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Northstars
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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	Alan Kerr			X		99.00	76	60	62	66	73	79	80	73	69	75	68	72	67	58	63	41	59	68	0	30	1	580,000$
2	Brian Noonan			X		100.00	75	60	65	68	71	79	78	68	63	71	70	76	66	44	50	46	46	67	0	29	1	400,000$
3	Stephan Lebeau	X				100.00	69	59	64	72	69	71	69	75	69	79	76	68	70	43	43	69	50	67	0	26	1	486,000$
4	Kelly Chase			X		100.00	90	89	25	63	74	70	72	69	61	70	64	78	58	57	59	61	76	66	0	27	3	532,000$
5	Vladimir Ruzicka	X				100.00	62	46	77	63	78	68	68	74	68	78	79	57	74	48	44	31	42	66	0	31	1	650,000$
6	Ken Baumgartner		X			100.00	89	82	40	60	77	68	66	68	59	66	60	75	55	56	61	54	60	64	0	28	1	400,000$
7	Mark Pederson		X			100.00	55	41	78	70	74	68	71	70	66	70	68	67	65	41	41	67	72	64	0	26	2	365,000$
8	Neil Brady	X				100.00	71	61	54	62	76	67	67	75	65	68	59	76	56	59	57	67	42	64	0	26	2	400,000$
9	Dave Brown		X			100.00	85	70	55	63	77	72	72	54	52	59	50	80	49	77	74	23	72	63	0	32	1	100,000$
10	Jim McKenzie		X			100.00	78	74	37	64	80	72	72	66	60	66	58	76	55	34	34	74	72	62	0	25	1	400,000$
11	Troy Mallette		X			100.00	89	87	26	66	80	69	70	60	58	66	60	71	58	34	51	81	68	62	0	24	3	402,000$
12	Rob Gaudreau (R)			X		100.00	43	33	85	71	72	59	60	66	61	72	71	59	66	34	28	82	37	61	0	24	1	425,000$
13	Marty McSorley				X	100.00	88	82	36	59	80	71	72	61	60	68	55	84	52	63	63	31	77	68	0	31	2	945,000$
14	Bryan Marchment				X	100.00	90	79	48	67	75	74	74	66	58	68	58	84	52	41	39	76	35	67	0	25	3	706,000$
15	Randy Ladouceur				X	100.00	79	72	50	59	77	74	73	55	54	63	51	79	50	82	87	8	53	67	0	34	1	100,000$
16	Robert Dirk				X	100.00	77	68	57	65	79	73	74	60	55	60	52	78	50	51	55	55	72	66	0	28	2	425,000$
17	Bobby Dollas				X	100.00	71	54	71	59	78	66	67	61	60	72	59	79	56	52	42	47	46	64	0	29	3	425,000$
18	Brad Berry				X	100.00	63	46	74	62	77	72	72	55	52	61	46	76	44	57	59	47	46	63	0	29	1	375,000$
Rayé
1	Rob DiMaio	X				98.47	70	51	72	69	72	68	72	75	64	73	70	76	64	47	52	67	62	67	0	26	3	609,000$
2	Brad May		X			100.00	85	78	42	66	76	62	64	58	54	58	60	76	58	34	34	89	20	60	0	23	3	275,000$
3	Darryl Shannon				X	100.00	69	52	71	65	77	78	77	63	58	65	65	79	62	50	57	67	60	67	0	26	1	695,000$
4	Enrico Ciccone (R)				X	100.00	82	77	36	61	81	64	66	57	54	61	42	74	40	29	29	81	51	61	0	24	1	260,000$

	MOYENNE D'ÉQUIPE					99.89	75	65	56	65	76	70	71	65	60	68	61	75	58	50	51	57	55	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	Dominic Roussel	100.00	73	72	71	74	72	72	79	80	77	73	72	44	47	82	25	69	0
2	Trevor Kidd (R)	100.00	67	74	75	76	71	69	77	80	76	69	68	28	28	96	62	66	0
Rayé
1	Mike Fountain (R)	100.00	69	66	72	73	70	52	65	70	62	67	64	34	38	96	20	61	0

