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	TA	SP
1	Marian Hossa (C)			X		100.00	53	35	90	79	72	76	88	74	37	71	76	72	50	99	94	0	50	73		0
2	Brandon Dubinsky (A)	X				100.00	85	65	71	72	75	78	92	73	85	77	69	71	58	66	57	0	50	71		0
3	Jordan Staal	X				100.00	71	50	83	72	77	78	93	73	91	75	70	73	45	70	62	0	50	71		0
4	James van Riemsdyk		X			100.00	59	43	85	80	73	74	86	74	35	73	75	61	53	61	52	0	50	69		0
5	Brad Richardson (A)	X	X			98.00	60	50	79	73	67	71	56	65	87	63	67	73	45	68	61	0	50	65		0
6	Jannik Hansen		X	X		99.00	57	50	79	72	66	72	68	67	35	63	70	74	45	66	57	0	50	65	X	0
7	Mikkel Boedker		X	X		100.00	57	35	91	73	72	72	94	66	35	66	65	61	50	59	51	0	50	65	X	0
8	Paul Byron		X	X		100.00	58	50	86	81	44	71	84	66	38	61	70	76	69	49	45	0	50	65		0
9	Brian Boyle	X	X			100.00	63	61	76	66	90	65	93	58	86	52	63	66	61	69	61	0	50	64	X	0
10	Eric Fehr	X		X		100.00	58	43	87	66	74	67	71	61	84	58	63	72	53	68	62	0	50	64		0
11	Connor Brown (R)			X		100.00	52	35	91	76	58	64	58	60	40	54	65	72	48	38	35	0	50	60		0
12	Alec Martinez				X	100.00	66	35	86	75	69	78	95	60	35	64	55	80	48	59	56	0	50	69		0
13	Nick Holden				X	100.00	75	50	85	72	71	78	94	59	35	58	59	79	48	47	44	0	50	68		0
14	Trevor Daley				X	100.00	60	50	81	73	62	78	78	58	35	60	55	77	48	72	63	0	50	67	X	0
15	Nick Schultz				X	100.00	62	43	84	61	67	70	61	47	40	49	45	80	48	74	63	0	50	63	X	0
16	Xavier Ouellet (R)				X	100.00	65	50	77	65	68	68	53	47	35	47	47	85	48	43	39	0	50	62		0
17	Nikita Zaitsev (R)				X	100.00	70	35	84	73	64	60	57	51	35	59	43	72	48	35	33	0	50	60		0
Rayé
1	Luke Glendening	X		X		43.62	69	43	85	71	68	68	93	54	86	53	54	77	48	49	40	0	50	62	X	0
2	Nick Jensen (R)				X	80.35	59	35	88	70	63	55	44	48	35	47	49	72	48	35	32	0	50	57		0
3	Paul LaDue (R)				X	78.38	51	35	89	66	66	52	37	45	35	58	32	62	48	35	32	0	50	53		0

	MOYENNE D'ÉQUIPE					94.90	63	45	84	72	68	70	75	60	51	60	60	73	50	58	52	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	Al Montoya	98.00	74	45	94	79	74	76	76	74	75	98	77	51	46	0	50	72	0
2	Peter Budaj	100.00	74	55	89	72	72	74	70	70	78	74	60	58	51	0	50	69	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	74	50	92	76	73	75	73	72	77	86	69	55	49	0	50	71

