Ligue de hockey Simulée Ste-Flanelle

Winnipeg
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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 Moyen
1	Conor Sheary		X			100.00	63	41	94	84	61	65	88	64	30	65	68	58	63	66	68	0	50	64	0	27	7	2,800,000$
2	Jordan Nolan		X	X		100.00	80	75	75	61	80	70	82	60	43	55	56	73	54	67	69	0	50	62	0	30	1	1,000,000$
3	Frederik Gauthier	X				100.00	77	48	94	70	88	56	83	56	68	57	57	73	25	63	64	0	50	62	0	24	5	1,200,000$
4	Micheal Ferland		X	X		100.00	93	79	84	80	79	59	62	59	27	72	61	56	25	65	66	0	50	62	0	27	4	3,000,000$
5	Michael Rasmussen	X				100.00	84	85	83	68	85	66	67	62	78	61	58	70	55	51	51	0	50	62	0	20	3	925,000$
6	Glenn Gawdin	X				100.00	75	71	84	64	71	74	76	66	80	67	61	65	58	44	44	0	50	62	0	22	1	650,000$
7	Mathieu Joseph		X	X		100.00	78	45	87	82	65	61	85	59	37	58	61	67	25	57	58	0	50	62	0	22	1	650,000$
8	Nic Petan	X	X	X		100.00	62	44	92	79	62	55	57	66	47	62	55	72	25	59	59	0	50	61	0	24	3	693,000$
9	Nicolas Roy	X				100.00	79	53	89	68	78	65	82	59	69	60	66	66	25	47	47	0	50	61	0	22	1	650,000$
10	Trevor Moore		X			100.00	76	45	95	66	61	62	75	64	40	60	62	74	25	52	53	0	50	61	0	24	2	925,000$
11	Joakim Nygard (R)		X			100.00	65	41	91	90	65	57	61	61	44	64	59	61	25	47	47	0	50	60	0	26	1	565,000$
12	Mark Pysyk				X	100.00	74	43	89	80	74	65	81	56	38	51	55	72	25	67	67	0	50	65	0	27	1	2,875,000$
13	Lawrence Pilut				X	100.00	71	42	90	77	61	69	74	56	25	39	47	80	25	48	48	0	50	63	0	23	2	925,000$
14	Jacob Middleton				X	100.00	81	91	73	68	79	60	68	58	25	50	45	68	25	51	51	0	50	61	0	23	2	735,000$
15	Nick DeSimone				X	100.00	78	72	87	65	72	69	73	50	25	46	43	64	40	44	44	0	50	59	0	24	3	700,000$
16	Maxime Lajoie				X	100.00	72	62	86	77	68	70	74	52	25	44	43	59	39	51	51	0	50	59	0	21	2	730,000$
Rayé
1	J.C. Beaudin (R)	X				100.00	88	75	89	75	71	52	66	58	73	55	55	67	25	46	46	0	50	59	0	22	1	700,000$
2	Karson Kuhlman	X		X		100.00	79	67	84	65	67	63	69	60	32	65	56	61	25	47	48	0	50	58	0	24	3	775,000$
3	Jeffrey Viel (R)		X			100.00	65	71	50	64	71	74	78	60	50	56	60	59	57	44	44	0	50	58	0	20	1	630,000$
4	Giorgio Estephan (R)	X				100.00	79	71	99	52	71	58	60	51	64	46	51	63	48	44	44	0	50	53	0	22	2	525,000$
5	Artur Kayumov (R)		X	X		100.00	41	45	45	45	53	39	39	41	45	41	41	45	43	32	30	0	50	41	0	21	2	825,000$
6	William Lockwood (R)			X		100.00	39	43	43	43	51	37	37	39	43	39	39	43	41	32	30	0	50	39	0	21	2	700,000$
7	Pavel Karnaukhov (R)		X			100.00	32	37	37	37	67	31	31	32	37	32	32	37	34	32	30	0	50	35	0	22	1	525,000$
8	Logan Stanley				X	100.00	78	87	56	62	87	68	74	47	25	37	41	62	39	44	44	0	50	58	0	21	2	925,000$
9	Scott Walford (R)				X	100.00	54	50	84	66	72	69	95	48	25	50	37	52	39	54	54	0	50	57	0	20	1	560,000$
10	Chad Krys (R)				X	100.00	73	67	86	67	67	57	60	47	25	37	41	59	39	44	44	0	50	55	0	21	2	825,000$
11	Mitchell Vande Sompel (R)				X	100.00	37	43	43	43	60	35	35	37	43	37	37	43	40	32	30	0	50	40	0	22	1	700,000$

	MOYENNE D'ÉQUIPE					100.00	69	59	78	67	70	59	68	54	43	52	51	62	37	49	49	0	50	57

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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	Collin Delia	100.00	57	66	78	75	63	65	61	60	65	57	30	45	45	0	50	61	0
2	Joren Van Pottelberghe (R)	100.00	36	40	38	68	35	34	34	34	34	34	33	32	30	0	50	38	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	47	53	58	72	49	50	48	47	50	46	32	39	38	0	50	50

