Ligue de hockey Simulée Ste-Flanelle

Washington
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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	Andreas Martinsen		X	X		100.00	83	50	81	66	77	58	58	48	69	48	48	61	48	38	35	0	50	55	0
2	Byron Froese	X				100.00	54	43	84	71	71	61	44	47	83	43	50	67	48	37	34	0	50	54	0
3	Michael McCarron (R)	X		X		100.00	67	66	64	64	84	59	43	47	77	48	46	54	48	38	35	0	50	53	0
4	Ryan Carpenter (R)	X				100.00	52	35	86	76	66	54	36	42	47	40	44	68	48	37	34	0	50	52	0
5	Brock Boeser (R)			X		100.00	50	35	95	77	64	58	35	47	35	46	48	55	48	35	32	0	50	52	0
6	Kevin Porter	X	X	X		100.00	56	35	95	72	62	58	36	39	35	43	35	64	48	51	45	0	50	51	0
7	Brian O'Neill			X		100.00	49	35	85	72	51	47	35	38	49	42	33	69	47	35	32	0	50	49	0
8	Emile Poirier		X	X		100.00	54	35	82	69	58	60	33	43	36	43	42	54	47	35	32	0	50	49	0
9	Tyler Biggs (R)			X		100.00	47	50	49	49	71	46	46	47	49	47	47	50	48	32	30	0	50	48	0
10	Ryan Gropp		X			100.00	45	45	45	45	72	45	45	45	45	45	45	45	45	32	30	0	50	46	0
11	Steven Shipley (R)	X				100.00	38	40	40	40	71	37	37	38	40	38	38	40	39	32	30	0	50	41	0
12	Shea Theodore (R)				X	100.00	54	35	78	68	64	68	43	50	35	51	49	66	56	39	36	0	50	57	0
13	Joe Morrow				X	100.00	64	35	86	62	64	61	38	44	35	40	47	64	48	38	35	0	50	54	0
14	Mikhail Sergachev (R)				X	100.00	56	35	95	62	71	48	35	31	35	30	32	60	48	35	32	0	50	50	0
15	Jakub Zboril				X	100.00	50	50	50	50	59	50	50	50	50	50	50	50	50	32	30	0	50	49	0
16	Madison Bowey (R)				X	100.00	43	45	45	45	63	42	42	43	45	43	43	45	44	32	30	0	50	45	0
17	Mathieu Brisebois (R)				X	100.00	43	45	45	45	55	42	42	43	45	43	43	45	44	32	30	0	50	44	0
18	Brycen Martin (R)				X	100.00	41	43	43	43	63	40	40	41	43	41	41	43	42	32	30	0	50	43	0
19	Joey Leach (R)				X	100.00	41	43	43	43	61	40	40	41	43	41	41	43	42	32	30	0	50	43	0
20	Adam Janosik (R)				X	100.00	41	43	43	43	50	40	40	41	43	41	41	43	42	32	30	0	50	42	0
21	Justin Weller (R)				X	100.00	38	40	40	40	68	37	37	38	40	38	38	40	39	32	30	0	50	41	0
22	Loic Leduc (R)				X	100.00	38	40	40	40	64	37	37	38	40	38	38	40	39	32	30	0	50	41	0
23	Mike McKee (R)				X	100.00	35	37	37	37	78	35	35	35	37	35	35	37	36	32	30	0	50	40	0
Rayé
1	Kelsey Tessier (R)	X				100.00	38	40	40	40	48	37	37	38	40	38	38	40	39	32	30	0	50	40	0
2	Evgeny Dadonov		X	X		100.00	31	87	33	42	53	31	43	32	35	32	32	46	46	37	34	0	50	39	0
3	Simon Moser		X	X		100.00	31	85	35	40	75	31	44	32	35	32	32	42	46	35	32	0	50	39	0
4	Jeremy Gregoire (R)	X				100.00	35	37	37	37	61	35	35	35	37	35	35	37	36	32	30	0	50	38	0
5	Greg Nemisz	X		X		100.00	31	89	31	35	69	31	37	32	35	32	32	33	46	37	34	0	50	37	0
6	Joshua Brown (R)				X	100.00	35	37	37	37	71	35	35	35	37	35	35	37	36	32	30	0	50	40	0
7	Teigan Zahn (R)				X	100.00	35	37	37	37	72	35	35	35	37	35	35	37	36	32	30	0	50	40	0
8	Chad Billins				X	100.00	31	85	35	39	54	31	43	32	35	32	32	35	46	35	32	0	50	38	0
9	Johan Motin				X	100.00	31	95	25	30	66	31	36	32	35	32	32	32	46	35	32	0	50	36	0

