Flames Expectations First Update
By RexLibris
9 years agoAt 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.
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.
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).
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).
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.
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.
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.
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.
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.
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.
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.
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.
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%).
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.
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.
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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