Ligue de hockey Simulée Ste-Flanelle

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Joueur	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP
1	Matt Duchene (C)	X	X	X		100.00	58	43	87	82	68	79	93	77	86	77	76	64	49	55	45	0	87	71	0
2	Sean Monahan	X				100.00	55	35	89	78	68	77	94	76	83	77	74	67	52	48	38	0	86	70	0
3	Brian Gionta (A)			X		100.00	51	35	89	84	52	77	93	67	56	66	68	72	50	79	72	0	84	69	0
4	Patric Hornqvist		X	X		100.00	65	35	83	80	60	76	93	73	36	73	73	65	56	60	54	0	83	69	0
5	Matt Cullen	X	X			100.00	50	35	88	73	69	69	92	65	89	65	65	71	53	87	80	0	81	68	0
6	Sean Couturier	X				100.00	56	50	84	72	74	76	84	68	82	70	65	76	50	51	42	0	80	67	0
7	Mark Letestu	X				100.00	54	43	92	74	66	68	90	57	84	53	60	73	53	53	46	0	85	63	0
8	Patrik Berglund	X	X			97.72	60	35	86	67	75	71	69	61	83	54	67	69	64	61	51	0	66	63	0
9	Jay Beagle	X		X		100.00	59	35	85	67	73	64	61	57	91	52	61	72	45	57	51	0	76	61	0
10	Josh Jooris	X		X		100.00	58	43	81	70	55	63	67	57	80	55	58	74	53	36	33	0	77	60	0
11	Melker Karlsson		X	X		100.00	60	35	87	72	55	64	71	58	43	52	63	75	53	37	35	0	57	60	0
12	Jordan Martinook	X	X			100.00	54	35	89	71	69	62	58	53	58	52	54	77	48	35	32	0	71	59	0
13	Duncan Keith (A)				X	100.00	59	43	86	76	62	87	88	67	35	75	58	89	48	75	70	0	70	73	0
14	Niklas Hjalmarsson				X	100.00	63	50	84	67	65	80	95	52	35	58	45	89	48	68	66	0	86	70	0
15	Braydon Coburn				X	100.00	76	56	80	60	78	74	88	46	35	47	45	80	48	73	64	0	84	67	0
16	Josh Gorges				X	100.00	71	50	76	64	67	75	78	46	35	48	43	86	48	69	59	0	84	66	0
17	Tobias Enstrom				X	100.00	54	50	81	70	54	79	82	54	35	58	49	78	48	54	44	0	68	64	0
18	Alex Petrovic				X	100.00	77	66	66	65	69	67	57	50	35	55	45	79	48	41	38	0	81	62	0
Rayé
1	Torrey Mitchell	X	X	X		100.00	57	43	79	73	62	64	78	54	84	48	60	70	48	63	54	0	53	61	0

	MOYENNE D'ÉQUIPE					99.84	60	43	84	72	65	72	81	60	61	60	59	75	51	58	51	0	77	65

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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	Corey Crawford	100.00	87	91	96	82	89	92	92	90	92	75	87	60	59	0	84	83	0
2	Joonas Korpisalo	100.00	66	45	94	67	69	63	71	72	55	65	94	35	32	0	72	62	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	77	68	95	75	79	78	82	81	74	70	91	48	46	0	78	73

