Category Archives: G Money

Edmonton Oilers, G Money, NHL, Prospects

The Oilers Have A Promising Rookie In Leon Puljujarvi By @OilersNerdAlert

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Oops, of course I mean Jesse Draisaitl.

Aaargh, no wait, it’s *JESSE* *PULJUJARVI*.

The comparison to Leon isn’t a coincidence though … not that I fooled any of you into thinking it was.

Pulju has had a bit of an unproductive rookie year, much like Draisaitl did, and people are a little worried about that.

On top of that, a lot of verbiage is being spilled recently on the fact that Pulju isn’t playing much for Finland’s team at the Worlds. Not sure what that’s about (I haven’t followed closely, but I keep hearing he’s been one of their better players, so … ?)

With that said, given all the negative ink, I see similarities in the way Draisaitl and Puljujarvi tracked during their rookie years that keeps me from getting too gloomy, so let me share that with you.

Twins

Let’s start with some basic stats from the rookie years of the two players:

**Note: the Sh% numbers above are on ice EV sh%. Personal sh% numbers were 2.4% for JP and 4.6% for LD**

The similarities here should be clear. Both played less than half a season. Both scored around a quarter of a point per game, and well shy of two points per 60 minutes. Both players had shooting percentages in line with fourth liners rather than first liners.

Pulju was a little ahead of Draisaitl in that regard, but not in any significant way.

But the thing I want to really emphasize is the possession. Both players were positive in possession metrics, both on an absolute and a relative basis.

The ‘relative’ part means the team did better on shot metrics with these guys on the ice than without them.

That’s a really important thing IMO.

Young skill players can often score as rookies, but even the highly skilled ones typically struggle with the defensive aspect of the game … which means they tend to give up a lot of shots and chances. That shows up in poor possession numbers.

If they don’t learn to think that defensive aspect of the game at the NHL level, the offensive skill may not overcome the defensive liability and that can derail or even torch an otherwise promising career (think: Gagner, Sammy; Yakupov, Nail).

That LD and JP at such a young age both allow(ed) their teams to get the better of the shot balance when on the ice is a very good thing indeed.

Replacement Impact

Let me dig in a bit more on this aspect, because there’s something *really* unusual (in a good way) with both players that needs highlighting.

Let me explain what the two charts I’ve posted below mean.

We start with WOWY (WithOUT you With You) data. WOWY looks at pairs of players to see how they do together and then without each other on the ice.

By looking at a player’s WOWY data across a range of teammates, we can start to get a sense of whether that player is carrying/dragging his teammates, or is being carried/dragged by them.

“Replacement Impact” is a specific way of looking at WOWY data where you ignore the ‘together’ data and look at the players as substitutes. That is to say, we compare how Player 1 does without Player 2, and vice versa. In other words, conceptually it’s kind of like we look at it and say “what happens when you replace Player 1 with Player 2 on the ice?”

The charts below show what happens to shot attempts (CF%) when you replace a particular player with Puljujarvi or Draisaitl. (This data is from 2016 for JP and 2014 for LD, and shows all non-goalies with whom they had 30 or more minutes of shared icetime).

Here’s Draisaitl:

And now Puljujarvi:

You see what’s happening?

In terms of replacement impacts, with just one single exception each – Maroon for Pulju and Perron for Draisaitl – the team gets better when Drai or Pulju step on the ice, EVEN AS ROOKIES.

Now let’s throw out a word of caution here … what I’ve put forward for you is hardly an iron clad or infallible type of analysis. There’s lots of confounding factors involved with teammates and competition and usage that aren’t accounted for.

But when you see such a consistent positive pattern across a wide variety of teammates, it’s a tell. A good one!

The Future

So we saw how this played out with Drai – as a rookie, the possession was there, the skill was there, but the scoring wasn’t. With experience and confidence, the scoring came on like gangbusters.

So don’t get down on Puljujarvi’s future.

He’s younger than Drai was (Drai was an October birthday and was 19 most of his rookie season; JP just turned 19 a day or two ago), and unlike Drai did not have the benefit of playing and adapting to North America in Junior, so adaptation *is* going to be a struggle.

