Ligue de Hockey Simulé de l'Estrie

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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	Mattias Janmark (C)	X				100.00	54	34	88	85	62	80	95	59	53	58	61	77	58	63	73	0	50	74	0
2	Garnet Hathaway			X		100.00	97	48	79	83	69	70	84	54	50	48	59	83	57	66	81	0	49	74	0
3	Anthony Beauvillier		X			100.00	74	33	92	87	54	78	95	60	51	53	68	69	64	48	68	0	50	73	0
4	Mathieu Joseph (R)			X		100.00	92	34	86	86	61	71	85	59	48	54	64	68	60	48	70	0	46	73	0
5	Markus Granlund		X			100.00	64	34	90	87	55	78	87	57	56	50	64	86	74	60	74	0	50	73	0
6	Brendan Perlini		X			100.00	67	35	87	83	72	73	83	58	48	50	66	61	64	51	66	0	50	71	0
7	Brett Ritchie			X		100.00	95	43	81	82	77	68	74	51	49	44	57	58	55	60	72	0	50	69	0
8	Adam Erne		X			100.00	91	41	88	82	69	67	66	54	49	51	56	63	54	54	70	0	50	69	0
9	William Carrier		X			100.00	99	41	82	82	70	69	61	52	49	43	60	62	58	57	72	0	50	69	0
10	Ryan Donato (R)	X				100.00	53	34	94	85	60	70	68	58	48	55	60	55	62	51	63	0	50	68	0
11	Jordan Weal	X				100.00	53	33	91	86	51	72	74	56	67	53	58	62	64	63	69	0	50	67	0
12	Jaret Anderson-Dolan (R)	X				100.00	47	34	95	84	56	56	25	46	47	41	50	60	50	42	54	0	50	57	0
13	Brendan Smith (A)				X	100.00	77	46	77	85	61	70	71	56	50	54	57	75	55	72	80	0	50	73	0
14	David Schlemko				X	100.00	67	32	93	85	58	63	43	54	51	55	53	82	54	78	82	0	50	71	0
15	Yannick Weber				X	100.00	70	33	89	83	57	58	74	53	50	52	55	75	53	75	79	0	50	70	0
16	Maxime Lajoie (R)				X	100.00	57	32	90	87	55	71	68	59	48	53	64	69	60	48	65	0	50	69	0
17	Mike Reilly				X	100.00	60	32	92	85	59	69	66	55	49	55	55	64	54	60	69	0	50	68	0
18	Libor Hajek (R)				X	100.00	51	33	93	83	64	52	25	52	47	45	58	71	56	45	60	0	50	63	0
Rayé
1	Phillip Di Giuseppe		X			100.00	72	36	93	84	59	63	42	50	49	46	53	59	54	60	68	0	50	63	0
2	Jacob Josefson	X				100.00	53	32	94	83	61	59	39	48	52	44	52	65	59	66	69	0	50	62	0
3	Timothy Gettinger (R)		X			100.00	50	36	95	82	81	67	25	45	47	40	50	61	50	45	56	0	50	61	0
4	Luke Johnson (R)	X				100.00	55	33	95	85	53	58	25	46	51	41	50	62	50	57	63	0	50	59	0
5	Victor Ejdsell (R)	X				100.00	45	30	95	82	77	50	25	45	40	40	50	55	50	54	59	0	50	58	0
6	Tyler Randell			X		100.00	45	30	95	83	63	50	25	45	40	40	50	55	50	66	65	0	50	58	0
7	Nicholas Baptiste (R)			X		100.00	45	30	95	82	66	50	25	45	40	40	50	55	50	54	59	0	51	57	0
8	Brendan Ranford (R)		X			100.00	45	30	95	83	55	50	25	45	40	40	50	55	50	63	63	0	50	57	0
9	Anton Rodin			X		100.00	45	30	95	84	55	50	25	45	40	40	50	55	50	69	66	0	50	57	0
10	Griffen Molino (R)	X				100.00	45	30	95	87	50	50	25	45	40	40	50	55	50	57	60	0	50	56	0
11	Igor Ozhiganov (R)				X	100.00	65	33	92	83	66	65	64	53	49	49	56	63	54	63	70	0	50	68	0
12	Casey Nelson				X	100.00	67	36	92	86	56	65	45	53	49	53	54	69	53	63	72	0	50	68	0
13	Jaycob Megna (R)				X	100.00	56	34	94	82	78	58	34	50	49	48	52	68	51	63	69	0	50	66	0
14	Anthony Bitetto				X	100.00	71	35	92	82	64	61	42	51	49	51	51	60	50	69	73	0	50	65	0
15	Brad Hunt				X	100.00	51	30	94	84	49	64	50	56	50	55	59	60	60	75	75	0	50	65	0
16	Justin Holl				X	100.00	48	32	95	84	69	63	25	49	49	46	52	56	52	63	65	0	50	62	0
17	Gavin Bayreuther (R)				X	100.00	49	32	94	84	59	57	25	51	48	48	54	61	53	57	64	0	50	61	0
18	Libor Sulak (R)				X	100.00	53	32	95	82	65	52	25	48	48	45	50	63	50	57	64	0	49	61	0
19	Chris Bigras				X	100.00	47	31	95	85	58	56	25	46	48	45	50	56	50	54	60	0	50	59	0
20	Daniel Brickley (R)				X	100.00	47	32	95	84	66	51	25	48	48	46	50	56	50	54	60	0	50	59	0
21	Roland McKeown (R)				X	100.00	45	31	95	84	59	50	25	45	47	45	50	55	50	51	58	0	50	58	0

