 770 720 93.5%
John Vanbiesbrouck 1996 FLA 22 12 10 1332 720 672 93.4%
Tim Thomas Yes Yes 2011 BOS 25 16 9 1542 789 736 93.3%
Jonathan Quick Yes Yes 2012 LAK 20 16 4 1238 546 509 93.2%
Dominik Hasek 1999 BUF 19 13 6 1217 616 574 93.2%
Tom Barrasso Yes 1991 PIT 20 12 7 1175 600 559 93.2%
Bill Ranford Yes Yes 1990 EDM 22 16 6 1401 676 629 93.2%
Patrick Roy* Yes Yes 2001 COL 23 16 7 1451 693 645 93%
Mike Smith 2012 PHX 16 9 7 1027 611 568 93%
Dwayne Roloson 2006 EDM 18 12 5 1160 625 581 92.9%
Sean Burke 1988 NJD 17 9 8 1001 530 492 92.9%
Kirk McLean 1994 VAN 24 15 9 1544 813 755 92.8%
Martin Brodeur 1994 NJD 17 8 9 1171 526 488 92.7%
Andy Moog 1990 BOS 20 13 7 1195 489 453 92.7%
Arturs Irbe 2002 CAR 18 10 8 1078 511 474 92.7%
Marc-Andre Fleury 2008 PIT 20 14 6 1251 603 559 92.6%
Tuukka Rask 2013 BOS 22 14 8 1466 724 669 92.4%
Alain Chevrier 1989 CHI 16 9 7 1013 478 441 92.3%
Ed Belfour* Yes 1999 DAL 23 16 7 1544 648 597 92.3%
Martin Brodeur Yes 2003 NJD 24 16 8 1491 678 626 92.2%
Chris Osgood Yes 2008 DET 19 14 4 1160 425 392 92.2%
Henrik Lundqvist 2014 NYR 25 13 11 1516 731 674 92.2%

I realize that 93.0% is an arbitrary threshold, but it's a pretty good summary of the best playoff performances of the past thirty years.

As I said in the previous post, there is little doubt that Roy is the greatest playoff goalie of the past three decades. He has three of the top seven performances, and five of the top thirty-three. He performed at an exceptionally high level on five different occasions where his team made the Stanley Cup finals, and he was a major reason why they were victorious four times.

Brodeur doesn't get enough credit for his spectacular performance in 1995. His 92.7% save percentage looks strong on paper, but it's even more incredible when you consider that the league average was only 89.3% that year (88.9% after removing Brodeur's shots and saves). I am adamantly opposed to the idea that Brodeur deserved the Smythe in 2003, but arguably he deserved it in 1995.

Update for 2012: there are two additions to this list. Smythe winner Jonathan Quick ranks 12th all-time. Mike Smith also had a very strong postseason.

Update for 2013: Rask joins the list in 25th place. The 2013 playoffs were very low-scoring and featured a lot excellent goaltending. Unfortunately this made it harder for each individual goalie to stand out since everything is evaluated on a relative basis. In other words, Rask's 94.0% save percentage is less impressive on a relative basis because all eight starting goalies for teams advancing to the second round posted at least a 91.8% save percentage.

Update for 2014: Lundqvist barely joins the list, placing 30th. That sounds about right; it was a very strong postseason, but I wouldn`t put it in the upper echelon of the past thirty years either.


Last edited by Hockey Outsider: 06-15-2014 at 06:54 PM.
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05-07-2012, 11:52 PM
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Stanley Cup Winners

