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	Reilly Smith		X	X		97.00	56	43	88	76	58	76	95	69	35	67	71	74	42	48	44	0	50	67	0
2	Jiri Hudler		X	X		99.00	51	43	88	78	60	68	62	68	37	69	66	56	56	71	64	0	50	64	0
3	Victor Rask	X				99.00	56	35	88	76	69	70	92	66	83	65	67	63	45	37	34	0	50	64	0
4	Matt Read		X	X		100.00	58	43	89	74	57	70	82	60	35	56	64	71	53	53	44	0	50	62	0
5	Tomas Fleischmann		X	X		100.00	51	35	84	72	65	64	84	57	47	52	61	70	54	65	56	0	50	62	0
6	Melker Karlsson		X	X		100.00	60	35	87	73	55	65	82	58	35	53	63	74	56	40	37	0	50	61	0
7	Sven Andrighetto		X	X		100.00	58	35	88	77	58	66	63	63	35	63	62	64	53	37	34	0	50	61	0
8	Markus Granlund	X	X	X		100.00	53	35	88	76	57	68	59	59	82	51	66	69	61	45	39	0	50	61	0
9	Austin Watson	X	X	X		100.00	70	67	70	65	72	58	64	50	41	50	50	80	48	40	37	0	50	58	0
10	Tom Kuhnhackl		X	X		100.00	64	35	85	70	68	60	54	53	35	54	52	71	48	41	42	0	50	58	0
11	Jordan Schroeder	X	X	X		100.00	52	35	95	77	56	54	43	55	46	51	58	62	48	46	41	0	50	56	0
12	Tyler Pitlick		X	X		100.00	65	35	89	71	70	52	39	50	40	44	56	58	48	41	36	0	50	54	0
13	Paul Martin				X	100.00	57	43	88	71	65	76	94	52	35	56	47	83	48	78	68	0	50	68	0
14	Michael Del Zotto				X	99.00	75	35	83	73	63	77	70	57	35	56	58	73	48	59	50	0	50	65	0
15	Marco Scandella				X	99.00	68	56	86	66	69	76	90	51	35	52	49	77	48	53	48	0	50	65	0
16	Jason Garrison				X	100.00	64	43	89	64	72	74	88	48	35	48	47	76	48	61	53	0	50	64	0
17	Tobias Enstrom				X	100.00	52	43	79	70	54	78	72	52	35	58	45	78	48	56	46	0	50	63	0
18	Brandon Montour (R)				X	100.00	54	35	82	74	62	55	38	47	35	45	49	71	56	37	34	0	50	57	0
Rayé
1	Shane Doan			X		100.00	62	50	76	72	77	72	90	64	81	63	65	60	42	89	78	0	50	67	0
2	Kyle Brodziak	X		X		98.97	56	56	84	68	74	65	88	57	83	52	61	73	48	69	60	0	50	63	0
3	Clayton Stoner				X	100.00	72	56	60	61	72	69	46	46	35	46	45	71	45	56	49	0	50	60	0

	MOYENNE D'ÉQUIPE					99.57	60	43	84	72	64	67	71	56	46	55	57	70	50	53	47	0	50	62

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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	Anders Nilsson	100.00	71	45	91	90	74	66	67	78	64	81	87	39	36	0	50	67	0
2	Alexandar Georgiyev (R)	99.00	45	45	45	45	45	45	45	45	45	45	45	45	45	0	50	45	0
Rayé
1	James Reimer	98.00	73	51	91	82	75	71	69	77	72	74	94	51	45	0	50	69	0
2	Scott Darling	93.46	76	45	86	91	78	71	71	80	71	65	94	38	37	0	50	69	0