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

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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	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Frederik Gauthier	Oceanics (Win)	C	82	38	52	90	48	14	0	101	255	269	88	175	14.13%	31	1709	20.84	8	7	15	54	222	0	1	1	5	249	11	1	60.61%	2640	0	1	1.05	3	9	0	0	0	7	6	4
2	Conor Sheary	Oceanics (Win)	LW	71	31	47	78	31	8	0	18	127	323	75	221	9.60%	7	1297	18.27	4	11	15	54	191	0	1	1	4	74	5	1	47.71%	109	0	1	1.20	5	7	0	0	0	5	4	2
3	Nick Bjugstad	Winnipeg	C/RW	52	27	43	70	28	28	0	131	98	239	67	167	11.30%	7	1085	20.88	3	8	11	43	140	0	0	0	8	155	4	3	47.67%	86	1	1	1.29	3	5	0	0	0	6	2	9
4	Lawrence Pilut	Oceanics (Win)	D	82	20	46	66	44	40	0	130	99	238	83	151	8.40%	138	1950	23.78	7	14	21	98	225	0	0	0	1	224	4	0	0.00%	0	0	0	0.68	0	0	0	0	0	5	4	2
5	Mark Pysyk	Oceanics (Win)	D	80	12	52	64	44	36	0	149	84	181	51	119	6.63%	114	1911	23.89	4	15	19	81	219	0	0	0	2	222	4	0	0.00%	0	0	0	0.67	0	0	0	0	0	2	4	7
6	Nic Petan	Oceanics (Win)	C/LW/RW	82	28	36	64	22	6	0	21	194	272	74	224	10.29%	15	1250	15.25	3	3	6	26	100	2	0	2	6	69	2	2	43.71%	151	0	1	1.02	0	1	0	0	0	4	4	0
7	Michael Rasmussen	Oceanics (Win)	C	79	23	39	62	24	49	5	129	184	284	76	170	8.10%	26	1439	18.22	5	7	12	52	208	0	0	0	9	149	2	1	63.41%	1943	0	0	0.86	1	4	1	0	0	3	4	3
8	Mathieu Joseph	Oceanics (Win)	LW/RW	77	25	33	58	34	16	0	82	144	335	80	213	7.46%	21	1403	18.23	6	4	10	63	198	0	0	0	10	141	3	1	32.04%	103	0	1	0.83	0	2	0	0	0	2	5	6
9	Trevor Moore	Oceanics (Win)	LW	82	29	29	58	21	18	0	72	112	257	72	174	11.28%	14	1038	12.67	0	1	1	1	7	0	0	0	0	1	4	0	51.56%	64	0	2	1.12	0	0	0	0	0	4	4	1
10	Micheal Ferland	Oceanics (Win)	LW/RW	82	21	35	56	17	66	0	204	105	258	69	179	8.14%	5	1232	15.03	2	9	11	34	145	0	0	0	0	6	2	1	38.89%	90	0	0	0.91	0	0	0	0	0	1	4	2
11	Glenn Gawdin	Oceanics (Win)	C	82	11	40	51	21	34	0	103	144	204	53	169	5.39%	12	1048	12.79	0	0	0	2	12	0	0	0	0	4	0	0	59.74%	1242	0	0	0.97	0	1	0	0	0	1	2	3
12	Jacob Middleton	Oceanics (Win)	D	80	9	40	49	43	102	20	247	53	134	38	76	6.72%	114	1677	20.96	0	5	5	45	194	0	0	0	1	187	2	1	0.00%	0	0	0	0.58	0	0	2	0	2	2	4	4
13	Joakim Nygard	Oceanics (Win)	LW	82	15	25	40	16	10	0	34	106	183	58	116	8.20%	9	643	7.85	0	0	0	0	2	0	0	0	0	1	3	1	41.67%	36	0	0	1.24	0	0	0	0	0	0	3	1
14	Nicolas Roy	Oceanics (Win)	C	82	16	20	36	16	18	0	87	79	194	43	113	8.25%	9	642	7.84	0	0	0	1	0	0	0	0	0	0	3	1	58.06%	732	0	1	1.12	0	0	0	0	0	1	2	1
15	Jordan Nolan	Oceanics (Win)	LW/RW	39	16	19	35	28	53	15	73	50	137	31	110	11.68%	8	779	19.99	3	2	5	16	113	1	0	1	7	106	0	4	44.83%	58	0	0	0.90	2	5	1	1	1	3	1	4
16	Nick DeSimone	Oceanics (Win)	D	82	8	23	31	43	44	0	106	32	92	17	48	8.70%	107	1774	21.65	4	4	8	33	210	0	0	0	2	214	0	1	0.00%	0	0	0	0.35	0	1	0	0	0	1	2	1
17	Logan Stanley	Oceanics (Win)	D	74	6	14	20	20	89	5	222	28	59	14	26	10.17%	57	1096	14.81	0	0	0	2	11	0	1	1	0	16	3	0	0.00%	0	0	0	0.36	0	0	0	0	1	0	1	3
18	Maxime Lajoie	Oceanics (Win)	D	82	3	17	20	19	40	0	60	32	44	22	29	6.82%	72	1293	15.77	0	0	0	4	26	0	1	1	0	65	0	0	0.00%	0	0	0	0.31	0	0	0	0	0	1	0	1
19	Karson Kuhlman	Oceanics (Win)	C/RW	16	7	12	19	12	4	0	32	17	53	10	30	13.21%	1	267	16.74	1	1	2	4	27	0	0	0	2	10	1	1	27.50%	40	0	0	1.42	0	0	0	0	0	2	1	0
20	J.C. Beaudin	Oceanics (Win)	C	3	2	0	2	-2	2	0	15	4	8	3	6	25.00%	0	48	16.16	0	0	0	1	4	0	0	0	0	3	0	0	57.75%	71	0	0	0.83	0	0	0	0	0	0	0	0
21	Scott Walford	Oceanics (Win)	D	2	0	1	1	4	0	0	0	2	2	0	0	0.00%	0	31	15.97	0	0	0	0	0	0	0	0	0	1	0	0	0.00%	0	0	0	0.63	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1393	347	623	970	533	677	45	2016	1949	3766	1024	2516	9.21%	767	23623	16.96	50	91	141	614	2265	3	4	7	57	1908	53	19	59.09%	7365	1	8	0.82	14	35	4	1	4	50	57	54

