Ligue de Hockey Simulé du Saguenay

Maple Leafs
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance

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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	TA	SP	Âge	Contrat	Salaire
1	Tim Schaller (R) (C)		X			100.00	80	31	74	79	74	71	77	74	67	76	70	66	67	66	62	36	79	71		0	25	1	995,000$
2	Linden Vey (R)			X		100.00	71	33	77	75	68	72	74	73	76	76	75	61	68	52	49	41	70	70		0	24	1	750,000$
3	Ryan Dzingel (R)		X			100.00	67	38	79	71	71	72	68	67	69	70	70	63	70	57	55	46	42	68	X	0	23	2	800,000$
4	JT Compher (R)		X			100.00	63	28	83	72	76	71	75	76	60	64	79	55	68	45	42	65	41	68		0	20	2	800,000$
5	Colton Sissons (R)	X				100.00	75	51	70	72	72	66	68	72	77	68	63	64	71	45	44	45	85	67	X	0	22	3	700,000$
6	Lucas Lessio (R)		X			100.00	59	31	75	72	67	70	69	73	61	67	79	61	65	46	44	47	77	67		0	22	2	550,000$
7	Justin Bailey (R)			X		100.00	66	34	83	59	74	68	64	71	72	70	83	49	64	44	42	63	78	67		0	20	2	900,000$
8	Shane Prince (R)	X				100.00	64	35	79	63	77	70	71	63	71	64	74	52	66	54	53	41	39	65		0	23	1	650,000$
9	Tom Kuhnhackl (R)			X		100.00	61	31	74	73	71	69	69	69	61	68	65	63	70	45	45	39	71	65		0	23	1	700,000$
10	Pavel Zacha (R)	X				100.00	61	27	77	58	73	62	59	68	65	69	84	49	64	40	40	83	67	64		0	18	2	500,000$
11	Christian Fischer (R)			X		100.00	67	33	74	53	80	65	60	63	60	67	82	43	59	40	40	82	52	63		0	18	2	500,000$
12	Aleksi Saarela (R)	X				100.00	53	25	68	76	50	55	45	70	55	60	66	44	71	40	40	80	64	59		0	18	2	500,000$
13	Tim Erixon (R)				X	100.00	72	40	83	70	69	79	69	73	59	70	64	75	63	53	46	39	55	70		0	24	2	950,000$
14	Shane Sims				X	100.00	67	24	79	76	72	79	72	68	59	74	70	72	62	66	49	26	57	70		0	27	1	500,000$
15	Dmitry Sinitsyn (R)				X	100.00	65	25	82	77	68	67	76	75	41	73	56	75	55	45	43	60	58	69		0	21	1	999,999$
16	Haydn Fleury (R)				X	100.00	68	35	86	69	72	57	72	60	33	66	52	84	51	43	41	67	68	68		0	19	1	500,000$
17	Neal Pionk (R)				X	100.00	60	33	86	76	54	59	69	83	38	79	64	71	47	43	44	66	59	67		0	20	2	500,000$
18	Brett Pesce (R)				X	100.00	59	30	76	81	66	64	72	73	38	81	59	68	49	47	43	52	58	67		0	21	2	650,000$
19	Jeff Corbett (R)				X	100.00	65	35	82	54	49	71	64	60	38	69	72	62	55	44	43	50	46	63		0	21	2	600,000$
Rayé
1	Johan Larsson (R)		X			100.00	61	36	72	71	60	68	63	66	72	73	69	46	60	45	45	45	19	64	X	0	23	1	600,000$
2	Mitchell Moroz (R)		X			100.00	72	34	66	60	71	51	69	63	56	65	65	60	54	43	43	45	19	61		0	21	1	600,000$
3	Henri Ikonen (R)		X			100.00	68	41	60	62	59	44	69	62	55	63	62	54	42	42	42	49	19	58		0	20	2	500,000$
4	Jakob Forsbacka-Karlsson (R)	X				100.00	63	34	60	64	51	54	49	49	56	47	65	48	49	42	42	63	20	54	X	0	19	2	600,000$
5	Zack MacEwen (R)	X				100.00	59	39	56	57	65	56	64	52	47	56	57	46	48	42	43	52	20	54		0	19	2	500,000$
6	Conner Bleackley (R)	X				100.00	60	25	57	47	62	47	46	55	48	57	58	43	51	41	41	64	19	52	X	0	19	1	350,000$
7	Jaden Lindo (R)			X		100.00	59	28	59	48	60	49	48	57	47	56	58	44	52	41	41	62	20	52		0	19	1	300,000$
8	Radovan Bondra (R)			X		100.00	61	21	53	47	49	39	54	54	35	56	49	45	37	40	40	60	19	48		0	18	2	400,000$
9	Dennis Gilbert (R)				X	100.00	65	33	67	59	51	58	58	42	33	62	43	66	31	41	42	57	19	57		0	19	2	500,000$
10	Brycen Martin (R)				X	100.00	51	26	57	64	48	39	47	63	19	65	42	60	33	41	41	64	20	54		0	19	2	300,000$
11	Simon Bourque (R)				X	100.00	35	28	49	51	41	39	54	51	23	57	32	54	40	40	40	65	20	46	X	0	18	2	400,000$

