Ligue de hockey Simulée Ste-Flanelle

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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	Patric Hornqvist			X		100.00	69	35	85	80	60	74	91	73	35	72	73	66	56	64	60	0	50	69	0
2	Brian Gionta			X		100.00	50	35	88	86	52	74	95	67	59	65	68	70	42	82	74	0	50	68	0
3	Matt Cullen	X	X			99.00	50	35	85	74	69	70	91	65	86	65	65	70	42	92	87	0	50	68	0
4	Sean Couturier	X				100.00	56	43	83	71	74	76	78	67	86	66	67	75	45	53	44	0	50	66	0
5	Michael Grabner		X	X		100.00	55	35	90	76	58	69	90	63	37	54	71	76	53	58	49	0	50	65	0
6	Patrik Berglund	X	X			100.00	64	35	85	71	79	72	88	62	83	53	70	67	64	65	54	0	50	65	0
7	David Legwand	X				100.00	49	35	87	70	72	61	86	56	82	57	55	73	54	80	70	0	50	63	0
8	Jordan Martinook	X	X			100.00	55	35	84	72	69	68	88	58	77	54	61	77	48	37	34	0	50	62	0
9	Torrey Mitchell	X		X		100.00	54	50	82	72	61	65	90	55	87	50	60	74	48	65	56	0	50	62	0
10	Josh Jooris	X	X	X		100.00	58	43	85	69	68	63	70	53	83	52	54	73	56	38	35	0	50	59	0
11	Gemel Smith (R)	X	X			100.00	50	43	68	72	60	55	36	57	44	52	62	71	48	35	32	0	50	57	0
12	Michael Blunden			X		100.00	56	35	58	65	76	58	35	50	35	44	56	59	48	55	51	0	50	54	0
13	Duncan Keith (C)				X	100.00	59	43	88	76	62	87	91	69	35	78	59	88	48	77	72	0	50	74	0
14	Niklas Hjalmarsson (A)				X	100.00	60	43	87	66	65	80	92	53	35	56	49	90	48	71	69	0	50	69	0
15	Braydon Coburn				X	100.00	74	61	80	63	76	72	94	47	35	45	49	78	48	75	66	0	50	67	0
16	Josh Gorges				X	100.00	75	56	76	63	67	73	82	45	35	46	43	85	48	71	61	0	50	66	0
17	Mark Streit				X	100.00	53	35	85	76	61	76	82	58	35	63	53	66	48	66	58	0	50	64	0
18	Joel Edmundson				X	100.00	77	56	75	63	74	67	64	45	35	46	43	81	48	40	37	0	50	62	0
Rayé
1	Matt Duchene	X		X		80.50	56	43	89	78	66	78	93	73	93	72	74	64	58	57	47	0	50	69	0
2	Sean Monahan (A)	X				100.00	56	35	88	78	68	76	95	76	84	76	75	64	44	50	40	0	50	69	0

	MOYENNE D'ÉQUIPE					98.95	59	42	82	72	67	71	82	60	59	58	60	73	50	62	55	0	50	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	Joonas Korpisalo	100.00	69	45	90	70	70	67	67	70	66	65	87	37	34	0	50	63	0
2	Linus Soderstrom (R)	100.00	39	40	39	69	39	38	38	38	38	38	37	32	30	0	50	42	0
Rayé
1	Corey Crawford	100.00	89	89	97	82	90	83	85	90	81	75	91	63	61	0	50	81	0

	MOYENNE D'ÉQUIPE	100.00	66	58	75	74	66	63	63	66	62	59	72	44	42	0	50	62

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Mike Babcock	91	88	87	95	99	99	93	CAN	54	1	500,000$