	MOYENNE D'ÉQUIPE					100.00	61	34	91	84	62	62	49	51	48	48	55	64	55	59	67	0	50	65

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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	Anders Nilsson	100.00	77	47	92	86	67	80	80	77	72	69	59	69	71	0	50	74	0
2	Michal Neuvirth	100.00	77	31	75	77	75	72	77	76	75	67	69	77	69	0	50	71	0
Rayé
1	Joni Ortio	100.00	62	26	67	72	65	62	62	62	62	65	55	65	56	0	57	60	0
2	Matthew O'Connor (R)	100.00	60	25	81	79	56	60	60	60	60	65	55	61	53	0	50	58	0
3	Zane McIntyre (R)	100.00	60	25	74	76	59	60	60	60	60	65	55	61	53	0	50	58	0

	MOYENNE D'ÉQUIPE	100.00	67	31	78	78	64	67	68	67	66	66	59	67	60	0	51	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Bob Boughner	79	80	90	83	73	74	77	CAN	48	2	1,300,000$

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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	GA	TA	P/20	S1	S2	S3
1	Ryan Donato	Monster (TOR)	C	5	1	4	5	3	0	5	6	11	7	8	9.09%	0	79	15.82	0	2	2	2	7	0	0	0	0	44.07%	59	3	2	1.26	0	0	1
2	Anthony Beauvillier	Monster (TOR)	LW	5	2	2	4	-2	4	10	3	21	4	12	9.52%	1	100	20.05	1	0	1	1	8	0	0	1	1	16.67%	6	10	8	0.80	1	0	0
3	Mattias Janmark	Monster (TOR)	C	5	1	3	4	-2	0	4	9	20	3	8	5.00%	2	102	20.54	0	1	1	1	8	2	4	0	0	56.92%	130	4	2	0.78	0	0	1
4	Mathieu Joseph	Monster (TOR)	RW	5	1	2	3	-3	6	6	4	13	3	14	7.69%	2	99	19.94	0	1	1	0	8	0	0	0	0	42.86%	7	3	5	0.60	0	1	0
5	Garnet Hathaway	Monster (TOR)	RW	5	2	1	3	3	4	4	5	11	0	4	18.18%	0	86	17.32	1	1	2	2	7	0	5	0	0	0.00%	2	1	1	0.69	0	0	0
6	Yannick Weber	Monster (TOR)	D	5	0	3	3	1	0	10	4	7	2	2	0.00%	8	126	25.35	0	1	1	1	9	0	13	0	0	0.00%	0	2	6	0.47	0	0	1
7	Mike Reilly	Monster (TOR)	D	5	1	1	2	-1	4	0	8	1	3	2	100.00%	6	80	16.09	1	0	1	1	7	0	1	0	0	0.00%	0	3	5	0.50	0	0	0
