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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	Anders Bjork		X	X		100.00	62	40	88	64	72	74	75	62	60	65	61	63	62	67	64	0	50	63	0	23	1	1,066,667$
2	Austin Wagner		X			100.00	87	49	81	63	74	72	83	61	53	60	64	56	63	65	66	0	50	63	0	22	1	925,000$
3	Chris Stewart		X	X		100.00	79	48	80	62	89	61	63	59	52	60	58	61	56	82	73	0	50	63	0	31	1	753,757$
4	Mackenzie MacEachern		X			100.00	82	43	78	61	78	80	71	62	54	55	63	57	62	71	68	0	50	63	0	25	1	750,000$
5	Andy Andreoff	X				100.00	64	53	83	62	78	79	77	61	56	59	60	58	62	77	74	0	50	63	0	28	2	750,000$
6	Mitchell Stephens	X				100.00	59	45	89	61	72	77	73	63	76	60	60	62	64	65	63	0	50	62	0	22	1	919,166$
7	Nathan Bastian			X		100.00	72	53	85	61	87	81	74	59	54	58	60	62	59	65	63	0	50	62	0	21	2	905,000$
8	Michael McLeod	X				100.00	64	49	85	62	78	82	76	63	77	61	58	64	59	63	62	0	50	62	0	21	2	1,363,333$
9	Austin Poganski			X		100.00	62	42	88	60	77	78	80	59	54	60	58	61	59	67	64	0	50	61	0	23	1	762,500$
10	Beck Malenstyn		X			100.00	64	48	88	59	83	81	79	56	52	57	58	61	56	63	62	0	50	61	0	21	2	773,333$
11	Lance Bouma	X	X	X		100.00	68	57	78	58	82	86	88	57	52	54	56	59	55	78	67	0	50	61	0	29	1	650,000$
12	Remi Elie		X			100.00	64	43	86	61	80	72	69	58	53	57	59	60	62	69	65	0	50	61	0	24	1	700,000$
13	Andy Welinski				X	100.00	65	43	88	62	78	84	75	61	30	60	59	63	52	73	67	0	50	63	0	26	1	750,000$
14	Cameron Gaunce				X	100.00	61	48	84	62	76	80	73	61	30	65	58	60	53	78	68	0	50	63	0	29	1	700,000$
15	Nate Prosser				X	100.00	63	46	88	60	81	74	71	58	30	57	56	59	53	84	74	0	50	62	0	33	2	700,000$
16	Rasmus Sandin				X	100.00	57	39	89	67	71	77	69	66	30	63	58	64	55	60	63	0	50	62	0	19	3	894,167$
17	Urho Vaakanainen				X	100.00	63	42	87	61	74	79	72	59	30	60	58	65	53	62	63	0	50	61	0	20	3	1,302,500$
Rayé
1	Clark Bishop	X				100.00	62	48	83	60	77	74	72	58	60	57	57	59	60	67	64	0	50	60	0	23	1	700,000$
2	Hudson Elynuik	X				100.00	70	51	85	55	88	75	77	53	60	52	54	56	53	65	63	0	50	59	0	21	1	650,000$
3	Marian Studenic			X		100.00	53	39	89	58	70	82	83	59	54	55	57	56	59	63	62	0	50	59	0	20	2	925,000$
4	Nate Schnarr	X				100.00	62	49	84	58	79	80	76	57	63	58	53	56	59	61	63	0	50	59	0	20	3	894,167$
5	Tanner Kaspick	X				100.00	61	47	88	55	74	84	82	56	59	53	54	57	55	63	62	0	50	59	0	21	2	822,222$
6	Blake Speers	X				100.00	53	45	87	56	69	85	84	55	61	53	54	52	56	65	63	0	50	58	0	22	1	935,833$
7	David Pope		X			100.00	62	43	88	55	78	75	77	53	51	50	54	56	53	71	66	0	50	58	0	25	1	1,437,500$
8	Dylan Blujus				X	100.00	65	49	83	55	82	78	77	54	30	53	53	56	45	71	66	0	50	59	0	25	1	650,000$
9	Hunter Drew				X	100.00	63	49	77	57	79	74	73	55	30	54	53	56	45	63	62	0	50	58	0	20	1	650,000$
10	Teemu Kivihalme				X	100.00	52	42	87	58	55	85	84	57	30	56	53	52	45	69	65	0	50	58	0	24	1	925,000$
11	Vili Saarijarvi				X	100.00	53	39	87	57	58	83	84	56	30	54	51	55	45	65	62	0	50	57	0	22	1	930,000$

