Analytics & fancy stats thread

Flames Fanatic

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It's really just distance, and others have said advanced stats valuing all shots are more valuable because a high danger shot may not be more dangerous than a low danger shot depending on the circumstances. I just hope our top 2 defense pairings all post juggernaut high danger chances, and our third pairing despite having poor HDCI, overall still make one of the best third pairings in the league.

Thanks for following up, as much as we crap on you at times, at least you start conversation during the doldrums of summer lol.

2. You cannot compare across teams. It must be within the same organization

Snipped for length, not quality.

Interesting summary. I think I like the idea of same team comparison more so than I do cross league. I'll have to look at that more closely.

short answer: I think a WAR model will or at least should be the future of hockey analytics.

long answer:

This is what I said half a year ago in this thread and I still feel this way. I used to believe should be, in programming-speak, a double[] instead of simple double variable. However, I feel like I exaggerated the importance of chemistry, roles, needs, fitting systems, etc and underestimed the chaotic nature of the game. I have a more "teams need the best players and that's it" black and white mindset.

Thanks. I'm sure WAR charts are going to become increasingly common.

I'm not sure I see the game in nearly as much black and white as you do, but that is personal opinion. Generally speaking I agree, more good players means you are better. However, I think things like chemistry and system absolutely play a role. Look at the Hagelin/Perron swap two years ago. Both players struggled, both looked night and day different on after changing teams.

Found the oilers fan.

Posts like this are why I sympathize with the advanced stats crowd.
 

Fig

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Dec 15, 2014
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Yeah my guess is analytics are very useful when used with extreme detail/multiple contexts. But the simplistic perspectives people provide from things like looking at exclusively shot differentials are just a waste of time, and generally lead people to create some false narrative. It's really just a microcosm of our societies obsession with data, even when that data is providing a limited perspective.

Cody Franson. Stat nerds love him. Coaches hate him. Why? Because he makes a lot of stupid plays that end up in his net. Much like Wideman all those years. A stat page says Wideman and Franson are okay. But the eyeball test shows they are actually junk. Basically the opposite of someone like Stone.

Agree. Which is why I think multiple facets need to be measured and then rock paper scissors against other facets. We could even measure coaches chemistry if we figure this out.

We know certain players have certain skills
We know systems can enhance certain skills (coach effectiveness)
We know you can shut down a skill (match up)
We know certain players of certain skills mess up other players (skills, speed, physicality etc)

But none IMO can make sense if mashed together into a single number.

Idea wise in my head, the future will be to a radar chart of individual skills. An overlay of one chart to another gives you an idea of best match up. Against opposing teams, points are rock paper scissors. On the same team + coaches, it's averaged out based on the weakest link. But I don't know how it ultimately looks like.
 

Flames Fanatic

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Agree. Which is why I think multiple facets need to be measured and then rock paper scissors against other facets. We could even measure coaches chemistry if we figure this out.

We know certain players have certain skills
We know systems can enhance certain skills (coach effectiveness)
We know you can shut down a skill (match up)
We know certain players of certain skills mess up other players (skills, speed, physicality etc)

But none IMO can make sense if mashed together into a single number.

Idea wise in my head, the future will be to a radar chart of individual skills. An overlay of one chart to another gives you an idea of best match up. Against opposing teams, points are rock paper scissors. On the same team + coaches, it's averaged out based on the weakest link. But I don't know how it ultimately looks like.

A more advanced hero chart sort of thing. A better breakdown of more stats.
 

SmellOfVictory

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Jun 3, 2011
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Agree. Which is why I think multiple facets need to be measured and then rock paper scissors against other facets. We could even measure coaches chemistry if we figure this out.

We know certain players have certain skills
We know systems can enhance certain skills (coach effectiveness)
We know you can shut down a skill (match up)
We know certain players of certain skills mess up other players (skills, speed, physicality etc)

But none IMO can make sense if mashed together into a single number.

Idea wise in my head, the future will be to a radar chart of individual skills. An overlay of one chart to another gives you an idea of best match up. Against opposing teams, points are rock paper scissors. On the same team + coaches, it's averaged out based on the weakest link. But I don't know how it ultimately looks like.

I can't remember the source, but I've seen charts like that on NHL players. They had different focus points for things like carry-in percentage, scoring chances created, scoring chances given up, etc. and I think there were about 6-8 different measures included.
 

Fig

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A more advanced hero chart sort of thing. A better breakdown of more stats.

Sorta, but not quite. I believe Hero charts are just an overlay of two charts and just looks at certain facets over other facets. (ie: +/- of a facet from one player to another) It doesn't take into account synergistic skills/attributes and other factors yet of the entire package, systems and player landscape yet.

I personally think a hero chart will be more likely to be embraced going forward than GAR/WAR.

I can't remember the source, but I've seen charts like that on NHL players. They had different focus points for things like carry-in percentage, scoring chances created, scoring chances given up, etc. and I think there were about 6-8 different measures included.

If you could find them, I'd love a look at what they're tracking in those charts. The charts on their own is IMO just raw data. Figuring out how to use statistical analysis on those charts will be the way forward. The problem is each point affects the other point. Figuring out how to get rid of that "noise" without losing valuable information is the hard part.

