Predicting The Oilers Ups And Downs For 2011-2012
"It is exceedingly difficult to make predictions, particularly about the future."
--Niels Bohr
Predictions are a funny business. It's not difficult to make simple predictions based on logic and mathematical principle and hit a number of them on the button. Move away from the simple, towards the absurd and predictions become more difficult. Leave the realm of numbers completely and predictions become a Sisyphean endeavor, though with experience, sometimes accuracy is unavoidable. In hockey analytics, one area of success has been using underlying stats to predict future performance, both at the team level and individual level. The application of some very simple formulas in combination with some even simpler comparisons can determine those Oilers who will rebound in 2011-2012 and those who will fall.
First some definitions of the stats used in this post. PDO, like an element on the periodic table, was discovered by and named for PDO, a frequent and bright commenter in the Oilogosphere. It was developed by Vic Ferrari at Irreverent Oiler Fans. Behind The Net Hockey has a simple definition for PDO:
It is just Save Percentage plus Shooting Percentage [more precisely: PDO=1000*(G/SF+SV/SA)]. What's interesting about it is that it trends very heavily - at the individual level or the team level - to its mean of 1000. But it is possible to assemble a team that plays above 1000.
MC79hockey did a wonderful job of breaking out the number in a series of posts, here. PDO can be found on the Corsi report at www.behindthenet.ca.
On Ice Sh % is the even strength team shooting percentage while the player is on the ice. On Ice Sh % can also be found on the Corsi report at www.behindthenet.ca. On Ice Sv % is the even strength team save percentage while the player is on the ice, and can once again be found on the Corsi report at www.behindthenet.ca.
How is this information instructive? Tyler and Gabe showed us that, except for the very best, PDO will cluster around 1000. We also know that over time shooters will shoot at their established rate and fall off as they age. Like a simple stock trading program, I set the spreadsheet up so that the top five values of concern in each category are in red and the top five values of interest in each category are in green. A bunch of red cells mean that it's likely that the player in question will see reversion and a bunch of green cells mean it's likely that the player in question will see improvement.
| Player | On Ice Sh% | On Ice Sv% | PDO | 10-11 Sh% | Career Sh% | Difference |
| Taylor Hall | 9.21 | 899 | 991 | 0.118 | N/A | N/A |
| Shawn Horcoff | 8.45 | 924 | 1008 | 0.115 | 0.126 | -0.010 |
| Andrew Cogliano | 6.93 | 905 | 974 | 0.085 | 0.130 | -0.045 |
| Jordan Eberle | 7.91 | 896 | 975 | 0.114 | N/A | N/A |
| Colin Fraser | 6.12 | 934 | 995 | 0.053 | 0.080 | -0.027 |
| J.F. Jacques | 4.38 | 929 | 972 | 0.143 | 0.059 | 0.084 |
| Linus Omark | 6.85 | 889 | 957 | 0.066 | N/A | N/A |
| Ryan Jones | 8.05 | 925 | 1005 | 0.143 | 0.120 | 0.023 |
| Zack Stortini | 8.54 | 912 | 997 | 0.000 | 0.113 | -0.113 |
| Gilbert Brule | 7.25 | 919 | 992 | 0.097 | 0.098 | -0.001 |
| Ales Hemsky | 12.09 | 900 | 1021 | 0.140 | 0.116 | 0.024 |
| Liam Reddox | 5.31 | 906 | 959 | 0.012 | 0.098 | -0.086 |
| Sam Gagner | 9.71 | 876 | 973 | 0.109 | 0.095 | 0.013 |
| Magnus Paajarvi | 7.91 | 904 | 983 | 0.083 | N/A | N/A |
| Jim Vandermeer | 7.21 | 905 | 977 | 0.035 | 0.056 | -0.021 |
| Ladislav Smid | 7.76 | 908 | 985 | 0.000 | 0.024 | -0.024 |
| Ryan Whitney | 12.5 | 935 | 1060 | 0.047 | 0.070 | -0.024 |
| Kurtis Foster | 7.05 | 917 | 987 | 0.044 | 0.052 | -0.008 |
| Jason Strudwick | 4.95 | 905 | 954 | 0.000 | 0.054 | -0.054 |
| Theo Peckham | 8.69 | 916 | 1003 | 0.073 | 0.000 | 0.073 |
| Jeff Petry | 7.36 | 885 | 959 | 0.024 | N/A | N/A |
| Tom Gilbert | 8.77 | 889 | 976 | 0.057 | 0.076 | -0.019 |
Expected counting numbers increase
- Andrew Cogliano - For the second consecutive year, Cogliano's shooting percentage was well below his career average. Last year his 7.2% shooting percentage greatly reduced his career average and this year's 8.5% wasn't much better. Is he closer to the 16.8% shooter from his first two years in the league or is he closer to the 7.8% shooter he's been over the last two years?
- Zack Stortini - He doesn't score many goals, but his 10-11 shooting percentage of 0% is slightly lower than his career average.
- Linus Omark - He doesn't have an NHL history, but he has a body of work in the SEL and KHL that suggests Omark will at least double his shooting percentage of 6.6% The goals will follow.