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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	PS %	PSA	ST	BG	S1	S2	S3
1	Collin Delia	Oceanics (Win)	80	54	21	3	0.909	2.78	4710	6	2	218	2387	1	4	0.700	20	80	0	5	4	1
2	Joren Van Pottelberghe	Oceanics (Win)	4	1	1	0	0.930	2.93	123	0	0	6	86	0	0	0.750	4	0	82	0	0	0
Stats d'équipe Total ou en Moyenne			84	55	22	3	0.909	2.78	4833	6	2	224	2473	1	4	0.708	24	80	82	5	4	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 Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Salaire Année 7	Link
Artur Kayumov	Oceanics (Win)	LW/RW	21	1998-02-14	Yes	176 Lbs	5 ft11	No	No	No	2	Pro & Farm	825,000$	82,500$	0$	No	825,000$						Lien
Chad Krys	Oceanics (Win)	D	21	1998-04-10	Yes	185 Lbs	5 ft11	No	No	No	2	Pro & Farm	825,000$	82,500$	0$	No	825,000$						Lien
Collin Delia	Oceanics (Win)	G	25	1994-06-19	No	190 Lbs	6 ft2	No	No	No	4	Pro & Farm	1,000,000$	100,000$	0$	No	1,000,000$	1,000,000$	1,000,000$				Lien
Conor Sheary	Oceanics (Win)	LW	27	1992-06-08	No	175 Lbs	5 ft8	No	No	No	7	Pro & Farm	2,800,000$	280,000$	0$	No	2,800,000$	2,800,000$	2,800,000$	2,800,000$	2,800,000$	2,800,000$	Lien
Frederik Gauthier	Oceanics (Win)	C	24	1995-04-26	No	238 Lbs	6 ft5	No	No	No	5	Pro & Farm	1,200,000$	120,000$	0$	No	1,200,000$	1,200,000$	1,200,000$	1,200,000$			Lien
Giorgio Estephan	Oceanics (Win)	C	22	1997-02-03	Yes	196 Lbs	6 ft0	No	No	No	2	Pro & Farm	525,000$	52,500$	0$	No	525,000$						Lien
Glenn Gawdin	Oceanics (Win)	C	22	1997-03-25	No	191 Lbs	6 ft1	No	No	No	1	Pro & Farm	650,000$	65,000$	0$	No							Lien
J.C. Beaudin	Oceanics (Win)	C	22	1997-03-24	Yes	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	70,000$	0$	No							Lien
Jacob Middleton	Oceanics (Win)	D	23	1996-01-01	No	200 Lbs	6 ft3	No	No	No	2	Pro & Farm	735,000$	73,500$	0$	No	735,000$						Lien
Jeffrey Viel	Oceanics (Win)	LW	20	1999-01-28	Yes	196 Lbs	6 ft0	Yes	No	No	1	Pro & Farm	630,000$	63,000$	0$	No							Lien
Joakim Nygard	Oceanics (Win)	LW	26	1993-01-08	Yes	179 Lbs	6 ft0	Yes	No	No	1	Pro & Farm	565,000$	56,500$	0$	No							Lien
Jordan Nolan	Oceanics (Win)	LW/RW	30	1989-06-22	No	219 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,000,000$	100,000$	0$	No							Lien
Joren Van Pottelberghe	Oceanics (Win)	G	22	1997-06-05	Yes	187 Lbs	6 ft2	No	No	No	1	Pro & Farm	650,000$	65,000$	0$	No							Lien
Karson Kuhlman	Oceanics (Win)	C/RW	24	1995-09-26	No	180 Lbs	5 ft11	No	No	No	3	Pro & Farm	775,000$	77,500$	0$	No	775,000$	775,000$					Lien
Lawrence Pilut	Oceanics (Win)	D	23	1995-12-29	No	165 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	92,500$	0$	No	925,000$						Lien
Logan Stanley	Oceanics (Win)	D	21	1998-05-25	No	228 Lbs	6 ft7	No	No	No	2	Pro & Farm	925,000$	92,500$	0$	No	925,000$						Lien
Mark Pysyk	Oceanics (Win)	D	27	1992-01-11	No	200 Lbs	6 ft1	No	No	No	1	Pro & Farm	4,000,000$	287,500$	0$	No							Lien
Mathieu Joseph	Oceanics (Win)	LW/RW	22	1997-02-09	No	173 Lbs	6 ft1	No	No	No	1	Pro & Farm	650,000$	65,000$	0$	No							Lien
Maxime Lajoie	Oceanics (Win)	D	21	1997-11-05	No	183 Lbs	6 ft1	No	No	No	2	Pro & Farm	730,000$	73,000$	0$	No	730,000$						Lien
Michael Rasmussen	Oceanics (Win)	C	20	1999-04-17	No	220 Lbs	6 ft6	No	No	No	3	Pro & Farm	925,000$	92,500$	0$	No	925,000$	925,000$					Lien
Micheal Ferland	Oceanics (Win)	LW/RW	27	1992-04-19	No	208 Lbs	6 ft2	No	No	No	4	Pro & Farm	3,000,000$	300,000$	0$	No	3,000,000$	3,000,000$	3,000,000$				Lien
Mitchell Vande Sompel	Oceanics (Win)	D	22	1997-02-11	Yes	190 Lbs	5 ft10	No	No	No	1	Pro & Farm	700,000$	70,000$	0$	No							Lien
Nic Petan	Oceanics (Win)	C/LW/RW	24	1995-03-21	No	179 Lbs	5 ft9	No	No	No	3	Pro & Farm	693,000$	69,300$	0$	No	693,000$	693,000$					Lien
Nick DeSimone	Oceanics (Win)	D	24	1994-11-21	No	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	700,000$	70,000$	0$	No	700,000$	700,000$					Lien
Nicolas Roy	Oceanics (Win)	C	22	1997-02-05	No	208 Lbs	6 ft4	No	No	No	1	Pro & Farm	650,000$	65,000$	0$	No							Lien
Pavel Karnaukhov	Oceanics (Win)	LW	22	1997-03-15	Yes	194 Lbs	6 ft3	No	No	No	1	Pro & Farm	525,000$	52,500$	0$	No							Lien
Scott Walford	Oceanics (Win)	D	20	1999-01-12	Yes	198 Lbs	6 ft2	Yes	No	No	1	Pro & Farm	560,000$	56,000$	0$	No							Lien
Trevor Moore	Oceanics (Win)	LW	24	1995-03-31	No	170 Lbs	5 ft9	No	No	No	2	Pro & Farm	925,000$	92,500$	0$	No	925,000$						Lien
William Lockwood	Oceanics (Win)	RW	21	1998-06-20	Yes	172 Lbs	5 ft11	No	No	No	2	Pro & Farm	700,000$	70,000$	0$	No	700,000$						Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
29	23.07	192 Lbs	6 ft1	2.14	1,016,828$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Conor Sheary	Frederik Gauthier	Mathieu Joseph	35	0	1	4
2	Jordan Nolan	Michael Rasmussen	Nic Petan	30	0	2	3
3	Trevor Moore	Glenn Gawdin	Micheal Ferland	25	0	2	3
4	Joakim Nygard	Nicolas Roy		10	0	2	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Pysyk	Lawrence Pilut	45	0	2	3
2	Jacob Middleton	Nick DeSimone	35	1	1	3
3	Maxime Lajoie		10	1	2	2
4	Mark Pysyk	Lawrence Pilut	10	0	1	4