8	Brendan Perlini	Monster (TOR)	LW	5	1	1	2	3	0	7	1	13	4	8	7.69%	3	82	16.48	0	0	0	0	8	0	0	0	0	0.00%	3	2	4	0.49	0	1	0
9	Markus Granlund	Monster (TOR)	LW	5	0	1	1	0	0	7	6	5	3	6	0.00%	4	78	15.73	0	0	0	0	0	0	13	0	0	75.00%	4	4	2	0.25	0	0	0
10	Maxime Lajoie	Monster (TOR)	D	5	1	0	1	-1	2	1	9	3	2	2	33.33%	3	81	16.31	0	0	0	0	7	0	2	0	0	0.00%	0	2	5	0.25	0	0	0
11	David Schlemko	Monster (TOR)	D	5	0	1	1	0	0	7	4	9	3	3	0.00%	9	104	20.86	0	0	0	0	0	0	8	0	0	0.00%	0	3	7	0.19	0	0	0
12	Jordan Weal	Monster (TOR)	C	5	1	0	1	0	0	3	4	12	3	7	8.33%	0	68	13.78	0	0	0	0	0	0	5	0	0	48.00%	25	6	0	0.29	0	0	0
13	Libor Hajek	Monster (TOR)	D	5	0	0	0	0	0	2	5	3	0	3	0.00%	5	94	18.94	0	0	0	0	1	0	10	0	0	0.00%	0	1	5	0.00	0	0	0
14	Brett Ritchie	Monster (TOR)	RW	5	0	0	0	-1	0	7	2	12	2	2	0.00%	1	48	9.70	0	0	0	0	1	0	0	0	0	0.00%	0	2	2	0.00	0	0	0
15	Adam Erne	Monster (TOR)	LW	4	0	0	0	1	4	6	4	5	1	4	0.00%	3	48	12.06	0	0	0	0	0	0	3	0	0	0.00%	2	1	1	0.00	0	0	0
16	William Carrier	Monster (TOR)	LW	5	0	0	0	-1	0	5	1	6	2	10	0.00%	0	46	9.27	0	0	0	0	0	0	0	0	0	0.00%	0	1	2	0.00	0	0	0
17	Jaret Anderson-Dolan	Monster (TOR)	C	5	0	0	0	-1	0	5	8	5	0	4	0.00%	0	60	12.16	0	0	0	0	0	1	11	0	0	48.57%	35	0	1	0.00	0	0	0
18	Brendan Smith	Monster (TOR)	D	5	0	0	0	1	8	12	8	8	3	3	0.00%	9	134	26.84	0	0	0	0	8	0	9	0	0	0.00%	0	4	6	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				89	11	19	30	0	32	101	91	165	45	102	6.67%	56	1524	17.12	3	6	9	8	88	3	90	1	1	49.82%	273	52	64	0.39	1	2	3

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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
1	Anders Nilsson	Monster (TOR)	5	1	3	1	0.920	2.50	312	0	0	13	163	87	0	1	0.000	0	5	0	0	0	0
Stats d'équipe Total ou en Moyenne			5	1	3	1	0.920	2.50	312	0	0	13	163	87	0	1	0.000	0	5	0	0	0	0

