NSLNH - Caroline

Caroline

GP: 16 | W: 8 | L: 7 | OTL: 1 | P: 17
GF: 57 | GA: 56 | PP%: 13.11% | PK%: 76.47%
DG: Mike Thifault | Morale : 50 | Moyenne d'Équipe : 74
Prochain matchs #256 vs Washington

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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	65	66	79	97	72	84	95	93	81	99	95	60	87	68	69	0	99	81	0
2	Tyler Seguin (C)	X		X		100.00	73	53	84	90	74	86	99	86	96	83	92	76	90	74	77	0	99	81	0
3	Auston Matthews	X				100.00	61	42	93	89	78	78	89	77	91	83	95	63	67	59	59	0	99	76	0
4	Artemi Panarin (A)		X	X		100.00	59	40	89	89	63	84	99	85	25	94	84	54	85	64	65	0	99	74	0
5	Patrik Laine		X	X		100.00	73	44	90	88	78	73	95	80	34	76	95	54	80	60	60	0	99	73	0
6	David Pastrnak		X	X		100.00	69	52	86	89	63	78	96	86	31	87	89	53	47	64	64	0	99	73	0
7	Blake Coleman	X	X	X		100.00	92	59	82	76	70	68	93	63	70	62	70	88	25	56	56	0	99	72	0
8	Trevor Lewis	X	X	X		100.00	83	55	88	74	73	70	92	62	44	64	72	79	41	74	78	0	99	71	0
9	Tim Schaller	X	X			100.00	81	58	85	75	77	65	88	60	48	61	68	86	25	61	61	0	99	70	0
10	Nate Thompson	X	X			100.00	83	45	90	69	76	64	68	58	90	63	58	85	25	75	78	0	99	70	0
11	Alex Tuch	X		X		100.00	78	55	89	74	85	70	88	78	46	73	71	60	45	55	55	0	99	69	0
12	Derek Ryan	X		X		100.00	69	42	89	77	63	72	95	77	94	74	71	58	25	60	60	0	99	69	0
13	Victor Hedman (A)				X	100.00	83	46	80	90	88	96	95	88	44	80	62	83	48	75	79	0	99	81	0
14	Ivan Provorov				X	100.00	83	45	91	89	74	91	99	74	25	64	61	89	25	60	60	0	99	79	0
15	Erik Karlsson				X	100.00	71	42	85	96	67	97	91	91	25	87	54	77	58	75	77	0	99	78	0
16	Jake Muzzin				X	100.00	88	46	84	84	79	84	95	79	25	73	51	84	25	70	73	0	99	78	0
17	Josh Manson				X	100.00	88	78	78	82	82	81	98	63	25	69	50	88	25	65	66	0	99	78	0
18	Andy Greene				X	100.00	75	53	91	77	69	83	91	58	25	51	48	99	25	80	83	0	99	77	0
Rayé
1	Johan Franzen	X	X	X		100.00	66	47	85	58	86	64	40	72	59	76	65	67	61	91	92	0	99	66	0

	MOYENNE D'ÉQUIPE					100.00	76	51	86	82	75	78	90	75	51	75	71	74	48	68	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	Henrik Lundqvist	98.00	82	90	89	72	78	86	59	82	85	82	81	80	86	0	99	80	0
2	Louis Domingue	100.00	61	64	63	83	71	51	50	63	61	60	89	56	56	0	99	63	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	72	77	76	78	75	69	55	73	73	71	85	68	71	0	99	72