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Conor Sheary	Frederik Gauthier	Mathieu Joseph	60	0	0	5
2	Jordan Nolan	Michael Rasmussen	Nic Petan	40	0	0	5

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Lawrence Pilut	Mark Pysyk	60	0	1	4
2	Jacob Middleton	Nick DeSimone	40	0	1	4

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Frederik Gauthier	Jordan Nolan	60	0	5	0
2	Michael Rasmussen	Conor Sheary	40	0	5	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Pysyk	Lawrence Pilut	60	0	5	0
2	Jacob Middleton	Nick DeSimone	40	0	5	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Frederik Gauthier	60	0	5	0	Lawrence Pilut	Mark Pysyk	60	0	5	0
2	Michael Rasmussen	40	0	5	0	Jacob Middleton	Nick DeSimone	40	0	5	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Frederik Gauthier	Conor Sheary	60	0	1	4
2	Michael Rasmussen	Nic Petan	40	0	1	4

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Lawrence Pilut	Mark Pysyk	60	0	1	4
2	Jacob Middleton	Nick DeSimone	40	0	2	3

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Conor Sheary	Frederik Gauthier	Mathieu Joseph	Mark Pysyk	Lawrence Pilut

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Micheal Ferland	Michael Rasmussen	Nic Petan	Mark Pysyk	Lawrence Pilut

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jordan Nolan, Frederik Gauthier, Conor Sheary	Conor Sheary, Michael Rasmussen	Jordan Nolan

