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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	Âge	Contrat	Salaire
1	Boris Katchouk		X			100.00	78	76	82	61	76	68	68	69	50	69	65	67	62	44	44	67	50	63	0	23	2	894,166$
2	Garrett Pilon	X				100.00	70	70	69	68	70	62	61	67	80	70	60	63	57	44	44	64	50	62	0	23	2	894,166$
3	Tyler Steenbergen	X	X	X		100.00	74	66	94	68	66	68	72	56	70	44	63	62	60	44	44	62	50	59	0	23	2	875,000$
4	Parker Kelly (R)	X		X		100.00	75	71	85	62	71	67	69	59	74	51	62	63	59	44	44	62	50	59	0	22	3	750,000$
5	C.J. Suess (R)		X			100.00	75	69	89	60	69	66	69	58	50	49	62	63	59	44	44	62	50	58	0	27	3	750,000$
6	Brett Seney	X	X			100.00	63	56	79	77	56	67	71	54	68	47	56	57	53	49	49	58	50	57	0	25	1	825,000$
7	Tanner Kaspick	X				100.00	74	73	77	65	73	59	62	50	63	47	47	61	45	44	44	54	50	55	0	23	2	822,222$
8	Michael Pezzetta (R)	X	X			100.00	71	75	60	64	75	52	53	50	63	47	47	59	45	44	44	53	50	53	0	23	3	750,000$
9	Gabriel Carlsson				X	100.00	71	43	90	78	78	65	56	58	25	55	49	66	25	55	55	58	50	63	0	24	2	894,166$
10	Kale Clague				X	100.00	65	41	92	71	65	71	74	66	25	65	47	69	25	46	46	58	50	63	0	23	2	761,666$
11	Mikko Lehtonen (R)				X	100.00	77	44	90	68	71	68	66	61	25	57	47	68	25	46	46	61	50	62	0	27	2	900,000$
12	Jacob Middleton				X	100.00	82	79	89	68	79	54	55	51	25	38	48	67	46	51	51	56	50	60	0	25	1	750,000$
13	Frederic Allard				X	100.00	70	66	79	61	66	65	67	58	25	55	45	62	43	51	51	57	50	59	0	23	2	921,666$
14	Ben Gleason				X	100.00	73	68	84	62	68	63	66	53	25	48	43	61	41	44	44	55	50	58	0	23	1	761,666$
15	Gavin Bayreuther				X	100.00	78	44	78	63	72	67	64	60	25	39	51	58	53	46	46	57	50	58	0	27	1	955,000$
16	Matt Kiersted (R)				X	100.00	77	67	99	64	67	45	47	41	25	28	39	60	37	44	44	49	50	53	0	23	1	1,350,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	73	63	84	66	70	63	64	57	45	51	52	63	46	46	46	58	50	59

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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	Alexandar Georgiev	100.00	66	61	60	67	70	62	74	66	75	66	70	56	56	67	50	65	0
2	Hunter Miska	100.00	57	55	69	65	59	58	51	60	56	55	30	44	44	56	50	56	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	62	58	65	66	65	60	63	63	66	61	50	50	50	62	50	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Trent Cull	68	65	72	67	73	68	78	CAN	47	2	750,000$

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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