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dominique Ducharme	55	55	55	55	55	55	55	CAN	49	3	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	PKS	PKM	GW	GT	FO%	FOT	GA	TA	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	David Pastrnak	Caroline	LW/RW	16	9	10	19	7	26	10	15	15	50	12	26	18.00%	8	264	16.54	1	1	2	2	43	0	0	1	1	27.27%	22	9	4	1.44	0	0	0	0	2	2	1	1
2	Auston Matthews	Caroline	C	16	5	11	16	8	0	0	13	23	37	7	18	13.51%	6	258	16.17	1	1	2	2	44	0	0	0	0	54.89%	235	11	2	1.24	1	1	0	0	0	0	0	0
3	Nathan MacKinnon	Caroline	C/RW	16	5	7	12	-14	28	10	16	13	51	24	43	9.80%	6	296	18.53	0	4	4	6	54	0	1	0	0	51.65%	91	19	4	0.81	0	1	1	0	1	1	0	1
4	Patrik Laine	Caroline	LW/RW	16	4	6	10	7	7	5	19	15	37	16	21	10.81%	8	269	16.86	1	1	2	3	54	0	0	1	0	31.25%	16	5	7	0.74	0	0	1	0	0	1	0	0
5	Victor Hedman	Caroline	D	16	0	9	9	-2	12	0	35	17	33	12	23	0.00%	24	333	20.84	0	3	3	1	64	1	1	0	0	0.00%	0	7	22	0.54	0	0	0	0	0	0	0	0
6	Tim Schaller	Caroline	C/LW	16	4	4	8	8	13	5	8	7	18	10	6	22.22%	1	134	8.38	0	0	0	0	5	0	1	2	0	100.00%	2	1	2	1.19	0	0	0	0	1	1	1	0
7	Blake Coleman	Caroline	C/LW/RW	16	4	4	8	8	4	0	22	11	27	7	16	14.81%	5	173	10.82	0	0	0	0	4	2	38	0	0	50.00%	4	0	2	0.92	0	0	0	0	0	0	2	1
8	Jake Muzzin	Caroline	D	16	2	6	8	5	4	0	27	23	31	14	16	6.45%	27	363	22.73	1	0	1	3	37	0	35	0	0	0.00%	0	4	13	0.44	0	0	0	0	0	0	0	2
9	Artemi Panarin	Caroline	LW/RW	16	2	6	8	-15	7	5	13	10	28	15	27	7.14%	5	302	18.89	2	2	4	5	52	0	4	0	0	10.00%	20	15	4	0.53	0	0	0	0	1	0	0	0
10	Erik Karlsson	Caroline	D	16	3	4	7	-1	11	5	15	18	25	7	15	12.00%	16	326	20.39	2	1	3	6	65	0	13	0	1	0.00%	0	11	11	0.43	0	0	0	1	0	0	0	1
11	Derek Ryan	Caroline	C/RW	16	5	2	7	4	6	0	6	18	40	12	28	12.50%	3	225	14.10	0	0	0	0	0	1	37	1	0	57.66%	222	8	4	0.62	0	0	0	0	0	1	0	1
12	Trevor Lewis	Caroline	C/LW/RW	16	5	2	7	4	2	0	27	10	26	6	11	19.23%	6	232	14.51	0	0	0	0	0	4	38	1	1	55.56%	9	0	4	0.60	0	0	0	0	0	1	2	0
13	Alex Tuch	Caroline	C/RW	16	1	5	6	3	2	0	15	10	40	11	24	2.50%	3	198	12.42	0	0	0	0	9	0	0	0	0	27.27%	11	13	1	0.60	0	0	0	0	0	1	0	0
14	Ivan Provorov	Caroline	D	16	2	4	6	3	4	0	9	28	23	9	9	8.70%	26	315	19.73	0	0	0	2	38	1	36	0	0	0.00%	0	5	13	0.38	0	0	0	0	0	0	0	0
15	Tyler Seguin	Caroline	C/RW	16	3	3	6	-15	11	5	25	20	38	12	19	7.89%	6	284	17.77	0	1	1	2	41	0	0	1	0	58.48%	330	3	5	0.42	1	1	0	1	0	0	0	1
16	Josh Manson	Caroline	D	16	1	5	6	3	38	20	27	21	10	2	6	10.00%	15	299	18.69	0	0	0	0	0	1	32	0	0	0.00%	0	2	9	0.40	0	0	1	2	1	0	0	0
17	Nate Thompson	Caroline	C/LW	16	1	4	5	8	2	0	8	18	9	4	12	11.11%	4	169	10.62	0	0	0	0	0	0	38	0	0	46.46%	99	1	3	0.59	0	0	0	0	0	0	0	0
18	Andy Greene	Caroline	D	16	0	3	3	1	0	0	7	25	16	5	5	0.00%	17	292	18.29	0	0	0	0	1	1	40	0	0	0.00%	0	1	9	0.21	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				288	56	95	151	22	177	65	307	302	539	185	325	10.39%	186	4740	16.46	8	14	22	32	517	11	320	7	3	53.53%	1061	115	119	0.64	2	3	3	4	6	8	6	8