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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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Adam Erne	Monster (TOR)	LW	25	1995-01-01	No	214 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Lien NHL
Anders Nilsson	Monster (TOR)	G	30	1990-01-01	No	232 Lbs	6 ft6	No	No	No	1	Pro & Farm	1,550,000$	0$	0$	No				Lien NHL
Anthony Beauvillier	Monster (TOR)	LW	23	1997-01-01	No	182 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,000,000$	0$	0$	No				Lien NHL
Anthony Bitetto	Monster (TOR)	D	30	1990-01-01	No	210 Lbs	6 ft1	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$		Lien / Lien NHL
Anton Rodin	Monster (TOR)	RW	30	1990-01-01	No	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	700,000$	0$	0$	No
Brad Hunt	Monster (TOR)	D	32	1988-01-01	No	187 Lbs	5 ft9	No	No	No	1	Pro & Farm	1,000,000$	0$	0$	No				Lien / Lien NHL
Brendan Perlini	Monster (TOR)	LW	24	1996-01-01	No	211 Lbs	6 ft3	No	No	No	4	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$	1,000,000$	1,000,000$	Lien NHL
Brendan Ranford	Monster (TOR)	LW	28	1992-01-01	Yes	190 Lbs	5 ft10	No	No	No	1	Pro & Farm	600,000$	0$	0$	No
Brendan Smith	Monster (TOR)	D	31	1989-01-01	No	195 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$			Lien / Lien NHL
Brett Ritchie	Monster (TOR)	RW	27	1993-01-01	No	220 Lbs	6 ft4	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Lien NHL
Casey Nelson	Monster (TOR)	D	28	1992-01-01	No	185 Lbs	6 ft1	No	No	No	3	Pro & Farm	900,000$	0$	0$	No	900,000$	900,000$		Lien / Lien NHL
Chris Bigras	Monster (TOR)	D	25	1995-01-01	No	190 Lbs	6 ft1	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Daniel Brickley	Monster (TOR)	D	25	1995-01-01	Yes	203 Lbs	6 ft3	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
David Schlemko	Monster (TOR)	D	33	1987-01-01	No	191 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,600,000$	0$	0$	No				Lien / Lien NHL
Garnet Hathaway	Monster (TOR)	RW	29	1991-01-01	No	210 Lbs	6 ft2	No	No	No	2	Pro & Farm	900,000$	0$	0$	No	900,000$			Lien NHL
Gavin Bayreuther	Monster (TOR)	D	26	1994-01-01	Yes	195 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien
Griffen Molino	Monster (TOR)	C	26	1994-01-01	Yes	171 Lbs	5 ft11	No	No	No	1	Pro & Farm	600,000$	0$	0$	No
Igor Ozhiganov	Monster (TOR)	D	28	1992-01-01	Yes	210 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien
Jacob Josefson	Monster (TOR)	C	29	1991-01-01	No	196 Lbs	6 ft0	No	No	No	2	Pro & Farm	900,000$	0$	0$	No	900,000$			Lien NHL
Jaret Anderson-Dolan	Monster (TOR)	C	21	1999-01-01	Yes	188 Lbs	5 ft11	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$
Jaycob Megna	Monster (TOR)	D	28	1992-01-01	Yes	221 Lbs	6 ft6	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$		Lien / Lien NHL
Joni Ortio	Monster (TOR)	G	29	1991-01-01	No	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	600,000$	0$	0$	No
Jordan Weal	Monster (TOR)	C	28	1992-01-01	No	179 Lbs	5 ft10	No	No	No	4	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$	800,000$	Lien NHL
Justin Holl	Monster (TOR)	D	28	1992-01-01	No	205 Lbs	6 ft4	No	No	No	3	Pro & Farm	950,000$	0$	0$	No	950,000$	950,000$		Lien / Lien NHL
Libor Hajek	Monster (TOR)	D	22	1998-01-01	Yes	204 Lbs	6 ft2	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Lien
Libor Sulak	Monster (TOR)	D	26	1994-01-01	Yes	207 Lbs	6 ft2	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien
Luke Johnson	Monster (TOR)	C	26	1994-01-01	Yes	179 Lbs	5 ft11	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$
Markus Granlund	Monster (TOR)	LW	27	1993-01-01	No	180 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$			Lien NHL
