Ligue de hockey Simulée Ste-Flanelle

Sound Tigers
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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	Blake Wheeler			X		100.00	62	50	79	77	80	80	95	79	37	82	75	70	57	59	49	0	35	72	0
2	Henrik Sedin (C)	X				100.00	52	43	87	80	62	78	93	76	81	84	67	63	50	82	71	0	79	72	0
3	Gabriel Landeskog		X	X		100.00	78	50	74	78	73	79	93	75	45	77	73	70	58	50	41	0	78	71	0
4	Patrick Sharp		X	X		100.00	60	43	85	78	67	77	91	75	61	77	73	61	69	79	75	0	62	71	0
5	Adam Henrique	X	X			100.00	60	43	86	76	66	79	94	69	80	64	74	79	47	51	45	0	79	69	0
6	Nathan MacKinnon (A)	X		X		100.00	57	43	86	82	66	76	86	74	81	75	72	64	69	47	37	0	79	69	0
7	Kyle Turris	X				100.00	56	35	82	75	63	80	79	74	84	74	73	63	59	57	49	0	70	68	0
8	Tomas Tatar		X	X		100.00	60	35	87	82	57	69	95	69	35	65	72	63	50	46	42	0	79	66	0
9	Joe Colborne	X	X	X		100.00	71	43	84	73	78	67	88	65	87	63	67	61	58	47	44	0	79	65	0
10	Ryan Strome	X		X		100.00	57	43	84	75	69	70	79	63	79	63	62	63	45	46	37	0	76	63	0
11	Lance Bouma	X	X	X		100.00	75	50	79	66	72	65	68	56	35	53	58	72	48	45	41	0	64	60	0
12	Cedric Paquette	X	X			100.00	78	56	75	69	69	59	54	51	83	44	58	70	48	47	41	0	79	58	0
13	Alex Pietrangelo (A)				X	100.00	62	50	87	70	69	88	92	63	35	72	53	87	45	58	51	0	79	71	0
14	Hampus Lindholm				X	100.00	60	35	83	69	68	78	94	57	35	58	55	81	48	49	39	0	78	67	0
15	Kris Russell				X	100.00	55	50	89	72	49	83	82	56	35	61	51	80	48	60	51	0	60	66	0
16	Mark Stuart				X	100.00	88	65	72	63	71	72	80	47	35	48	45	76	48	64	55	0	61	65	0
17	Rob Scuderi				X	100.00	55	50	89	64	69	69	78	45	35	49	41	78	48	76	70	0	38	64	0
18	David Schlemko				X	100.00	58	35	88	70	61	71	77	51	35	50	51	73	56	54	48	0	79	63	0
Rayé
1	Derek Dorsett		X	X		100.00	74	70	49	72	64	60	70	54	35	53	54	65	48	59	51	0	38	59	0

	MOYENNE D'ÉQUIPE					100.00	64	47	81	73	67	74	84	63	54	64	62	70	53	57	49	0	68	66

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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	Simeon Varlamov	100.00	78	88	94	79	79	77	75	79	79	71	93	47	43	0	79	74	0
2	Scott Wedgewood	100.00	52	45	75	72	53	54	54	53	54	65	70	35	32	0	70	54	0
Rayé
1	Brian Elliott	84.24	92	51	90	79	93	91	89	93	92	83	80	58	52	0	42	81	0

