Ligue de hockey Simulée Ste-Flanelle

Minnesota
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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	Kyle Okposo			X		100.00	55	43	82	82	75	78	92	76	46	79	73	59	73	58	50	0	90	71	0
2	Mikko Koivu (C)	X				100.00	58	35	83	75	75	81	95	74	89	78	69	68	49	66	56	0	90	71	0
3	Paul Stastny	X				100.00	53	43	84	78	71	79	82	75	89	82	68	68	42	65	55	0	90	71	0
4	Jiri Hudler		X	X		100.00	52	43	86	84	56	74	91	75	37	77	72	60	61	69	62	0	90	70	0
5	Jaden Schwartz	X	X			100.00	56	35	88	77	60	77	64	76	45	77	74	70	45	49	44	0	80	68	0
6	Charlie Coyle	X		X		100.00	74	43	88	73	76	72	95	64	80	61	67	64	60	47	41	0	90	66	0
7	Craig Smith			X		100.00	61	35	83	75	72	72	95	66	68	60	71	61	52	50	41	0	90	65	0
8	Rickard Rakell	X	X	X		100.00	61	43	88	76	70	66	77	64	78	61	67	61	53	43	40	0	90	64	0
9	David Pastrnak		X	X		100.00	57	35	86	79	49	65	60	64	35	58	69	61	42	35	32	0	86	61	0
10	Clarke MacArthur		X			100.00	55	43	83	66	66	66	47	64	41	61	67	55	45	60	52	0	90	60	0
11	J.T. Brown		X	X		100.00	61	61	78	75	52	59	64	52	48	51	52	73	48	45	42	0	86	58	0
12	William Karlsson	X	X			100.00	52	35	93	71	58	64	61	52	78	48	56	72	96	35	32	0	90	58	0
13	Travis Hamonic				X	100.00	80	61	79	68	68	83	90	56	35	59	53	83	48	52	43	0	90	69	0
14	Marco Scandella				X	100.00	73	50	84	67	70	78	88	55	35	57	53	82	48	51	45	0	91	68	0
15	Dougie Hamilton				X	100.00	68	43	81	75	70	78	94	64	35	68	59	67	45	47	40	0	90	67	0
16	Mark Streit				X	100.00	53	35	86	73	61	80	82	61	35	66	55	70	48	64	54	0	90	66	0
17	Brian Dumoulin				X	100.00	60	35	89	65	69	63	57	44	45	48	39	81	48	45	41	0	90	61	0
18	Brandon Manning				X	100.00	68	56	70	63	67	66	47	46	35	51	41	78	48	43	38	0	70	60	0
Rayé
1	Valeri Nichushkin		X	X		100.00	61	35	90	71	72	64	77	58	35	57	58	63	56	45	37	0	21	60	0
2	Chase De Leo (R)	X	X			97.64	46	35	95	79	56	50	35	35	45	35	35	57	48	35	32	0	53	48	0

	MOYENNE D'ÉQUIPE					99.85	60	42	85	74	66	71	75	61	52	62	60	68	53	50	44	0	83	64

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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	Henrik Lundqvist	100.00	84	95	97	68	87	85	87	89	83	84	92	74	64	0	83	81	0
2	Andrei Vasilevskiy	100.00	65	45	86	78	66	58	59	67	57	65	94	36	34	0	70	60	0
Rayé
1	Jonas Gustavsson	100.00	46	45	83	76	47	47	47	48	46	65	87	50	45	0	20	52	0