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#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	S1	S2	S3
1	Boris Katchouk	Canucks (VAN)	LW	14	11	13	24	18	24	20	21	40	16	31	27.50%	1	184	13.20	4	1	5	11	30	0	7	2	0	88.89%	9	0	2.60	0	0	3	1	1
2	Garrett Pilon	Canucks (VAN)	C	16	9	13	22	20	12	14	38	39	10	23	23.08%	0	190	11.88	1	1	2	5	16	0	9	2	1	75.24%	210	0	2.31	1	1	0	2	3
3	Tyler Steenbergen	Canucks (VAN)	C/LW/RW	16	4	8	12	20	4	5	9	24	6	14	16.67%	1	180	11.30	0	1	1	1	16	0	0	1	0	90.00%	10	0	1.33	0	0	0	1	0
4	Jacob Middleton	Canucks (VAN)	D	16	3	7	10	10	14	28	12	24	11	12	12.50%	11	280	17.51	1	1	2	7	28	1	26	0	0	0.00%	0	0	0.71	0	0	0	1	1
5	Frederic Allard	Canucks (VAN)	D	16	2	8	10	13	4	17	3	11	6	7	18.18%	3	229	14.33	1	1	2	6	9	0	10	0	0	0.00%	0	0	0.87	0	0	0	0	1
6	Gabriel Carlsson	Canucks (VAN)	D	16	3	6	9	9	4	28	8	12	6	13	25.00%	11	259	16.21	1	1	2	5	20	0	21	1	0	0.00%	0	0	0.69	0	0	0	1	0
7	Gavin Bayreuther	Canucks (VAN)	D	16	3	6	9	10	20	50	5	13	7	10	23.08%	15	261	16.34	0	3	3	1	11	0	18	0	0	0.00%	0	0	0.69	0	0	1	1	2
8	Rudolfs Balcers	Canucks	LW/RW	3	3	6	9	8	0	10	4	17	2	19	17.65%	0	66	22.06	0	1	1	3	6	0	10	0	0	56.25%	16	0	2.72	0	0	3	0	0
9	Kale Clague	Canucks (VAN)	D	7	0	9	9	3	0	3	1	9	1	6	0.00%	5	134	19.26	0	3	3	7	22	1	23	0	0	0.00%	0	0	1.33	0	0	0	0	0
10	Haydn Fleury	Canucks	D	3	2	6	8	7	0	6	1	14	4	6	14.29%	3	69	23.17	0	2	2	5	15	1	8	0	0	0.00%	0	0	2.30	0	0	1	0	2
11	Alexander True	Canucks	C	5	3	5	8	9	2	7	7	13	6	12	23.08%	1	88	17.76	0	1	1	0	6	0	11	1	0	77.22%	79	0	1.80	0	0	0	2	0
12	Mikko Lehtonen	Canucks (VAN)	D	7	1	6	7	8	2	9	2	2	4	11	50.00%	5	140	20.10	0	1	1	1	19	0	21	0	0	0.00%	0	0	0.99	0	0	0	0	2
13	Parker Kelly	Canucks (VAN)	C/RW	7	4	3	7	9	8	20	11	23	9	20	17.39%	1	135	19.36	0	1	1	2	23	0	0	2	0	63.64%	11	0	1.03	0	0	2	0	0
14	Anton Blidh	Canucks	LW/RW	3	4	0	4	-1	0	10	11	28	7	12	14.29%	0	60	20.33	2	0	2	7	14	0	0	0	0	20.00%	5	0	1.31	0	0	1	0	0
15	Logan O'Connor	Canucks	RW	2	4	0	4	3	0	3	2	17	2	9	23.53%	0	31	15.69	1	0	1	2	5	0	0	0	0	0.00%	0	1	2.55	0	0	0	1	0
16	Brett Seney	Canucks (VAN)	C/LW	7	2	0	2	2	4	4	7	14	1	7	14.29%	0	80	11.45	0	0	0	0	2	0	3	0	0	77.61%	67	0	0.50	0	0	0	0	0
17	Brian Pinho	Canucks	C	3	1	1	2	1	2	2	2	7	2	8	14.29%	0	15	5.14	0	0	0	0	0	0	0	0	0	80.00%	10	0	2.59	0	0	0	0	0
18	Michael Pezzetta	Canucks (VAN)	C/LW	7	2	0	2	2	12	2	3	6	0	2	33.33%	0	39	5.67	0	0	0	0	0	0	8	1	0	75.00%	8	0	1.01	0	0	0	0	0
19	Tanner Kaspick	Canucks (VAN)	C	7	1	1	2	4	4	4	3	5	3	2	20.00%	0	101	14.45	0	0	0	0	0	0	0	0	0	80.56%	36	0	0.40	0	0	0	0	0
20	Ben Gleason	Canucks (VAN)	D	7	0	1	1	1	2	2	3	2	0	1	0.00%	2	45	6.43	0	0	0	1	4	0	9	0	0	0.00%	0	0	0.44	0	0	0	0	0
21	C.J. Suess	Canucks (VAN)	LW	7	0	1	1	2	2	2	5	18	6	6	0.00%	0	87	12.44	0	0	0	2	5	2	6	0	0	75.00%	4	0	0.23	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				185	62	100	162	158	120	246	158	338	109	231	18.34%	59	2682	14.50	11	18	29	66	260	5	195	10	1	75.48%	465	1	1.21	1	1	11	10	12

