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	Andrew Desjardins	X	X	X		100.00	68	56	84	67	67	62	71	46	68	44	48	64	45	56	51	0	50	56	0
2	William Carrier (R)		X	X		100.00	77	43	83	68	74	50	42	50	50	43	56	59	48	35	32	0	50	54	0
3	Mike Brown		X	X		100.00	78	66	60	69	70	48	45	42	74	39	44	56	47	58	50	0	50	52	0
4	Pontus Aberg (R)		X	X		100.00	52	35	88	72	66	54	36	47	45	43	50	62	48	37	34	0	50	52	0
5	Jeremy Morin		X	X		100.00	53	50	75	67	62	49	43	45	36	44	47	59	52	44	41	0	50	51	0
6	Jerry D'Amigo		X			100.00	45	35	89	66	71	49	33	39	73	37	40	71	46	37	34	0	50	50	0
7	Nick Sorensen (R)			X		100.00	49	35	85	69	57	52	35	44	45	53	35	57	48	35	32	0	50	50	0
8	Zach Senyshyn			X		100.00	50	50	50	50	68	50	50	50	50	50	50	50	50	32	30	0	50	50	0
9	Chandler Stephenson (R)	X				100.00	53	35	92	70	70	53	35	35	52	35	35	60	48	37	34	0	50	48	0
10	Scott Kosmachuk			X		100.00	47	35	87	71	57	49	33	36	35	39	33	64	47	35	32	0	50	48	0
11	Tanner Richard (R)	X				100.00	54	35	79	71	64	54	35	35	47	35	35	60	48	35	32	0	50	48	0
12	Alexander Khokhlachev	X	X			100.00	47	35	94	74	55	50	33	33	40	33	33	61	54	39	36	0	50	47	0
13	Mario Lucia (R)		X	X		100.00	43	45	45	45	61	42	42	43	45	43	43	45	44	32	30	0	50	44	0
14	Adam Tambellini (R)	X	X			100.00	41	43	43	43	51	40	40	41	43	41	41	43	42	32	30	0	50	42	0
15	Milan Kytnar	X		X		100.00	31	90	30	33	62	31	33	32	35	32	32	33	46	35	32	0	50	36	0
16	Jonathon Blum				X	100.00	46	35	86	66	60	43	31	39	35	45	32	63	46	46	40	0	50	51	0
17	Rasmus Rissanen				X	100.00	54	35	77	58	72	45	31	32	35	32	32	71	46	35	32	0	50	51	0
18	Erik Burgdoerfer				X	100.00	53	35	95	68	68	47	35	31	35	30	32	66	48	35	32	0	50	51	0
19	Jeremy Roy				X	100.00	45	45	45	45	64	45	45	45	45	45	45	45	45	32	30	0	50	46	0
20	Mark Cundari				X	100.00	31	85	35	52	62	31	49	32	35	32	32	55	46	37	34	0	50	45	0
21	Reece Scarlett (R)				X	100.00	35	37	37	37	50	35	35	35	37	35	35	37	36	32	30	0	50	38	0
Rayé
1	Maxim Kitsyn (R)		X			100.00	35	37	37	37	67	35	35	35	37	35	35	37	36	32	30	0	50	39	0
2	Dominic Toninato (R)	X				100.00	35	37	37	37	48	35	35	35	37	35	35	37	36	32	30	0	50	38	0
3	Cade Fairchild				X	100.00	31	90	30	34	52	31	34	32	35	32	32	33	46	35	32	0	50	36	0
4	Andreas Lilja				X	100.00	19	20	20	20	20	19	19	19	20	19	19	20	20	69	63	0	50	27	0

	MOYENNE D'ÉQUIPE					100.00	47	46	63	56	61	44	38	38	44	38	38	52	45	39	35	0	50	46

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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	Alex Stalock	100.00	42	45	72	68	39	47	49	36	45	95	70	46	43	0	50	51	0
