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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	Otto Koivula		X	X		100.00	82	84	77	66	84	58	59	55	69	58	47	66	45	45	45	57	50	58	0	23	2	786,666$
2	Jan Drozg (R)		X			100.00	73	66	89	63	66	64	67	52	50	43	56	61	53	44	44	58	50	56	0	22	2	925,000$
3	Tanner Fritz	X		X		100.00	74	69	85	56	69	45	44	53	66	47	54	61	51	44	44	56	50	53	0	30	2	850,000$
4	Brett Kulak				X	100.00	67	42	87	75	71	69	79	60	25	50	48	61	25	65	66	59	50	63	0	27	1	1,850,000$
5	Sami Niku				X	100.00	69	41	76	75	66	66	48	58	24	60	45	63	25	49	49	48	50	60	0	25	1	916,666$
6	Colton White				X	100.00	76	69	91	66	69	60	64	49	25	40	40	64	38	55	55	53	50	59	0	24	1	935,833$
7	Jordan Schmaltz				X	100.00	77	73	86	68	73	58	62	47	25	36	41	63	39	49	49	53	50	58	0	28	2	750,000$
Rayé

	MOYENNE D'ÉQUIPE					100.00	74	63	84	67	71	60	60	53	41	48	47	63	39	50	50	55	50	58

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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	Francois Brassard	100.00	51	55	55	55	55	55	55	55	55	55	55	55	55	55	50	54	0
2	Kevin Boyle	100.00	48	52	65	73	45	47	51	54	47	48	30	44	44	49	50	51	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	50	54	60	64	50	51	53	55	51	52	43	50	50	52	50	53

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
John Hynes	80	86	82	80	69	64	79	USA	46	2	1,000,000$

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKM	FO%	FOT	HT	P/20	S1	S2	S3
1	Jan Drozg	Crunch (TBL)	LW	16	11	1	12	-1	12	35	16	37	13	28	29.73%	11	151	9.48	0	0	0	0	0	0	66.67%	6	1	1.58	1	0	0
2	Colton White	Crunch (TBL)	D	16	3	8	11	-22	22	90	29	38	12	21	7.89%	31	310	19.38	2	2	4	19	25	11	0.00%	0	0	0.71	0	2	2
Stats d'équipe Total ou en Moyenne				32	14	9	23	-23	34	125	45	75	25	49	18.67%	42	461	14.43	2	2	4	19	25	12	66.67%	6	1	1.00	1	2	2

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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 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
Stats d'équipe Total ou en Moyenne							0.000	0.00	0								0.000

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Nom du Joueur	Nom de l'Équipe	POS	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	Link
Brett Kulak	Crunch (TBL)	D	27	1994-01-05	No	192 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,850,000$	1,850,000$	0$	0$	No		Lien / Lien NHL
Colton White	Crunch (TBL)	D	24	1997-05-03	No	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	935,833$	935,833$	0$	0$	No		Lien / Lien NHL
Francois Brassard	Crunch (TBL)	G	27	1994-01-31 2:16:29 PM	No	172 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No
Jan Drozg	Crunch (TBL)	LW	22	1999-04-01	Yes	174 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	Lien / Lien NHL
Jordan Schmaltz	Crunch (TBL)	D	28	1993-10-08	No	196 Lbs	6 ft2	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	Lien / Lien NHL
Kevin Boyle	Crunch (TBL)	G	29	1992-05-29	No	201 Lbs	6 ft0	No	No	No	2	Pro & Farm	975,000$	975,000$	0$	0$	No	975,000$	Lien / Lien NHL
Otto Koivula	Crunch (TBL)	LW/RW	23	1998-09-01	No	223 Lbs	6 ft5	No	No	No	2	Pro & Farm	786,666$	786,666$	0$	0$	No	786,666$	Lien / Lien NHL
Sami Niku	Crunch (TBL)	D	25	1996-10-10	No	176 Lbs	6 ft1	No	No	No	1	Pro & Farm	916,666$	916,666$	0$	0$	No		Lien / Lien NHL
Tanner Fritz	Crunch (TBL)	C/RW	30	1991-08-20	No	192 Lbs	5 ft11	Yes	No	No	2	Pro & Farm	850,000$	850,000$	0$	0$	No	850,000$	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
9	26.11	190 Lbs	6 ft1	1.56	971,018$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3	Jan Drozg			20	1	2	2
4				10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Colton White	40	1	2	2
2			30	1	2	2
3			20	1	2	2
4		Colton White	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				60	1	2	2
2				40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Colton White	60	1	2	2
2			40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2		Jan Drozg	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Colton White	60	1	2	2
2			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		Colton White	60	1	2	2
2		40	1	2	2			40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			60	1	2	2
2		Jan Drozg	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Colton White	60	1	2	2
2			40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
				Colton White

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
				Colton White

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jan Drozg, ,	Jan Drozg,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, , , Jan Drozg,

Gardien
#1 : , #2 :

