OTHL - Bears

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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	Gabriel Vilardi (R)	X				100.00	61	42	96	80	76	68	78	73	80	69	71	61	25	51	51	70	50	67	0	22	2	1,627,500$
2	Jaret Anderson-Dolan (R)	X	X			100.00	80	44	93	79	67	65	71	57	75	61	72	65	25	47	47	69	50	63	0	22	3	913,333$
3	A.J. Greer		X	X		100.00	78	76	82	64	76	61	62	61	50	60	57	66	54	46	46	62	50	60	0	24	1	825,000$
4	Cameron Darcy	X				100.00	75	68	90	63	68	53	55	48	60	47	44	61	42	44	44	53	50	53	0	27	2	750,000$
5	Kevin Gravel				X	100.00	80	78	86	70	78	57	60	48	25	39	40	66	38	56	57	53	50	60	0	29	2	750,000$
6	Kyle Capobianco				X	100.00	75	72	81	64	72	59	61	55	25	53	42	63	40	45	45	56	50	59	0	24	2	750,000$
7	Nicolas Meloche				X	100.00	80	76	90	68	76	61	64	50	25	46	39	64	37	44	44	54	50	59	0	24	2	853,333$
Rayé

	MOYENNE D'ÉQUIPE					100.00	76	65	88	70	73	61	64	56	49	54	52	64	37	48	48	60	50	60

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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	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV
Rayé

	MOYENNE D'ÉQUIPE	0.00	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dallas Eakins	82	83	77	79	81	76	67	USA	54	1	800,000$

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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	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
1	A.J. Greer	Bears (WSH)	LW/RW	16	24	3	27	10	10	0	55	21	103	26	66	23.30%	32	250	15.63	1	0	1	1	0	0	0	0	0	2	1	0	72.22%	18	0	0	0	2	2.16	0	0	0	0	0	0	1	2
Stats d'équipe Total ou en Moyenne				16	24	3	27	10	10	0	55	21	103	26	66	23.30%	32	250	15.63	1	0	1	1	0	0	0	0	0	2	1	0	72.22%	18	0	0	0	2	2.16	0	0	0	0	0	0	1	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

#	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	Salaire Année 3	Link
A.J. Greer	Bears (WSH)	LW/RW	24	1996-12-14	No	204 Lbs	6 ft3	No	No	No	1	Pro & Farm	825,000$	825,000$	0$	0$	No			Lien / Lien NHL
Cameron Darcy	Bears (WSH)	C	27	1994-03-02	No	186 Lbs	6 ft0	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Gabriel Vilardi	Bears (WSH)	C	22	1999-08-16	Yes	201 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,627,500$	1,627,500$	0$	0$	No	1,627,500$		Lien / Lien NHL
Jaret Anderson-Dolan	Bears (WSH)	C/LW	22	1999-09-12	Yes	188 Lbs	5 ft11	No	No	No	3	Pro & Farm	913,333$	913,333$	0$	0$	No	913,333$	913,333$	Lien / Lien NHL
Kevin Gravel	Bears (WSH)	D	29	1992-03-06	No	205 Lbs	6 ft4	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Kyle Capobianco	Bears (WSH)	D	24	1997-08-13	No	196 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$		Lien / Lien NHL
Nicolas Meloche	Bears (WSH)	D	24	1997-07-18	No	204 Lbs	6 ft3	No	No	No	2	Pro & Farm	853,333$	853,333$	0$	0$	No	853,333$		Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
7	24.57	198 Lbs	6 ft2	2.00	924,167$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1				40	1	2	2
2	A.J. Greer			30	1	2	2
3				20	1	2	2
4				10	1	2	2

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

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

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			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	A.J. Greer		40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			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			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	A.J. Greer		40	1	2	2

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

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
A.J. Greer, ,	A.J. Greer,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, ,		,

Tirs de Pénalité
, , , A.J. Greer,

Gardien
#1 : , #2 :