	MOYENNE D'ÉQUIPE	100.00	70	71	73	74	71	64	74	77	72	70	68	35	38	91	36	65

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Brian Sutter	72	71	70	67	79	84	80	CAN	38	2	95,000$

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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	EG	HT	P/20	FW	FL	FT	S1	S2	S3
1	Stephan Lebeau	As (MIN)	C	82	29	46	75	0	26	0	67	175	255	71	174	11.37%	13	1706	20.81	10	20	30	53	312	1	2	3	11	361	7	1	47.58%	1738	1	0	0.88	0	0	0	7	4	2
2	Mark Pederson	As (MIN)	LW	82	28	35	63	13	4	0	17	86	161	43	146	17.39%	3	1237	15.09	5	16	21	44	328	0	0	0	0	0	5	0	47.19%	89	0	0	1.02	0	0	0	4	4	4
3	Rob DiMaio	As (MIN)	C	76	20	42	62	11	22	0	61	179	225	59	150	8.89%	14	1512	19.90	6	20	26	46	288	1	1	2	8	270	4	1	51.72%	1688	0	1	0.82	0	0	0	7	2	1
4	Alan Kerr	As (MIN)	RW	66	25	35	60	12	73	5	156	160	212	59	135	11.79%	13	1635	24.79	9	10	19	65	268	2	1	3	11	358	1	2	55.27%	1044	0	0	0.73	0	0	1	4	5	6
5	Kelly Chase	As (MIN)	RW	82	20	33	53	0	148	10	215	109	203	52	133	9.85%	8	1209	14.75	3	9	12	24	136	0	0	0	0	11	4	0	46.34%	82	0	0	0.88	1	0	1	0	6	4
6	Darryl Shannon	As (MIN)	D	78	12	38	50	18	18	0	38	92	123	44	91	9.76%	103	1860	23.85	9	7	16	78	307	0	2	2	3	402	3	0	0.00%	0	0	0	0.54	0	0	0	2	4	2
7	Marty McSorley	As (MIN)	D	82	12	36	48	7	183	15	301	86	124	30	74	9.68%	113	1924	23.46	5	8	13	69	327	0	1	1	4	344	1	1	0.00%	0	1	0	0.50	1	0	2	4	2	3
8	Robert Dirk	As (MIN)	D	82	8	30	38	6	100	0	131	64	94	31	54	8.51%	84	1746	21.30	6	8	14	53	285	0	1	1	2	332	0	0	0.00%	0	0	0	0.44	0	0	0	1	1	2
9	Brian Noonan	As (MIN)	RW	68	23	14	37	0	36	0	108	111	173	28	118	13.29%	11	1452	21.35	9	3	12	40	253	1	0	1	9	304	3	1	45.40%	326	0	0	0.51	0	0	0	3	2	1
10	Bryan Marchment	As (MIN)	D	65	10	27	37	-7	130	10	157	89	87	25	57	11.49%	70	1470	22.62	6	10	16	55	240	1	0	1	1	289	2	0	0.00%	0	0	1	0.50	1	0	1	0	3	4
11	Ken Baumgartner	As (MIN)	LW	82	11	17	28	-6	150	20	247	70	139	51	101	7.91%	5	1357	16.56	3	11	14	37	310	0	0	0	1	49	1	1	56.60%	106	0	0	0.41	0	3	1	0	1	2
12	Vladimir Ruzicka	As (MIN)	C	68	12	13	25	4	0	0	7	112	124	26	80	9.68%	0	1053	15.49	0	2	2	4	30	0	1	1	3	175	0	0	51.87%	989	0	0	0.47	0	0	0	2	0	0
13	Dave Brown	As (MIN)	LW	82	10	14	24	-3	72	0	94	78	96	31	77	10.42%	19	1103	13.46	1	0	1	2	4	0	0	0	0	73	1	1	38.94%	113	0	0	0.43	0	0	0	0	1	1
14	Neil Brady	As (MIN)	C	72	12	11	23	-2	8	0	15	91	71	13	49	16.90%	3	574	7.98	0	1	1	1	6	0	0	0	1	56	2	0	51.18%	633	0	0	0.80	0	0	0	0	0	2
15	Bobby Dollas	As (MIN)	D	67	4	16	20	3	18	0	29	67	18	15	26	22.22%	49	984	14.70	0	1	1	1	24	0	0	0	1	66	1	1	0.00%	0	0	0	0.41	0	0	0	0	2	0
16	Enrico Ciccone	As (MIN)	D	72	3	14	17	-4	150	10	222	50	19	9	15	15.79%	66	1066	14.82	0	0	0	0	18	0	0	0	0	139	0	0	0.00%	0	0	0	0.32	0	0	2	0	3	1
17	Randy Ladouceur	As (MIN)	D	27	1	12	13	-3	33	5	48	21	32	3	22	3.13%	35	612	22.69	1	2	3	20	116	0	0	0	1	122	1	0	0.00%	0	0	0	0.42	1	0	0	1	1	0
18	Rob Gaudreau	As (MIN)	RW	53	4	6	10	-4	0	0	0	30	52	12	44	7.69%	2	492	9.30	0	0	0	1	7	0	0	0	0	0	0	1	53.57%	28	0	0	0.41	0	0	0	0	0	0
19	Jim McKenzie	As (MIN)	LW	82	4	4	8	1	36	0	66	25	48	6	25	8.33%	1	323	3.94	0	0	0	1	8	0	0	0	0	4	0	0	43.90%	41	0	0	0.49	0	0	0	0	1	0
20	Troy Mallette	As (MIN)	LW	79	2	6	8	-4	20	0	46	14	17	6	11	11.76%	2	225	2.85	0	2	2	2	31	0	0	0	0	0	1	0	52.27%	88	0	0	0.71	0	0	0	0	0	0
21	Brad Berry	As (MIN)	D	19	1	6	7	2	0	0	4	7	7	11	10	14.29%	14	260	13.71	0	1	1	1	5	0	0	0	0	9	0	0	0.00%	0	0	0	0.54	0	0	0	0	0	1
22	Brad May	As (MIN)	LW	10	0	0	0	0	0	0	1	2	1	0	0	0.00%	0	9	0.98	0	0	0	1	4	0	0	0	0	1	0	0	100.00%	1	0	0	0.00	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1476	251	455	706	44	1227	75	2030	1718	2281	625	1592	11.00%	628	23821	16.14	73	131	204	598	3317	6	9	15	56	3374	37	10	50.62%	6966	2	2	0.59	4	3	8	35	42	36