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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	PCT	GAA	MP	PIM	SO	GA	SA	A	PS %	PSA	ST	BG	S1	S2
1	Alexandar Georgiev	Canucks (VAN)	16	13	3	0.910	1.96	917	2	3	30	332	2	1.000	5	16	0	2	1
2	Hunter Miska	Canucks (VAN)	1	0	0	0.875	2.61	46	0	0	2	16	0	0.000	0	0	16	0	0
Stats d'équipe Total ou en Moyenne			17	13	3	0.908	1.99	964	2	3	32	348	2	1.000	5	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	Type	Salaire Actuel	Salaire Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Alexandar Georgiev	Canucks (VAN)	G	25	1996-02-10	No	178 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No			Lien / Lien NHL
Ben Gleason	Canucks (VAN)	D	23	1998-03-24	No	180 Lbs	6 ft1	No	No	No	1	Pro & Farm	761,666$	761,666$	0$	0$	No			Lien / Lien NHL
Boris Katchouk	Canucks (VAN)	LW	23	1998-06-17	No	206 Lbs	6 ft2	No	No	No	2	Pro & Farm	894,166$	894,166$	0$	0$	No	894,166$		Lien / Lien NHL
Brett Seney	Canucks (VAN)	C/LW	25	1996-02-27	No	156 Lbs	5 ft9	No	No	No	1	Pro & Farm	825,000$	825,000$	0$	0$	No			Lien / Lien NHL
C.J. Suess	Canucks (VAN)	LW	27	1994-03-16	Yes	190 Lbs	5 ft11	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$	Lien
Frederic Allard	Canucks (VAN)	D	23	1997-12-27	No	179 Lbs	6 ft1	No	No	No	2	Pro & Farm	921,666$	921,666$	0$	0$	No	921,666$		Lien / Lien NHL
Gabriel Carlsson	Canucks (VAN)	D	24	1997-01-02	No	203 Lbs	6 ft5	No	No	No	2	Pro & Farm	894,166$	894,166$	0$	0$	No	894,166$		Lien / Lien NHL
Garrett Pilon	Canucks (VAN)	C	23	1998-04-13	No	190 Lbs	6 ft0	No	No	No	2	Pro & Farm	894,166$	894,166$	0$	0$	No	894,166$		Lien / Lien NHL
Gavin Bayreuther	Canucks (VAN)	D	27	1994-05-12	No	195 Lbs	6 ft1	No	No	No	1	Pro & Farm	955,000$	955,000$	0$	0$	No			Lien / Lien NHL
Hunter Miska	Canucks (VAN)	G	26	1995-07-06	No	175 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Jacob Middleton	Canucks (VAN)	D	25	1996-01-02	No	210 Lbs	6 ft3	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Lien / Lien NHL
Kale Clague	Canucks (VAN)	D	23	1998-06-05	No	177 Lbs	6 ft0	No	No	No	2	Pro & Farm	761,666$	761,666$	0$	0$	No	761,666$		Lien / Lien NHL
Matt Kiersted	Canucks (VAN)	D	23	1998-04-14	Yes	181 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,350,000$	1,350,000$	0$	0$	No			Lien
Michael Pezzetta	Canucks (VAN)	C/LW	23	1998-03-13	Yes	205 Lbs	6 ft1	No	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Mikko Lehtonen	Canucks (VAN)	D	27	1994-01-16	Yes	196 Lbs	6 ft0	Yes	No	No	2	Pro & Farm	900,000$	900,000$	0$	0$	No	900,000$		Lien
Parker Kelly	Canucks (VAN)	C/RW	22	1999-05-14	Yes	196 Lbs	6 ft0	Yes	No	No	3	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	750,000$	Lien / Lien NHL
Tanner Kaspick	Canucks (VAN)	C	23	1998-01-28	No	200 Lbs	6 ft0	No	No	No	2	Pro & Farm	822,222$	822,222$	0$	0$	No	822,222$		Lien / Lien NHL
Tyler Steenbergen	Canucks (VAN)	C/LW/RW	23	1998-01-07	No	188 Lbs	5 ft10	No	No	No	2	Pro & Farm	875,000$	875,000$	0$	0$	No	875,000$		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
18	24.17	189 Lbs	6 ft1	1.83	894,707$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Parker Kelly	40	1	2	2
2	Boris Katchouk	Garrett Pilon	Tyler Steenbergen	30	1	2	2
3	C.J. Suess	Brett Seney	Tanner Kaspick	20	1	2	2
4	Michael Pezzetta	Tanner Kaspick		10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Gabriel Carlsson	Kale Clague	40	1	2	2
2	Mikko Lehtonen	Jacob Middleton	30	1	2	2
3	Frederic Allard	Gavin Bayreuther	20	1	2	2
4	Ben Gleason	Gabriel Carlsson	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Parker Kelly	60	1	2	2
2	Boris Katchouk	Garrett Pilon	Tyler Steenbergen	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Gabriel Carlsson	Kale Clague	60	1	2	2
2	Mikko Lehtonen	Jacob Middleton	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2	Boris Katchouk	Garrett Pilon	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Gabriel Carlsson	Kale Clague	60	1	2	2
2	Mikko Lehtonen	Jacob Middleton	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		60	1	2	2	Gabriel Carlsson	Kale Clague	60	1	2	2
2		40	1	2	2	Mikko Lehtonen	Jacob Middleton	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2	Boris Katchouk	Garrett Pilon	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Gabriel Carlsson	Kale Clague	60	1	2	2
2	Mikko Lehtonen	Jacob Middleton	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Parker Kelly	Gabriel Carlsson	Kale Clague

