Ligue Canadienne de Hockey Simulé

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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	Mikko Koivu	X				100.00	67	48	75	74	77	87	98	99	99	95	96	89	90	99	99	18	38	85	0
2	Justin Williams			X		100.00	71	49	72	80	73	89	97	81	71	99	99	98	99	93	99	59	33	85	0
3	Thomas Vanek		X			100.00	62	44	76	72	78	80	96	81	78	99	99	99	99	86	99	42	36	83	0
4	Josh Bailey			X		100.00	57	41	85	84	75	88	94	95	57	95	88	94	67	80	66	68	36	82	0
5	Frans Nielsen	X				100.00	60	39	88	76	72	82	95	84	96	87	89	93	84	99	99	29	36	81	0
6	Alex Killorn		X			100.00	70	47	76	76	74	82	98	93	69	82	85	81	79	78	79	50	26	78	0
7	Adam Lowry	X				100.00	85	38	91	69	80	82	80	97	89	72	75	91	67	77	73	45	19	76	0
8	Gabriel Dumont		X			100.00	71	43	77	66	72	83	92	95	87	91	73	68	61	84	65	35	36	75	0
9	J.T. Miller		X			100.00	77	48	76	75	77	86	98	75	84	77	76	83	73	79	78	79	32	75	0
10	Charlie Coyle			X		100.00	68	39	88	72	79	86	87	95	84	66	70	83	73	86	78	73	24	74	0
11	Cedric Paquette	X				100.00	76	44	77	72	75	75	93	83	86	66	71	83	70	77	73	58	36	73	0
12	Carter Rowney (R)			X		100.00	89	35	75	68	82	80	75	67	78	67	65	75	55	72	52	35	36	68	0
13	Victor Hedman				X	100.00	64	35	90	80	84	98	93	90	25	87	86	99	82	87	89	45	36	83	0
14	Alex Pietrangelo				X	100.00	56	31	99	78	80	99	99	83	25	85	78	95	87	87	91	59	55	81	0
15	Ryan McDonagh				X	100.00	65	39	92	69	77	97	95	78	30	83	77	99	77	81	82	66	36	79	0
16	Ryan Murphy				X	100.00	61	33	82	68	71	84	82	99	63	97	92	83	73	77	73	65	36	77	0
17	Brian Dumoulin				X	100.00	66	38	93	67	78	85	97	82	30	76	73	84	66	74	72	57	36	74	0
18	Patrik Nemeth (R)				X	100.00	64	40	89	65	78	84	83	79	30	75	76	96	56	68	59	70	36	74	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	68	41	83	73	77	86	92	86	66	83	82	89	75	82	79	53	35	78

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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	Andrei Vasilevski	100.00	97	90	97	89	96	99	99	99	99	95	96	66	82	80	35	92	0
2	Antti Niemi	100.00	76	77	85	81	79	92	97	97	97	85	91	99	97	19	36	86	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	87	84	91	85	88	96	98	98	98	90	94	83	90	50	36	89