	MOYENNE D'ÉQUIPE	100.00	65	62	89	74	67	63	64	68	62	71	91	53	48	0	58	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Claude Julien	99	92	85	99	99	99	95	CAN	56	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	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKP	PKS	PKM	GW	GT	FO%	FOT	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Paul Stastny	Minnesota	C	84	33	59	92	16	46	0	82	166	200	0	16.50%	11	1602	19.07	10	23	33	61	377	0	0	15	5	1	55.31%	2072	0	0	1	1.15	0	0	0	0	0	7	6	6
2	Kyle Okposo	Minnesota	RW	82	32	46	78	24	42	0	114	95	260	0	12.31%	3	1596	19.47	6	16	22	63	390	0	0	7	10	2	29.75%	121	0	1	1	0.98	2	11	0	0	0	4	9	7
3	Jaden Schwartz	Minnesota	C/LW	74	37	39	76	18	36	0	81	88	251	0	14.74%	10	1521	20.56	13	12	25	73	340	0	5	160	8	6	37.50%	200	0	0	1	1.00	0	0	0	0	0	9	6	6
4	Mikko Koivu	Minnesota	C	82	26	38	64	12	60	0	101	189	217	0	11.98%	23	1699	20.73	9	13	22	55	346	0	3	325	7	2	56.11%	2315	0	0	0	0.75	0	1	0	0	0	2	5	3
5	Dougie Hamilton	Minnesota	D	82	15	48	63	21	61	5	70	62	118	0	12.71%	67	1821	22.21	6	15	21	75	378	0	1	133	0	4	0.00%	0	0	0	0	0.69	0	0	1	0	0	4	3	3
6	Travis Hamonic	Minnesota	D	82	11	46	57	22	160	30	207	82	117	0	9.40%	127	2042	24.90	7	13	20	67	375	0	0	385	1	0	0.00%	0	0	0	0	0.56	0	0	2	2	1	2	3	4
7	Jiri Hudler	Minnesota	LW/RW	82	24	30	54	7	26	0	60	98	260	0	9.23%	5	1393	16.99	9	11	20	61	326	0	0	9	3	0	34.82%	112	0	1	0	0.78	1	2	0	0	0	1	7	2
8	Mark Streit	Minnesota	D	82	7	35	42	-6	22	0	39	77	103	0	6.80%	72	1789	21.82	6	17	23	64	347	0	1	255	2	1	0.00%	0	0	0	0	0.47	0	0	0	0	0	1	2	1
9	Craig Smith	Minnesota	RW	82	14	20	34	1	46	0	77	56	133	0	10.53%	7	1295	15.80	2	6	8	39	320	0	0	1	1	3	46.39%	97	0	0	0	0.52	0	1	0	0	0	1	0	2
10	Marco Scandella	Minnesota	D	82	5	26	31	-3	179	35	174	91	104	0	4.81%	119	1867	22.78	2	8	10	58	339	0	1	323	0	0	0.00%	0	0	0	0	0.33	0	0	2	1	3	1	2	1
11	Charlie Coyle	Minnesota	C/RW	82	12	15	27	2	79	5	109	127	114	0	10.53%	7	1133	13.82	0	3	3	5	30	0	6	217	3	1	52.01%	896	0	1	0	0.48	5	11	0	0	0	0	3	0
12	Rickard Rakell	Minnesota	C/LW/RW	82	9	17	26	1	22	0	32	76	95	0	9.47%	3	935	11.41	1	2	3	8	59	0	0	0	1	0	55.28%	123	0	0	0	0.56	2	4	0	0	0	1	2	0
13	David Pastrnak	Minnesota	LW/RW	80	11	8	19	2	20	0	30	56	83	0	13.25%	7	860	10.76	1	0	1	1	19	0	0	0	2	1	23.33%	60	0	0	0	0.44	0	0	0	0	0	0	0	4
14	Brian Dumoulin	Minnesota	D	82	3	14	17	6	30	0	45	54	33	0	9.09%	100	1294	15.79	0	2	2	2	10	0	2	258	0	0	0.00%	0	0	0	0	0.26	0	0	0	0	0	1	0	1
15	William Karlsson	Minnesota	C/LW	82	7	5	12	4	8	0	16	82	46	0	15.22%	9	633	7.73	0	0	0	0	0	0	2	219	0	1	47.50%	701	0	2	0	0.38	3	11	0	0	0	1	0	1
16	Brandon Manning	Minnesota	D	70	3	7	10	14	137	35	107	47	18	0	16.67%	60	970	13.87	0	0	0	4	24	0	0	77	2	0	0.00%	0	0	0	0	0.21	0	0	0	2	5	1	0	2
17	J.T. Brown	Minnesota	LW/RW	69	5	5	10	2	45	15	51	33	43	0	11.63%	9	667	9.67	1	0	1	1	3	0	2	332	0	0	32.69%	52	0	0	0	0.30	0	0	0	2	1	2	0	1
18	Clarke MacArthur	Minnesota	LW	82	5	4	9	-9	24	0	32	26	52	0	9.62%	1	548	6.69	0	0	0	1	16	0	2	69	1	0	26.83%	41	0	0	0	0.33	0	0	0	0	0	1	0	1
19	Valeri Nichushkin	Minnesota	LW/RW	23	1	2	3	-2	2	0	11	5	15	0	6.67%	1	147	6.43	0	0	0	0	0	0	0	10	0	0	45.45%	11	0	0	0	0.41	0	1	0	0	0	0	0	0
20	Chase De Leo	Minnesota	C/LW	1	0	0	0	0	0	0	0	1	0	0	0.00%	0	2	2.78	0	0	0	0	0	0	0	0	0	0	50.00%	4	0	0	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne			1467	260	464	724	132	1045	125	1438	1511	2262	0	11.49%	641	23826	16.24	73	141	214	638	3706	0	25	2803	46	22	52.26%	6805	0	5	3	0.61	13	42	5	7	10	39	48	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	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Henrik Lundqvist	Minnesota	72	46	18	6	0.902	2.58	4251	4	3	183	1863	0	1	0	0.763	38	69	13	7	4	5
2	Andrei Vasilevskiy	Minnesota	16	9	3	0	0.879	3.35	734	4	0	41	339	0	0	0	1.000	2	13	66	1	0	0
Stats d'équipe Total ou en Moyenne		88	55	21	6	0.898	2.70	4985	8	3	224	2202	0	1	0	0.775	40	82	79	8	4	5