	MOYENNE D'ÉQUIPE					100.00	64	46	85	60	76	78	76	59	49	57	57	59	56	68	65	0	50	61

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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	Joey Daccord	100.00	77	63	61	80	76	75	77	76	75	77	76	67	71	0	50	66	0
2	Stuart Skinner	100.00	74	73	71	88	73	72	74	73	72	74	73	63	67	0	50	65	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	76	68	66	84	75	74	76	75	74	76	75	65	69	0	50	66

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire

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	PKM	GW	FO%	FOT	HT	P/20	S1	S2	S3
1	Rasmus Sandin	Marlies (TOR)	D	3	1	3	4	0	2	6	8	11	1	4	9.09%	13	64	21.51	1	1	2	11	6	7	0	0.00%	0	0	1.24	0	1	0
2	Anders Bjork	Marlies (TOR)	LW/RW	3	3	0	3	0	0	2	11	8	5	2	37.50%	3	53	17.73	0	0	0	0	6	0	0	50.00%	2	1	1.13	1	0	0
3	Chris Stewart	Marlies (TOR)	LW/RW	3	1	2	3	-8	0	12	4	12	5	3	8.33%	6	52	17.49	1	2	3	2	5	0	1	40.00%	5	0	1.14	0	0	0
4	Nate Prosser	Marlies (TOR)	D	3	2	0	2	-8	4	3	6	4	0	3	50.00%	6	45	15.18	1	0	1	2	0	0	0	0.00%	0	0	0.88	0	0	1
5	Andy Andreoff	Marlies (TOR)	C	3	0	2	2	0	0	2	10	6	3	4	0.00%	0	52	17.62	0	0	0	2	6	0	0	55.41%	74	0	0.76	0	0	0
6	Beck Malenstyn	Marlies (TOR)	LW	3	0	1	1	1	0	0	0	0	0	0	0.00%	0	0	0.14	0	0	0	0	0	0	0	0.00%	1	0	46.15	0	0	0
7	Cameron Gaunce	Marlies (TOR)	D	3	0	1	1	-3	0	12	4	2	1	0	0.00%	5	69	23.03	0	0	0	2	5	6	0	0.00%	0	0	0.29	0	0	0
8	Mackenzie MacEachern	Marlies (TOR)	LW	3	0	1	1	-3	6	16	7	10	3	6	0.00%	1	58	19.51	0	0	0	0	0	0	0	0.00%	1	0	0.34	0	0	0
9	Andy Welinski	Marlies (TOR)	D	3	0	0	0	-3	4	10	5	5	1	5	0.00%	6	66	22.32	0	0	0	1	5	4	0	0.00%	0	0	0.00	0	0	0
10	Mitchell Stephens	Marlies (TOR)	C	3	0	0	0	-9	0	3	4	4	2	2	0.00%	4	50	16.84	0	0	0	0	0	0	0	50.00%	14	0	0.00	0	0	0
11	Nathan Bastian	Marlies (TOR)	RW	3	0	0	0	0	2	5	2	9	2	6	0.00%	0	52	17.62	0	0	0	1	6	0	0	60.00%	5	0	0.00	0	0	0
12	Michael McLeod	Marlies (TOR)	C	3	0	0	0	-1	0	0	0	1	0	1	0.00%	0	11	3.72	0	0	0	0	0	0	0	42.86%	7	0	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				36	7	10	17	-34	18	71	61	72	23	36	9.72%	44	578	16.06	3	3	6	21	43	18	1	52.29%	109	1	0.59	1	1	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 Gardien	Nom de l'Équipe	GP	W	L	PCT	GAA	MP	GA	SA	A	ST	BG
1	Joey Daccord	Marlies (TOR)	3	1	2	0.863	5.61	139	13	95	2	3	0
2	Stuart Skinner	Marlies (TOR)	1	0	0	0.925	6.00	40	4	53	0	0	3
Stats d'équipe Total ou en Moyenne			4	1	2	0.885	5.67	180	17	148	2	3	3

