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	Henrik Zetterberg	X	X			100.00	54	43	87	85	67	80	95	76	85	83	69	61	66	82	74	0	50	73	0
2	Bryan Little	X				100.00	55	43	87	82	63	77	75	76	87	77	75	66	58	61	51	0	50	70	0
3	Brayden Schenn	X	X	X		100.00	70	61	83	81	67	75	94	74	82	73	74	60	42	54	48	0	50	69	0
4	Tyler Johnson	X				99.00	55	35	85	83	55	78	82	75	84	76	73	68	53	49	45	0	50	69	0
5	Kyle Palmieri			X		100.00	67	50	82	81	57	75	95	71	38	69	73	68	53	53	48	0	50	68	0
6	Marian Gaborik		X	X		100.00	50	35	86	76	71	71	72	63	38	60	65	57	47	81	72	0	50	64	0
7	Adam Lowry	X	X			100.00	75	56	80	69	74	70	93	58	83	54	62	72	48	38	35	0	50	63	0
8	Marcus Kruger	X				100.00	54	43	83	71	58	67	78	53	83	54	52	77	48	59	56	0	50	61	0
9	Nick Spaling	X	X			100.00	58	43	84	67	68	62	72	52	81	52	51	77	54	59	50	0	50	60	0
10	Nick Ritchie		X			100.00	80	50	76	77	82	62	61	58	50	51	64	59	42	39	36	0	50	60	0
11	Scott Laughton	X	X			100.00	56	43	84	70	63	59	41	54	80	54	54	67	45	44	38	0	50	57	0
12	Teemu Pulkkinen		X	X		100.00	54	35	84	74	57	60	47	55	36	46	63	60	48	43	38	0	50	56	0
13	Alex Goligoski				X	99.00	65	43	86	76	57	84	95	60	35	65	55	84	48	61	55	0	50	70	0
14	Dion Phaneuf				X	99.00	82	61	68	70	73	82	94	58	35	61	55	79	48	70	60	0	50	70	0
15	T.J. Brodie				X	100.00	55	43	87	76	57	84	94	65	35	73	57	82	48	49	44	0	50	69	0
16	Jason Demers				X	100.00	72	56	77	74	65	76	93	57	35	56	58	77	48	58	50	0	50	68	0
17	Keith Yandle				X	100.00	55	43	83	75	64	79	95	61	35	72	49	72	48	66	57	0	50	67	0
18	Nate Prosser				X	100.00	58	56	84	66	66	61	63	45	35	45	45	68	48	53	48	0	50	59	0
Rayé
1	Rene Bourque		X	X		100.00	62	43	76	70	75	63	73	54	35	45	62	59	48	67	57	0	50	59	0
2	Nick Schmaltz (R)	X	X			100.00	48	35	92	81	54	57	48	59	46	63	54	62	45	35	33	0	50	58	0
3	Jakub Kindl				X	100.00	64	35	80	63	66	63	46	44	35	46	41	65	48	55	48	0	50	57	0

	MOYENNE D'ÉQUIPE					99.86	61	45	83	75	65	71	76	60	55	61	60	69	49	56	50	0	50	64

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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	Devan Dubnyk	100.00	91	99	96	82	90	82	85	89	79	70	92	55	49	0	50	80	0
2	Charlie Lindgren (R)	100.00	51	45	67	69	52	50	55	52	45	65	70	37	34	0	50	52	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	71	72	82	76	71	66	70	71	62	68	81	46	42	0	50	66

