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Photo Credit: Jeff Vinnick / Getty Images

Travis Green’s Defence of Michael Del Zotto is Littered With Flawed and Troublesome Numbers

It’s been a trying season for Canucks defenceman Michael Del Zotto. The off-season free agent signing has been relied upon heavily by rookie head coach Travis Green, and the numbers haven’t been particularly flattering.

Although, I guess that depends on who you ask.

If you ask me (or, likely, many of my peers, be it here or elsewhere), you’ll hear a tale of a defencemen that gets buried in shots, scoring chances, and of course goals. One that appears to be ill suited to playing heavy minutes against top opponents, and yet has to do it anyway, with disastrous results.

Del Zotto’s 44.4% Corsi-for percentage is better only than Gudbranson’s 43.7%. He also has the second worst Fenwick-for percentage, shots-for percentage, goals-for percentage, and fourth worst expected goals-for percentage.

Player GP TOI CF% FF% SF% GF% xGF%
ERIK.GUDBRANSON 31 470.8 43.7 43.0 41.8 43.2 43.3
MICHAEL.DEL ZOTTO 48 803.6 44.4 44.5 44.7 39.0 45.5
ALEX.EDLER 37 628.0 46.4 47.2 48.5 41.6 43.9
BEN.HUTTON 43 680.0 47.6 46.4 47.3 47.6 46.0
CHRIS.TANEV 32 500.6 48.2 47.3 48.2 53.7 47.7
DERRICK.POULIOT 40 621.8 48.2 49.5 48.8 37.9 48.9
ALEX.BIEGA 24 338.2 48.7 49.2 51.2 47.1 51.6
TROY.STECHER 35 546.5 49.2 48.1 47.9 40.5 44.4

Most of this is driven by how much he allows. Among Canucks defencmen, Del Zotto has the worst rates of Corsi, Fenwick, shots, and goals against. All of this is to say that the numbers are pretty bad.

If you ask Travis Green, however, he can give you a list of metrics that purportedly support Del Zotto and the contributions he has made to the team. Let’s just say that they aren’t exactly the type of numbers you’d find us at Canucks Army using to support players (and there’s a reason for that, which I’ll get to).

A lot of people base numbers on plus-minus. He’s got some points for us, he’s got 14 points. I know he’s minus-19. There was a stretch of games where he probably had four or five pucks that went off him. He was probably on the ice for a few empty net goals. You take that away and all the sudden that’s six different and he’s a minus-13.

He also has 123 hits for our team, on a team that isn’t really physical. We don’t have a whole lot of physical guys. He leads our team in hits, he’s right up there in blocked shots. And those are things that a lot of people miss and they don’t talk about a lot with Michael Del Zotto. It’s a good example of how hard he works on the ice, how hard he competes, he makes some mistakes but he also plays against top guys in the league. I look at our d-core – we’ve got a group where I like all of them. It’s not an easy decision. Michael Del Zotto’s been in the league for a long time. We have some other young D that we need to push to get the most out of [them]. I think that Del Zotto is a player that, can he tighten his game up, can he become a better player? At his age, he’s almost where he’s at.

We need to make sure that the young d-men that we have, the young forwards that we have, we develop them, we make sure that they’re accountable and a lot of times playing or not playing is based on age, and sometimes it doesn’t matter and you see a veteran guy sit out. But you have to give those guys the benefit some nights, and sometimes you don’t, and we haven’t gotten to that stage yet. I love Del Zotto’s compete.

(h/t to Jason Botchford and the Provies, which is where I first noticed the quotes.)

First of all, I’ll touch briefly on the mention of plus-minus here. If you’ve managed to find your way to this website, you probably already know that plus-minus is a very, very bad statistic. In fact, Travis Green did a fine job here of listing some reasons why plus-minus is so bad.

For one, plus-minus includes multiple types of situations. So you think it’s silly that Del Zotto is punished statistically for empty net goals? That’s why we prefer to use 5-on-5 time. Secondly, luck plays an excessively large role. On-ice goals are a volatile statistic even over large samples (for reasons that I touched on here), and assigning meaning to them at small samples, even half a season, can be foolish.