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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	A	EG	ST	BG	S1	S2	S3
1	Dominic Roussel	As (MIN)	78	35	34	7	0.884	3.23	4443	2	2	239	2053	3	3	76	6	2	2	2
2	Trevor Kidd	As (MIN)	14	2	3	1	0.895	3.11	521	2	0	27	256	0	0	6	76	0	0	0
Stats d'équipe Total ou en Moyenne			92	37	37	8	0.885	3.22	4964	4	2	266	2309	3	3	82	82	2	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

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
Alan Kerr	As (MIN)	RW	30	1991-02-09 9:08:37 PM	No	195 Lbs	5 ft11	No	No	No	1	Pro & Farm	580,000$	58,000$	426$	No
Bobby Dollas	As (MIN)	D	29	1992-02-09 9:08:37 PM	No	220 Lbs	6 ft2	No	No	No	3	Pro & Farm	425,000$	42,500$	312$	No	425,000$	425,000$
Brad Berry	As (MIN)	D	29	1992-02-09 9:08:37 PM	No	205 Lbs	6 ft3	No	No	No	1	Pro & Farm	375,000$	37,500$	276$	No
Brad May	As (MIN)	LW	23	1998-02-09 9:08:37 PM	No	209 Lbs	6 ft0	No	No	No	3	Pro & Farm	275,000$	27,500$	202$	No	275,000$	275,000$
Brian Noonan	As (MIN)	RW	29	1992-02-09 9:08:37 PM	No	180 Lbs	6 ft1	No	No	No	1	Pro & Farm	400,000$	40,000$	294$	No
Bryan Marchment	As (MIN)	D	25	1996-02-09 9:08:37 PM	No	208 Lbs	6 ft1	No	No	No	3	Pro & Farm	706,000$	70,600$	519$	No	706,000$	706,000$
Darryl Shannon	As (MIN)	D	26	1995-02-09 9:08:37 PM	No	208 Lbs	6 ft2	No	No	No	1	Pro & Farm	695,000$	69,500$	511$	No
Dave Brown	As (MIN)	LW	32	1989-02-09 9:08:37 PM	No	205 Lbs	6 ft5	No	No	No	1	Pro & Farm	100,000$	10,000$	74$	No
Dominic Roussel	As (MIN)	G	24	1997-02-09 9:08:37 PM	No	180 Lbs	6 ft1	No	No	No	1	Pro & Farm	250,000$	25,000$	184$	No
Enrico Ciccone	As (MIN)	D	24	1997-02-09 9:08:37 PM	Yes	220 Lbs	6 ft5	No	No	No	1	Pro & Farm	260,000$	26,000$	191$	No
Jim McKenzie	As (MIN)	LW	25	1996-02-09 9:08:37 PM	No	221 Lbs	6 ft4	No	No	No	1	Pro & Farm	400,000$	40,000$	294$	No
Kelly Chase	As (MIN)	RW	27	1994-02-09 9:08:37 PM	No	200 Lbs	6 ft0	No	No	No	3	Pro & Farm	532,000$	53,200$	391$	No	532,000$	532,000$
Ken Baumgartner	As (MIN)	LW	28	1993-02-09 9:08:37 PM	No	215 Lbs	6 ft1	No	No	No	1	Pro & Farm	400,000$	40,000$	294$	No
Mark Pederson	As (MIN)	LW	26	1995-02-09 9:08:37 PM	No	196 Lbs	6 ft2	No	No	No	2	Pro & Farm	365,000$	36,500$	268$	No	365,000$
Marty McSorley	As (MIN)	D	31	1990-02-09 9:08:37 PM	No	225 Lbs	6 ft1	No	No	No	2	Pro & Farm	945,000$	94,500$	695$	No	945,000$
Mike Fountain	As (MIN)	G	22	1999-02-09 9:08:37 PM	Yes	176 Lbs	6 ft1	No	No	No	3	Pro & Farm	450,000$	45,000$	331$	No	450,000$	450,000$
Neil Brady	As (MIN)	C	26	1995-02-09 9:08:37 PM	No	205 Lbs	6 ft3	No	No	No	2	Pro & Farm	400,000$	40,000$	294$	No	400,000$