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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	GA	SA	SAR	PS %	PSA	ST	BG	S2	S3
1	Henrik Lundqvist	Caroline	15	7	7	1	0.897	3.46	867	50	484	228	0.667	3	15	1	2	1
2	Louis Domingue	Caroline	3	1	0	0	0.860	3.67	98	6	43	23	0.000	0	1	15	0	0
Stats d'équipe Total ou en Moyenne			18	8	7	1	0.894	3.48	966	56	527	251	0.333	3	16	16	2	1

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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	4	Avec Restriction	Pro & Farm	925,000$	925,000$	758,500$	No	Lien / Lien NHL
Andy Greene	Caroline	D	36	1983-01-01	No	190 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	1,600,000$	1,600,000$	1,312,000$	No	Lien
Artemi Panarin	Caroline	LW/RW	27	1992-01-01	No	170 Lbs	5 ft11	No	No	No	5	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	6,970,000$	No	Lien
Auston Matthews	Caroline	C	20	1998-01-01	No	216 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	925,000$	925,000$	758,500$	No	Lien
Blake Coleman	Caroline	C/LW/RW	27	1992-01-01	No	200 Lbs	5 ft11	No	No	No	3	Sans Restriction	Pro & Farm	1,800,000$	1,800,000$	1,476,000$	No	Lien
David Pastrnak	Caroline	LW/RW	23	1996-01-01	No	181 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	6,500,000$	6,500,000$	5,330,000$	No	Lien
Derek Ryan	Caroline	C/RW	32	1986-12-29	No	170 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	500,000$	500,000$	410,000$	No	Lien
Erik Karlsson	Caroline	D	28	1991-01-01	No	191 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	6,970,000$	No	Lien
Henrik Lundqvist	Caroline	G	36	1983-01-01	No	188 Lbs	6 ft1	No	No	No	4	Sans Restriction	Pro & Farm	8,500,000$	8,500,000$	6,970,000$	No	Lien
Ivan Provorov	Caroline	D	20	1998-01-01	No	201 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	925,000$	925,000$	758,500$	No	Lien
Jake Muzzin	Caroline	D	29	1989-01-01	No	216 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	7,000,000$	7,000,000$	5,740,000$	No	Lien
Johan Franzen	Caroline	C/LW/RW	39	1980-01-01	No	232 Lbs	6 ft4	No	No	No	4	Sans Restriction	Pro & Farm	900,000$	900,000$	738,000$	No
Josh Manson	Caroline	D	27	1992-01-01	No	215 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	2,000,000$	2,000,000$	1,640,000$	No	Lien
Louis Domingue	Caroline	G	27	1992-01-01	No	210 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	1,150,000$	1,150,000$	943,000$	No	Lien
Nate Thompson	Caroline	C/LW	33	1985-01-01	No	212 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	2,000,000$	2,000,000$	1,640,000$	No	Lien
Nathan MacKinnon	Caroline	C/RW	23	1996-01-01	No	205 Lbs	6 ft0	No	No	No	4	Avec Restriction	Pro & Farm	6,300,000$	6,300,000$	5,166,000$	No	Lien
Patrik Laine	Caroline	LW/RW	20	1999-01-01	No	206 Lbs	6 ft4	No	No	No	2	Avec Restriction	Pro & Farm	925,000$	925,000$	758,500$	No	Lien
Tim Schaller	Caroline	C/LW	28	1990-11-16	No	219 Lbs	6 ft2	No	No	No	3	Sans Restriction	Pro & Farm	900,000$	900,000$	738,000$	No	Lien
Trevor Lewis	Caroline	C/LW/RW	31	1988-01-01	No	201 Lbs	6 ft1	No	No	No	4	Sans Restriction	Pro & Farm	2,000,000$	2,000,000$	1,640,000$	No	Lien
Tyler Seguin	Caroline	C/RW	25	1993-01-01	No	200 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	8,000,000$	8,000,000$	6,560,000$	No	Lien
Victor Hedman	Caroline	D	28	1991-01-01	No	223 Lbs	6 ft6	No	No	No	2	Sans Restriction	Pro & Farm	7,700,000$	7,700,000$	6,314,000$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
21	27.67	203 Lbs	6 ft2	2.71	3,692,857$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
77,550,000$	65,450,000$	46,475,000$	27,125,000$	8,500,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Artemi Panarin	Tyler Seguin	Nathan MacKinnon	33	0	1	4
2	David Pastrnak	Auston Matthews	Patrik Laine	30	0	1	4
3	Trevor Lewis	Derek Ryan	Alex Tuch	24	2	2	1
4	Tim Schaller	Nate Thompson	Blake Coleman	13	2	2	1

