Announcement

Collapse
No announcement yet.

Trying to rank defensemen

Collapse
X
 
  • Time
  • Show
Clear All
new posts

  • Trying to rank defensemen

    OK so after Josh and I had a disagreement on ranking some of the top defensemen in the league, I decided to try to find some reliable stats to objectively evaluate and rank defensemen. I've already talked about the Vollman numbers, and I've talked ad nauseum about the value I assign to TOI. And then obviously there's points. But not much beyond that readily available to the public.

    So I came up with a few stats of my own.

    RelPPGF/60 – This stat measures how many more or less goals a team scores on the powerplay when a given player is on the ice, per 60 minutes of powerplay time. I actually set it only for 5-4 PP, to keep things consistent. When inventing a new stat (I’m certain I’m not the first person to invent it, but I haven’t seen it in common use, and it wasn’t a stat that some site had ready-made, I had to put together some filters and such to get to it), you always want to check and make sure it passes the common sense, and indeed, the top guys (minimum 50 PP mins) are basically the guys you’d expect to help a powerplay – Draisaitl, Marchand, Point, McDavid, Pastrnak are the top five. As a funny aside, I remember one article on advanced stats years ago talked about the “Pavel Datsyuk test”, as in if Pavel Datsyuk doesn’t rank well in it then you know it’s not a good stat.

    The first surprise comes with Alex Chiasson at number ten, but this can largely be explained by him mostly playing with McDavid and Draisaitl on the PP; clearly McDavid and Draisaitl themselves are so high because the rest of the powerplay without them is utter garbage. So yeah, it is partly team dependent in a variety of ways, but overall I’m pretty happy with this stat. On the other end of the spectrum, there are some surprises. Common sense test is satisfied to see guys like Lars Eller, Sven Andrighetto, Mikael Backlund and Dmitry Orlov in the bottom ten. But there were also some surprises in Charlie McAvoy, Kevin Shattenkirk and Tyler Johnson.

    RelSHGA/60 – Same idea as above. This stat measures how many more or less goals a team give up on the penalty kill when a given player is on the ice, per 60 minutes of PK time. Specific to 4-5 PK. This one is a little fuzzier on the common sense test. Penalty killing is a very specific skill, that we don’t really have any mainstream stats for besides plain SHTOI, and as much as I glorify TOI, of course coaches can get it wrong sometimes, and interestingly, the teams who got this wrong and kept playing guys who struggle in this stat, were almost universally non-playoff teams. I would like to think that this could become the first mainstream stat for evaluating individual performance on the penalty kill.

    First looking at some of the worst ranked players (min 50 mins SH): Brian Gibbon ranked the worst; a career AHLer got stuck killing penalties on an awful team because most of the forwards are under 23. Darren Helm and Trocheck ranked 2nd and 9th worst. Maybe the coaches can be excused somewhat here because both guys are there for faceoff abilities and maybe to try to back off opponents with their speed or skill. Kesler ranked 3rd worst, he is there for faceoffs but is old and broken and the coach refused to make a change. As for the top players in this stat, Charlie McAvoy redeems himself for his powerplay woes, ranking 1st in the league here. Next we have Ryan Johansen, Erik Cernak, Leo Komarov, Brandon Sutter, Valteri Filppula and Evander Kane. Again, penalty killing is a very specific skill, and until now we haven’t really had any stats to assess individual’s PK performance, so it is hard to know what to expect, but that all sounds reasonable to me.

    Note that this stat is goals against, so a more negative number is better, meaning the player allowed less goals against compared to team average.

    RelGF% - This stat measures what percent more or less of the goals a team scores at 5 on 5 when a given player is on the ice. So basically it is adjusted +/-. If a team, on average, scores 48% of the goals at even strength (and their opponents score 52%) and when a given player is on the ice, the team scores 50% of the goals, then that player is +2%. While this is a hell of a lot more useful than +/-, it still isn’t the greatest. Corsi is much more valuable, as luck plays more of a role in being on the ice for a goal scored for or against, as well as the quality of teammates and opponents; whereas an individual player can have more of an effect on driving possession.