So it’s a good thing that he’s casting aside Del Zotto’s plus-minus here. However, the reference in and of itself is troublesome.

Green’s reference to plus-minus is what we call a concession, in combination with attitude inoculation. He readily admits a flaw in the player he is about to defend, anticipating a counterargument before it presents itself, and then attempts to quash it. The idea is to make it clear to others that you have considered the opposing viewpoint, in a effort to strengthen the appearance of soundness of your own argument. It’s a smart tactic, but the fact that plus-minus is the counterargument that he anticipates is odd, and suggests that he doesn’t exactly know what the actual criticisms of the player are.

You’ve probably heard the saying that statistics can be manipulated to support any argument, and that is most certainly true. Travis Green has just shown that there are numbers in Del Zotto’s favour, in addition to the numbers I laid out above that are not nearly as complimentary.

Here’s the thing about that saying though: not all support has equal weight, and even if there are numbers that support both sides, that doesn’t mean that both sides are equally right. The saying is frequently used by stats doubters as a method to weaken a statistical argument, but it requires a certain naivety to be duped by faulty stats, and so the only reason to fear that a statistical argument might be selling you a false conclusion is if don’t have the ability to assess the methodology.

So, if this is something that you struggle with, I’ll be happy to do it for you.

Let’s take a look at some of the stats involved in this issue, and what they really tell us.

Blocked Shots

You may have heard this wonderful adage before: blocking shots is akin to killing rats; it’s preferable to do it, but if you’re doing it all the time, you probably have bigger problems. Originally credited to Kent Wilson (a Nation Network employee covering the Calgary Flames), this very succinct comparison undercuts even the most devout of Kris Russel supporters. While blocked shots are better than ones that make their way to the goalie, the bigger problem being referred to therein is that if you’re blocking a lot of shots, it means that you don’t have the puck very much.

This is far from ground breaking information. Public research on this goes back at least as far as 2009, when Richard Pollock found that blocked shots (at a team level) had a negative correlation with standings points (i.e. the more shots a team blocked in a season, the fewer standings points they had).

Since then, there is a wealth of further research on the subject. In 2012, Cam Charron (now an employee of the Toronto Maple Leafs) looked at the difference between raw blocked shots and the marginally more useful blocked shot percentage; HockeyGoalieEh delved deeper into correlations between blocked shots and shot shares over at Match Sticks and Gasoline; Ari Yanover of FlamesNation has published a couple of articles on the perceived value of shot blocking that included which events were most likely to occur immediately after a shot is blocked versus after a save is made.

Every article that digs into blocked shots finds some variation on the same conclusion: doing it too often means that you aren’t spending that time generating offence, and thus are more than likely being outplayed.

Hits

Hits is another interesting statistic from an “old school” versus “new school” perspective. Like blocked shots, it’s one of the few statistics that it presented during broadcasts of NHL games (at least on Sportsnet), and, like blocked shots, it is often linked to toughness.

Also like blocked shots, it’s been criticized as a statistic that inflates for teams (or players) that don’t have the puck. Richard Pollock ran the numbers here too, back in 2010, and found that there is essentially no correlation between hits and standings points, which means (sorry Garry Valk) you can’t routinely out-hit your way to wins.

If you get into the nitty gritty of it, as Garret Hohl did over at Hockey Graphs, you’ll see that on a player-by-player basis, those that spend more time hitting also spend more time getting scored on.

(Source: Hockey-Graphs)

The hits statistic has another problem though: is a fundamentally flawed as a result of the subjectivity of what counts as a hit. With blocked shots, we all know the formula: shot leaves stick + shot hits opposing player = blocked shot. With hits, though, it’s difficult to tease apart what counts as a hit and what doesn’t. Hockey is a physical game, and bodies are constantly rubbing up against one another (as Judd Brackett would say). Not everyone’s idea of where the threshold for a hit is the same, and as a result, hits vary wildly depending on which building they occur in.

