Lane Hutson Burgeoning Star Watch

WhiskeyYerTheDevils

yer leadin me astray
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Apr 27, 2005
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Hutson caving in the two best players in the league at 20 years old
He only saw 2 mins vs McDavid. He literally played less against McDavid than any Oiler lol.

His most common forward opponents were Henrique, Podkolzin, Perry, Brown, and Skinner.

Habs played great, but let's not pretend Hutson was out there dominating McDavid all night.
 

NikolaTesla

Registered User
Aug 2, 2009
357
362
Just want to clarify, these same stats that you have spent months calling irrelevant are now being used by you, the second they say something good about hutson?

Shameless
But are xGF% really relevant considering Hutson played only 2 mins against McDavid yet has a xGF% of 80. Does that mean it doesn't take into account the strenght of competition? If thats the case then thats a meaningless stats.

LOL. Ya'll talking about the Oilers game? Quite possibly the worst hockey i've seen all year, by both teams.
You haven't watched enough habs.
 

Baksfamous112

Registered User
Jul 21, 2016
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Just want to clarify, these same stats that you have spent months calling irrelevant are now being used by you, the second they say something good about hutson?

Shameless
Kinda weird how when the whole team is playing much better that the guy who’s been quietly good gets good advanced stats?

Feels like it goes hand in hand with how the whole team is playing, isn’t it?
 

dgibb10

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Feb 29, 2024
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Kinda weird how when the whole team is playing much better that the guy who’s been quietly good gets good advanced stats?

Feels like it goes hand in hand with how the whole team is playing, isn’t it?
You have this view of the "team" as some magical entity holding players back rather than a collection of individual players.

Yes, when players play better, such as hutson having an excellent game, the team will do better.

You could apply that logic you just did for hutson to every single other player on the habs, blaming their past failures on the team around them and justifying them as a good player, into circular logic that tries to prop up players on bad teams and bring down players on good teams.

You could go down every single player from the 1st line to the 4th line and from the 1st pairing to the 3rd pairing blaming "the team", and saying the player on the shit team is better than the player on the good team.
 

dgibb10

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Feb 29, 2024
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But are xGF% really relevant considering Hutson played only 2 mins against McDavid yet has a xGF% of 80. Does that mean it doesn't take into account the strenght of competition? If thats the case then thats a meaningless stats.


You haven't watched enough habs.
What stats do you consider relevant and "not meaningless" if they need to be weighed for QoC?

Goals and Assists definitely don't weigh for QoC. Are they meaningless?
 

HuGo Sham

MR. CLEAN-up ©Runner77
Apr 7, 2010
28,651
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Guhle is such a f***ing stud
..IF he can stay healthy
and Montembeault can somehow find consistency habs should hover around 2nd WC in a close and inconsistent Eastern conference..

ottawa, detroit, buffalo, Pittsburgh, boston, philly and Columbus haven't shown very much either
 

dgibb10

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Feb 29, 2024
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..if he can stay healthy
and Montembeault can somehow find consistency habs should hoover around 2nd WC in a close and inconsistent Eastern conference
Unlikely.

They are still dead last in the conference, with horrible underlyings.
 

Raistlin

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Aug 25, 2006
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A bit off topic but I found Slafkovsky looked physically unbeatable last night.
Im surprised they let Desharnais go. He wouldve been their only guy that hits with Kane and Nurse out. Podkolzin hits but hes not physically intimidating at all.
 

NikolaTesla

Registered User
Aug 2, 2009
357
362
What stats do you consider relevant and "not meaningless" if they need to be weighed for QoC?

Goals and Assists definitely don't weigh for QoC. Are they meaningless?
Theyre not meaningless but they're not the ultimate truth either. Just like xGF%, whom some consider like the be it end all of all statistics (You're one of them BTW). In the Bedard vs Hughes poll thread someone acted like bedard's rookie 44% vs Hughes 55% was the undeniable proof that Hughes had a better rookie season. Yet that stats doesnt even take account qoc so points and assists are basically just as relevant as that "advanced" stats.
 