	MOYENNE D'ÉQUIPE	94.67	74	61	86	77	75	74	73	75	75	73	81	47	42	0	64	70

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jeff Blashill	62	91	83	63	70	78	74	USA	43	3	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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Henrik Sedin	Islanders	C	82	26	59	85	15	12	0	42	193	202	0	12.87%	3	1443	17.60	10	20	30	59	360	0	0	0	0	20	5	5	54.25%	1893	0	0	1.18	1	4	0	0	0	5	6	8
2	Gabriel Landeskog	Islanders	LW/RW	82	37	44	81	15	152	30	254	117	275	0	13.45%	13	1506	18.37	15	10	25	81	355	0	0	0	4	86	4	3	29.70%	101	0	2	1.08	0	4	1	1	4	7	5	1
3	Kyle Turris	Islanders	C	77	30	47	77	14	16	0	24	146	187	0	16.04%	7	1308	16.99	8	24	32	56	333	0	0	0	0	0	3	1	53.14%	1560	0	1	1.18	2	3	0	0	0	6	4	3
4	Blake Wheeler	Islanders	RW	73	29	41	70	-10	18	0	42	96	219	0	13.24%	12	1299	17.80	11	21	32	64	328	0	0	0	1	73	2	1	36.09%	266	0	0	1.08	2	4	0	0	0	4	4	2
5	Nathan MacKinnon	Islanders	C/RW	82	32	35	67	22	32	0	67	100	234	0	13.68%	5	1405	17.14	5	8	13	59	295	1	0	1	1	66	5	1	53.46%	159	0	1	0.95	1	4	0	0	0	4	5	6
6	Tomas Tatar	Islanders	LW/RW	82	22	43	65	16	28	0	50	98	191	0	11.52%	5	1294	15.79	9	19	28	62	272	0	0	0	0	0	7	2	26.92%	78	0	0	1.00	0	0	0	0	0	2	1	6
7	Adam Henrique	Islanders	C/LW	82	31	33	64	31	40	0	88	166	227	0	13.66%	16	1501	18.32	6	2	8	24	91	0	0	0	8	363	5	1	51.32%	947	0	0	0.85	0	1	0	0	0	2	7	2
8	Alex Pietrangelo	Islanders	D	82	14	48	62	-6	50	10	52	121	120	0	11.67%	128	2000	24.40	9	15	24	79	352	0	1	1	1	369	5	2	0.00%	0	0	0	0.62	0	0	0	1	1	2	2	2
9	Patrick Sharp	Islanders	LW/RW	86	22	31	53	6	49	5	90	84	193	0	11.40%	10	1562	18.17	4	8	12	35	309	0	1	1	6	179	2	1	48.99%	149	0	0	0.68	4	9	0	0	1	2	5	2
10	Hampus Lindholm	Islanders	D	82	14	35	49	14	135	5	147	70	103	0	13.59%	108	1822	22.22	5	12	17	45	348	0	0	0	0	241	0	1	0.00%	0	0	0	0.54	0	0	0	0	0	2	3	1
11	Kris Russell	Islanders	D	77	7	39	46	26	53	5	70	79	82	0	8.54%	83	1615	20.98	4	10	14	48	231	0	1	1	3	317	1	0	0.00%	0	0	0	0.57	0	0	0	1	0	0	0	2
12	Joe Colborne	Islanders	C/LW/RW	82	13	21	34	-4	42	0	87	75	115	0	11.30%	8	889	10.84	3	10	13	25	189	0	0	0	4	68	1	2	51.71%	526	0	0	0.76	0	1	0	0	0	1	2	3
13	David Schlemko	Islanders	D	82	5	23	28	6	46	0	88	57	78	0	6.41%	66	1614	19.69	3	8	11	44	346	0	0	0	0	154	0	0	0.00%	0	0	0	0.35	1	2	0	0	0	0	1	1
14	Ryan Strome	Islanders	C/RW	75	10	10	20	0	10	0	15	60	101	0	9.90%	5	819	10.93	0	0	0	0	2	0	0	0	2	80	3	0	49.25%	201	0	0	0.49	0	0	0	0	0	1	2	2
15	Rob Scuderi	Islanders	D	62	4	11	15	16	79	35	48	40	36	0	11.11%	68	1122	18.11	1	2	3	5	102	0	0	0	2	186	1	0	0.00%	0	0	0	0.27	0	0	0	3	4	0	0	0
16	Cedric Paquette	Islanders	C/LW	81	5	8	13	-8	54	10	101	122	57	0	8.77%	9	1035	12.78	0	0	0	0	2	1	1	2	9	335	0	0	50.44%	1253	0	0	0.25	0	0	0	1	1	1	1	0
17	Lance Bouma	Islanders	C/LW/RW	71	7	4	11	-2	50	0	61	45	67	0	10.45%	13	874	12.32	0	0	0	0	5	0	0	0	4	285	1	0	34.78%	69	0	0	0.25	0	0	0	0	0	1	2	1
18	Mark Stuart	Islanders	D	76	4	7	11	4	183	5	220	33	28	0	14.29%	64	1275	16.78	1	1	2	1	22	0	0	0	0	209	0	1	0.00%	0	0	0	0.17	0	0	0	0	0	1	0	3
19	Derek Dorsett	Islanders	LW/RW	47	1	0	1	-2	40	0	39	21	26	0	3.85%	1	390	8.30	0	0	0	0	6	0	0	0	1	134	1	0	29.73%	37	0	0	0.05	0	0	0	0	0	0	0	1
Stats d'équipe Total ou en Moyenne			1463	313	539	852	153	1089	105	1585	1723	2541	0	12.32%	624	24783	16.94	94	170	264	687	3955	2	4	6	46	3175	46	21	50.90%	7239	0	4	0.69	11	32	1	7	11	41	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	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	Simeon Varlamov	Islanders	47	23	14	6	0.900	2.71	2609	2	3	118	1178	0	3	0	0.700	10	39	42	2	2	3
2	Brian Elliott	Islanders	35	21	8	3	0.895	2.78	1940	0	0	90	855	0	2	1	0.700	10	35	22	3	1	1
3	Scott Wedgewood	Islanders	7	4	1	1	0.847	4.14	362	0	0	25	163	0	0	0	0.600	5	7	17	0	0	0
Stats d'équipe Total ou en Moyenne		89	48	23	10	0.894	2.85	4912	2	3	233	2196	0	5	1	0.680	25	81	81	5	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	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Link
Adam Henrique	Islanders	C/LW	25	1990-02-06	No	195 Lbs	6 ft0	No	No	3	Avec Restriction	Pro & Farm	3,200,000$	3,200,000$	3,200,000$				Lien
Alex Pietrangelo	Islanders	D	25	1990-01-18	No	210 Lbs	6 ft3	No	No	1	Avec Restriction	Pro & Farm	3,000,000$						Lien
Blake Wheeler	Islanders	RW	29	1986-08-31	No	225 Lbs	6 ft5	No	No	1	Avec Restriction	Pro & Farm	4,500,000$						Lien
Brian Elliott	Islanders	G	30	1985-04-09	No	209 Lbs	6 ft2	No	No	1	Sans Restriction	Pro & Farm	2,000,000$						Lien
Cedric Paquette	Islanders	C/LW	22	1993-08-13	No	199 Lbs	6 ft1	No	No	2	Avec Restriction	Pro & Farm	625,000$	625,000$					Lien
David Schlemko	Islanders	D	28	1987-05-07	No	190 Lbs	6 ft0	No	No	1	Avec Restriction	Pro & Farm	1,300,000$						Lien
Derek Dorsett	Islanders	LW/RW	28	1986-12-20	No	192 Lbs	6 ft0	No	No	1	Avec Restriction	Pro & Farm	1,500,000$						Lien
Gabriel Landeskog	Islanders	LW/RW	22	1992-11-23	No	210 Lbs	6 ft1	No	No	4	Avec Restriction	Pro & Farm	3,500,000$	3,500,000$	3,500,000$	3,500,000$			Lien
Hampus Lindholm	Islanders	D	21	1994-01-20	No	205 Lbs	6 ft3	No	No	2	Contrat d'Entrée	Pro & Farm	925,000$	925,000$					Lien
Henrik Sedin	Islanders	C	35	1980-09-26	No	188 Lbs	6 ft2	No	No	1	Sans Restriction	Pro & Farm	8,000,000$						Lien
Joe Colborne	Islanders	C/LW/RW	25	1990-01-30	No	221 Lbs	6 ft5	No	No	3	Avec Restriction	Pro & Farm	1,325,000$	1,325,000$	1,325,000$				Lien
Kris Russell	Islanders	D	28	1987-05-02	No	170 Lbs	5 ft10	No	No	4	Avec Restriction	Pro & Farm	3,600,000$	3,600,000$	3,600,000$	3,600,000$			Lien
Kyle Turris	Islanders	C	26	1989-08-14	No	190 Lbs	6 ft1	No	No	6	Avec Restriction	Pro & Farm	5,000,000$	5,000,000$	5,000,000$	5,000,000$	5,000,000$	5,000,000$	Lien
Lance Bouma	Islanders	C/LW/RW	25	1990-03-25	No	208 Lbs	6 ft2	No	No	3	Avec Restriction	Pro & Farm	1,700,000$	1,700,000$	1,700,000$				Lien
Mark Stuart	Islanders	D	31	1984-04-27	No	215 Lbs	6 ft2	No	No	2	Sans Restriction	Pro & Farm	2,500,000$	2,500,000$					Lien
Nathan MacKinnon	Islanders	C/RW	20	1995-09-01	No	195 Lbs	6 ft0	No	No	2	Contrat d'Entrée	Pro & Farm	925,000$	925,000$					Lien
Patrick Sharp	Islanders	LW/RW	33	1981-12-27	No	195 Lbs	6 ft1	No	No	1	Sans Restriction	Pro & Farm	6,300,000$						Lien
Rob Scuderi (Contrat à 1 Volet)	Islanders	D	36	1978-12-30	No	212 Lbs	6 ft1	No	No	2	Sans Restriction	Pro & Farm	2,100,000$	1,100,000$					Lien
Ryan Strome	Islanders	C/RW	22	1993-07-11	No	199 Lbs	6 ft1	No	No	2	Avec Restriction	Pro & Farm	925,000$	925,000$					Lien
Scott Wedgewood	Islanders	G	23	1992-08-14	No	195 Lbs	6 ft2	No	No	4	Avec Restriction	Pro & Farm	575,000$	575,000$	575,000$	575,000$			Lien
Simeon Varlamov	Islanders	G	27	1988-04-27	No	209 Lbs	6 ft2	No	No	1	Avec Restriction	Pro & Farm	3,000,000$						Lien
Tomas Tatar	Islanders	LW/RW	24	1990-12-01	No	185 Lbs	5 ft10	No	No	4	Avec Restriction	Pro & Farm	2,500,000$	2,500,000$	2,500,000$	2,500,000$			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
22	26.59	201 Lbs	6 ft1	2.32	2,681,818$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
59,000,000$	28,400,000$	21,400,000$	15,175,000$	5,000,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Adam Henrique	Kyle Turris	Nathan MacKinnon	32	0	3	2
2	Gabriel Landeskog	Henrik Sedin	Blake Wheeler	32	0	1	4
3	Patrick Sharp	Ryan Strome	Tomas Tatar	26	0	2	3
4	Cedric Paquette	Joe Colborne	Lance Bouma	10	0	4	1