    How does RelGF% do on the common sense test? Radulov ranks 1st, Tyler Seguin 4th, and Jamie Benn 14th in the league. When you have such a top heavy team that relies so much on one elite line, and the rest of the team struggled through injuries and lack of depth, that top line is going to have to come through, and I think the fact that this team managed to make the playoffs is evidence enough that they did indeed come through. Also Teravainen and Aho are 5th and 12th – again, a hard-working, well-structured team that relies heavily on a couple of high-end skilled players. Demers and Copp ranked 2nd and 3rd, and I’m not entirely sure what to make of that. Call them underrated? Again, this is my least favorite of these stats I’m considering, but I think it does have some value. Sidney Crosby ranks 7th, so that’s always a good sign.

    Then if we look at the bottom ranking players (min 500 mins), everything looks in order. Dubinsky and Riley Nash rank 1st and 4th worst. The other side of the spectrum from Dallas - when you have such a stacked team as Columbus, and you have a couple players having some struggles, of course they’re going to rank poorly here, and Torts rightly played them on the 4th line, 12 and 10 mins a game. Chandler Stephenson ranked 2nd worst, again a mediocre player on a top team. Jack Johnson ranked 11th worst, and any stat that makes Jack Johnson look bad gets bonus points in my book.

    OK, now using these stats to try to rate defensemen:

    1. Mark Giordano – 74 points in 78 games = .95 p/g… 3:06 SHTOI, 3:08 PPTOI, 24:47 TOI… 9.16% RelGF%, 5.2 RelPPGF/60, -1.04 RelSHGA/60
    2. Kris Letang – 56 points in 65 games = .86 p/g… 2:35 SHTOI, 3:06 PPTOI, 25:20 TOI… 11.48% RelGF%, 0.49 RelPPGF/60, 0.14 RelSHGA/60
    3. Brent Burns – 83 points in 82 games = 1.01 p/g… 1:31 SHTOI, 3:41 PPTOI, 25:15 TOI … 3.88% RelGF%, -1.12 RelPPGF/60, 1.88 RelSHGA/60
    4. John Carlson – 70 points in 80 games = .88 p/g… 2:35 SHTOI, 4:05 PPTOI, 25:04 TOI … 7.76% RelGF%, 5.84 RelPPGF/60, -1.41 RelSHGA/60
    5. Morgan Rielly – 72 points in 82 games = .88 p/g…1:05 SHTOI, 2:36 PPTOI, 23:07 TOI… 8.09% RelGF%, 3.18 RelPPGF/60, -3.27 RelSHGA/60

    I'm pretty comfortable with that top five, but from there it gets trickier. Guys like Yandle, Chabot, Klingberg have outstanding offensive numbers, but don't kill penalties and/or struggle in some other area. Spurgeon, Pietrangelo, Ekholm have some other really good numbers, but not as much offensive output. Byfuglien, Weber and Edler have outstanding numbers all around and should be top ten if not for injuries.

    Beyond that, I marked down a bunch of players for my made-up stats - some noteable defensemen:

    Alex Pietrangelo – -.04% RelGF%, 1.12 RelPPGF/60, 3.48 RelSHGA/60
    Drew Doughty – -6.22% RelGF%, 2.37 RelPPGF/60, 3.97 RelSHGA/60
    Ryan Suter – 4.00% RelGF%, -1.68 RelPPGF/60, 3.82 RelSHGA/60
    Erik Karlsson – 4.13% RelGF%, -0.02 RelPPGF/60, 1.53 RelSHGA/60
    Jeff Petry – -6.71% RelGF%, -0.25 RelPPGF/60, 0.21 RelSHGA/60
    Jake Muzzin – 14.86% RelGF%, -1.37 RelPPGF/60, -3.16 RelSHGA/60
    Ryan McDonagh – 5.18% RelGF%, -2.02 RelPPGF/60, -1.60 RelSHGA/60
    Duncan Keith – 11.01% RelGF%, -4.15 RelPPGF/60, 1.03 RelSHGA/60
    Roman Josi – -2.37% RelGF%, -1.83 RelPPGF/60, -0.41 RelSHGA/60
    Victor Hedman – 0.36% RelGF%, 3.65 RelPPGF/60, 0.9 RelSHGA/60
    Mattias Ekholm – 5.39% RelGF%, 0.30 RelPPGF/60, 0.09 RelSHGA/60
    Matt Dumba – -4.63% RelGF%, 3.04 RelPPGF/60, 3.87 RelSHGA/60
    Oliver Ekman-Larsson – -2.74% RelGF%, -1.03 RelPPGF/60, 1.72 RelSHGA/60
    Cody Ceci – -2.44% RelGF%, 0.88 RelSHGA/60
    Nate Schmidt – 1.28% RelGF%, 1.57 RelPPGF/60, -1.17 RelSHGA/60
    PK Subban – -7.57% RelGF%, 2.57 RelPPGF/60, 2.42 RelPKGA/60
    Erik Johnson – -7.50% RelGF%, -2.38 RelSHGA/60
    Oscar Klefbom – -9.03% RelGF%, 1.18 RelPPGF/60, 0.85 RelSHGA/60
    Ryan Ellis – 0.44% RelGF%, 0.17 RelPPGF/60, -0.75 RelSHGA/60
    TJ Brodie – 4.13% RelGF%, -3.17 RelPPGF/60, 2.2 RelSHGA/60
    John Klingberg – 8.93% RelGF%, 1.91 RelPPGF/60
    Keith Yandle – 3.24% RelGF%, 1.02 RelPPGF/60, -1.95 RelSHGA/60
    Tyson Barrie – 4.73% RelGF%, 1.54 RelPPGF/60, -6.51 RelSHGA/60
    Ryan McDonagh – 5.18% RelGF%, -2.02 RelPPGF/60, -1.60 RelSHGA/60
    Jared Spurgeon – 6.41% RelGF%, 1.28 RelPPGF/60, 2.31 RelSHGA/60
    Cam Fowler – 2.92% RelGF%, 2.99 RelPPGF/60, -2.62 RelSHGA/60
    Justin Faulk – 5.77% RelGF%, 2.95 RelPPGF/60, -1.10 RelSHGA/60
    Shea Weber – 2.64% RelGF%, 2.59 RelPPGF/60, -1.87 RelSHGA/60
    Tory Krug – 7.01% RelGF%, 2.19 RelPPGF/60
    Jake Gardiner – 6.96% RelGF%, -3.55 RelPPGF/60
    Colton Parayko – 6.94% RelGF%, -0.35 RelPPGF/60, -4.30 RelSHGA/60
    Alex Edler – -0.61% RelGF%, 3.7 RelPPGF/60, -0.20 RelSHGA/60
    Dustin Byfuglien – 6.93% RelGF%, 3.39 RelPPGF/60, -1.68 RelSHGA/60
    Erik Gustafsson – 4.01% RelGF%, 2.86 RelPPGF/60
    Nick Leddy – -6.72% RelGF%, 1.46 RelPPGF/60
    Marc-Edouard Vlasic – -8.22% RelGF%, -0.38 RelPPGF/60, 2.08 RelSHGA/60

    And some under-25 defensemen:

    Thomas Chabot – 10.52% RelGF%, -1.28 RelPPGF/60, -2.33 RelSHGA/60
    Esa Lindell – -0.10% RelGF%, -1.37 RelPPGF/60, 1.68 RelSHGA/60
    Hampus Lindholm – 5.80% RelGF%, -1.37 RelPPGF/60, 1.70 RelSHGA/60
    Seth Jones – -6.10 RelGF%, -2.13 RelPPGF/60, 1.9 RelSHGA/60
    Jacob Trouba – -1.03% RelGF%, -0.23 RelPPGF/60, -0.58 RelSHGA/60
    Brandon Montour – 8.29% RelGF%, -5.16 RelPPGF/60, -1.35 RelSHGA/60
    Miro Heiskanen – -1.74% RelGF%, -2.21 RelPPGF/60, -1.80 RelSHGA/60
    Charlie McAvoy – -2.11% RelGF%, -7.99 RelPPGF/60, -7.22 RelSHGA/60
    Rasmus Ristolainen – -10.22% RelGF%, 1.51 RelPPGF/60, 1.06 RelSHGA/60
    Brett Pesce – 10.06% RelGF%, -2.14 RelSHGA/60
    Brandon Carlo – 5.86% RelGF%, 2.12 RelSHGA/60
    Neal Pionk – -6.63% RelGF% 4.73 RelPPGF/60, 2.6 RelSHGA/60
    Jaccob Slavin – -5.86% RelGF%, -1.52 RelPPGF/60, -0.58 RelSHGA/60
    Shayne Gostisbehere – -5.37% RelGF%, 1.12 RelPPGF/60
    Zach Werenski – -5.67% RelGF%, 1.28 RelPPGF/60, 3.4 RelSHGA/60
    Jakob Chychrun – -1.52% RelGF%, 4.00 RelPPGF/60
    Brady Skjei – 5.87% RelGF%, -2.41 RelSHGA/60
    Dougie Hamilton – 0.36% RelGF%, -1.86 RelPPGF/60
    Damon Severson – -0.36% RelGF%, -1.1 RelPPGF/60, 1.99 RelSHGA/60
    Mikhail Sergachev – -0.07% RelGF%, -6.0 RelPPGF/60
    Ivan Provorov – -2.07% RelGF%, -3.36 RelPPGF/60, -0.33 RelSHGA/60
    Aaron Ekblad – 5.38% RelGF%, -2.72 RelPPGF/60, 0.82 RelSHGA/60
    Ryan Pulock – 6.43% RelGF%, -2.94 RelPPGF/60, 0.9 RelSHGA/60
    Darnell Nurse – 2.17% RelGF%, 1.87 RelPPGF/60, -0.20 RelSHGA/60
    Josh Morrissey – 2.64% RelGF%, -1.37 RelPPGF/60, 2.18 RelSHGA/60
    Rasmus Dahlin – 7.58% RelGF%, 0.43 RelPPGF/60
    Travis Sanheim – 5.66% RelGF%, -2.46 RelPPGF/60
    Shea Theodore – -6.02% RelGF%, -0.41 RelPPGF/60
    Samuel Girard – 7.12% RelGF%, -0.88 RelPPGF/60
    Vince Dunn – 7.05% RelGF%, -0.63 RelPPGF/60
    Anthony DeAngelo – 3.24% RelGF%, -0.20 RelPPGF/60
    Mike Matheson – -5.23% RelGF%, 1.87 RelPPGF/60, 2.39 RelSHGA/60
    Noah Hanifin – -4.53% RelGF%, -4.01 RelPPGF/60, 0.49 RelSHGA/60
    Last edited by matchesmalone; 06-20-2019, 08:42 AM.

  • #2
    Very interesting stuff. I like your three measures. So how to aggregate them? Maybe it isn’t possible, so instead the three values need to be observed in tandem. I’m curious to see whether or not it settles our disagreement.

    To be fair, I didn’t argue that Jones was anything short of stellar. I think he can easily be top-ten next season. But this past season, I had these defensemen ranked ahead of him:

    Barrie
    Burns
    Carlson
    Chabot
    Doughty
    Giordano
    Gustafsson
    Hamilton
    Hedman
    Josi
    Letang
    Petry
    Rielly
    Ristolainen
    Trouba
    Yandle

    Comment


    • #3
      Yeah these new metrics do Jones no favors. I'd probably hold back on calling him top 15 in the league at this point, but I'd still have him ahead of Ristolainen, Hamilton, Gustafsson, Doughty, Petry for sure. Not so sure about Trouba, Josi and Hedman.

