Ligue Canadienne de Hockey Simulé

Bruins
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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	Jeff Carter	X				100.00	61	39	90	73	79	89	99	97	99	99	99	99	99	99	99	60	51	87	0
2	Ilya Kovalchuk		X			100.00	60	35	80	72	88	85	99	99	92	99	99	99	99	86	99	64	47	87	0
3	Blake Wheeler			X		100.00	65	41	87	83	84	91	97	94	77	96	99	81	69	86	71	49	54	84	0
4	Evgeny Kuznetsov	X				100.00	68	49	73	84	76	89	97	88	81	92	99	76	63	83	85	74	52	82	0
5	T.J. Oshie			X		100.00	80	35	93	76	73	84	89	90	80	89	89	82	86	94	99	64	52	81	0
6	Reid Boucher (R)		X			100.00	44	27	99	73	74	78	79	99	63	90	90	77	70	72	80	58	41	78	0
7	Peter Holland	X				100.00	87	78	69	65	75	75	81	89	87	86	85	81	73	82	82	59	45	77	0
8	Chris Tierney	X				100.00	56	38	91	75	73	82	97	78	85	93	73	79	61	74	78	65	52	76	0
9	Colin Wilson		X			100.00	33	25	99	57	79	85	86	94	83	74	91	81	83	85	80	53	51	76	0
10	Jason Zucker			X		100.00	70	47	75	82	70	88	98	83	55	73	90	69	63	82	62	62	48	75	0
11	Wojtek Wolski		X			100.00	24	17	99	61	79	94	97	65	42	70	61	86	68	99	99	64	51	70	0
12	Jamie McGinn			X		100.00	73	39	81	67	77	78	89	68	70	69	67	70	71	75	75	59	51	68	0
13	Dustin Byfuglien				X	100.00	77	41	71	78	88	99	97	92	25	88	80	96	79	96	84	26	52	84	0
14	Trevor Daley				X	100.00	57	29	89	65	74	97	94	95	58	82	76	96	78	97	83	14	51	79	0
15	Marc Methot				X	100.00	82	44	81	63	85	83	90	84	45	61	60	99	61	92	94	25	52	78	0
16	Karl Alzner				X	100.00	76	41	88	69	80	86	97	67	25	70	60	97	50	87	88	51	51	77	0
17	Eric Gelinas				X	100.00	78	34	84	68	79	77	78	99	54	99	93	67	72	74	70	50	51	76	0
18	Matt Bartkowski				X	100.00	83	40	85	68	75	77	78	77	25	58	67	87	70	88	82	12	25	74	0
Rayé

	MOYENNE D'ÉQUIPE					100.00	65	39	85	71	78	85	91	87	64	83	82	85	73	86	84	51	49	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	Semyon Varlamov	100.00	88	88	92	81	87	91	99	98	95	88	91	99	99	61	50	89	0
2	Michal Neuvirth	100.00	83	81	86	79	81	99	99	99	99	89	91	82	83	70	51	87	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	86	85	89	80	84	95	99	99	97	89	91	91	91	66	51	88

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Bill Peters	76	82	80	88	77	66	72	CAN	58	3	2,000,000$

