Ligue Canadienne de Hockey Simulé

Red Wings
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Stats d'équipe en Carrière

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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
1	Zach Parise		X			100.00	63	43	86	74	73	86	99	99	99	99	99	99	99	99	99	40	36	87	0
2	Patrice Bergeron	X				100.00	53	43	99	78	76	96	96	94	99	94	96	99	61	99	99	30	36	85	0
3	Jaromir Jagr			X		100.00	5	1	99	63	81	96	99	99	69	99	99	99	99	99	99	25	36	85	0
4	Ryan Nugent-Hopkins	X				100.00	63	41	85	81	74	84	92	84	95	97	87	88	87	83	78	85	36	81	0
5	Mikko Rantanen (R)			X		100.00	64	35	75	86	89	94	96	99	75	95	85	70	82	76	59	83	36	81	0
6	Artemi Panarin		X			100.00	57	42	88	89	65	94	98	87	48	99	95	73	73	77	77	34	36	81	0
7	Drew Stafford			X		100.00	46	30	97	68	78	84	87	99	74	90	85	85	75	95	83	26	36	80	0
8	Elias Lindholm	X				100.00	67	35	82	76	93	94	88	84	85	92	87	79	81	76	69	85	36	79	0
9	Kyle Okposo			X		100.00	74	62	71	75	76	81	88	80	59	79	90	86	92	88	99	70	34	78	0
10	Curtis Lazar (R)		X			100.00	85	56	92	70	74	78	78	99	68	86	86	72	69	78	74	52	32	77	0
11	Nino Niederreiter		X			100.00	69	35	75	75	84	85	95	80	74	77	80	79	76	87	79	72	36	76	0
12	Eric Fehr	X				100.00	62	35	71	65	88	77	85	74	84	90	73	83	77	98	89	25	36	75	0
13	P.K. Subban				X	100.00	82	50	73	82	76	99	99	94	25	96	90	83	90	92	96	40	36	84	0
14	Kristopher Letang				X	100.00	84	47	84	82	75	93	99	97	25	99	81	88	90	90	94	30	38	83	0
15	Brent Seabrook				X	100.00	79	42	87	75	82	89	91	97	25	77	81	98	82	99	99	22	18	83	0
16	Marco Scandella				X	100.00	66	40	91	67	80	94	98	83	25	77	74	97	67	87	79	56	37	79	0
17	Simon Després (R)				X	100.00	81	34	99	74	78	86	74	99	25	91	86	78	71	82	77	59	17	78	0
18	Sami Vatanen				X	100.00	71	43	85	81	71	84	86	83	25	84	78	91	90	80	73	44	36	78	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	65	40	86	76	79	89	92	91	60	90	86	86	81	88	85	49	34	81

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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	Ben Bishop	99.00	97	86	87	98	96	99	99	99	99	96	98	78	88	38	36	92	0
2	Eddie Lack	100.00	75	83	78	78	75	99	99	99	99	82	90	98	99	63	32	86	0
Rayé

	MOYENNE D'ÉQUIPE	99.50	86	85	83	88	86	99	99	99	99	89	94	88	94	51	34	89

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jeff Blashill	42	93	82	42	69	79	65	USA	45	3	1,900,000$