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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	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Link
Andrei Vasilevskiy	Minnesota	G	21	1994-07-25	No	207 Lbs	6 ft3	No	No	3	Contrat d'Entrée	Pro & Farm	925,000$	925,000$	925,000$				Lien
Brandon Manning	Minnesota	D	25	1990-06-04	No	205 Lbs	6 ft1	No	No	3	Avec Restriction	Pro & Farm	1,000,000$	1,000,000$	1,000,000$				Lien
Brian Dumoulin	Minnesota	D	24	1991-09-06	No	207 Lbs	6 ft4	No	No	2	Avec Restriction	Pro & Farm	815,000$	815,000$					Lien
Charlie Coyle	Minnesota	C/RW	23	1992-03-02	No	218 Lbs	6 ft3	No	No	1	Avec Restriction	Pro & Farm	900,000$						Lien
Chase De Leo	Minnesota	C/LW	19	1995-10-25	Yes	185 Lbs	5 ft9	No	No	4	Contrat d'Entrée	Pro & Farm	685,000$	685,000$	685,000$	685,000$			Lien
Clarke MacArthur	Minnesota	LW	30	1985-04-06	No	195 Lbs	6 ft0	No	No	4	Sans Restriction	Pro & Farm	3,700,000$	3,700,000$	3,700,000$	3,700,000$			Lien
Craig Smith	Minnesota	RW	26	1989-09-05	No	208 Lbs	6 ft1	No	No	6	Avec Restriction	Pro & Farm	3,400,000$	3,400,000$	3,400,000$	3,400,000$	3,400,000$	3,400,000$	Lien
David Pastrnak	Minnesota	LW/RW	19	1996-05-25	No	167 Lbs	6 ft0	No	No	3	Contrat d'Entrée	Pro & Farm	925,000$	925,000$	925,000$				Lien
Dougie Hamilton	Minnesota	D	22	1993-06-17	No	210 Lbs	6 ft6	No	No	1	Avec Restriction	Pro & Farm	925,000$						Lien
Henrik Lundqvist	Minnesota	G	33	1982-03-02	No	188 Lbs	6 ft1	No	No	2	Sans Restriction	Pro & Farm	6,000,000$	6,000,000$					Lien
J.T. Brown	Minnesota	LW/RW	25	1990-07-02	No	175 Lbs	5 ft10	No	No	3	Avec Restriction	Pro & Farm	900,000$	900,000$	900,000$				Lien
Jaden Schwartz	Minnesota	C/LW	23	1992-06-25	No	190 Lbs	5 ft10	No	No	5	Avec Restriction	Pro & Farm	3,750,000$	3,750,000$	3,750,000$	3,750,000$	3,750,000$		Lien
Jiri Hudler	Minnesota	LW/RW	31	1984-01-04	No	183 Lbs	5 ft10	No	No	1	Sans Restriction	Pro & Farm	3,500,000$						Lien
Jonas Gustavsson	Minnesota	G	30	1984-10-24	No	201 Lbs	6 ft4	No	No	2	Sans Restriction	Pro & Farm	1,300,000$	1,300,000$					Lien
Kyle Okposo	Minnesota	RW	27	1988-04-16	No	217 Lbs	6 ft0	No	No	6	Avec Restriction	Pro & Farm	4,250,000$	4,250,000$	4,250,000$	4,250,000$	4,250,000$	4,250,000$	Lien
Marco Scandella	Minnesota	D	25	1990-02-23	No	211 Lbs	6 ft3	No	No	3	Avec Restriction	Pro & Farm	2,700,000$	2,700,000$	2,700,000$				Lien
Mark Streit	Minnesota	D	37	1977-12-11	No	191 Lbs	5 ft11	Yes	No	1	Sans Restriction	Pro & Farm	3,500,000$						Lien
Mikko Koivu	Minnesota	C	32	1983-03-12	No	215 Lbs	6 ft3	No	No	4	Sans Restriction	Pro & Farm	4,800,000$	4,800,000$	4,800,000$	4,800,000$			Lien
Paul Stastny	Minnesota	C	29	1985-12-27	No	205 Lbs	6 ft0	No	No	4	Avec Restriction	Pro & Farm	6,000,000$	6,000,000$	6,000,000$	6,000,000$			Lien
Rickard Rakell	Minnesota	C/LW/RW	22	1993-05-05	No	201 Lbs	6 ft2	No	No	1	Avec Restriction	Pro & Farm	925,000$						Lien
Travis Hamonic	Minnesota	D	25	1990-08-16	No	205 Lbs	6 ft2	No	No	3	Avec Restriction	Pro & Farm	2,600,000$	2,600,000$	2,600,000$				Lien
Valeri Nichushkin	Minnesota	LW/RW	20	1995-03-04	No	205 Lbs	6 ft4	No	No	2	Contrat d'Entrée	Pro & Farm	925,000$	925,000$					Lien
William Karlsson	Minnesota	C/LW	22	1993-01-08	No	185 Lbs	6 ft0	No	No	3	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$				Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	25.65	199 Lbs	6 ft1	2.91	2,406,522$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
55,350,000$	45,600,000$	36,560,000$	26,585,000$	11,400,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jaden Schwartz	Paul Stastny	Kyle Okposo	35	1	1	3
2	Jiri Hudler	Mikko Koivu	Craig Smith	30	1	2	2
3	David Pastrnak	Charlie Coyle	Rickard Rakell	25	1	2	2
4	Clarke MacArthur	William Karlsson	J.T. Brown	10	1	3	1

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dougie Hamilton	Travis Hamonic	35	1	2	2
2	Marco Scandella	Mark Streit	30	1	3	1
3	Brian Dumoulin	Brandon Manning	25	1	3	1
4	Dougie Hamilton	Travis Hamonic	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jaden Schwartz	Paul Stastny	Kyle Okposo	60	1	0	4
2	Jiri Hudler	Mikko Koivu	Craig Smith	40	1	0	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Dougie Hamilton	Travis Hamonic	60	1	1	3
2	Marco Scandella	Mark Streit	40	1	1	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mikko Koivu	J.T. Brown	60	1	3	1
2	William Karlsson	Charlie Coyle	40	1	3	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Travis Hamonic	Marco Scandella	60	1	3	1
2	Brian Dumoulin	Brandon Manning	40	1	3	1

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Mikko Koivu	60	1	3	1	Travis Hamonic	Marco Scandella	60	1	3	1
2	William Karlsson	40	1	3	1	Brian Dumoulin	Brandon Manning	40	1	3	1

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Paul Stastny	Kyle Okposo	60	1	1	3
2	Mikko Koivu	Jaden Schwartz	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Travis Hamonic	Marco Scandella	60	1	2	2
2	Dougie Hamilton	Mark Streit	40	1	3	1