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman	Jake Muzzin	33	0	3	2
2	Ivan Provorov	Erik Karlsson	30	0	3	2
3	Josh Manson	Andy Greene	24	1	3	1
4	Josh Manson	Andy Greene	13	2	3	0

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Patrik Laine	Nathan MacKinnon	Artemi Panarin	70	0	0	5
2	Auston Matthews	Tyler Seguin	David Pastrnak	30	0	0	5

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman	Erik Karlsson	70	0	0	5
2	Ivan Provorov	Jake Muzzin	30	0	0	5

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Derek Ryan	Blake Coleman	50	0	4	1
2	Nate Thompson	Trevor Lewis	50	1	4	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Josh Manson	Andy Greene	50	1	4	0
2	Ivan Provorov	Jake Muzzin	50	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Nate Thompson	50	0	5	0	Victor Hedman	Andy Greene	50	0	5	0
2	Derek Ryan	50	0	5	0	Ivan Provorov	Josh Manson	50	0	5	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tyler Seguin	Nathan MacKinnon	70	0	3	2
2	Auston Matthews	Artemi Panarin	30	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Victor Hedman	Erik Karlsson	70	1	2	2
2	Ivan Provorov	Jake Muzzin	30	1	2	2

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

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tim Schaller	Nate Thompson	Blake Coleman	Victor Hedman	Jake Muzzin

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

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Erik Karlsson, Josh Manson, Andy Greene	Erik Karlsson	Erik Karlsson, Josh Manson

Tirs de Pénalité
Nathan MacKinnon, Tyler Seguin, Auston Matthews, Patrik Laine, Artemi Panarin

Gardien
#1 : Henrik Lundqvist, #2 : Louis Domingue

Lignes d'Attaque Perso. en Prol.
Nathan MacKinnon, Tyler Seguin, Auston Matthews, Patrik Laine, Artemi Panarin, David Pastrnak, David Pastrnak, Blake Coleman, Trevor Lewis, Tim Schaller, Nate Thompson

Lignes de Défense Perso. en Prol.
Victor Hedman, Jake Muzzin, Ivan Provorov, Erik Karlsson, Josh Manson

