Post-Game Talk: Jets over the Sens!

HannuJ

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Nov 20, 2011
8,108
3,670
Toronno
I know there is a big following of the Jets in East & West Perth in Southern Ontario, because I have extended family there. They say the Jets are very popular; most don't cheer for the Leafs or Sens.

My Uncle owned a feed company and had life long season tickets, rarely went, was for clients. I don't think he was necessarily a Leaf fan - he was a fan of his business, My aunt, his children and grandchildren. God bless him.
when the jets went to the semi-finals, it resulted in a HUGE jets following out here. the merch started appearing. i'd suggest that, after the leafs and maybe, maybe habs, it's the top 3 in hockey merch here.
i don't see it often (i mean, with the pandemic, i see nothign often) but it's around
 
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Gil Fisher

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Mar 18, 2012
8,031
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Winnipeg
This won't remove Ottawa, but this shows performance adjusted somewhat by who you played against*, Jets:

5v5 Goals +0.15 per hour
13th in league
5th in division

5v5 xGoals -0.31 per hour
26th in league
7th in division!

5v5 Corsi -0.66 per hour
15th in league
4th in division
I have a question about our GF. Since 2017 (3+ seasons), we have outperfomed our 5v5 xGF by 80 goals. (GA has been approximately equal to xGA, as we would expect as sample size increases.)

Is this still random or is it attributable to something about the way we generate offense relative to what xG values?
 
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Whileee

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May 29, 2010
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I have a question about our GF. Since 2017 (3+ seasons), we have outperfomed our 5v5 xGF by 80 goals. (GA has been approximately equal to xGA, as we would expect as sample size increases.)

Is this still random or is it attributable to something about the way we generate offense relative to what xG values?
I think it's a mix of style and scoring talent. I posted an analysis a while back showing substantial variability among teams in terms of the ratio of GF to xGF. I doubt that the 40% variation is purely random, mainly because the same teams tend to overperform (TB, WSH, WPG) and underperform (CAR, MTL, DAL). I've commented in the past that I think it's more than just individual shooting talent, and you can see this stylistically. The Jets top lines, especially with Scheifele, really tend to avoid taking low percentage shots, and will circle and cycle until they find a seam. In contrast, Carolina and Montreal have typically focused on high shot attempts from a range of angles.

This raises another pet peeve I have about current xG models - they include only shot attempts. They don't count any plays that would be very high danger if they connected, but a shot wasn't attempted. So, for example, a weak shot from far out has an xG value, but a 2-on-1 break where a pass is deflected or a pass to the slot that is just missed has 0 expected goal value. That's analogous to counting only shots that hit the net as xG, and ignoring shot attempts that are blocked or miss the net. I'd bet that many teams chart scoring chances that don't result in a shot attempt per se as part of their xG metrics, which could explain why teams say they like their xG models better. If you think about it, a team that tries to create chances with dangerous passing plays instead of low percentage shots is more likely to outperform their xG metrics in terms of goals.
 

Whileee

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May 29, 2010
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In reference to above...

upload_2021-2-12_18-14-29.png
 
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garret9

AKA#VitoCorrelationi
Mar 31, 2012
21,740
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Vancouver
www.hockey-graphs.com
I have a question about our GF. Since 2017 (3+ seasons), we have outperfomed our 5v5 xGF by 80 goals. (GA has been approximately equal to xGA, as we would expect as sample size increases.)

Is this still random or is it attributable to something about the way we generate offense relative to what xG values?

xG doesn't account for finishing talent.

Public models also do not account for some things that impact shot quality that isn't publically available. The things public models do account for are the driving factors of shot quality but not the only factor.

Public models also aren't perfect in their data.

(Also, minor but I am someone who believes that luck impacts psychology which then impacts performance.)
 
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Whileee

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May 29, 2010
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xG doesn't account for finishing talent.

Public models also do not account for some things that impact shot quality that isn't publically available. The things public models do account for are the driving factors of shot quality but not the only factor.

Public models also aren't perfect in their data.

(Also, minor but I am someone who believes that luck impacts psychology which then impacts performance.)
Are you aware of models, public or proprietary, that are incorporating xG types of metrics that include events that don't result in shot attempts?
 
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truck

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Jun 27, 2012
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In reference to above...

View attachment 395671
Finishing talent plays a big role, and I firmly believe the Jets have had one of the best top 6 forward groups in the NHL in recent years.

I will say though... If the Jets weren't out-performing their xGoals for, they'd be Detroit or worse.
 

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Krauser

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Oct 3, 2017
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Are you aware of models, public or proprietary, that are incorporating xG types of metrics that include events that don't result in shot attempts?

There’s a similar concept in soccer called non-shot xG (non-shot expected goals).

The models I’ve seen for it are pretty simple, based on the location where the ball is possessed. Advancing the ball to a more dangerous location (further up the pitch and closer to the goal, basically) from where you started earns NSxG, even if there is no immediate or subsequent shot attempt on that possession. The concept is similar to EPA (expected points added) in NFL football, which is based almost entirely on field position, down and distance and time remaining.