NikolaTesla

Registered User
Aug 2, 2009
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You have this view of the "team" as some magical entity holding players back rather than a collection of individual players.

Yes, when players play better, such as hutson having an excellent game, the team will do better.

You could apply that logic you just did for hutson to every single other player on the habs, blaming their past failures on the team around them and justifying them as a good player, into circular logic that tries to prop up players on bad teams and bring down players on good teams.

You could go down every single player from the 1st line to the 4th line and from the 1st pairing to the 3rd pairing blaming "the team", and saying the player on the shit team is better than the player on the good team.
The difference between a win and a loss makes basically every single player xGF% go up 20%. You can't say that suddenly every single players got so much better.

Yes each individual performances helps a team, but it goes the other way around. A great team will make everyone's individual performance much better. You cannot deny that.
 
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dgibb10

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Feb 29, 2024
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The difference between a win and a loss makes basically every single player xGF% go up 20%. You can't say that suddenly every single players got so much better.

Yes each individual performances helps a team, but it goes the other way around. A great team will make everyone's individual performance much better. You cannot deny that.
Got better vs had a better game is a different thing.

If your players play well you win, not the other way around.

There is an impact of playing on a good team, however it is VASTLY overstated. (as is QoC metrics and zone starts, outside of extreme examples like Guhle's ridiculously hard usage or Xhekaj's ridiculously easy usage).

Here are some players on similarly shit teams (Anaheim, Chicago, MTL, CBJ, SJS). Do we apply the same logic we give to hutson here to henry thrun?
Screenshot 2024-11-19 at 6.00.03 PM.png


For example, before last night hutson had a 40% xGoals share, and Luke had a 53% xGoals share.

People in here were justifying that 13% difference (and more) as because of the team. If I applied that to every member of the habs, you'd go up and down the roster and come to the conclusion that basically every player on the habs was better than their corresponding devils player.

Which clearly doesn't track. As the devils are the better team. BECAUSE they have the better players.

Fans of bad teams pick and choose which players to excuse using the team excuse.
 

dgibb10

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Feb 29, 2024
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Theyre not meaningless but they're not the ultimate truth either. Just like xGF%, whom some consider like the be it end all of all statistics (You're one of them BTW). In the Bedard vs Hughes poll thread someone acted like bedard's rookie 44% vs Hughes 55% was the undeniable proof that Hughes had a better rookie season. Yet that stats doesnt even take account qoc so points and assists are basically just as relevant as that "advanced" stats.
Massive gaps cannot be justified using such excuses, unless there is an extreme outlier in usage,

Jack Hughes and his linemates problem in his 2nd year was finishing, not chance generation. It depends on what you're asking. Jack's 2nd season (which is what is being referred to) was very promising in chance generation and play driving. He just couldn't bury a chance and neither could his linemates. So, when the shooting normalized, Jack's production skyrocketed in a way that was predictable to anyone paying attention, but shocking to anyone not.

Also, I think you overestimate the impact of QoC on players who aren't extreme outliers, and only when it suits the narrative.

Eg, Arber Xhekaj gets arguably the easiest usage in hockey. No MTL fans seems to acknowledge that.

Eg, the matheson-guhle pairing gets utterly ridiculous usage (only the Seider pairing has it worse), but nobody gives matheson credit for that when comparing him to Hutson.

Hutson's normal, 2nd pairing QoC is not a meaningful impact.

Eg, the difference between Jack and Bedard both playing normal minutes isn't particularly relevant.
 

