Such a formulaic response.
Here's the funny thing, I already stated that I thought Gardiner has the skills to be a #3 but is a 4/5 right now.
And some of us are saying that Gardiner is a top-4 defenseman
right now, and have offered quantifiable proof that doesn't rely on 'LOL stats suck as much as Gardiner', or 'look at his plus-minus and ignore, momentarily, my view on statistics; Gardiner sux'.
I acknowledged his abilities, my point was that when you try and take into account, and breakdown every minute spec of the game, project over 60 etc...there can be arguments easily made on both sides.
Then make some arguments.
It is how stats are interpreted. There is not only one way to interpret every stat, only the closed minded would believe so.
I agree, to an extent.
There's a proper way to interpret a particular statistic in a particular situation, but there are many statistics, and copious amounts of situations.
What you don't do, is the analysis on why that particular players stats may show what they do.
Sure I do, I just don't think they're nearly as important as you believe they are. A guy could skate around on his hands, and I'd call him a good defenseman if he prevented/generated goals. I think the statistics presented inherently account for variables you believe should be measured separately. If you don't believe they're considered, then how important are they if they don't help prevent/generate goals, and subsequently wins? *(shoutout to Nithoniniel for this point; I edited my post after reading your post)*
Your analysis stops at what you see on paper and becomes the gospel. From reading your posts over the last while, you always revert to advanced stats, but do not seem to look at the context of how the game is played, coached, momentum shifts etc and even some luck that can affect a players stats.
I absolutely do look at how the game is played (I watch a
lot of hockey), I just don't think the factors that you consider important are, in the grand scheme, all that important. I think we can all agree that wins are
the primary goal.
I do look at OnIceSV%, OnIceSh%, Sh%, PDO, CPDO, and FPDO, so I certainly take luck into account. Gardiner was actually (very) unlucky this season, so I don't believe luck had the effect you desired it to have.
It is simply read these stats, they are designed by "doctorate level mathematicians", even they would tell you it is not absolute the way you make them out to be.
Statistics certainly are not absolute, and they have a long way to go. They are better than the eye-test of HFBoard posters who insist that hits, blocked shots and face punching are the 'go-to stats' when judging defensive performance, though.
Of course Hockey people, ex-players, Babcock included, who may look at stats you deem garbage are just loudmouths looking for ratings.
I deem plus-minus garbage because it is garbage. I think it's used because it's simple to understand (although more advanced metrics really aren't very difficult to comprehend either), and attracts more discussion.
In short, plus/minus is highly variable, there are countless factors that influence it, and more of them are outside of an individual player's control than not.
Two teammates doing everything absolutely identically to one another can see huge variance - well over 100% - in their plus/minus based on factors outside of their control like ice time, their goalie's performance, and the opposing goalie's performance. You may be wondering if players such as those in the examples above exist, and the answer is absolutely, yes. Dustin Byfuglien's goalies posted an .888 on-ice save percentage at even strength this season, Byfuglien's on-ice shooting percentage is 7.7%, and Byfuglien was playing just under 20 minutes/60 at even strength until his position change. These kinds of percentages are totally normal.
In fact, the crazy thing is, the variance can actually be much worse than this. We only discussed three factors and I didn't even pick percentages at the extreme ends of the spectrum. When the Wild's Erik Haula was on the ice at 5-on-5 in his 44 games this season, his goalies saved 96.8% of shots they've faced. The same figure for Zenon Konopka, Haula's teammate? 89.2%. That's a spread of 7.2%, or nearly double the example scenario above. And it's not just the Wild. In Edmonton, Ryan Jones' 5-on-5 on-ice SV% was 95.0% this past season, while Nail Yakupov's was a lowly 88.2% (spread of 6.8%). In Pittsburgh, Chuck Kobasew's on-ice SV% was 96.1%, while Paul Martin's was 89.0% (spread of 7.1%).
http://www.arcticicehockey.com/2014/6/5/5602668/why-plus-minus-is-the-worst-statistic-in-hockey
Yes, hockey is simply a mathematical game and if we all got on board, we could play moneyball and win.
Statistics are not a guarantee, but they can certainly help. That's why so many of the Leafs' staff use them to assist in their daily processes.
Toronto's hiring of Steve Briere, the Leafs new goalie coach, represents an ongoing progressive shift within the organization, and the hockey world at large.
A longtime goalie coach through his own business, with stints in the USHL, NAHL, NCAA and AHL, Briere joins the Leafs without the notoriety the organization is accustomed to hiring as its goalie coaches, including Rick St. Croix and Francois Allaire -- two Stanley Cup winning goalie coaches.
But Briere isn't concerned with the past. Instead, he's looking ahead.
"I'd definitely consider myself a progressive goalie coach," Briere said in a phone interview on Wednesday. "There's always people trying to either copy your business or come up with something better to outdo your business so goalie coaching is very similar, you're always trying to be on the cutting edge."