2	Jean-Francois Berube (R)	100.00	40	45	62	64	40	48	51	39	45	65	45	38	35	0	50	48	0
3	David Honzik (R)	100.00	42	43	42	79	42	41	41	41	41	41	40	32	30	0	50	44	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	41	44	59	70	40	45	47	39	44	67	52	39	36	0	50	48

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Trent Yawney	66	84	71	65	89	76	75	CAN	52	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	Scott Laughton	Columbus	C/LW	57	36	66	102	23	19	5	23	180	247	0	0	14.57%	14	1055	18.52	13	22	35	74	233	0	0	0	0	5	7	2	67.56%	1344	0	1	1.93	1	1	0	0	1	9	11	1
2	William Carrier	Monsters (Clb)	LW/RW	82	40	61	101	30	75	5	178	91	322	18	55	12.42%	13	1513	18.46	9	22	31	68	327	0	0	0	0	16	8	3	47.52%	101	0	1	1.33	0	4	1	0	0	6	9	9
3	Andrew Desjardins	Monsters (Clb)	C/LW/RW	66	32	58	90	25	60	30	65	97	234	13	44	13.68%	13	1235	18.73	11	17	28	60	273	1	0	1	4	42	2	1	58.60%	157	0	0	1.46	1	3	1	0	5	7	3	5
4	Pontus Aberg	Monsters (Clb)	LW/RW	82	32	48	80	11	6	0	17	146	284	25	49	11.27%	20	1513	18.46	6	20	26	67	321	0	1	1	7	152	4	2	42.97%	263	0	0	1.06	1	1	0	0	0	2	3	6
5	Nick Schmaltz	Columbus	C/LW	52	20	37	57	5	4	0	1	132	170	0	0	11.76%	7	885	17.04	6	12	18	58	194	0	0	0	1	9	6	2	49.11%	953	0	0	1.29	2	2	0	0	0	2	2	4
6	Mike Brown	Monsters (Clb)	LW/RW	82	23	29	52	5	96	30	269	71	154	11	30	14.94%	5	1337	16.31	8	14	22	47	315	0	0	0	0	0	5	3	68.48%	92	0	0	0.78	0	0	0	2	4	4	3	4
7	Rasmus Rissanen	Monsters (Clb)	D	78	7	35	42	20	42	0	73	50	82	7	16	8.54%	85	1656	21.23	5	7	12	30	272	0	0	0	3	182	1	0	0.00%	0	0	0	0.51	0	0	0	0	0	1	0	2
8	Jeremy Morin	Monsters (Clb)	LW/RW	82	14	27	41	3	30	10	47	115	172	14	16	8.14%	13	963	11.75	1	5	6	11	61	0	0	0	2	90	0	2	39.53%	86	1	0	0.85	0	0	0	2	0	2	1	0
9	Jerry D'Amigo	Monsters (Clb)	LW	82	22	17	39	17	21	5	28	134	149	11	24	14.77%	22	1057	12.90	1	0	1	4	12	0	0	0	8	283	1	1	61.88%	564	1	0	0.74	0	0	0	0	1	4	3	0
10	Scott Kosmachuk	Monsters (Clb)	RW	82	11	28	39	20	18	0	51	100	115	10	22	9.57%	26	1030	12.57	1	2	3	3	25	0	1	1	7	273	2	1	33.33%	63	0	0	0.76	0	0	0	0	0	1	3	2
11	Jonathon Blum	Monsters (Clb)	D	76	13	24	37	34	40	0	53	50	85	4	9	15.29%	75	1521	20.02	4	6	10	44	259	0	0	0	2	181	1	0	0.00%	0	0	0	0.49	0	0	0	0	0	2	0	3
12	Jakub Kindl	Columbus	D	46	9	26	35	15	34	0	68	42	82	0	1	10.98%	42	1066	23.18	8	10	18	57	188	0	0	0	1	126	0	2	0.00%	0	0	0	0.66	0	0	0	0	0	2	0	1
13	Chandler Stephenson	Monsters (Clb)	C	82	6	27	33	11	14	0	33	140	114	7	25	5.26%	26	1202	14.66	2	5	7	19	116	0	1	1	4	203	1	0	54.44%	1071	0	0	0.55	0	0	0	0	0	0	0	1