Randy Ladouceur	As (MIN)	D	34	1987-02-09 9:08:37 PM	No	221 Lbs	6 ft2	No	No	No	1	Pro & Farm	100,000$	10,000$	74$	No
Rob DiMaio	As (MIN)	C	26	1995-02-09 9:08:37 PM	No	190 Lbs	5 ft10	No	No	No	3	Pro & Farm	609,000$	60,900$	448$	No	609,000$	609,000$
Rob Gaudreau	As (MIN)	RW	24	1997-02-09 9:08:37 PM	Yes	185 Lbs	5 ft11	No	No	No	1	Pro & Farm	425,000$	42,500$	312$	No
Robert Dirk	As (MIN)	D	28	1993-02-09 9:08:37 PM	No	207 Lbs	6 ft4	No	No	No	2	Pro & Farm	425,000$	42,500$	312$	No	425,000$
Stephan Lebeau	As (MIN)	C	26	1995-02-09 9:08:37 PM	No	172 Lbs	5 ft10	No	No	No	1	Pro & Farm	486,000$	48,600$	357$	No
Trevor Kidd	As (MIN)	G	22	1999-02-09 9:08:37 PM	Yes	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	350,000$	35,000$	257$	No
Troy Mallette	As (MIN)	LW	24	1997-02-09 9:08:37 PM	No	219 Lbs	6 ft3	No	No	No	3	Pro & Farm	402,000$	40,200$	296$	No	402,000$	402,000$
Vladimir Ruzicka	As (MIN)	C	31	1990-02-09 9:08:37 PM	No	212 Lbs	6 ft3	No	No	No	1	Pro & Farm	650,000$	65,000$	478$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
25	26.84	203 Lbs	6 ft2	1.72	440,200$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mark Pederson	Stephan Lebeau	Alan Kerr	35	1	2	2
2	Ken Baumgartner	Vladimir Ruzicka	Brian Noonan	30	1	2	2
3	Dave Brown	Neil Brady	Kelly Chase	20	1	2	2
4	Jim McKenzie	Alan Kerr	Rob Gaudreau	15	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marty McSorley	Randy Ladouceur	35	1	2	2
2	Bryan Marchment	Robert Dirk	30	1	2	2
3	Bobby Dollas	Brad Berry	20	1	2	2
4	Marty McSorley	Randy Ladouceur	15	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mark Pederson	Stephan Lebeau	Alan Kerr	60	1	2	2
2	Ken Baumgartner	Vladimir Ruzicka	Brian Noonan	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marty McSorley	Randy Ladouceur	60	1	2	2
2	Bryan Marchment	Robert Dirk	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Alan Kerr	Stephan Lebeau	60	1	2	2
2	Brian Noonan	Vladimir Ruzicka	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marty McSorley	Randy Ladouceur	60	1	2	2
2	Bryan Marchment	Robert Dirk	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Alan Kerr	60	1	2	2	Marty McSorley	Randy Ladouceur	60	1	2	2
2	Stephan Lebeau	40	1	2	2	Bryan Marchment	Robert Dirk	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Alan Kerr	Stephan Lebeau	60	1	2	2
2	Brian Noonan	Vladimir Ruzicka	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marty McSorley	Randy Ladouceur	60	1	2	2
2	Bryan Marchment	Robert Dirk	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Mark Pederson	Stephan Lebeau	Alan Kerr	Marty McSorley	Randy Ladouceur