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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	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Sean Monahan	Pittsburgh	C	82	34	50	84	27	16	0	62	160	252	7	45	13.49%	2	1580	19.28	10	23	33	79	378	0	0	0	0	0	7	1	51.50%	1998	0	0	1.06	1	1	0	0	0	9	5	10
2	Duncan Keith	Pittsburgh	D	82	16	62	78	23	71	15	75	146	156	9	26	10.26%	94	2096	25.57	9	20	29	112	388	1	0	1	1	332	3	0	0.00%	0	0	1	0.74	0	0	0	2	1	4	3	5
3	Patric Hornqvist	Pittsburgh	RW	82	28	49	77	21	82	0	193	92	272	20	36	10.29%	5	1547	18.87	11	19	30	83	376	0	0	0	0	0	9	2	33.02%	106	0	0	1.00	1	3	0	0	0	6	6	9
4	Matt Duchene	Pittsburgh	C/RW	73	24	41	65	20	43	15	67	99	232	4	14	10.34%	7	1271	17.41	3	16	19	67	316	0	0	0	4	63	3	2	58.31%	662	0	0	1.02	1	2	2	0	1	4	4	4
5	Michael Grabner	Pittsburgh	LW/RW	81	29	27	56	-6	36	0	70	102	205	14	30	14.15%	21	1506	18.60	12	13	25	75	347	0	0	0	4	271	3	4	34.35%	131	0	0	0.74	0	0	0	0	0	2	8	3
6	Matt Cullen	Pittsburgh	C/LW	82	22	29	51	23	20	0	48	81	158	8	27	13.92%	15	1620	19.76	8	10	18	48	352	0	0	0	0	75	5	2	57.75%	142	0	1	0.63	0	0	0	0	0	2	5	1
7	Brian Gionta	Pittsburgh	RW	82	17	26	43	4	34	0	44	111	196	24	37	8.67%	2	1108	13.51	7	9	16	67	315	0	0	0	1	3	2	1	48.86%	88	0	0	0.78	0	0	0	0	0	4	3	2
8	Sean Couturier	Pittsburgh	C	73	18	25	43	22	34	0	55	176	142	11	25	12.68%	21	1189	16.30	0	0	0	9	40	0	1	1	7	323	2	1	51.23%	1632	1	0	0.72	0	1	0	0	0	2	4	2
9	Niklas Hjalmarsson	Pittsburgh	D	72	4	26	30	7	76	10	83	70	78	7	11	5.13%	88	1640	22.78	1	6	7	49	287	0	1	1	1	281	1	1	0.00%	0	0	0	0.37	0	0	1	1	0	1	2	1
10	Mark Streit	Pittsburgh	D	68	6	22	28	11	8	0	18	34	51	7	7	11.76%	43	1222	17.98	4	5	9	37	325	0	0	0	0	40	1	0	0.00%	0	0	0	0.46	0	0	0	0	0	0	0	1
11	Braydon Coburn	Pittsburgh	D	82	6	21	27	19	150	50	106	45	74	4	12	8.11%	59	1620	19.77	2	8	10	40	326	0	0	0	0	169	1	1	0.00%	0	0	0	0.33	1	1	1	7	2	0	1	2
12	Patrik Berglund	Pittsburgh	C/LW	79	10	16	26	8	54	0	102	57	125	8	20	8.00%	6	1075	13.62	2	3	5	25	166	0	0	0	0	1	2	0	54.14%	266	0	0	0.48	1	3	0	0	0	0	2	4
13	Josh Gorges	Pittsburgh	D	82	5	20	25	19	133	15	149	71	45	4	8	11.11%	110	1507	18.39	1	0	1	3	11	0	0	0	1	281	1	0	0.00%	0	0	0	0.33	0	0	2	1	0	0	2	1
14	Joel Edmundson	Pittsburgh	D	82	5	17	22	12	107	15	159	46	32	1	5	15.63%	88	1387	16.92	1	0	1	6	74	0	0	0	1	252	0	0	0.00%	0	0	0	0.32	0	0	1	2	0	0	0	2
15	Jordan Martinook	Pittsburgh	C/LW	82	11	10	21	8	34	0	53	73	96	9	22	11.46%	8	1065	12.99	0	0	0	0	1	0	0	0	3	304	2	0	52.52%	278	0	0	0.39	0	0	0	0	0	2	2	2
16	Torrey Mitchell	Pittsburgh	C/RW	82	9	5	14	8	37	5	79	105	53	1	6	16.98%	9	931	11.36	0	0	0	0	0	0	0	0	3	213	2	1	54.90%	989	0	0	0.30	0	0	1	0	0	2	0	0
17	Gemel Smith	Pittsburgh	C/LW	82	5	6	11	-4	24	0	40	42	70	7	11	7.14%	2	590	7.20	0	0	0	4	23	0	0	0	1	9	1	0	43.75%	48	0	0	0.37	0	0	0	0	0	0	1	0
18	Josh Jooris	Pittsburgh	C/LW/RW	73	5	4	9	-3	16	0	31	58	47	3	3	10.64%	6	621	8.51	0	0	0	1	8	0	0	0	3	88	2	0	51.34%	335	0	0	0.29	0	1	0	0	0	0	2	0
19	David Legwand	Pittsburgh	C	32	1	7	8	-13	8	0	10	29	28	2	6	3.57%	1	364	11.40	0	2	2	1	46	0	0	0	1	47	0	0	55.91%	406	0	0	0.44	1	2	0	0	0	0	1	0
20	Michael Blunden	Pittsburgh	RW	7	0	1	1	-4	4	0	5	1	3	0	0	0.00%	0	43	6.24	0	0	0	0	2	0	0	0	0	0	0	0	50.00%	4	0	0	0.46	0	0	0	0	0	0	0	0
21	Matt Greene	Manchots (Pit)	D	5	0	0	0	-1	2	0	2	2	0	0	0	0.00%	2	64	12.99	0	0	0	0	4	0	0	0	0	1	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0	0
22	Ryan Stanton	Manchots (Pit)	D	8	0	0	0	4	8	0	10	2	3	0	0	0.00%	2	136	17.12	0	0	0	1	31	0	0	0	0	0	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0	0
23	Craig Cunningham	Manchots (Pit)	LW/RW	7	0	0	0	3	0	0	1	0	2	0	0	0.00%	0	54	7.80	0	0	0	0	0	0	0	0	0	0	0	0	33.33%	3	0	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1480	255	464	719	208	997	125	1462	1602	2320	150	351	10.99%	591	24249	16.38	71	134	205	707	3827	1	2	3	31	2762	47	16	52.37%	7088	1	2	0.59	6	14	8	13	4	38	51	49

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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	PS %	PSA	ST	BG	S1	S2	S3
1	Corey Crawford	Pittsburgh	70	42	20	5	0.906	2.25	3847	2	10	144	1525	2	0.800	5	65	15	10	3	1
2	Joonas Korpisalo	Pittsburgh	22	7	5	3	0.899	2.50	1056	2	2	44	436	0	0.500	8	17	59	2	0	0
3	Linus Soderstrom	Pittsburgh	1	0	0	0	0.813	3.83	47	0	0	3	16	0	0.000	0	0	8	0	0	0
Stats d'équipe Total ou en Moyenne			93	49	25	8	0.903	2.32	4951	4	12	191	1977	2	0.615	13	82	82	12	3	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	Status	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
Braydon Coburn	Pittsburgh	D	31	1985-02-27	No	223 Lbs	6 ft5	No	No	No	2	Sans Restriction	Pro & Farm	3,200,000$