Ligue Canadienne de Hockey Simulé

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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	Mike Hoffman (R)		X			100.00	49	36	98	81	73	82	89	85	61	90	95	76	50	75	71	34	89	78	0
2	Drew Stafford			X		100.00	55	39	88	73	78	86	87	95	73	81	76	79	75	86	74	31	90	76	0
3	Brock Nelson	X				100.00	52	37	75	76	79	83	94	83	73	71	92	80	80	78	73	64	89	76	0
4	Rene Bourque		X			100.00	87	60	53	62	78	72	71	78	42	72	85	99	81	99	99	57	92	76	0
5	Jonathan Drouin (R) (C)			X		100.00	51	35	99	85	66	81	79	76	59	83	88	69	81	68	73	62	90	74	0
6	Ryan Spooner	X				100.00	48	36	80	81	66	83	82	81	87	94	79	71	73	62	62	63	91	74	0
7	Niklas Hagman (A)		X			100.00	49	23	96	63	77	93	96	64	37	55	70	99	71	99	99	20	90	72	0
8	Dale Weise (R)	X				100.00	83	38	94	69	77	78	86	76	64	71	81	70	60	70	70	48	89	71	0
9	Michael Chaput (R)	X				100.00	59	37	74	69	76	64	70	67	85	86	68	76	68	69	67	53	84	69	0
10	Richard Panik (R)			X		100.00	71	48	75	76	74	55	79	73	61	64	73	63	73	64	65	55	90	67	0
11	Michael Bournival			X		100.00	54	36	79	73	74	68	66	69	63	65	61	71	61	70	65	63	87	65	0
12	Joseph Blandisi (R)	X				100.00	64	45	69	71	70	62	67	72	61	68	64	68	56	58	49	79	87	64	0
13	Dustin Jeffrey (R)	X				100.00	88	75	78	64	62	67	70	66	85	66	59	65	56	62	62	47	86	63	0
14	Kevin Porter (R)		X			100.00	63	37	76	72	66	56	73	65	60	57	58	69	55	74	68	46	89	63	0
15	Freddie Hamilton (R)	X				100.00	64	40	78	69	72	69	68	61	84	60	58	60	52	62	49	63	84	61	0
16	Olli Maatta (R)				X	100.00	72	40	89	86	78	79	76	85	25	83	82	92	75	65	69	46	87	78	0
17	Simon Després (R)				X	100.00	91	44	90	79	78	80	74	87	25	78	73	80	71	77	72	63	90	76	0
18	Jordie Benn (R)				X	100.00	64	40	77	74	75	69	86	99	55	84	78	87	71	77	71	48	88	76	0
19	Eric Gelinas				X	100.00	79	35	83	73	78	72	78	95	54	86	79	72	72	72	68	51	84	74	0
20	Jaccob Slavin (R)				X	100.00	54	36	89	77	76	86	87	77	25	75	60	89	90	66	66	79	91	74	0
21	Kevin Dallman				X	100.00	14	4	99	60	75	95	97	70	47	69	76	99	77	96	99	23	89	74	0
22	Zach Redmond (R)				X	100.00	69	32	91	63	78	79	77	77	51	75	72	77	71	68	69	26	88	70	0
Rayé
1	Travis Konecny (R)			X		99.64	56	39	72	83	60	52	61	67	31	64	63	58	63	52	50	95	63	61	0
2	Matt Halischuk (R)			X		100.00	75	43	68	71	56	52	68	64	60	60	59	66	50	68	69	1	25	61	0
3	Andrew Agozzino (R)		X			100.00	57	66	60	68	56	67	64	62	71	61	60	59	56	46	46	48	25	58	0
4	Martin Frk (R)			X		100.00	53	38	69	71	71	47	43	63	30	53	60	63	58	60	51	71	25	57	0
5	Kyle Rau (R)		X			100.00	48	35	76	74	56	46	51	57	41	52	54	63	56	62	51	63	25	56	0
6	Hunter Shinkaruk (R)	X				100.00	46	35	79	73	61	47	43	58	40	53	55	61	55	58	51	79	25	55	0
7	Vladimir Sobotka (R)	X				100.00	43	35	88	69	64	65	41	52	53	40	49	57	52	72	65	23	25	53	0
8	Jeff Schultz				X	87.02	46	25	99	58	84	85	88	48	21	50	45	99	48	97	89	75	84	71	0
9	Colin Miller (R)				X	100.00	66	53	86	74	76	78	85	67	25	63	56	75	54	64	64	63	39	68	0
10	Viktor Svedberg (R)				X	100.00	62	44	89	60	89	71	75	61	25	55	56	67	50	63	63	47	36	63	0