Furthermore, merely being credited with a hit gives you zero insight into the usefulness of the action. Some hits remove the puck from an opponent, while others occur after a successful pass has already been made. Some hits knock players on their asses, while others are token rub outs that barely impede a player’s movement.

The effect of a hit can range from a forced turnover, to accomplishing nothing more than putting oneself out of position. Merely adding to a hit total doesn’t tell us anything about what the effect actually is.

And that’s not even touching on the fact that highly physical players tend to have shorter careers. In 2015, just prior to getting hired by the Florida Panthers, former Canucks Army staffer Cam Lawrence found that players with high hit rates (>2.6 hits per game) play significantly fewer games from age-27 onward compared to players with lower hit rates. Obviously each team needs some physicality, but this is worth keeping in mind with players like the 27-year old Del Zotto.

In any case, hits are becoming less and less important in the modern NHL, as the good teams begin to deviate from “heavy hockey” in favour of speed and skill. The type of player that needs to be defended using his hit totals is probably the type of player that doesn’t have much to offer in areas that actually move the needle.

(Source: TSN)

Quality of Competition

A frequent excuse for players that are struggling in big minutes is that they are playing against the opposition’s top players, and that’s why they continuously get outshot or outplayed. This is another one of those examples where the data doesn’t back up what seems like common sense, as in reality, quality of competition is a lot more complicated that many think.

The main reason for this is the same as the one that stats-doubters give when they suggest that analytics can’t explain hockey: that it’s a fast and fluid game. Players are constantly coming on and off the ice, and even though coach’s are responsible for deciding who goes over the board and when, their ability to match up against opponents is often greatly exaggerated. This is especially true when on the road, where the home team has last change and matchups become increasingly difficult. (Of course, in Del Zotto’s case, it’s possible that opposing coaches would want to get their best players out against him because he struggles to contain them.)

Because there is so much change on the ice all the time, players actually spend a lot of time against all tiers of opposing players, especially over a great length of time. Quality of teammates is much easier to influence, as the coach almost always decides who plays with who (players getting trapped on the ice is really the only time the coach doesn’t control this), but quality of competition is much harder to control, and thus the variability of quality of competition tends to be much smaller.

Additionally, the point is often made that defencemen that are truly good at handling top six forwards actually have positive shot differentials. If they’re being buried in shots each game, chances are it’s against all opponents, not just the best ones. Consider Chris Tanev’s generally positive on-ice numbers (this year aside), despite the fact that he very clearly plays more against top opponents than anyone else in the lineup.

The following graphs plots score adjusted Corsi percentage against Quality of Competition (determined by the opponents’ average percentage of 5-on-5 time on ice). In it, you’ll notice that there is actually a slight positive correlation between shot shares and quality of competition. This is because coaches are generally good at pitting their best defencemen against top competition. You’ll also notice that not only does Michael Del Zotto have the worst shot share on any defencemen that made the cut, but his quality of competition is actually in the middle of the pack.

Chris Tanev and Alex Edler regularly take the brunt of the tough matchups, and although Del Zotto occasionally plays with Tanev, his quality of competition on average is much lower because he also plays on other pairings that get much easier matchups. You can see in the graph immediately above that Del Zotto’s QoC is markedly lower than the likes of Edler, Tanev, and Dan Hamhuis, and lower even than Gudbranson, Jason Garrison, Troy Stecher and Kevin Bieksa. He’s not getting buried while playing mostly against top forwards, he’s getting buried by everyone.

While we’re on the topic of shot attempts, let’s move on to some numbers that actually have some serious support behind them.

Shots (or Shot Attempts)

I don’t know if there’s anyone reading this that doesn’t understand why shot shares (Corsi, Fenwick, etc) are important, but I’ll run through it quickly anyway.

Obviously, goals are important in the game of hockey. They are the only thing that really matters when it comes to actually winning games. The value of everything else involved in hockey (from shots and zone entries to toughness and leadership) should be measured only by its ability to predict and influence increases in goals for and decreases in goals against.