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Mark Pysyk, Lawrence Pilut, Jacob Middleton	Mark Pysyk	Mark Pysyk, Lawrence Pilut

Tirs de Pénalité
Frederik Gauthier, Jordan Nolan, Conor Sheary, Michael Rasmussen, Mathieu Joseph

Gardien
#1 : Collin Delia, #2 : Joren Van Pottelberghe

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	Admirals	3	1	2	0	0	0	0	0	11	9	2	1	1	0	0	0	0	0	0	8	3	5	2	0	2	0	0	0	0	0	3	6	-3	2	0.333	11	19	30	0	0	135	109	96	17	125	1248	1155	1290	80	76	30	20	85	8	3	37.50%	10	3	70.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
2	Baby Hawks	5	4	1	0	0	0	0	0	22	11	11	3	3	0	0	0	0	0	0	14	7	7	2	1	1	0	0	0	0	0	8	4	4	8	0.800	22	35	57	0	0	135	109	96	17	215	1248	1155	1290	80	143	43	18	120	29	7	24.14%	7	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
3	Bears	2	1	0	0	0	0	1	0	10	7	3	1	0	0	0	0	0	1	0	6	5	1	1	1	0	0	0	0	0	0	4	2	2	4	1.000	10	15	25	0	0	135	109	96	17	112	1248	1155	1290	80	71	15	6	37	9	1	11.11%	3	1	66.67%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
4	Bruins	2	0	1	0	1	0	0	0	5	8	-3	1	0	1	0	0	0	0	0	3	7	-4	1	0	0	0	1	0	0	0	2	1	1	2	0.500	5	10	15	0	0	135	109	96	17	70	1248	1155	1290	80	56	20	12	46	7	1	14.29%	6	2	66.67%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
5	Cabaret Lady Mary Ann	2	2	0	0	0	0	0	0	14	3	11	1	1	0	0	0	0	0	0	8	1	7	1	1	0	0	0	0	0	0	6	2	4	4	1.000	14	26	40	0	0	135	109	96	17	122	1248	1155	1290	80	62	23	15	61	1	1	100.00%	5	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
6	Caroline	2	2	0	0	0	0	0	0	10	3	7	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	6	1	5	4	1.000	10	19	29	0	0	135	109	96	17	87	1248	1155	1290	80	54	10	16	55	5	1	20.00%	7	1	85.71%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
7	Chiefs	4	1	3	0	0	0	0	0	12	16	-4	2	1	1	0	0	0	0	0	6	6	0	2	0	2	0	0	0	0	0	6	10	-4	2	0.250	12	23	35	1	0	135	109	96	17	157	1248	1155	1290	80	144	46	58	122	13	2	15.38%	19	3	84.21%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
8	Chill	4	3	1	0	0	0	0	0	19	13	6	2	2	0	0	0	0	0	0	11	5	6	2	1	1	0	0	0	0	0	8	8	0	6	0.750	19	35	54	0	0	135	109	96	17	162	1248	1155	1290	80	142	50	51	94	19	4	21.05%	17	4	76.47%	1	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
9	Comets	3	3	0	0	0	0	0	0	18	8	10	2	2	0	0	0	0	0	0	15	7	8	1	1	0	0	0	0	0	0	3	1	2	6	1.000	18	34	52	0	0	135	109	96	17	144	1248	1155	1290	80	98	26	18	89	11	4	36.36%	8	1	87.50%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
10	Cougars	2	1	1	0	0	0	0	0	6	9	-3	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	3	7	-4	2	0.500	6	12	18	0	0	135	109	96	17	93	1248	1155	1290	80	64	21	26	39	8	2	25.00%	13	4	69.23%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
11	Crunch	2	2	0	0	0	0	0	0	10	5	5	1	1	0	0	0	0	0	0	6	3	3	1	1	0	0	0	0	0	0	4	2	2	4	1.000	10	20	30	0	0	135	109	96	17	104	1248	1155	1290	80	59	22	12	47	5	1	20.00%	6	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
12	Heat	3	2	0	0	1	0	0	0	15	7	8	1	0	0	0	1	0	0	0	3	2	1	2	2	0	0	0	0	0	0	12	5	7	6	1.000	15	28	43	0	0	135	109	96	17	139	1248	1155	1290	80	66	16	22	57	11	1	9.09%	11	3	72.73%	1	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
13	Jayhawks	3	1	0	0	1	0	1	0	11	7	4	2	1	0	0	1	0	0	0	8	5	3	1	0	0	0	0	0	1	0	3	2	1	6	1.000	11	18	29	0	0	135	109	96	17	139	1248	1155	1290	80	99	31	18	65	5	0	0.00%	8	1	87.50%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
14	Las Vegas	3	1	1	0	0	0	1	0	8	8	0	2	1	0	0	0	0	1	0	7	5	2	1	0	1	0	0	0	0	0	1	3	-2	4	0.667	8	12	20	0	0	135	109	96	17	146	1248	1155	1290	80	109	30	33	74	11	1	9.09%	13	3	76.92%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
15	Manchots	2	0	0	0	0	0	2	0	10	8	2	1	0	0	0	0	0	1	0	5	4	1	1	0	0	0	0	0	1	0	5	4	1	4	1.000	10	13	23	0	0	135	109	96	17	87	1248	1155	1290	80	105	28	26	63	7	1	14.29%	11	2	81.82%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
16	Marlies	2	0	1	0	1	0	0	0	7	7	0	1	0	1	0	0	0	0	0	3	4	-1	1	0	0	0	1	0	0	0	4	3	1	2	0.500	7	11	18	0	0	135	109	96	17	72	1248	1155	1290	80	66	25	16	46	6	1	16.67%	8	1	87.50%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
17	Minnesota	4	4	0	0	0	0	0	0	21	9	12	2	2	0	0	0	0	0	0	8	2	6	2	2	0	0	0	0	0	0	13	7	6	8	1.000	21	39	60	0	0	135	109	96	17	283	1248	1155	1290	80	113	37	45	85	9	1	11.11%	15	3	80.00%	1	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