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Mark Pederson	Stephan Lebeau	Alan Kerr	Marty McSorley	Randy Ladouceur

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Troy Mallette, Kelly Chase, Neil Brady	Troy Mallette, Kelly Chase	Neil Brady

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Bobby Dollas, Brad Berry, Bryan Marchment	Bobby Dollas	Brad Berry, Bryan Marchment

Tirs de Pénalité
Alan Kerr, Stephan Lebeau, Brian Noonan, Vladimir Ruzicka, Kelly Chase

Gardien
#1 : Dominic Roussel, #2 : Trevor Kidd

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	Ailes Rouges	9	4	2	2	1	0	0	0	27	24	3	5	2	1	1	1	0	0	0	15	14	1	4	2	1	1	0	0	0	0	12	10	2	12	0.667	27	48	75	0	0	88	87	72	4	254	730	749	775	27	243	69	154	222	53	11	20.75%	59	7	88.14%	1	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
2	Banshees	5	3	2	0	0	0	0	0	14	18	-4	2	1	1	0	0	0	0	0	7	9	-2	3	2	1	0	0	0	0	0	7	9	-2	6	0.600	14	27	41	0	1	88	87	72	4	111	730	749	775	27	130	30	81	129	18	2	11.11%	31	8	74.19%	1	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
3	Canadiens	6	1	4	1	0	0	0	0	18	24	-6	2	0	2	0	0	0	0	0	3	6	-3	4	1	2	1	0	0	0	0	15	18	-3	3	0.250	18	32	50	0	0	88	87	72	4	203	730	749	775	27	162	35	87	135	30	10	33.33%	38	9	76.32%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
4	Chiefs	5	1	3	1	0	0	0	0	14	20	-6	3	1	1	1	0	0	0	0	10	11	-1	2	0	2	0	0	0	0	0	4	9	-5	3	0.300	14	26	40	0	0	88	87	72	4	124	730	749	775	27	133	48	76	114	30	3	10.00%	35	11	68.57%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
5	Citadelles	6	3	2	1	0	0	0	0	21	18	3	3	1	1	1	0	0	0	0	11	10	1	3	2	1	0	0	0	0	0	10	8	2	7	0.583	21	38	59	1	0	88	87	72	4	153	730	749	775	27	191	54	100	139	24	5	20.83%	50	4	92.00%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
6	Croque-Morts	10	3	7	0	0	0	0	0	33	39	-6	5	2	3	0	0	0	0	0	22	19	3	5	1	4	0	0	0	0	0	11	20	-9	6	0.300	33	59	92	1	0	88	87	72	4	277	730	749	775	27	305	90	116	267	57	13	22.81%	55	11	80.00%	1	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
7	Harvard	6	4	2	0	0	0	0	0	18	16	2	3	1	2	0	0	0	0	0	3	9	-6	3	3	0	0	0	0	0	0	15	7	8	8	0.667	18	32	50	0	0	88	87	72	4	179	730	749	775	27	152	35	89	144	34	6	17.65%	37	7	81.08%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
8	Isotopes	5	3	0	1	1	0	0	0	20	10	10	3	1	0	1	1	0	0	0	9	7	2	2	2	0	0	0	0	0	0	11	3	8	9	0.900	20	38	58	0	0	88	87	72	4	164	730	749	775	27	144	42	68	118	24	5	20.83%	29	2	93.10%	2	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
9	Pacifiques de la route	7	4	2	1	0	0	0	0	21	18	3	4	2	2	0	0	0	0	0	12	12	0	3	2	0	1	0	0	0	0	9	6	3	9	0.643	21	38	59	0	0	88	87	72	4	178	730	749	775	27	196	42	130	178	25	5	20.00%	45	7	84.44%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