The thing is, some of these things are difficult to measure, either logistically or theoretically. Zone entries (as with as things like zone exits, shot assists, and entry break-ups) have to be hand tracked, which naturally reduces the overall amount of data available, and increases the difficulty in accessing it. Abstract ideas like toughness, grit, compete, and leadership may well be very important, but the level of importance is nearly impossible to nail down because they are subjective qualities that can’t be measured objectively. We simply don’t have the ability to assess the correlation between leadership and goal differential, and while that may not be important to some people, it’s significant in terms of legitimately knowing where intangibles stand compared to tangible statistics in terms of influencing wins.

Shots on the other hand are widely available, and have been for quite sometime, leading to a large amount of research on the subject in terms of repeatability and predictivity. Consider this table from CJ Turturo at All About the Jersey that lays the correlations (R) and goodness of fit (R^2) of various tiers of shots and goals.

As you can see, Corsi is the dominant shot type in terms of predicting future goals, and both the repeatability and predictivity of goals decreases as you can down in tier, eventually leading to goals, which, comparatively, do a very poor job of predicting future goals. Part of the reason for this is reducing the sample and eliminating useful, something that I wrote about in my piece on analytics as hockey’s representation of the scientific method.

Shots in hockey are tiered based on their level of success. Some are blocked before coming close to the net; some miss the net; some are stopped by the goalie. It’s only a select few that land in the back of the net. It’s also only these that are required for a victory.

Only one in every 20 or so attempted shots becomes a goal, on average, and it’s difficult to pinpoint which shots those are going to be, even with what we’ve nailed down regarding shot quality. But the fact that in some games there are goals three goals for every 20 shot attempts and in others there are none doesn’t change the fact that the average will force the shooting percentage to balance out over the long term. This is how regression to the mean works.

It’s also why shots are a more reliable indicator of future success than goals are. By and large, we know that eventually a specific percentage of them are likely to go in the net, so their value can still be objectified, and there are roughly 20 times as many of them. So we can feel comfortable making some light conclusions based on shots after 20 or 30 games, while goals (or wins, for that matter) can be misleading even on a season scale.

Another part of it is that the idea behind using shot shares to measure player success is that it is supposed to be a proxy for puck possession, which most agree is fundamentally important to winning in hockey. While scoring chances are technically a closer tier to goals than shot attempts are, shot attempts are a closer approximation of pure possession, and from than angle, they are actually more important.

This can be a bit counterintuitive, because some shots are clearly more likely to go in than others. If we want to get even more accurate, we’d want to weight all shot attempts so that dangerous scoring chances are given more weight, but a high volume of longer distance shots, or shots that hit the post (which are counted as misses rather than shots on net) aren’t entirely ignored.

That’s the whole purpose of Expected Goals. There are a variety of methods of creating this metric, though they are all similar theoretically, and they are all highly efficient at predicting future offence. Take Dawson Sprigings’ version for example, which has been shown to be more effective at predicting goals-for percentage at the team level than even Corsi-for percentage, the previous goal standard.

(Source: Hockey-Graphs)

Production

There’s one thing that I haven’t covered in detail here, and that’s Del Zotto’s production. Green also mentioned Del Zotto’s 14 points (two goals, 12 assists), which is second among Canucks defencemen right now.

Three things have helped him this regard: he hasn’t missed any games, he gets a lot of ice time in the games he plays in, and he’s had plenty of power play time, especially early on. He leads the team’s blueliners in 5-on-4 points per hour, though four of his five 5-on-4 points are secondary assists. His primary points per hour on the power play is actually last among Vancouver defencemen who see regular power play time. In terms of 5-on-5 production, he sits fifth, behind Edler, Tanev, Derrick Pouliot and Alex Biega.

Del Zotto has a slightly above above on-ice shooting percentage, which is helping him get some extra points, by all in all, this is a good thing. I don’t want to take too much away from a player who is producing, as that really is the end goal.