14	Erik Burgdoerfer	Monsters (Clb)	D	76	10	23	33	24	40	0	87	51	59	5	11	16.95%	85	1487	19.57	6	3	9	25	147	0	0	0	1	204	3	0	50.00%	6	0	0	0.44	0	0	0	0	0	2	1	0
15	Zach Senyshyn	Monsters (Clb)	RW	82	17	16	33	6	67	15	104	50	122	5	20	13.93%	8	836	10.20	1	0	1	3	40	0	0	0	0	6	3	0	58.70%	46	0	0	0.79	0	0	0	1	2	2	2	1
16	Tanner Richard	Monsters (Clb)	C	82	8	17	25	10	24	0	58	96	80	3	21	10.00%	10	737	8.99	0	0	0	1	3	0	0	0	0	1	0	0	51.35%	740	0	0	0.68	0	0	0	0	0	0	0	1
17	Alexander Khokhlachev	Monsters (Clb)	C/LW	27	6	17	23	11	2	0	1	69	45	10	27	13.33%	6	476	17.66	0	4	4	15	100	0	0	0	0	3	3	0	46.07%	547	0	0	0.96	0	1	0	0	0	0	3	2
18	Teemu Pulkkinen	Columbus	LW/RW	16	10	11	21	7	0	0	7	31	74	0	0	13.51%	3	303	18.94	4	7	11	17	63	0	0	0	0	4	2	1	50.00%	16	0	0	1.39	1	1	0	0	0	2	1	2
19	Jeremy Roy	Monsters (Clb)	D	82	6	9	15	-9	94	10	137	14	31	0	8	19.35%	51	1553	18.95	2	3	5	16	277	1	0	1	2	150	1	0	0.00%	0	0	0	0.19	0	0	0	0	2	1	1	0
20	Mark Cundari	Monsters (Clb)	D	72	9	5	14	4	77	35	61	25	29	0	5	31.03%	39	1138	15.82	1	2	3	5	69	0	0	0	0	126	1	0	0.00%	0	0	0	0.25	0	0	3	0	4	0	1	3
21	Reece Scarlett	Monsters (Clb)	D	41	1	3	4	9	44	10	49	3	2	0	1	50.00%	7	701	17.11	0	0	0	0	127	0	0	0	0	34	0	0	0.00%	0	0	0	0.11	0	0	1	1	0	0	0	0
22	Milan Kytnar	Monsters (Clb)	C/RW	24	1	1	2	2	30	10	26	13	4	0	3	25.00%	0	213	8.88	0	0	0	0	1	0	0	0	0	0	0	0	42.23%	206	0	0	0.19	0	0	1	1	0	0	0	0
23	Nick Sorensen	Monsters (Clb)	RW	2	1	1	2	1	0	0	0	2	4	0	0	25.00%	0	34	17.10	0	0	0	0	6	0	0	0	0	0	0	0	0.00%	3	0	0	1.17	0	0	0	0	0	0	1	0
24	Cade Fairchild	Monsters (Clb)	D	10	0	1	1	4	10	0	17	2	1	0	0	0.00%	4	170	17.09	0	0	0	0	14	0	0	0	0	11	0	0	0.00%	0	0	0	0.12	0	0	0	0	0	0	0	0
25	Andreas Lilja	Monsters (Clb)	D	6	0	0	0	3	0	0	4	0	0	0	0	0.00%	0	96	16.11	0	0	0	0	8	0	0	0	0	4	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1469	334	587	921	291	847	165	1457	1704	2661	143	387	12.55%	574	23791	16.20	89	161	250	624	3462	2	3	5	42	2117	51	20	54.91%	6258	2	2	0.77	6	13	7	7	19	49	48	47

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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	S3
1	Alex Stalock	Monsters (Clb)	46	29	13	4	0.881	3.09	2661	4	2	137	1147	1	2	0.364	11	46	0	2	1
2	Jean-Francois Berube	Monsters (Clb)	40	23	10	1	0.876	3.19	2183	0	1	116	935	2	0	0.000	0	36	46	0	1
3	David Honzik	Monsters (Clb)	3	0	1	1	0.900	1.82	99	0	0	3	30	0	0	0.333	3	0	36	0	0
Stats d'équipe Total ou en Moyenne			89	52	24	6	0.879	3.11	4944	4	3	256	2112	3	2	0.357	14	82	82	2	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
Adam Tambellini	Monsters (Clb)	C/LW	21	1994-11-01	Yes	169 Lbs	6 ft2	No	No	No	3	Contrat d'Entrée	Pro & Farm	743,000$