10	Riverman	5	0	4	1	0	0	0	0	9	18	-9	2	0	2	0	0	0	0	0	5	10	-5	3	0	2	1	0	0	0	0	4	8	-4	1	0.100	9	17	26	0	0	88	87	72	4	138	730	749	775	27	158	30	65	119	23	2	8.70%	29	8	72.41%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
11	Snipers	5	0	3	0	2	0	0	0	16	22	-6	3	0	2	0	1	0	0	0	10	15	-5	2	0	1	0	1	0	0	0	6	7	-1	4	0.400	16	29	45	0	0	88	87	72	4	131	730	749	775	27	156	40	80	139	18	2	11.11%	38	10	73.68%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
12	Spoonman's	5	1	3	0	0	1	0	0	10	19	-9	2	0	1	0	0	1	0	0	4	8	-4	3	1	2	0	0	0	0	0	6	11	-5	3	0.300	10	18	28	0	1	88	87	72	4	136	730	749	775	27	146	54	86	110	21	2	9.52%	37	9	75.68%	0	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
13	Wolves	8	6	2	0	0	0	0	0	30	23	7	4	3	1	0	0	0	0	0	18	12	6	4	3	1	0	0	0	0	0	12	11	1	12	0.750	30	53	83	1	0	88	87	72	4	233	730	749	775	27	196	59	99	216	49	7	14.29%	45	9	80.00%	1	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
	Total	82	33	36	8	4	1	0	0	251	269	-18	41	14	19	4	3	1	0	0	129	142	-13	41	19	17	4	1	0	0	0	122	127	-5	83	0.506	251	455	706	3	2	88	87	72	4	2281	730	749	775	27	2312	628	1231	2030	406	73	17.98%	528	102	80.68%	6	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
	_Since Last GM Reset	82	41	36	0	4	1	0	0	251	269	-18	41	14	19	4	3	1	0	0	129	142	-13	41	27	17	-4	1	0	0	0	122	127	-5	91	0.555	251	455	706	3	2	88	87	72	4	2281	730	749	775	27	2312	628	1231	2030	406	73	17.98%	528	102	80.68%	6	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
	_Vs Conference	44	21	20	0	3	0	0	0	136	144	-8	23	9	11	1	2	0	0	0	82	82	0	21	12	9	-1	1	0	0	0	54	62	-8	48	0.545	136	244	380	2	0	88	87	72	4	1211	730	749	775	27	1254	330	644	1141	225	40	17.78%	271	52	80.81%	3	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524
	_Vs Division	27	15	11	0	1	0	0	0	90	86	4	14	7	5	1	1	0	0	0	55	45	10	13	8	6	-1	0	0	0	0	35	41	-6	32	0.593	90	160	250	2	0	88	87	72	4	764	730	749	775	27	744	218	369	705	159	31	19.50%	159	27	83.02%	3	1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%	1947	1285	1957	654	1069	524

			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
82	83	OTL1	251	455	706	2281	2312	628	1231	2030	3	2

Tous les Matchs
GP	W	L	OTW	OTL	T	GF	GA
82	33	36	4	1	8	251	269

Matchs locaux
GP	W	L	OTW	OTL	T	GF	GA
41	14	19	3	1	4	129	142

Matchs Éxtérieurs
GP	W	L	OTW	OTL	T	GF	GA
41	19	17	1	0	4	122	127

Derniers 10 Matchs
W	L	OTW	OTL	T
3	5	0	1	1

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
406	73	17.98%	528	102	80.68%	6