Even in the best case, it’s going to take Puljujarvi some time, moreso than it did with Drai.

But the speed and skill is there, in spades. The possession impacts are excellent – indeed, for a rookie they are stellar. What’s missing for Puljujarvi is confidence and experience (and also like Drai, some man strength to be able to play his imposing power game against NHL size players).

There are no sure things when you’re projecting young players, and like all of his ilk, Jesse will need to be dedicated to getting better … but this first season tells me we’re quite likely seeing a star in the making.

Don’t forget about Drai, but remember Puljujarvi!

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Edmonton Oilers, Fancy Stats, G Money, NHL

Assessing the Western Conference Playoff Landscape by @Oilersnerdalert

Who’s the favourite? We know the Oilers are going to play San Jose first, but in the big picture, who should the Oilers want to play most/least? Enquiring minds want to know!

There is no magical way to ‘know’ what’s going to happen in the various series, but we can look at how the season has shaped up and make some decent guesses about who to favour.  I’m going to walk through a few different methods and we’ll see what we see.

Don’t Use Standings

First, one thing that I’ll start with is to stay you can generally throw the regular season standings (or points) out the window.  There is a fairly weak relationship between points and post-season success (though it may surprise you to learn that the PresCup winner, far from being ‘cursed’, actually tends to do quite well in the post-season).

Head to Head Score Adjusted Corsi

Our first data stop will look at how the various West teams fared head to head in 5v5 score adjusted Corsi. Since the refs tend to put away their whistles in the post season, the importance of 5v5 is magnified, so this gives us a sense of how the ‘playoff’ part of their games went.

http://i.imgur.com/diHK3SO.png – source @OilersNerdAlert

From an Oilers perspective, MIN and ANA look like good matchups, while the others, especially CGY, CHI, and S.J look like tougher matches. But wait! Didn’t we go undefeated against CGY?? Not to mention STL? How is this possible?

Actually, this is the weakness of any statistical look – small sample size. In the case of CGY vs EDM, the Oilers blew out the Flames early in several games. For example, the first game of the season, the gameflow looks like this:

http://i.imgur.com/rbbg7Cn.png – source @OilersNerdAlert

The Oilers basically ran up the score early, dominated for most of the game, and then went into a defensive shell – which allowed the Flames to run up the fancystat counters, even as their loss was already written. Same story in the last game of the season, where the Oilers ran up a 5-0 edge and then coasted.

Now you might ask, isn’t score adjustment supposed to take care of that? Well – yes, sort of. It takes care of that at a statistical level. The score adjustment is done based on league wide averages.  So it works really well when you get at least 10 to 20 games of data, enough where the averages start to apply in a meaningful way.

But a score adjustment at a game level, or even at a season series of 4 or 5 games, while it will almost always push the fancystats in the right direction, won’t necessarily be reflective of that game or games. Especially if there were blowouts, as there were twice in this series.

So I wouldn’t take these numbers too seriously. That’s why I put this look first – it’s actually not that reliable IMO. It’s more for interest.

And as we’ll see later, if the Oilers face the Flames, take the Oilers all the way!

Head to Head Records

I don’t actually know if anyone has tested to see if head to head records have any predictive power for the post-season (my gut says probably not), BUT I sure do like this!

https://twitter.com/humantorch/status/851498850430976000

Goal Differential

I mentioned earlier that points are not that great a way to assess post-season chances. A much better a predictor is goal differential. (Read the detailed analysis here: https://www.stats.com/insights/nhl/debunking-myth-playoff-vs-regular-season-hockey/)

When we look at the teams sorted by goal differential, it gets pretty interesting:

http://i.imgur.com/KPObkSA.png – source NHL.com

Now Edmonton is starting to look more like a powerhouse than a weak sister, yes?  If Talbot Talbots and McDavid McDavids, the Oilers can beat anyone.

And of course, the weak sister in the West is in fact … Da Flames.

