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2009-2010 Edmonton Oilers' Scoring Chances -- The Forwards

The next breakthrough in hockey stats is right around the corner.  A small but dedicated group of online writers have committed to tracking scoring chances by team for the entire NHL season.  Even though it's certain that Roger Neilson was counting scoring chances thirty years ago, the thinking minds and stats crunchers are just now unlocking the secrets contained in the scoring chances charts.  In 2009-2010, Dennis King tracked the Edmonton Oilers through their long and painful voyage to meet Taylor Hall.  Dennis plies his trade at mc79hockey, home of scoring chance tracking for two seasons running.  Scott and I chose to continue the project into the playoffs as we tracked chances for the Avalanche, Blackhawks, Canucks, Flyers, Kings, Red Wings, and Sharks.

For those who'd like a definition: a scoring chance is defined as a clear play directed toward the opposing net from a dangerous scoring area - loosely defined as the top of the circle in and inside the faceoff dots, though sometimes slightly more generous than that depending on the amount of immediately-preceding puck movement or screens in front of the net.  Blocked shots are generally not included but missed shots are.  A player is awarded a scoring chance anytime he is on the ice and someone from either team has a chance to score.  He is awarded a "chance for" if someone on his team has a chance to score and a "chance against" if the opposing team has a chance to score.  And, of course, a big thanks to Vic Ferrari for making the whole damn thing possible with his awesome scripts and Dennis King for counting chances over most of the 2009-10 season, an extra-tedious task considering the state of the Oilers over that time.

Star-divide

Because it was such tedious work, Dennis missed 13 games, some of them around New Year's and most of them towards the very end of the season.  I now believe that Dennis has some sort of precognitive abilities, as he picked some "great" games to miss, at least from an Oiler fan's point of view.  At the end of the season I had grand plans to go back and record the scoring chances for those games using NHL Gamecenter, however, after running through the box scores from those games, I decided against it.

In those 13 games, the Oilers went 4-9, scoring 33 goals and surrendering 50.  The goals for / goals against ratio of .66 during this "stretch" of games was much worse than their season GF/GA ratio of .753, and in fact, the ratio in the other 69 games climbs to .773.  The details of those 13 games are below:

 

Game Date  Teams Game # Score
39  28 Dec '09   CGY @ EDM 20581 1-4 L
40  30 Dec '09   TOR @ EDM 20596 3-1 W
41  31 Dec '09   EDM @ CGY 20608 1-3 L
42  02 Jan '10   EDM @ SJS 20622 1-4 L
43  05 Jan '10   PHX @ EDM 20636 4-5 L
56  04 Feb '10   EDM @ MIN 20848 2-4 L
61  14 Feb '10   ANA @ EDM 20921 3-7 L
66  09 Mar '10   OTT @ EDM 20983 1-4 L
78  03 Apr '10   EDM @ PHX 21173 2-3 SOL
79  05 Apr '10   MIN @ EDM 21181 4-1 W
80  07 Apr '10   COL @ EDM 21196 5-4 W
81  10 Apr '10   EDM @ LAK 21213 4-3 SOW
82  11 Apr '10   EDM @ ANA 21230 2-7 L

 

Rather than record the chances for those 13 games, I went through the box scores and eliminated the even strength goals for on ice and even strength goals against on ice from each player, arriving at their total ESGF and ESGA for the 69 games recorded to use for comparison. 

The table below contains a number of new abbreviations, even for our more stat-oriented readers.  The first five stats all deal with raw scoring chance numbers.  TSC = Total Scoring Chances; TSCA = Total Scoring Chances Against.  Desjardins tends to use rates / 60 when displaying any stat over minutes played, but I've decided to display scoring chances in chances / 15 minutes of on ice even strength time because I feel it allows the reader to see what a player would average per game if given first line even strength minutes. That means that CF/15 = Chances For per 15 minutes of on ice even strength time; CA/15 = Chances Against per 15 minutes of on ice even strength time.  The fifth stat is DIFF/15, or Scoring Chance Differential per 15 minutes of on ice even strength time.