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Mark Stuart	32	0	3	2
2	Kris Russell	Hampus Lindholm	32	0	3	2
3	David Schlemko	Rob Scuderi	32	0	3	2
4	Alex Pietrangelo	Hampus Lindholm	4	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Gabriel Landeskog	Henrik Sedin	Blake Wheeler	50	0	1	4
2	Patrick Sharp	Kyle Turris	Nathan MacKinnon	50	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Hampus Lindholm	50	0	2	3
2	David Schlemko	Rob Scuderi	50	0	2	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Adam Henrique	Lance Bouma	50	0	5	0
2	Cedric Paquette	Joe Colborne	50	0	5	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Hampus Lindholm	50	0	5	0
2	Kris Russell	Mark Stuart	50	0	5	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Adam Henrique	50	0	5	0	Alex Pietrangelo	Hampus Lindholm	50	0	5	0
2	Cedric Paquette	50	0	5	0	Kris Russell	Mark Stuart	50	0	5	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Joe Colborne	Ryan Strome	50	0	1	4
2	Cedric Paquette	Patrick Sharp	50	0	1	4

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Pietrangelo	Hampus Lindholm	50	0	3	2
2	Mark Stuart	Rob Scuderi	50	0	3	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Gabriel Landeskog	Henrik Sedin	Blake Wheeler	Alex Pietrangelo	Kris Russell

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Gabriel Landeskog	Adam Henrique	Lance Bouma	Alex Pietrangelo	Hampus Lindholm

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Patrick Sharp, Tomas Tatar, Joe Colborne	Patrick Sharp, Nathan MacKinnon	Joe Colborne