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jaden Schwartz	Paul Stastny	Kyle Okposo	Dougie Hamilton	Travis Hamonic

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
William Karlsson	Mikko Koivu	J.T. Brown	Marco Scandella	Travis Hamonic

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jiri Hudler, Kyle Okposo, Clarke MacArthur	Craig Smith, Mikko Koivu	Charlie Coyle

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Brian Dumoulin, Brandon Manning, Dougie Hamilton	Brian Dumoulin	Mark Streit, Dougie Hamilton

Tirs de Pénalité
William Karlsson, Kyle Okposo, Jiri Hudler, Charlie Coyle, Rickard Rakell

Gardien
#1 : Henrik Lundqvist, #2 : Andrei Vasilevskiy

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

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
Anaheim	3	2	0	0	0	0	1	0	9	6	3	2	2	0	0	0	0	0	0	6	4	2	1	0	0	0	0	0	1	0	3	2	1	6	1.000	9	15	24	0	0	3	2	3	1	85	32	27	25	4	79	20	47	55	18	2	11.11%	20	1	95.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	81	55	67	22	36	19
Atlanta	2	1	0	0	0	0	0	1	8	6	2	1	0	0	0	0	0	0	1	4	5	-1	1	1	0	0	0	0	0	0	4	1	3	3	0.750	8	15	23	0	0	5	0	3	1	56	24	14	18	4	54	12	31	31	9	0	0.00%	12	2	83.33%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	48	34	49	16	26	13
Boston	2	0	2	0	0	0	0	0	2	9	-7	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	0	6	-6	0	0.000	2	4	6	0	0	1	1	0	0	52	10	22	20	0	53	19	23	37	11	0	0.00%	8	2	75.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	48	33	46	14	24	12
Buffalo	2	1	1	0	0	0	0	0	3	3	0	1	0	1	0	0	0	0	0	0	1	-1	1	1	0	0	0	0	0	0	3	2	1	2	0.500	3	6	9	0	0	1	1	1	0	55	16	15	24	0	60	17	32	33	10	3	30.00%	15	1	93.33%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	40	25	52	16	27	12
Calgary	3	0	2	0	0	0	1	0	4	9	-5	1	0	0	0	0	0	1	0	2	1	1	2	0	2	0	0	0	0	0	2	8	-6	2	0.333	4	6	10	0	0	3	0	0	2	49	22	13	13	4	82	22	41	50	15	1	6.67%	17	3	82.35%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	74	50	70	24	39	20
Philadelphie	2	2	0	0	0	0	0	0	12	5	7	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	7	2	5	4	1.000	12	21	33	0	0	5	4	3	0	63	17	17	29	0	60	14	35	23	10	1	10.00%	15	3	80.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	46	31	48	15	25	12
Chicago	4	1	1	0	0	0	1	1	7	12	-5	2	1	0	0	0	0	1	0	5	3	2	2	0	1	0	0	0	0	1	2	9	-7	5	0.625	7	11	18	0	0	4	1	1	1	94	31	33	26	11	124	34	51	73	17	2	11.76%	23	2	91.30%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	91	61	105	31	53	26
Colorado	5	1	2	0	1	0	1	0	10	13	-3	3	0	1	0	1	0	1	0	8	9	-1	2	1	1	0	0	0	0	0	2	4	-2	6	0.600	10	18	28	0	1	2	4	2	2	132	42	47	40	6	144	45	70	87	20	3	15.00%	34	8	76.47%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	115	78	125	40	64	30
Kansas City	5	4	0	0	0	1	0	0	19	13	6	2	2	0	0	0	0	0	0	7	4	3	3	2	0	0	0	1	0	0	12	9	3	9	0.900	19	32	51	0	0	6	6	7	0	140	57	45	36	2	138	60	56	92	23	6	26.09%	26	5	80.77%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	124	85	114	38	65	32
Detroit	2	1	1	0	0	0	0	0	7	9	-2	1	1	0	0	0	0	0	0	4	1	3	1	0	1	0	0	0	0	0	3	8	-5	2	0.500	7	11	18	0	0	1	5	1	0	57	19	19	19	0	53	17	28	36	18	6	33.33%	10	2	80.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	46	30	47	16	26	12
Edmonton	3	2	1	0	0	0	0	0	10	10	0	1	1	0	0	0	0	0	0	3	1	2	2	1	1	0	0	0	0	0	7	9	-2	4	0.667	10	19	29	0	0	1	6	3	0	93	23	43	27	0	98	22	40	67	15	4	26.67%	15	3	80.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	72	49	69	22	37	18
Islanders	2	1	0	0	1	0	0	0	10	7	3	1	1	0	0	0	0	0	0	6	4	2	1	0	0	0	1	0	0	0	4	3	1	4	1.000	10	18	28	0	0	0	2	7	1	60	8	18	32	2	71	19	22	36	12	2	16.67%	11	2	81.82%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	49	33	50	15	24	11
LA Kings	3	1	2	0	0	0	0	0	4	7	-3	2	1	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	1	3	-2	2	0.333	4	8	12	0	1	1	2	1	0	71	26	25	20	0	70	29	26	51	16	1	6.25%	12	3	75.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	73	49	69	22	37	19
Hartford	2	2	0	0	0	0	0	0	10	3	7	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	4	1	3	4	1.000	10	19	29	0	0	3	5	2	0	55	19	23	13	0	54	10	21	51	14	4	28.57%	7	0	100.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	48	32	45	14	25	13
Ottawa	2	2	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	2	2	4	1.000	8	14	22	0	0	5	3	0	0	66	33	19	14	0	33	11	18	37	19	3	15.79%	8	0	100.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	52	38	42	15	24	12