	MOYENNE D'ÉQUIPE					99.56	60	40	82	72	72	71	74	72	52	68	68	74	64	71	67	53	72	68

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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	Mike Condon (R)	100.00	79	88	83	79	82	89	87	86	94	82	84	75	74	48	90	82	0
2	Michael Hutchinson	98.00	68	76	86	79	78	89	86	94	97	80	88	88	67	44	90	81	0
Rayé
1	Juuse Saros (R)	100.00	77	58	73	61	78	79	81	83	85	79	59	56	51	87	30	72	0

	MOYENNE D'ÉQUIPE	99.33	75	74	81	73	79	86	85	88	92	80	77	73	64	60	70	78

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Todd Richards	99	88	88	98	85	69	88	USA	51	5	1,900,000$

Afficher ou Masquer des Colonnes

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	GA	TA	EG	HT	P/20	FW	FL	FT	S1	S2	S3
1	Ryan Spooner	Wild (MIN)	C	25	11	31	42	7	16	0	46	80	85	28	65	12.94%	14	548	21.96	2	14	16	17	113	0	0	0	0	32	1	0	52.90%	758	11	9	1	0	1.53	0	0	0	3	5	0
2	Mike Hoffman	Wild (MIN)	LW	25	19	17	36	9	0	0	27	35	101	28	85	18.81%	10	531	21.24	10	6	16	24	113	0	0	0	0	17	2	0	37.50%	48	28	6	0	1	1.36	0	0	0	1	3	3
3	Jonathan Drouin	Wild (MIN)	RW	25	12	13	25	7	0	0	29	38	73	20	42	16.44%	14	531	21.25	4	5	9	16	113	0	0	0	2	19	2	0	29.41%	34	11	8	0	0	0.94	0	0	0	0	1	4
4	Drew Stafford	Wild (MIN)	RW	25	14	10	24	5	2	0	26	30	101	35	66	13.86%	9	433	17.33	3	4	7	6	84	0	0	0	0	3	2	0	45.45%	22	17	3	0	0	1.11	0	0	0	3	0	3
5	Brock Nelson	Wild (MIN)	C	25	12	10	22	10	8	0	38	62	95	17	60	12.63%	10	453	18.13	2	1	3	10	84	1	0	1	1	54	4	1	49.23%	392	17	4	0	0	0.97	0	0	0	3	0	1
6	Olli Maatta	Wild (MIN)	D	25	5	13	18	8	5	5	33	45	57	24	22	8.77%	30	574	22.98	3	4	7	19	125	0	0	0	0	21	1	0	0.00%	0	15	9	0	0	0.63	0	1	0	2	0	0
7	Eric Gelinas	Wild (MIN)	D	23	3	11	14	1	12	0	45	26	37	22	20	8.11%	18	417	18.17	3	6	9	9	107	0	0	0	0	3	0	0	0.00%	0	7	6	0	0	0.67	0	0	0	0	1	1
8	Jordie Benn	Wild (MIN)	D	25	3	7	10	8	19	5	33	38	53	15	22	5.66%	30	497	19.90	1	0	1	4	72	0	0	0	0	1	1	0	0.00%	0	11	10	0	0	0.40	0	1	0	0	0	2
9	Rene Bourque	Wild (MIN)	LW	25	1	9	10	5	37	15	86	21	41	14	29	2.44%	6	385	15.43	0	2	2	3	36	0	0	0	0	3	0	0	30.00%	20	5	9	0	0	0.52	1	1	1	0	1	0
10	Simon Després	Wild (MIN)	D	25	0	8	8	5	2	0	42	39	31	19	19	0.00%	23	374	14.97	0	2	2	1	20	0	0	0	0	12	0	0	0.00%	0	6	16	0	0	0.43	0	0	0	0	0	0
11	Dale Weise	Wild (MIN)	C	25	5	3	8	1	0	0	29	18	48	16	28	10.42%	2	300	12.03	0	0	0	0	3	0	0	0	0	1	1	1	53.33%	30	4	7	0	0	0.53	0	0	0	1	0	1
