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Guess the player 2

Créé par: Ajp_18
Équipe: 2019-20 Équipe personnalisée
Date de création initiale: 7 juin 2020
Publié: 7 juin 2020
Mode - plafond salarial: Basique
Description
All players are all defenseman on an ELC in 2019-2020, I’m using the players stats fron 2019-2020.

Player 1- 70 GP, 18 points, 56.1 corsi%, 58 oiGF, 40 oiGA
Player 2- 56 GP, 26 points, 51.6 corsi%, 51 oiGF, 35 oiGA
TAILLE DE LA FORMATIONPLAFOND SALARIALCAP HITEXCÉDENTS Info-bulleBONISESPACE SOUS LE PLAFOND SALARIAL
1490 000 000 $11 626 389 $0 $7 822 500 $78 373 611 $
Ailier gaucheCentreAilier droit
Défenseur gaucherDéfenseur droitierGardien de but
Logo de Oilers d'Edmonton
720 000 $720 000 $ (Bonis de performance20 000 $$20K)
DD
UFA - 1
Logo de Blackhawks de Chicago
894 167 $894 167 $ (Bonis de performance850 000 $$850K)
DD
RFA - 3
Logo de Predators de Nashville
925 000 $925 000 $ (Bonis de performance850 000 $$850K)
DD
UFA - 2
Logo de Rangers de New York
925 000 $925 000 $ (Bonis de performance850 000 $$850K)
DD
UFA - 3
Logo de Canadiens de Montréal
771 666 $771 666 $ (Bonis de performance132 500 $$132K)
DD
RFA - 2
Logo de Blue Jackets de Columbus
925 000 $925 000 $ (Bonis de performance850 000 $$850K)
DG
UFA - 1
Logo de Canucks de Vancouver
916 667 $916 667 $ (Bonis de performance850 000 $$850K)
DG
UFA - 2
Logo de Oilers d'Edmonton
720 000 $720 000 $ (Bonis de performance70 000 $$70K)
DG/DD
UFA - 1
Logo de Avalanche du Colorado
880 833 $880 833 $ (Bonis de performance2 500 000 $$2M)
DD
UFA - 2
Logo de Penguins de Pittsburgh
925 000 $925 000 $ (Bonis de performance850 000 $$850K)
DD
UFA - 2
Logo de Flyers de Philadelphie
678 889 $678 889 $
DD
UFA - 1
Logo de Kings de Los Angeles
700 000 $700 000 $
DD
UFA - 2
Logo de Maple Leafs de Toronto
894 167 $894 167 $
DG
UFA - 3
Logo de Wild du Minnesota
750 000 $750 000 $
DG/DD
UFA - 1

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7 juin 2020 à 15 h 26
#1
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Matt Roy

John Marino

(It wouldve been a lot harder if you didnt say it was only rookie D men)
7 juin 2020 à 15 h 34
#2
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Quoting: moli92
Matt Roy

John Marino

(It wouldve been a lot harder if you didnt say it was only rookie D men)


Well I also posted the players is could have been.
I didn’t try to make it hard. Just letting people see some Comparable players. To players they want to acquire.
7 juin 2020 à 15 h 42
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I’d prob say use rel cf% and gf vs. xGA to get a more complete picture.
7 juin 2020 à 15 h 48
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Quoting: Sagecoll
I’d prob say use rel cf% and gf vs. xGA to get a more complete picture.


Relative corsi and expected goals for are not for a more complete picture. Expected goals is kinda a BS stat imo. Just shows what you’re expected to do in your current role.

These are more possession numbers, not so much advanced stats. Plus advanced stats don’t give you a complete picture, it’s 1/3rd of the full picture.
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7 juin 2020 à 16 h 31
#5
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Quoting: Ajp_18
Relative corsi and expected goals for are not for a more complete picture. Expected goals is kinda a BS stat imo. Just shows what you’re expected to do in your current role.

These are more possession numbers, not so much advanced stats. Plus advanced stats don’t give you a complete picture, it’s 1/3rd of the full picture.


I mean that’s cool. They’re just way more liable to team and goaltending strength. 1 of a billion examples: Despite playing same minutes this year. Alex Goligoski gave up fewer GA than Jonas Brodin. Now if you thought GA reflected defense at all you’d think Goligoski was in Brodin’s ballpark defensively. But if you were smart, you’d realize that Arizona goaltending is awesome and Minnesota goaltending is terrible and if you just saw the xGA you’d see that Brodin was on ice for 14 fewer xGA.

Similar situation with cf%, of course if you just used cf% you’d think Thomas Chabot had an OK year (49 cf%), but certainly not even close to how dominant Ben Chiarot was (54%).

All of this to say. Poorly implemented analytics are worse than no analytics. If you’re trying to equate numbers to evaluations (this metric = good defense, etc) it’s probably best to know the optimal tool for your argument. Otherwise you end up thinking that analytics can only give you 1/3rd of a player evaluation at best.
7 juin 2020 à 17 h 9
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Quoting: Sagecoll
I mean that’s cool. They’re just way more liable to team and goaltending strength. 1 of a billion examples: Despite playing same minutes this year. Alex Goligoski gave up fewer GA than Jonas Brodin. Now if you thought GA reflected defense at all you’d think Goligoski was in Brodin’s ballpark defensively. But if you were smart, you’d realize that Arizona goaltending is awesome and Minnesota goaltending is terrible and if you just saw the xGA you’d see that Brodin was on ice for 14 fewer xGA.

Similar situation with cf%, of course if you just used cf% you’d think Thomas Chabot had an OK year (49 cf%), but certainly not even close to how dominant Ben Chiarot was (54%).

All of this to say. Poorly implemented analytics are worse than no analytics. If you’re trying to equate numbers to evaluations (this metric = good defense, etc) it’s probably best to know the optimal tool for your argument. Otherwise you end up thinking that analytics can only give you 1/3rd of a player evaluation at best.


Yeah. I know and I tend to use them more as a this is what I’m seeing, is that the case. Some people only use eyes and regular stats. Plus 90% of the people on here don’t understand the more advanced stats and don’t understand them. So this was just a few things so maybe some people start using not just one or the other. Plus I don’t need to use some of those because you can watch a hockey game and see the Arizona’s goaltending is 20x better then Minnesota’s, but I’d also say that system does tend to help some defensive players. IE Seth Jones had awful advanced stats last year, but he’s better in game then his stats show or is that because of the goalies in Columbus are good to make him look good or was is they were bad and tanked his stats at the start of the year?
7 juin 2020 à 17 h 55
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Quoting: Ajp_18
Yeah. I know and I tend to use them more as a this is what I’m seeing, is that the case. Some people only use eyes and regular stats. Plus 90% of the people on here don’t understand the more advanced stats and don’t understand them. So this was just a few things so maybe some people start using not just one or the other. Plus I don’t need to use some of those because you can watch a hockey game and see the Arizona’s goaltending is 20x better then Minnesota’s, but I’d also say that system does tend to help some defensive players. IE Seth Jones had awful advanced stats last year, but he’s better in game then his stats show or is that because of the goalies in Columbus are good to make him look good or was is they were bad and tanked his stats at the start of the year?


Jones had awful advanced stats last year? I’m looking at his numbers and they look totally fine. Curious what you’re referring to. GF stats are affected by goaltending CF/xGF numbers are not.

But yeah the bar is embarrassingly low on this site for this stuff.
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