	MOYENNE D'ÉQUIPE	97.50	66	47	78	77	68	63	63	70	63	66	80	43	41	0	50	63

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dave Hakstol	94	91	86	94	66	61	82	CAN	48	4	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	Reilly Smith	Toronto	LW/RW	81	33	37	70	1	24	0	68	113	234	23	47	14.10%	5	1327	16.39	9	15	24	56	215	0	0	0	6	136	3	2	28.89%	90	2	1.05	1	3	0	0	0	11	2	2
2	Victor Rask	Toronto	C	80	24	36	60	-3	30	0	94	135	187	10	28	12.83%	10	1491	18.65	5	14	19	44	353	0	0	0	0	31	2	2	51.69%	1865	2	0.80	1	1	0	0	0	6	3	3
3	Michael Del Zotto	Toronto	D	82	10	46	56	-5	106	10	140	79	139	13	26	7.19%	73	1787	21.79	8	12	20	92	323	0	0	0	0	160	2	1	0.00%	0	0	0.63	0	0	0	0	1	4	2	0
4	Jiri Hudler	Toronto	LW/RW	81	23	33	56	-10	30	0	50	115	183	11	33	12.57%	5	1532	18.92	8	15	23	47	354	0	0	0	2	82	4	1	29.93%	147	0	0.73	0	3	0	0	0	3	2	5
5	Shane Doan	Toronto	RW	77	19	35	54	-7	79	15	141	64	160	4	31	11.88%	9	1226	15.93	8	12	20	43	271	0	0	0	0	4	2	0	56.60%	106	0	0.88	0	0	0	1	2	2	5	2
6	Markus Granlund	Toronto	C/LW/RW	82	24	30	54	2	18	0	50	131	187	11	30	12.83%	5	1246	15.20	7	15	22	46	257	0	0	0	0	2	5	0	53.03%	511	0	0.87	1	4	0	0	0	4	2	2
7	Tobias Enstrom	Toronto	D	81	13	35	48	-8	46	0	63	68	87	5	11	14.94%	77	1626	20.08	10	11	21	62	338	0	1	1	0	182	0	1	0.00%	0	0	0.59	0	0	0	0	0	0	2	3
8	Marco Scandella	Toronto	D	82	11	32	43	-10	138	40	164	76	96	10	15	11.46%	103	1843	22.48	6	14	20	61	334	0	0	0	0	292	3	0	0.00%	0	0	0.47	0	0	1	2	4	2	0	4
9	Paul Martin	Toronto	D	55	7	21	28	3	32	0	33	60	66	4	12	10.61%	67	1225	22.27	3	7	10	40	199	0	0	0	0	183	1	1	0.00%	0	0	0.46	0	0	0	0	0	1	0	1
10	Sven Andrighetto	Toronto	LW/RW	78	10	15	25	2	16	0	46	52	93	9	26	10.75%	8	737	9.45	1	2	3	11	70	0	0	0	0	3	1	1	25.00%	44	0	0.68	0	0	0	0	0	0	2	2
11	Brandon Montour	Toronto	D	73	6	17	23	-3	34	0	39	51	45	2	3	13.33%	46	1097	15.04	1	4	5	14	122	0	0	0	0	88	0	0	0.00%	0	0	0.42	0	1	0	0	0	0	1	1
12	Matt Read	Toronto	LW/RW	81	12	9	21	0	12	0	39	61	93	3	14	12.90%	11	758	9.36	1	0	1	3	22	0	0	0	0	7	0	1	34.78%	46	0	0.55	0	1	0	0	0	1	2	0
13	Austin Watson	Toronto	C/LW/RW	81	7	5	12	-10	76	30	108	88	50	3	4	14.00%	16	913	11.28	1	1	2	6	36	0	0	0	5	254	3	0	31.70%	918	0	0.26	0	0	2	0	4	0	1	2
14	Tomas Fleischmann	Toronto	LW/RW	82	7	4	11	3	20	0	29	60	80	4	10	8.75%	6	932	11.37	0	0	0	4	29	1	0	1	4	154	1	0	41.07%	56	0	0.24	0	2	0	0	0	0	0	0
15	Clayton Stoner	Toronto	D	43	2	7	9	-2	95	15	99	22	28	0	2	7.14%	45	733	17.05	0	1	1	12	61	0	0	0	0	126	0	0	0.00%	0	0	0.25	0	0	0	0	2	0	0	0