12	Travis Konecny	Wild (MIN)	RW	21	4	3	7	2	6	0	21	8	41	9	18	9.76%	3	190	9.09	0	0	0	0	2	0	0	0	0	0	1	0	25.00%	4	9	1	0	0	0.73	0	0	0	0	0	1
13	Niklas Hagman	Wild (MIN)	LW	25	2	5	7	4	0	0	15	18	33	13	17	6.06%	11	317	12.69	0	0	0	0	2	0	0	0	1	59	0	0	38.10%	21	3	5	0	0	0.44	0	0	0	0	0	0
14	Zach Redmond	Wild (MIN)	D	22	0	6	6	-1	19	5	27	28	12	8	4	0.00%	16	308	14.04	0	2	2	2	65	0	0	0	0	4	0	0	0.00%	0	3	5	0	0	0.39	0	0	0	0	0	0
15	Michael Chaput	Wild (MIN)	C	22	1	5	6	0	13	5	38	36	41	8	25	2.44%	4	342	15.57	0	2	2	3	46	0	0	0	0	9	0	0	50.65%	310	1	7	0	0	0.35	0	0	1	0	0	0
16	Dustin Jeffrey	Wild (MIN)	C	25	3	3	6	2	18	10	37	22	20	6	16	15.00%	4	238	9.54	0	0	0	0	0	0	0	0	0	0	0	0	63.04%	138	1	4	0	0	0.50	0	2	0	0	1	0
17	Jaccob Slavin	Wild (MIN)	D	25	0	5	5	4	9	5	8	17	19	5	5	0.00%	26	308	12.35	0	0	0	0	7	0	0	0	0	38	0	0	0.00%	0	2	9	0	0	0.32	1	0	0	0	0	0
18	Kevin Dallman	Wild (MIN)	D	25	0	4	4	6	0	0	2	23	21	8	6	0.00%	25	350	14.01	0	0	0	0	0	0	0	0	1	62	0	0	0.00%	0	8	14	0	0	0.23	0	0	0	0	0	0
19	Joseph Blandisi	Wild (MIN)	C	25	2	1	3	2	29	5	40	20	20	5	9	10.00%	5	280	11.22	0	0	0	0	0	0	0	0	0	0	1	1	44.44%	18	2	4	0	0	0.21	0	0	0	0	0	0
20	Jeff Schultz	Wild (MIN)	D	25	0	1	1	5	4	0	10	24	14	4	5	0.00%	22	308	12.36	0	0	0	0	4	0	1	1	0	58	0	0	0.00%	0	0	7	0	0	0.06	0	0	0	0	0	0
21	Richard Panik	Wild (MIN)	RW	22	1	0	1	1	0	0	5	6	7	4	9	14.29%	2	45	2.07	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	2	6	1	0	0	0.44	0	0	0	0	1	0
22	Colin Miller	Wild (MIN)	D	3	0	1	1	2	4	0	1	2	0	1	1	0.00%	0	23	7.87	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	1	0	0	0.85	0	0	0	0	0	0
23	Viktor Svedberg	Wild (MIN)	D	8	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.11	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0	0.00	0	0	0	0	0	0
24	Michael Bournival	Wild (MIN)	RW	13	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	1	0.15	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0	0.00	0	0	0	0	0	0
25	Freddie Hamilton	Wild (MIN)	C	25	0	0	0	1	0	0	3	1	2	0	3	0.00%	0	28	1.13	0	0	0	0	0	0	0	0	0	0	0	0	52.94%	17	0	1	0	0	0.00	0	0	0	0	0	0
26	Kevin Porter	Wild (MIN)	LW	25	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	2	0.09	0	0	0	0	0	0	0	0	0	1	0	0	0.00%	0	0	0	0	0	0.00	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				584	98	166	264	94	203	55	641	637	952	309	576	10.29%	284	7797	13.35	28	48	76	114	1005	1	1	2	5	405	16	3	50.94%	1814	167	146	1	1	0.68	2	5	2	13	13	16

