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Flames Expectations First Update
alt
RexLibris
Dec 8, 2014, 10:30 ESTUpdated: Invalid DateTime
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At the beginning of the
season I took a look at the Flames and ran some numbers like sh%, ppg pace,
historical games played and the like. Using that information I estimated the
number of games played, estimated sh%, sv%, and so on for the Flames players.
Most times we stop at the
quarter-points of the season to assess a team. I’m choosing to stop at the
one-third marker in order to provide a larger sample size and to try to bridge
some of the borders that exists within a season, to blur the edges so to speak,
so that the data may have a bit more applicability to the larger season rather
than being a snapshot of the here and now.
There is quite a lot of data,
so bear with me, but I hope that what will become clear is the enormously high
percentages that the Flames are currently riding (and their fan base thereby
enjoying).
Here is a link to the
original articles for forwards and defense.
Now, to the Great Tableau of Data (I apologize for the ugly format)
 

Player
est. gp  
actual
  gp   
  gp
 pace 
est. ppg
hist. ppg
hist.
sh%   
 actual
  sh%
  est.
  pts.
   pts
  to date
 pts pace
Hudler
80
25
78
0.7
0.56
14.2
26.2
56
25
78
Stajan
70
11
35
0.48
0.48
13.3
11.1
33.6
2
7
Glencross 
78
26
82
0.6
0.55
15
8.9
47
16
50
Raymond
75
10
31
0.5
0.49
9.7
20.8
38
7
57
Monahan
75
26
82
0.4
0.45
12
13.2
30
17
53
Colborne
80
11
35
0.35
0.35
12
0
28
8
57
Jones
70
13
41
0.4
0.45
13.7
16.7
28
6
20
Backlund
73
11
35
0.5
0.41
8.5
5.6
37
4
12
Byron
70
26
82
0.38
0.36
15
13.9
26
10
26
Baertschi
41
13
41
0.42
0.47
8.7
0
17
3
9
Bouma
73
25
78
0.18
0.16
5.1
20.8
13
9
28
Bollig
70
24
75
0.15
0.11
4.4
0
11
2
6
McGrattan
60
7
22
0.1
0.09
5.1
0
6
0
0
Van Brabant
15
0
0
0.08
NA
0.05
0
2
0
0
Agostino
12
0
24
0.2
NA
8.3
0
2
0
0
Gaudreau
70
25
78
0.55
NA
NA
8.9
38
19
59
Wolf
15
0
0
0.05
NA
NA
0
1
0
0
Arnold
12
0
4
0.25
NA
NA
0
3
0
0
Knight
20
2
7
0.35
NA
NA
0
7
0
0
Granlund
20
15
48
0.35
NA
NA
13
7
9
29
Jooris
10
19
60
0.25
NA
NA
27.6
2.5
12
38
Hanowski
20
0
34
0.25
NA
NA
0
5
0
0
Reinhart
12
4
12
0.26
NA
NA
0
3
0
0
Ferland
10
7
22
0.29
NA
NA
0
3
0
0
Bennett
9
0
0
0.33
NA
NA
0
3
0
0
Setoguchi
73
12
37
0.48
0.54
11.4
0
35
0
0
Giordano
82
26
82
0.53
0.44
7.1
10.3
43
26
82
Brodie
82
26
82
0.32
0.46
4.1
13.3
26
21
65
Wideman
75
25
78
0.47
0.47
6
15.1
32
15
46
Engelland
75
21
66
0.14
0.19
5.7
0
11
2
7
Russell
70
24
75
0.35
0.29
5.2
0
25
10
31
Diaz
42
10
31
0.25
0.29
3.6
0
8
0
0
Smid
76
24
75
0.11
0.13
3.6
0
8
1
3
Wotherspoon
30
0
0.15
0.19 (AHL)
0.5
0
5
0
0

Player   
est. gp  
gp pace  
est. shpg  
shpg actual  
est. sv% 
 sv% actual 
est ga/game  
ga/game actual
Hiller
68
50
28.5
28.1
0.912
0.913
2.5
2.49
Ramo
14
32
28.6
27.4
0.905
0.921
2.7
2.25
0.9085
0.917
2.6
2.37