By the way, you might be wondering – isn’t this basically PLUS MINUS, and isn’t PLUS MINUS the pariah of the fancystats world?

Indeed, it is – at the player level. That’s for two reasons – the assignation of plus minus at the player level is extremely noisy, and because goals are such rare events, it takes multiple seasons to generate enough player sample size to overcome that noise – and by that time, your player has usually changed (situation, or even age!)

We don’t have as much noise, or as much of a sample size problem at the team level though, which is why goal differential works pretty well.

Score and Venue Adjusted [Corsi, Fenwick, Expected Goals]

Now let’s get on to some actual fancystats. I’m using Corsi, Fenwick, and corsica’s xGF.  Corsi has historically been something of a gold standard for predicting the future.  What’s interesting though is there’s an argument to be made that this relationship may be weakening as more teams pay attention to shots/possession and the resulting ‘market efficiency in action’ takes away some of the advantage historically measured by shot metrics.

We’re going to take the full seasons 5v5 measures and rank teams that way. So we’ll roll all three together to get a sense of where the teams fit:

http://i.imgur.com/OZPNHdY.png – source corsica.hockey

Ooh, that’s a bit ugly, isn’t it?  The Oilers are much weaker by this measure – ranking 7th, 2nd, and 6th out of 8.  So why such a big difference from goal differential?

Well, the easiest way to way outperform (or underperform) your underlying shot metrics is through the quality of goalering (you can also do it through special teams but I’d say that’s ‘harder’ in some sense).  So I think this really reflects the fact that Cam Talbot this season has been incredible – arguably a Top 4 or Top 5 goalie league-wide.

If the Oilers are to have success in the post-season, he’s going to have to continue his strong play. No surprise there.

San Jose looks a lot like the powerhouse that made it to the Cup Finals last year. Not going to be an easy series!

I guess the saving grace is that the Flames are still weak at 5, 8, and 8.

Tweaking the Fancystats

There’s an interesting tweak we can make to these numbers to increase their assessment/prediction capability. One of the things we know is that shot metrics in-season have their peak predictivity around 20 to 25 games, after which there is a slow decline in predictivity. Some of that is due to increasing randomness as games predicted declines.

But I think a significant part of it is also that teams change over the course of the season. Key players get hurt (or come back from injury).  Sometimes coaches change.  Teams get into a groove or fall out of one.

So we have this balance to find – we want the maximum amount of data possible, but if we use data that’s too old, it isn’t actually reflective of the team right now.

As it turns out, using the last 25 games gives adequate data volume and yet doesn’t get overloaded with games from early in the season that aren’t really indicative of a team now, producing a fairly high level of predictivity. (see for example Micah Blake McCurdy’s work on his Oscar prediction model).

So let’s look at two things – how a team did over the last 25 games of the season, and also the trend of that data, as a bit of a projection as to the direction of the teams level of play.  (Note: out of laziness, I’ve taken data for the Oilers from Feb 15th, which equates to 25 games. Other teams may be a bit more or less – ha ha, too bad for them! More seriously, it shouldn’t change the results much, if at all)

Let’s take a look.

Here’s the West teams from best to worst in SACF% over the last 25 games:

http://i.imgur.com/7ocNV8l.png – source corsica.hockey

Oooh.  Still sucks to be the Oilers on that basis though, doesn’t it?  But we also know that those 25 games started with a fairly poor stretch for the Oilers, but they’ve been coming on strong of late. And the opposite is true for the Flames. So let’s look at the trend over those games too.

http://i.imgur.com/2HcmCVp.png – source corsica.hockey (chart by @OilersNerdAlert)

Hmm, that’s encouraging, right? Despite the rather soft numbers the Oilers put up in the second half, in fact (as the eyes would suggest), the Oilers appear to be improving in a big way as they head towards the post-season. Yeah!

Cowtown on the other hand – again, as the eyes would suggest – are sliding back to Earth after the unsustainable hot streak that pulled them into the playoffs.

San Jose has solid numbers, but is neither hot nor cold.

I’ll leave you to mull over the rest of the trends.