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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	GA	SA	SAR	A	ST	BG	S1	S2
1	Michael Hutchinson	Wild (MIN)	24	16	6	2	0.922	2.69	1496	67	862	414	1	24	1	3	4
2	Mike Condon	Wild (MIN)	2	0	0	1	0.938	2.20	82	3	48	22	0	1	24	0	0
Stats d'équipe Total ou en Moyenne			26	16	6	3	0.923	2.66	1579	70	910	436	1	25	25	3	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	CONT	Status	Type	Salaire Actuel	Salaire Année 2	Salaire Année 3
Andrew Agozzino	Wild (MIN)	LW	27	1991-01-02 04:38:16	Yes	187 Lbs	5 ft10	No	No	No	2	Avec Restriction	Pro & Farm	600,000$	600,000$
Brock Nelson	Wild (MIN)	C	25	1992-08-02 23:11:13	No	201 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	1,250,000$	1,250,000$	1,250,000$
Colin Miller	Wild (MIN)	D	25	1992-10-29 04:23:29	Yes	201 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	603,000$	603,000$
Dale Weise	Wild (MIN)	C	28	1989-08-03 05:11:13	Yes	212 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	750,000$
Drew Stafford	Wild (MIN)	RW	32	1985-08-03 05:11:13	No	212 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	900,000$
Dustin Jeffrey	Wild (MIN)	C	30	1988-02-26 04:25:12	Yes	205 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	575,000$
Eric Gelinas	Wild (MIN)	D	25	1992-08-02 23:11:13	No	213 Lbs	6 ft4	No	No	No	3	Avec Restriction	Pro & Farm	1,650,000$	1,650,000$	1,650,000$
Freddie Hamilton	Wild (MIN)	C	26	1991-12-30 04:26:42	Yes	195 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	688,000$	688,000$
Hunter Shinkaruk	Wild (MIN)	C	23	1994-10-13 08:27:39	Yes	181 Lbs	5 ft10	No	No	No	3	Avec Restriction	Pro & Farm	863,333$	863,333$	863,333$
Jaccob Slavin	Wild (MIN)	D	24	1994-05-01 12:36:34	Yes	200 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	925,000$	925,000$
Jeff Schultz (Sur la Masse Salariale)	Wild (MIN)	D	30	1987-08-03 17:11:13	No	235 Lbs	6 ft6	No	No	No	3	Avec Restriction	Pro & Farm	1,000,000$	1,000,000$	1,000,000$
Jonathan Drouin	Wild (MIN)	RW	21	1996-08-02 23:11:13	Yes	187 Lbs	6 ft1	No	No	No	1	Contrat d'Entrée	Pro & Farm	894,167$
Jordie Benn	Wild (MIN)	D	29	1988-08-02 23:11:13	Yes	200 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	700,000$
Joseph Blandisi	Wild (MIN)	C	23	1994-07-18 04:31:57	Yes	182 Lbs	5 ft11	No	No	No	2	Avec Restriction	Pro & Farm	788,000$	788,000$
Juuse Saros	Wild (MIN)	RW	23	1995-04-19 08:25:44	Yes	180 Lbs	5 ft11	No	No	No	3	Avec Restriction	Pro & Farm	692,500$	692,500$	692,500$
Kevin Dallman	Wild (MIN)	D	35	1982-08-03 11:11:13	No	208 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	2,750,000$
Kevin Porter	Wild (MIN)	LW	32	1986-03-12 04:35:02	Yes	194 Lbs	5 ft11	No	No	No	2	Sans Restriction	Pro & Farm	680,000$	680,000$
Kyle Rau	Wild (MIN)	LW	25	1992-10-24 08:23:57	Yes	178 Lbs	5 ft8	No	No	No	3	Avec Restriction	Pro & Farm	700,000$	700,000$	700,000$
Martin Frk	Wild (MIN)	RW	24	1993-10-05 08:21:53	Yes	194 Lbs	6 ft1	No	No	No	3	Avec Restriction	Pro & Farm	650,000$	650,000$	650,000$
Matt Halischuk	Wild (MIN)	RW	29	1988-05-30 04:22:00	Yes	180 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	750,000$
Michael Bournival	Wild (MIN)	RW	24	1993-08-03 05:11:13	No	203 Lbs	5 ft11	No	No	No	3	Avec Restriction	Pro & Farm	575,000$	575,000$	575,000$