* updated for 2014

PlayerCup?Smythe?YearTeamGPWinLossMinsSASvSv%
Martin Brodeur Yes 1995 NJD 20 16 4 1222 475 448 94.4%
Patrick Roy* Yes Yes 1993 MTL 20 16 4 1293 611 577 94.3%
Patrick Roy* Yes Yes 1986 MTL 20 15 5 1218 489 458 93.7%
Tim Thomas Yes Yes 2011 BOS 25 16 9 1542 789 736 93.3%
Jonathan Quick Yes Yes 2012 LAK 20 16 4 1238 546 509 93.2%
Tom Barrasso Yes 1991 PIT 20 12 7 1175 600 559 93.2%
Bill Ranford Yes Yes 1990 EDM 22 16 6 1401 676 629 93.2%
Patrick Roy* Yes Yes 2001 COL 23 16 7 1451 693 645 93%
Ed Belfour* Yes 1999 DAL 23 16 7 1544 648 597 92.3%
Martin Brodeur Yes 2003 NJD 24 16 8 1491 678 626 92.2%
Chris Osgood Yes 2008 DET 19 14 4 1160 425 392 92.2%
Grant Fuhr* Yes 1988 EDM 19 16 2 1136 485 446 92.1%
Patrick Roy* Yes 1996 COL 22 16 6 1454 635 585 92.1%
Cam Ward Yes Yes 2006 CAR 23 15 8 1320 590 543 92%
Grant Fuhr* Yes 1984 EDM 16 11 4 883 479 441 92%
Grant Fuhr* Yes 1985 EDM 18 15 3 1064 498 458 92%
Mike Richter Yes 1994 NYR 23 16 7 1417 618 568 92%
Mike Vernon Yes 1989 CGY 22 16 5 1381 543 499 91.9%
Tom Barrasso Yes 1992 PIT 21 16 5 1233 604 554 91.7%
Nikolai Khabibulin Yes 2004 TBL 23 16 7 1401 652 598 91.7%
Grant Fuhr* Yes 1987 EDM 19 14 5 1148 499 457 91.6%
Martin Brodeur Yes 2000 NJD 23 16 7 1450 575 527 91.5%
Corey Crawford Yes 2013 CHI 23 16 7 1504 641 587 91.5%
Mike Vernon Yes Yes 1997 DET 20 16 4 1229 469 429 91.4%
Jean-Sebastien Giguere Yes 2007 ANA 18 13 4 1067 462 420 90.9%
Chris Osgood Yes 1998 DET 22 16 6 1361 612 556 90.9%
Dominik Hasek Yes 2002 DET 23 16 7 1455 599 543 90.7%
Antti Niemi Yes 2010 CHI 22 16 6 1322 614 557 90.7%
Jonathan Quick Yes 2014 LAK 26 16 10 1605 768 694 90.4%
Marc-Andre Fleury Yes 2009 PIT 24 16 8 1447 650 584 89.7%

Only eight goalies have won the Stanley Cup while posting an adjusted save percentage of 93.0% or higher. Six of those netminders won the Conn Smythe. As for the other two - as incredible as Barrasso was in 1991, I don't think he was more valuable than Lemieux's insane 44 point performance. The more I think about it, the more I think that Brodeur should have won the 1995 Smythe.

Detroit won three Stanley Cups in six years with only above-average goaltending. Vernon, Osgood and Hasek played well enough not to cost the powerhouse Red Wings any series, but rarely stole any games. I was critical of Osgood in a previous post but, to his credit, he played very well in 2008.

Only two of the past thirty Stanley Cup winners posted a below average save percentage: Marc-Andre Fleury and Jonathan Quick (just barely below average).

Update for 2012: Quick was phenomenal this spring. He has the fifth best adjusted save percentage among Stanley Cup winning goalies.

Update for 2013: the numbers indicate that Crawford's performance this spring was below-average compared to other Cup winning goalies. Keep in mind this statistic is based on relative performance and 2013 may have featured the most consistent display of goaltending I've ever seen in the postseason. As the quality of goaltending rises, it becomes increasingly difficult for any individual to stand out. What do others think?

Update for 2014: see the opposite of my commentary in 2012. Quick was good enough not to cost the Kings games, but generally wasn`t a difference maker. Statistically, he was one of the worst performing Cup winning goalies of the the past three decades.