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Darryl Sutter	99	95	86	99	99	99	96	CAN	59	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	Brandon Dubinsky	Kansas City	C	79	29	55	84	26	160	30	239	131	213	18	37	13.62%	9	1347	17.06	6	12	18	54	343	0	1	1	1	24	4	1	54.80%	1668	0	2	1.25	2	2	2	1	3	6	6	6
2	Jordan Staal	Kansas City	C	81	22	49	71	2	63	5	140	193	214	14	33	10.28%	12	1542	19.04	5	18	23	60	330	0	1	1	4	176	5	3	56.93%	1948	0	0	0.92	0	0	0	0	1	6	4	3
3	Paul Byron	Kansas City	LW/RW	81	25	41	66	1	24	10	35	106	257	18	51	9.73%	11	1550	19.14	5	13	18	58	309	1	0	1	13	289	7	0	30.33%	122	0	1	0.85	1	3	0	0	2	6	3	7
4	Marian Hossa	Kansas City	RW	66	30	34	64	7	14	0	13	93	211	11	33	14.22%	9	1101	16.69	11	7	18	60	279	0	0	0	0	0	8	3	28.21%	78	0	0	1.16	1	1	0	0	0	5	5	5
5	Nick Holden	Kansas City	D	82	14	44	58	9	153	25	168	82	106	10	16	13.21%	84	1871	22.82	10	11	21	60	340	0	2	2	2	280	1	2	0.00%	0	0	0	0.62	0	0	0	3	2	1	0	6
6	James van Riemsdyk	Kansas City	LW	83	20	34	54	-10	39	5	100	87	207	15	41	9.66%	9	1414	17.05	5	14	19	62	388	0	0	0	0	25	4	0	31.78%	107	0	0	0.76	1	3	0	0	1	4	5	2
7	Alec Martinez	Kansas City	D	82	11	42	53	-1	86	0	95	98	124	19	28	8.87%	90	1979	24.14	8	9	17	77	344	0	1	1	4	335	2	1	0.00%	0	0	0	0.54	0	0	0	0	0	3	3	3
8	Brad Richardson	Kansas City	C/LW	82	20	27	47	13	38	10	90	124	158	7	26	12.66%	14	1455	17.75	5	10	15	33	231	2	0	2	8	295	0	1	58.37%	627	0	0	0.65	0	0	1	0	1	1	8	3
9	Trevor Daley	Kansas City	D	79	8	37	45	-1	70	0	82	70	85	9	13	9.41%	80	1694	21.45	6	11	17	62	321	0	0	0	3	281	2	1	0.00%	0	0	0	0.53	0	0	0	0	0	1	3	2
10	Jannik Hansen	Kansas City	LW/RW	80	23	21	44	10	42	10	32	79	147	10	13	15.65%	11	1173	14.67	1	5	6	15	104	0	0	0	1	163	5	0	35.40%	113	0	1	0.75	0	0	1	0	1	3	4	3
11	Eric Fehr	Kansas City	C/RW	84	16	22	38	-9	43	15	72	128	144	5	16	11.11%	16	1359	16.18	1	8	9	30	243	0	0	0	4	155	3	4	53.45%	1231	0	0	0.56	0	0	3	0	0	4	3	1
12	Mikkel Boedker	Kansas City	LW/RW	81	14	19	33	5	18	0	30	62	112	7	19	12.50%	6	1046	12.92	1	4	5	17	170	0	0	0	0	0	1	2	22.50%	80	0	0	0.63	0	0	0	0	0	2	1	3
13	Nick Schultz	Kansas City	D	82	5	20	25	-6	48	0	89	56	71	2	9	7.04%	114	1648	20.11	2	6	8	31	228	1	0	1	1	306	0	1	0.00%	0	0	0	0.30	0	0	0	0	0	0	0	1
14	Connor Brown	Kansas City	RW	80	10	13	23	11	6	0	14	52	105	12	14	9.52%	11	702	8.78	0	3	3	4	26	0	0	0	1	9	2	0	37.78%	45	0	0	0.65	0	0	0	0	0	0	1	0
15	Brian Boyle	Kansas City	C/LW	78	5	12	17	4	49	15	59	51	66	2	13	7.58%	8	767	9.84	0	0	0	0	7	1	0	1	5	191	1	0	57.14%	595	0	0	0.44	0	0	1	1	1	0	1	2
16	Luke Glendening	Kansas City	C/RW	79	7	9	16	6	38	10	73	155	65	8	10	10.77%	21	1019	12.90	0	0	0	0	1	0	1	1	1	402	1	1	52.01%	1319	1	0	0.31	0	0	1	1	0	1	1	0
17	Xavier Ouellet	Kansas City	D	60	2	12	14	0	57	15	59	55	47	0	7	4.26%	77	1004	16.73	1	5	6	16	83	0	0	0	0	166	0	0	0.00%	1	0	0	0.28	0	0	0	0	3	0	0	0
18	Nikita Zaitsev	Kansas City	D	58	2	12	14	-3	50	0	68	32	32	1	10	6.25%	52	1090	18.80	2	1	3	17	179	0	0	0	2	145	1	0	0.00%	0	0	0	0.26	0	0	0	0	0	0	0	0
19	Steve Bernier	Jayhawks (KC )	RW	40	6	2	8	-5	4	0	31	20	33	0	0	18.18%	2	445	11.15	0	0	0	3	43	0	0	0	0	9	1	1	31.25%	32	0	0	0.36	1	2	0	0	0	0	1	1
20	Nick Jensen	Kansas City	D	66	0	8	8	4	42	0	51	37	24	4	8	0.00%	54	1081	16.39	0	1	1	7	130	0	0	0	0	111	0	0	0.00%	0	0	0	0.15	0	0	0	0	0	0	0	0
21	Jordan Oesterle	Jayhawks (KC )	D	14	1	3	4	-1	4	0	3	7	4	0	0	25.00%	6	201	14.36	0	0	0	0	6	0	0	0	0	22	0	0	0.00%	0	0	0	0.40	0	0	0	0	0	0	0	0
22	Evan Rodrigues	Jayhawks (KC )	C/LW/RW	8	1	0	1	-3	2	0	0	1	2	0	0	50.00%	0	54	6.86	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	2	0	0	0.36	0	0	0	0	0	0	0	0
23	Nikita Soshnikov	Jayhawks (KC )	LW/RW	11	0	1	1	-1	4	0	5	5	4	0	0	0.00%	0	75	6.90	0	0	0	0	0	0	0	0	0	0	0	0	57.14%	7	0	0	0.26	0	0	0	0	0	0	0	0
24	Drake Caggiula	Jayhawks (KC )	C/LW/RW	15	0	1	1	-3	2	0	2	7	6	0	0	0.00%	0	117	7.82	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	4	0	0	0.17	0	0	0	0	0	0	0	0
25	Paul LaDue	Kansas City	D	8	0	1	1	3	0	0	3	1	1	0	0	0.00%	2	98	12.33	0	0	0	1	1	0	0	0	0	3	0	0	0.00%	0	0	0	0.20	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1559	271	519	790	58	1056	150	1553	1732	2438	172	397	11.12%	698	25845	16.58	69	138	207	667	4117	5	6	11	50	3397	48	21	53.33%	7979	1	4	0.61	6	11	9	6	15	43	49	48

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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	Peter Budaj	Kansas City	49	28	15	5	0.889	2.73	2905	0	2	132	1189	1	0.333	3	49	19	2	2	2
2	Al Montoya	Kansas City	26	14	9	0	0.885	3.25	1423	2	0	77	672	0	1.000	5	23	50	0	0	1
3	Carter Hutton	Jayhawks (KC )	9	4	4	0	0.894	2.93	450	2	0	22	208	1	0.000	0	7	9	0	0	1
Stats d'équipe Total ou en Moyenne			84	46	28	5	0.888	2.90	4779	4	2	231	2069	2	0.750	8	79	78	2	2	4

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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
Al Montoya	Kansas City	G	31	1985-02-13	No	209 Lbs	6 ft2	Yes	No	No	6	Sans Restriction	Pro & Farm	3,000,000$