Pittsburgh	2	1	1	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	4	0	4	1	0	1	0	0	0	0	0	3	4	-1	2	0.500	7	14	21	0	1	4	0	3	0	62	34	15	13	0	57	14	24	28	11	2	18.18%	10	1	90.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	51	39	48	13	20	9
Rangers	2	1	1	0	0	0	0	0	5	6	-1	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	5	9	14	0	0	2	2	1	0	34	14	10	10	0	49	15	37	34	10	3	30.00%	17	2	88.24%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	39	23	53	16	26	13
San Jose	3	2	1	0	0	0	0	0	10	7	3	2	1	1	0	0	0	0	0	5	6	-1	1	1	0	0	0	0	0	0	5	1	4	4	0.667	10	17	27	0	0	4	4	2	0	77	35	26	16	0	56	10	34	52	10	0	0.00%	15	1	93.33%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	72	49	68	23	38	19
St-Louis	5	1	2	0	0	0	1	1	12	18	-6	3	1	1	0	0	0	0	1	8	11	-3	2	0	1	0	0	0	1	0	4	7	-3	5	0.500	12	19	31	0	0	7	2	2	3	171	57	43	68	12	135	39	83	104	28	3	10.71%	30	7	76.67%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	123	84	123	39	62	32
Tampa Bay	2	2	0	0	0	0	0	0	6	3	3	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	1	2	4	1.000	6	11	17	0	0	1	4	1	0	42	11	17	14	0	53	6	18	42	7	1	14.29%	8	1	87.50%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	43	30	51	15	24	11
Toronto	2	1	0	0	0	0	1	0	12	4	8	1	1	0	0	0	0	0	0	8	1	7	1	0	0	0	0	0	1	0	4	3	1	4	1.000	12	21	33	0	0	4	5	2	2	60	17	18	24	4	57	16	21	37	14	4	28.57%	8	2	75.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	52	37	46	15	25	13
Vancouver	3	3	0	0	0	0	0	0	12	7	5	1	1	0	0	0	0	0	0	5	3	2	2	2	0	0	0	0	0	0	7	4	3	6	1.000	12	23	35	0	0	3	4	5	0	62	21	21	20	0	71	21	33	56	10	0	0.00%	10	1	90.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	67	46	76	21	35	17
Quebec	2	1	1	0	0	0	0	0	11	9	2	1	1	0	0	0	0	0	0	6	2	4	1	0	1	0	0	0	0	0	5	7	-2	2	0.500	11	17	28	0	0	2	3	6	0	45	9	16	20	0	67	23	35	27	10	1	10.00%	10	1	90.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	43	28	52	14	24	12
Winnipeg	5	1	2	0	0	1	0	1	9	20	-11	2	1	1	0	0	0	0	0	2	6	-4	3	0	1	0	0	1	0	1	7	14	-7	4	0.400	9	16	25	0	0	5	2	2	1	145	55	48	38	11	140	43	74	82	31	2	6.45%	32	5	84.38%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	125	86	114	39	66	32
Nashville	3	3	0	0	0	0	0	0	9	4	5	2	2	0	0	0	0	0	0	6	3	3	1	1	0	0	0	0	0	0	3	1	2	6	1.000	9	18	27	0	0	4	2	3	0	88	27	39	22	0	80	31	56	50	19	2	10.53%	17	1	94.12%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	80	57	64	21	35	17
Montreal	2	1	0	0	0	0	1	0	8	5	3	1	1	0	0	0	0	0	0	5	3	2	1	0	0	0	0	0	1	0	3	2	1	4	1.000	8	10	18	0	0	2	3	2	1	51	25	12	13	4	46	12	10	41	16	2	12.50%	5	1	80.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	52	35	46	17	25	13
Washington	2	1	1	0	0	0	0	0	7	8	-1	1	0	1	0	0	0	0	0	2	5	-3	1	1	0	0	0	0	0	0	5	3	2	2	0.500	7	13	20	0	0	4	0	3	0	60	24	15	21	0	51	8	12	35	14	3	21.43%	6	2	66.67%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	54	38	41	14	24	13
Caroline	2	2	0	0	0	0	0	0	11	5	6	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	5	3	2	4	1.000	11	20	31	0	0	2	3	6	0	74	24	15	35	0	47	23	22	36	17	4	23.53%	10	0	100.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	54	37	39	15	25	13
Las Vegas	5	5	0	0	0	0	0	0	25	13	12	2	2	0	0	0	0	0	0	10	6	4	3	3	0	0	0	0	0	0	15	7	8	10	1.000	25	41	66	0	0	6	8	11	0	170	54	49	67	0	120	40	74	83	29	10	34.48%	25	4	84.00%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	130	90	106	36	62	33
Vs Division	29	13	7	0	1	2	3	3	82	89	-7	14	7	3	0	1	0	2	1	40	39	1	15	6	4	0	0	2	1	2	42	50	-8	39	0.672	82	137	219	0	1	30	23	25	7	852	296	265	275	42	801	261	408	521	148	26	17.57%	170	31	81.76%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	711	487	691	225	375	187
Vs Conference	50	26	13	0	1	2	5	3	140	139	1	25	15	5	0	1	0	3	1	70	61	9	25	11	8	0	0	2	2	2	70	78	-8	69	0.690	140	243	383	0	2	49	43	42	10	1377	482	459	418	50	1337	416	685	902	251	36	14.34%	276	44	84.06%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	1233	845	1177	385	636	320
Since Last GM Reset	82	46	21	0	2	2	7	4	267	228	39	41	27	8	0	1	0	3	2	138	98	40	41	19	13	0	1	2	4	2	129	130	-1	116	0.707	267	466	733	0	3	91	84	83	15	2269	786	724	737	64	2202	652	1074	1466	453	75	16.56%	436	66	84.86%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	2006	1374	1941	632	1038	522
Total	82	46	21	0	2	2	7	4	267	228	39	41	27	8	0	1	0	3	2	138	98	40	41	19	13	0	1	2	4	2	129	130	-1	116	0.707	267	466	733	0	3	91	84	83	15	2269	786	724	737	64	2202	652	1074	1466	453	75	16.56%	436	66	84.86%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	2006	1374	1941	632	1038	522