Last edited by Hockey Outsider: 06-15-2014 at 06:57 PM.
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05-07-2012, 11:53 PM
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Conn Smythe winners

* updated for 2014

PlayerCup?Smythe?YearTeamGPWinLossMinsSASvSv%
Patrick Roy* Yes Yes 1993 MTL 20 16 4 1293 611 577 94.3%
Patrick Roy* Yes Yes 1986 MTL 20 15 5 1218 489 458 93.7%
Jean-Sebastien Giguere Yes 2003 MDA 21 15 6 1407 760 711 93.6%
Tim Thomas Yes Yes 2011 BOS 25 16 9 1542 789 736 93.3%
Jonathan Quick Yes Yes 2012 LAK 26 16 4 1238 546 509 93.2%
Bill Ranford Yes Yes 1990 EDM 22 16 6 1401 676 629 93.2%
Patrick Roy* Yes Yes 2001 COL 23 16 7 1451 693 645 93%
Cam Ward Yes Yes 2006 CAR 23 15 8 1320 590 543 92%
Ron Hextall Yes 1987 PHI 26 15 11 1540 751 688 91.6%
Mike Vernon Yes Yes 1997 DET 20 16 4 1229 469 429 91.4%

Over the past 28 years, ten goalie have won the Conn Smythe. The first seven listed above were strong selections; although there were other strong candidates in some years, it’s impossible to argue that the actual winners were poor selections.

Cam Ward was very good in 2006, but I would have given the Smythe to Chris Pronger (no defenseman has ever won the Smythe while failing to win the Stanley Cup). I probably would have given the Smythe to Brind’Amour ahead of Ward as well.

Wayne Gretzky deserved the Smythe in 1997, but probably fell victim to the impossibly high expectations others had of him. Although his 34 points in 23 points are staggering, it was weaker than his previous four playoffs! Ron Hextall’s save percentage is almost certainly understated since he faced so many shots from the incredibly dangerous Oilers.

I don’t think that Mike Vernon had a good case for winning the Smythe in 1997. He was solidly above average, but that’s not Conn Smythe material. There were several better candidates including Fedorov (led Wings in scoring and provided exceptional two-way play), Shanahan (second on Wings in scoring and was credited for giving the Wings the toughness and grit they lacked in previous years) and Lidstrom & Murphy (for shutting down Lindros so effectively in the Cup finals).

Update for 2012: Quick was phenomenal this spring. He has the fifth best adjusted save percentage among Conn Smythe winning goalies.

Update for 2013: Patrick Kane won the Smythe, no changes to this list.

Update for 2014: Justin Williams won the Smythe, no changes to this list.


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05-07-2012, 11:53 PM
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Support Neutral Wins & Losses

* update for 2014

GoalieDecisionsWinsLossesWin%
Patrick Roy* 245 143 102 58.2%
Martin Brodeur 204 109 95 53.5%
Ed Belfour* 156 89 67 57%
Grant Fuhr* 137 72 65 52.3%
Curtis Joseph 129 69 60 53.6%
Mike Vernon 133 65 68 49.1%
Dominik Hasek 114 65 49 57.2%
Chris Osgood 123 63 60 51.4%
Tom Barrasso 115 59 56 51.7%
Henrik Lundqvist 91 50 41 54.5%
Andy Moog 100 47 53 47.3%
Ron Hextall 90 46 44 50.8%
Jonathan Quick 76 43 33 56%
Marc-Andre Fleury 92 42 50 46%
Kelly Hrudey 82 41 41 49.8%
Mike Richter 74 40 34 53.4%
Evgeni Nabokov 84 39 45 46.5%
Felix Potvin 72 38 34 53%
Kirk McLean 68 37 31 54.8%
Nikolai Khabibulin 70 36 34 51.2%
Roberto Luongo 63 32 31 50.8%
Tim Thomas 50 31 19 62.4%
Ken Wregget 53 31 22 58.6%
Jon Casey 63 30 33 47.6%
Corey Crawford 55 29 26 52.2%
Antti Niemi 61 28 33 46.4%
Jean-Sebastien Giguere 50 28 22 56.5%
Tuukka Rask 47 28 19 59.8%
Miikka Kiprusoff 53 28 25 52.6%
Ryan Miller 53 27 26 51.7%
Bill Ranford 53 27 26 51.6%
Olaf Kolzig 44 26 18 59.1%
Don Beaupre 53 26 27 48.8%
Dwayne Roloson 46 25 21 53.9%
Jose Theodore 51 24 27 47.9%
Arturs Irbe 50 24 26 48.1%
Marty Turco 47 24 23 50.8%
Jimmy Howard 45 23 22 51.5%
Patrick Lalime 41 23 18 55.5%
Cam Ward 41 22 19 54.8%
Greg Millen 46 22 24 48.8%
Ilya Bryzgalov 45 21 24 46.5%
Mike Liut 35 19 16 53.5%
Reggie Lemelin 36 19 17 51.6%
Carey Price 38 18 20 48.3%
Pete Peeters 34 17 17 50.2%
Sean Burke 35 17 18 47.6%
Ray Emery 38 16 22 42.8%
Mario Gosselin 31 15 16 47.3%