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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	P/20	PSG	PSS	FL	FT	S1	S2	S3
1	Zach Parise	Red Wings	LW	82	30	40	70	-4	54	0	200	198	333	115	137	9.01%	48	1831	22.34	6	13	19	73	339	3	2	5	11	289	4	4	52.20%	659	51	23	0	0.76	1	10	0	0	7	2	5
2	Patrice Bergeron	Red Wings	C	82	28	41	69	-7	0	0	134	198	282	93	176	9.93%	37	1668	20.35	7	15	22	56	339	2	0	2	11	144	3	3	49.06%	2069	52	27	1	0.83	2	9	0	0	5	5	4
3	Mikko Rantanen	Red Wings	RW	82	27	30	57	3	120	0	180	120	221	73	141	12.22%	33	1424	17.37	4	2	6	25	263	0	0	0	0	0	3	2	45.16%	93	51	9	0	0.80	0	1	0	0	5	4	1
4	Artemi Panarin	Red Wings	LW	82	23	30	53	4	16	0	132	107	245	86	153	9.39%	40	1560	19.03	2	6	8	26	262	0	2	2	6	125	4	3	32.10%	81	51	26	0	0.68	1	8	0	0	4	3	5
5	Jaromir Jagr	Red Wings	RW	82	21	30	51	-4	6	0	47	129	200	59	133	10.50%	48	1825	22.26	9	9	18	33	340	1	2	3	9	299	4	3	38.56%	153	17	38	0	0.56	3	10	0	0	1	3	4
6	Ryan Nugent-Hopkins	Red Wings	C	82	16	28	44	2	36	0	121	189	165	55	87	9.70%	33	1434	17.49	4	4	8	21	262	0	0	0	0	6	2	2	52.42%	1532	20	15	0	0.61	1	3	0	0	1	3	2
7	Elias Lindholm	Red Wings	C	82	15	24	39	14	32	0	98	102	175	45	87	8.57%	20	974	11.88	0	0	0	0	7	0	0	0	1	25	2	1	47.46%	729	23	19	0	0.80	0	1	0	0	0	3	2
8	Drew Stafford	Red Wings	RW	82	17	16	33	12	8	0	21	79	167	49	93	10.18%	36	932	11.37	0	0	0	1	11	0	0	0	0	1	2	1	56.86%	51	19	17	0	0.71	1	1	0	0	3	2	1
9	Kristopher Letang	Red Wings	D	82	7	26	33	10	66	10	213	169	137	59	57	5.11%	133	2027	24.73	3	6	9	30	367	0	2	2	4	292	0	1	0.00%	0	42	55	0	0.33	1	1	0	2	2	3	1
10	Curtis Lazar	Red Wings	LW	82	16	16	32	10	24	0	129	60	135	43	87	11.85%	28	912	11.13	0	0	0	0	0	0	0	0	1	4	2	0	54.17%	24	15	5	0	0.70	0	0	0	0	1	2	3
11	P.K. Subban	Red Wings	D	82	5	23	28	-1	130	0	226	144	129	41	50	3.88%	126	1850	22.57	1	3	4	15	307	0	0	0	4	210	2	1	0.00%	0	33	50	0	0.30	0	1	0	0	0	2	1
12	Brent Seabrook	Red Wings	D	79	2	22	24	6	30	0	173	134	94	24	44	2.13%	107	1797	22.76	1	4	5	19	287	0	0	0	2	241	0	0	0.00%	0	17	39	0	0.27	0	0	0	0	1	0	1
13	Kyle Okposo	Red Wings	RW	82	12	7	19	-1	21	5	68	58	94	24	49	12.77%	11	614	7.49	0	0	0	1	5	0	0	0	2	90	1	0	41.25%	80	11	10	0	0.62	2	2	1	0	1	2	1
14	Sami Vatanen	Red Wings	D	82	1	16	17	9	44	0	98	96	75	34	24	1.33%	75	1229	15.00	0	1	1	1	15	0	0	0	3	75	1	0	0.00%	0	16	29	0	0.28	0	1	0	0	0	0	1
15	Marco Scandella	Red Wings	D	82	0	15	15	23	29	5	107	120	55	25	28	0.00%	80	1515	18.48	0	1	1	3	140	0	0	0	0	110	0	0	0.00%	0	8	49	0	0.20	0	0	0	1	0	0	0
16	Nino Niederreiter	Red Wings	LW	82	4	10	14	2	24	0	49	57	93	34	55	4.30%	15	594	7.25	0	0	0	0	2	0	0	0	4	59	2	0	47.06%	17	15	1	0	0.47	0	0	0	0	0	1	1
17	Eric Fehr	Red Wings	C	82	6	7	13	3	24	0	37	40	41	10	30	14.63%	17	491	5.99	0	0	0	0	0	0	0	0	0	0	1	0	52.20%	182	5	8	0	0.53	0	0	0	0	0	0	3
18	Simon Després	Red Wings	D	80	2	9	11	-24	4	0	107	109	63	39	27	3.17%	69	1417	17.71	1	1	2	4	109	0	1	1	0	123	1	0	0.00%	0	28	31	0	0.16	0	0	0	0	0	0	0
19	Joe Morrow	Red Wings (DET)	D	4	1	0	1	2	2	0	6	2	1	1	1	100.00%	10	61	15.35	0	0	0	0	0	0	0	0	0	7	0	0	0.00%	0	0	2	1	0.33	0	0	0	0	0	0	0
20	Will Butcher	Red Wings (DET)	D	1	0	0	0	-1	0	0	1	1	1	0	0	0.00%	3	13	13.40	0	0	0	0	0	0	0	0	0	1	0	0	0.00%	0	0	0	0	0.00	0	0	0	0	0	0	0
21	Justin Fontaine	Red Wings (DET)	RW	1	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.10	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0.00	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1477	233	390	623	58	670	20	2147	2112	2706	909	1459	8.61%	969	24177	16.37	38	65	103	308	3064	6	9	15	58	2111	34	21	49.61%	5670	474	453	2	0.52	12	48	1	3	31	35	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	SAR	A	PS %	PSA	ST	BG	S1	S2	S3
1	Eddie Lack	Red Wings	48	25	15	7	0.921	2.62	2791	2	1	122	1542	635	2	0.667	39	46	35	7	1	5
2	Ben Bishop	Red Wings	38	12	20	3	0.912	2.95	2178	2	0	107	1213	479	0	0.778	9	36	46	3	1	3
Stats d'équipe Total ou en Moyenne			86	37	35	10	0.917	2.77	4970	4	1	229	2755	1114	2	0.688	48	82	81	10	2	8

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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	Salaire Année 4	Salaire Année 5	Salaire Année 6	Salaire Année 7	Salaire Année 8	Salaire Année 9	Salaire Année 10	Link
Artemi Panarin	Red Wings	LW	28	1991-10-30 19:53:08	No	173 Lbs	5 ft11	No	No	No	8	Pro & Farm	5,000,000$