(Player data taken from Flames website)
I had the Flames pegged at
about 206 goals for this season. Their current pace puts them at 253 goals for
on the season.
Hiller’s actual sv% is out by
0.001 and Ramo’s is ahead by 0.016, substantial improvement over his career
average. The goals against per game was estimated at 2.6 on average and the Flames
are currently averaging 2.5 goals against and 3.08 goals for per game. Ramo is
playing more often than anticipated, obviously on account of his strong play
thus far, and is on pace to play 32 games this season.
The rest of the data more or
less speaks for itself. Giordano is on a ppg pace with Brodie not far behind.
Wideman, surprisingly, isn’t actually off his career pace.
As expected, Jiri Hudler
looks like the forward offensive engine of the team with a collection of other
players chipping in offense, albeit at a far more productive level than
anticipated, and there are a few players whose offensive output has been underwhelming
thus far but are being sheltered by the output of others in the roster or are
seeing diminished results due to injuries.
As of December 3rd,
when this information was collected, Calgary had four players in the top 30 in
the NHL for shooting percentage for players who have played more than 10 games.
All of those were above 20%. No other team had that many. Those players are
Jooris, Raymond, Hudler and Bouma, one core player, two complementary talents
and a rookie.
I’m going to include a table
here showing PDO history for seasons dating back to 2009-2010. I’ve selected
the teams from each season whose PDO was above 100 and tracked them the
following season. I’ve marked the 2012-13 season with an asterisk to denote the
lockout-amended season and put an exclamation point in front of this season because
we are only one-third complete.
The Finish column denotes
where the team finished while the Following column marks where that same team
finished the following season. I’ve kept Conference standings rather than
overall standings to highlight the difference in competition between the two
conferences and thereby reflect the perception that the Western Conference is
the more difficult of the two.
In the final column I note
the difference in standings from one season to next with the coloured cells
highlighting positive adjustments from one year to another and all others being
negative adjustments. The majority of the events show a regression in the following
season, with some season-by-season eccentricities such as a universal
regression by all teams in 2012-13 and a 50/50 split on regression in 2013-14.
The sum total of all standings adjustments was -35, meaning that the overall
trend was for teams to lose ground the following season, while the average
standing loss was -1.4 places following a PDO peak with the most common
occurrence being a setback of 1 place in the standings.
Before we begin, I’d like to address PDO as a concept. I think this statistical category is useful, but misunderstood. Like Corsi, Fenwick and others, it is one tool in helping to illustrate a larger picture. When we say that PDO historically regresses towards the mean, it doesn’t mean that every single team will ultimately come back to 100. Some teams are better than others for long stretches and there is always the role of the exceptional individual to account for. But, by and large, teams that have shooting percentages that sit at 15% or a save percentage around 0.941 for a season are unlikely to sustain that peak for too long a time. The league is too good and the parity amongst teams far too strong for that kind of advantage to be maintained.
Also, the mean that we refer isn’t as strict as many believe it to be, just as strong possession numbers are an indicator of a good team but not necessarily a proxy for one. Mikael Backlund and Kyle Brodziak have been possession darlings in the past and neither was ever in danger of being voted to the All-Star team as a result of it. But both are very good players to have on a team, and successful teams usually have one or two of those guys on them, and if they have elite-level talent as well then those teams tend to win championships. It is a correlation, not a causation. With PDO, don’t look for the teams that are always at the top of the list, instead check for the teams making a cameo. The exceptions, in this case, often prove the rule.
Think of it like weather. The average daily temperature for Calgary in December is -2 Celsius. It may never actually be -2 C in Calgary during that month, but on average the temperatures during the day will even out to somewhere within that range. There will be hotter days and colder ones, just as there are better and worse teams in the NHL. The good teams have better players who may have higher shooting percentages or goalies with higher save percentages. It comes back to the basic philosophy of sport: to win you need better players. Going back to our weather analogy, if you woke up one mid-December day and it was 15 degrees above you probably wouldn’t think that Calgary was now in an equatorial climate zone. You are more likely to think that there are some funky weather patterns messing things up and would expect it to go, more or less, back to normal in a little while.
 