Putting it All Together

We’ve taken a few different looks at how teams did in the regular season to get a sense of how they might fare in the playoffs.  Now, has this work given you the definitive guide to who’s going to win the West?

Ha, of course not! Statistics give you a sense of which way the probabilities lean, they are most certainly not fait accompli.

Rather, what we’ve got is some sturdy data to suggest which teams are leaning positive and which are leaning negative.

You still have to understand context though. Statistically, Anaheim is looking pretty good – but if Lindholm, Vatanen, and Fowler are out or not 100%, that’s a huge hit. Ditto San Hoser and Jumbo Joe. (In fact, one of the defining characteristics of Cup champions is that they are good and healthy when they hit the playoffs, and are still mostly healthy, or at least healthier than their opponents, by the time they get to the finals).

The Oilers meanwhile actually look pretty good, my friend!  Probably not to win it all, but I’d say we’ll be a tough out even for a legit contender.

And with McDavid and Dadbot on our side, anything can happen.

Bring it on!

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Edmonton Oilers, G Money, NHL

How Big Are the Oilers Really?

We know that Pete Chiarelli has prioritized adding size over the last year.  Those moves have been universally lauded where the package included skill (e.g. Pat Maroon), but less universally loved when it involved a size vs speed+skill tradeoff (Lucic for Hall for example).

No question, though, that the Oilers are now a bigger and tougher team than they have been in the past.

Seems that a couple of questions are now floating in the heads of some Oilers fans: a. do we need to get even bigger? b. will we?

Maybe, maybe not.

There does seem to be a tendency for teams to copycat the latest Stanley Cup champions “formula”.  So now the focus turns to Pittsburgh’s speed and skill rather than size. It always works that way – follow the “leader”!

But how big are the Oilers really?

Before most Oilers games, I tweet out what I call my “Heavy Hockey Update”, which scrapes the NHL roster pages for the Oilers and the team they are playing. I take all players listed on the active roster for each team, and calculate the average height and weight of the forwards and defensemen separately.

Although I do this mostly for fun, splitting the data this way I think is more useful than just giving a roster height and weight, which not only conflates the two player positions, but also rolls in goalies (who, let’s be honest, are not relevant to the question of how big a team really is!).

(The ideal way to do this would be to weight the players based on TOI, but I won’t have that improvement ready for a little while yet as I’m preoccupied with other projects).

All Thirty

What I did for this article is tweak my program to scrape the rosters of all 30 teams at once. You can take a look at the raw data table at the end of this article.  What can we glean from it? Let’s dig in!

First off, you can see that height is mostly not a big deal – the shortest team forwards are TBL at ~5’11”, and the biggest are COL and WSH at 6’2″. That’s a range of about 4%. For defensemen, that range compresses, running 6’1″ to 6’3″.

The bigger discrepancy is in weight, where the range is ~11% for forwards and defense.

The roster size of forwards ranges from 190 lbs (CHI) to 210 lbs (COL).

For defense, that range runs from 194 lbs (MIN) to 217 lbs (CBJ).

In the table, I’ve highlighted the Oilers, as well as the top and bottom teams in the two categories.

Based on these parameters, the Oilers now rank:

  • 14th overall in the forward size ranks
  • 21st overall in the defense size ranks

Again, this is based on the NHL.com active roster listings as of January 4th, 2017.

There is no question the Oilers are bigger – in times past, the Oilers were bottom 5 in the league in both categories. But still far from ‘big’!

Is it enough?

Well, if you look at the table, you’ll note that there really doesn’t appear to be much of a relationship between size and results.  CHI and MIN and PIT are all well down there, and they’re pretty good!  Mind you, so are CBJ and LAK up at the top of the table.

But BUF and COL are both big and terrible.

Also funny to see how average Chiarelli’s old team is size-wise.

Personally, I’d rather add speed and skill over more size. The Oilers need a right handed shooter, and someone on defense who has a PP cannon and/or can make headman passes like Ryan Whitney or Pronger or Visnovsky used to do.

If you are going to add size, though, it’s the defensemen that are smallish, not the forwards.