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
David Schlemko, Rob Scuderi, Kris Russell	Kris Russell	Mark Stuart, David Schlemko

Tirs de Pénalité
Henrik Sedin, Blake Wheeler, Gabriel Landeskog, Patrick Sharp, Adam Henrique

Gardien
#1 : Simeon Varlamov, #2 : Scott Wedgewood

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	2	1	0	0	1	0	0	0	5	3	2	1	1	0	0	0	0	0	0	3	2	1	1	0	0	0	1	0	0	0	2	1	1	4	1.000	5	10	15	0	0	3	1	0	1	66	25	26	14	1	56	18	41	33	10	2	20.00%	12	1	91.67%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	51	34	43	15	24	12
Atlanta	4	1	1	0	0	1	0	1	16	15	1	2	1	0	0	0	0	0	1	8	5	3	2	0	1	0	0	1	0	0	8	10	-2	4	0.500	16	27	43	0	0	6	1	9	1	108	32	32	40	7	104	36	64	74	20	5	25.00%	24	5	79.17%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	89	57	101	32	54	26
Boston	3	3	0	0	0	0	0	0	9	4	5	1	1	0	0	0	0	0	0	3	2	1	2	2	0	0	0	0	0	0	6	2	4	6	1.000	9	18	27	0	1	6	2	1	0	79	44	21	14	0	79	27	24	52	18	3	16.67%	10	1	90.00%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	74	52	66	22	38	19
Buffalo	3	1	1	0	0	1	0	0	6	6	0	1	0	0	0	0	1	0	0	2	3	-1	2	1	1	0	0	0	0	0	4	3	1	3	0.500	6	10	16	0	0	1	3	2	0	83	28	30	24	1	65	15	41	69	14	3	21.43%	17	1	94.12%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	75	51	69	24	37	18
Calgary	2	1	1	0	0	0	0	0	8	9	-1	1	1	0	0	0	0	0	0	7	5	2	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	8	14	22	0	0	3	3	2	0	60	25	14	21	0	85	27	28	33	14	3	21.43%	14	6	57.14%	1	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	45	30	50	15	24	12
Philadelphie	4	2	2	0	0	0	0	0	11	11	0	2	1	1	0	0	0	0	0	6	5	1	2	1	1	0	0	0	0	0	5	6	-1	4	0.500	11	19	30	0	0	3	6	2	0	96	27	30	39	0	108	32	43	93	18	3	16.67%	17	4	76.47%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	87	60	102	30	49	24
Chicago	2	1	0	0	1	0	0	0	11	7	4	1	1	0	0	0	0	0	0	6	3	3	1	0	0	0	1	0	0	0	5	4	1	4	1.000	11	19	30	0	0	4	3	3	1	71	24	19	22	6	59	29	23	39	12	3	25.00%	8	3	62.50%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	48	33	49	15	26	13
Colorado	2	0	2	0	0	0	0	0	4	10	-6	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	4	6	10	0	0	1	2	1	0	44	20	10	14	0	64	21	35	35	8	1	12.50%	13	1	92.31%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	47	32	46	15	25	12
Kansas City	2	1	1	0	0	0	0	0	6	8	-2	1	1	0	0	0	0	0	0	4	3	1	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	6	10	16	0	0	1	2	3	0	57	18	15	24	0	72	19	36	32	9	1	11.11%	18	3	83.33%	1	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	46	31	47	15	25	12
Detroit	3	2	0	0	0	0	0	1	11	10	1	1	0	0	0	0	0	0	1	3	4	-1	2	2	0	0	0	0	0	0	8	6	2	5	0.833	11	17	28	0	0	2	5	4	1	69	23	16	27	6	97	23	59	72	13	5	38.46%	22	2	90.91%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	66	43	79	24	38	17
Edmonton	2	1	0	0	0	1	0	0	9	6	3	1	1	0	0	0	0	0	0	6	2	4	1	0	0	0	0	1	0	0	3	4	-1	3	0.750	9	17	26	0	0	6	1	2	0	51	21	12	16	2	60	15	28	49	12	4	33.33%	9	2	77.78%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	49	33	47	15	25	11
LA Kings	2	2	0	0	0	0	0	0	9	3	6	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	4	0	4	4	1.000	9	16	25	0	1	4	3	2	0	77	25	25	27	0	52	10	20	37	14	4	28.57%	5	0	100.00%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	52	37	40	15	26	13
Minnesota	2	0	1	0	0	1	0	0	7	10	-3	1	0	0	0	0	1	0	0	3	4	-1	1	0	1	0	0	0	0	0	4	6	-2	1	0.250	7	12	19	0	0	1	3	3	0	71	24	25	21	1	60	16	24	43	11	2	18.18%	12	2	83.33%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	50	35	49	15	24	12
Hartford	4	1	3	0	0	0	0	0	13	14	-1	2	1	1	0	0	0	0	0	10	8	2	2	0	2	0	0	0	0	0	3	6	-3	2	0.250	13	23	36	0	0	5	4	4	0	105	36	21	48	0	114	36	75	57	17	3	17.65%	34	5	85.29%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	89	60	99	32	50	24
Ottawa	3	2	0	0	0	0	0	1	9	7	2	2	1	0	0	0	0	0	1	4	4	0	1	1	0	0	0	0	0	0	5	3	2	5	0.833	9	17	26	0	0	3	2	4	0	83	28	24	31	2	65	20	45	57	20	1	5.00%	19	2	89.47%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	78	54	70	23	35	17
Pittsburgh	4	2	0	0	2	0	0	0	15	9	6	2	2	0	0	0	0	0	0	6	2	4	2	0	0	0	2	0	0	0	9	7	2	8	1.000	15	26	41	0	0	7	4	2	2	135	37	48	45	5	116	36	58	93	24	6	25.00%	22	4	81.82%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	99	67	92	30	52	26