The problem with Del Zotto is the same problem that we had with Brandon Sutter last year when he was producing at a decent rate. It doesn’t really matter how many points a player is getting if the other team is scoring twice as many goals as his team is whenever he’s on the ice. With a goals-for percentage of 38.8%, Del Zotto is dangerously close to that right now. It’s important to team success that he continues to produce, but it’s even more important that he gets a handle on the goals against.

Closing Thoughts

Michael Del Zotto is a clear cut case of a player who is tallying up some nice old school numbers, but is being buried in the areas that actually matter in terms of outscoring an opponent. The fact that he’s racking up a lot of hits and blocked shots does not come close to absolving him of being among the NHL’s worst defencemen in suppressing shots and scoring chances.

It can be difficult to sift through so many different metrics to determine what sort of effect a player is having on the game, whether he is thriving, surviving, or struggling. The best way to sift through that information is to lean towards metrics that have strong support in terms of predicting goals and wins, and be wary of metrics that don’t. Moreover, stay away from praising a player for numbers that outright indicate that he’s chasing the game.

Travis Green and the Canucks staff would probably be better off if they adhered to these general principles. At best, they could see noticeable improvements on the ice if the put these basic ideas into practice, and at worst they could avoid looking like they’re lacking an understanding of which numbers are helpful and which are not.

  • Bud Poile

    “I don’t want to take too much away from a player who is producing, as that really is the end goal.”
    Outscoring Hutton,Stetcher and Biega-combined or Tanev and Hutton-combined.
    “In any case, hits are becoming less and less important in the modern NHL, as the good teams begin to deviate from “heavy hockey” in favour of speed and skill.”
    And then the playoffs begin,as all Canucks fans are forced to remember.
    Well,maybe some of us have short memories.

      • Freud

        My sympathies Jeremy. It must be frustrating to do charity work for the likes of Pud, in the form of this dumbed down piece, only to realize they are too dim to even understand the basics of a dumbed down piece?

      • Bud Poile

        You’re welcome,Jeremy.I enjoy your work.
        The NHL post season hasn’t changed much over the five decades I’ve been watching.
        Gillis relied upon “speed and skill” and the Benning Bruins beat us into pulp.
        The NHL game changes at a snail’s pace.
        It hasn’t become the Swedish Elite League since the spring of 2011.
        Ballerina and pretty boy stats from the regular season mean little come May each year.

          • Bud Poile

            With a name like ‘Goon’ I expect as much.
            How was Edler’s stats after a slash broke two fingers on his shooting hand?
            How did Ehrhoff pad his statss after being crushed in the SJ series game 3?
            Raymond’s stats slid to a scissor stop upon having his back broken.
            Samuelson-broken abductor tendon and hernia.Surgery on both.
            Higgins played with a broken foot.Stats suffering there.
            Kesler played with both groin nd labrum tears.Yeah.
            Hamhuis missed the final five SCF games with a groin tear.
            Bieksa was chopped with a Peverly two-hander behind his knee in game 5.
            Tambellini is quoted as saying that 7 of those Canucks left standing were shot up for game 7.
            There’s your real facts, Goon.
            Utter nonsense,indeed.

          • Dirk22

            Bud logic – So the Canucks had a bunch of injuries in the cup final 7 years ago and those wouldn’t have happened if they had more toughness like Del Zotto.

          • truthseeker

            Except that the penguins were one of the worst “possession” teams in the playoffs. And won the cup.

            I’m still waiting for the correlation percentages of positive puck possession numbers and position in the standings, winning, or player production over a given season. Funny how the stats guys can’t produce those numbers.

          • liqueur des fenetres

            Truculence isn’t the only way to avoid injuries in the Cup final. They can also be avoided by getting knocked out early, or missing the playoffs all together.