Now, more than ever, there's opportunity to learn and advance the craft, according to Briere.
"Because there’s so many different goaltenders from so many different countries, I’ve coached goaltenders from every single country in the world now, people learn different things and understanding things different ways," he said.
"Part of being innovative isn’t always because you need to reinvent goaltending, I think the fundamentals are the base for everything, but the new innovations are just ways of being able to allow the goaltenders to understand those fundamentals in a different way."
http://www.pensionplanpuppets.com/2015/7/24/9027953/new-leafs-goalie-coach-steve-briere-part-of-organizational-shift
Moving forward, Belfry believes the things he's teaching will become the norm for NHL teams and are already evident in today's top franchises.
One of the areas that are important in order to succeed in the NHL is in how teams enter the offensive zone. Belfry believes creating dynamic zone entries are more effective than the dump and chase style that some teams still play.
"Any time you put the puck in a 50/50 or you give the puck to the other team, the players in today’s NHL are so skilled with the puck that it’s very difficult to get the puck back in a good spot," Belfry said. "If you have the puck already on your stick, it’s much more advantageous, and I’m not going to say it’s easier, but it’s definitely better to create a play or to improve your position than it is to go get a puck back and start again."
By entering the offensive zone with the puck, teams are able to force the other teams into a reaction mode, according to Belfry.
The problem with dump and chase, he argues, is that the coordinated recovery of the defenders is so strong that it's hard to pin opposing players in and even if you can create a turnover, it's difficult to pinpoint where that turnover will occur.
By dumping, the forechecking team is forced to react.
http://www.pensionplanpuppets.com/2015/5/25/8653245/leafs-skills-development-coach-darryl-belfry-part-of-new-philosophy
You use advanced stats like they are forensic DNA evidence of how things work on the ice and they are irrefutable through your analysis.
SportLogIQ and HockeyTech are currently positioning themselves to track every event that occurs in any given hockey game using motion tracking software. Obviously that's not going to account for intangibles, but I maintain that the most skilled/productive teams will be better than the teams with the best leadership (that's my opinion; feel free to refute it).
Also,
in this case, yeah, they are pretty irrefutable. If the argument is that Gardiner is good defensively, then the only way to disprove that would be to argue that being able to prevents goals against, shots against, and scoring chances against are less important than being able to hit, punch or block a shot.
You can see that coaches obviously believe in match-ups, but you will still insist QOC is really irrelevant.
It's not irrelevant
in theory, or in short samples, but
in reality the difference between two players and the opposition they face is negligible (which I've already shown) over a moderately large sample.
The game is played a certain way and I have seen the way it is played change numerous times. You don't think that helps and hurts certain players stats? Like I said, if stats were the be all end all you make them out to be, we would have guys radioing down from the press box to the coach "ok Bab's we need ______ out in this situation, send in the play" like offensive co-coordinators in Football.
Analytics
are incorporated in-game.
Bolded...that is hilarious coming from you. A guy who claims to be always correct using advanced stats and that only how you interpret them is correct.
If someone shows me, with evidence, that I'm misinterpreting a statistic, then I'm happy to acknowledge my mistake. When I first started reading and implementing these statistics in my analysis, I was
constantly wrong (Corsi, for example, was designed to measure goalie workload, which I didn't know). I'd rather someone proved that I was improperly using a certain statistic in a certain situation, than continue to misuse the statistic.
I'm not always right, and I'm always trying to adapt to the changing environment of statistics. I've started to rely less on Corsi as tracking numbers have become more available. I understand that shot metrics aren't well correlated to future (YoY) winning percentage (but they are well correlated to current, in-season winning), but rather that there's a correlation between them and future
goal percentages, which
does have a strong correlation with future winning percentage.
http://hockeyanalytics.com/2008/01/the-ten-laws-of-hockey-analytics/
These are ranked with respect to their correlation to Win%. Everything listed here is important to a description of how a team is doing in the regular season and virtually every stat listed is a requirement for a team to be successful. The top seven statistics are all measures of goals for and/or against during the season. Obviously these would have the largest impact on wins and losses. Next come the shot metrics, all of which are reflective of factors that make a significant difference on the ice. Lastly in the middle there - you'll notice 5v5 PDO - which is just the sum of a team's 5v5 SH% and SV%. This is yet another meaningful and important way of tracking a team's success in the regular season.
So we have a collection of the most relevant team metrics in hockey for a single year - but they are NOT all reliable in the long run over multiple years. How can we tell this? Look at the Reliability column right beside the statistic. Those values represent year over year R^2 values for each of the stats over the 6 years of data available. The higher the numbers the more repeatable a given statistic is at the team level year to year.
Look carefully at the 5v5 Close metrics. 5v5 Close Corsi For % is quite highly repeatable - it's the most reliable metric on this list year over year. It is also highly informative of a team's likelihood of winning games. If you want a stat that tells you if your team is doing well, that is likely to mean anything in the future, this is probably the best statistic you can make use of.
http://www.pensionplanpuppets.com/2013/7/10/4508094/what-statistics-are-meaningful-in-a-given-season-corsi-fenwick-PDO-hits-fights-blocked-shots
I'm not abashed when I'm wrong; I learn from my mistakes.