      And I'd agree on having Barrie, Burns, Yandle, Rielly, Letang, Giordano, Chabot, Carlson in the top 10-15. But then ahead of Jones and the rest of your list, I would instead have Pietrangelo, Ekholm, Klingberg, Edler, Byfuglien, Weber, Spurgeon.

      The major thing that stands out for me looking over these new metrics, is how drastically they justify veterans over the U25s. The great majority of player on the U25 list have negative RelPPGF/60, and positive RelSHGA/60, while most of the top veterans are in the green for at least one if not both.

      ​​​​​​​A lot of interesting things to note, but one that stood out to me is in Nashville it looks like Ellis and Ekholm have developed into at least as good, if not better defensemen than Subban and Josi. Of course Josi and Subban are still scoring more, but they're also seeing more powerplay time. Will be interesting to see if Nashville trades Subban this summer, and what Ellis and Ekholm can do next year. How does that team keep doing it? Weber, Suter, Jones...

      Another general thing standing out is how many good defensemen are actually negative influences on the powerplay. I've thought of two possible explanations for this. One is that perhaps teams score more on the PP with more forwards on the ice. Most of the true elite defensemen are positive influences to their powerplays, so likely those are the guys who are usually the one forward out, but on the occasions where the coach uses two defensemen on the powerplay, it will be safer but less effective, and so that second defenseman brings down the average? The other possible explanation is that some of the defensemen are facing tougher quality of competition against teams' top PK units, and so compared to their team's other PP unit their numbers suffer. I'm currently trying to figure out a good way to account for quality of competition on special teams, but it is not easy.

      Just for fun, I threw together a top 10 and bottom 5 for each category, just amongst the defensemen I have listed in the original post. Like you alluded to, right now it is just a mass of numbers, so I want to try to sort it and get as much out of it as I can. Perhaps down the road I'll try to aggregate everything into some kind of defenseman-rating, but the first step to that will be to try and solve the special teams QoC problem.

      Top 10 RelGF% (vets)
      - Jake Muzzin: 14.86%
      - Kris Letang: 11.48%
      - Duncan Keith: 11.01%
      - Mark Giordano: 9.16%
      - John Klingberg: 8.93%
      - Brandon Montour: 8.29%
      - Morgan Rielly: 8.09%
      - John Carlson: 7.76%
      - Torey Krug: 7.01%
      - Jake Gardiner: 6.96%
      - Colton Parayko: 6.94%

      Top 5 RelGF% (U25)
      - Thomas Chabot: 10.52%
      - Brett Pesce: 10.06% (25 this November)
      - Rasmus Dahlin: 7.58%
      - Samuel Girard: 7.12%
      - Vince Dunn: 7.05%

      Bottom 10 RelGF% (all ages)
      - Rasmus Ristolainen: -10.22%
      - Oscar Klefbom: -9.03%
      - ME Vlasic: -8.22%
      - PK Subban: -7.57%
      - Erik Johnson: -7.50%
      - Nick Leddy: -6.72%
      - Jeff Petry: -6.71%
      - Neal Pionk: -6.63%
      - Drew Doughty: -6.22%
      - Seth Jones: -6.10%
      _____________________________________

      Top 10 RelPPGF/60 (vets)
      - John Carlson: +5.84
      - Mark Giordano: +5.20
      - Alex Edler: +3.70
      - Victor Hedman: +3.65
      - Dustin Byfuglien: +3.39
      - Morgan Rielly: +3.18
      - Matt Dumba: +3.04
      - Cam Fowler: +2.99
      - Justin Faulk: +2.95
      - Erik Gustafsson: +2.86

      Top 5 RelPPGF/60 (U25)
      - Neal Pionk: +4.73
      - Jakob Chychrun: +4.00
      - Darnell Nurse: +1.87
      - Rasmus Ristolainen: +1.51 (25 this October)
      - Zach Werenski: +1.28

      Bottom 5 RelPPGF/60 (all)
      - Charlie McAvoy: -7.99
      - Mikhail Sergachev: -6.00
      - Brandon Montour: -5.16
      - Duncan Keith: -4.15
      - Noah Hanifin: -4.01
      _____________________________________