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
1	Anaheim	1	1	0	0	0	0	0	0	5	2	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	2	3	2	1.000	5	7	12	0	0	3	1	1	0	34	11	10	13	0	34	11	15	19	1	0	0.00%	5	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	22	12	20	9	17	8
2	Arizona	1	1	0	0	0	0	0	0	5	3	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	3	2	2	1.000	5	8	13	0	0	2	0	3	0	40	17	7	16	0	31	10	15	16	1	0	0.00%	5	1	80.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	21	12	20	9	17	8
3	Columbus	1	0	1	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	2	7	-5	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	3	5	0	0	2	0	0	0	35	10	12	13	0	38	7	15	18	3	0	0.00%	5	3	40.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	20	11	22	8	16	8
4	Los Angeles	1	1	0	0	0	0	0	0	5	2	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	2	3	2	1.000	5	9	14	0	0	1	2	2	0	29	1	20	8	0	33	15	7	24	6	1	16.67%	1	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	23	13	20	8	16	9
5	Minnesota	1	1	0	0	0	0	0	0	6	1	5	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	6	1	5	2	1.000	6	11	17	0	0	5	1	0	0	35	14	11	10	0	20	8	24	21	3	0	0.00%	2	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	22	12	18	9	19	10
6	NY Islanders	2	0	2	0	0	0	0	0	5	12	-7	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	2	8	-6	0	0.000	5	9	14	0	0	3	2	0	0	64	22	26	16	0	66	31	30	44	8	1	12.50%	5	3	40.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	43	25	41	17	34	17
7	NY Rangers	2	0	2	0	0	0	0	0	5	8	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	5	9	14	0	0	1	2	2	0	67	24	21	22	0	66	24	16	31	10	2	20.00%	8	2	75.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	50	31	36	16	33	17
8	New Jersey	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	2	5	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	2	0	0	0	36	10	15	11	0	33	17	4	17	3	1	33.33%	2	2	0.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	20	12	22	8	17	8
9	Ottawa	1	0	0	0	0	0	1	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	3	2	1	2	1.000	3	3	6	0	0	1	0	1	2	33	10	9	13	4	40	14	8	25	6	0	0.00%	4	1	75.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	23	12	22	9	18	10
10	Pittsburgh	2	2	0	0	0	0	0	0	8	4	4	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	3	2	1	4	1.000	8	14	22	0	0	1	3	4	0	59	18	17	24	0	71	21	20	42	9	2	22.22%	5	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	41	22	42	18	36	18
	Total	16	7	7	0	0	1	1	0	57	56	1	8	2	5	0	0	1	0	0	25	31	-6	8	5	2	0	0	0	1	0	32	25	7	17	0.531	57	95	152	0	0	23	13	20	2	539	174	172	189	7	527	186	177	307	61	8	13.11%	51	12	76.47%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	360	208	326	141	280	145
12	Vancouver	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	6	2	4	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	9	15	0	0	1	1	4	0	35	14	8	13	0	26	8	2	15	4	1	25.00%	1	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	24	15	18	8	17	9
13	Washington	2	0	1	0	0	1	0	0	5	8	-3	2	0	1	0	0	1	0	0	5	8	-3	0	0	0	0	0	0	0	0	0	0	0	1	0.250	5	9	14	0	0	1	1	3	0	72	23	16	30	3	69	20	21	35	7	0	0.00%	8	0	100.00%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	45	26	41	17	34	17
	_Since Last GM Reset	16	7	7	0	0	1	1	0	57	56	1	8	2	5	0	0	1	0	0	25	31	-6	8	5	2	0	0	0	1	0	32	25	7	17	0.531	57	95	152	0	0	23	13	20	2	539	174	172	189	7	527	186	177	307	61	8	13.11%	51	12	76.47%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	360	208	326	141	280	145
	_Vs Conference	11	2	7	0	0	1	1	0	30	46	-16	7	1	5	0	0	1	0	0	19	29	-10	4	1	2	0	0	0	1	0	11	17	-6	7	0.318	30	51	81	0	0	11	8	10	2	366	117	116	129	7	383	134	114	212	46	6	13.04%	37	11	70.27%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	246	142	228	96	192	99
	_Vs Division	10	2	7	0	0	1	0	0	27	44	-17	7	1	5	0	0	1	0	0	19	29	-10	3	1	2	0	0	0	0	0	8	15	-7	5	0.250	27	48	75	0	0	10	8	9	0	333	107	107	116	3	343	120	106	187	40	6	15.00%	33	10	69.70%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	222	129	206	87	173	88

			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
16	17	W1	57	95	152	539	527	186	177	307	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	7	7	0	1	1	0	57	56

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	2	5	0	1	0	0	25	31

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	5	2	0	0	1	0	32	25

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	5	0	1	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
61	8	13.11%	51	12	76.47%	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
174	172	189	7	23	13	20	2

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
227	425	53.41%	198	365	54.25%	143	261	54.79%