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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	Blake Wheeler	Bruins	RW	82	39	40	79	-5	19	5	170	124	334	92	185	11.68%	26	1626	19.84	12	19	31	63	319	0	0	0	5	132	3	1	43.40%	159	67	28	0	0	0.97	0	11	1	0	0	7	4	6
2	Jeff Carter	Bruins	C	82	29	41	70	-4	20	0	148	228	237	80	146	12.24%	39	1844	22.49	11	14	25	53	319	0	0	0	6	296	6	2	53.24%	2096	45	39	0	0	0.76	2	13	0	0	0	4	6	4
3	Ilya Kovalchuk	Bruins	LW	82	24	41	65	-1	91	5	176	168	251	72	144	9.56%	40	1798	21.93	7	18	25	55	318	0	0	0	7	272	3	2	49.50%	606	33	31	1	1	0.72	0	11	0	0	0	2	3	2
4	Evgeny Kuznetsov	Bruins	C	82	27	35	62	-4	139	5	210	208	273	86	134	9.89%	44	1547	18.88	3	7	10	22	239	0	0	0	6	112	2	2	47.74%	1546	43	20	0	0	0.80	1	5	0	0	1	2	4	5
5	T.J. Oshie	Bruins	RW	82	16	38	54	-2	9	5	153	120	193	57	116	8.29%	36	1396	17.03	6	8	14	20	239	0	0	0	0	0	1	2	48.75%	80	37	18	0	0	0.77	1	2	0	0	1	1	3	1
6	Reid Boucher	Bruins	LW	82	24	27	51	-3	4	0	56	118	229	67	145	10.48%	28	1418	17.30	3	7	10	30	239	0	0	0	0	6	6	1	40.86%	93	23	13	0	1	0.72	0	0	0	0	0	5	1	5
7	Peter Holland	Bruins	C	82	10	30	40	-3	92	10	176	122	184	51	103	5.43%	27	956	11.67	0	0	0	1	10	0	0	0	0	3	0	4	51.76%	680	13	12	0	0	0.84	0	0	0	2	0	2	2	1
8	Jason Zucker	Bruins	RW	82	20	17	37	-6	62	10	97	61	213	64	116	9.39%	23	920	11.22	0	1	1	1	4	0	0	0	0	0	2	0	33.33%	39	35	7	0	1	0.80	0	0	0	0	1	2	1	4
9	Dustin Byfuglien	Bruins	D	82	8	28	36	-15	103	5	223	146	131	47	62	6.11%	102	1975	24.09	4	5	9	31	343	0	0	0	4	273	1	1	0.00%	0	46	59	0	0	0.36	1	1	0	0	1	2	0	0
10	Eric Gelinas	Bruins	D	82	5	24	29	-10	34	0	132	90	98	35	40	5.10%	67	1267	15.46	0	0	0	2	55	0	0	0	0	24	1	0	0.00%	0	25	37	0	0	0.46	0	0	0	0	0	0	3	2
11	Marc Methot	Bruins	D	82	5	19	24	0	47	5	178	124	77	37	45	6.49%	101	1831	22.33	1	5	6	9	243	0	1	1	4	212	1	0	0.00%	0	9	42	0	0	0.26	0	0	0	0	1	0	2	1
12	Chris Tierney	Bruins	C	82	8	13	21	-2	7	5	39	70	112	38	76	7.14%	13	659	8.04	0	0	0	0	5	0	0	0	0	90	4	1	49.01%	202	15	13	0	0	0.64	0	0	0	0	1	0	0	0
13	Colin Wilson	Bruins	LW	82	12	9	21	-1	0	0	16	103	111	39	54	10.81%	24	998	12.18	0	0	0	1	3	1	1	2	4	61	2	3	44.29%	70	12	20	0	0	0.42	1	2	0	0	0	0	2	1
14	Trevor Daley	Bruins	D	82	3	17	20	-8	18	0	86	160	91	30	55	3.30%	117	1980	24.15	2	2	4	20	322	0	0	0	8	301	0	0	0.00%	0	22	41	0	0	0.20	0	0	0	0	0	0	0	1
15	Karl Alzner	Bruins	D	82	4	12	16	11	16	0	131	131	79	30	35	5.06%	103	1703	20.77	2	1	3	10	170	0	1	1	1	198	0	0	0.00%	0	5	41	0	0	0.19	0	1	0	0	0	0	1	0
16	Wojtek Wolski	Bruins	LW	82	4	5	9	-6	0	0	7	58	24	11	16	16.67%	23	648	7.90	0	0	0	0	2	1	0	1	2	88	2	0	16.67%	18	1	11	0	0	0.28	0	0	0	0	0	0	0	0
17	Matt Bartkowski	Bruins	D	66	1	8	9	-11	47	5	89	83	43	21	12	2.33%	54	931	14.11	0	0	0	0	1	0	0	0	0	55	0	0	0.00%	0	3	35	0	0	0.19	0	0	0	0	0	0	0	0
18	Jamie McGinn	Bruins	RW	82	2	5	7	-8	18	0	60	30	50	10	33	4.00%	11	501	6.12	0	0	0	0	0	0	0	0	0	0	0	1	20.00%	5	7	6	0	0	0.28	0	0	0	0	0	0	0	0
19	Ben Hutton	Bruins (BOS)	D	16	0	2	2	3	10	0	16	13	14	5	6	0.00%	17	245	15.34	0	0	0	0	0	0	0	0	0	9	0	0	100.00%	1	2	6	0	0	0.16	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1476	241	411	652	-75	736	60	2163	2157	2744	872	1523	8.78%	895	24250	16.43	51	87	138	318	2841	2	3	5	47	2140	34	20	50.04%	5595	443	479	1	3	0.54	6	46	1	2	6	27	32	33

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Semyon Varlamov	Bruins	69	30	20	12	0.914	2.78	3867	0	1	179	2078	870	3	2	0.767	43	65	17	8	5	2
2	Michal Neuvirth	Bruins	23	8	12	0	0.894	3.47	1125	2	0	65	614	253	1	0	0.000	0	17	65	1	0	1
Stats d'équipe Total ou en Moyenne			92	38	32	12	0.909	2.93	4993	2	1	244	2692	1123	4	2	0.767	43	82	82	9	5	3

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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
Blake Wheeler	Bruins	RW	33	1986-08-31 17:11:13	No	225 Lbs	6 ft5	No	No	No	3	Pro & Farm	5,000,000$