The next three columns are traditional even strength goals for and even strength goals against stats, totaling the goals scored for and against during the 69 games measured in 2009-2010.

The last four columns are more for a meta-analysis of the relationship between chances and goals scored.  CF/GF is simply Chances For / Goals For, and CA/GA is Chances Against / Goals Against.  The relationship shows how many chances per goal were recorded while on ice.  The final two columns show that relationship by percentage.  %CONF is the percentage of chances converted for; %CONA is the percentage of chances converted against.

All of the above stats were made up by me throughout the year as I compiled Dennis' game-by-game reports, so if you have suggestions for improving them, or ideas for additional stats you think would be meaningful, let me know.

 

This table is sortable by column -- simply click on the desired column header cell.

#  Player  TSC TSCA CF/15 CA/15 DIFF/15 ESGF ESGA ES+/- CF/GF CA/GA %CONF %CONA
32 R. STONE  73 61 5.010 4.186 0.823 14 11 3 5.214 5.545 19.2% 18.0%
27 D. PENNER  360 328 5.508 5.018 0.490 49 38 11 7.347 8.632 13.6% 11.6%
83 A. HEMSKY  115 112 5.547 5.402 0.145 17 10 7 6.765 11.200 14.8% 8.9%
12 R. NILSSON  195 189 4.670 4.527 0.144 22 36 -14 8.864 5.250 11.3% 19.0%
57 C. MCDONALD 3 3 3.362 3.362 0.000 1 0 1 3.000 - 33.3% 0.0%
89 S. GAGNER  267 273 4.846 4.955 -0.109 34 38 -4 7.853 7.184 12.7% 13.9%
91 M. COMRIE  116 124 4.508 4.819 -0.311 13 22 -9 8.923 5.636 11.2% 17.7%
16 R. POTULNY 188 209 4.474 4.973 -0.500 20 37 -17 9.400 5.649 10.6% 17.7%
67 G. BRULE  227 255 4.610 5.179 -0.569 36 40 -4 6.306 6.375 15.9% 15.7%
13 A. COGLIANO  248 293 4.303 5.083 -0.781 35 34 1 7.086 8.618 14.1% 11.6%
00 FORWARD AVG 2847 3441 4.246 5.132 -0.886 377 499 -122 7.552 6.896 13.2% 14.5%
46 Z. STORTINI  115 160 3.076 4.280 -1.204 22 16 6 5.227 10.000 19.1% 10.0%
19 P. O’SULLIVAN  224 291 4.113 5.344 -1.230 22 54 -32 10.182 5.389 9.8% 18.6%
10 S. HORCOFF  260 350 4.139 5.572 -1.433 26 51 -25 10.000 6.863 10.0% 14.6%
22 J. JACQUES  109 156 3.479 4.979 -1.500 17 30 -13 6.412 5.200 15.6% 19.2%
78 M. POULIOT 68 106 3.456 5.388 -1.932 14 14 0 4.857 7.571 20.6% 13.2%
42 R. O'MARRA 3 6 2.265 4.530 -2.265 1 1 0 3.000 6.000 33.3% 16.7%
33 S. MACINTYRE 0 1 0.000 2.381 -2.381 0 0 0 - - - 0.0%
18 E. MOREAU 175 305 3.347 5.834 -2.486 21 33 -12 8.333 9.242 12.0% 10.8%
34 F. PISANI 74 141 2.902 5.529 -2.627 10 24 -14 7.400 5.875 13.5% 17.0%
85 L. REDDOX 19 41 2.777 5.993 -3.216 3 5 -2 6.333 8.200 15.8% 12.2%
28 R. JONES 1 10 0.555 5.545 -4.991 0 0 0 - - 0.0% 0.0%
36 C. LINGLET 1 5 1.389 6.944 -5.556 0 2 -2 - 2.500 0.0% 40.0%
39 C. MINARD 6 22 2.086 7.648 -5.562 0 3 -3 - 7.333 0.0% 13.6%