Data

Team Avg F Height Avg F Weight F Weight Rank Avg D Height Avg D Weight D Weight Rank
ANA 73 202.4 12 74 205.7 18
ARI 73 201.2 15 74 203 23
BOS 72 196 20 75 208 13
BUF 73 206 3 75 213.4 3
CAR 73 195.6 23 74 202.6 24
CBJ 73 202.9 10 74 217 1
CGY 73 195.2 25 74 202.3 26
CHI 72 189.8 30 73 197.4 29
COL 74 209.9 1 74 211.4 4
DAL 73 203.4 7 74 209.4 7
DET 73 196.7 19 74 207 15
EDM 73 202.3 14 74 205.1 21
FLA 72 194.6 26 75 206.6 17
LAK 74 208.9 2 75 213.6 2
MIN 73 203.2 8 73 194.1 30
MTL 72 191.9 29 74 208.3 11
NJD 73 195.9 21 74 205.6 19
NSH 73 200.8 17 73 201.9 27
NYI 72 203.1 9 73 205.6 19
NYR 73 202.6 11 74 209.1 9
OTT 73 195.7 22 73 204.7 22
PHI 72 195.6 23 72 198.9 28
PIT 72 193.9 27 73 202.4 25
SJS 72 201.1 16 74 208.6 10
STL 72 205.2 5 74 210.8 5
TBL 71 192.2 28 75 208.3 11
TOR 73 202.4 12 73 206.9 16
VAN 73 197.8 18 74 210.4 6
WPG 74 203.5 6 74 209.4 7
WSH 74 205.8 4 73 207.1 14
G Money, NHL

Oilers and Playoffs – Guidelines for Scoreboard Watching

Oilers and – gasp! – playoffs?!?

Yes, indeed, here we are in January and the Oilers don’t just have a shot at the playoffs, but should be favoured to end up with a spot in the post-season dance!

That means we as Oilers fans get to do something that should be quite familiar – scoreboard watching.

The difference is, this time we’ll be watching the scoreboard for the playoffs and not the lottery. Which means now we want to win, and we want other teams to lose! Refreshing!

So I thought I would lay out my particular set of rules for scoreboard watching as it sits today: the things we want to happen with other teams in order to get the Oilers into the playoffs.

Of course, ideally we want the Oilers to win every game and be in complete control of their own destiny … that hopefully is a given, yes? But it’s not that realistic, so hoping for other teams to suffer strategic losses is par for the course.

So, here they are, my actual rules for scoreboard watching:

  1. Since we don’t compete with the East for playoff spots, any time there is an Eastern matchup with any other Western team, we want the Eastern team to win.  Always.  So gird your loins and start cheering for BUF, TOR, PHI, etc!
  2. At this point, the teams with a realistic chance of overtaking the Oilers are CGY, DAL, and WPG, with VAN having an outside chance and COL and ARI already pretty much out. So we want them, especially the first four, to lose. Always. (With CGY and VAN that should go without saying).  Especially important for the Oilers to win these games, which is why the SO loss to Vancouver on New Years Eve was … annoying.
  3. In any matchup between those five teams that are chasing the Oilers, we don’t really care much who wins, but we want the win to be in regulation, with no Bettman point awarded!
  4. With any other West-West matchup, we generally want the teams the Oilers are unlikely to be ahead of (SJS, LAK, ANA, MIN, CHI, STL) to win out over the teams the Oilers are likely to be with or ahead of (NSH plus the teams mentioned in point #2).  NSH losing decreases the likelihood that one of the teams that are behind can actually displace the Oilers out of a playoff spot. Again, obviously a regulation win is preferred.

So to summarize:

  • Oilers uber alles
  • East always over West (except Oilers)
  • CGY, DAL, WPG, VAN, COL, ARI to lose. Especially to the Oilers. If playing each other, no Bettman point.
  • High West vs Low West, we want higher to win, now including NSH among the “Low”. Again, preferably with no Bettman point.

Did I miss any other rule you think is critical? Please post in the comments section.

Otherwise, let’s git to watchin’ that scoreboard!