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	Link
Anders Bjork	Marlies (TOR)	LW/RW	23	1996-08-05	No	190 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,066,667$	0$	0$	No			Lien / Lien NHL
Andy Andreoff	Marlies (TOR)	C	28	1991-05-17	No	203 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Andy Welinski	Marlies (TOR)	D	26	1993-04-27	No	201 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien / Lien NHL
Austin Poganski	Marlies (TOR)	RW	23	1996-02-16	No	198 Lbs	6 ft1	No	No	No	1	Pro & Farm	762,500$	0$	0$	No			Lien / Lien NHL
Austin Wagner	Marlies (TOR)	LW	22	1997-06-23	No	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien / Lien NHL
Beck Malenstyn	Marlies (TOR)	LW	21	1998-02-04	No	200 Lbs	6 ft3	No	No	No	2	Pro & Farm	773,333$	0$	0$	No	773,333$		Lien / Lien NHL
Blake Speers	Marlies (TOR)	C	22	1997-01-02	No	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	935,833$	0$	0$	No			Lien / Lien NHL
Cameron Gaunce	Marlies (TOR)	D	29	1990-03-19	No	194 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien / Lien NHL
Chris Stewart	Marlies (TOR)	LW/RW	31	1987-10-30	No	242 Lbs	6 ft2	No	No	No	1	Pro & Farm	753,757$	0$	0$	No			Lien
Clark Bishop	Marlies (TOR)	C	23	1996-03-29	No	199 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien / Lien NHL
David Pope	Marlies (TOR)	LW	25	1994-09-27	No	187 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,437,500$	0$	0$	No			Lien / Lien NHL
Dylan Blujus	Marlies (TOR)	D	25	1994-01-22	No	191 Lbs	6 ft3	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien / Lien NHL
Hudson Elynuik	Marlies (TOR)	C	21	1997-10-12	No	194 Lbs	6 ft5	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien / Lien NHL
Hunter Drew	Marlies (TOR)	D	20	1998-10-21	No	191 Lbs	6 ft2	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien
Joey Daccord	Marlies (TOR)	G	23	1996-08-19	No	197 Lbs	6 ft2	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien / Lien NHL
Lance Bouma	Marlies (TOR)	C/LW/RW	29	1990-03-25	No	208 Lbs	6 ft2	No	No	No	1	Pro & Farm	650,000$	0$	0$	No			Lien
Mackenzie MacEachern	Marlies (TOR)	LW	25	1994-03-09	No	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Lien / Lien NHL
Marian Studenic	Marlies (TOR)	RW	20	1998-10-28	No	164 Lbs	6 ft1	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Michael McLeod	Marlies (TOR)	C	21	1998-02-03	No	188 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,363,333$	0$	0$	No	1,363,333$		Lien / Lien NHL
Mitchell Stephens	Marlies (TOR)	C	22	1997-02-05	No	193 Lbs	5 ft11	No	No	No	1	Pro & Farm	919,166$	0$	0$	No			Lien / Lien NHL