	MOYENNE D'ÉQUIPE					100.00	63	32	71	65	64	61	64	65	53	66	64	58	56	46	44	55	46	62

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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	TA	SP
1	Al Montoya	100.00	76	75	78	69	72	78	77	76	73	78	70	72	70	22	83	75		1
2	Malcolm Subban	100.00	67	72	83	67	65	77	84	67	65	87	66	51	46	52	81	71		0
Rayé
1	Charlie Lindgren (R)	100.00	69	73	76	53	60	88	75	53	49	75	73	49	46	64	20	65	X	0
2	Jamie Phillips	100.00	73	65	78	54	54	75	70	56	51	74	60	46	44	39	19	62	X	0

	MOYENNE D'ÉQUIPE	100.00	71	71	79	61	63	80	77	63	60	79	67	55	52	44	51	68

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Larry Robinson	77	93	56	82	99	83	45	CAN	60	1	500,000$

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

#	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

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

#	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

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

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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3
Al Montoya	Influenza (Tor)	G	30	1985-01-01	No	195 Lbs	6 ft2	No	No	No	1	Pro & Farm	500,000$	0$	0$	No
Aleksi Saarela	Influenza (Tor)	C	18	1997-01-01	Yes	200 Lbs	5 ft10	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Brett Pesce	Influenza (Tor)	D	21	1994-01-01	Yes	185 Lbs	6 ft3	No	No	No	2	Pro & Farm	650,000$	0$	0$	No	650,000$
Brycen Martin	Influenza (Tor)	D	19	1996-01-01	Yes	198 Lbs	6 ft2	No	No	No	2	Pro & Farm	300,000$	0$	0$	No	300,000$
Charlie Lindgren	Influenza (Tor)	G	22	1993-01-01	Yes	180 Lbs	6 ft1	No	Yes	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Christian Fischer	Influenza (Tor)	RW	18	1997-01-01	Yes	214 Lbs	6 ft2	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Colton Sissons	Influenza (Tor)	C	22	1993-01-01	Yes	187 Lbs	6 ft0	No	Yes	No	3	Pro & Farm	700,000$	0$	0$	No	800,000$	900,000$
Conner Bleackley	Influenza (Tor)	C	19	1996-01-01	Yes	195 Lbs	5 ft11	No	Yes	No	1	Pro & Farm	350,000$	0$	0$	No
Dennis Gilbert	Influenza (Tor)	D	19	1996-01-01	Yes	216 Lbs	6 ft2	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Dmitry Sinitsyn	Influenza (Tor)	D	21	1994-01-01	Yes	200 Lbs	6 ft2	No	No	No	1	Pro & Farm	999,999$	0$	0$	No
Haydn Fleury	Influenza (Tor)	D	19	1996-01-01	Yes	208 Lbs	6 ft3	No	No	No	1	Pro & Farm	500,000$	0$	0$	No
Henri Ikonen	Influenza (Tor)	LW	20	1995-01-01	Yes	185 Lbs	6 ft0	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
JT Compher	Influenza (Tor)	LW	20	1995-01-01	Yes	185 Lbs	5 ft10	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$
Jaden Lindo	Influenza (Tor)	RW	19	1996-01-01	Yes	215 Lbs	6 ft2	No	No	No	1	Pro & Farm	300,000$	0$	0$	No
Jakob Forsbacka-Karlsson	Influenza (Tor)	C	19	1996-01-01	Yes	184 Lbs	6 ft1	No	Yes	No	2	Pro & Farm	600,000$	0$	0$	No	600,000$
Jamie Phillips	Influenza (Tor)	G	22	1993-01-01	No	180 Lbs	6 ft0	No	Yes	No	1	Pro & Farm	500,000$	0$	0$	No
Jeff Corbett	Influenza (Tor)	D	21	1994-01-01	Yes	185 Lbs	6 ft1	No	No	No	2	Pro & Farm	600,000$	0$	0$	No	600,000$
Johan Larsson	Influenza (Tor)	LW	23	1992-01-01	Yes	206 Lbs	5 ft11	No	Yes	No	1	Pro & Farm	600,000$	0$	0$	No
Justin Bailey	Influenza (Tor)	RW	20	1995-01-01	Yes	185 Lbs	6 ft0	No	No	No	2	Pro & Farm	900,000$	0$	0$	No	900,000$
Linden Vey	Influenza (Tor)	RW	24	1991-01-01	Yes	189 Lbs	6 ft0	No	No	No	1	Pro & Farm	750,000$	0$	0$	No
Lucas Lessio	Influenza (Tor)	LW	22	1993-01-01	Yes	213 Lbs	6 ft1	No	No	No	2	Pro & Farm	550,000$	0$	0$	No	600,000$
Malcolm Subban	Influenza (Tor)	G	22	1993-01-01	No	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	800,000$
Mitchell Moroz	Influenza (Tor)	LW	21	1994-01-01	Yes	208 Lbs	6 ft1	No	No	No	1	Pro & Farm	600,000$	0$	0$	No
Neal Pionk	Influenza (Tor)	D	20	1995-01-01	Yes	186 Lbs	6 ft0	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Pavel Zacha	Influenza (Tor)	C	18	1997-01-01	Yes	210 Lbs	6 ft3	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$