ponder

Registered User
Jul 11, 2007
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But are xGF% really relevant considering Hutson played only 2 mins against McDavid yet has a xGF% of 80. Does that mean it doesn't take into account the strenght of competition? If thats the case then thats a meaningless stats.
It does not. It's really just:
  • The official NHL publishes an event log, which includes stats about every shot, that has info like shot type (wrist shot, slap shot, snap shot, tip, etc.) and where on the ice the shot came from
    • The data looks like this (this is an event describing a shot, and the most meaningful bits are the shot type (details.shotType) and the location (details.xCoord and details.yCoord):
JSON:
{
    "eventId": 104,
    "periodDescriptor":
    {
        "number": 1,
        "periodType": "REG",
        "maxRegulationPeriods": 3
    },
    "timeInPeriod": "00:16",
    "timeRemaining": "19:44",
    "situationCode": "1551",
    "homeTeamDefendingSide": "right",
    "typeCode": 506,
    "typeDescKey": "shot-on-goal",
    "sortOrder": 13,
    "details":
    {
        "xCoord": 6,
        "yCoord": 16,
        "zoneCode": "N",
        "shotType": "slap",
        "shootingPlayerId": 8476967,
        "goalieInNetId": 8478470,
        "eventOwnerTeamId": 22,
        "awaySOG": 1,
        "homeSOG": 0
    }
}
  • A model is then trained with this, and a few other factors (for example was there another shot shortly before, indicating a rebound), so that you can then feed these parameters into the model, and it'll spit out a probability of that shot being a goal
    • The trained model will say things like "a wrist shot from the top of the right circle, 4 seconds after the previous shot, has a 3.5% chance of being a goal"
  • Then they simply sum up all those probabilities when you are on the ice, for shots by your team and the opposition, and you get expected goals for and against
  • And finally expected goals for/against when you were on the ice can be turned into an xGF%
    • e.g. maybe the goal probabilities from all shots sum to 1.2 expected goals for, 0.5 expected goals against when you were on the ice
    • 1.2 / (1.2 + 0.5) = 70.59 xGF%
Of course, this has massive problems when trying to use it as the absolute stat to evaluate player quality, like:
  • Quality of teammates
  • Quality of opposition
  • Are you getting put out for mostly o-zone work (o-zone faceoffs, or hopping over the boards on the fly when your team has possession) or d-zone work (the opposite)?
  • Simply knowing "slap shot from the right dot" isn't actually very good at predicting the goal probability of a shot
    • None of this sort of info is available, and this data would be crucial for accurately estimating the probability of a shot being a goal:
      • Was the goalie moving, or set?
      • Was the goalie screened?
      • Was it a one-timer? And if so, where did the pass come from? (one-timer with a pass from behind the net to the high slot is WAY more dangerous than a player skating the puck in and taking a shot from the same spot)
      • Did the player have the time/space to get off a quality shot, hard and with great placement, or were they heavily pressured and could only get off a weak shot with bad placement?
      • etc.
    • It's a "garbage in garbage out" situation, the NHL event data that basically all advanced stats are based on is simply missing a TONNE of crucial information
  • Finally, missed and blocked shots are important too, and xGF% only looks at actual shots on net. Hitting a post is way closer to being a goal that an unscreened point shot with the goalie set, but every expected goals model I'm aware of ignores all missed/blocked shots, including close misses like posts
Basically, it's a stat to take with a massive, massive grain of salt. It's very common to see players that are clearly not very good (coaches don't play them much, little value in trades/signings, don't look good on the eye test) who have great xGF%, because they're getting really soft/sheltered minutes on a strong team. Or, also very common to see players that are clearly very good (coaches play them heavily, lots of trade/signing value, look great on the eye test) have terrible xGF%, because they're getting really tough minutes on a bad team. And that's over the course of entire seasons - over the course of a single game, it says even less about the player.

FWIW, I've got an MSc in a stats heavy field, and used to be a Data Scientist (am now a Software Engineer), so I've got pretty strong experience in stats and data analysis, and I personally put minimal value in xGF%. It's one statistic about a player, but to make sense of it you need to fully understand the (massive) weaknesses it has, and fully understand the context around the player's team and role within their team. Acting like it's a single number that meaningfully describes a player's value is IMO crazy - even over the course of a full season, and especially so for a single game.
 