This is a concept developed by Taco McArthur – link. Essentially, it shows how many games a goalie would be expected to win, had they played on an average team. I’m not sure if I like this or Wins Added more (the latter is a statistic I created), but TM’s statistic is far easier to calculate and gives fairly similar results, so let’s go with his! The chart above shows the results for all goalies with 30+ decisions.

Roy’s dominance continues. He has the most Support Neutral Wins by a massive margin. He also has the best win percentage out of any goalie with 60+ decisions. Once again, there is little doubt that Roy is greatest playoff goalie of the past three decades.

Tim Thomas has a staggering SNWL record. He has an exceptional win percentage, and his 50 decisions are a substantial number – only 27 goalies have earned the decision in more than fifty playoff games.

Fuhr actually went 90-47 in the playoffs (from 1984 onwards). The numbers suggest that he would have been 72-65 on an average team. That means that Fuhr was a very good goalie (and even better during his prime), but he clearly benefited by playing on the highest-scoring team of the modern era.

For all the criticism he's received, Joseph ranks 5th in playoff wins and has the 10th best win percentage of the 30 goalies who earned 50+ decisions. I don't think he's a HOF goalie, but he's often unfairly criticized (especially in Detroit, when his teammates scored just 1.88 goals per game, despite finishing 1st and 2nd in regular season scoring those two years).

Update for 2012: Brodeur extends his lead over third place. Despite a first-round exit, Thomas breaks the 30 win barrier.

Update for 2013: Quick continues to climb the charts and how has almost matched Thomas' career playoff record. Lundqvist continues to climb the chart, albeit slowly. Rask is off to an excellent 21-14 start to his career.

Update for 2014: Lundqvist moves up to 10th place all-time, and Quick moves up to 13th place.


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05-08-2012, 12:53 AM
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Quote:
Originally Posted by Hockey Outsider View Post
Brodeur doesn't get enough credit for his spectacular performance in 1995. His 92.7% save percentage looks strong on paper, but it's even more incredible when you consider that the league average was only 89.3% that year (88.9% after removing Brodeur's shots and saves). I am adamantly opposed to the idea that Brodeur deserved the Smythe in 2003, but arguably he deserved it in 1995.
I came to the same conclusion about 14 months ago.

http://hfboards.hockeysfuture.com/sh...&postcount=113


Adjusting to the regular season average made more sense to me though. For one, it's a larger sample size that includes all NHL goalies. More than that, it eliminates the issue of a 1995 Dominik Hasek going from an NHL best .930 to a .863 and helping throw the average off from where one would expect it to be from having watched the season. After all, 1995 was one of those rare three seasons in which the playoff save percentage was lower than the regular season save percentage (which really shouldn't happen for any reason other than sample size, given that half the leagues worst teams are out).

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05-08-2012, 01:53 PM
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Very interesting stuff - I'm curious to see how it compares to what I've got in my database.

Agreed on Brodeur's non-Smythe in 1995; on the whole, he probably has the right number of Smythes, but they're not allocated optimally to my tastes.