Mathieu Joseph	Monster (TOR)	RW	23	1997-01-01	Yes	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	550,000$	0$	0$	No
Matthew O'Connor	Monster (TOR)	G	28	1992-01-01	Yes	205 Lbs	6 ft6	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$
Mattias Janmark	Monster (TOR)	C	28	1992-01-01	No	195 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,100,000$	0$	0$	No	1,100,000$	1,100,000$		Lien NHL
Maxime Lajoie	Monster (TOR)	D	23	1997-01-01	Yes	183 Lbs	6 ft1	No	No	No	1	Pro & Farm	550,000$	0$	0$	No				Lien
Michal Neuvirth	Monster (TOR)	G	32	1988-01-01	No	209 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$			Lien NHL
Mike Reilly	Monster (TOR)	D	27	1993-01-01	No	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	950,000$	0$	0$	No	950,000$			Lien / Lien NHL
Nicholas Baptiste	Monster (TOR)	RW	25	1995-01-01	Yes	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No				Lien NHL
Phillip Di Giuseppe	Monster (TOR)	LW	27	1993-01-01	No	192 Lbs	6 ft0	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$			Lien NHL
Roland McKeown	Monster (TOR)	D	24	1996-01-01	Yes	195 Lbs	6 ft1	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien / Lien NHL
Ryan Donato	Monster (TOR)	C	24	1996-01-01	Yes	193 Lbs	6 ft0	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$			Lien NHL
Timothy Gettinger	Monster (TOR)	LW	22	1998-01-01	Yes	220 Lbs	6 ft6	No	No	No	1	Pro & Farm	550,000$	0$	0$	No
Tyler Randell	Monster (TOR)	RW	29	1991-01-01	No	198 Lbs	6 ft1	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$
Victor Ejdsell	Monster (TOR)	C	25	1995-01-01	Yes	214 Lbs	6 ft5	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Lien NHL
William Carrier	Monster (TOR)	LW	26	1994-01-01	No	212 Lbs	6 ft2	No	No	No	1	Pro & Farm	800,000$	0$	0$	No				Lien NHL
Yannick Weber	Monster (TOR)	D	32	1988-01-01	No	200 Lbs	5 ft11	No	No	No	3	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$	1,000,000$		Lien / Lien NHL
Zane McIntyre	Monster (TOR)	G	28	1992-01-01	Yes	206 Lbs	6 ft2	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
44	26.98	199 Lbs	6 ft1	2.00	832,386$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Anthony Beauvillier	Mattias Janmark	Mathieu Joseph	40	1	2	2
2	Brendan Perlini	Ryan Donato	Garnet Hathaway	30	1	2	2
3	Adam Erne	Jordan Weal	Markus Granlund	20	1	2	2
4	William Carrier	Jaret Anderson-Dolan	Brett Ritchie	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Brendan Smith	40	1	2	2
2	Libor Hajek	David Schlemko	30	1	2	2
3	Maxime Lajoie	Mike Reilly	20	1	2	2
4	Brendan Smith	David Schlemko	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Anthony Beauvillier	Mattias Janmark	Mathieu Joseph	60	1	2	2
2	Brendan Perlini	Ryan Donato	Garnet Hathaway	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Brendan Smith	60	1	2	2
2	Mike Reilly	Maxime Lajoie	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jaret Anderson-Dolan	Markus Granlund	60	1	2	2
2	Jordan Weal	Garnet Hathaway	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Brendan Smith	60	1	2	2
2	Libor Hajek	David Schlemko	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Markus Granlund	60	1	2	2	Yannick Weber	Brendan Smith	60	1	2	2
2	Garnet Hathaway	40	1	2	2	Libor Hajek	David Schlemko	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mattias Janmark	Anthony Beauvillier	60	1	2	2
2	Ryan Donato	Brendan Perlini	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Yannick Weber	Brendan Smith	60	1	2	2
2	Mike Reilly	Libor Hajek	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Anthony Beauvillier	Mattias Janmark	Mathieu Joseph	Mike Reilly	Brendan Smith