Last edited:

dgibb10

Registered User
Feb 29, 2024
3,544
3,067
It does not. It's really just:
  • The official NHL stats, for every shot, have extra info like shot type (wrist shot, slap shot, snap shot, tip, etc.) and where on the ice the shot came from
    • The data looks like this:
JSON:
{
    "eventId": 104,
    "periodDescriptor":
    {
        "number": 1,
        "periodType": "REG",
        "maxRegulationPeriods": 3
    },
    "timeInPeriod": "00:16",
    "timeRemaining": "19:44",
    "situationCode": "1551",
    "homeTeamDefendingSide": "right",
    "typeCode": 506,
    "typeDescKey": "shot-on-goal",
    "sortOrder": 13,
    "details":
    {
        "xCoord": 6,
        "yCoord": 16,
        "zoneCode": "N",
        "shotType": "slap",
        "shootingPlayerId": 8476967,
        "goalieInNetId": 8478470,
        "eventOwnerTeamId": 22,
        "awaySOG": 1,
        "homeSOG": 0
    }
}
  • A model is then trained with this, and a few other factors (for example was there another shot shortly before, indicating a rebound), so that you can then feed these parameters into the model, and it'll spit out a probability of that shot being a goal
    • e.g. "a wrist shot from the top of the right circle, 4 seconds after the previous shot, has a 3.5% chance of being a goal"
  • Then they simply sum up all those probabilities when you are on the ice, and you get expected goals for an against
  • And finally expected goals for/against when you were on the ice can be turned into an xGF%
    • e.g. maybe the goal probabilities from all shots sum to 1.2 expected goals for, 0.5 expected goals against when you were on the ice
    • 1.2 / (1.2 + 0.5) = 70.59 xGF%
Of course, this has massive problems when trying to use it as the absolute stat to evaluate player quality, like:
  • Quality of teammates
  • Quality of opposition
  • Are you getting put out for mostly o-zone work (o-zone faceoffs, or hopping over the boards on the fly when your team has possession) or d-zone work (the opposite)?
  • Simply knowing "slap shot from the right dot" isn't actually very good at predicting the danger of a shot. None of this sort of info is available:
    • Was the goalie moving, or set?
    • Was the goalie screened?
    • Did the player have the time/space to get off a quality shot, hard and with great placement, or were they heavily pressured and could only get off a weak shot with bad placement?
Basically, it's a stat to take with a massive, massive grain of salt. It's very common to see players that are clearly not very good (coaches don't play them much, little value in trades/signings, don't look good on the eye test) who have great xGF%, because they're getting really soft/sheltered minutes on a strong team. Or, also very common to see players that care clearly very good (coaches play them heavily, lots of trade/signing value, look great on the eye test) have have terrible xGF%, because they're getting really tough minutes on a bad team. And that's over the course of entire seasons - over the course of a single game, it says even less about the player.

FWIW, I've got an MSc in a stats heavy field, and used to be a Data Scientist (am now a Software Engineer), and I personally put minimal value in xGF%. It's one data point about a player, but to make sense of it you need to fully understand the (massive) weaknesses it has as a stat, and fully understand the context around the player's team and role within their team.
  • Quality of teammates
  • Quality of opposition
  • Are you getting put out for mostly o-zone work (o-zone faceoffs, or hopping over the boards on the fly when your team has possession) or d-zone work (the opposite)?
All of this information can also be found and used (although QoC and zone starts are vastly overrated in terms of impact outside of the outliers).

Eg, you can see on MTL, the Guhle pairing plays ridiculous (hard) minutes, the Xhekaj pairing plays ridiculous (easy) minutes.

  • Simply knowing "slap shot from the right dot" isn't actually very good at predicting the danger of a shot. None of this sort of info is available:
    • Was the goalie moving, or set?
    • Was the goalie screened?
    • Did the player have the time/space to get off a quality shot, hard and with great placement, or were they heavily pressured and could only get off a weak shot with bad placement?
Better models use this information to varying extents, but yes, it is a developing stat.

Also, players who consistently generate chances in ways that models do not account for will outperform those models over a large sample size (which can be easily recognized if you again look). It's why most WAR models use actual goals for offense, and expected goals for defense.

If you are expecting it to be a perfect stat, you're crazy.

Ignoring it's value is also crazy.
 

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