	MOYENNE D'ÉQUIPE					100.00	45	49	55	51	65	44	40	40	43	40	40	48	44	35	32	0	50	45

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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	Malcolm Subban (R)	100.00	21	45	67	75	35	46	46	35	45	95	94	37	34	0	50	48	0
2	Troy Grosenick	100.00	47	45	52	67	46	46	43	45	48	59	58	35	32	0	50	48	0
Rayé
1	Harri Sateri (R)	100.00	39	40	39	76	39	38	38	38	38	38	37	32	30	0	50	42	0

	MOYENNE D'ÉQUIPE	100.00	36	43	53	73	40	43	42	39	44	64	63	35	32	0	50	46

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Larry Robinson	54	51	62	60	99	92	70	CAN	66	2	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	Byron Froese	Bears (Was)	C	72	47	57	104	36	45	5	41	201	319	28	82	14.73%	39	1205	16.74	16	18	34	101	255	0	1	1	3	74	4	2	69.32%	1405	0	1	1.73	0	3	0	0	1	5	12	5
2	Andreas Martinsen	Bears (Was)	LW/RW	75	40	51	91	18	135	25	174	114	242	14	48	16.53%	24	1303	17.38	15	15	30	60	261	0	1	1	3	108	2	1	58.71%	155	1	0	1.40	1	2	1	1	3	5	3	6
3	Joe Morrow	Bears (Was)	D	71	22	38	60	14	74	0	173	47	155	19	30	14.19%	93	1519	21.41	13	12	25	84	257	1	0	1	4	248	2	1	0.00%	0	0	0	0.79	0	0	0	0	0	2	3	3
4	Mikhail Grigorenko	Washington	C/LW	31	28	29	57	10	4	0	10	112	153	22	59	18.30%	5	671	21.65	12	10	22	46	115	0	0	0	5	166	4	1	68.71%	962	2	2	1.70	0	2	0	0	0	8	2	1
5	Michael McCarron	Bears (Was)	C/RW	60	24	33	57	20	96	10	139	80	162	14	54	14.81%	8	905	15.09	5	13	18	40	194	0	0	0	0	2	5	1	65.03%	163	0	0	1.26	0	0	1	1	0	4	2	6
6	Phillip Di Giuseppe	Washington	LW/RW	46	21	35	56	12	45	5	58	84	167	19	54	12.57%	14	901	19.60	3	14	17	38	171	0	0	0	7	130	1	2	37.10%	62	0	0	1.24	0	3	0	1	0	1	5	3
7	Jakub Zboril	Bears (Was)	D	82	11	32	43	26	122	10	166	48	75	9	19	14.67%	51	1369	16.70	5	5	10	39	212	0	0	0	1	187	0	2	0.00%	0	0	0	0.63	0	1	0	2	0	0	2	2
8	Ryan Carpenter	Bears (Was)	C	82	14	26	40	-3	40	0	60	140	167	6	25	8.38%	19	936	11.42	0	2	2	9	28	0	0	0	0	12	3	0	52.73%	933	0	0	0.85	0	0	0	0	0	0	3	1
9	Brock Boeser	Bears (Was)	RW	82	13	24	37	1	22	0	43	106	175	10	30	7.43%	7	1017	12.41	0	2	2	6	36	0	0	0	2	59	2	0	38.82%	85	0	0	0.73	0	0	0	0	0	0	2	3
10	Mikhail Sergachev	Bears (Was)	D	82	8	26	34	28	18	0	43	50	64	7	14	12.50%	81	1395	17.01	3	7	10	36	211	0	0	0	1	207	2	1	0.00%	0	0	0	0.49	0	0	0	0	0	0	0	1
11	Emile Poirier	Bears (Was)	LW/RW	77	11	16	27	0	18	0	33	64	93	5	16	11.83%	9	621	8.08	0	0	0	2	3	0	0	0	1	13	1	2	48.84%	43	0	0	0.87	0	0	0	0	0	1	1	1
12	Oliver Bjorkstrand	Washington	RW	10	9	16	25	6	2	0	5	14	42	0	0	21.43%	2	208	20.88	3	8	11	16	26	0	0	0	0	41	0	2	51.28%	39	0	1	2.40	0	0	0	0	0	2	1	2