Rangers	4	1	3	0	0	0	0	0	12	14	-2	2	1	1	0	0	0	0	0	10	9	1	2	0	2	0	0	0	0	0	2	5	-3	2	0.250	12	18	30	0	0	5	4	3	0	126	38	50	38	0	90	17	36	71	30	2	6.67%	18	3	83.33%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	105	74	86	29	48	24
San Jose	2	2	0	0	0	0	0	0	9	4	5	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	5	2	3	4	1.000	9	18	27	0	0	2	4	3	0	55	14	16	25	0	46	5	32	34	11	4	36.36%	15	1	93.33%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	51	35	44	15	24	12
St-Louis	2	1	1	0	0	0	0	0	6	8	-2	1	1	0	0	0	0	0	0	5	2	3	1	0	1	0	0	0	0	0	1	6	-5	2	0.500	6	9	15	0	0	3	1	2	0	44	17	8	19	0	43	16	22	39	10	3	30.00%	11	2	81.82%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	47	32	46	15	25	12
Tampa Bay	3	0	3	0	0	0	0	0	5	9	-4	2	0	2	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	5	9	14	1	0	1	1	3	0	74	10	33	31	0	80	22	41	58	14	2	14.29%	17	1	94.12%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	63	41	78	23	38	18
Toronto	3	2	0	0	0	0	0	1	13	8	5	2	2	0	0	0	0	0	0	10	4	6	1	0	0	0	0	0	0	1	3	4	-1	5	0.833	13	25	38	0	0	7	3	3	0	101	38	31	29	7	77	18	20	48	18	3	16.67%	10	1	90.00%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	84	60	62	22	37	19
Vancouver	2	2	0	0	0	0	0	0	9	4	5	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	4	2	2	4	1.000	9	14	23	0	0	3	4	2	0	48	9	18	21	0	39	12	20	37	10	3	30.00%	10	0	100.00%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	46	30	47	15	25	12
Quebec	3	1	1	0	0	0	1	0	8	7	1	1	0	0	0	0	0	1	0	4	3	1	2	1	1	0	0	0	0	0	4	4	0	4	0.667	8	13	21	0	0	2	4	1	1	77	27	26	24	2	83	22	46	58	23	2	8.70%	21	2	90.48%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	71	46	75	24	38	19
Winnipeg	2	1	0	0	0	1	0	0	11	4	7	1	0	0	0	0	1	0	0	2	3	-1	1	1	0	0	0	0	0	0	9	1	8	3	0.750	11	19	30	0	0	3	5	3	0	55	14	25	14	2	62	16	28	45	9	3	33.33%	14	2	85.71%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	49	32	47	16	26	13
Nashville	2	1	1	0	0	0	0	0	9	9	0	1	1	0	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	4	5	-1	2	0.500	9	16	25	0	0	4	5	0	0	50	20	21	9	0	62	23	18	46	10	1	10.00%	8	3	62.50%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	43	28	50	15	25	13
Montreal	3	2	0	0	0	0	1	0	13	9	4	2	2	0	0	0	0	0	0	8	5	3	1	0	0	0	0	0	1	0	5	4	1	6	1.000	13	21	34	0	0	4	3	5	2	94	38	24	29	5	98	26	33	52	18	3	16.67%	13	3	76.92%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	71	48	75	23	38	18
Washington	5	3	2	0	0	0	0	0	16	15	1	3	1	2	0	0	0	0	0	7	11	-4	2	2	0	0	0	0	0	0	9	4	5	6	0.600	16	28	44	0	1	4	7	5	0	171	48	71	52	0	137	26	68	84	24	5	20.83%	28	3	89.29%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	126	87	108	36	65	33
Caroline	5	3	1	0	0	0	1	0	17	11	6	2	2	0	0	0	0	0	0	6	3	3	3	1	1	0	0	0	1	0	11	8	3	8	0.800	17	30	47	0	0	6	5	5	2	153	45	43	64	8	109	29	58	103	29	4	13.79%	24	3	87.50%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	129	90	112	37	63	32
Las Vegas	2	1	0	0	0	1	0	0	11	8	3	1	0	0	0	0	1	0	0	4	5	-1	1	1	0	0	0	0	0	0	7	3	4	3	0.750	11	21	32	0	0	5	3	3	0	60	26	16	18	0	56	10	24	29	12	2	16.67%	10	0	100.00%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	52	35	42	15	26	14
Vs Division	30	13	12	0	2	1	1	1	100	89	11	15	9	5	0	0	0	0	1	53	43	10	15	4	7	0	2	1	1	0	47	46	1	34	0.567	100	171	271	0	1	36	31	30	5	894	263	295	326	20	778	212	402	575	162	28	17.28%	167	27	83.83%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	727	498	703	229	383	192
Vs Conference	54	26	17	0	2	2	3	4	174	149	25	27	15	7	0	0	1	1	3	90	74	16	27	11	10	0	2	1	2	1	84	75	9	68	0.630	174	301	475	1	2	62	54	53	9	1554	499	500	535	43	1422	385	711	1041	300	50	16.67%	296	40	86.49%	0	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	1312	898	1282	416	687	342
Since Last GM Reset	82	41	24	0	4	6	3	4	288	242	46	41	25	8	0	0	4	1	3	150	118	32	41	16	16	0	4	2	2	1	138	124	14	106	0.646	288	502	790	1	3	105	94	82	11	2363	781	750	800	55	2238	622	1090	1572	452	86	19.03%	455	66	85.49%	2	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	1994	1361	1937	633	1045	523
Total	82	41	24	0	4	6	3	4	288	242	46	41	25	8	0	0	4	1	3	150	118	32	41	16	16	0	4	2	2	1	138	124	14	106	0.646	288	502	790	1	3	105	94	82	11	2363	781	750	800	55	2238	622	1090	1572	452	86	19.03%	455	66	85.49%	2	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	1994	1361	1937	633	1045	523