I'm also working on a concept called "par", which Bill James used to use to measure managers' success. I'm not sure how well it will work for goalies, but I like what I'm seeing so far.

Nice to see Kirk McLean up there!

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05-08-2012, 02:06 PM
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Originally Posted by Taco MacArthur View Post
Agreed on Brodeur's non-Smythe in 1995; on the whole, he probably has the right number of Smythes, but they're not allocated optimally to my tastes.
You'd have given Brodeur his zero Conn Smythes in different years than he didn't win them?
Either way, 1 Conn Smythe seems about right for his career, but that never works as a measuring stick for players anyway (unless the question is "was Patrick Roy awesome? Y/N"), since only one person on one of two teams wins them every year.

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05-08-2012, 02:08 PM
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You'd have given Brodeur his zero Conn Smythes in different years than he didn't win them?
Ah, sorry - in my defense, I'm drunk (on work, not alcohol) right now.

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05-08-2012, 03:39 PM
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Adjusting to the regular season average made more sense to me though. For one, it's a larger sample size that includes all NHL goalies.
I've been thinking the same thing lately.

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05-08-2012, 06:16 PM
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poor poor irbe. ._. And ill chip in my obligatory broken record of I think he should have won the conn smythe in 2k2.

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05-08-2012, 06:18 PM
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poor poor irbe. ._. And ill chip in my obligatory broken record of I think he should have won the conn smythe in 2k2.
Yeah, Irbe does pretty poorly from a career perspective when you consider that includes one very stellar year.

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05-08-2012, 06:24 PM
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Yeah, Irbe does pretty poorly from a career perspective when you consider that includes one very stellar year.

Hah yea, the first couple of san jose years he had some great high light games...then followed with some blow outs that really hurt him. I still wish dallas would have given him a chance that year he was with them. Moog wasnt doing anything, and irbe actually played pretty well that year at times. Woulda been nice to see him get some playoff action with a team that was actually expected to win. Oh well...

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05-09-2012, 07:01 PM
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I think anyone using or assuming Gausian distribution in their adjustments should take a look at the results of this large study which included NHL players.

I'm not an expert in this so I would encourage interested readers to read the study rather than simply accept my summary.

http://onlinelibrary.wiley.com/doi/1...1.01239.x/full

I saw some criticism but nothing that seemed more deep than a casual defense of the bell curve.

In short the idea seems to be that a small percentage of elite performers including outliers have a disproportionately large impact on the average result. The rest fall below the mathematical average of the group.

The other end of the scale, negative performances have the same impact and no they don't balance out.

They show that a bell curve doesn't match the data without massaging the data first. the data aligns much more closely to a Paretian http://www.vigorinnovation.com/from-...-the-long-tail or power curve.

I suppose one could say that the outliers at both ends are the data. Eliminating or normalizing them distorts the data.

So when examining data for a season say goals scored or save % one must look at the outliers for explanation since they are most responsible for the data. Adjusting them to make the curve smoother or bell-like is wrong. That just ignores and distorts the most meaningful data.

It appears to support the 80-20 rule. 20% of sales people are responsible for 80% of the sales. Within that group the same rule applies. Furthermore this appears to apply within a team, season or career.

Similarly a small percentage of the group is responsible for most of the negative stats.

So a season with a few really bad goalies would greatly impact the overall data just as a season with a few really good goalies.

Normalizing this data creates the false impression that the group as a whole were better or worse. It would also serve to lessen the performance of the good goalies or enhance the performance of the bad goalies.

I did see a link to using Excel to calculate power curves which may interest those of you who've amassed the raw data.

The first two paragraphs-

"We revisit a long-held assumption in human resource management, organizational behavior, and industrial and organizational psychology that individual performance follows a Gaussian (normal) distribution. We conducted 5 studies involving 198 samples including 633,263 researchers, entertainers, politicians, and amateur and professional athletes. Results are remarkably consistent across industries, types of jobs, types of performance measures, and time frames and indicate that individual performance is not normally distributed—instead, it follows a Paretian (power law) distribution. Assuming normality of individual performance can lead to misspecified theories and misleading practices. Thus, our results have implications for all theories and applications that directly or indirectly address the performance of individual workers including performance measurement and management, utility analysis in preemployment testing and training and development, personnel selection, leadership, and the prediction of performance, among others.

