NSLNH - Caroline

Caroline

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Mike Thifault | Morale : 50 | Moyenne d'Équipe : 74

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Nathan MacKinnon	X		X		100.00	69	43	87	97	74	89	95	97	82	95	93	55	84	68	69	0	99	81	0
2	Auston Matthews	X				100.00	63	42	93	89	80	79	82	79	92	86	95	58	48	64	65	0	99	76	0
3	Blake Coleman	X	X	X		100.00	94	56	75	85	72	75	96	67	51	64	79	89	45	61	62	0	99	75	0
4	David Pastrnak		X	X		100.00	73	43	85	89	68	80	91	89	34	92	96	55	32	66	67	0	99	75	0
5	Artemi Panarin (A)		X	X		100.00	59	50	90	92	62	84	97	83	31	97	85	52	80	66	67	0	99	74	0
6	Colton Sissons	X		X		100.00	80	54	90	79	74	73	95	68	89	65	72	87	25	65	67	0	99	74	0
7	Patrik Laine		X	X		100.00	73	44	85	88	79	75	99	84	36	69	86	53	80	60	61	0	99	72	0
8	Alex Tuch	X		X		100.00	77	45	96	82	83	74	95	78	42	81	78	55	38	60	61	0	99	71	0
9	Travis Konecny	X	X	X		100.00	71	55	85	86	64	70	99	73	35	75	80	59	25	60	61	0	99	69	0
10	Victor Hedman (A)				X	100.00	71	44	82	90	85	87	91	89	25	80	60	81	66	75	80	0	99	79	0
11	Erik Karlsson				X	100.00	71	43	87	93	70	91	79	88	44	89	48	73	61	76	78	0	99	76	0
Rayé
1	Tyler Seguin (C)	X		X		100.00	73	43	92	90	74	85	99	83	95	88	88	66	87	74	77	0	99	79	0
2	Derek Ryan	X		X		100.00	59	40	90	77	63	66	98	73	92	75	70	78	25	64	64	0	99	71	0
3	Josh Manson				X	100.00	90	60	76	82	79	85	94	60	25	54	48	93	25	65	66	0	99	78	0
4	Roman Polak				X	100.00	90	57	75	66	86	78	83	59	25	50	47	96	25	77	80	0	99	77	0
5	Jonas Brodin				X	100.00	69	42	88	83	71	81	95	64	25	53	48	86	25	70	72	0	99	74	0

	MOYENNE D'ÉQUIPE					100.00	74	48	86	86	74	80	93	77	51	76	73	71	48	67	69	0	99	75

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Louis Domingue	100.00	71	66	65	83	73	68	61	72	78	71	87	58	58	0	99	70	0
2	Cam Talbot	100.00	61	81	79	82	68	54	50	61	60	61	66	65	66	0	99	64	0
Rayé
1	Jordan Binnington	100.00	84	68	65	62	90	78	83	85	90	84	95	47	47	0	99	77	0

	MOYENNE D'ÉQUIPE	100.00	72	72	70	76	77	67	65	73	76	72	83	57	57	0	99	70

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dominique Ducharme	55	55	55	55	55	55	55	CAN	50	2	500,000$