  • Gampbler

    Green and the coaching staff review hours of video after each and every game breaking down mistakes, positioning, pinches, zone entries/exits and other various “little” details of the game. I think he knows exactly what he is looking for in each and every player, so I will let him use plus/minus, hits and blocked shots as talking points. It is his job to use that knowledge to improve his players in specific areas and if he fails at that, then he fails at the NHL level. But to question his and,any NHL coach for that matter, inability to use the proper stats is barking up the wrong tree.

    • Rayman

      yeah, but what about the last year, man? You mean WD used all those high-end analysis-skills and did what he did?

      It’s one thing to gather infos and completely other thing to know how to apply them to your decision. For a decision making, Green becomes dangerously close to WD……

  • OMAR49

    I spent most of my career working with statistics. The one thing I learned is that if you rely totally on statistics to come to a conclusion you will be wrong most of the time. I also learned that if you don’t use statistics your conclusion will also be wrong. The point being, that statistics are valuable tools and should be used BUT there are other factors that should be taken into consideration.
    Now, I am not a Del Zotto fan. I think he makes a number of poor decisions but, if I were to replace him and rely only on the statistics, then the “logical” choice is Alex Biega. Based on the same statistics used to determine that Del Zotto is totally incompetent, Biega should be this teams #1 D-Man. After all, he is 2nd in Corsi, 2nd in Fenwick, 1st in Shots For, 3rd in Goals For, and 1st in Expected Goals For.
    Somehow, I have trouble picturing our back up as this teams #1 D-Man, but, then again, statistics don’t lie.

      • Gampbler

        It’s almost like what google has done for the medical field, in that people think they know more than their doctor or surgeon about what their symptoms mean.

    • Roshirai

      This is a pretty reasonable comment, but to be fair to Jeremy, he’s also come out specifically against using statistics as the sole determination of a player’s ability/worth. He did it all the way back in November, in fact, _in an article he linked to in this very post_.

      I don’t believe there’s a single writer for this site who believes that advanced statistics are the be all and end all of hockey analysis. They are just one tool among many for evaluating players and performance, alongside things like the much vaunted “eye test”.

      • Betty

        Maybe I’m new, have you ever seen a CanucksArmy writer argue that the stats were wrong and that a player passes the eye test? (I imagine they have to do this for Boeser as his advanced stats aren’t great but anyone else?)

  • Charlie Allnut

    I believe that you were one of those guys that picked LVGN to finish somewhat down in the standings. I wonder what Gerard Gallant would have to say to you now.

  • Betty

    Jeremy, please check with someone who does understand stats (like, a professor or someone with a stats degree). Most of these shot attempts metrics have almost no statistical validity. The samples aren’t random and heavily influenced by whom you play with and against, which are huge confounding variables. (Eg, Tanev may play against top competition more often, but he also plays with our best players more often. How much does that matter? Hard to say because we can’t really disentangle the effects. How about what is the effect of playing with Edler? Again, hard to say.)

    It’s kind of why the statistics is empircal science bit was hilarious. Good statistics are fairly reliable, poor ones aren’t. To use bad statistics and claim anyone who doesn’t agree disagrees with science is a little like Aristotle yelling at people that to disagree with his elements view of the world means they don’t understand logic.

  • valleycanuck

    /honeymoon

    Not at all happy to hear a coach emphasizing seniority over merit-based ice time. I was excited at the beginning of the season for a fresh system and more understandable deployment. This article, more specifically Greene’s comments get me a bit worried about the (possible) introduction of potential franchise-face players like Petterson and Juolevi next year. The uproar from fans and broadcasters alike will be even louder if we find ourselves having this discussion next year with Juolevi getting scratched because MDZ is 28 and Sam Gagner is 29…

    Good all-around article though, thanks for the read.

  • bushdog

    somebody gets paid for this blithering stupidity? it boggles me that a single, simple topic can be dragged out for pages and says absolutely nothing. the only reason anybody cares about these numbers is because we keep getting this crap jammed up our bum.
    this could easily be a statement like ‘blah blah’, and 25 letters long.
    this site is rapidly becoming just like all the others, babbling stupidity just
    to catch a click. i used to be comfortable here but it’s become so tedious at
    times that i’m not any more.
    please get back on track and give insights and opinions…not any of this garbage. PLEASE
    long-winded and silly that i simply can’t abide it any more.