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Markus Granlund	Ryan Donato	Garnet Hathaway	Yannick Weber	David Schlemko

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Adam Erne, Mathieu Joseph, Brendan Perlini	Mattias Janmark, Anthony Beauvillier	Markus Granlund

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Maxime Lajoie, Mike Reilly, Libor Hajek	Brendan Smith	Libor Hajek, Yannick Weber

Tirs de Pénalité
Mattias Janmark, Mathieu Joseph, Markus Granlund, Anthony Beauvillier, Brendan Perlini

Gardien
#1 : Anders Nilsson, #2 : Michal Neuvirth

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

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

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	Heat	5	1	4	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	4	7	-3	3	1	2	0	0	0	0	0	7	7	0	2	0.200	11	19	30	1	0	2	3	6	0	165	38	41	67	19	164	56	32	101	12	3	25.00%	16	6	62.50%	0	50	107	46.73%	51	101	50.50%	35	65	53.85%	107	58	109	47	96	49
	Total	5	1	4	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	4	7	-3	3	1	2	0	0	0	0	0	7	7	0	2	0.200	11	19	30	1	0	2	3	6	0	165	38	41	67	19	164	56	32	101	12	3	25.00%	16	6	62.50%	0	50	107	46.73%	51	101	50.50%	35	65	53.85%	107	58	109	47	96	49
	_Since Last GM Reset	5	1	4	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	4	7	-3	3	1	2	0	0	0	0	0	7	7	0	2	0.200	11	19	30	1	0	2	3	6	0	165	38	41	67	19	164	56	32	101	12	3	25.00%	16	6	62.50%	0	50	107	46.73%	51	101	50.50%	35	65	53.85%	107	58	109	47	96	49
	_Vs Conference	5	1	4	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	4	7	-3	3	1	2	0	0	0	0	0	7	7	0	2	0.200	11	19	30	1	0	2	3	6	0	165	38	41	67	19	164	56	32	101	12	3	25.00%	16	6	62.50%	0	50	107	46.73%	51	101	50.50%	35	65	53.85%	107	58	109	47	96	49

			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
5	2	L3	11	19	30	165	164	56	32	101	1	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	11	14

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	4	7

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	7	7

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
1	3	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
12	3	25.00%	16	6	62.50%	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
38	41	67	19	2	3	6	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
50	107	46.73%	51	101	50.50%	35	65	53.85%

