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	Logan Couture (A)	X				100.00	56	43	89	78	69	77	80	76	80	77	75	70	69	64	55	0	50	71	0
2	Loui Eriksson		X	X		100.00	51	43	91	71	68	79	86	70	38	69	71	73	42	66	56	0	50	68	0
3	Gustav Nyquist		X	X		100.00	54	35	87	82	57	74	93	71	35	74	68	61	55	50	45	0	50	67	0
4	Bo Horvat	X				100.00	60	43	87	75	77	70	82	65	84	64	66	75	61	38	35	0	50	66	0
5	Antoine Roussel		X			100.00	69	66	57	73	69	67	79	62	39	58	65	74	56	47	41	0	50	64	0
6	Carl Hagelin		X			99.00	58	43	87	73	58	71	80	62	35	61	62	73	48	62	58	0	50	64	0
7	Scottie Upshall		X	X		100.00	62	43	80	72	69	62	90	56	35	50	61	67	56	71	64	0	50	62	0
8	Maxime Talbot	X	X	X		100.00	60	43	84	70	58	59	63	52	78	50	53	73	54	70	63	0	50	60	0
9	Brian Flynn	X	X	X		100.00	52	35	92	70	57	64	71	54	85	50	58	74	58	46	41	0	50	59	0
10	Ryan Hartman (R)		X	X		100.00	71	50	74	77	56	65	54	59	35	51	66	63	48	38	35	0	50	59	0
11	Ivan Barbashev (R)	X	X			100.00	52	35	93	79	55	58	39	58	55	55	61	62	48	36	33	0	50	57	0
12	Pierre-Edouard Bellemare	X	X	X		100.00	54	50	87	68	68	63	76	47	82	43	50	78	48	37	34	0	50	57	0
13	Oliver Ekman-Larsson				X	100.00	73	43	77	76	66	85	93	67	35	70	64	75	53	55	46	0	50	70	0
14	Seth Jones				X	99.00	63	43	87	75	74	80	93	62	35	66	58	79	56	50	40	0	50	69	0
15	Sami Vatanen				X	100.00	63	35	85	73	56	79	88	60	35	67	53	79	56	47	44	0	50	66	0
16	Olli Maatta				X	100.00	66	43	88	62	68	72	74	48	35	48	47	84	48	52	48	0	50	64	0
17	Adam Clendening				X	100.00	58	43	81	71	63	59	42	49	35	53	45	64	48	37	34	0	50	56	0
18	Slater Koekkoek (R)				X	100.00	55	35	87	64	63	53	39	38	35	43	32	68	48	38	35	0	50	53	0
Rayé
1	Vladimir Tarasenko			X		100.00	56	43	88	85	75	78	95	82	37	78	86	62	49	50	44	0	50	73	0
2	David Krejci (C)	X				100.00	53	35	86	80	58	78	94	76	85	79	72	64	53	71	64	0	50	71	0
3	Erik Johnson (A)				X	100.00	74	50	86	63	77	82	70	58	35	60	55	82	45	59	49	0	50	67	0
4	Nate Schmidt				X	100.00	59	43	88	70	63	65	58	47	35	50	43	75	48	48	41	0	50	60	0

	MOYENNE D'ÉQUIPE					99.91	60	43	85	73	65	70	75	60	49	60	60	72	52	51	46	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	Karri Ramo	99.00	57	45	88	77	57	56	57	57	54	71	69	47	43	0	50	58	0
2	Joacim Eriksson	100.00	41	45	42	69	41	39	39	40	39	39	38	35	32	0	50	43	0
Rayé
1	Carey Price	100.00	92	84	98	87	92	81	88	91	74	76	89	65	56	0	50	81	0