    • wjohn1925

      I just finished giving a big thumbs up to Omar49. He was articulate, clear, and most importantly avoided the ‘snark’, making the same basic point as bushdog.

    • Sandpaper

      Are you still banned from that other site?
      How many times have you been banned from that site since you joined 1.5 years ago?
      My guess is you get banned once every 3.4 months.

    • MDZ’s got another year on his contract so he’s not likely to get moved at this year’s trade deadline. If he’s moved, it’ll probably be at the draft, or at next year’s deadline.

  • dj2

    @Jeremy, I enjoy these articles with statistical analysis, but wish you would just put a bit more effort into explaining what the graphs mean. E.g. SCF%, HDCF% I can probably guess or look at the source article, but why not just list the abbreviations?

    In the “predicting future GF%” graph, I see a bunch of lines trending towards the same point, but I don’t actually know what that means. If a lower number for R^2 is better then doesn’t that actually mean that current GF% is actually the most predictive factor for future GF% according to that graph?

    • NeverWas

      Higher the Rsquared the better. Anything below 50% is statistically irrelevant… sooo I don’t even kmow why they would have it. Generally you wanna see models with an Rsquared of 90% as a minimum.

      • DJ_44

        The above statement is and imperfect understanding of what R^2 represents. “higher is better” may be a correct interpretation for some data; it may be wildly incorrect with other data. You have to look at a number of factors when assessing the validity of the analysis, or in this case, the relationship between the data.

        I have not looked at the data presented in detail. In general, the publicly available hockey data (which underlies the stats) is what it is, and the analytics community does the best with what it has.

        • NeverWas

          DJ, I’m not statistician… only have a master degree in finance with a focus on analysis aka decision modelling… so you don’t have to believe me but I’m pretty sure I’m right and your dead wrong.

          R squared is known as the “coefficient of determination”. It’s indicates the correlation between the data and the regression line. R squared value of zero means there is no relationship. 99.99999…. means this model and the regression equation could predict the foreseeable future with almost certainly ( depending on the sample size) anything less than 50%… atleast in the financial world we deem statisictally irrelevant or junk. Even below 80% the models don’t work well… but who knows, maybe I’m wrong. I only build models for a living (small part of my day-to-day but I use them regularly). You do you though pal.

          • DJ_44

            so you don’t have to believe me but I’m pretty sure I’m right and your dead wrong.

            Regarding your conviction I have no doubt.

            I am not a statistician either, but I (am assuming) like you, I use statistics ( advanced stats) nearly every day in my professional life. I also develop, build, run and assess a number models used to predict natural phenomena.

            I understand what R^2 is, and what it represents. I also understand that an very high R^2 does not necessarily mean you can predict something (like the relationship) with a high degree of confidence carte blanche (and vise versa). It MAY indicate that, and if that is the case in the financial data sets/models you use; great. For many other areas where data is produced, it is not the be all and end all — just one of the tools.
            With respect to the topic of the article, I stated I did not look at the data sets, so could not comment with respect the the R^2 values presented.

            Are all financial types so condescending?

  • TheRealPB

    I’m a bit confused by the blowback against this article. Even if you didn’t agree with the statistical analysis, isn’t MDZ one of those cases where the eye test and the stats test meet? He is — especially for a veteran — constantly out of position (which leads to him diving desperately to block shots or throw hits — look at how differently Tanev or Edler do those two things, in a much more controlled fashion) and he makes reads almost as poor as Gudbranson. One of the reasons the Canucks d is so poor is because there’s the two very good vets (Tanev and Edler), a bunch of green kids with potential (Stetcher, Pouliot and Hutton), an AHLer (Biega) and then the tire fire that is Gudbranson and MDZ. I honestly don’t know how anyone can defend either. And in the case of MDZ, he has had similar problems in New York, Nashville and Philadelphia. He never progressed past that early potential and now he doesn’t seem to have the mobility he once had and his gambles rarely pay off. Of all of our FA signings he’s been the most disappointing to me (way more than Eriksson who I think is more effective and has been bounced all up and down lines). Green himself says in the Botchford article that MDZ is what he’s going to be. That’s what’s so damning to me about the old boys network in the NHL (and all coaches seem to be embedded in this no matter what their tactics and schemes are) — they’ll always play a low risk low ceiling player over a higher risk higher reward one. For all the grief that WD got, in this respect he’s not really out of step with any of his brethren (and you could argue he’s done a better job of developing younger players than Green; Boeser isn’t a result of him and he hasn’t done much to give Boucher or Goldobin or Virtanen a chance)