18	Monarchs	3	3	0	0	0	0	0	0	19	5	14	2	2	0	0	0	0	0	0	13	3	10	1	1	0	0	0	0	0	0	6	2	4	6	1.000	19	35	54	0	0	135	109	96	17	189	1248	1155	1290	80	97	30	16	86	13	5	38.46%	8	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
19	Monsters	2	1	1	0	0	0	0	0	8	8	0	1	0	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	5	3	2	2	0.500	8	13	21	0	0	135	109	96	17	61	1248	1155	1290	80	73	19	24	51	4	0	0.00%	12	1	91.67%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
20	Monsters	4	1	2	0	0	0	1	0	11	13	-2	2	0	2	0	0	0	0	0	3	7	-4	2	1	0	0	0	0	1	0	8	6	2	4	0.500	11	19	30	0	0	135	109	96	17	152	1248	1155	1290	80	133	37	24	83	13	1	7.69%	11	2	81.82%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
21	Oil Kings	3	3	0	0	0	0	0	0	15	8	7	1	1	0	0	0	0	0	0	5	1	4	2	2	0	0	0	0	0	0	10	7	3	6	1.000	15	30	45	0	0	135	109	96	17	143	1248	1155	1290	80	125	34	31	86	13	3	23.08%	8	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
22	Phantoms	2	1	1	0	0	0	0	0	6	4	2	1	0	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	4	1	3	2	0.500	6	12	18	0	0	135	109	96	17	57	1248	1155	1290	80	62	24	22	54	5	1	20.00%	11	2	81.82%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
23	Rocket	2	1	1	0	0	0	0	0	9	9	0	1	0	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	6	4	2	2	0.500	9	17	26	0	0	135	109	96	17	70	1248	1155	1290	80	64	15	8	55	4	2	50.00%	4	0	100.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
24	Senators	2	1	1	0	0	0	0	0	7	8	-1	1	0	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	4	3	1	2	0.500	7	13	20	0	0	135	109	96	17	84	1248	1155	1290	80	70	20	24	49	5	0	0.00%	10	2	80.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
25	Sharks	3	2	1	0	0	0	0	0	9	8	1	1	1	0	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	5	5	0	4	0.667	9	15	24	1	0	135	109	96	17	129	1248	1155	1290	80	66	16	12	62	10	2	20.00%	5	2	60.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
26	Sound Tigers	2	1	0	0	0	0	0	1	10	6	4	1	1	0	0	0	0	0	0	7	2	5	1	0	0	0	0	0	0	1	3	4	-1	3	0.750	10	18	28	0	0	135	109	96	17	91	1248	1155	1290	80	70	15	16	54	5	2	40.00%	7	2	71.43%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
27	Spiders	2	1	0	0	0	0	0	1	6	5	1	1	1	0	0	0	0	0	0	4	2	2	1	0	0	0	0	0	0	1	2	3	-1	3	0.750	6	10	16	0	0	135	109	96	17	75	1248	1155	1290	80	83	21	18	46	4	0	0.00%	9	1	88.89%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
28	Stars	5	3	1	0	0	0	0	1	26	16	10	2	0	1	0	0	0	0	1	5	8	-3	3	3	0	0	0	0	0	0	21	8	13	7	0.700	26	46	72	1	0	135	109	96	17	233	1248	1155	1290	80	136	42	45	110	12	1	8.33%	17	2	88.24%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
29	Thunder	2	2	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	4	0	4	4	1.000	8	15	23	0	1	135	109	96	17	93	1248	1155	1290	80	43	14	8	43	6	1	16.67%	4	2	50.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
	Total	82	49	20	0	4	0	6	3	350	235	115	41	25	10	0	2	0	3	1	180	119	61	41	24	10	0	2	0	3	2	170	116	54	121	0.738	350	625	975	3	1	135	109	96	17	3739	1248	1155	1290	80	2586	773	678	2003	267	50	18.73%	281	50	82.21%	3	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
30	Wolf Pack	2	1	1	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	6	2	4	1	0	1	0	0	0	0	0	1	2	-1	2	0.500	7	13	20	0	0	135	109	96	17	105	1248	1155	1290	80	37	13	18	39	9	0	0.00%	8	2	75.00%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
	_Since Last GM Reset	82	49	20	0	4	0	6	3	350	235	115	41	25	10	0	2	0	3	1	180	119	61	41	24	10	0	2	0	3	2	170	116	54	121	0.738	350	625	975	3	1	135	109	96	17	3739	1248	1155	1290	80	2586	773	678	2003	267	50	18.73%	281	50	82.21%	3	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
	_Vs Conference	35	18	10	0	2	0	3	2	142	103	39	17	10	5	0	0	0	2	0	82	56	26	18	8	5	0	2	0	1	2	60	47	13	48	0.686	142	247	389	1	1	135	109	96	17	1512	1248	1155	1290	80	1117	340	289	855	117	22	18.80%	129	27	79.07%	1	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552
	_Vs Division	16	8	4	0	2	0	0	0	66	52	14	8	5	2	0	0	0	0	0	33	30	3	8	3	2	0	2	0	0	0	33	22	11	20	0.625	66	124	190	0	1	135	109	96	17	708	1248	1155	1290	80	484	160	121	386	42	9	21.43%	56	11	80.36%	0	1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%	2225	1599	1694	571	1052	552