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
1	Bruins	2	0	2	0	0	0	0	0	3	17	-14	1	0	1	0	0	0	0	0	2	10	-8	1	0	1	0	0	0	0	0	1	7	-6	0	0.000	3	5	8	0	0	19	18	16	0	47	182	173	212	0	105	31	8	31	5	2	40.00%	4	1	75.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
2	Checkers	2	0	2	0	0	0	0	0	8	13	-5	1	0	1	0	0	0	0	0	5	8	-3	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	8	13	21	0	0	19	18	16	0	54	182	173	212	0	130	45	4	49	2	0	0.00%	2	0	100.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
3	Penguins	2	0	2	0	0	0	0	0	9	12	-3	1	0	1	0	0	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	5	7	-2	0	0.000	9	18	27	0	0	19	18	16	0	79	182	173	212	0	92	25	4	42	3	1	33.33%	2	0	100.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
4	Phantoms	2	0	2	0	0	0	0	0	2	18	-16	1	0	1	0	0	0	0	0	1	11	-10	1	0	1	0	0	0	0	0	1	7	-6	0	0.000	2	3	5	0	0	19	18	16	0	29	182	173	212	0	98	23	6	32	7	0	0.00%	2	0	100.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
5	Senators	1	0	1	0	0	0	0	0	2	9	-7	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	2	9	-7	0	0.000	2	4	6	0	0	19	18	16	0	47	182	173	212	0	51	10	4	19	3	0	0.00%	3	2	33.33%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
6	Sound Tigers	2	1	0	0	0	1	0	0	10	8	2	1	0	0	0	0	1	0	0	4	5	-1	1	1	0	0	0	0	0	0	6	3	3	3	0.750	10	18	28	0	0	19	18	16	0	115	182	173	212	0	102	43	4	58	3	1	33.33%	2	0	100.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
7	Thunderbirds	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	6	9	0	0	19	18	16	0	32	182	173	212	0	79	28	4	23	4	0	0.00%	2	1	50.00%	0	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
8	Wolf Pack	3	2	1	0	0	0	0	0	16	15	1	2	1	1	0	0	0	0	0	9	10	-1	1	1	0	0	0	0	0	0	7	5	2	4	0.667	16	30	46	0	0	19	18	16	0	164	182	173	212	0	124	34	12	76	0	0	0.00%	5	0	100.00%	1	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
	Total	16	3	12	0	0	1	0	0	53	103	-50	8	1	6	0	0	1	0	0	26	57	-31	8	2	6	0	0	0	0	0	27	46	-19	7	0.219	53	97	150	0	0	19	18	16	0	567	182	173	212	0	781	239	46	330	27	4	14.81%	22	4	81.82%	1	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
	_Since Last GM Reset	16	3	12	0	0	1	0	0	53	103	-50	8	1	6	0	0	1	0	0	26	57	-31	8	2	6	0	0	0	0	0	27	46	-19	7	0.219	53	97	150	0	0	19	18	16	0	567	182	173	212	0	781	239	46	330	27	4	14.81%	22	4	81.82%	1	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
	_Vs Conference	16	3	12	0	0	1	0	0	53	103	-50	8	1	6	0	0	1	0	0	26	57	-31	8	2	6	0	0	0	0	0	27	46	-19	7	0.219	53	97	150	0	0	19	18	16	0	567	182	173	212	0	781	239	46	330	27	4	14.81%	22	4	81.82%	1	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78
	_Vs Division	11	3	11	0	0	1	0	0	45	66	-21	6	1	6	0	0	1	0	0	23	39	-16	5	2	5	0	0	0	0	0	22	27	-5	7	0.318	45	82	127	0	0	19	18	16	0	441	182	173	212	0	546	170	30	257	15	2	13.33%	13	0	100.00%	1	169	391	43.22%	152	411	36.98%	108	279	38.71%	298	210	489	101	173	78

			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	7	L3	53	97	150	567	781	239	46	330	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	3	12	0	1	0	0	53	103

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	1	6	0	1	0	0	26	57

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	2	6	0	0	0	0	27	46

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	7	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
27	4	14.81%	22	4	81.82%	1

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
182	173	212	0	19	18	16	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
169	391	43.22%	152	411	36.98%	108	279	38.71%

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
298	210	489	101	173	78

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
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
1 - 2021-10-18	5	Wolf Pack	5	Bears	3	L		Sommaire du Match
2 - 2021-10-19	28	Bears	7	Wolf Pack	5	W		Sommaire du Match
4 - 2021-10-21	41	Bears	3	Checkers	5	L		Sommaire du Match
5 - 2021-10-22	57	Thunderbirds	8	Bears	1	L		Sommaire du Match
7 - 2021-10-24	74	Bears	1	Phantoms	7	L		Sommaire du Match
8 - 2021-10-25	89	Phantoms	11	Bears	1	L		Sommaire du Match
9 - 2021-10-26	107	Bears	2	Senators	9	L		Sommaire du Match
10 - 2021-10-27	120	Checkers	8	Bears	5	L		Sommaire du Match
11 - 2021-10-28	141	Bruins	10	Bears	2	L		Sommaire du Match
12 - 2021-10-29	149	Bears	5	Penguins	7	L		Sommaire du Match
14 - 2021-10-31	165	Bears	6	Sound Tigers	3	W		Sommaire du Match
16 - 2021-11-02	185	Sound Tigers	5	Bears	4	L	X	Sommaire du Match
17 - 2021-11-03	201	Wolf Pack	5	Bears	6	W		Sommaire du Match
18 - 2021-11-04	218	Bears	1	Bruins	7	L		Sommaire du Match
19 - 2021-11-05	223	Bears	2	Thunderbirds	3	L		Sommaire du Match
21 - 2021-11-07	246	Penguins	5	Bears	4	L		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des Billets	35	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$	646,916$	646,916$	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

	Bears
	GP: 16 \| W: 3 \| L: 12 \| OTL: 1 \| P: 7 GF: 53 \| GA: 103 \| PP%: 14.81% \| PK%: 81.82% DG: Bo \| Morale : 50 \| Moyenne d'Équipe : 60