Here are a couple of overviews of NSxG in soccer:
The Power of Goals.: Non-Shot xG Models
The Next Level of xG: Expected Possession Goals — American Soccer Analysis

Applying the NSxG approach to hockey would reward offensive zone time, not just shot attempts, which would tend to even out some of the differences in attacking styles you suspect underlie the team-wide trends in G/xG across the last few seasons in the NHL. A classic Scheifele line shift that results in 30+ seconds of possession often in dangerous areas but in the end no good shot attempts (after the last incisive pass bounces over a stick in the slot, or whatever) would score highly by this metric.

But even that wouldn’t account entirely for more or less dangerous pass attempts or other offensive moves, if they weren’t completed and didn’t result in possession in a more dangerous area. A 2-on-1 that results in a shot into the pads would grade the same as one where a pass attempt from that same spot just misses the stick of its targeted teammate, who had an open net if he’d been able to reach the pass.

And a purely location-based NSxG model wouldn’t account for the value in hockey (which IMO is significant) of cycling the puck from one area of the offensive zone to another location that’s “only” equally (or maybe even less) dangerous, but where the quick switch in possession from side to side, or high/low or low/high, opens up a shooting angle and space to shoot. For instance Stastny’s pass on the PP last game from the front of the net to Wheeler on the side would probably lose NSxG (because Wheeler was further from the goal), even though that quick switch in play created a much higher danger scoring chance than if Stastny had shot it himself.

The positioning of the skaters and especially the goalie is so dynamic, and the details of their movements (not just where they are, but which direction they’re moving, and how fast) are so important to the actual danger of each shot or possession that it’s hard to believe a NSxG model will give an full account of the value of possession in hockey until those factors can be included.
 
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Whileee

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May 29, 2010
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There’s a similar concept in soccer called non-shot xG (non-shot expected goals).

The models I’ve seen for it are pretty simple, based on the location where the ball is possessed. Advancing the ball to a more dangerous location (further up the pitch and closer to the goal, basically) from where you started earns NSxG, even if there is no immediate or subsequent shot attempt on that possession. The concept is similar to EPA (expected points added) in NFL football, which is based almost entirely on field position, down and distance and time remaining.

Here are a couple of overviews of NSxG in soccer:
The Power of Goals.: Non-Shot xG Models
The Next Level of xG: Expected Possession Goals — American Soccer Analysis

Applying the NSxG approach to hockey would reward offensive zone time, not just shot attempts, which would tend to even out some of the differences in attacking styles you suspect underlie the team-wide trends in G/xG across the last few seasons in the NHL. A classic Scheifele line shift that results in 30+ seconds of possession often in dangerous areas but in the end no good shot attempts (after the last incisive pass bounces over a stick in the slot, or whatever) would score highly by this metric.

But even that wouldn’t account entirely for more or less dangerous pass attempts or other offensive moves, if they weren’t completed and didn’t result in possession in a more dangerous area. A 2-on-1 that results in a shot into the pads would grade the same as one where a pass attempt from that same spot just misses the stick of its targeted teammate, who had an open net if he’d been able to reach the pass.

And a purely location-based NSxG model wouldn’t account for the value in hockey (which IMO is significant) of cycling the puck from one area of the offensive zone to another location that’s “only” equally (or maybe even less) dangerous, but where the quick switch in possession from side to side, or high/low or low/high, opens up a shooting angle and space to shoot. For instance Stastny’s pass on the PP last game from the front of the net to Wheeler on the side would probably lose NSxG (because Wheeler was further from the goal), even though that quick switch in play created a much higher danger scoring chance than if Stastny had shot it himself.

The positioning of the skaters and especially the goalie is so dynamic, and the details of their movements (not just where they are, but which direction they’re moving, and how fast) are so important to the actual danger of each shot or possession that it’s hard to believe a NSxG model will give an full account of the value of possession in hockey until those factors can be included.
Thanks. Very interesting and relevant. I don't think you could transpose the same methodology as in soccer without adjustments, but there would certainly be ways to improve xG models by including factors beyond simply shot attempts.
 

garret9

AKA#VitoCorrelationi
Mar 31, 2012
21,740
4,385
Vancouver
www.hockey-graphs.com
Are you aware of models, public or proprietary, that are incorporating xG types of metrics that include events that don't result in shot attempts?

xG is mostly taken from football/soccer (just like RAPM was taken from basketball) so Krauser has a good write up above on what a NSxG looks like.

There is no specific public model exactly like that due to the data that exists publically.

However, There are adjusted plus/minus or possession models that exist that look at events that are non-shot attempts that correlate to goals and/or possession with location to get a "true value" plus-minus that is similar to that.

Examples:
1) Brian MacDonald added penalties, hits, and giveaways to make an Adjusted Plus-Minus model.
2) DTMAH WAR model combined his RAPM xG model with a ML blended (5 ML models IIRC) Boxscore Plus-Minus model, the latter looking at non-shot attempts.

Aside but related: For shot attempt xG models there was one public research piece done on correlating non-public events to chance of goal:
variable-importance.png
 

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