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

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

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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
1	Canucks	2	0	2	0	0	0	0	0	3	11	-8	1	0	1	0	0	0	0	0	1	8	-7	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	3	5	8	0	0	15	15	8	0	45	107	126	127	0	42	15	14	39	8	0	0.00%	7	3	57.14%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
2	Comets	3	1	2	0	0	0	0	0	13	18	-5	1	0	1	0	0	0	0	0	5	9	-4	2	1	1	0	0	0	0	0	8	9	-1	2	0.333	13	26	39	0	0	15	15	8	0	90	107	126	127	0	113	42	12	78	6	3	50.00%	6	3	50.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
3	Griffins	2	1	1	0	0	0	0	0	6	7	-1	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	3	5	-2	2	0.500	6	12	18	0	0	15	15	8	0	54	107	126	127	0	43	11	4	21	8	1	12.50%	2	1	50.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
4	Marlies	2	0	2	0	0	0	0	0	4	18	-14	1	0	1	0	0	0	0	0	2	10	-8	1	0	1	0	0	0	0	0	2	8	-6	0	0.000	4	6	10	0	0	15	15	8	0	34	107	126	127	0	98	42	10	34	7	1	14.29%	4	1	75.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
5	Monsters	2	0	2	0	0	0	0	0	1	15	-14	1	0	1	0	0	0	0	0	1	7	-6	1	0	1	0	0	0	0	0	0	8	-8	0	0.000	1	2	3	0	0	15	15	8	0	24	107	126	127	0	82	26	12	32	6	0	0.00%	6	0	100.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
6	Rocket	3	0	3	0	0	0	0	0	4	14	-10	2	0	2	0	0	0	0	0	3	10	-7	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	4	7	11	0	0	15	15	8	0	48	107	126	127	0	74	23	12	46	9	0	0.00%	5	1	80.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
7	Senators	2	0	2	0	0	0	0	0	7	12	-5	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	7	12	19	0	0	15	15	8	0	65	107	126	127	0	105	36	22	52	2	1	50.00%	5	1	80.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
	Total	16	2	14	0	0	0	0	0	38	95	-57	8	1	7	0	0	0	0	0	19	52	-33	8	1	7	0	0	0	0	0	19	43	-24	4	0.125	38	70	108	0	0	15	15	8	0	360	107	126	127	0	557	195	86	302	46	6	13.04%	35	10	71.43%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
	_Since Last GM Reset	16	2	14	0	0	0	0	0	38	95	-57	8	1	7	0	0	0	0	0	19	52	-33	8	1	7	0	0	0	0	0	19	43	-24	4	0.125	38	70	108	0	0	15	15	8	0	360	107	126	127	0	557	195	86	302	46	6	13.04%	35	10	71.43%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
	_Vs Conference	16	2	14	0	0	0	0	0	38	95	-57	8	1	7	0	0	0	0	0	19	52	-33	8	1	7	0	0	0	0	0	19	43	-24	4	0.125	38	70	108	0	0	15	15	8	0	360	107	126	127	0	557	195	86	302	46	6	13.04%	35	10	71.43%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72
	_Vs Division	9	2	14	0	0	0	0	0	21	51	-30	5	1	7	0	0	0	0	0	12	28	-16	4	1	7	0	0	0	0	0	9	23	-14	4	0.222	21	37	58	0	0	15	15	8	0	201	107	126	127	0	320	112	48	153	26	3	11.54%	16	4	75.00%	0	105	322	32.61%	130	394	32.99%	79	274	28.83%	257	176	522	115	179	72

			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	4	L3	38	70	108	360	557	195	86	302	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	2	14	0	0	0	0	38	95

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	1	7	0	0	0	0	19	52

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	1	7	0	0	0	0	19	43

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
1	9	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
46	6	13.04%	35	10	71.43%	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
107	126	127	0	15	15	8	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
105	322	32.61%	130	394	32.99%	79	274	28.83%

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
257	176	522	115	179	72

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
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2021-10-18	2	Rocket	6	Crunch	2	L	Sommaire du Match
2 - 2021-10-19	19	Crunch	2	Comets	4	L	Sommaire du Match
3 - 2021-10-20	31	Crunch	3	Senators	6	L	Sommaire du Match
5 - 2021-10-22	56	Crunch	2	Canucks	3	L	Sommaire du Match
6 - 2021-10-23	63	Comets	9	Crunch	5	L	Sommaire du Match
7 - 2021-10-24	82	Griffins	2	Crunch	3	W	Sommaire du Match
9 - 2021-10-26	108	Monsters	7	Crunch	1	L	Sommaire du Match
10 - 2021-10-27	118	Crunch	1	Rocket	4	L	Sommaire du Match
12 - 2021-10-29	143	Marlies	10	Crunch	2	L	Sommaire du Match
13 - 2021-10-30	155	Crunch	3	Griffins	5	L	Sommaire du Match
15 - 2021-11-01	176	Canucks	8	Crunch	1	L	Sommaire du Match
16 - 2021-11-02	196	Rocket	4	Crunch	1	L	Sommaire du Match
18 - 2021-11-04	213	Crunch	6	Comets	5	W	Sommaire du Match
19 - 2021-11-05	228	Crunch	2	Marlies	8	L	Sommaire du Match
20 - 2021-11-06	234	Senators	6	Crunch	4	L	Sommaire du Match
21 - 2021-11-07	237	Crunch	0	Monsters	8	L	Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	30	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$	873,917$	873,917$	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

	Crunch
	GP: 16 \| W: 2 \| L: 14 \| OTL: 0 \| P: 4 GF: 38 \| GA: 95 \| PP%: 13.04% \| PK%: 71.43% DG: Ron \| Morale : 50 \| Moyenne d'Équipe : 57