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Alex Tuch	Caroline	C/RW	22	1996-05-10	No	222 Lbs	6 ft4	No	No	No	3	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$	No	Lien / Lien NHL
Artemi Panarin	Caroline	LW/RW	27	1992-01-01	No	168 Lbs	5 ft11	No	No	No	4	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	8,500,000$	No	Lien
Auston Matthews	Caroline	C	20	1998-01-01	No	216 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$	No	Lien
Blake Coleman	Caroline	C/LW/RW	27	1992-01-01	No	200 Lbs	5 ft11	No	No	No	2	Sans Restriction	Pro & Farm	1,800,000$	1,800,000$	1,800,000$	No	Lien
Cam Talbot	Caroline	G	31	1988-01-01	No	196 Lbs	6 ft4	No	No	No	1	Sans Restriction	Pro & Farm	4,000,000$	4,000,000$	4,000,000$	No	Lien
Colton Sissons	Caroline	C/RW	24	1994-01-01	No	200 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	625,000$	625,000$	625,000$	No	Lien
David Pastrnak	Caroline	LW/RW	23	1996-01-01	No	188 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	6,500,000$	6,500,000$	6,500,000$	No	Lien
Derek Ryan	Caroline	C/RW	32	1986-12-29	No	170 Lbs	5 ft11	No	No	No	0	Sans Restriction	Pro & Farm		0$	0$	No	Lien
Erik Karlsson	Caroline	D	28	1991-01-01	No	191 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	8,500,000$	No	Lien
Jonas Brodin	Caroline	D	24	1994-01-01	No	194 Lbs	6 ft1	No	No	No	0	Avec Restriction	Pro & Farm		0$	0$	No	Lien
Jordan Binnington	Caroline	G	24	1994-01-01	No	167 Lbs	6 ft1	No	No	No	0	Avec Restriction	Pro & Farm		0$	0$	No	Lien
Josh Manson	Caroline	D	27	1992-01-01	No	213 Lbs	6 ft3	No	No	No	0	Sans Restriction	Pro & Farm		0$	0$	No	Lien
Louis Domingue	Caroline	G	27	1992-01-01	No	210 Lbs	6 ft3	No	No	No	2	Sans Restriction	Pro & Farm	1,150,000$	1,150,000$	1,150,000$	No	Lien
Nathan MacKinnon	Caroline	C/RW	23	1996-01-01	No	205 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	6,300,000$	6,300,000$	6,300,000$	No	Lien
Patrik Laine	Caroline	LW/RW	20	1999-01-01	No	206 Lbs	6 ft5	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$	No	Lien
Roman Polak	Caroline	D	32	1987-01-01	No	235 Lbs	6 ft2	No	No	No	0	Sans Restriction	Pro & Farm		0$	0$	No	Lien
Travis Konecny	Caroline	C/LW/RW	20	1998-01-01	No	175 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$	No	Lien
Tyler Seguin	Caroline	C/RW	25	1993-01-01	No	201 Lbs	6 ft1	No	No	No	0	Avec Restriction	Pro & Farm		0$	0$	No	Lien
Victor Hedman	Caroline	D	28	1991-01-01	No	223 Lbs	6 ft6	No	No	No	1	Sans Restriction	Pro & Farm	7,700,000$	7,700,000$	7,700,000$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	25.47	199 Lbs	6 ft2	1.21	2,567,105$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
48,775,000$	25,175,000$	15,725,000$	8,500,000$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Artemi Panarin		David Pastrnak	41	0	0	5
2	Patrik Laine	Auston Matthews	Nathan MacKinnon	40	0	3	2
3	Travis Konecny		Alex Tuch	14	2	2	1
4		Colton Sissons	Blake Coleman	5	3	2	0

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman		40	0	4	1
2		Erik Karlsson	40	0	4	1
3			20	0	4	1
4			0	0	4	1

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Artemi Panarin		Nathan MacKinnon	60	1	0	4
2	Patrik Laine	Auston Matthews	David Pastrnak	40	1	0	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman	Erik Karlsson	70	0	1	4
2	Travis Konecny		30	0	1	4

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Colton Sissons	Blake Coleman	50	0	4	1
2			50	0	4	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			50	1	4	0
2			50	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Colton Sissons	50	0	5	0	Victor Hedman		50	0	5	0
2		50	0	5	0			50	0	5	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Nathan MacKinnon	50	0	3	2
2	Auston Matthews	Artemi Panarin	50	0	3	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman		50	0	4	1
2		Erik Karlsson	50	0	4	1

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Artemi Panarin		Nathan MacKinnon	Victor Hedman	Erik Karlsson

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Blake Coleman	Colton Sissons