    • It’s a head-scratcher for sure.

      MDZ seems like a guy who could add something of value if played in the right way, but he’s really struggled this year. I thought everyone was on the same page on this one, too.

    • truthseeker

      I think the blow back is not necessarily about MDZ himself but rather the implication that shot metrics are a sure basis for analysis.

      I don’t think anyone, short of maybe that bud guy would argue MDZ is not looking like the best D man out there on many nights. Either by using those metrics or simply watching the game.

      The correlations between individual player success and shot metrics seem to be fairly flimsy at best and no real percentages ever seem to be given showing direct correlations between shot metrics and the points race leaders, not to mention ranking D men. And to me shot metrics seem to fail even more when evaluating team success. If you go look at any given year plenty of teams with low possession numbers make the playoffs and plenty with great possession numbers don’t. The final four last year had the Sens and Pens who both had low possession numbers, and the Pens won the cup with inferior possession numbers.

      I’m still waiting for the writers or anyone who argues so fervently for the value of possession stats to provide the percentages that show that it translates to actual regular season points and success over a short playoff period. I don’t think they’ve made their case at all. Articles like the one above say things like “possession leads to shots and shots lead to goals therefore possession is an indicator of success”. lol.

      I think this article is goes a long way to showing the flaws in the thinking of the possession stats crowd.

      http://thesportjournal.org/article/goal-based-metrics-better-than-shot-based-metrics-at-predicting-hockey-success/

      I’d welcome someone to critique that and counter the points made. I’m too lazy to go beyond what I did one time which was looking at all situation possession and even strength 5v5 possession number rankings and comparing that to the end of year standings and finding virtually no link. It seems to only show up when you start looking at team success over many years. Like over a 5 or 7 year span teams with better possession seem to be consistently among the better teams over that time frame. ie, Kings and Hawks. But then, that seems to not really play a role in winning cups. They’ve won their share using that method but then you get the Pens who’ve won basically as many as those teams but by bouncing up and down in terms of long term success. At that point does it really matter which way you do it?

    • DJ_44

      The funny thing is, if you look at MDZ’s game and Hutton’s game, the are very similar. Del Zotto is a better defenceman, in the sense his is a 4/5; while Hutton is a 6/7.

      Their perceived strenghts? Puck movers, good at the offensive blueline. Weaknesses? Play in their own zone, defensive awareness, staying with their man, battles below the goal line.

      The difference, MDZ has more defensive awareness then Hutton (and that statement alone should make one pause).

      Yet, one is a top-4 shutdown dmen according to select analysis and the other should be sat. Funny how the top-4 shutdown guy has seen little ice-time when the Canucks are tied or leading in the last 5 minutes of the game.

      Del Zotto’s problem is lack of effort: thinking he must play like Suter or Karlson in case he may see 32 minutes a night.

  • Killer Marmot

    In any case, hits are becoming less and less important in the modern NHL, as the good teams begin to deviate from “heavy hockey” in favour of speed and skill.

    Hits are becoming less common, but that doesn’t mean they are less effective. They might even be more effective as today’s players are less accustomed to it.

  • Holly Wood

    Your a little late Jeremy. I used the eye test and have been repeatedly telling the Army that MDZ ‘s play has fallen off a cliff since November. Didn’t need any fancy stats to determine that.