			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	121	W4	350	625	975	3739	2586	773	678	2003	3	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	49	20	4	0	6	3	350	235

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	25	10	2	0	3	1	180	119

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	24	10	2	0	3	2	170	116

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
8	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
267	50	18.73%	281	50	82.21%	3

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
1248	1155	1290	80	135	109	96	17

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
1990	3325	59.85%	1555	2672	58.20%	813	1397	58.20%

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
2225	1599	1694	571	1052	552

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	SO	Lien
2 - 2020-10-23	6	Oceanics	1	Wolf Pack	2	L			Sommaire du Match
3 - 2020-10-24	14	Oceanics	2	Spiders	3	L	X	X	Sommaire du Match
5 - 2020-10-26	33	Oceanics	3	Sound Tigers	4	L	X	X	Sommaire du Match
7 - 2020-10-28	38	Oceanics	5	Manchots	4	W	X	X	Sommaire du Match
9 - 2020-10-30	53	Minnesota	1	Oceanics	5	W			Sommaire du Match
11 - 2020-11-01	64	Oceanics	2	Baby Hawks	3	L			Sommaire du Match
12 - 2020-11-02	75	Manchots	4	Oceanics	5	W	X	X	Sommaire du Match
14 - 2020-11-04	87	Jayhawks	4	Oceanics	5	W	X		Sommaire du Match
16 - 2020-11-06	102	Sound Tigers	2	Oceanics	7	W			Sommaire du Match
19 - 2020-11-09	127	Oil Kings	1	Oceanics	5	W			Sommaire du Match
21 - 2020-11-11	140	Monarchs	1	Oceanics	8	W			Sommaire du Match
25 - 2020-11-15	169	Heat	2	Oceanics	3	W	X		Sommaire du Match
28 - 2020-11-18	187	Oceanics	2	Admirals	4	L			Sommaire du Match
31 - 2020-11-21	203	Oceanics	3	Sharks	1	W			Sommaire du Match
32 - 2020-11-22	215	Oceanics	1	Las Vegas	3	L			Sommaire du Match
35 - 2020-11-25	229	Spiders	2	Oceanics	4	W			Sommaire du Match
38 - 2020-11-28	250	Comets	5	Oceanics	8	W			Sommaire du Match
40 - 2020-11-30	264	Stars	4	Oceanics	3	L	X	X	Sommaire du Match
42 - 2020-12-02	276	Monsters	4	Oceanics	2	L			Sommaire du Match
44 - 2020-12-04	288	Oceanics	6	Cabaret Lady Mary Ann	2	W			Sommaire du Match
46 - 2020-12-06	302	Oceanics	4	Thunder	0	W			Sommaire du Match
49 - 2020-12-09	325	Oceanics	4	Chill	2	W			Sommaire du Match
51 - 2020-12-11	342	Oceanics	5	Stars	1	W			Sommaire du Match
53 - 2020-12-13	352	Monsters	5	Oceanics	3	L			Sommaire du Match
57 - 2020-12-17	389	Oceanics	2	Sharks	4	L			Sommaire du Match
59 - 2020-12-19	392	Oceanics	1	Admirals	2	L			Sommaire du Match
60 - 2020-12-20	414	Oceanics	6	Monarchs	2	W			Sommaire du Match
63 - 2020-12-23	431	Stars	4	Oceanics	2	L			Sommaire du Match
65 - 2020-12-25	445	Oceanics	9	Stars	4	W			Sommaire du Match
68 - 2020-12-28	463	Admirals	3	Oceanics	8	W			Sommaire du Match
70 - 2020-12-30	477	Cougars	2	Oceanics	3	W			Sommaire du Match
72 - 2021-01-01	491	Oceanics	3	Cougars	7	L			Sommaire du Match
75 - 2021-01-04	515	Phantoms	3	Oceanics	2	L			Sommaire du Match
77 - 2021-01-06	530	Caroline	2	Oceanics	4	W			Sommaire du Match
79 - 2021-01-08	543	Baby Hawks	2	Oceanics	4	W			Sommaire du Match
81 - 2021-01-10	554	Oceanics	5	Minnesota	3	W			Sommaire du Match
83 - 2021-01-12	577	Rocket	5	Oceanics	3	L			Sommaire du Match
87 - 2021-01-16	588	Chiefs	3	Oceanics	5	W			Sommaire du Match
89 - 2021-01-18	602	Oceanics	2	Chiefs	4	L			Sommaire du Match