Michael Chaput	Wild (MIN)	C	24	1993-08-03 05:11:13	Yes	202 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	1,000,000$	1,000,000$	1,000,000$
Michael Hutchinson	Wild (MIN)	D	26	1991-08-03 17:11:14	No	205 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	1,500,000$	1,500,000$	1,500,000$
Mike Condon	Wild (MIN)	RW	28	1990-04-26 04:16:15	Yes	196 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	575,000$	575,000$
Mike Hoffman	Wild (MIN)	LW	27	1990-08-03 11:11:13	Yes	188 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	2,000,000$	2,000,000$	2,000,000$
Niklas Hagman	Wild (MIN)	LW	37	1980-08-02 23:11:13	No	211 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	2,000,000$	2,000,000$
Olli Maatta	Wild (MIN)	D	22	1995-08-03 17:11:13	Yes	210 Lbs	6 ft2	No	No	No	1	Contrat d'Entrée	Pro & Farm	894,167$
Rene Bourque	Wild (MIN)	LW	36	1981-08-03 05:11:13	No	219 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	1,750,000$
Richard Panik	Wild (MIN)	RW	27	1991-02-07 04:14:12	Yes	208 Lbs	6 ft1	No	No	No	2	Avec Restriction	Pro & Farm	975,000$	975,000$
Ryan Spooner	Wild (MIN)	C	24	1993-08-03 05:11:13	No	185 Lbs	5 ft11	No	No	No	3	Avec Restriction	Pro & Farm	1,250,000$	1,250,000$	1,250,000$
Simon Després	Wild (MIN)	D	26	1991-08-03 17:11:13	Yes	213 Lbs	6 ft4	No	No	No	1	Avec Restriction	Pro & Farm	1,450,000$
Travis Konecny	Wild (MIN)	RW	21	1997-03-11 08:19:19	Yes	175 Lbs	5 ft10	No	No	No	3	Contrat d'Entrée	Pro & Farm	894,167$	894,167$	894,167$
Viktor Svedberg	Wild (MIN)	D	26	1991-05-24 04:12:08	Yes	238 Lbs	6 ft8	No	No	No	2	Avec Restriction	Pro & Farm	575,000$	575,000$
Vladimir Sobotka	Wild (MIN)	C	30	1987-07-02 08:12:52	Yes	197 Lbs	5 ft10	No	No	No	3	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$
Zach Redmond	Wild (MIN)	D	28	1989-08-03 05:11:13	Yes	209 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	1,000,000$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
35	26.91	200 Lbs	6 ft1	2.11	1,022,067$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mike Hoffman	Ryan Spooner	Jonathan Drouin	32	0	0	5
2	Rene Bourque	Brock Nelson	Drew Stafford	28	0	2	3
3	Dale Weise	Michael Chaput	Joseph Blandisi	22	0	3	2
4	Niklas Hagman	Dustin Jeffrey	Richard Panik	18	0	3	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Olli Maatta	Jordie Benn	30	1	2	2
2	Simon Després	Eric Gelinas	27	1	2	2
3	Jaccob Slavin	Zach Redmond	23	1	2	2
4		Kevin Dallman	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mike Hoffman	Ryan Spooner	Jonathan Drouin	60	1	1	3
2	Rene Bourque	Brock Nelson	Drew Stafford	40	1	1	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Olli Maatta	Eric Gelinas	60	1	2	2
2	Jordie Benn	Simon Després	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Brock Nelson	Niklas Hagman	60	1	2	2
2	Drew Stafford	Rene Bourque	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Kevin Dallman	60	1	2	2
2	Jaccob Slavin	Jordie Benn	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Niklas Hagman	60	1	2	2		Kevin Dallman	60	1	2	2
2	Rene Bourque	40	1	2	2	Jaccob Slavin	Olli Maatta	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Dale Weise	Drew Stafford	60	1	2	2
2	Brock Nelson	Jonathan Drouin	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Olli Maatta		60	1	2	2
2	Kevin Dallman	Jaccob Slavin	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Mike Hoffman	Ryan Spooner	Jonathan Drouin	Olli Maatta	Eric Gelinas