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
360	208	326	141	280	145

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	Lien
1 - 2019-04-05	13	Caroline	5	Arizona	3	W			Sommaire du Match
2 - 2019-04-06	19	Vancouver	2	Caroline	6	W			Sommaire du Match
3 - 2019-04-07	44	Caroline	5	Anaheim	2	W			Sommaire du Match
4 - 2019-04-08	49	Washington	4	Caroline	2	L			Sommaire du Match
5 - 2019-04-09	68	NY Rangers	3	Caroline	2	L			Sommaire du Match
6 - 2019-04-10	84	Caroline	6	Minnesota	1	W			Sommaire du Match
7 - 2019-04-11	95	Caroline	5	Los Angeles	2	W			Sommaire du Match
9 - 2019-04-13	108	New Jersey	5	Caroline	2	L			Sommaire du Match
10 - 2019-04-14	125	Caroline	2	NY Islanders	8	L			Sommaire du Match
11 - 2019-04-15	142	Columbus	7	Caroline	2	L			Sommaire du Match
12 - 2019-04-16	163	Caroline	3	NY Rangers	5	L			Sommaire du Match
13 - 2019-04-17	177	Pittsburgh	2	Caroline	5	W			Sommaire du Match
14 - 2019-04-18	193	Caroline	3	Ottawa	2	W	X	X	Sommaire du Match
15 - 2019-04-19	207	Washington	4	Caroline	3	L	X		Sommaire du Match
17 - 2019-04-21	225	NY Islanders	4	Caroline	3	L			Sommaire du Match
18 - 2019-04-22	238	Caroline	3	Pittsburgh	2	W			Sommaire du Match
19 - 2019-04-23	256	Washington	-	Caroline	-
20 - 2019-04-24	268	Caroline	-	Toronto	-
21 - 2019-04-25	275	Caroline	-	Boston	-
22 - 2019-04-26	293	Columbus	-	Caroline	-
23 - 2019-04-27	309	Caroline	-	Minnesota	-
25 - 2019-04-29	329	Montreal	-	Caroline	-
26 - 2019-04-30	348	Winnipeg	-	Caroline	-
27 - 2019-05-01	350	Caroline	-	Edmonton	-
28 - 2019-05-02	375	Caroline	-	Montreal	-
29 - 2019-05-03	392	Philadelphie	-	Caroline	-
30 - 2019-05-04	408	Vegas	-	Caroline	-
31 - 2019-05-05	416	Caroline	-	San Jose	-
32 - 2019-05-06	430	Caroline	-	Ottawa	-
33 - 2019-05-07	447	Boston	-	Caroline	-
34 - 2019-05-08	460	Caroline	-	Pittsburgh	-
36 - 2019-05-10	486	Edmonton	-	Caroline	-
37 - 2019-05-11	504	Dallas	-	Caroline	-
38 - 2019-05-12	518	Caroline	-	Colorado	-
39 - 2019-05-13	534	Caroline	-	New Jersey	-
40 - 2019-05-14	548	New Jersey	-	Caroline	-
41 - 2019-05-15	565	Caroline	-	Arizona	-
42 - 2019-05-16	579	Edmonton	-	Caroline	-
44 - 2019-05-18	596	Caroline	-	Dallas	-
45 - 2019-05-19	608	Nashville	-	Caroline	-
46 - 2019-05-20	622	Caroline	-	Vegas	-
47 - 2019-05-21	639	Caroline	-	Chicago	-
48 - 2019-05-22	652	Caroline	-	New Jersey	-
49 - 2019-05-23	667	Calgary	-	Caroline	-
50 - 2019-05-24	682	Chicago	-	Caroline	-
51 - 2019-05-25	702	Buffalo	-	Caroline	-
52 - 2019-05-26	723	Floride	-	Caroline	-
54 - 2019-05-28	743	Caroline	-	Vancouver	-
55 - 2019-05-29	755	Ottawa	-	Caroline	-
56 - 2019-05-30	771	Caroline	-	Nashville	-
57 - 2019-05-31	784	St. Louis	-	Caroline	-
58 - 2019-06-01	798	Caroline	-	Los Angeles	-
59 - 2019-06-02	817	Colorado	-	Caroline	-
61 - 2019-06-04	837	Caroline	-	Calgary	-
62 - 2019-06-05	846	Caroline	-	Tampa Bay	-
63 - 2019-06-06	861	Minnesota	-	Caroline	-
64 - 2019-06-07	882	Vancouver	-	Caroline	-
65 - 2019-06-08	890	Caroline	-	St. Louis	-
66 - 2019-06-09	910	Tampa Bay	-	Caroline	-
68 - 2019-06-11	938	Detroit	-	Caroline	-
69 - 2019-06-12	947	Caroline	-	Winnipeg	-
70 - 2019-06-13	966	Anaheim	-	Caroline	-
71 - 2019-06-14	989	Caroline	-	Washington	-
72 - 2019-06-15	995	Los Angeles	-	Caroline	-
74 - 2019-06-17	1020	Caroline	-	NY Rangers	-
75 - 2019-06-18	1031	Toronto	-	Caroline	-
76 - 2019-06-19	1048	Caroline	-	Washington	-
77 - 2019-06-20	1062	Arizona	-	Caroline	-
78 - 2019-06-21	1078	Caroline	-	Floride	-
79 - 2019-06-22	1089	Colorado	-	Caroline	-
81 - 2019-06-24	1109	Caroline	-	Detroit	-
82 - 2019-06-25	1121	San Jose	-	Caroline	-
83 - 2019-06-26	1135	Caroline	-	Philadelphie	-
85 - 2019-06-28	1155	NY Rangers	-	Caroline	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
87 - 2019-06-30	1182	Philadelphie	-	Caroline	-
89 - 2019-07-02	1203	Caroline	-	Columbus	-
90 - 2019-07-03	1211	Caroline	-	Buffalo	-
91 - 2019-07-04	1216	Pittsburgh	-	Caroline	-
92 - 2019-07-05	1224	Caroline	-	Columbus	-
93 - 2019-07-06	1230	Caroline	-	Philadelphie	-
97 - 2019-07-10	1250	Caroline	-	NY Islanders	-
98 - 2019-07-11	1258	NY Islanders	-	Caroline	-