			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
82	116	W3	267	466	733	2269	2202	652	1074	1466	0	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	46	21	2	2	7	4	267	228

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	27	8	1	0	3	2	138	98

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	19	13	1	2	4	2	129	130

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	2	0	0	1	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
453	75	16.56%	436	66	84.86%	0

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
786	724	737	64	91	84	83	15

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
1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%

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
2006	1374	1941	632	1038	522

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	SO	Lien
2 - 2016-10-13	7	Minnesota	2	St-Louis	1	W	X	X	Sommaire du Match
4 - 2016-10-15	25	Winnipeg	5	Minnesota	0	L			Sommaire du Match
7 - 2016-10-18	45	LA Kings	4	Minnesota	0	L			Sommaire du Match
9 - 2016-10-20	57	Toronto	1	Minnesota	8	W			Sommaire du Match
11 - 2016-10-22	66	Minnesota	4	Hartford	1	W			Sommaire du Match
12 - 2016-10-23	80	Minnesota	4	Islanders	3	W	X		Sommaire du Match
14 - 2016-10-25	83	Minnesota	0	Boston	6	L			Sommaire du Match
16 - 2016-10-27	98	Minnesota	3	Buffalo	2	W			Sommaire du Match
18 - 2016-10-29	117	Kansas City	2	Minnesota	3	W			Sommaire du Match
21 - 2016-11-01	133	Buffalo	1	Minnesota	0	L			Sommaire du Match
25 - 2016-11-05	161	Minnesota	0	Colorado	4	L			Sommaire du Match
30 - 2016-11-10	204	Minnesota	3	Pittsburgh	4	L			Sommaire du Match
32 - 2016-11-12	220	Minnesota	7	Philadelphie	2	W			Sommaire du Match
33 - 2016-11-13	225	Minnesota	4	Ottawa	2	W			Sommaire du Match
35 - 2016-11-15	232	Calgary	1	Minnesota	2	W	X	X	Sommaire du Match
37 - 2016-11-17	248	Boston	3	Minnesota	2	L			Sommaire du Match
39 - 2016-11-19	262	Colorado	1	Minnesota	2	W	X		Sommaire du Match
41 - 2016-11-21	280	Minnesota	4	Kansas City	2	W			Sommaire du Match
43 - 2016-11-23	293	Winnipeg	1	Minnesota	2	W			Sommaire du Match
45 - 2016-11-25	310	Pittsburgh	0	Minnesota	4	W			Sommaire du Match
46 - 2016-11-26	318	Minnesota	2	St-Louis	6	L			Sommaire du Match
49 - 2016-11-29	339	Minnesota	4	Vancouver	2	W			Sommaire du Match
52 - 2016-12-02	357	Minnesota	1	Calgary	4	L			Sommaire du Match
54 - 2016-12-04	376	Minnesota	4	Edmonton	3	W			Sommaire du Match
57 - 2016-12-07	391	Minnesota	4	Toronto	3	W	X	X	Sommaire du Match
59 - 2016-12-09	408	Edmonton	1	Minnesota	3	W			Sommaire du Match
61 - 2016-12-11	424	St-Louis	2	Minnesota	3	W			Sommaire du Match
63 - 2016-12-13	434	Quebec	2	Minnesota	6	W			Sommaire du Match
65 - 2016-12-15	450	Minnesota	3	Las Vegas	2	W			Sommaire du Match
67 - 2016-12-17	461	Nashville	1	Minnesota	3	W			Sommaire du Match
70 - 2016-12-20	488	Colorado	4	Minnesota	1	L			Sommaire du Match
72 - 2016-12-22	498	Minnesota	3	Montreal	2	W	X	X	Sommaire du Match
73 - 2016-12-23	510	Minnesota	2	Rangers	4	L			Sommaire du Match
77 - 2016-12-27	522	Minnesota	6	Las Vegas	1	W			Sommaire du Match
79 - 2016-12-29	538	Islanders	4	Minnesota	6	W			Sommaire du Match
81 - 2016-12-31	554	Atlanta	5	Minnesota	4	L	X	X	Sommaire du Match
86 - 2017-01-05	584	Minnesota	5	San Jose	1	W			Sommaire du Match
88 - 2017-01-07	602	Minnesota	1	LA Kings	3	L			Sommaire du Match
89 - 2017-01-08	608	Minnesota	3	Anaheim	2	W	X	X	Sommaire du Match
93 - 2017-01-12	628	Montreal	3	Minnesota	5	W			Sommaire du Match
95 - 2017-01-14	648	Minnesota	3	Kansas City	4	L	X		Sommaire du Match
96 - 2017-01-15	652	Minnesota	0	Chicago	6	L			Sommaire du Match
98 - 2017-01-17	667	Hartford	2	Minnesota	6	W			Sommaire du Match
100 - 2017-01-19	681	Nashville	2	Minnesota	3	W			Sommaire du Match
102 - 2017-01-21	698	Anaheim	2	Minnesota	3	W			Sommaire du Match