You now claim that even Babcock is open to being proven wrong about players because advanced stats, and probably the way you read them, tell him otherwise.
Yes, because he's an intelligent human being.
Maybe you should open your mind up to the fact that your stats do not take into account heart, drive, desire, will, what a big hit or three blocked shots on a penalty kill does for momentum in a game.
Neither do your eyes, since you have no idea the exact impact said 'big hit' has on 'momentum'. Also, do you have any proof of the existence of 'momentum', or are you just going to argue that it's axiomatic; that it's present because you've always assumed it to be?
Game-to-game, carry-over momentum is a myth.
A hot hand may be hokum: Cornell researchers have examined the concept of “winning momentum” with varsity college hockey teams, and they conclude that momentum advantages don’t exist, says a new study in the journal Economics Letters.
“Whether it’s sports commentators or stock analysts who are talking, momentum is routinely assumed to be important on a day-to-day basis,” said Kevin M. Kniffin, a postdoctoral research associate at Cornell’s Dyson School of Applied Economics and Management. “In our evidence, we see that ‘momentum’ is really just illusory.”
Kniffin and Vince Mihalek ’13, a four-year veteran of Cornell’s men’s ice hockey team, examined 916 games over a six-year period from the Western Collegiate Hockey Association (NCAA, Division 1). Teams in that league regularly play two-game weekend series, which the researchers explain “presents a uniquely ripe environment for momentum to potentially occur.”
http://news.cornell.edu/stories/2014/02/game-winning-momentum-illusion-delusion
So is in-game momentum, to an extent:
If momentum was playing a large role in future goal scoring, we’d expect the shades of green to get darker for the lower rows in each tied game scenario.
For example, the home team scores more often after sequence AH than sequence HA (54.3%, versus 52.1%), suggesting a slight increase in goal likelihood for the team that tied the game at 1-1.
However, home teams appear to score more often in 2-2 and 3-3 games when they don’t have any supposed momentum, as opposed to when they do (that’s comparing sequence HHAA versus AAHH, and sequence HHHAAA versus AAAHHH).
The home goal rate after sequence HHAA is 54.4%, for example, while the rate after sequence AAHH is 52.7%. If home teams have momentum after scoring two goals to tie the game at 2-2, they certainly don’t play like it.
Note: The table omits the large number of sequences in 3-3 games where the previous two goals were not scored by the same team; these proportions paint a similar picture to the ones above.
Final Notes
On the whole, there is little to no evidence that momentum exists within hockey, as judged by whether or not previous goal sequences imply future outcomes.
http://statsbylopez.com/2014/04/29/momentum-and-hockey/
With that said, some in-game momentum does exist on an individual level (in basketball and baseball, so likely hockey as well), and in terms of penalties taken/drawn:
That said, the “hot hand bias”—the tendency to impulsively infer a player is hot, based on limited data—is still alive and well. The behavioral researchers were correct to identify this as an important cognitive error. But this does not mean there is no hot hand at all. A player who hits a few tough shots in a row may indeed be the best option for the team’s next shot.
Aside from enhancing our understanding of basketball, why is this new hot hand research important? It indicates the previous work was an interesting case study of scholarly overreach. Saying “there is no hot hand”—that virtually all players and fans were wrong—was much more attention-grabbing, and thus, perhaps, appealing, than simply saying there is a more subtle hot hand bias.
It is poignant that behavioral economics and psychology researchers seem guilty of the overreach here because a) they should be especially aware of the bias to exaggerate and believe what we want, rather than what is supported by the data, and b) those researchers should have been relatively confident in the existence of the hot hand, and thus skeptical of the initial research interpretation, since becoming "hot" is likely largely a psychological phenomenon.
http://www.psmag.com/books-and-culture/stop-denying-hot-hand-basketball-streak-75519
Jason Abrevaya inspired my table above in his analysis of penalty outcomes in hockey. Abrevaya found that previous penalty sequences are highly correlated with future penalty calls (i.e, AAA implies a future penalty on the home team, while HHH implies the next infraction on the away team). This paper requires a subscription.
Funny how the players get up and pat a guy on the back and bang their sticks against the boards etc for those kind of plays, but not because Jake lugs the puck up the ice. Where is your stat that shows how being softer in the D-zone causes the opponent to spend less energy to control the puck?
It's an emotional game, it is not played strictly on paper.
SportLogIQ tracks an 'energy' variable (or the exertion of energy by a particular individual) using specific variables.
Gardiner may not tire the opposition out with exceptional physicality, but he's also significantly more involved in the play than players who do, like Phaneuf and Polak, so the energy the opposition gains from not taking a beating is counteracted by the fact that they have to work harder to get/maintain possession.