Research and practice in organizational behavior and human resource management (OBHRM), industrial and organizational (I-O) psychology, and other fields including strategic management and entrepreneurship ultimately build upon, directly or indirectly, the output of the individual worker. In fact, a central goal of OBHRM is to understand and predict the performance of individual workers. There is a long-held assumption in OBHRM that individual performance clusters around a mean and then fans out into symmetrical tails. That is, individual performance is assumed to follow a normal distribution (Hull, 1928; Schmidt & Hunter, 1983; Tiffin, 1947). When performance data do not conform to the normal distribution, then the conclusion is that the error “must” lie within the sample not the population. Subsequent adjustments are made (e.g., dropping outliers) in order to make the sample “better reflect” the “true” underlying normal curve. Gaussian distributions are in stark contrast to Paretian or power law distributions, which are typified by unstable means, infinite variance, and a greater proportion of extreme events. Figure 1 shows a Paretian distribution overlaid with a normal curve.
"

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05-09-2012, 08:51 PM
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I wouldn't expect anything in the NHL to reasonably follow a bell curve - since for anything you're measuring a hockey ability by, the sample set of National Hockey League players represents the far right end of a bell curve.

For instance, suppose that the NHL-average save percentage is 91%. There's a hell of a lot more people out there who could post save percentages four standard deviations beneath that than there are who could post save percentages four standard deviations above that.

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05-10-2012, 05:01 AM
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The results of the study suggest that the data doesn't fit a Bell curve at all. No matter what end you're talking about. The data fits a power curve.

The authors reveal the software they use and say it works with excel.

"Results reported in Table 1 show that the Paretian distribution yielded a superior fit than the Gaussian distribution in every one of the 54 scientific fields. Recall that a larger chi-square value indicates worse fit and, thus, can be considered an index of badness of fit. As Table 1 shows, the average misfit for the Paretian distribution was 23,888 whereas the misfit of the normal distribution was larger than forty-four trillion (i.e., 44,199,201,241,681)—a difference in favor of the Paretian distribution in the order of 1:1.9 billion. Figure 2a displays a histogram of the empirically observed performance distribution of researchers. To interpret these results further, consider the field of Agriculture (see Table 1). A normal distribution and a sample size of 25,006 would lead to approximately 35 scholars with more than 9.5 publications (three standard deviations above the mean). In contrast, our data include 460 scholars with 10 or more publications. In other words, the normal distribution underestimates the number of extreme events and does not describe the actual distribution well."

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05-11-2012, 03:48 PM
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Originally Posted by quoipourquoi View Post
Adjusting to the regular season average made more sense to me though. For one, it's a larger sample size that includes all NHL goalies. More than that, it eliminates the issue of a 1995 Dominik Hasek going from an NHL best .930 to a .863 and helping throw the average off from where one would expect it to be from having watched the season. After all, 1995 was one of those rare three seasons in which the playoff save percentage was lower than the regular season save percentage (which really shouldn't happen for any reason other than sample size, given that half the leagues worst teams are out).
I debated whether to compare the numbers to the regular season or playoff average. I used the playoff average because save percentages usually increase in the playoffs (teams are generally more disciplined and conservative, and arguably some of the weaker goalies don't qualify). Thus a 91.5% save percentage might be good in the regular season but merely average in the playoffs.

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Nice to see Kirk McLean up there!
Thanks! McLean benefits because substantially all of his playoff career coincided with his peak (88% of his career playoff games occured between 1992 and 1995). Contrast that with, say, Tom Barrasso, who played a lot of games before and after his peak. Still, a very impressive showing.