I also think an OUR team vs league average aspect is needed as well as a systems "multiplier" added around those data sets. We know certain coaches drag everyone down, certain boost everyone and certain ones do a mix of both based on their stylistic expectations.

Getting too complicated now. Sorry.
 

OvermanKingGainer

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Given CFHF's downright amorous relationship with four quadrant graphs, here's a zone-entry denial four quadrant graph for everyone to write page long posts about how fantaboulously great their eyes are. More Break-ups + less opponent carry-ins = less time wasted in the wrong zone.

SW5hGJi.png


- Not sure where Wideman would be on the chart, maybe he was just so bad that he's not even in the range,
- Stone's breakup percentage of 0% can't be repeatable. That sounds like the injury taking away any aggressiveness he might have.
- Hamonic and Brodie are okay, they'll probably both improve each other?
- Giordano/Hamilton are about where you would expect given they're mostly playing against first liners who are going to get their carry-ins.
- Kulak... what a beauty. Played basically the same competition as Jokipakka/Engelland/Bartkowski but absolutely dominant.
 
Last edited:

Flames Fanatic

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Given CFHF's downright amorous relationship with four quadrant graphs, here's a zone-entry denial four quadrant graph for everyone to write page long posts about how fantaboulously great their eyes are. More Break-ups + less opponent carry-ins = less time wasted in the wrong zone.

Now that is one I find more interesting. Is that purely 2017 stats? I'm just curious as I'm a little surprised Hamonic plays more passively on zone entry.
 

Mr Snrub

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Given CFHF's downright amorous relationship with four quadrant graphs, here's a zone-entry denial four quadrant graph for everyone to write page long posts about how fantaboulously great their eyes are. More Break-ups + less opponent carry-ins = less time wasted in the wrong zone.

SW5hGJi.png


- Not sure where Wideman would be on the chart, maybe he was just so bad that he's not even in the range,
- Stone's breakup percentage of 0% can't be repeatable. That sounds like the injury taking away any aggressiveness he might have.
- Hamonic and Brodie are okay, they'll probably both improve each other?
- Giordano/Hamilton are about where you would expect given they're mostly playing against first liners who are going to get their carry-ins.
- Kulak... what a beauty. Played basically the same competition as Jokipakka/Engelland/Bartkowski but absolutely dominant.

Brett Kulak may be the greatest Flames defenseman ever.

Curious, did you use a combination of Stone's stats from both Arizona and Calgary? 0% sounds impossible to sustain over a full season.

EDIT: Now seeing you pulled the graph from somewhere else. Could you provide a link to the article you found it in?
 

SmellOfVictory

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Jun 3, 2011
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Given CFHF's downright amorous relationship with four quadrant graphs, here's a zone-entry denial four quadrant graph for everyone to write page long posts about how fantaboulously great their eyes are. More Break-ups + less opponent carry-ins = less time wasted in the wrong zone.

SW5hGJi.png


- Not sure where Wideman would be on the chart, maybe he was just so bad that he's not even in the range,
- Stone's breakup percentage of 0% can't be repeatable. That sounds like the injury taking away any aggressiveness he might have.
- Hamonic and Brodie are okay, they'll probably both improve each other?
- Giordano/Hamilton are about where you would expect given they're mostly playing against first liners who are going to get their carry-ins.
- Kulak... what a beauty. Played basically the same competition as Jokipakka/Engelland/Bartkowski but absolutely dominant.

Fits with the way I think of Gio and Brodie. Brodie does a lot of positional/stick work to attempt to prevent offensive players from getting where they want to go, and "aggressive" is about the best description of Gio as a defenceman that I can think of. I would be curious to know what it would have looked like last year, because I think Brodie would have more break-ups.
 

SmellOfVictory

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If you could find them, I'd love a look at what they're tracking in those charts. The charts on their own is IMO just raw data. Figuring out how to use statistical analysis on those charts will be the way forward. The problem is each point affects the other point. Figuring out how to get rid of that "noise" without losing valuable information is the hard part.

I didn't find them, but OKG posted one on the main board so I figured I'd link the source here.
 

Fig

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Question...

RelTM.

Is there a stat that does team relative to other teams and league average? Hoping to poke around and see if there are team/coach style stats I can look at.
 

Dack

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Jun 16, 2014
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Unrelated but this site has some really interesting prospect stats mainly for the OHL but it has some data on other leagues.

http://prospect-stats.com/DEV/16-17/

If you go to OHL goalies they have advanced stats for them and Parsons was far and away the best goalie in the league, I think most of us already knew that but it's nice to see the underlying numbers agree.
 

SmellOfVictory

Registered User
Jun 3, 2011
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Question...

RelTM.

Is there a stat that does team relative to other teams and league average? Hoping to poke around and see if there are team/coach style stats I can look at.

Relative to other teams: Not that I'm aware of. But I would think relative to league average (for the ratios, at any rate) is basically whether you're positive or negative.
 

Fig

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I didn't find them, but OKG posted one on the main board so I figured I'd link the source here.