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Michel Therrien	89	74	70	90	99	94	86	QUE	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	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Henrik Zetterberg	Columbus	C/LW	82	23	48	71	13	38	0	72	133	217	12	35	10.60%	12	1570	19.15	9	16	25	74	400	0	1	1	0	54	3	0	53.54%	254	0	0.90	1	5	0	0	0	5	4	5
2	Bryan Little	Columbus	C	78	30	36	66	9	26	0	61	172	250	13	59	12.00%	7	1485	19.04	5	13	18	73	360	3	0	3	7	101	5	3	55.29%	1700	1	0.89	0	3	0	0	0	6	3	5
3	T.J. Brodie	Columbus	D	78	14	52	66	6	45	5	60	98	131	5	13	10.69%	113	1924	24.67	10	17	27	100	369	0	2	2	1	351	4	0	0.00%	0	0	0.69	0	0	0	0	1	1	5	4
4	Brayden Schenn	Columbus	C/LW/RW	80	27	37	64	6	111	25	180	89	181	20	42	14.92%	6	1453	18.17	7	18	25	58	385	0	0	0	0	29	6	1	55.24%	105	0	0.88	0	0	0	2	3	4	4	10
5	Tyler Johnson	Columbus	C	78	25	35	60	13	22	0	46	185	242	10	35	10.33%	6	1440	18.47	12	14	26	93	363	0	0	0	1	55	4	5	52.95%	1745	0	0.83	2	2	0	0	0	1	3	2
6	Kyle Palmieri	Columbus	RW	82	31	28	59	4	69	5	127	110	201	12	26	15.42%	9	1523	18.58	5	11	16	55	385	0	0	0	5	65	6	1	28.57%	98	0	0.77	1	1	0	1	0	5	7	5
7	Keith Yandle	Columbus	D	82	7	37	44	-12	42	0	39	78	101	8	11	6.93%	64	1674	20.42	1	12	13	63	398	0	1	1	0	161	1	1	0.00%	0	0	0.53	0	0	0	0	0	0	3	2
8	Alex Goligoski	Columbus	D	82	11	32	43	5	100	10	125	98	119	5	20	9.24%	110	1990	24.28	6	12	18	84	386	0	0	0	2	312	2	4	0.00%	0	0	0.43	0	0	0	1	1	1	2	1
9	Jason Demers	Columbus	D	82	9	29	38	-9	163	35	134	72	71	4	12	12.68%	98	1560	19.03	4	8	12	30	179	0	2	2	1	272	3	1	0.00%	0	0	0.49	0	0	1	2	3	1	4	2
10	Dion Phaneuf	Columbus	D	78	8	22	30	-7	246	40	207	84	109	9	13	7.34%	80	1658	21.27	6	6	12	68	315	0	1	1	0	249	1	0	0.00%	0	0	0.36	0	0	5	0	3	2	1	0
11	Adam Lowry	Columbus	C/LW	82	13	11	24	2	89	15	123	61	104	8	11	12.50%	20	1104	13.47	0	0	0	0	30	1	0	1	5	228	1	3	44.75%	181	0	0.43	0	0	1	1	1	4	0	2
12	Marian Gaborik	Columbus	LW/RW	82	9	8	17	-7	24	0	51	39	66	2	14	13.64%	3	1194	14.57	4	1	5	14	259	0	0	0	0	2	0	2	40.30%	67	0	0.28	1	1	0	0	0	0	1	2
13	Nick Spaling	Columbus	C/LW	82	5	11	16	4	22	0	42	90	77	6	14	6.49%	17	982	11.99	0	0	0	0	0	0	0	0	4	384	0	0	51.91%	603	0	0.33	0	2	0	0	0	0	0	1
14	Nate Prosser	Columbus	D	59	1	8	9	-7	45	15	34	24	23	0	1	4.35%	47	741	12.56	0	0	0	1	5	0	0	0	0	40	0	0	0.00%	0	0	0.24	0	0	2	1	0	0	0	0
15	Marcus Kruger	Columbus	C	82	5	4	9	-14	11	5	26	176	56	6	6	8.93%	19	1069	13.04	0	0	0	0	0	0	0	0	2	404	0	2	50.62%	1543	0	0.17	0	0	0	0	1	1	0	2
16	Teemu Pulkkinen	Columbus	LW/RW	66	4	4	8	0	4	0	11	14	38	3	10	10.53%	2	437	6.62	0	0	0	1	1	0	0	0	0	0	1	0	31.03%	29	0	0.37	0	0	0	0	0	1	0	0
17	Scott Laughton	Columbus	C/LW	25	3	4	7	5	8	0	12	11	22	8	10	13.64%	2	186	7.48	0	0	0	0	0	0	0	0	0	0	1	0	85.71%	7	0	0.75	0	0	0	0	0	0	0	0
18	Nick Ritchie	Columbus	LW	82	5	1	6	-11	83	5	134	30	42	7	6	11.90%	3	688	8.40	1	0	1	5	135	0	0	0	0	0	1	0	44.07%	59	0	0.17	0	0	0	0	1	0	1	1
19	Jakub Kindl	Columbus	D	25	1	4	5	17	6	0	20	9	8	0	0	12.50%	11	337	13.51	0	0	0	0	5	0	0	0	0	21	0	0	0.00%	0	0	0.30	0	0	0	0	0	1	0	0
20	Rene Bourque	Columbus	LW/RW	57	4	1	5	-10	18	0	26	19	31	0	0	12.90%	1	509	8.93	0	0	0	0	3	0	0	0	0	0	1	1	43.90%	41	0	0.20	0	0	0	0	0	0	0	0
21	Nick Schmaltz	Columbus	C/LW	6	1	1	2	-1	6	0	3	3	4	0	0	25.00%	0	76	12.69	0	0	0	0	4	0	0	0	0	0	0	0	28.57%	28	0	0.53	0	0	0	0	0	0	0	0
22	Andrew Desjardins	Monsters (Clb)	C/LW/RW	15	0	1	1	1	9	5	7	0	4	0	0	0.00%	0	90	6.01	0	0	0	0	0	0	0	0	0	10	0	0	50.00%	8	0	0.22	0	0	0	1	0	0	0	0
23	Rasmus Rissanen	Monsters (Clb)	D	4	0	1	1	4	4	0	1	1	4	0	0	0.00%	5	49	12.32	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.41	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1469	236	415	651	11	1191	165	1541	1596	2101	138	338	11.23%	635	23751	16.17	70	128	198	719	3992	4	7	11	28	2747	40	24	51.93%	6468	1	0.55	5	14	9	9	14	33	38	44

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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	Devan Dubnyk	Columbus	75	44	24	4	0.906	2.25	4320	4	4	162	1724	5	2	0.714	21	71	11	6	4	1
2	Charlie Lindgren	Columbus	8	1	6	0	0.828	4.71	433	0	0	34	198	0	0	0.000	0	7	39	0	0	0
3	Alex Stalock	Monsters (Clb)	6	0	3	0	0.750	6.43	196	0	0	21	84	0	0	0.000	0	4	32	0	0	0
Stats d'équipe Total ou en Moyenne			89	45	33	4	0.892	2.63	4949	4	4	217	2006	5	2	0.714	21	82	82	6	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	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
Adam Lowry	Columbus	C/LW	23	1993-03-29	No	210 Lbs	6 ft5	No	No	No	2	Avec Restriction	Pro & Farm	818,000$