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
107	58	109	47	96	49

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	Lien
1 - 2020-07-20	8	Monster	3	Heat	4	L	X	Sommaire du Match
2 - 2020-07-21	16	Monster	3	Heat	1	W		Sommaire du Match
3 - 2020-07-22	24	Heat	4	Monster	2	L		Sommaire du Match
4 - 2020-07-23	32	Heat	3	Monster	2	L		Sommaire du Match
5 - 2020-07-24	40	Monster	1	Heat	2	L		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	3,994	1,994
Assistance PCT	99.85%	99.70%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
37	2994 - 99.80%	97,577$	195,154$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	3,662,500$	3,662,500$	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
Saison Régulière
11	78	41	21	0	2	3	7	4	251	176	75	39	21	8	0	1	1	4	4	125	89	36	39	20	13	0	1	2	3	0	126	87	39	82	251	390	641	1	3	46	104	92	14	2666	755	1024	851	76	2318	771	547	1687	309	136	44.01%	264	97	63.26%	5	1082	1764	61.34%	1038	1747	59.42%	689	1140	60.44%	1754	992	1567	698	1426	745
12	82	38	30	0	4	2	7	1	227	194	33	41	20	14	0	2	0	4	1	113	100	13	41	18	16	0	2	2	3	0	114	94	20	76	227	354	581	2	2	42	87	87	14	2530	728	863	915	48	2515	877	774	1803	295	105	35.59%	325	109	66.46%	5	1002	1752	57.19%	1159	1954	59.31%	687	1145	60.00%	1809	983	1631	745	1527	807
13	82	33	30	0	2	5	8	4	223	231	-8	41	16	15	0	1	2	4	3	110	103	7	41	17	15	0	1	3	4	1	113	128	-15	66	223	344	567	4	4	30	91	92	16	2655	732	990	898	83	2726	867	814	1845	295	112	37.97%	347	125	63.98%	4	968	1807	53.57%	1021	1956	52.20%	606	1176	51.53%	1801	991	1703	740	1489	776
14	82	41	21	0	1	4	7	8	216	179	37	41	19	10	0	1	1	5	5	98	80	18	41	22	11	0	0	3	2	3	118	99	19	82	216	331	547	2	5	27	84	97	18	2655	700	978	947	92	2519	903	546	1886	298	114	38.26%	265	90	66.04%	1	997	1822	54.72%	1054	1821	57.88%	611	1120	54.55%	1827	1016	1672	738	1502	782
15	82	41	26	0	3	3	7	2	254	194	60	41	20	13	0	2	1	4	1	133	104	29	41	21	13	0	1	2	3	1	121	90	31	82	254	407	661	1	8	31	121	92	14	2582	666	966	936	40	2521	826	698	1837	305	127	41.64%	327	109	66.67%	4	1006	1737	57.92%	1058	1824	58.00%	689	1194	57.71%	1777	975	1713	739	1483	770
16	82	39	29	0	2	3	4	5	257	220	37	41	23	14	0	0	2	1	1	129	102	27	41	16	15	0	2	1	3	4	128	118	10	78	257	410	667	3	2	45	98	108	13	2596	690	959	924	58	2620	893	667	1774	301	129	42.86%	331	125	62.24%	4	949	1694	56.02%	1060	1873	56.59%	672	1238	54.28%	1780	975	1736	720	1466	778
17	82	36	33	0	1	5	2	5	222	207	15	41	22	13	0	0	2	1	3	133	101	32	41	14	20	0	1	3	1	2	89	106	-17	72	222	366	588	3	0	30	99	90	3	2660	697	972	975	37	2522	860	598	1855	299	123	41.14%	298	109	63.42%	2	1016	1765	57.56%	1037	1843	56.27%	650	1113	58.40%	1834	1027	1666	714	1469	780
18	82	30	32	0	5	3	11	1	253	210	43	41	16	12	0	4	1	7	1	137	99	38	41	14	20	0	1	2	4	0	116	111	5	60	253	398	651	3	0	32	99	106	24	2616	729	948	903	73	2532	861	717	1817	331	128	38.67%	348	111	68.10%	5	994	1745	56.96%	1044	1869	55.86%	639	1182	54.06%	1834	1019	1687	725	1474	783