Beer League Hero, Edmonton Oilers, Fancy Stats, G Money, NHL

G-Money on Dealing Nugent-Hopkins

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***Yesterday we posted an article speaking to the disappointing seasons that Ryan Nugent-Hopkins and Jesse Puljujarvi were having and I asked the boys for their thoughts on what we should do with the Nuge. You can read that article HERE.

I did the same on Twitter with this poll and I’m not surprised with the results. It’s not like my followers are wrong 🙂

It’s funny, each time I’ve decided to post an article detailing how unimpressed I am with a specific player, they decide to go ahead in the following game and put up some points… Maybe I should do it more often.

Now, as I mentioned in the article yesterday, G-Money’s (@oilersnerdalert) excerpt was lifted from a longer reply to my question and now I’d like to share G-Money’s full reply with you. Bon Appetit! – BLH***

Q: What’s wrong with Ryan Nugent-Hopkins, and Should the Oilers Trade Him?

A: a. Nothing other than a run of bad luck, and b. God no!

On point a, one of my lenses for looking at a player is “WoodMoney“, the matchup-based quality of competition methodology that @Woodguy55 and I put together. Here’s a look at how much time Nuge is spending facing the various levels of competition, and how he is doing so far this year as compared to the other two main centres (I’ve included both Corsi and DangerFen for the Elite tier, but only CF% vs the others so as not to turn an intimidating table of numbers into an overwhelming one ):

Nuge

% TOI vs Elite – 41%
CF% –  45.9%
DFF%  – 44.9%
% TOI vs Middle – 39%
CF% – 53.9%
% TOI vs Gritensity – 20%
CF% – 59.7%

McDavid 

% TOI vs Elite – 32%
CF% – 53.4%
DFF% – 56.0%
% TOI vs Middle – 46%
CF% – 55.1%
% TOI vs Gritensity – 22%
CF% – 56.8%

Draisaitl 

% TOI vs Elite – 27%
CF% – 49.5%
DFF% – 48.0%
% TOI vs Middle – 49%
CF% – 50.0%
% TOI vs Gritensity – 24%
CF% – 55.0%

Conclusions

On point a:

1. McDavid is stupid good. He destroys everyone.

2. Nuge is being used by TMc as the shutdown power vs power centre this year. Not McDavid. Not Draisaitl. Nuge is the guy spending 41% of his time against the best players in the NHL. That’s creating a ton of clear air for McDavid and Draisaitl. If you’re comparing things like points, you better take that into account. Nuge’s points are being sacrificed to give the other two a chance to score more.

3. When Nuge is up against those great players, it’s true he’s struggling to keep his head above water.  Moreso than in years past.  And he’s not the only one. My suggestion: give him Eberle and Pouliot on an ongoing basis. Let those two (who are both struggling) right their ships. Nuge’s ship will get fixed right along with them.

4. When Nuge is not against those great players, against pretty much every one else, he runs roughshod.  The Nuge is Yuuuuuuuge!

5. So there is nothing wrong with Nuge, except:

On point b:

Nuge is shooting at 5.1% this season. He has a career average of 11.2% prior to this season. So he’s shooting at less than half of his career average.

He’ll find his groove again, guaranteed.

Every player’s sh% varies wildly above and below their long-term average. And it’s more or less random (if a player could control it, they’d always shoot above their average, which would raise their average, which means they’d shoot at random above and below that average, which…)

That’s just how it goes. Sh% controls you, you don’t control sh%.

Now as for trading Nuge … well, my thought process is always that whether it makes sense to trade a player is based entirely on the return.  Anyone is on the block if what you’re getting back is good enough.

But you know what would be stupid though? Trading a player at what would in effect be the maximum possible discount because of one of those sh% lows.

***With G-Money’s balanced analysis and down-to-Earth reasoning, it’s hard, for me at least, to want to move Nuge ASAP because I’m curious as hell as to what the Oilers might look like if they have all three of McDavid, Draisaitl, and RNH humming along on the offense.

What do you think? Let us know in the comments below!***

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