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Niklas Hagman	Brock Nelson	Rene Bourque		Kevin Dallman

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Niklas Hagman, Dale Weise, Brock Nelson	Brock Nelson, Dale Weise	Niklas Hagman

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Olli Maatta, Jordie Benn, Simon Després	Olli Maatta	Kevin Dallman, Jaccob Slavin

Tirs de Pénalité
Jonathan Drouin, Mike Hoffman, Brock Nelson, Rene Bourque, Drew Stafford

Gardien
#1 : Michael Hutchinson, #2 : Mike Condon

Lignes d'Attaque Perso. en Prol.
Brock Nelson, Niklas Hagman, Ryan Spooner, Dale Weise, Jonathan Drouin, , , , Dustin Jeffrey, , Joseph Blandisi

Lignes de Défense Perso. en Prol.
Kevin Dallman, , Jaccob Slavin, , Jordie Benn

Afficher ou Masquer des Colonnes

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Avalanche	5	4	1	0	0	0	0	0	27	13	14	3	3	0	0	0	0	0	0	16	6	10	2	1	1	0	0	0	0	0	11	7	4	8	0.800	27	46	73	0	0	31	29	33	5	193	343	292	271	46	175	51	83	132	35	10	28.57%	25	9	64.00%	0	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
2	Blackhawks	7	4	3	0	0	0	0	0	24	20	4	4	3	1	0	0	0	0	0	16	9	7	3	1	2	0	0	0	0	0	8	11	-3	8	0.571	24	42	66	0	0	31	29	33	5	243	343	292	271	46	245	75	76	168	38	9	23.68%	24	7	70.83%	0	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
3	Islanders	6	4	2	0	0	0	0	0	24	17	7	3	3	0	0	0	0	0	0	17	9	8	3	1	2	0	0	0	0	0	7	8	-1	8	0.667	24	41	65	0	0	31	29	33	5	227	343	292	271	46	231	76	17	168	29	6	20.69%	6	3	50.00%	1	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
4	Sharks	7	4	3	0	0	0	0	0	23	20	3	4	3	1	0	0	0	0	0	13	10	3	3	1	2	0	0	0	0	0	10	10	0	8	0.571	23	37	60	0	0	31	29	33	5	289	343	292	271	46	259	82	27	173	24	3	12.50%	11	0	100.00%	0	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
	Total	25	16	9	0	0	0	0	0	98	70	28	14	12	2	0	0	0	0	0	62	34	28	11	4	7	0	0	0	0	0	36	36	0	32	0.640	98	166	264	0	0	31	29	33	5	952	343	292	271	46	910	284	203	641	126	28	22.22%	66	19	71.21%	1	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
	_Since Last GM Reset	25	16	9	0	0	0	0	0	98	70	28	14	12	2	0	0	0	0	0	62	34	28	11	4	7	0	0	0	0	0	36	36	0	32	0.640	98	166	264	0	0	31	29	33	5	952	343	292	271	46	910	284	203	641	126	28	22.22%	66	19	71.21%	1	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
	_Vs Conference	19	12	7	0	0	0	0	0	74	53	21	11	9	2	0	0	0	0	0	45	25	20	8	3	5	0	0	0	0	0	29	28	1	24	0.632	74	125	199	0	0	31	29	33	5	725	343	292	271	46	679	208	186	473	97	22	22.68%	60	16	73.33%	0	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
	_Vs Division	12	8	4	0	0	0	0	0	51	33	18	7	6	1	0	0	0	0	0	32	15	17	5	2	3	0	0	0	0	0	19	18	1	16	0.667	51	88	139	0	0	31	29	33	5	436	343	292	271	46	420	126	159	300	73	19	26.03%	49	16	67.35%	0	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
25	32	W2	98	166	264	952	910	284	203	641	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
25	16	9	0	0	0	0	98	70