91 - 2021-01-20	621	Oceanics	3	Monsters	2	W			Sommaire du Match
93 - 2021-01-22	633	Marlies	4	Oceanics	3	L			Sommaire du Match
95 - 2021-01-24	643	Oceanics	8	Minnesota	4	W			Sommaire du Match
97 - 2021-01-26	660	Oceanics	6	Rocket	4	W			Sommaire du Match
99 - 2021-01-28	675	Oceanics	4	Marlies	3	W	X		Sommaire du Match
100 - 2021-01-29	678	Oceanics	2	Bruins	1	W	X		Sommaire du Match
103 - 2021-02-01	703	Chill	2	Oceanics	5	W			Sommaire du Match
105 - 2021-02-03	721	Comets	2	Oceanics	7	W			Sommaire du Match
108 - 2021-02-06	742	Thunder	3	Oceanics	4	W			Sommaire du Match
110 - 2021-02-08	757	Oceanics	6	Baby Hawks	1	W			Sommaire du Match
112 - 2021-02-10	764	Oceanics	6	Caroline	1	W			Sommaire du Match
113 - 2021-02-11	766	Oceanics	5	Monsters	3	W			Sommaire du Match
122 - 2021-02-20	789	Bruins	7	Oceanics	3	L			Sommaire du Match
123 - 2021-02-21	795	Chiefs	3	Oceanics	1	L			Sommaire du Match
126 - 2021-02-24	822	Chill	3	Oceanics	6	W			Sommaire du Match
128 - 2021-02-26	834	Oceanics	4	Chiefs	6	L			Sommaire du Match
130 - 2021-02-28	843	Senators	5	Oceanics	3	L			Sommaire du Match
131 - 2021-03-01	858	Baby Hawks	3	Oceanics	5	W			Sommaire du Match
133 - 2021-03-03	872	Wolf Pack	2	Oceanics	6	W			Sommaire du Match
136 - 2021-03-06	891	Sharks	3	Oceanics	4	W			Sommaire du Match
138 - 2021-03-08	914	Baby Hawks	2	Oceanics	5	W			Sommaire du Match
140 - 2021-03-10	926	Monarchs	2	Oceanics	5	W			Sommaire du Match
142 - 2021-03-12	937	Oceanics	4	Senators	3	W			Sommaire du Match
144 - 2021-03-14	949	Oceanics	4	Phantoms	1	W			Sommaire du Match
145 - 2021-03-15	961	Oceanics	4	Crunch	2	W			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17	973	Oceanics	4	Bears	2	W			Sommaire du Match
149 - 2021-03-19	992	Bears	5	Oceanics	6	W	X	X	Sommaire du Match
151 - 2021-03-21	1009	Oceanics	5	Oil Kings	3	W			Sommaire du Match
154 - 2021-03-24	1024	Crunch	3	Oceanics	6	W			Sommaire du Match
157 - 2021-03-27	1045	Las Vegas	2	Oceanics	3	W			Sommaire du Match
160 - 2021-03-30	1067	Jayhawks	1	Oceanics	3	W			Sommaire du Match
162 - 2021-04-01	1080	Oceanics	5	Oil Kings	4	W			Sommaire du Match
165 - 2021-04-04	1108	Oceanics	6	Heat	1	W			Sommaire du Match
166 - 2021-04-05	1117	Oceanics	3	Comets	1	W			Sommaire du Match
168 - 2021-04-07	1128	Cabaret Lady Mary Ann	1	Oceanics	8	W			Sommaire du Match
171 - 2021-04-10	1148	Minnesota	1	Oceanics	3	W			Sommaire du Match
173 - 2021-04-12	1168	Oceanics	7	Stars	3	W			Sommaire du Match
175 - 2021-04-14	1183	Oceanics	4	Chill	6	L			Sommaire du Match
178 - 2021-04-17	1201	Monsters	3	Oceanics	1	L			Sommaire du Match
180 - 2021-04-19	1218	Las Vegas	3	Oceanics	4	W	X	X	Sommaire du Match
182 - 2021-04-21	1236	Oceanics	6	Heat	4	W			Sommaire du Match
184 - 2021-04-23	1251	Oceanics	5	Monsters	4	W	X	X	Sommaire du Match
186 - 2021-04-25	1259	Oceanics	3	Jayhawks	2	W	X	X	Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	40	20
Assistance	61,677	26,975
Assistance PCT	75.22%	65.79%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
0	2162 - 72.07%	73,331$	3,006,580$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
3,209,345$	2,948,800$	2,836,300$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
15,249$	3,058,258$	29	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	15,854$	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