			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	106	SOL1	288	502	790	2363	2238	622	1090	1572	1	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	41	24	4	6	3	4	288	242

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	25	8	0	4	1	3	150	118

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	16	16	4	2	2	1	138	124

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
5	2	1	1	0	1

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
452	86	19.03%	455	66	85.49%	2

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
781	750	800	55	105	94	82	11

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
1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%

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
1994	1361	1937	633	1045	523

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	11	Islanders	1	Rangers	2	L			Sommaire du Match
4 - 2016-10-15	23	Islanders	5	Washington	4	W			Sommaire du Match
5 - 2016-10-16	30	Anaheim	2	Islanders	3	W			Sommaire du Match
7 - 2016-10-18	39	San Jose	2	Islanders	4	W			Sommaire du Match
10 - 2016-10-21	62	Nashville	4	Islanders	5	W			Sommaire du Match
12 - 2016-10-23	80	Minnesota	4	Islanders	3	L	X		Sommaire du Match
15 - 2016-10-26	97	Montreal	4	Islanders	5	W			Sommaire du Match
16 - 2016-10-27	100	Islanders	6	Pittsburgh	5	W	X		Sommaire du Match
19 - 2016-10-30	126	Toronto	2	Islanders	5	W			Sommaire du Match
21 - 2016-11-01	139	Tampa Bay	3	Islanders	2	L			Sommaire du Match
23 - 2016-11-03	150	Philadelphie	3	Islanders	2	L			Sommaire du Match
25 - 2016-11-05	167	Edmonton	2	Islanders	6	W			Sommaire du Match
27 - 2016-11-07	181	Vancouver	2	Islanders	5	W			Sommaire du Match
30 - 2016-11-10	198	Islanders	2	Tampa Bay	3	L			Sommaire du Match
32 - 2016-11-12	218	Islanders	3	Quebec	2	W			Sommaire du Match
34 - 2016-11-14	229	Tampa Bay	3	Islanders	1	L			Sommaire du Match
38 - 2016-11-18	255	Pittsburgh	1	Islanders	2	W			Sommaire du Match
42 - 2016-11-22	284	Islanders	2	Anaheim	1	W	X		Sommaire du Match
43 - 2016-11-23	298	Islanders	4	LA Kings	0	W			Sommaire du Match
45 - 2016-11-25	312	Islanders	5	San Jose	2	W			Sommaire du Match
48 - 2016-11-28	328	Calgary	5	Islanders	7	W			Sommaire du Match
50 - 2016-11-30	343	Pittsburgh	1	Islanders	4	W			Sommaire du Match
51 - 2016-12-01	348	Islanders	4	Washington	0	W			Sommaire du Match
54 - 2016-12-04	372	Detroit	4	Islanders	3	L	X	X	Sommaire du Match
56 - 2016-12-06	382	Rangers	3	Islanders	6	W			Sommaire du Match
58 - 2016-12-08	396	St-Louis	2	Islanders	5	W			Sommaire du Match
60 - 2016-12-10	413	Islanders	2	Atlanta	3	L			Sommaire du Match
63 - 2016-12-13	438	Washington	4	Islanders	1	L			Sommaire du Match
65 - 2016-12-15	446	Chicago	3	Islanders	6	W			Sommaire du Match
66 - 2016-12-16	459	Islanders	4	Buffalo	1	W			Sommaire du Match
68 - 2016-12-18	470	Ottawa	1	Islanders	2	W			Sommaire du Match
70 - 2016-12-20	481	Islanders	1	Boston	0	W			Sommaire du Match
73 - 2016-12-23	509	Buffalo	3	Islanders	2	L	X		Sommaire du Match
77 - 2016-12-27	518	Washington	3	Islanders	4	W			Sommaire du Match
79 - 2016-12-29	538	Islanders	4	Minnesota	6	L			Sommaire du Match
81 - 2016-12-31	557	Islanders	9	Winnipeg	1	W			Sommaire du Match
87 - 2017-01-06	588	Islanders	3	Colorado	6	L			Sommaire du Match
88 - 2017-01-07	597	Islanders	4	Nashville	5	L			Sommaire du Match
92 - 2017-01-11	620	Quebec	3	Islanders	4	W	X	X	Sommaire du Match
94 - 2017-01-13	636	Islanders	1	Quebec	2	L			Sommaire du Match
95 - 2017-01-14	646	Islanders	3	Caroline	2	W	X	X	Sommaire du Match
97 - 2017-01-16	656	Islanders	5	Boston	2	W			Sommaire du Match
100 - 2017-01-19	677	Kansas City	3	Islanders	4	W			Sommaire du Match
102 - 2017-01-21	694	LA Kings	3	Islanders	5	W			Sommaire du Match
103 - 2017-01-22	705	Philadelphie	2	Islanders	4	W			Sommaire du Match
105 - 2017-01-24	716	Atlanta	2	Islanders	6	W			Sommaire du Match
107 - 2017-01-26	740	Montreal	1	Islanders	3	W			Sommaire du Match
112 - 2017-01-31	746	Washington	4	Islanders	2	L			Sommaire du Match
115 - 2017-02-03	768	Islanders	4	Detroit	3	W			Sommaire du Match
116 - 2017-02-04	777	Caroline	1	Islanders	3	W			Sommaire du Match
118 - 2017-02-06	789	Toronto	2	Islanders	5	W			Sommaire du Match
121 - 2017-02-09	809	Islanders	2	Philadelphie	5	L			Sommaire du Match
123 - 2017-02-11	816	Islanders	5	Ottawa	3	W			Sommaire du Match
124 - 2017-02-12	830	Colorado	4	Islanders	1	L			Sommaire du Match
126 - 2017-02-14	838	Islanders	3	Toronto	4	L	X	X	Sommaire du Match
128 - 2017-02-16	848	Rangers	6	Islanders	4	L			Sommaire du Match
130 - 2017-02-18	861	Islanders	1	Hartford	3	L			Sommaire du Match
131 - 2017-02-19	870	Hartford	3	Islanders	2	L			Sommaire du Match
133 - 2017-02-21	886	Islanders	4	Detroit	3	W			Sommaire du Match
135 - 2017-02-23	895	Islanders	5	Montreal	4	W	X	X	Sommaire du Match
137 - 2017-02-25	910	Islanders	6	Atlanta	7	L	X		Sommaire du Match
142 - 2017-03-02	943	Islanders	2	Kansas City	5	L			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2017-03-03	951	Islanders	5	Chicago	4	W	X		Sommaire du Match
145 - 2017-03-05	962	Islanders	1	Calgary	4	L			Sommaire du Match
147 - 2017-03-07	979	Islanders	3	Edmonton	4	L	X		Sommaire du Match
149 - 2017-03-09	988	Islanders	4	Vancouver	2	W			Sommaire du Match
151 - 2017-03-11	1009	Islanders	1	St-Louis	6	L			Sommaire du Match
153 - 2017-03-13	1016	Caroline	2	Islanders	3	W			Sommaire du Match
154 - 2017-03-14	1031	Islanders	3	Caroline	5	L			Sommaire du Match
156 - 2017-03-16	1040	Winnipeg	3	Islanders	2	L	X		Sommaire du Match
158 - 2017-03-18	1054	Atlanta	3	Islanders	2	L	X	X	Sommaire du Match
162 - 2017-03-22	1086	Islanders	1	Rangers	3	L			Sommaire du Match
164 - 2017-03-24	1101	Islanders	3	Pittsburgh	2	W	X		Sommaire du Match
165 - 2017-03-25	1110	Boston	2	Islanders	3	W			Sommaire du Match
167 - 2017-03-27	1125	Las Vegas	5	Islanders	4	L	X		Sommaire du Match
170 - 2017-03-30	1147	Islanders	3	Philadelphie	1	W			Sommaire du Match
171 - 2017-03-31	1151	Hartford	5	Islanders	8	W			Sommaire du Match
173 - 2017-04-02	1166	Islanders	0	Buffalo	2	L			Sommaire du Match
175 - 2017-04-04	1180	Islanders	7	Las Vegas	3	W			Sommaire du Match
177 - 2017-04-06	1199	Islanders	5	Caroline	1	W			Sommaire du Match
179 - 2017-04-08	1210	Islanders	2	Hartford	3	L			Sommaire du Match
180 - 2017-04-09	1221	Ottawa	3	Islanders	2	L	X	X	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	6500	5000	2000	4000	1000
Prix des Billets	95	65	40	30	400
Assistance	261877	204732	82000	162329	29839
Attendance PCT	98.27%	99.87%	100.00%	98.98%	72.78%

