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Pre-season Player Projection Review
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Kent Wilson
Apr 8, 2011, 10:14 EDT
(Rob Vollman of Hockey Prospectus returns to take a look at his pre-season player projections)
In October we used the Snepsts System to search the NHL’s vast historical database to find players with era-adjusted statistics comparable to today’s Flames, and used their average to project their performance this season.  Let’s look back and compare that with their actual results (well, minus their final game).
Part 1: http://flamesnation.ca/2010/9/28/flames-comparables-part-1
Part 2: http://flamesnation.ca/2010/9/29/flames-comparables-part-2
Part 3: http://flamesnation.ca/2010/10/2/flames-comparables-part-3
Remember that games played aren’t part of the projection system; all projections were made based on a full 82-game season.  Without further ado, let’s dive in with the Flames celebrated captain.
Jarome Iginla
Worst (Langkow)              82 23 30  53
Best (Fedorov)               82 38 51  89
Average                      82 27 37  64
Actual                       81 42 43  85
Based on our projections, we didn’t expect the two-time Olympic gold medalist to enjoy his amazing 10th straight 30-goal season, and even the optimistic folks at Behind the Net reached a consensus of 75 points, just shy of the 1000-point career mark.  Luckily Iginla fought his way past that, all the way up to the best-case, Sergei Fedorov level.  Keep this in mind next season, and focus on the best-case scenario instead of the average.
Olli Jokinen
Worst (Arvedson)             82 17 23  40
Best (Boldirev)              82 27 39  66
Average                      82 21 32  53
Actual                       78 17 37  54
While his shooting percentage did bounce back from 6.4%, a few too many goal posts stood in the way of it reaching 10%, and his consequently falling just shy of the 21-goal projection.  Otherwise Jokinen performed exactly as history suggested.
Alex Tanguay
Worst (Grosso)               82  0  6   6
Best (Reay)                  82  9 52  61
Average                      82 14 28  42
Actual                       78 22 46  68
As predicted, Tanguay’s shooting percentage did bounce back, and he did indeed exceed the average historical projection, and by more than we expected.  Of the historical comparables only two of them were on pace for the modern-day equivalent of 20 goals, and just barely.  Like Iginla, Tanguay finished at the best-case end of expectations, and perhaps a touch beyond.
Rene Bourque
Worst (Gould)                82 13 21  33
Best (Schmautz)              82 25 38  63
Average                      82 23 29  52
Actual                       79 27 23  50
While we generously hoped that Rene Bourque had a legitimate shot at the high-end, 60+point end of expectations, we’re still pleased that we got a full, healthy season out of the veteran winger, resulting in a season almost dead-on with historical projections.
Matt Stajan
Worst (Smith)                82  8 14  22
Best (Ribeiro)               82 30 61  91
Average                      82 18 36  54
Actual                       75  6 25  31
Unfortunately we grossly miscalculated with Matt Stajan, believing he was “on the brink of breaking the 20 goal and 60 point barriers” that he “could actually be Tanguay’s equal as a playmaker,” and optimistically taking the over on his 54-point projection.  Sadly he spent most of the season struggling closer to the low, Derek Smith end of expectations.
Niklas Hagman
Worst (Clark)                82  2 12  14
Best (Wharram)               82 34 39  73
Average                      82 17 22  39
Actual                       71 11 16  27
Before the season began, we figured Hagman was “bound to return to his previously-established scoring level of 21-29 points eventually – will it be this year?”  As we feared, fighting for ice-time on the left side is going to keep Hagman from hanging on to the 20-goal, 40-point level for the remainder of his high-price contract, leaving the Flames with a $3.0 million version of Mike McPhee.
Jay Bouwmeester
Worst (Smehlik)              82  4 13  17
Best (Gadsby)                82 16 44  60
Average                      82 10 27  37
Actual                       81  4 20  24
Quite frankly, Bouwmeester’s lack of offense was shocking.  We felt very comfortable that “his goal scoring would bounce back to a double-digit threat” and that the historical average projection would be accurate.  As encouraging as his defensive play has been, it’s rather unfortunate to pay $6.68 million for someone with the limited offense of a Richard Smehlik.
Ian White
Worst (Pothier)              82  3 10  13
Best (Wideman)               82 13 37  50
Average                      82  9 24  33
Actual                       76  2 22  24
He may have changed addresses a couple of time this season, but it’s still interesting to see how close White came to meeting expectations.  Despite a career shooting percentage near 5%, he hasn’t scored a single goal in his 95 shots since leaving the Flames, so a little more luck and he’d have nailed it.
Mark Giordano
Worst (Burt)                 82  4  9  13
Best (Keith)                 82  8 37  45
Average                      82  7 21  28
Actual                       81  8 33  41
We asked whether his 30 point season was “his high-water mark, or a stepping stone to an even higher level?” and boy did he answer.  Last year we felt that the comparison to Duncan Keith was overly flattering, but we may have been mistaken.  Giordano’s scoring is indeed following the same trajectory as Keith’s, albeit at two years older.  Dare we dream that a 69-point, Norris-caliber season is upon him?
Wrap Up
Looking at all 9 projections (we left out Daymond Langkow’s for obvious reasons), the Flames as a group performed almost exactly as projected, even a couple points better when you adjust for the extra 5 games.
Average                      82 16 28  44
Actual                       77 15 29  44
 
That’s the trick with projections.  Despite how wide a net history cast, it just barely caught players like Iginla, Tanguay and Giordano at one end, and Bouwmeester, Stajan and Hagman at the other.  Over a sufficiently large sample size they’ll usually average, which was the case this year in Calgary.  Still, it’s useful to see how players matched up to objective, historical expectations rather than our own.
Is there any interest in doing this again next year?