103 - 2017-01-22	707	Las Vegas	3	Minnesota	5	W			Sommaire du Match
105 - 2017-01-24	723	Minnesota	5	Kansas City	3	W			Sommaire du Match
107 - 2017-01-26	733	St-Louis	6	Minnesota	3	L			Sommaire du Match
112 - 2017-01-31	742	Minnesota	3	Edmonton	6	L			Sommaire du Match
113 - 2017-02-01	756	Minnesota	1	Calgary	4	L			Sommaire du Match
116 - 2017-02-04	782	Minnesota	3	Vancouver	2	W			Sommaire du Match
119 - 2017-02-07	799	Minnesota	3	Winnipeg	4	L	X	X	Sommaire du Match
120 - 2017-02-08	801	Chicago	2	Minnesota	3	W	X	X	Sommaire du Match
122 - 2017-02-10	813	Tampa Bay	2	Minnesota	3	W			Sommaire du Match
124 - 2017-02-12	829	Detroit	1	Minnesota	4	W			Sommaire du Match
126 - 2017-02-14	840	Anaheim	2	Minnesota	3	W			Sommaire du Match
128 - 2017-02-16	851	Kansas City	2	Minnesota	4	W			Sommaire du Match
130 - 2017-02-18	865	Las Vegas	3	Minnesota	5	W			Sommaire du Match
133 - 2017-02-21	889	Chicago	1	Minnesota	2	W			Sommaire du Match
139 - 2017-02-27	921	LA Kings	0	Minnesota	3	W			Sommaire du Match
140 - 2017-02-28	932	Minnesota	0	Winnipeg	5	L			Sommaire du Match
142 - 2017-03-02	940	Minnesota	4	Atlanta	1	W			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
145 - 2017-03-05	965	San Jose	3	Minnesota	4	W			Sommaire du Match
147 - 2017-03-07	977	St-Louis	3	Minnesota	2	L	X	X	Sommaire du Match
149 - 2017-03-09	993	Minnesota	3	Tampa Bay	1	W			Sommaire du Match
150 - 2017-03-10	997	Minnesota	5	Quebec	7	L			Sommaire du Match
152 - 2017-03-12	1012	Minnesota	2	Chicago	3	L	X	X	Sommaire du Match
154 - 2017-03-14	1030	Minnesota	5	Washington	3	W			Sommaire du Match
156 - 2017-03-16	1042	Minnesota	5	Caroline	3	W			Sommaire du Match
158 - 2017-03-18	1059	Rangers	2	Minnesota	3	W			Sommaire du Match
159 - 2017-03-19	1068	Minnesota	4	Winnipeg	5	L	X		Sommaire du Match
161 - 2017-03-21	1082	San Jose	3	Minnesota	1	L			Sommaire du Match
163 - 2017-03-23	1097	Philadelphie	3	Minnesota	5	W			Sommaire du Match
165 - 2017-03-25	1105	Vancouver	3	Minnesota	5	W			Sommaire du Match
166 - 2017-03-26	1119	Minnesota	3	Detroit	8	L			Sommaire du Match
168 - 2017-03-28	1133	Washington	5	Minnesota	2	L			Sommaire du Match
170 - 2017-03-30	1143	Ottawa	1	Minnesota	4	W			Sommaire du Match
172 - 2017-04-01	1158	Minnesota	6	Las Vegas	4	W			Sommaire du Match
173 - 2017-04-02	1171	Colorado	4	Minnesota	5	W	X	X	Sommaire du Match
175 - 2017-04-04	1181	Caroline	2	Minnesota	6	W			Sommaire du Match
177 - 2017-04-06	1204	Minnesota	2	Colorado	0	W			Sommaire du Match
179 - 2017-04-08	1217	Minnesota	3	Nashville	1	W			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	6000	5000	2000	4000	1000
Prix des Billets	100	60	35	20	200
Assistance	245460	204677	82000	164000	41000
Attendance PCT	99.78%	99.84%	100.00%	100.00%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
0	17979 - 99.88%	1,248,210$	51,176,620$	18000	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
55,350,000$	55,350,000$	0$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale
55,247,909$	305,801$	54,745,194$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	308,564$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	56,513,037$	88,070,733$	88,070,733$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Jiri Hudler	AGE:31	PO:0	OV:70
Jaden Schwartz	AGE:23	PO:0	OV:68
Rickard Rakell	AGE:22	PO:0	OV:64
David Pastrnak	AGE:19	PO:0	OV:61
Clarke MacArthur	AGE:30	PO:0	OV:60
Valeri Nichushkin	AGE:20	PO:0	OV:60
J.T. Brown	AGE:25	PO:0	OV:58
William Karlsson	AGE:22	PO:0	OV:58
Chris Thorburn	AGE:32	PO:0	OV:57
Chris Terry	AGE:26	PO:0	OV:56
*Chase De Leo	AGE:19	PO:0	OV:48
*Alexander Guptill	AGE:23	PO:0	OV:44
*Travis Ewanyk	AGE:22	PO:0	OV:44
*David Pope	AGE:21	PO:0	OV:42
*Martin Reway	AGE:20	PO:0	OV:41
Jan Mursak	AGE:27	PO:0	OV:40
*Julius Vahatalo	AGE:20	PO:0	OV:40
*Saku Maenalanen	AGE:21	PO:0	OV:39
Kristopher Foucault	AGE:24	PO:0	OV:38