Nate Prosser	Marlies (TOR)	D	33	1986-05-07	No	201 Lbs	6 ft2	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$		Lien / Lien NHL
Nate Schnarr	Marlies (TOR)	C	20	1999-02-25	No	180 Lbs	6 ft3	No	No	No	3	Pro & Farm	894,167$	0$	0$	No	894,167$	894,167$	Lien
Nathan Bastian	Marlies (TOR)	RW	21	1997-12-06	No	205 Lbs	6 ft4	No	No	No	2	Pro & Farm	905,000$	0$	0$	No	905,000$		Lien / Lien NHL
Rasmus Sandin	Marlies (TOR)	D	19	2000-03-07	No	183 Lbs	5 ft11	No	No	No	3	Pro & Farm	894,167$	0$	0$	No	894,167$	894,167$	Lien / Lien NHL
Remi Elie	Marlies (TOR)	LW	24	1995-04-16	No	215 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	0$	0$	No			Lien / Lien NHL
Stuart Skinner	Marlies (TOR)	G	20	1998-11-01	No	206 Lbs	6 ft4	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$		Lien / Lien NHL
Tanner Kaspick	Marlies (TOR)	C	21	1998-01-28	No	200 Lbs	6 ft0	No	No	No	2	Pro & Farm	822,222$	0$	0$	No	822,222$		Lien / Lien NHL
Teemu Kivihalme	Marlies (TOR)	D	24	1995-06-17	No	161 Lbs	5 ft1	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Lien
Urho Vaakanainen	Marlies (TOR)	D	20	1999-01-01	No	185 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,302,500$	0$	0$	No	1,302,500$	1,302,500$	Lien / Lien NHL
Vili Saarijarvi	Marlies (TOR)	D	22	1997-05-15	No	182 Lbs	5 ft1	No	No	No	1	Pro & Farm	930,000$	0$	0$	No			Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
30	23.43	194 Lbs	6 ft1	1.47	867,838$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Chris Stewart	30	1	2	2
2	Anders Bjork	Andy Andreoff	Nathan Bastian	30	1	2	2
3			Mackenzie MacEachern	25	1	2	2
4	Mackenzie MacEachern	Mitchell Stephens		15	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Gaunce	Andy Welinski	30	1	2	2
2		Rasmus Sandin	30	1	2	2
3	Nate Prosser	Mitchell Stephens	25	1	2	2
4	Cameron Gaunce	Andy Welinski	15	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Chris Stewart	60	1	2	2
2	Anders Bjork	Andy Andreoff	Nathan Bastian	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Gaunce	Andy Welinski	60	1	2	2
2		Rasmus Sandin	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2	Chris Stewart	Anders Bjork	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Gaunce	Andy Welinski	60	1	2	2
2		Rasmus Sandin	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	Cameron Gaunce	Andy Welinski	60	1	2	2
2		40	1	2	2		Rasmus Sandin	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2	Chris Stewart	Anders Bjork	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Cameron Gaunce	Andy Welinski	60	1	2	2
2		Rasmus Sandin	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Chris Stewart	Cameron Gaunce	Andy Welinski