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	42,385	37,421	18,626	29,642	12,209
Attendance PCT	75.69%	77.96%	77.61%	74.11%	76.31%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
33	17535 - 76.24%	1,626,086$	13,008,690$	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
14,049,000$	77,550,000$	62,050,000$	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
775,500$	13,959,000$	0$	21	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
53,660,846$	82	780,500$	64,001,000$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
65,583,308$	77,550,000$	5,961,909$	-5,960,553$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Artemi Panarin	AGE:27	PO:0	OV:74
Patrik Laine	AGE:20	PO:0	OV:73
David Pastrnak	AGE:23	PO:0	OV:73
Blake Coleman	AGE:27	PO:0	OV:72
Trevor Lewis	AGE:31	PO:0	OV:71
Tim Schaller	AGE:28	PO:0	OV:70
Nate Thompson	AGE:33	PO:0	OV:70
Johan Franzen	AGE:39	PO:0	OV:66
Brad Malone	AGE:28	PO:0	OV:64
Michael Bournival	AGE:25	PO:0	OV:63
Cole Schneider	AGE:28	PO:0	OV:63
Ryan Donato	AGE:22	PO:0	OV:63
Curtis Valk	AGE:25	PO:0	OV:60
Calvin Thurkauf	AGE:21	PO:0	OV:59
Daniel Maggio	AGE:27	PO:0	OV:54
Jimmy Mullin	AGE:25	PO:0	OV:49
Axel Jonsson-Fjallby	AGE:20	PO:0	OV:47
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:81
Auston Matthews	AGE:20	PO:0	OV:76
Blake Coleman	AGE:27	PO:0	OV:72
Trevor Lewis	AGE:31	PO:0	OV:71
Tim Schaller	AGE:28	PO:0	OV:70
Nate Thompson	AGE:33	PO:0	OV:70
Alex Tuch	AGE:22	PO:0	OV:69
Derek Ryan	AGE:32	PO:0	OV:69
Johan Franzen	AGE:39	PO:0	OV:66
Brad Malone	AGE:28	PO:0	OV:64
Michael Bournival	AGE:25	PO:0	OV:63
Ryan Donato	AGE:22	PO:0	OV:63
Jordan Nolan	AGE:28	PO:0	OV:61
Curtis Valk	AGE:25	PO:0	OV:60
Calvin Thurkauf	AGE:21	PO:0	OV:59
Daniel Maggio	AGE:27	PO:0	OV:54
Garrett Meurs	AGE:24	PO:0	OV:49
Jimmy Mullin	AGE:25	PO:0	OV:49
Ross Colton	AGE:22	PO:0	OV:47