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
730	749	775	27	88	87	72	4

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
1386	2782	49.82%	1473	2870	51.32%	667	1314	50.76%

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
1947	1285	1957	654	1069	524

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 - 2020-09-21	3	As	3	Croque-Morts	5	L		Sommaire du Match
2 - 2020-09-22	12	Croque-Morts	2	As	6	W		Sommaire du Match
4 - 2020-09-24	19	As	4	Canadiens	4	T	X	Sommaire du Match
5 - 2020-09-25	23	Ailes Rouges	4	As	5	W	X	Sommaire du Match
6 - 2020-09-26	30	As	3	Wolves	1	W		Sommaire du Match
8 - 2020-09-28	38	Wolves	4	As	2	L		Sommaire du Match
9 - 2020-09-29	45	As	2	Croque-Morts	3	L		Sommaire du Match
10 - 2020-09-30	52	As	4	Banshees	3	W		Sommaire du Match
11 - 2020-10-01	55	Croque-Morts	5	As	3	L		Sommaire du Match
14 - 2020-10-04	66	Ailes Rouges	3	As	1	L		Sommaire du Match
15 - 2020-10-05	71	As	4	Canadiens	3	W		Sommaire du Match
17 - 2020-10-07	77	Pacifiques de la route	2	As	3	W		Sommaire du Match
19 - 2020-10-09	83	As	5	Harvard	4	W		Sommaire du Match
21 - 2020-10-11	91	As	2	Pacifiques de la route	2	T	X	Sommaire du Match
23 - 2020-10-13	98	Wolves	2	As	4	W		Sommaire du Match
25 - 2020-10-15	106	As	5	Ailes Rouges	3	W		Sommaire du Match
27 - 2020-10-17	110	Snipers	8	As	3	L		Sommaire du Match
29 - 2020-10-19	121	Chiefs	3	As	4	W		Sommaire du Match
31 - 2020-10-21	128	As	3	Pacifiques de la route	2	W		Sommaire du Match
33 - 2020-10-23	133	As	2	Banshees	6	L		Sommaire du Match
35 - 2020-10-25	138	As	4	Canadiens	6	L		Sommaire du Match
37 - 2020-10-27	145	Chiefs	4	As	2	L		Sommaire du Match
39 - 2020-10-29	153	Wolves	4	As	5	W		Sommaire du Match
41 - 2020-10-31	162	As	1	Croque-Morts	2	L		Sommaire du Match
42 - 2020-11-01	166	Riverman	6	As	2	L		Sommaire du Match
44 - 2020-11-03	177	Ailes Rouges	1	As	2	W		Sommaire du Match
46 - 2020-11-05	184	As	1	Chiefs	5	L		Sommaire du Match
47 - 2020-11-06	191	As	1	Banshees	0	W		Sommaire du Match
49 - 2020-11-08	196	Snipers	4	As	5	W	X	Sommaire du Match
50 - 2020-11-09	205	Snipers	3	As	2	L		Sommaire du Match
52 - 2020-11-11	212	As	4	Wolves	3	W		Sommaire du Match
53 - 2020-11-12	218	Banshees	2	As	4	W		Sommaire du Match
55 - 2020-11-14	221	As	6	Isotopes	1	W		Sommaire du Match
57 - 2020-11-16	233	Harvard	1	As	2	W		Sommaire du Match
58 - 2020-11-17	241	As	3	Citadelles	5	L		Sommaire du Match
60 - 2020-11-19	247	Pacifiques de la route	1	As	6	W		Sommaire du Match
61 - 2020-11-20	253	As	1	Wolves	6	L		Sommaire du Match
62 - 2020-11-21	255	As	3	Citadelles	2	W		Sommaire du Match
64 - 2020-11-23	264	Citadelles	3	As	3	T	X	Sommaire du Match
65 - 2020-11-24	271	As	2	Riverman	4	L		Sommaire du Match
67 - 2020-11-26	277	Citadelles	4	As	3	L		Sommaire du Match
68 - 2020-11-27	288	As	3	Snipers	2	W	X	Sommaire du Match
70 - 2020-11-29	293	Canadiens	3	As	1	L		Sommaire du Match