      Top 5 RelSHGA/60 (vets) -
      - Colton Parayko: -4.30
      - Morgan Rielly: -3.27
      - Jake Muzzin: -3.16
      - Cam Fowler: -2.62
      - Brady Skjei: -2.41
      - Brent Burns: -1.88
      - Shea Weber: -1.87
      - Dustin Byfuglien -1.68
      - Ryan McDonagh: -1.60

      Top 5 RelSHGA/60 (U25)
      - Charlie McAvoy: -7.22
      - Brett Pesce: -2.14
      - Miro Heiskanen: -1.80
      - Ivan Provorov: -0.33
      - Darnell Nurse: -0.20

      Bottom 5 RelSHGA/60 (all)
      - Drew Doughty: +3.97
      - Ryan Suter: +3.82
      - Alex Pietrangelo: +3.48
      - Zach Werenski: +3.4
      - Neal Pionk: +2.6

      Interestingly, but unsurprisingly, most of the top statistical penalty killers are not these top defensemen, but relatively no-name stay-at-home defenders. The top of the powerplay list, conversely, is dominated by the big names. The living anomaly Charlie McAvoy notwithstanding, one thing that stands out, and aligns with common sense, is that veterans seem to be generally much better penalty killers than young defensemen. I noticed a few players like Chabot and Barrie, who had very strong PK numbers, but played under the 50 min limit.

      And finally, the players who rank well in all three stats: Mark Giordano, John Carlson, Morgan Rielly, Dustin Byfuglien, Shea Weber, Nate Schmidt, Cam Fowler, Justin Faulk, Darnell Nurse.
      Last edited by matchesmalone; 06-21-2019, 04:07 AM.

      Comment


      • #4
        Originally posted by matchesmalone
        I started to realize/remember how flawed GA/TA are, which threw a wrench in my argument, because they make guys like Yandle (110-27) and Petry (129-39) look really bad. These are guys who in my opinion are not nearly as good as their offensive numbers suggest. The Vollman numbers do indeed do some work to discredit them, but I realized that I need more numbers. But of course, while I want to be right, I'm more interested in getting to some kind of truth. If there are numbers out there to convince me Yandle is an elite defenseman, I want to find them.
        And I'm convinced.

        Comment


        • #5
          Hoping I have some time tomorrow, I'm planning to look at how Sens players rank in these stats, and they to work on the QOC problem. I've been thinking about it, and I'm sure I could find a site that you can take QOC, abs filter it for special teams situation. But QOC is just the corsi of the player's competition, which is relatively useless in this context. Special teams are such a specific skill - if we take a powerplay specialist, I don't want to know how good of players in general are the penalty killers he plays against, I want to know how good of penalty killers they are...

          I don't suppose there is a script/generator (I dunno the right word) where you can punch in the the stat you want to measure the competition of a player for and it figures it out. Does that even make sense? It sounds like I'm wishing for a miracle, but I mean it is 2019, there are automatic carwashes and self-tying shoes.

          Comment


          • #6
            What other stats might be useful for assessing PP and PK ability? I'm thinking mainly for defenseman right now but either way.

            For PP, relative corsi for doesn't make too much sense because there's a lot more holding the puck and passing it around, while shooting can mean loss of possession and zone. At even strength, zone possession can be valuable whether or not you're creating chances, but not as much so on the PP.A

            High danger scoring chances gets a little weird, I'm assuming due to the small sample sizes.

            Regular scoring chances - RelSCF/60 seem fairly useful, but I dunno how much they're adding that goals don't already tell you about.

            I'm kinda thinking on-ice shooting% could be pretty useful. At even strength I don't put much stock into it for defensemen (although I take it seriously for forwards), but on the powerplay, whether it is forwards or defensemen, it says something about the quality of chances the unit is creating. Particularly when you want to be creating chances on less shots because, again, on the PP shots can often mean loss of possession and zone.