	MOYENNE D'ÉQUIPE	99.67	63	58	76	78	63	59	61	63	56	62	65	49	44	0	50	61

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jon Cooper	83	94	88	85	80	86	86	CAN	38	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	Vladimir Tarasenko	Colorado	RW	81	42	46	88	15	49	5	103	125	321	29	73	13.08%	5	1581	19.52	13	19	32	72	368	0	0	0	0	0	4	5	35.48%	93	1	1.11	0	3	0	0	1	11	6	3
2	David Krejci	Colorado	C	81	25	55	80	21	38	0	87	180	232	17	42	10.78%	5	1611	19.90	6	21	27	55	369	0	0	0	0	14	4	0	53.50%	2017	0	0.99	0	0	0	0	0	5	8	3
3	Loui Eriksson	Colorado	LW/RW	82	27	38	65	19	23	5	46	88	210	14	52	12.86%	15	1539	18.77	13	13	26	64	364	0	0	0	0	5	5	1	35.48%	93	0	0.84	0	0	1	0	0	5	5	3
4	Oliver Ekman-Larsson	Colorado	D	82	13	47	60	2	117	5	180	101	154	21	32	8.44%	86	1913	23.34	7	16	23	83	372	0	0	0	0	144	2	1	0.00%	0	0	0.63	0	1	0	1	0	0	4	5
5	Logan Couture	Colorado	C	76	24	35	59	5	46	10	88	156	221	11	32	10.86%	6	1330	17.51	7	14	21	65	307	0	0	0	2	59	6	3	51.77%	1584	0	0.89	2	7	0	2	0	7	1	3
6	Gustav Nyquist	Colorado	LW/RW	78	22	34	56	13	30	0	73	82	174	12	56	12.64%	7	1248	16.00	7	14	21	43	308	0	0	0	0	3	5	0	28.00%	75	0	0.90	0	3	0	0	0	6	4	2
7	Seth Jones	Colorado	D	82	13	41	54	15	56	0	92	81	153	11	30	8.50%	98	1937	23.63	7	13	20	94	370	0	1	1	1	285	4	0	0.00%	0	0	0.56	1	6	0	0	0	3	1	5
8	Sami Vatanen	Colorado	D	82	6	34	40	2	50	0	102	81	101	12	8	5.94%	92	1646	20.08	3	12	15	75	330	0	0	0	2	253	1	1	0.00%	0	0	0.49	1	3	0	0	0	2	3	0
9	Carl Hagelin	Colorado	LW	82	11	27	38	21	35	5	88	74	112	8	14	9.82%	17	1364	16.65	1	1	2	7	43	1	3	4	11	333	2	0	34.38%	96	0	0.56	0	0	0	0	1	1	2	3
10	Erik Johnson	Colorado	D	74	6	17	23	4	131	35	97	77	87	8	13	6.90%	78	1641	22.18	5	2	7	51	265	0	0	0	2	238	1	0	0.00%	0	0	0.28	0	0	0	2	5	0	1	0
11	Ryan Hartman	Colorado	LW/RW	82	11	12	23	-6	52	10	147	39	98	7	17	11.22%	4	891	10.87	2	3	5	13	183	0	0	0	0	0	2	2	35.29%	51	0	0.52	0	0	1	1	0	2	2	1
12	Antoine Roussel	Colorado	LW	82	7	6	13	1	133	35	107	58	88	6	13	7.95%	8	895	10.92	0	0	0	0	4	0	0	0	2	235	1	0	32.76%	58	0	0.29	2	9	2	2	3	1	2	1
13	Pierre-Edouard Bellemare	Colorado	C/LW/RW	43	7	5	12	9	20	10	16	55	26	6	10	26.92%	16	515	11.98	0	0	0	0	7	1	0	1	1	156	0	0	49.67%	610	0	0.47	0	0	0	2	0	0	1	1
14	Olli Maatta	Colorado	D	82	2	10	12	9	84	0	103	51	44	4	9	4.55%	118	1499	18.29	0	0	0	15	74	0	0	0	1	279	0	0	0.00%	0	0	0.16	0	0	0	0	0	0	2	0
15	Bo Horvat	Colorado	C	56	7	4	11	-3	14	0	31	131	60	4	19	11.67%	10	790	14.12	1	0	1	4	29	1	1	2	5	219	1	0	51.80%	1002	0	0.28	0	5	0	0	0	2	1	0