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
14	12	2	0	0	0	0	62	34

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	4	7	0	0	0	0	36	36

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	1	0	2	0	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
126	28	22.22%	66	19	71.21%	1

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
343	292	271	46	31	29	33	5

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
406	751	54.06%	322	664	48.49%	196	399	49.12%

Temps Avec la Rondelle
En Zone Offensive	Contrôle en Zone Offensive	En Zone Défensive	Contrôle en Zone Défensive	En Zone Neutre	Contrôle en Zone Neutre
610	363	522	227	448	235

Derniers Match Joués

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	RI	Lien
2 - 2017-10-01	5	Sharks	2	Wild	3	W	X		Sommaire du Match
4 - 2017-10-03	13	Sharks	4	Wild	3	L	X		Sommaire du Match
6 - 2017-10-05	21	Wild	5	Sharks	1	W			Sommaire du Match
8 - 2017-10-07	29	Wild	2	Sharks	4	L			Sommaire du Match
10 - 2017-10-09	37	Sharks	1	Wild	3	W			Sommaire du Match
12 - 2017-10-11	45	Wild	3	Sharks	5	L			Sommaire du Match
14 - 2017-10-13	53	Sharks	3	Wild	4	W	X		Sommaire du Match
16 - 2017-10-15	59	Avalanche	1	Wild	4	W		R3	Sommaire du Match
18 - 2017-10-17	63	Avalanche	2	Wild	7	W			Sommaire du Match
20 - 2017-10-19	67	Wild	6	Avalanche	1	W		R3	Sommaire du Match
22 - 2017-10-21	71	Wild	5	Avalanche	6	L			Sommaire du Match
24 - 2017-10-23	75	Avalanche	3	Wild	5	W		R3	Sommaire du Match
30 - 2017-10-29	86	Blackhawks	3	Wild	2	L			Sommaire du Match
32 - 2017-10-31	88	Blackhawks	4	Wild	5	W	X		Sommaire du Match
34 - 2017-11-02	90	Wild	2	Blackhawks	6	L			Sommaire du Match
36 - 2017-11-04	92	Wild	2	Blackhawks	3	L	X		Sommaire du Match
38 - 2017-11-06	94	Blackhawks	1	Wild	4	W			Sommaire du Match
40 - 2017-11-08	96	Wild	4	Blackhawks	2	W			Sommaire du Match
42 - 2017-11-10	98	Blackhawks	1	Wild	5	W			Sommaire du Match
43 - 2017-11-11	99	Islanders	3	Wild	4	W	X		Sommaire du Match
44 - 2017-11-12	100	Islanders	3	Wild	9	W			Sommaire du Match
45 - 2017-11-13	101	Wild	2	Islanders	3	L	X		Sommaire du Match
46 - 2017-11-14	102	Wild	2	Islanders	3	L			Sommaire du Match
47 - 2017-11-15	103	Islanders	3	Wild	4	W			Sommaire du Match
48 - 2017-11-16	104	Wild	3	Islanders	2	W	X		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	90	50
Assistance	27259	13632
Assistance PCT	97.35%	97.37%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
27	2921 - 97.36%	140,193$	1,962,703$	3000	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
3,477,234$	1,503,400$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour
0$	0$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

Afficher ou Masquer des Colonnes

	Ligue											Domicile											Visiteur
Année	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
12	25	16	9	0	0	0	0	0	98	70	28	14	12	2	0	0	0	0	0	62	34	28	11	4	7	0	0	0	0	0	36	36	0	32	98	166	264	0	0	31	29	33	5	952	343	292	271	46	910	284	203	641	126	28	22.22%	66	19	71.21%	1	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235
Total Séries	25	16	9	0	0	0	0	0	98	70	28	14	12	2	0	0	0	0	0	62	34	28	11	4	7	0	0	0	0	0	36	36	0	32	98	166	264	0	0	31	29	33	5	952	343	292	271	46	910	284	203	641	126	28	22.22%	66	19	71.21%	1	406	751	54.06%	322	664	48.49%	196	399	49.12%	610	363	522	227	448	235

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