Thanks, I like the idea of those charts. Essentially, I'm thinking something along the lines of the idea NHL players have more than one skill. If being thrashed by a player of a certain skill set they can tweak to a different skill to try and keep up. Perhaps these charts could be used to compare a coach. But it requires the below.

Relative to other teams: Not that I'm aware of. But I would think relative to league average (for the ratios, at any rate) is basically whether you're positive or negative.

Aww, that sucks. Oh well. Thanks for the other chart though.

IMO A coach's chart could be the team's total of the collected dataset categories on a year to year basis. Then it would be cross referenced to the personnel individual stats.
(https://public.tableau.com/profile/publish/Player_Types/Dashboard1#!/publish-confirm)

You'd compare it to the league total, overlay it against the other team's coaches and begin watching for statistical correlations between "styles" as measured by those charts. Essentially wondering if we can quantify a "style". I think the categories in those charts are a good start, but perhaps not the right categories. I'm leaning towards things like:

Puck possession
Transitions
Passing
Physicality
Penalties
Average speed
Shots for
Shots against

etc. to see if we can quantify a style. IMO such a chart might look different to an individual's skill chart.

You could even take individual metrics and overlay them against the style to see if the team is "stifled". I hesitate to say this, but GAR may even have use by determining if specific players or groups of players have enough strengths to push a style of play.

For instance:

Let's say you have 4 players high in transition play. If you acquire a coach historically known to play a transition style, perceived synergy. But if you have a coach who historically preaches shot volume, then you determine if that style can still fit with a strong transition style game, or if the players are suppressed.
 

Volica

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May 15, 2012
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Bump this thread.

Where are people going for their stats these days?
Corsica & Puckanalytics are both down/gone.

Naturalstattrick is still around, but man, it feels archaic.
 

Dertell

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Jul 14, 2015
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firstlinestats is a new one, but right now it's so limited to the point of being useless. Hopefully there's some improvements coming soon.
 

OvermanKingGainer

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Feb 3, 2015
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I know I already made a similar post before in this thread, but I don't think I specifically isolated the Ducks series of the three teams last time. Here are the SCA/60 VS Anaheim in the playoffs of our three defense pairs.


5v5 score / venue adjusted SCA/60 VS Ducks Playoffs
Pair | LD | RD
1st | | |
Giordano-Hamilton |14.38 |17.15
Ekholm-Subban | 22.79 | 21.16
Klefbom-Larsson | 36.11 | 37.59
2nd | |
Brodie-Stone | 25.56 | 26.09
Josi-Ellis | 28.92 | 29.56
Sekera-Russell | 33.28 | 34.09
3rd | |
Bartkowski-Engelland | 39.16 | 34.54
Irwin-Weber | 18.07 | 19.11
Nurse-Benning | 26.53 | 31.39

A tad bit frustrating to see it laid out like that.
 

BigRangy

Get well soon oliver
Mar 17, 2015
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I actually don't know how people paid to make player decisions in order to win hockey games could have decided that Bartkowski was the right choice to play down the stretch.

So so bad

Also for those numbers I wouldn't mind seeing CF%, SCF%, and xGF% for the pairs. SCA/60 is nice but the ratio is way more important than the raw number.
 

BigRangy

Get well soon oliver
Mar 17, 2015
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SCF% for pairs vs Ducks, 2017 Playoffs
5v5 SCF% VS Ducks Playoffs
Pair | LD | RD
1st | | |
Giordano-Hamilton |64.71 |62.07
Ekholm-Subban | 52.94 | 54.26
Klefbom-Larsson | 38.18 | 39.87
2nd | |
Brodie-Stone | 56.45 | 57.14
Josi-Ellis | 53.39 | 51.33
Sekera-Russell | 47.89 | 43.94
3rd | |
Bartkowski-Engelland | 39.62 | 40.43
Irwin-Weber | 59.18 | 55.32
Nurse-Benning | 51.43 | 44.44

seriously how is somebody being paid several hundred thousand dollars allowed to make decisions this stupid

I usually use Corsica for xGF% but they're down for the summer...
 

Mr Snrub

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Oct 12, 2016
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SCF% for pairs vs Ducks, 2017 Playoffs
5v5 SCF% VS Ducks Playoffs
Pair | LD | RD
1st | | |
Giordano-Hamilton |64.71 |62.07
Ekholm-Subban | 52.94 | 54.26
Klefbom-Larsson | 38.18 | 39.87
2nd | |
Brodie-Stone | 56.45 | 57.14
Josi-Ellis | 53.39 | 51.33
Sekera-Russell | 47.89 | 43.94
3rd | |
Bartkowski-Engelland | 39.62 | 40.43
Irwin-Weber | 59.18 | 55.32
Nurse-Benning | 51.43 | 44.44

seriously how is somebody being paid several hundred thousand dollars allowed to make decisions this stupid

I usually use Corsica for xGF% but they're down for the summer...

I may have a reputation as an anti-stats guy on this board but that's a margin you can't argue with. Absolutely disgusting, and that was our best third pair all year.
 

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