Radovan Bondra	Influenza (Tor)	RW	18	1997-01-01	Yes	217 Lbs	6 ft5	No	No	No	2	Pro & Farm	400,000$	0$	0$	No	400,000$
Ryan Dzingel	Influenza (Tor)	LW	23	1992-01-01	Yes	190 Lbs	6 ft0	No	Yes	No	2	Pro & Farm	800,000$	0$	0$	No	900,000$
Shane Prince	Influenza (Tor)	C	23	1992-01-01	Yes	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	650,000$	0$	0$	No
Shane Sims	Influenza (Tor)	D	27	1988-01-01	No	195 Lbs	6 ft1	No	No	No	1	Pro & Farm	500,000$	0$	0$	No
Simon Bourque	Influenza (Tor)	D	18	1997-01-01	Yes	198 Lbs	6 ft1	No	Yes	No	2	Pro & Farm	400,000$	0$	0$	No	400,000$
Tim Erixon	Influenza (Tor)	D	24	1991-01-01	Yes	200 Lbs	6 ft2	No	No	No	2	Pro & Farm	950,000$	0$	0$	No	950,000$
Tim Schaller	Influenza (Tor)	LW	25	1990-01-01	Yes	206 Lbs	6 ft2	No	No	No	1	Pro & Farm	995,000$	0$	0$	No
Tom Kuhnhackl	Influenza (Tor)	RW	23	1992-01-01	Yes	196 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No
Zack MacEwen	Influenza (Tor)	C	19	1996-01-01	Yes	205 Lbs	6 ft3	No	No	No	2	Pro & Farm	500,000$	0$	0$	No	500,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
34	21.15	197 Lbs	6 ft1	1.65	596,912$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Tim Schaller	Colton Sissons	Linden Vey	40	1	2	2
2	JT Compher	Shane Prince	Justin Bailey	30	1	2	2
3	Ryan Dzingel	Pavel Zacha	Tom Kuhnhackl	20	1	2	2
4	Lucas Lessio	Aleksi Saarela	Christian Fischer	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Shane Sims	Tim Erixon	40	1	2	2
2	Dmitry Sinitsyn	Haydn Fleury	30	1	2	2
3	Neal Pionk	Brett Pesce	20	1	2	2
4	Jeff Corbett	Shane Sims	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Tim Schaller	Colton Sissons	Linden Vey	60	1	2	2
2	JT Compher	Shane Prince	Justin Bailey	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Shane Sims	Tim Erixon	60	1	2	2
2	Dmitry Sinitsyn	Haydn Fleury	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tim Schaller	Linden Vey	60	1	2	2
2	JT Compher	Ryan Dzingel	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Shane Sims	Tim Erixon	60	1	2	2
2	Dmitry Sinitsyn	Haydn Fleury	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Tim Schaller	60	1	2	2	Shane Sims	Tim Erixon	60	1	2	2
2	Linden Vey	40	1	2	2	Dmitry Sinitsyn	Haydn Fleury	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Tim Schaller	Linden Vey	60	1	2	2
2	JT Compher	Ryan Dzingel	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Shane Sims	Tim Erixon	60	1	2	2
2	Dmitry Sinitsyn	Haydn Fleury	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tim Schaller	Colton Sissons	Linden Vey	Shane Sims	Tim Erixon

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Tim Schaller	Colton Sissons	Linden Vey	Shane Sims	Tim Erixon

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Lucas Lessio, Tom Kuhnhackl, Pavel Zacha	Lucas Lessio, Tom Kuhnhackl	Pavel Zacha

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Neal Pionk, Brett Pesce, Jeff Corbett	Neal Pionk	Brett Pesce, Jeff Corbett

Tirs de Pénalité
Tim Schaller, Linden Vey, JT Compher, Ryan Dzingel, Colton Sissons

Gardien
#1 : Al Montoya, #2 : Malcolm Subban

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

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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

	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
Capacité	2000	1000
Prix des Billets	40	20
Assistance	0.00%	0.00%
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
40	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$	2,029,500$	1,999,500$	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

	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

	Influenza
	GP: 0 \| W: 0 \| L: 0 GF: 0 \| GA: 0 \| PP%: 0.00% \| PK%: 0.00% DG: Pascal Landry \| Morale : 1 \| Moyenne d'Équipe : 63