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	18068 - 97.66%	1,421,253$	58,271,365$	18500	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
59,000,000$	58,800,000$	0$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale
53,936,042$	325,967$	53,433,267$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	328,729$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	56,042,425$	125,512,715$	125,512,715$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Gabriel Landeskog	AGE:22	PO:0	OV:71
Patrick Sharp	AGE:33	PO:0	OV:71
Adam Henrique	AGE:25	PO:0	OV:69
Tomas Tatar	AGE:24	PO:0	OV:66
Joe Colborne	AGE:25	PO:0	OV:65
Lance Bouma	AGE:25	PO:0	OV:60
Derek Dorsett	AGE:28	PO:0	OV:59
Marko Dano	AGE:20	PO:0	OV:58
Cedric Paquette	AGE:22	PO:0	OV:58
Mattias Janmark	AGE:22	PO:0	OV:58
Richard Panik	AGE:24	PO:0	OV:57
Micheal Ferland	AGE:23	PO:0	OV:56
Jordan Schroeder	AGE:25	PO:0	OV:54
Tomas Vincour	AGE:24	PO:0	OV:51
Eric Selleck	AGE:27	PO:0	OV:47
Dominik Uher	AGE:22	PO:0	OV:46
*Peter Cehlarik	AGE:20	PO:0	OV:44
Mattias Tedenby	AGE:25	PO:0	OV:41