            Comment


            • #7
              Originally posted by matchesmalone
              Hoping I have some time tomorrow, I'm planning to look at how Sens players rank in these stats, and they to work on the QOC problem. I've been thinking about it, and I'm sure I could find a site that you can take QOC, abs filter it for special teams situation. But QOC is just the corsi of the player's competition, which is relatively useless in this context. Special teams are such a specific skill - if we take a powerplay specialist, I don't want to know how good of players in general are the penalty killers he plays against, I want to know how good of penalty killers they are...

              I don't suppose there is a script/generator (I dunno the right word) where you can punch in the the stat you want to measure the competition of a player for and it figures it out. Does that even make sense? It sounds like I'm wishing for a miracle, but I mean it is 2019, there are automatic carwashes and self-tying shoes.
              When I use this site: http://corsica.hockey/skater-stats/ and check Bergeron's CF%QOC, it's 47.91 at even-strength, but 13.86 when he's on the powerplay. Wouldn't that imply that they're calculating his opponents' CF% while they're PKing against Bergeron, and not that teams are putting out their weaker players against him?

              Then you could just set a TOI limit and look at average CF% while on the PK, set a base, and use it to determine how good of penalty killers the top powerplay specialists are facing. If that is indeed your goal..

              Comment


              • #8
                Originally posted by Josh

                When I use this site: http://corsica.hockey/skater-stats/ and check Bergeron's CF%QOC, it's 47.91 at even-strength, but 13.86 when he's on the powerplay. Wouldn't that imply that they're calculating his opponents' CF% while they're PKing against Bergeron, and not that teams are putting out their weaker players against him?

                Then you could just set a TOI limit and look at average CF% while on the PK, set a base, and use it to determine how good of penalty killers the top powerplay specialists are facing. If that is indeed your goal..
                By Jove! I think you might be right.

                Haha imagine if that actually was the ES CF% though, 13%.

                Opponent's assistant coach: "alright coach, they're coming with Bergeron, Marchand, Pastrnak for the powerplay, one of the most lethal combinations in the game today. What's our move?"
                coach: "give me Larry, Curly, Moe... and Mr. Bean"

                Comment


                • #9
                  Originally posted by matchesmalone

                  By Jove! I think you might be right.

                  Haha imagine if that actually was the ES CF% though, 13%.

                  Opponent's assistant coach: "alright coach, they're coming with Bergeron, Marchand, Pastrnak for the powerplay, one of the most lethal combinations in the game today. What's our move?"
                  coach: "give me Larry, Curly, Moe... and Mr. Bean"
                  Might be close to what Ottawa ices against them..

                  Comment


                  • #10
                    Hahaha harsh. I actually think based on the forward core of Tierney, Pageau, Anisimov, Brown, this could be a middle tier penalty kill. But based on defense and goaltending it could be close to last place. Overall, depending on coaching, I'm expecting we'll be closer to 25 than 31.

                    The powerplay will be a lot worse than last year though, sans Duchene, Stone and Boucher. Hopefully better than 25th, but I'm not confident. Kids like Drake, Balcers and Veronneau would have to drastically overperform.

                    Comment


                    • #11
                      I started looking at the special teams QOC on corsica, using both corsi and TOI%. I found the results pretty similar with either. The strange thing about CF%QOC is how small the variance is. Among all players in the league with 50+ minutes SH 4on5, the range is from 84.15 to 86.07. Maybe I'm just tired, but I can't make any good sense of that fact. Doesn't seem like a serious problem though, just a bit odd.

                      It does seem to be passing the common sense test in the little bit I've looked at it. I recall being startled at first by Charlie McAvoy ranking first in the league in RelSHGA/60, but now my suspicion is confirmed - McAvoy ranks third in the league in easiest CF%QOC at 84.25. Chara, still playing over 3:00 a game shorthanded, takes the brunt of opponents' firepower, and McAvoy comes out for the leftovers.