72 - 2020-12-01	303	As	3	Harvard	1	W		Sommaire du Match
73 - 2020-12-02	306	Harvard	4	As	0	L		Sommaire du Match
74 - 2020-12-03	317	Ailes Rouges	5	As	5	T	X	Sommaire du Match
75 - 2020-12-04	321	As	1	Spoonman's	5	L		Sommaire du Match
77 - 2020-12-06	327	As	2	Riverman	2	T	X	Sommaire du Match
78 - 2020-12-07	335	Croque-Morts	2	As	6	W		Sommaire du Match
79 - 2020-12-08	340	As	2	Croque-Morts	8	L		Sommaire du Match
80 - 2020-12-09	348	Citadelles	3	As	5	W		Sommaire du Match
82 - 2020-12-11	353	As	1	Spoonman's	6	L		Sommaire du Match
84 - 2020-12-13	363	Ailes Rouges	1	As	2	W		Sommaire du Match
86 - 2020-12-15	371	As	5	Isotopes	2	W		Sommaire du Match
88 - 2020-12-17	376	Banshees	7	As	3	L		Sommaire du Match
90 - 2020-12-19	386	As	4	Pacifiques de la route	2	W		Sommaire du Match
92 - 2020-12-21	390	Croque-Morts	5	As	4	L		Sommaire du Match
94 - 2020-12-23	400	Isotopes	2	As	3	W		Sommaire du Match
96 - 2020-12-25	404	As	7	Harvard	2	W		Sommaire du Match
98 - 2020-12-27	414	As	2	Ailes Rouges	2	T	X	Sommaire du Match
100 - 2020-12-29	418	Wolves	2	As	7	W		Sommaire du Match
101 - 2020-12-30	424	As	0	Riverman	2	L		Sommaire du Match
103 - 2021-01-01	432	Spoonman's	4	As	1	L		Sommaire du Match
105 - 2021-01-03	442	Isotopes	2	As	3	W	X	Sommaire du Match
106 - 2021-01-04	445	As	3	Snipers	5	L		Sommaire du Match
108 - 2021-01-06	450	As	4	Spoonman's	0	W		Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
110 - 2021-01-08	459	Pacifiques de la route	6	As	2	L		Sommaire du Match
112 - 2021-01-10	465	As	3	Canadiens	5	L		Sommaire du Match
113 - 2021-01-11	473	Croque-Morts	5	As	3	L		Sommaire du Match
115 - 2021-01-13	479	As	3	Croque-Morts	2	W		Sommaire du Match
116 - 2021-01-14	486	As	3	Chiefs	4	L		Sommaire du Match
117 - 2021-01-15	491	Chiefs	4	As	4	T	X	Sommaire du Match
118 - 2021-01-16	500	Isotopes	3	As	3	T	X	Sommaire du Match
120 - 2021-01-18	509	As	4	Wolves	1	W		Sommaire du Match
121 - 2021-01-19	515	Pacifiques de la route	3	As	1	L		Sommaire du Match
123 - 2021-01-21	528	Harvard	4	As	1	L		Sommaire du Match
124 - 2021-01-22	531	As	4	Ailes Rouges	3	W		Sommaire du Match
126 - 2021-01-24	541	Canadiens	3	As	2	L		Sommaire du Match
127 - 2021-01-25	543	As	1	Ailes Rouges	2	L		Sommaire du Match
130 - 2021-01-28	556	Riverman	4	As	3	L		Sommaire du Match
133 - 2021-01-31	565	As	4	Citadelles	1	W		Sommaire du Match
134 - 2021-02-01	569	Spoonman's	4	As	3	L	X	Sommaire du Match

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
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
1,134,525$	1,100,500$	1,040,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
1,100,500$	1,134,525$	25	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	1	8,790$	8,790$

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

	As
	GP: 82 \| W: 37 \| L: 36 \| T: 8 \| P: 83 GF: 251 \| GA: 269 \| PP%: 17.98% \| PK%: 80.68% DG: Christian Nolet \| Morale : 51 \| Moyenne d'Équipe : 65