Henrik Sedin	AGE:35	PO:0	OV:72
Adam Henrique	AGE:25	PO:0	OV:69
Nathan MacKinnon	AGE:20	PO:0	OV:69
Kyle Turris	AGE:26	PO:0	OV:68
Joe Colborne	AGE:25	PO:0	OV:65
Ryan Strome	AGE:22	PO:0	OV:63
Lance Bouma	AGE:25	PO:0	OV:60
Cedric Paquette	AGE:22	PO:0	OV:58
Mattias Janmark	AGE:22	PO:0	OV:58
Markus Granlund	AGE:22	PO:0	OV:57
Jordan Schroeder	AGE:25	PO:0	OV:54
Zac Dalpe	AGE:25	PO:0	OV:54
Dominik Uher	AGE:22	PO:0	OV:46
*Blake Coleman	AGE:23	PO:0	OV:44
*Brayden Point	AGE:19	PO:0	OV:43
*Tony Cameranesi	AGE:22	PO:0	OV:38

Blake Wheeler	AGE:29	PO:0	OV:72
Gabriel Landeskog	AGE:22	PO:0	OV:71
Patrick Sharp	AGE:33	PO:0	OV:71
Nathan MacKinnon	AGE:20	PO:0	OV:69
Tomas Tatar	AGE:24	PO:0	OV:66
Joe Colborne	AGE:25	PO:0	OV:65
Ryan Strome	AGE:22	PO:0	OV:63
Lance Bouma	AGE:25	PO:0	OV:60
Derek Dorsett	AGE:28	PO:0	OV:59
Alex Chiasson	AGE:25	PO:0	OV:58
Marko Dano	AGE:20	PO:0	OV:58
Richard Panik	AGE:24	PO:0	OV:57
Micheal Ferland	AGE:23	PO:0	OV:56
Seth Griffith	AGE:22	PO:0	OV:55
Jordan Schroeder	AGE:25	PO:0	OV:54
Zac Dalpe	AGE:25	PO:0	OV:54
Tomas Vincour	AGE:24	PO:0	OV:51
*Martin Frk	AGE:21	PO:0	OV:46

Défense #1

Défense #2

Gardien

Alex Pietrangelo	AGE:25	PO:0	OV:71
Hampus Lindholm	AGE:21	PO:0	OV:67
Kris Russell	AGE:28	PO:0	OV:66
Mark Stuart	AGE:31	PO:0	OV:65
Rob Scuderi	AGE:36	PO:0	OV:64
David Schlemko	AGE:28	PO:0	OV:63
Ladislav Smid	AGE:29	PO:0	OV:56
Aaron Ness	AGE:25	PO:0	OV:54

*Petter Granberg	AGE:23	PO:0	OV:54
Duncan Siemens	AGE:22	PO:0	OV:51
*Samuel Morin	AGE:20	PO:0	OV:50
*Jordan Schmaltz	AGE:21	PO:0	OV:49
*Julius Bergman	AGE:19	PO:0	OV:45
*Brenden Kichton	AGE:23	PO:0	OV:39
Ryan Sproul	AGE:22	PO:0	OV:39

Brian Elliott	AGE:30	PO:0	OV:81
Simeon Varlamov	AGE:27	PO:0	OV:74
Scott Wedgewood	AGE:23	PO:0	OV:54
Kristers Gudlevskis	AGE:23	PO:0	OV:53

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
Carl Grundstrom	Islanders	2016	76
Denis Malgin	Islanders	2015	79
Evan Smith	Islanders	2015	199
Jake Kupsky	Islanders	2015	169
Robin Kovacs	Islanders	2015	109
Veeti Vainio	Islanders	2015	139
Wade Allison	Islanders	2016	40

Choix au Repêchage

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

[2016-09-25 19:26:00] - TRADE : From Islanders to Las Vegas : Tyler Cuma (39).
[2016-12-23 20:00:22] - New Record for Team's Most Hits (34) in 1 Game for Islanders!
[2017-02-02 20:56:14] - Patrick Sharp was added to Islanders.
[2017-02-02 20:56:15] - TRADE : From Islanders to Anaheim : Jordan Weal (48), Y:2017-RND:1-Isl, Y:2017-RND:6-Isl.
[2017-02-02 20:56:15] - TRADE : From Anaheim to Islanders : Patrick Sharp (71).
[2017-02-02 20:56:50] - Blake Wheeler was added to Islanders.
[2017-02-02 20:56:51] - TRADE : From Islanders to Toronto : Sebastien Aho (45), Kieffer Bellows (P), Y:2018-RND:1-Isl, Y:2018-RND:3-Isl.
[2017-02-02 20:56:51] - TRADE : From Toronto to Islanders : Blake Wheeler (72).
[2017-03-03 20:00:21] - New Record for Team's Most Shots Blocked (17) in 1 Game for Islanders!
[2017-03-05 20:00:16] - New Record for Team's Most Shots Blocked (18) in 1 Game for Islanders!

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	41	24	0	4	6	3	4	288	242	46	41	25	8	0	0	4	1	3	150	118	32	41	16	16	0	4	2	2	1	138	124	14	82	288	502	790	1	3	105	94	82	11	2363	781	750	800	55	2238	622	1090	1572	452	86	19.03%	455	66	85.49%	2	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	1994	1361	1937	633	1045	523
Total Saison Régulière	82	41	24	0	4	6	3	4	288	242	46	41	25	8	0	0	4	1	3	150	118	32	41	16	16	0	4	2	2	1	138	124	14	82	288	502	790	1	3	105	94	82	11	2363	781	750	800	55	2238	622	1090	1572	452	86	19.03%	455	66	85.49%	2	1486	2868	51.81%	1424	2798	50.89%	678	1329	51.02%	1994	1361	1937	633	1045	523