                      I was also looking into RelSHSCA/60 and RelSHHDCA/60 (SH scoring chances and high-danger chances against) earlier and found that, while Pageau ranks well in preventing goals against while shorthanded, he is on the ice for more scoring chances and high-danger scoring chances against while shorthanded than just about anyone on the Sens. Based on my own opinion, and broadly supported by the other stats I rely on, Pageau is clearly the best penalty killing forward on the Sens. So why is he on the ice for so many powerplay chances against? Because he faced the second most difficult (first among forwards) competition while shorthanded on the team, of course, at 85.77.
                      Last edited by matchesmalone; 09-02-2019, 12:51 PM.

                      Comment


                      • #12
                        Ok yeah I've decided using CF% for QOC doesn't make much sense. Even CF/60 would be better then CF%. A player with a low CF% on the powerplay kinda just means they give up shorthanded chances. Doesn't really say much about how good they are on the powerplay. As I said elsewhere, corsi doesn't tell you much on special teams. Would be best if they had QOC based on scoring chances for or something like that.

                        At least corsica has TOI%QOC. Still not ideal but I'm finding it exponentially more useful than CF%QOC. Was looking at the top and bottom players in CF%QOC and there is absolutely no rhyme or reason to any of it. TOI%QOC looks so much better to common sense.

                        First little test I'm gonna run is to look at the bottom five guys on my list for RelPPGF/60 and see if we can excuse them to some extent. The range for TOI%QOC for players with 50+ PP mins is 33.35 to 41.67.

                        McAvoy - 35.41 (340th of 360)
                        Sergachev - 38.89 (175th)
                        Montour - 38.09 (223rd)
                        Keith - 36.49 (313th)
                        Hanifin - 36.25 (328th)

                        Hmmmm.

                        Since I have it right here, might as well also look at TOI%QOT. Range is 28.74 to 78.16. It actually makes perfect sense that the range is so much wider in QOT vs QOC. Because quality of teammates is consistently determined by a single coach - the top four guys in QOT are all Capitals, because they always all play together - whereas QOC is determined partly by 30 other coaches, so it is going to be a lot more random.

                        Actually I just figured out why the variance in SHCF%QOC was so tiny. Because that is just the average range for that stat for everyone, and it's not something the players have any real control over so any variance is based mostly on random chance. Anyway,

                        McAvoy - 41.35 (266th)
                        Sergachev - 40.92 (272nd)
                        Montour - 41.95 (255th)
                        Keith - 41.73 (259th)
                        Hanifin - 31.54 (347th)

                        Ok, so there you have it. These guys just aren't great on the powerplay at this stage in their careers. I'm sure Keith used to be, and Sergachev and McAvoy will be. They're all on secondary units with mediocre linemates, but also up against secondary penalty killers.

                        Since RelPPGF/60 is relative to the rest of the team, we also have to take into account the teammates they're measuring up against. When you have Tampa's fantastic four (Hedman, Stamkos, Kucherov, Point plus Miller/Killorn) annihilating opponents, Boston's "perfection line" plus Krug and DeBrusk, and Chicago's top unit of Kane, Toews, DeBrincat, Strome and Gustavsson all playing a ton of minutes and driving up the team average... then yeah when Keith, Sergachev and McAvoy come out leading the second units, they're going to suffer by comparison.
                        Last edited by matchesmalone; 09-03-2019, 04:04 PM.

                        Comment


                        • #13
                          I'm realizing now that the biggest difference between the most positive and most negative RelPPGF/60 defensemen is running the point on the first or second unit of a really good powerplay. The guys with really good numbers run a really good powerplay unit, and the guys with really bad numbers run the second unit opposite a really good unit.

                          On the other hand, looking as Jones and Werenski, neither has very extreme numbers either way. When the powerplay is that bad, neither unit is so much better than the other. And in fact I actually remember Torts talking about trying to balance out the units because you need two strong powerplay in today's NHL

                          I dunno, I am certain there is serious value to be found in these stats. It is just a matter of figuring our how to get the most out of them.

                          Comment

                          Working...
                          X
                          😀
                          🥰
                          🤢
                          😎
                          😡
                          👍
                          👎