Non-traditional metrics: PDO
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08-09-2012, 01:07 PM
Join Date: Dec 2010
Originally Posted by
Czech Your Math
I still don't see the difference. If a team is scoring 4 GPG in today's NHL, or giving up 1.5 GPG, it will also likely regress to the mean. However, if the 80s Oilers were scoring 1 GPG more than the league, I wouldn't hold your breath waiting for it to "regress to the mean." It's being proposed that PDO should be 1000 for all teams and individuals, but that's not even close to being true.
I gave examples of teams whose overall S% +SV% generally stayed above or below the mean over multiple seasons:
Islanders were 985, 986, 989, 998, and 984 the last 5 seasons.
Columbus was 990, 999, 994, 984, and 984 the last 5 seasons.
Toronto was 986, 981, 975, 997, and 998 the last 5 seasons.
These teams weren't unlucky, they were just below average. I doubt Toronto was "less unlucky", but instead was "less bad."
When Boston won the Cup two years ago, they were 1023 during the season. They improved to 1042 in the playoffs. How is that regressing to the mean? Yes, teams will regress to the mean over multiple seasons, because there's a lot of parity and teams change from year to year. They add players, they lose players, players get better, players get injured.
I gave examples of teams whose overall S% + SV% generally stayed above or below the mean over multiple seasons:
Vancouver was 1006, 1018, 1019, 1026 and 1019 the last 5 seasons.
Boston was 1004, 1036, 998, 1023 and 1019 the last 5 seasons.
Those teams weren't lucky, they were good, especially their goalies.
How is it primarily luck-driven, when the best teams tend to be higher and the bad teams tend to be lower over multiple seasons? The bad teams provide better examples in general, because it's a lot easier to be bad than good. Somehow, certain teams tend to remain lucky:
I know some people that will be glad to know that Gretzky was simply lucky and not great.
Sigh. You take a team measurement and then use it to logically conclude that Gretzky is lucky? Do you see the logical fallacy there?
The teams you picked have some of the best shot differentials over the past 5 seasons - a much better indicator of success - and also feature two of the most extreme examples of shooting percentage and save percentage outliers respectively: the Sedins and Tim Thomas.
Why don't you take a look at all 30 teams at once, like a true statistical analysis would. Maybe you would be surprised to find that on average teams regress to 1000.
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