Mikko Koivu	AGE:32	PO:0	OV:71
Paul Stastny	AGE:29	PO:0	OV:71
Jaden Schwartz	AGE:23	PO:0	OV:68
Charlie Coyle	AGE:23	PO:0	OV:66
Rickard Rakell	AGE:22	PO:0	OV:64
William Karlsson	AGE:22	PO:0	OV:58
*Chase De Leo	AGE:19	PO:0	OV:48
*Austin Czarnik	AGE:22	PO:0	OV:45
*Travis Ewanyk	AGE:22	PO:0	OV:44
Ben Maxwell	AGE:27	PO:0	OV:42
James Wright	AGE:25	PO:0	OV:41
*Martin Reway	AGE:20	PO:0	OV:41
Maxime Macenauer	AGE:26	PO:0	OV:40
*Jonny Brodzinski	AGE:22	PO:0	OV:40
*Anthony Louis	AGE:20	PO:0	OV:38

Kyle Okposo	AGE:27	PO:0	OV:71
Jiri Hudler	AGE:31	PO:0	OV:70
Charlie Coyle	AGE:23	PO:0	OV:66
Craig Smith	AGE:26	PO:0	OV:65
Rickard Rakell	AGE:22	PO:0	OV:64
David Pastrnak	AGE:19	PO:0	OV:61
Valeri Nichushkin	AGE:20	PO:0	OV:60
J.T. Brown	AGE:25	PO:0	OV:58
Chris Thorburn	AGE:32	PO:0	OV:57
Chris Terry	AGE:26	PO:0	OV:56
Jason Akeson	AGE:25	PO:0	OV:48
Peter Mueller	AGE:27	PO:0	OV:45
Jan Mursak	AGE:27	PO:0	OV:40
*Jonny Brodzinski	AGE:22	PO:0	OV:40
*Saku Maenalanen	AGE:21	PO:0	OV:39

Défense #1

Défense #2

Gardien

Travis Hamonic	AGE:25	PO:0	OV:69
Marco Scandella	AGE:25	PO:0	OV:68
Dougie Hamilton	AGE:22	PO:0	OV:67
Mark Streit	AGE:37	PO:0	OV:66
John Moore	AGE:24	PO:0	OV:61
Brian Dumoulin	AGE:24	PO:0	OV:61

Brandon Manning	AGE:25	PO:0	OV:60
Matt Dumba	AGE:21	PO:0	OV:60
*Oliver Kylington	AGE:18	PO:0	OV:51
*Miles Gendron	AGE:19	PO:0	OV:44
*Will Butcher	AGE:20	PO:0	OV:40

Henrik Lundqvist	AGE:33	PO:0	OV:81
Andrei Vasilevskiy	AGE:21	PO:0	OV:60
Jonas Gustavsson	AGE:30	PO:0	OV:52
Kevin Poulin	AGE:25	PO:0	OV:50
Niko Hovinen	AGE:27	PO:0	OV:41

Éspoirs

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

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total
Adam Fox	Minnesota	2016	41
Bobby Nardella	Minnesota	2016	191
Evgeny Svechnikov	Minnesota	2015	13
Filip Berglund	Minnesota	2016	101
Joseph Anderson	Minnesota	2016	71
Logan Brown	Minnesota	2016	11
Mathias From	Minnesota	2016	161
Travis Dermott	Minnesota	2015	64

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
2017	Min	Min	Min	Min	Min	Min
2018	Min	Min	Min	Min	Min	Min	Min
2019	Min	Min	Min	Min	Min	Min	Min
2020	Min	Min	Min	Min	Min	Min	Min
2021	Min	Min	Min	Min	Min	Min	Min

[2016-09-11 15:34:27] - Oliver Kylington was added to Minnesota.
[2016-09-29 07:31:14] - Mark Streit was added to Minnesota.
[2016-09-29 07:31:16] - TRADE : From Kansas City to Minnesota : Mark Streit (65).
[2016-09-29 07:31:16] - TRADE : From Minnesota to Kansas City : Brendan Smith (62), David Cotton (P), Otto Koivula (P).
[2016-11-12 12:09:52] - Paul Stastny was added to Minnesota.
[2016-11-12 12:09:53] - TRADE : From Kansas City to Minnesota : Paul Stastny (70).
[2016-11-12 12:09:53] - TRADE : From Minnesota to Kansas City : Calvin de Haan (63), Jordan Staal (70).
[2017-03-08 00:50:37] - New Record for Team's Most Shots (56) in 1 Game for Minnesota!

Pas de Blessure ou de Suspension.

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
Saison Régulière
2016	82	46	21	0	2	2	7	4	267	228	39	41	27	8	0	1	0	3	2	138	98	40	41	19	13	0	1	2	4	2	129	130	-1	92	267	466	733	0	3	91	84	83	15	2269	786	724	737	64	2202	652	1074	1466	453	75	16.56%	436	66	84.86%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	2006	1374	1941	632	1038	522
Total Saison Régulière	82	46	21	0	2	2	7	4	267	228	39	41	27	8	0	1	0	3	2	138	98	40	41	19	13	0	1	2	4	2	129	130	-1	92	267	466	733	0	3	91	84	83	15	2269	786	724	737	64	2202	652	1074	1466	453	75	16.56%	436	66	84.86%	0	1463	2780	52.63%	1457	2793	52.17%	658	1275	51.61%	2006	1374	1941	632	1038	522