Nathan MacKinnon	AGE:23	PO:0	OV:81
Tyler Seguin	AGE:25	PO:0	OV:81
Artemi Panarin	AGE:27	PO:0	OV:74
Patrik Laine	AGE:20	PO:0	OV:73
David Pastrnak	AGE:23	PO:0	OV:73
Blake Coleman	AGE:27	PO:0	OV:72
Trevor Lewis	AGE:31	PO:0	OV:71
Alex Tuch	AGE:22	PO:0	OV:69
Derek Ryan	AGE:32	PO:0	OV:69
Johan Franzen	AGE:39	PO:0	OV:66
Cole Schneider	AGE:28	PO:0	OV:63
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:81
Ivan Provorov	AGE:20	PO:0	OV:79
Erik Karlsson	AGE:28	PO:0	OV:78
Jake Muzzin	AGE:29	PO:0	OV:78
Josh Manson	AGE:27	PO:0	OV:78
Andy Greene	AGE:36	PO:0	OV:77
Charlie McAvoy	AGE:20	PO:0	OV:72
Travis Dermott	AGE:22	PO:0	OV:65

Victor Mete	AGE:20	PO:0	OV:62
Patrick Sieloff	AGE:24	PO:0	OV:60
Christian Wolanin	AGE:23	PO:0	OV:59
Calle Rosen	AGE:24	PO:0	OV:59
Daniel Maggio	AGE:27	PO:0	OV:54
Max Lajoie	AGE:21	PO:0	OV:49
Christopher Breen	AGE:29	PO:0	OV:49

Henrik Lundqvist	AGE:36	PO:0	OV:80
Daniel Altshuller	AGE:24	PO:0	OV:65
Louis Domingue	AGE:27	PO:0	OV:63
Martin Ouellette	AGE:27	PO:0	OV:53

Éspoirs

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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

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
Filip Zadina	Caroline	2029	3
Jack Studnicka	Caroline	2026	37
Jay OBrien	Caroline	2028	16
Joel Farabee	Caroline	2029	6
Linus Karlsson	Caroline	2028	34
Nicolas Beaudin	Caroline	2028	14
Olli Juolevi	Caroline	2025	8
Travis Barron	Caroline	2025	142
Ty Smith	Caroline	2028	6

Choix au Repêchage

Année	R1	R2	R3	R4	R5
2030	NYR PHI PIT
2031	CAR SJS
2032	CAR		CAR		CAR
2033	CAR	CAR	CAR	CAR	CAR
2034	CAR	CAR	CAR	CAR CAR	CAR CAR

Pas de Blessure ou de Suspension.

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	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
2029	16	7	7	0	0	1	1	0	57	56	1	8	2	5	0	0	1	0	0	25	31	-6	8	5	2	0	0	0	1	0	32	25	7	17	57	95	152	0	0	23	13	20	2	539	174	172	189	7	527	186	177	307	61	8	13.11%	51	12	76.47%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	360	208	326	141	280	145
Total Saison Régulière	16	7	7	0	0	1	1	0	57	56	1	8	2	5	0	0	1	0	0	25	31	-6	8	5	2	0	0	0	1	0	32	25	7	17	57	95	152	0	0	23	13	20	2	539	174	172	189	7	527	186	177	307	61	8	13.11%	51	12	76.47%	0	227	425	53.41%	198	365	54.25%	143	261	54.79%	360	208	326	141	280	145

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