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Parker Kelly	Gabriel Carlsson	Kale Clague

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
C.J. Suess, Brett Seney, Michael Pezzetta	C.J. Suess, Brett Seney	Michael Pezzetta

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Frederic Allard, Gavin Bayreuther, Ben Gleason	Frederic Allard	Gavin Bayreuther, Ben Gleason

Tirs de Pénalité
, , Boris Katchouk, Garrett Pilon, Parker Kelly

Gardien
#1 : Alexandar Georgiev, #2 : Hunter Miska

Lignes d'Attaque Perso. en Prol.
, , Boris Katchouk, Garrett Pilon, Parker Kelly, Tyler Steenbergen, Tyler Steenbergen, C.J. Suess, Brett Seney, Tanner Kaspick, Michael Pezzetta

Lignes de Défense Perso. en Prol.
Gabriel Carlsson, Kale Clague, Mikko Lehtonen, Jacob Middleton, Frederic Allard

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	Comets	2	1	0	0	0	0	1	0	10	7	3	1	1	0	0	0	0	0	0	5	3	2	1	0	0	0	0	0	1	0	5	4	1	4	1.000	10	16	26	0	0	38	16	19	1	64	154	161	144	5	64	16	12	37	4	2	50.00%	6	1	83.33%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
2	Crunch	2	2	0	0	0	0	0	0	11	3	8	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	8	1	7	4	1.000	11	22	33	0	0	38	16	19	1	42	154	161	144	5	45	22	16	41	7	3	42.86%	8	0	100.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
3	Griffins	2	2	0	0	0	0	0	0	11	3	8	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	6	0	6	4	1.000	11	19	30	0	1	38	16	19	1	54	154	161	144	5	42	9	8	41	9	1	11.11%	3	1	66.67%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
4	Marlies	2	2	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	1	0	1	1	1	0	0	0	0	0	0	3	2	1	4	1.000	4	6	10	0	1	38	16	19	1	37	154	161	144	5	35	7	16	32	16	3	18.75%	7	0	100.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
5	Monsters	2	1	1	0	0	0	0	0	6	8	-2	1	0	1	0	0	0	0	0	2	6	-4	1	1	0	0	0	0	0	0	4	2	2	2	0.500	6	8	14	0	0	38	16	19	1	62	154	161	144	5	50	17	22	35	12	2	16.67%	10	5	50.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
6	Rocket	2	0	2	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	2	2	4	0	0	38	16	19	1	31	154	161	144	5	31	17	19	43	4	0	0.00%	7	1	85.71%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
7	Senators	2	2	0	0	0	0	0	0	18	2	16	1	1	0	0	0	0	0	0	12	2	10	1	1	0	0	0	0	0	0	6	0	6	4	1.000	18	31	49	0	1	38	16	19	1	84	154	161	144	5	39	4	20	48	3	1	33.33%	10	0	100.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
8	Sound Tigers	1	1	0	0	0	0	0	0	7	1	6	1	1	0	0	0	0	0	0	7	1	6	0	0	0	0	0	0	0	0	0	0	0	2	1.000	7	12	19	0	0	38	16	19	1	36	154	161	144	5	12	3	14	20	2	1	50.00%	6	0	100.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
9	Wolf Pack	1	1	0	0	0	0	0	0	5	1	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	1	4	2	1.000	5	10	15	0	0	38	16	19	1	49	154	161	144	5	30	10	4	20	2	0	0.00%	2	0	100.00%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
	Total	16	12	3	0	0	0	1	0	74	32	42	8	6	2	0	0	0	0	0	36	20	16	8	6	1	0	0	0	1	0	38	12	26	26	0.813	74	126	200	0	3	38	16	19	1	459	154	161	144	5	348	105	131	317	59	13	22.03%	59	8	86.44%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
	_Since Last GM Reset	16	12	3	0	0	0	1	0	74	32	42	8	6	2	0	0	0	0	0	36	20	16	8	6	1	0	0	0	1	0	38	12	26	26	0.813	74	126	200	0	3	38	16	19	1	459	154	161	144	5	348	105	131	317	59	13	22.03%	59	8	86.44%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
	_Vs Conference	16	12	3	0	0	0	1	0	74	32	42	8	6	2	0	0	0	0	0	36	20	16	8	6	1	0	0	0	1	0	38	12	26	26	0.813	74	126	200	0	3	38	16	19	1	459	154	161	144	5	348	105	131	317	59	13	22.03%	59	8	86.44%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101
	_Vs Division	10	10	3	0	0	0	1	0	46	15	31	5	5	2	0	0	0	0	0	22	10	12	5	5	1	0	0	0	1	0	24	5	19	22	1.100	46	80	126	0	3	38	16	19	1	248	154	161	144	5	192	59	79	205	39	8	20.51%	35	2	94.29%	0	226	403	56.08%	220	383	57.44%	133	239	55.65%	464	351	316	97	183	101