 

  • As a unit, the Oilers had the boots put to them early and often.  Dustin Penner and Robert Nilsson were the only two full-season forwards in the black in DIFF/15, though Sam Gagner was very close.  Ethan Moreau was just blown away in the chances department and was twice as bad as Patrick O'Sullivan in DIFF/15.  Ryan Stone's 27 games were very strong, and it's not as if he was playing the dregs.   It's numbers like DIFF/15 that have people worried that Steve Tambellini let Curtis Glencross Part II get away.
  • Not only did Penner lead the team in DIFF/15, he led the team in TSC with 360, 93 more than second place Sam Gagner.  Penner was the only regular above 5 CF/15; there were eight Oilers that surrendered more than 5 CA/15.
  • Looking at ES +/- is a bit confusing when considered in context with the chances data.  Penner was obviously the best forward on the team once again, but Nilsson is on the right side of the ledger in chances, yet was -14, fourth-worst on the team.  
  • CA/GA shows a bit more of the Nilsson story - he was scored on once every 5.25 chances, the second worst on the team.  Nilsson's even strength save percentage was bad at .894, but not nearly as bad as others on the team, so was it just his "Matador Defense" that was causing the problems?
  • On the flip side, Dustin Penner's conversion rate wasn't anything special, though his personal shooting percentage was above normal.
  • Shawn Horcoff and Patrick O'Sullivan's conversion rates were awful.  They each needed ten scoring chances per goal, far and away the worst on the team.  O'Sullivan shooting half of his career average and a lengthy stint with Jean-Francois Jacques will do that to you.
  • The lowest CA/15 belonged to Zack Stortini at 4.280 (though Ryan Stone was lower in limited minutes) and not only that, Stortini held his opponents to the worst conversion rate -- his opponents needed 10 chances to score on him, almost double that of Jacques and Nilsson.
  • Andrew Cogliano looks pretty good by these numbers, especially considering that he's well clear of both of his most common linemates in CF/15 and CA/15.

Next up - the defensive chances.

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How are you guys tracking scoring chances, in terms of the bare logistics? Just a running tally, or within context such as shift charts?

I’m wondering because it might be interesting to track scoring chances within the context of offensive zone and defensive zone starts. Obviously the waters will become muddled with on-the-fly shift changes, but I think it might be fruitful nonetheless.

One particular example would be Penner. Given his generous offensive zone start ratio, I’d be curious to see his differential scoring chance production between offensive and defensive zones. I think that information would be interesting for any player, actually.

Just a thought.

by Jon Kerber on Aug 10, 2010 7:30 AM MDT reply actions  

Every chance is time-stamped so this is something you could go back and check using the gamesheets at nhl.com and the individual game summaries provided by Dennis, but it would be extremely tedious work. We have an idea of the relationship between Fenwick/Corsi and ZS’s (more OZ starts results in a better Corsi) and between Fenwick/Corsi and SC’s (there’s a positive correlation), so you could math those out to infer how much players are benefiting.

Your example of Penner is confusing. From what I can tell he started 288 shifts in the OZ and 343 shifts in the DZ. It was one of the toughest ratios on the team.

by Scott Reynolds on Aug 10, 2010 2:53 PM MDT up reply actions  

Also, it’s worth noting that of the 9 forwards (who played regularly) above the dubious team average, we see that management has flushed 4 of them. Of the 8 “regulars” below team average, they’ve dismissed 2. Hmm.

by Jon Kerber on Aug 10, 2010 7:32 AM MDT reply actions  

This gives me hope for Cogs. Hopefully with some new linemates he can show he can still play like his rookie season indicated.

by BusDriver on Aug 10, 2010 8:28 AM MDT reply actions  

I’m convinced he’s already a much better player than he was during his rookie season. Many of the underlying numbers (his personal shot rate, his SC%, Corsi% and Shot%) have improved consistently despite playing in more difficult circumstances. Shooting over 18% in his rookie season was “lucky” in that it helped him score some goals, but very, very unlucky in that it’s obscured a lot of the improvement he’s made over the last two seasons.

by Scott Reynolds on Aug 10, 2010 2:56 PM MDT up reply actions  

(Reply fail)

Also, it’s worth noting that of the 9 forwards (who played regularly) above the dubious team average, we see that management has flushed 4 of them. Of the 8 "regulars" below team average, they’ve dismissed 2. Hmm.

