## 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

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.

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