19	82	34	30	0	2	3	7	6	242	197	45	41	16	16	0	1	2	4	2	119	104	15	41	18	14	0	1	1	3	4	123	93	30	68	242	359	601	0	3	38	100	95	16	2567	696	917	923	86	2475	821	685	1865	316	122	38.61%	336	103	69.35%	4	924	1704	54.23%	1010	1834	55.07%	614	1135	54.10%	1787	974	1711	739	1501	789
20	78	39	24	0	2	5	7	1	233	189	44	39	18	13	0	1	2	4	1	109	99	10	39	21	11	0	1	3	3	0	124	90	34	78	233	348	581	3	4	28	95	101	15	2451	700	861	861	55	2351	789	520	1787	317	117	36.91%	259	92	64.48%	3	865	1672	51.73%	884	1722	51.34%	550	1069	51.45%	1725	963	1611	694	1402	734
Total Saison Régulière	812	372	276	0	24	36	67	37	2378	1997	381	406	191	128	0	13	14	38	22	1206	981	225	406	181	148	0	11	22	29	15	1172	1016	156	744	2378	3707	6085	22	31	349	978	960	147	25978	7093	9478	9133	648	25099	8468	6566	18156	3066	1213	39.56%	3100	1070	65.48%	37	9803	17462	56.14%	10365	18443	56.20%	6407	11512	55.65%	17934	9922	16702	7257	14744	7749
Séries
11	5	1	4	0	0	0	0	0	9	15	-6	3	0	3	0	0	0	0	0	4	9	-5	2	1	1	0	0	0	0	0	5	6	-1	2	9	13	22	0	0	1	6	1	1	179	50	82	38	9	135	50	40	131	12	4	33.33%	20	11	45.00%	0	58	109	53.21%	57	96	59.38%	39	67	58.21%	122	70	88	44	101	50
12	6	2	4	0	0	0	0	0	10	12	-2	3	1	2	0	0	0	0	0	4	5	-1	3	1	2	0	0	0	0	0	6	7	-1	4	10	15	25	0	0	2	3	5	0	185	49	59	75	2	198	78	102	153	17	6	35.29%	31	9	70.97%	0	74	147	50.34%	71	157	45.22%	40	68	58.82%	128	68	120	56	112	57
14	10	5	5	0	0	0	0	0	27	22	5	5	3	2	0	0	0	0	0	15	10	5	5	2	3	0	0	0	0	0	12	12	0	10	27	46	73	0	1	3	10	13	1	350	93	141	108	8	343	132	78	243	42	9	21.43%	40	8	80.00%	0	122	231	52.81%	145	237	61.18%	76	143	53.15%	225	123	203	94	189	98
15	7	3	4	0	0	0	0	0	20	20	0	3	2	1	0	0	0	0	0	12	10	2	4	1	3	0	0	0	0	0	8	10	-2	6	20	36	56	0	0	5	6	8	1	220	59	85	70	6	205	74	62	156	25	8	32.00%	31	9	70.97%	0	68	152	44.74%	78	169	46.15%	41	91	45.05%	144	75	150	67	133	65
16	7	3	4	0	0	0	0	0	20	20	0	3	2	1	0	0	0	0	0	12	10	2	4	1	3	0	0	0	0	0	8	10	-2	6	20	36	56	0	0	5	6	8	1	220	59	85	70	6	205	74	62	156	25	8	32.00%	31	9	70.97%	0	68	152	44.74%	78	169	46.15%	41	91	45.05%	144	75	150	67	133	65
18	5	1	4	0	0	0	0	0	5	8	-3	2	1	1	0	0	0	0	0	2	2	0	3	0	3	0	0	0	0	0	3	6	-3	2	5	7	12	0	1	1	4	0	0	177	52	57	64	4	88	31	57	144	6	1	16.67%	27	7	74.07%	0	63	124	50.81%	47	81	58.02%	31	47	65.96%	121	67	86	49	101	49
20	5	1	4	0	0	0	0	0	11	14	-3	2	0	2	0	0	0	0	0	4	7	-3	3	1	2	0	0	0	0	0	7	7	0	2	11	19	30	1	0	2	3	6	0	165	38	41	67	19	164	56	32	101	12	3	25.00%	16	6	62.50%	0	50	107	46.73%	51	101	50.50%	35	65	53.85%	107	58	109	47	96	49
Total Séries	45	16	29	0	0	0	0	0	102	111	-9	21	9	12	0	0	0	0	0	53	53	0	24	7	17	0	0	0	0	0	49	58	-9	32	102	172	274	1	2	19	38	41	4	1496	400	550	492	54	1338	495	433	1084	139	39	28.06%	196	59	69.90%	0	503	1022	49.22%	527	1010	52.18%	303	572	52.97%	994	538	908	428	868	437