16	Kyle Brodziak	Toronto	C/RW	60	3	6	9	3	46	10	41	113	63	3	11	4.76%	19	876	14.60	0	0	0	0	13	0	0	0	2	271	1	0	52.88%	1146	0	0.21	0	0	1	0	1	0	0	1
17	Melker Karlsson	Toronto	LW/RW	76	5	3	8	-15	6	0	43	56	76	6	6	6.58%	16	891	11.73	0	0	0	2	3	0	0	0	4	294	0	0	20.93%	86	0	0.18	1	2	0	0	0	0	0	1
18	Corey Potter	Marlies (Tor)	D	34	2	5	7	-14	22	0	32	15	8	0	0	25.00%	40	545	16.05	2	1	3	4	40	0	1	1	0	73	0	0	0.00%	1	0	0.26	0	0	0	0	0	0	0	0
19	Tom Kuhnhackl	Toronto	LW/RW	56	1	5	6	-4	16	0	29	25	35	0	5	2.86%	2	476	8.51	0	0	0	0	0	0	0	0	1	66	0	0	25.93%	27	0	0.25	0	0	0	0	0	0	0	1
20	Jason Garrison	Toronto	D	55	2	3	5	-4	42	0	57	45	24	3	2	8.33%	68	1048	19.06	0	0	0	3	47	0	0	0	2	192	1	0	0.00%	0	0	0.10	0	0	0	0	0	0	0	0
21	Alexander Burmistrov	Marlies (Tor)	C/LW/RW	8	0	3	3	3	2	0	1	8	6	0	0	0.00%	0	66	8.29	0	0	0	0	3	0	0	0	0	9	0	0	47.37%	57	0	0.90	0	0	0	0	0	0	0	0
22	Brayden McNabb	Marlies (Tor)	D	1	0	1	1	0	7	5	3	1	0	0	0	0.00%	0	16	16.22	0	0	0	0	0	0	0	0	0	4	0	0	0.00%	0	0	1.23	0	0	1	0	0	0	0	0
23	Alexey Marchenko	Marlies (Tor)	D	1	0	1	1	0	0	0	0	3	0	0	0	0.00%	1	15	15.85	0	0	0	0	0	0	0	0	0	2	0	0	0.00%	0	0	1.26	0	0	0	0	0	0	0	0
24	Jordan Schroeder	Toronto	C/LW/RW	5	0	0	0	-4	0	0	1	6	4	3	5	0.00%	1	41	8.26	0	0	0	0	2	0	0	0	0	4	0	0	35.14%	37	0	0.00	0	0	0	0	0	0	0	0
25	Tyler Pitlick	Toronto	LW/RW	5	0	0	0	-4	0	0	1	1	2	1	1	0.00%	0	36	7.29	0	0	0	0	0	0	0	0	0	0	0	0	25.00%	8	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1440	221	389	610	-86	897	125	1371	1448	1946	128	322	11.36%	633	22493	15.62	70	124	194	550	3103	1	2	3	26	2630	29	10	46.24%	5145	4	0.54	4	17	5	3	14	34	24	30

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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	SO	GA	SA	A	EG	PS %	PSA	ST	BG	S1	S2
1	Scott Darling	Toronto	30	17	9	2	0.901	2.34	1716	2	67	674	1	0	0.600	10	28	35	2	1
2	James Reimer	Toronto	37	15	15	4	0.892	2.82	1999	1	94	874	1	0	0.600	10	33	22	2	1
3	Anders Nilsson	Toronto	12	2	5	2	0.867	3.46	589	0	34	255	1	1	0.500	6	9	17	0	0
4	Alexandar Georgiyev	Toronto	1	0	1	0	0.750	12.63	19	0	4	16	0	0	0.000	0	1	2	0	0
5	Anthony Stolarz	Marlies (Tor)	6	0	3	0	0.889	2.93	225	0	11	99	0	0	0.000	0	2	24	0	0
Stats d'équipe Total ou en Moyenne			86	34	33	8	0.891	2.77	4550	3	210	1918	3	1	0.577	26	73	100	4	2

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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
Alexandar Georgiyev	Toronto	G	20	1996-02-10 04:11:51	Yes	176 Lbs	6 ft1	No	No	No	4	Contrat d'Entrée	Pro & Farm	792,500$