			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	26	W3	74	126	200	459	348	105	131	317	0	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	12	3	0	0	1	0	74	32

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	6	2	0	0	0	0	36	20

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	6	1	0	0	1	0	38	12

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
8	2	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
59	13	22.03%	59	8	86.44%	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
154	161	144	5	38	16	19	1

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
226	403	56.08%	220	383	57.44%	133	239	55.65%

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
464	351	316	97	183	101

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
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2021-10-18	7	Canucks	4	Monsters	2	W			Sommaire du Match
2 - 2021-10-19	18	Senators	2	Canucks	12	W			Sommaire du Match
4 - 2021-10-21	45	Canucks	3	Marlies	2	W			Sommaire du Match
5 - 2021-10-22	56	Crunch	2	Canucks	3	W			Sommaire du Match
6 - 2021-10-23	73	Rocket	3	Canucks	1	L			Sommaire du Match
7 - 2021-10-24	88	Canucks	5	Comets	4	W	X	X	Sommaire du Match
8 - 2021-10-25	97	Canucks	5	Wolf Pack	1	W			Sommaire du Match
9 - 2021-10-26	114	Comets	3	Canucks	5	W			Sommaire du Match
11 - 2021-10-28	137	Griffins	3	Canucks	5	W			Sommaire du Match
12 - 2021-10-29	150	Canucks	6	Senators	0	W			Sommaire du Match
14 - 2021-10-31	168	Canucks	1	Rocket	2	L			Sommaire du Match
15 - 2021-11-01	176	Canucks	8	Crunch	1	W			Sommaire du Match
16 - 2021-11-02	190	Monsters	6	Canucks	2	L			Sommaire du Match
18 - 2021-11-04	216	Sound Tigers	1	Canucks	7	W			Sommaire du Match
19 - 2021-11-05	222	Canucks	6	Griffins	0	W			Sommaire du Match
22 - 2021-11-08	254	Marlies	0	Canucks	1	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	100	0
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
0	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	1,610,474$	1,609,807$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0	0

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

Afficher ou Masquer des Colonnes

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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

	Canucks
	GP: 16 \| W: 13 \| L: 3 \| OTL: 0 \| P: 26 GF: 74 \| GA: 32 \| PP%: 22.03% \| PK%: 86.44% DG: Rob \| Morale : 50 \| Moyenne d'Équipe : 59