??? I count Stone, Nilsson, Comrie and Potulny above the line, and O’Sullivan, Pouliot, Moreau and Pisani below.

Writer for The Copper & Blue and primary shareholder of Zorg Industries

"Never be ashamed of who you are" -- Jean-Baptiste Emanuel Zorg

by Bruce McCurdy on Aug 10, 2010 9:29 AM MDT reply actions  

No denying the hard work of Dennis King here. Tremendous dedication.

The stat generally indicates who played well, from what I observed, though it tends to overrate Robert Nilsson, I’d argue. Gagner, Brule and Cogliano all out-performed him in their two-way play. Is this what you folks observed as well?

And there’s also the Horcoff issue. Was he really that bad or did he just get stuck on the ice too much with crappy even strength players (O’Sullivan, Jacques, Moreau, Pisani)?

The stat is silent on that question, which is why I prefer breaking down each scoring chance to see who is involved in the chance — for and against — and who is not. If you did that, I’m certain that Horcoff would have a much better number (and Nilsson would drop somewhat).

by David Staples @ The Cult of Hockey on Aug 10, 2010 10:37 AM MDT reply actions  

Once you get above 500 minutes of ice time, from what I can tell, you just won’t see a player luck into that many on-ice scoring chances. But a cross-tabulation between players would probably help seeing up to which point a given guy is being driven around by better teammates. The raw data from the Scoring Chances script output allows that, but I’ll cut the guy some slack, it’s summer time after all.

by Olivier on Aug 10, 2010 12:07 PM MDT up reply actions  

I don’t think anyone is saying that you should only use this one statistic to evaluate the players David. There obviously needs to be some context added to help in the interpretation (and Derek does some of that after presenting the data), but breaking down every single chance would just take a lot of time. I’m sure you’d learn an awful lot doing so, but there are also other ways to add context that would lead to some similar conclusions, at least as it pertains to Horcoff (SC’s with and without Jacques and/or Moreau, his ZS ratio, his QC numbers)

As for Nilsson, I thought that we was okay defensively. I certainly liked him better positionally than Brule. It’s hard to compare him to the other two guys because they mostly played center and Nilsson mostly played wing.

by Scott Reynolds on Aug 10, 2010 3:06 PM MDT up reply actions  

Also, since the influential Desjardins has adopted the XX/60 as the standard for expressing these stats, why not express them in that manner?

by David Staples @ The Cult of Hockey on Aug 10, 2010 10:40 AM MDT reply actions  

From the article above:

Desjardins tends to use rates / 60 when displaying any stat over minutes played, but I’ve decided to display scoring chances in chances / 15 minutes of on ice even strength time because I feel it allows the reader to see what a player would average per game if given first line even strength minutes.

Editor of The Copper & Blue, and leader of The Cult Of Hartikainen.

by Derek Zona on Aug 10, 2010 10:56 AM MDT up reply actions  

Here is another Stat (%Con/Diff or percent of chances converted differential)
  1. Player %Con/Diff
    32 R. STONE 1.2%
    27 D. PENNER 2.0%
    83 A. HEMSKY 5.9%
    12 R. NILSSON -7.7%
    57 C. MCDONALD 33%
    89 S. GAGNER -1.2%
    91 M. COMRIE -6.5%
    16 R. POTULNY -7.1%
    67 G. BRULE 0.2%
    13 A. COGLIANO 2.5%
    00 FORWARD AVG -1.3%
    46 Z. STORTINI 9.1%
    19 P. O’SULLIVAN -8.8%
    10 S. HORCOFF -4.6%
    22 J. JACQUES -10.4%
    78 M. POULIOT -13.029%
    42 R. O’MARRA -27.3%
    33 S. MACINTYRE N/A
    18 E. MOREAU -2.758%
    34 F. PISANI -3.5%
    85 L. REDDOX 3.6%
    28 R. JONES N/A
    36 C. LINGLET -40%
    39 C. MINARD -13.6%