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poor poor irbe. ._. And ill chip in my obligatory broken record of I think he should have won the conn smythe in 2k2.
Irbe is tough to evaluate. Brutal numbers in San Jose (86.7% adjusted save percentage), but a strong showing in Carolina (91.4%). Part of that was Irbe improving with age, but it's also partly due to the Hurricanes being better defensively than the Sharks.

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05-11-2012, 03:59 PM
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I think anyone using or assuming Gausian distribution in their adjustments should take a look at the results of this large study which included NHL players.
Here's a chart showing the distribution of adjusted save percentages. I'm only using goalies with 300+ minutes; that threshold is arbitrary, but there needs to be some kind of arbitrary threshold or else we'd be looking at statistically meaningless results for goalies who faced only a few dozen shots.



The largest single category (90% to 91%) straddles the mean and features nearly 25% of all observations. Although there are more observations above the mean than below, the distribution appears to follow roughly a bell curve.

If the average save percentage was 90.5%, but most goalies were actually stopping say 85% but Patrick Roy and a few other superstars were stopping 95%, than another distribution (and therefore another method to evaluate goalies) might be more meaningful. Let me know if I've misunderstood your post.

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05-11-2012, 04:06 PM
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I don’t think that anybody has done a comprehensive study about playoff save percentage. I thought it was an important enough topic to spend a couple of hours analyzing the data.
Just curious... Have you been able to also make some kind of adjustment for shots against when playing penalty killing? I would think that you (or others), even if not providing it here, may have thought about it? If you (or someone else) have looked, are there any particular things/patterns that stands out?

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05-11-2012, 04:17 PM
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Just curious... Have you been able to also make some kind of adjustment for shots against when playing penalty killing? I would think that you (or others), even if not providing it here, may have thought about it? If you (or someone else) have looked, are there any particular things/patterns that stands out?
I haven't made an adjustment for penalty killing. (For those who are unfamiliar, what we mean is that a goalie who plays on a (un)disciplined team would face a disproportionately low (high) percentage of powerplay shots, which are significantly more likely to result in a goal).

All the data I used was taken from hockey-reference.com because it's well formatted and easy to use. That website doesn't have ES/PP/SH shot and save breakdowns. I know that data exists on NHL.com back to 1998, but it would be very time consuming to merge the data from those two websites. I'm not sure if that type of data even exists prior to 1998.

In summary, although I think it would be valuable to take that information into account, but I'm not sure if it exists prior to 1998, and I'm not willing to spend the countless hours it would take to merge and clean the data after 1998.

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05-11-2012, 04:26 PM
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Originally Posted by Hockey Outsider View Post
If the average save percentage was 90.5%, but most goalies were actually stopping say 85% but Patrick Roy and a few other superstars were stopping 95%, than another distribution (and therefore another method to evaluate goalies) might be more meaningful. Let me know if I've misunderstood your post.
Ultimately, it's not going to be a normal distribution, but (something) reasonably approximating the right-end tail of one. There are thousands of goaltenders out there who could post an NHL save percentage six standard deviations lower than the NHL average, and on the other hand, there are none (because none would get that opportunity).

The other poster is suggesting that it follows a power distributions, and he's probably right (I've written and spoke enough on the topic to know that power distributions handle outliers far more reasonably). I don't think that it matters too much in this context.

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05-11-2012, 04:37 PM
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Originally Posted by Hockey Outsider View Post
I haven't made an adjustment for penalty killing. (For those who are unfamiliar, what we mean is that a goalie who plays on a (un)disciplined team would face a disproportionately low (high) percentage of powerplay shots, which are significantly more likely to result in a goal).

All the data I used was taken from hockey-reference.com because it's well formatted and easy to use. That website doesn't have ES/PP/SH shot and save breakdowns. I know that data exists on NHL.com back to 1998, but it would be very time consuming to merge the data from those two websites. I'm not sure if that type of data even exists prior to 1998.