Expected counting numbers decrease
- J.F. Jacques - Though he's no longer in Edmonton, the team that picks him up should expect his goal-scoring to decrease. He shot 14% last year, three times his career rate.
- Ales Hemsky - The sample size was small, but 14% is slightly above his career rate.
- Ryan Whitney - His unbelievable PDO led to a career offensive season. His on-ice shooting percentage should fall significantly in the coming season and his assists will fall off sharply.
Underlying stats expected to improve
- Linus Omark leads the way here. He was a -15 in 51 games at even strength, but with an average PDO, Omark would have been -1 at even strength. Both his on-ice shooting percentage and on-ice save percentage were among the worst on the team last season.
- Jeff Petry was -11 in 35 games at even strength, but a league-average goaltender could have bailed him out. With a .920 even strength save percentage, he would have been -1. With an 8% on-ice on shooting percentage, he would've been +1.
Underlying stats expected to decline
- Ryan Whitney - With his on-ice shooting percentage and his on-ice save percentage set to fall, his PDO will revert back towards 1000 and bring his traditional +/- with it.
- Ales Hemsky - His on-ice shooting percentage should decline (part of which will be driven by his own shooting percentage reversion).
If Ryan Whitney was healthy and without an injury history, his trade value would never be higher. Of course, suggesting a Whitney trade to the casual fan would be looked upon as lunacy. It will be interesting to see just how far Linus Omark bounces back as his numbers settle in where they belong. There's a real possibility that he will amaze a number of observers with his point totals next year. With moderate power play minutes next season, I wouldn't be surprised to see Omark average .6 points per game and clock in at 50-55 points in 2011-2012.
16 comments
|
0 recs |
Do you like this story?
Comments
Curious what your cut off is for ONSV% improvement?
I see Hall with a .899, Eberle .896 and not tagged for improvement, but Omark and GIlbert are at .889.
Just for fun I just looked at EVSV% for all NHL goalies who played at least 20 games last year. There were 51 goalies who played 20+ games (my arbitrary number).
The median was .922
DD was .921
Khabby was .905
If the Oilers add another relatively competent goalie, perhaps we can expect an improvement for everyone under .900? (variance aside)
Fun fact – out of the 566 NHL player who played at least 40 games last year, Sam Gagner was last in the league for ONSV% with a .876
The median was .918
Can’t wait for the Oilers to trade him and then everyone say “Sam just needed a change of scenery” when his underlying numbers even out and has a good year.
Also,
You’ve been banging the Ray Emery drum for the Oilers. He only played 10 games, but his 5v5 SV% was .935
No way Tambellini goes for him though, he doesn’t like “problem children”
Sam has come around. I’ve said a number of times that he can’t carry a line yet, but he’s only 22. When he has competent wings, he’s pretty good. I’m sure I’m going to take a ton of guff for the ranking I’ve given him in the summer top 25 under 25.
Editor of The Copper & Blue, and leader of The Cult Of Hartikainen.
As I recall, you took a ton of guff for the ranking you gave him in our last top 25!
The biggest fanana of the Havana Bananas.
by Scott Reynolds on Jul 4, 2011 11:37 AM MDT up reply actions
I’m going to again. I can’t wait.
Editor of The Copper & Blue, and leader of The Cult Of Hartikainen.
The problem is that there will always be outliers, even on the same team.
Even with “good” goaltending There are going to be guys that get a .950 sv% while on the ice and others who get saddled with a .895.
In theory, there is little difference between practice and theory, but in practice there is!
That’s why I wrote “(variance aside)”
You will get your outliers every year, but with a better goalie than Khabby playing a number of games, the median should be higher.
Median 5v5 ONSV% was .905 on the Oilers, and was .918 league wide.
If the Oilers improve in net, we can expect the median to improve as well.
I dunno about the “problem children” thing, Tambo IS the GM that picked up Jesse Boulerice on waivers and just signed UFA Ben Eager, two guys not necessarily known for being complete gentlemen on the ice.
I’m still a little new to this stuff. League average ONSH% is 8.5%, and average ONSV% is what? 920? So any player that strays significantly from these medians should expect to regress back, correct?
by melancholyculkin on Jul 4, 2011 12:05 PM MDT reply actions
ONSH% + ONSV% = 100% for the league as a whole. So if ONSH% is 8.5%, then ONSV% is 91.5%.
Puck Worlds: Chasing Pucks from here to Turku.
For Twitter Updates on Puck Worlds, follow @puckworlds. For updates plus additional witty banter from yours truly, follow @saskhab.
To what extent can individual skill and/or systems impact these numbers? For example, over the past two seasons Stamkos has had ONSH% of 10.92% and 11.56%. How much of that do we attribute to luck and how much to skill?
by melancholyculkin on Jul 4, 2011 6:37 PM MDT up reply actions
Tyler and Gabe showed us that, except for the very best, PDO will cluster around 1000
So yes, individual abilities will have an impact on this, more so on the shooting% side.
In theory, there is little difference between practice and theory, but in practice there is!

by 

