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Chris Stewart	Cameron Gaunce	Andy Welinski

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Michael McLeod, Beck Malenstyn,	Michael McLeod, Beck Malenstyn

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Nate Prosser, , Rasmus Sandin	Nate Prosser	, Rasmus Sandin

Tirs de Pénalité
, , Chris Stewart, Anders Bjork,

Gardien
#1 : Joey Daccord, #2 : Stuart Skinner

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	Crunch	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	0.333	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17
	Total	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	0.333	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17
	_Since Last GM Reset	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	0.333	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17
	_Vs Conference	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	0.333	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17
	_Vs Division	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	0.333	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17

			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
3	2	L2	7	12	19	73	148	45	18	71	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	7	17

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
1	0	1	0	0	0	0	1	6

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	6	11

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
1	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
9	3	33.33%	9	2	77.78%	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
26	22	25	0	2	4	1	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
25	81	30.86%	36	137	26.28%	12	44	27.27%

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
60	41	83	22	36	17

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	Lien
1 - 2021-04-06	4	Marlies	6	Crunch	3	W	Sommaire du Match
3 - 2021-04-08	12	Marlies	0	Crunch	8	L	Sommaire du Match
5 - 2021-04-10	20	Crunch	6	Marlies	1	L	Sommaire du Match
7 - 2021-04-12	28	Crunch	-	Marlies	-
9 - 2021-04-14	36	Marlies	-	Crunch	-
11 - 2021-04-16	44	Crunch	-	Marlies	-
13 - 2021-04-18	52	Marlies	-	Crunch	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	35	15
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
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$	2,603,515$	1,580,951$	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$	8	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
2	82	22	49	0	5	2	2	2	247	346	-99	41	11	23	0	3	2	0	2	125	181	-56	41	11	26	0	2	0	2	0	122	165	-43	44	247	440	687	0	2	89	82	69	8	2310	774	742	774	34	3354	964	1041	1582	274	56	20.44%	410	96	76.59%	2	1023	2411	42.43%	1069	2873	37.21%	539	1347	40.01%	1724	1155	2212	611	1016	480
3	82	11	65	0	1	1	2	2	177	424	-247	41	5	32	0	0	0	2	2	91	206	-115	41	6	33	0	1	1	0	0	86	218	-132	22	177	317	494	0	0	67	57	50	3	2458	756	890	795	27	4421	1293	911	1621	284	39	13.73%	367	104	71.66%	1	834	2375	35.12%	1100	3254	33.80%	466	1337	34.85%	1370	905	2640	607	933	386
4	82	12	61	0	1	0	3	5	167	428	-261	41	6	29	0	1	0	2	3	88	194	-106	41	6	32	0	0	0	1	2	79	234	-155	24	167	309	476	1	0	60	57	46	9	2288	753	776	730	60	4160	1244	1069	1522	480	58	12.08%	414	122	70.53%	1	967	2443	39.58%	1094	3191	34.28%	527	1327	39.71%	1366	873	2631	654	964	400