16	Nate Schmidt	Colorado	D	81	2	8	10	-3	35	5	58	39	20	3	4	10.00%	48	1138	14.06	0	0	0	1	21	0	0	0	0	95	0	0	0.00%	0	0	0.18	0	0	0	1	0	0	0	1
17	Maxime Talbot	Colorado	C/LW/RW	62	4	5	9	-10	20	0	23	28	41	1	14	9.76%	3	484	7.81	0	0	0	0	2	0	0	0	2	37	0	0	48.09%	131	0	0.37	1	2	0	0	0	0	0	0
18	Anthony Duclair	Monsters (Col)	LW/RW	63	5	3	8	-22	12	0	24	27	39	0	2	12.82%	3	709	11.27	1	1	2	6	121	0	0	0	0	10	0	0	22.22%	54	0	0.23	1	1	0	0	0	0	0	1
19	Scottie Upshall	Colorado	LW/RW	77	4	4	8	-4	37	5	49	28	68	6	12	5.88%	4	571	7.42	0	0	0	0	5	1	0	1	1	35	1	0	28.95%	38	0	0.28	0	0	0	0	1	0	1	0
20	Brian Flynn	Colorado	C/LW/RW	58	3	3	6	-8	10	0	11	39	58	1	6	5.17%	5	575	9.93	0	0	0	3	16	0	0	0	7	183	1	0	44.23%	104	0	0.21	1	1	0	0	0	0	0	0
21	Ivan Barbashev	Colorado	C/LW	10	1	1	2	-4	0	0	3	2	9	0	3	11.11%	1	78	7.89	0	0	0	0	4	0	0	0	0	0	0	0	25.00%	20	0	0.51	0	0	0	0	0	0	0	0
22	Adam Clendening	Colorado	D	1	0	1	1	0	0	0	2	0	0	0	1	0.00%	1	15	15.27	0	0	0	0	2	0	0	0	0	0	0	0	0.00%	0	0	1.31	0	0	0	0	0	0	0	0
23	Slater Koekkoek	Colorado	D	4	0	1	1	2	2	0	2	0	1	0	0	0.00%	5	55	13.98	0	0	0	0	1	0	0	0	0	6	0	0	0.00%	0	0	0.36	0	0	0	0	0	0	0	0
24	Adam Pardy	Monsters (Col)	D	1	0	0	0	-3	0	0	0	0	0	0	0	0.00%	0	13	13.55	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00	0	0	0	0	0	0	0	0
25	Michael Kostka	Monsters (Col)	D	3	0	0	0	-5	2	0	3	1	0	0	0	0.00%	1	31	10.54	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00	0	0	0	0	0	0	0	0
26	Jakub Vrana	Monsters (Col)	LW/RW	4	0	0	0	0	0	0	2	1	2	0	0	0.00%	0	26	6.66	0	0	0	0	0	0	0	0	0	0	0	0	33.33%	3	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1509	242	437	679	70	996	130	1537	1544	2319	181	462	10.44%	636	24110	15.98	73	129	202	651	3575	4	5	9	37	2599	40	13	50.02%	6029	1	0.56	9	41	4	11	11	45	44	32

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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	Carey Price	Colorado	72	37	26	7	0.902	2.49	4249	2	5	176	1795	4	1	0.861	36	71	6	3	4	6
2	Karri Ramo	Colorado	12	6	4	2	0.851	3.42	650	2	0	37	248	1	0	0.750	4	11	16	0	0	0
3	Joacim Eriksson	Colorado	4	0	0	0	0.860	4.62	78	0	0	6	43	0	0	0.000	0	0	50	0	0	0
Stats d'équipe Total ou en Moyenne			88	43	30	9	0.895	2.64	4979	4	5	219	2086	5	1	0.850	40	82	72	3	4	6

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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 Clendening	Colorado	D	23	1992-10-26	No	196 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	818,000$