In summary, although I think it would be valuable to take that information into account, but I'm not sure if it exists prior to 1998, and I'm not willing to spend the countless hours it would take to merge and clean the data after 1998.
I can understand that. It was just that I remember someone doing it for the regular season, and that it might have been you. I haven't looked into the playoffs at all myself, and have no idea how much that kind of adjustment would change stats. For example, Philadelphia used to take many penalty minutes during the regular season, and if that meant they played more PK than most other teams, it may even further push their goalies up (Lindbergh. Perhaps Parent?) (But this is to me completely hypothetical as I don't even know if they played more PK during the playoffs than other teams.)

I think you have a few duplicates in your third table, the one showing Stanley Cup winners. I noticed it when counting the occurences of Patrick Roy's name, but also Fuhr occurs twice. Roy anyhow looks impressive! Before I started spending time here, I suspected he might have been somewhat overrated, because I've seen him make many mistakes too (especially when handling the puck behind/around the net). But in threads like this one he (or his stats) lives up to his high reputation.

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05-11-2012, 04:40 PM
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Originally Posted by plusandminus View Post
I can understand that. It was just that I remember someone doing it for the regular season, and that it might have been you. I haven't looked into the playoffs at all myself, and have no idea how much that kind of adjustment would change stats. For example, Philadelphia used to take many penalty minutes during the regular season, and if that meant they played more PK than most other teams, it may even further push their goalies up (Lindbergh. Perhaps Parent?) (But this is to me completely hypothetical as I don't even know if they played more PK during the playoffs than other teams.).
Since we don't know the PPOA for the teams in the playoffs before a certain year, this would have to be estimated using team PIM. But we do have enough information available to draw reasonable conclusions: The fighting majors earned by the teams in the regular season, the number of PIMs they had, and the number of PPOAs those PIMs resulted in. You would get results that are pretty close, I think.

If anyone really wants to do the work, they can scour the HSP game-by-game to find exactly how many PPs each team faced.

You are right that facing a higher percentage of your shots from the PP is going to drag down your sv%. Adjusting for actual shot quality is probably more important than just situational adjustments, but particularly for pre-lockout seasons where that data doesn't exist I think situational adjustments get us closer to the truth than further away.

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05-11-2012, 05:30 PM
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Originally Posted by Taco MacArthur View Post
Ultimately, it's not going to be a normal distribution, but (something) reasonably approximating the right-end tail of one. There are thousands of goaltenders out there who could post an NHL save percentage six standard deviations lower than the NHL average, and on the other hand, there are none (because none would get that opportunity).

The other poster is suggesting that it follows a power distributions, and he's probably right (I've written and spoke enough on the topic to know that power distributions handle outliers far more reasonably). I don't think that it matters too much in this context.
Thanks for the explanation - I have a better understand of that now.

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I can understand that. It was just that I remember someone doing it for the regular season, and that it might have been you. I haven't looked into the playoffs at all myself, and have no idea how much that kind of adjustment would change stats. For example, Philadelphia used to take many penalty minutes during the regular season, and if that meant they played more PK than most other teams, it may even further push their goalies up (Lindbergh. Perhaps Parent?) (But this is to me completely hypothetical as I don't even know if they played more PK during the playoffs than other teams.)
Yes, I looked into it with my recent post about 2009-2012 regular season stats. I think shot situations are worth taking into account, though of course there's a trade-off. In this case, I decided that the additional information that this adjustment would produce is not worth the dozens of hours it would take me to accumulate, organization and analyze the data. If anyone is interested in doing this, I can send them what I've worked on thus far.

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I think you have a few duplicates in your third table, the one showing Stanley Cup winners. I noticed it when counting the occurences of Patrick Roy's name, but also Fuhr occurs twice. Roy anyhow looks impressive! Before I started spending time here, I suspected he might have been somewhat overrated, because I've seen him make many mistakes too (especially when handling the puck behind/around the net). But in threads like this one he (or his stats) lives up to his high reputation.
Thanks, that's a good catch. I updated the table.

Had you asked me five years ago, I would have said that Hasek was the greatest goalie of all-time by a sizable margin. Although I still have Hasek first, I now rank Roy a very close second. Relative to their peers, Hasek was only marginally better at stopping the puck than Roy (though I do recognize that Hasek played against a better peer group).

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