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Mike Sullivan	51	56	62	53	82	71	56	USA	50	3	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	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Mikko Koivu	Penguins	C	82	33	65	98	22	58	10	178	230	301	79	181	10.96%	40	1806	22.03	8	22	30	55	305	1	0	1	4	301	6	5	53.30%	2109	44	34	0	0	1.08	6	10	0	0	2	4	8	10
2	Justin Williams	Penguins	RW	82	34	38	72	22	113	5	236	169	263	100	167	12.93%	46	1760	21.46	9	8	17	43	306	0	0	0	2	269	2	1	41.83%	557	47	34	1	0	0.82	3	10	0	1	0	8	6	2
3	Thomas Vanek	Penguins	LW	82	35	33	68	27	78	0	179	122	207	47	108	16.91%	31	1583	19.32	9	8	17	31	305	1	2	3	11	118	5	3	40.78%	179	24	17	0	1	0.86	1	7	0	0	0	5	3	7
4	Josh Bailey	Penguins	RW	82	25	37	62	-4	54	0	170	156	296	82	189	8.45%	44	1547	18.87	3	2	5	35	242	2	1	3	8	125	3	2	46.99%	83	67	20	0	1	0.80	0	2	0	0	0	7	4	3
5	Frans Nielsen	Penguins	C	82	20	29	49	-7	28	0	133	208	171	54	107	11.70%	30	1402	17.10	2	3	5	15	240	0	0	0	0	0	2	1	51.78%	1576	23	27	0	0	0.70	0	0	0	0	0	2	2	4
6	Alex Killorn	Penguins	LW	81	19	22	41	-5	142	10	215	121	238	80	118	7.98%	22	1406	17.36	2	4	6	24	237	0	0	0	0	6	2	2	41.46%	82	32	14	0	0	0.58	0	0	1	0	0	2	5	2
7	Victor Hedman	Penguins	D	82	8	23	31	5	20	0	101	167	135	53	77	5.93%	112	2033	24.80	5	8	13	32	333	0	0	0	5	335	0	1	0.00%	0	66	52	0	0	0.30	0	1	0	0	0	0	2	1
8	Adam Lowry	Penguins	C	77	16	13	29	-4	25	5	119	123	152	45	76	10.53%	31	957	12.43	0	0	0	0	16	0	0	0	2	55	6	0	48.45%	644	14	17	0	0	0.61	0	0	0	1	0	2	3	0
9	Gabriel Dumont	Penguins	LW	82	12	15	27	-2	60	0	85	59	136	42	101	8.82%	12	795	9.70	0	2	2	0	8	0	0	0	6	124	2	1	57.14%	77	20	9	0	0	0.68	0	1	0	0	0	1	0	0
10	J.T. Miller	Penguins	LW	82	8	15	23	-15	53	5	132	72	139	52	79	5.76%	16	969	11.82	0	0	0	1	5	0	0	0	4	83	0	1	56.16%	73	24	13	0	0	0.47	0	1	0	0	0	1	0	1
11	Charlie Coyle	Penguins	RW	81	9	13	22	-6	10	0	88	65	166	43	92	5.42%	25	900	11.12	0	0	0	0	6	0	0	0	0	5	2	2	48.72%	39	20	11	0	0	0.49	0	0	0	0	0	1	1	2
12	Ryan Murphy	Penguins	D	82	2	19	21	5	48	0	101	165	139	45	56	1.44%	105	1770	21.59	1	2	3	13	220	0	1	1	5	197	1	0	0.00%	0	35	43	0	0	0.24	0	0	0	0	0	0	0	1
13	Patrik Nemeth	Penguins	D	82	3	17	20	-2	10	0	48	76	67	32	27	4.48%	73	1123	13.70	1	0	1	1	4	0	0	0	0	5	0	1	0.00%	0	19	29	0	0	0.36	0	0	0	0	0	0	0	0
14	Alex Pietrangelo	Penguins	D	82	1	17	18	-4	6	0	89	165	92	38	36	1.09%	111	1908	23.28	0	3	3	13	211	0	0	0	4	331	0	0	0.00%	0	35	56	0	0	0.19	0	1	0	0	0	0	0	1
15	Ryan McDonagh	Penguins	D	82	2	13	15	2	10	0	103	140	82	33	26	2.44%	88	1800	21.96	1	1	2	4	221	0	2	2	2	217	0	1	0.00%	0	15	34	0	0	0.17	0	0	0	0	0	0	0	0
16	Brian Dumoulin	Penguins	D	82	4	9	13	-2	6	0	58	110	66	22	23	6.06%	83	1152	14.06	0	0	0	0	4	0	1	1	1	35	1	0	0.00%	0	16	29	0	0	0.23	0	0	0	0	0	0	1	0
17	Cedric Paquette	Penguins	C	82	1	7	8	-7	8	0	43	52	70	22	52	1.43%	14	551	6.73	0	0	0	0	0	0	0	0	0	16	0	0	50.83%	240	7	10	0	0	0.29	0	0	0	0	0	0	0	0
18	Carter Rowney	Penguins	RW	82	2	1	3	-4	10	0	65	35	24	8	15	8.33%	5	500	6.10	0	0	0	0	0	0	0	0	0	0	0	0	57.14%	7	1	4	0	0	0.12	0	0	0	0	0	0	0	0
19	Conor Sheary	Penguins (PIT)	LW	1	0	1	1	-1	0	0	4	5	1	0	0	0.00%	1	14	14.27	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	1	2	1	0	0	1.40	0	0	0	0	0	0	0	0
20	Maxim Lapierre	Penguins (PIT)	C	5	0	1	1	2	2	0	5	2	2	0	0	0.00%	1	39	7.82	0	0	0	0	0	0	0	0	0	2	0	0	58.82%	17	0	1	0	0	0.51	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1475	234	388	622	22	741	35	2152	2242	2747	877	1530	8.52%	890	24024	16.29	41	63	104	267	2671	4	7	11	54	2231	32	21	50.51%	5684	511	455	1	2	0.52	10	33	1	2	2	33	35	34

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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	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Andrei Vasilevski	Penguins	45	19	15	8	0.911	2.97	2609	0	129	1447	572	1	1	0.647	17	42	40	5	3	3
2	Antti Niemi	Penguins	41	17	19	4	0.912	3.03	2360	2	119	1348	577	5	1	0.615	13	40	42	3	2	4
Stats d'équipe Total ou en Moyenne			86	36	34	12	0.911	3.00	4969	2	248	2795	1149	6	2	0.633	30	82	82	8	5	7

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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
Adam Lowry	Penguins	C	27	1993-03-29 11:11:13	No	210 Lbs	6 ft5	No	No	No	2	Pro & Farm	2,500,000$