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
David Pastrnak, Blake Coleman,	David Pastrnak, Blake Coleman

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, Nathan MacKinnon, Auston Matthews, Artemi Panarin, David Pastrnak

Gardien
#1 : , #2 : Louis Domingue

Lignes d'Attaque Perso. en Prol.
, Nathan MacKinnon, Auston Matthews, Artemi Panarin, Colton Sissons, Patrik Laine, Patrik Laine, David Pastrnak, Blake Coleman, ,

Lignes de Défense Perso. en Prol.
Victor Hedman, , , Erik Karlsson,

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
	Total	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
0	0	N/A	0	0	0	0	0	0	0	0	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	0	0	0	0	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
0	0	0.00%	0	0	0.00%	0

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
0	0	0	0	0	0	0	0

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
0	0	0.00%	0	0	0.00%	0	0	0.00%

Temps Avec la Rondelle
En Zone Offensive	Contrôle en Zone Offensive	En Zone Défensive	Contrôle en Zone Défensive	En Zone Neutre	Contrôle en Zone Neutre
0	0	0	0	0	0

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	RI	Lien

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	7000	6000	3000	5000	2000
Prix des Billets	250	175	125	80	300
Assistance	0.00%	0.00%	0.00%	0.00%	0.00%
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
41	0 - 0.00%	0$	0$	23000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
0$	48,775,000$	42,925,000$	0$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0$	13	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	0$	18,344,828$	18,344,828$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Blake Coleman	AGE:27	PO:0	OV:75
David Pastrnak	AGE:23	PO:0	OV:75
Artemi Panarin	AGE:27	PO:0	OV:74
Patrik Laine	AGE:20	PO:0	OV:72
Travis Konecny	AGE:20	PO:0	OV:69
Cole Schneider	AGE:28	PO:0	OV:64
Roope Hintz	AGE:22	PO:0	OV:64
Michael Bournival	AGE:25	PO:0	OV:63
Curtis Valk	AGE:25	PO:0	OV:60
Axel Jonsson-Fjallby	AGE:20	PO:0	OV:55
Calvin Thurkauf	AGE:21	PO:0	OV:55
Daniel Maggio	AGE:27	PO:0	OV:54
Jimmy Mullin	AGE:25	PO:0	OV:49
Collin Adams	AGE:20	PO:0	OV:47
Jack Walker	AGE:22	PO:0	OV:47

Nathan MacKinnon	AGE:23	PO:0	OV:81
Tyler Seguin	AGE:25	PO:0	OV:79
Auston Matthews	AGE:20	PO:0	OV:76
Blake Coleman	AGE:27	PO:0	OV:75
Colton Sissons	AGE:24	PO:0	OV:74
Alex Tuch	AGE:22	PO:0	OV:71
Derek Ryan	AGE:32	PO:0	OV:71
Travis Konecny	AGE:20	PO:0	OV:69
Lucas Wallmark	AGE:23	PO:0	OV:66
Roope Hintz	AGE:22	PO:0	OV:64
Michael Bournival	AGE:25	PO:0	OV:63
Jordan Nolan	AGE:28	PO:0	OV:62
Curtis Valk	AGE:25	PO:0	OV:60
Ross Colton	AGE:22	PO:0	OV:59
Calvin Thurkauf	AGE:21	PO:0	OV:55
Daniel Maggio	AGE:27	PO:0	OV:54
Garrett Meurs	AGE:24	PO:0	OV:49
Jimmy Mullin	AGE:25	PO:0	OV:49