5	82	22	49	0	1	2	4	4	243	345	-102	41	15	20	0	1	2	1	2	134	160	-26	41	7	29	0	0	0	3	2	109	185	-76	44	243	383	626	1	1	86	78	74	10	2929	908	981	1008	71	3280	919	435	1933	208	43	20.67%	201	53	73.63%	3	1371	2765	49.58%	1244	2707	45.95%	676	1403	48.18%	1847	1329	2151	559	970	459
6	82	34	40	0	0	2	3	3	304	274	30	41	21	17	0	0	0	2	1	161	125	36	41	13	23	0	0	2	1	2	143	149	-6	68	304	501	805	5	6	141	81	79	6	3640	1147	1213	1266	36	3314	973	441	2097	218	42	19.27%	172	41	76.16%	1	1554	3150	49.33%	1405	3211	43.76%	621	1343	46.24%	1965	1426	2007	559	979	478
7	82	34	34	0	2	2	8	2	293	273	20	41	16	18	0	1	0	5	1	147	140	7	41	18	16	0	1	2	3	1	146	133	13	68	293	520	813	2	1	119	86	78	14	3484	1155	1187	1107	82	3123	883	500	2157	218	40	18.35%	221	47	78.73%	1	1828	3181	57.47%	1639	3098	52.91%	737	1369	53.83%	2039	1459	1925	560	1014	510
8	82	50	25	0	1	0	4	2	402	237	165	41	26	11	0	1	0	2	1	200	104	96	41	24	14	0	0	0	2	1	202	133	69	100	402	736	1138	1	3	184	124	89	7	4048	1337	1320	1368	45	2619	756	474	2048	188	44	23.40%	190	40	78.95%	1	2052	3369	60.91%	1470	2703	54.38%	838	1388	60.37%	2276	1688	1690	514	987	524
8	82	50	25	0	1	0	4	2	402	237	165	41	26	11	0	1	0	2	1	200	104	96	41	24	14	0	0	0	2	1	202	133	69	100	402	736	1138	1	3	184	124	89	7	4048	1337	1320	1368	45	2619	756	474	2048	188	44	23.40%	190	40	78.95%	1	2052	3369	60.91%	1470	2703	54.38%	838	1388	60.37%	2276	1688	1690	514	987	524
9	82	33	27	0	4	5	8	5	288	249	39	41	20	13	0	2	2	3	1	144	107	37	41	13	14	0	2	3	5	4	144	142	2	100	288	504	792	2	2	119	95	62	17	3143	1051	1072	981	83	3101	931	460	1972	213	53	24.88%	192	38	80.21%	2	1338	3035	44.09%	1258	3134	40.14%	632	1390	45.47%	2023	1456	1967	562	1016	515
Total Saison Régulière	738	268	375	0	16	14	38	27	2523	2813	-290	369	146	174	0	10	6	19	14	1290	1321	-31	369	122	201	0	6	8	19	13	1233	1492	-259	570	2523	4446	6969	13	18	1049	784	636	81	28348	9218	9501	9397	483	29991	8719	5805	16980	2271	419	18.45%	2357	581	75.35%	13	13019	26098	49.89%	11749	26874	43.72%	5874	12292	47.79%	16890	11985	18918	5145	8871	4279
Séries
6	4	0	4	0	0	0	0	0	10	22	-12	2	0	2	0	0	0	0	0	6	13	-7	2	0	2	0	0	0	0	0	4	9	-5	0	10	15	25	0	0	5	3	2	0	126	34	49	43	0	204	63	26	70	14	1	7.14%	13	4	69.23%	0	42	132	31.82%	81	175	46.29%	32	66	48.48%	74	49	117	31	47	21
7	11	6	5	0	0	0	0	0	39	36	3	5	3	2	0	0	0	0	0	23	18	5	6	3	3	0	0	0	0	0	16	18	-2	12	39	66	105	0	0	11	14	13	1	436	138	150	135	13	427	125	70	275	36	10	27.78%	31	7	77.42%	0	231	450	51.33%	206	422	48.82%	96	193	49.74%	262	181	283	84	149	71
8	6	2	4	0	0	0	0	0	23	26	-3	3	2	1	0	0	0	0	0	12	12	0	3	0	3	0	0	0	0	0	11	14	-3	4	23	41	64	0	0	9	7	7	0	205	72	60	72	1	230	70	44	116	17	5	29.41%	21	9	57.14%	0	109	216	50.46%	80	216	37.04%	61	112	54.46%	131	89	156	41	73	35
9	3	1	2	0	0	0	0	0	7	17	-10	1	0	1	0	0	0	0	0	1	6	-5	2	1	1	0	0	0	0	0	6	11	-5	2	7	12	19	0	0	2	4	1	0	73	26	22	25	0	148	45	18	71	9	3	33.33%	9	2	77.78%	0	25	81	30.86%	36	137	26.28%	12	44	27.27%	60	41	83	22	36	17
Total Séries	24	9	15	0	0	0	0	0	79	101	-22	11	5	6	0	0	0	0	0	42	49	-7	13	4	9	0	0	0	0	0	37	52	-15	18	79	134	213	0	0	27	28	23	1	840	270	281	275	14	1009	303	158	532	76	19	25.00%	74	22	70.27%	0	407	879	46.30%	403	950	42.42%	201	415	48.43%	528	361	641	179	306	145

	Marlies
	GP: 3 \| W: 1 \| L: 2 GF: 7 \| GA: 17 \| PP%: 33.33% \| PK%: 77.78% DG: Jeremie Pelland \| Morale : 50 \| Moyenne d'Équipe : 61 Prochain matchs #28 vs Crunch