13	Brian O'Neill	Bears (Was)	RW	77	8	15	23	-9	4	0	21	82	84	5	14	9.52%	18	550	7.15	0	0	0	0	0	0	0	0	0	0	1	0	48.15%	27	0	0	0.84	0	0	0	0	0	0	0	1
14	Kevin Porter	Bears (Was)	C/LW/RW	77	11	12	23	-10	30	0	51	72	107	7	24	10.28%	8	785	10.20	1	0	1	4	37	0	0	0	0	3	0	0	51.65%	273	0	0	0.59	0	0	0	0	0	1	0	1
15	Shea Theodore	Bears (Was)	D	23	4	17	21	2	22	0	27	21	47	4	3	8.51%	21	485	21.10	2	8	10	20	78	0	0	0	0	92	0	0	0.00%	0	1	0	0.87	0	0	0	0	0	0	1	1
16	Madison Bowey	Bears (Was)	D	77	3	9	12	17	41	5	90	20	16	1	2	18.75%	43	895	11.63	0	0	0	1	18	0	1	1	0	62	0	1	0.00%	0	0	0	0.27	0	0	0	1	0	1	0	1
17	Mathieu Brisebois	Bears (Was)	D	77	1	10	11	16	81	15	67	9	21	2	1	4.76%	40	849	11.03	0	0	0	0	12	0	0	0	0	28	1	0	0.00%	0	0	0	0.26	0	0	0	1	2	0	0	0
18	Steven Shipley	Bears (Was)	C	55	2	7	9	3	30	0	40	25	14	1	2	14.29%	2	396	7.20	0	0	0	0	0	0	0	0	0	24	0	0	47.39%	403	0	0	0.45	0	0	0	0	0	0	0	0
19	Brycen Martin	Bears (Was)	D	69	0	6	6	-5	18	0	60	7	7	1	2	0.00%	19	462	6.70	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0.26	0	0	0	0	0	0	1	0
20	Ryan Gropp	Bears (Was)	LW	77	4	1	5	0	6	0	7	4	14	1	0	28.57%	1	134	1.75	1	0	1	6	25	1	0	1	2	50	1	0	58.33%	12	0	0	0.74	0	0	0	0	0	0	0	1
21	Joey Leach	Bears (Was)	D	69	0	4	4	-5	34	10	49	10	2	0	2	0.00%	21	461	6.69	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0.17	0	0	0	1	1	0	0	0
22	Tyler Biggs	Bears (Was)	RW	77	0	4	4	-1	0	0	8	4	20	2	6	0.00%	2	96	1.25	0	1	1	8	43	0	0	0	0	1	0	0	56.60%	53	0	0	0.83	1	1	0	0	0	0	0	0
23	Adam Janosik	Bears (Was)	D	69	0	2	2	4	2	0	5	1	8	1	0	0.00%	2	79	1.15	0	2	2	6	42	0	0	0	0	15	0	0	0.00%	0	0	0	0.50	0	0	0	0	0	0	0	0
24	Justin Weller	Bears (Was)	D	37	0	0	0	1	0	0	3	3	0	0	1	0.00%	7	65	1.77	0	0	0	0	0	0	0	0	0	64	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1554	281	470	751	181	889	85	1373	1318	2154	178	488	13.05%	536	17318	11.14	79	117	196	522	2033	2	3	5	29	1597	29	16	60.74%	4615	4	4	0.87	2	12	2	8	7	30	38	39

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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	GA	SA	A	EG	PS %	PSA	ST	BG	S2	S3
1	Malcolm Subban	Bears (Was)	82	48	23	6	0.861	3.74	4487	2	280	2014	7	0	0.500	16	82	0	1	1
2	Troy Grosenick	Bears (Was)	15	3	2	0	0.931	1.97	458	0	15	217	0	1	1.000	5	0	77	0	0
Stats d'équipe Total ou en Moyenne			97	51	25	6	0.868	3.58	4946	2	295	2231	7	1	0.619	21	82	77	1	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 Janosik	Bears (Was)	D	24	1992-09-07	Yes	170 Lbs	5 ft11	No	No	No	3	Avec Restriction	Pro & Farm	700,000$