Nathan MacKinnon	AGE:23	PO:0	OV:81
Tyler Seguin	AGE:25	PO:0	OV:79
Blake Coleman	AGE:27	PO:0	OV:75
David Pastrnak	AGE:23	PO:0	OV:75
Artemi Panarin	AGE:27	PO:0	OV:74
Colton Sissons	AGE:24	PO:0	OV:74
Patrik Laine	AGE:20	PO:0	OV:72
Alex Tuch	AGE:22	PO:0	OV:71
Derek Ryan	AGE:32	PO:0	OV:71
Travis Konecny	AGE:20	PO:0	OV:69
Cole Schneider	AGE:28	PO:0	OV:64
Daniel Maggio	AGE:27	PO:0	OV:54
Garrett Meurs	AGE:24	PO:0	OV:49
Jimmy Mullin	AGE:25	PO:0	OV:49

Défense #1

Défense #2

Gardien

Victor Hedman	AGE:28	PO:0	OV:79
Josh Manson	AGE:27	PO:0	OV:78
Roman Polak	AGE:32	PO:0	OV:77
Erik Karlsson	AGE:28	PO:0	OV:76
Charlie McAvoy	AGE:20	PO:0	OV:74
Jonas Brodin	AGE:24	PO:0	OV:74

Samuel Girard	AGE:20	PO:0	OV:67
Calle Rosen	AGE:24	PO:0	OV:63
Patrick Sieloff	AGE:24	PO:0	OV:58
Daniel Maggio	AGE:27	PO:0	OV:54
Christopher Breen	AGE:29	PO:0	OV:49

Jordan Binnington	AGE:24	PO:0	OV:77
Louis Domingue	AGE:27	PO:0	OV:70
Daniel Altshuller	AGE:24	PO:0	OV:65
Martin Ouellette	AGE:27	PO:0	OV:64
Cam Talbot	AGE:31	PO:0	OV:64

Éspoirs

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total
Alexander Alexeyev	Caroline	2028	19
Alexander Romanov	Caroline	2029	10
Anthony Salinitri	Caroline	2025	176
Brett McKenzie	Caroline	2025	160
Elvis Merzlikins	Caroline	2022	78
Filip Zadina	Caroline	2029	3
Jay OBrien	Caroline	2028	16
Joel Farabee	Caroline	2029	6
Nicolas Beaudin	Caroline	2028	14
Olli Juolevi	Caroline	2025	8
Ty Smith	Caroline	2028	6

Choix au Repêchage

Année	R1	R2	R3	R4	R5
2030	NYR PIT	NYI	VEG NYR CBJ
2031	CAR NJD OTT SJS				LAK
2032	CAR SJS				CBJ
2033	CAR	CAR	CAR	CAR	CAR
2034	CAR	CAR	CAR	CAR CAR	CAR CAR

[2019-07-03 7:03:47 AM] - TRADE : From NY Islanders to Caroline : Cam Talbot (64), Y:2030-RND:2-NYI, Y:2030-RND:3-NYR, Y:2030-RND:3-CBJ.

[2019-07-03 7:03:47 AM] TRADE : From NY Islanders to Caroline : Cam Talbot (64), Y:2030-RND:2-NYI, Y:2030-RND:3-NYR, Y:2030-RND:3-CBJ.
[2019-07-03 7:03:47 AM] TRADE : From Caroline to NY Islanders : Henrik Lundqvist (76), Tim Schaller (68).

Pas de Blessure ou de Suspension.

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Séries
2029	23	16	7	0	0	0	0	0	72	60	12	11	8	3	0	0	0	0	0	37	21	16	12	8	4	0	0	0	0	0	35	39	-4	32	72	122	194	1	1	22	15	30	5	791	267	242	259	23	694	235	139	517	76	12	15.79%	67	6	91.04%	3	255	538	47.40%	252	499	50.50%	182	331	54.98%	542	317	466	203	409	212
Total Séries	23	16	7	0	0	0	0	0	72	60	12	11	8	3	0	0	0	0	0	37	21	16	12	8	4	0	0	0	0	0	35	39	-4	32	72	122	194	1	1	22	15	30	5	791	267	242	259	23	694	235	139	517	76	12	15.79%	67	6	91.04%	3	255	538	47.40%	252	499	50.50%	182	331	54.98%	542	317	466	203	409	212

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