 Could this be used to help judge out scoring?

one of the founders and most prolific writers of Bringing Back the Glory

by B.C.B. on Aug 10, 2010 11:21 AM MDT reply actions  

That depends if it’s repeatable or not. My initial intuition is that there’s likely too much noise (in terms of seperating personal effects on this from linemates, as well as puck luck and bad goaltending) to tease out much here. Like PDO, a large deviation away from average strikes me as more likely to indicate luck than skill.

by MattM on Aug 10, 2010 11:31 AM MDT up reply actions  

Well course, it depends on if it is repeatable (but all stats are dependent on that or they would not be of use). This is a one year set of data so this will take multiple years of an ongoing project to tell, but I think it an interesting one. I see no reason why ‘luck’ would have more influence on %Con/Diff then any other stat category in the post.

one of the founders and most prolific writers of Bringing Back the Glory

by B.C.B. on Aug 10, 2010 12:07 PM MDT reply actions  

m certainly not dogmatic on the subject. In fact, if the %Con/Diff displays significant repeatability I would think that would be an excellent and interesting result. I notice my earlier post seems more dismissive than I intended. Apologies. I certainly think it’s an interesting thing to look at, I’m just suggesting which way I think it will go when someone more industrious than me does the math. My thought process here is basically by analogy to the PDO numbers and Corsi.

When you look at Desjardin’s shooting percentage stuff, it generally suggests that most players who demonstrate an ability to control their shooting percentage do so by getting higher quality shots, rather than by being better shooters. That aspect seems to me to be handled by the SC for, rather than the conversion rate. Defensive conversion seems even more likely to not be within a player’s control to me, simply because I’d think that opponent conversion rate is primarily a result of goaltending, with the defensive ability of the players on the ice primarily impacting whether or not a scoring chance occurs. By analogy to Vic’s results indicating that there is very little room for defensive player skill in ONSV%, I suspect there is very little room for player skill in opponent SC conversion.

When Vic, Desjardins, et al looked at percentages vs. shot rates, they found that most of the player skill was in the rates. I think as we drill farther down in encapsulating shot quality in the rate numbers, we also move more and more player skill into those numbers and leave less in the percentages. It’s completely possible that I’ve misunderstood something in these earlier articles, or that my analogy logic here is flawed. This is just a starting hypothesis and I’d love to see a more rigorous exploration of the idea.

by MattM on Aug 10, 2010 2:31 PM MDT up reply actions  

Bruce:

I’m having difficulty replying as well.

Anyway, that’s what happens when I attempt to count before having my coffee.

by Jon Kerber on Aug 10, 2010 12:49 PM MDT reply actions  

You guys made me tabulate the numbers for the habs. Turns out none of the regulars are over 50%. Gionta (308/-312) and Cammalleri (311/-315) almost make it, and Gomez, Plekanec, AKostitsyn, Moore and Metropolit are hovering around 48%.

Jeebus. Between the flames, the Avalanche and Minny, is it me or did we all scored chances on teams laying turds at ES?

Well, I guess Slava Duris got something with the leafs.

by Olivier on Aug 10, 2010 2:30 PM MDT reply actions  

Please tell me you’re posting one of your patented chart. :)

by MathMan on Aug 10, 2010 3:36 PM MDT up reply actions  

Excel be willing, the big charts are up tonight.

by Olivier on Aug 10, 2010 5:51 PM MDT up reply actions  

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