Team 
PDO     
Sh%   
Sv%    
Finish      
Following  
PDO      
Difference
2009-10
Wsh
103.15
10.30
0.928
1st EC
1st EC
100.18
-1
Van
101.71
9.35
0.923
3rd WC
1st WC
101.53
2
SJ
101.65
8.71
0.929
1st WC
2nd WC
100.21
-1
Col
101.50
8.89
0.926
8th WC
14th WC
99.33
-6
Ana
100.99
8.19
0.927
11th WC
4th WC
100.13
7
2010-11
Bos
102.43
8.29
0.941
3rd EC
2nd EC
101.41
-1
Nsh
101.62
8.17
0.934
5th WC
4th WC
101.04
-1
Van
101.53
8.19
0.933
1st WC
1st WC
101.35
Phi
101.38
8.74
0.926
2nd EC
5th EC
100.44
-3
Phx
101.32
8.02
0.933
6th WC
3rd WC
101.18
3
Dal
101.19
8.69
0.925
9th WC
10th WC
99.83
-1
2011-12
Det
101.50
8.75
0.927
5th WC
7th WC
100.19
-2
Bos
101.41
9.02
0.923
2nd EC
4th EC
100.51
-2
Van
101.35
8.20
0.931
1st WC
3rd WC
100.59
-2
Phx
101.18
8.03
0.931
3rd WC
10th WC
100.35
-7
NYR
101.08
8.35
0.927
1st EC
6th EC
100.92
-5
Nsh
101.04
8.47
0.925
4th WC
14th WC
99.54
-10
*2012-13
Tor
102.99
10.67
0.923
5th EC
12th EC
101.20
-7
Pit
102.82
9.66
0.931
1st EC
2nd WC
100.06
-1
Chi
102.03
9.08
0.929
1st WC
5th WC
99.87
-4
Ana
101.72
8.65
0.931
2nd WC
1st WC
102.32
1
CBJ
101.63
8.70
0.929
9th WC
7th EC
100.72
2
Wsh
101.41
8.61
0.928
3rd EC
9th EC
100.16
-6
Dal
101.29
9.47
0.918
11th WC
8th WC
100.34
3
TB
101.23
9.80
0.914
14th EC
3rd EC
100.58
9
Mtl
101.03
8.93
0.921
2nd EC
4th EC
100.54
-2
2013-14
Bos
102.46
8.46
0.939
1st EC
Ana
102.32
9.79
0.925
1st WC
Col
101.75
8.80
0.929
2nd WC
Tor
101.20
8.40
0.927
12th EC
Min
101.13
7.91
0.932
7th WC
!2014-15
Pit
102.89
9.17
0.937
Nsh
102.90
8.26
0.946
Cgy
102.37
9.78
0.925
LA
101.80
7.96
0.938
TB
101.41
9.82
0.915
Tor
101.19
9.59
0.916
NYR
101.12
9.21
0.919
StL
101.00
7.17
0.938

(PDO data taken from War on Ice)
What this data means for the
Flames is that they are likely experiencing a PDO peak (aka lightning in a
bottle) and can be reasonably expected to have a regression. Unless you believe the Flames, as a team, are going to maintain a shooting percentage of 9.78 (league average this year is 8.85 and hasn’t been above 9.5% since 2006-07, in fact this site has the Flames’ sh% at an astonishing 11.54%).
The Flames’ save percentage is high, but not abnormally so, in my opinion. I would suggest that Pittsburgh, Nashville and St. Louis are likely to see a correction there from their lofty sv% heights, less likely with L.A. based on the history of Jonathan Quick as a player and the L.A. Kings’ playing style in limiting scoring chances against.
This does not
necessarily mean that a Flames’ regression will occur this season and when it does eventually, because it
will, it may not necessarily be a catastrophic collapse into the bottom of the
league (think Colorado over the past few years), but may result in the
team hovering around a few places mid-standings.
There are quite a few factors
waiting to play out, namely consistency in this season personnel and asset
decisions at the trade deadline and the eventual inclusion of prospects like
Sam Bennett, so we will see how the team evolves over the next few months.

Why this song?

Heavy Fuel isn’t one of my favourite Dire Straits songs. Mark Knopfler is a tremendous talent and On Every Street is a great album, but this track always felt out of place, put there by record executives who needed something radio-ready. That being said, the song fits for the Flames. It is about a working man leading a hard life, earning his pay and enjoying every ounce of good fortune that comes his way, deserved or not. Others warn him of the cost of his hard-driving lifestyle, telling him it is unsustainable, but the lure of the road and the joys that come with it are more rewarding.
There are a lot of voices telling the Flames and their fans that this can’t last and they are probably right, but you can’t tell a Flames fan looking at the standings and dreaming about playoff dates and a C of red in May not to be excited about what this team has accomplished.

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