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Mike Babcock	90	88	86	95	99	99	93	CAN	53	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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Matt Duchene	Pittsburgh	C/LW/RW	81	40	44	84	28	32	0	85	98	291	0	13.75%	3	1591	19.65	10	20	30	85	385	1	0	1	4	82	9	2	56.29%	167	0	0	1	1.06	3	5	0	0	0	8	10	4
2	Sean Monahan	Pittsburgh	C	82	34	44	78	16	28	0	65	160	245	0	13.88%	9	1457	17.78	11	18	29	80	376	0	0	0	0	0	8	3	51.40%	1825	0	0	0	1.07	1	1	0	0	0	8	5	8
3	Patric Hornqvist	Pittsburgh	LW/RW	81	32	39	71	23	117	5	158	96	245	0	13.06%	9	1471	18.17	12	12	24	64	388	0	0	0	0	3	7	1	26.21%	103	0	1	0	0.96	1	5	0	0	0	9	5	3
4	Duncan Keith	Pittsburgh	D	68	22	43	65	0	30	0	46	114	134	0	16.42%	102	1727	25.41	18	19	37	104	327	0	0	0	0	295	3	2	0.00%	0	0	0	1	0.75	0	0	0	0	0	5	3	4
5	Brian Gionta	Pittsburgh	RW	81	26	33	59	2	28	0	53	135	250	0	10.40%	11	1287	15.89	11	19	30	82	331	0	0	0	0	2	2	3	48.28%	87	0	0	0	0.92	0	0	0	0	0	4	3	3
6	Matt Cullen	Pittsburgh	C/LW	81	11	32	43	10	14	0	39	132	159	0	6.92%	4	1371	16.93	3	15	18	34	322	1	0	1	2	9	4	0	54.19%	1395	0	0	0	0.63	0	5	0	0	0	1	1	4
7	Niklas Hjalmarsson	Pittsburgh	D	80	8	28	36	3	61	15	87	84	89	0	8.99%	107	1879	23.49	6	6	12	56	293	0	2	2	0	323	3	0	0.00%	0	0	0	0	0.38	0	0	1	2	0	1	2	2
8	Sean Couturier	Pittsburgh	C	70	16	15	31	9	24	0	58	148	127	0	12.60%	10	1135	16.22	0	0	0	1	5	0	0	0	6	348	3	2	51.87%	1521	0	1	0	0.55	0	0	0	0	0	2	2	3
9	Patrik Berglund	Pittsburgh	C/LW	75	9	19	28	3	56	0	96	39	116	0	7.76%	6	1144	15.26	4	10	14	39	298	0	0	0	0	0	2	1	49.00%	249	0	0	0	0.49	1	1	0	0	0	1	3	1
10	Tobias Enstrom	Pittsburgh	D	50	3	23	26	5	10	0	15	33	57	0	5.26%	34	932	18.64	3	9	12	33	249	0	0	0	0	10	1	0	0.00%	0	0	0	0	0.56	0	0	0	0	0	0	0	1
11	Jay Beagle	Pittsburgh	C/RW	73	9	15	24	11	24	0	48	100	110	0	8.18%	9	1022	14.01	0	4	4	8	75	0	0	0	5	202	3	0	57.01%	549	0	0	0	0.47	0	0	0	0	0	0	5	1
12	Josh Gorges	Pittsburgh	D	82	3	20	23	9	139	25	149	55	36	0	8.33%	105	1521	18.56	1	0	1	2	15	0	1	1	1	321	0	0	0.00%	0	0	0	0	0.30	0	0	0	1	3	0	0	0
13	Melker Karlsson	Pittsburgh	LW/RW	81	10	12	22	6	22	0	60	74	94	0	10.64%	10	1007	12.44	0	2	2	4	35	1	0	1	2	136	0	0	30.99%	71	0	0	0	0.44	1	2	0	0	0	0	2	4
14	Alex Petrovic	Pittsburgh	D	73	1	20	21	17	142	20	102	56	63	0	1.59%	58	1321	18.10	0	5	5	35	313	0	0	0	0	132	1	0	0.00%	0	0	0	0	0.32	0	0	2	0	2	0	1	2
15	Braydon Coburn	Pittsburgh	D	79	5	16	21	14	141	35	124	50	45	0	11.11%	81	1666	21.09	2	4	6	21	252	0	0	0	3	272	1	0	0.00%	0	0	0	0	0.25	0	0	2	1	4	1	1	1
16	Mark Letestu	Pittsburgh	C	81	4	11	15	-4	16	0	16	96	90	0	4.44%	4	805	9.94	0	1	1	5	29	0	0	0	1	182	1	0	51.08%	834	0	0	0	0.37	1	1	0	0	0	0	0	1
17	Torrey Mitchell	Pittsburgh	C/LW/RW	62	7	8	15	-7	18	0	44	60	89	0	7.87%	6	738	11.91	2	3	5	21	94	0	0	0	1	63	2	0	54.55%	165	0	0	0	0.41	0	0	0	0	0	0	0	2
18	Jordan Martinook	Pittsburgh	C/LW	78	4	8	12	4	18	0	27	42	48	0	8.33%	17	791	10.14	0	0	0	0	4	0	0	0	5	286	2	0	25.45%	55	0	1	0	0.30	0	0	0	0	0	0	1	3
19	Josh Jooris	Pittsburgh	C/RW	74	6	6	12	5	18	0	51	56	55	0	10.91%	10	694	9.39	1	0	1	2	10	0	0	0	1	196	0	0	53.57%	336	0	0	0	0.35	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne			1432	250	436	686	154	938	100	1323	1628	2343	0	10.67%	595	23567	16.46	84	147	231	676	3811	3	3	6	31	2871	52	14	51.83%	7357	0	3	2	0.58	8	20	5	4	9	40	44	47

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Corey Crawford	Pittsburgh	67	45	15	5	0.915	2.11	3978	6	4	140	1638	0	3	0	0.706	17	64	17	8	8	2
2	Joonas Korpisalo	Pittsburgh	19	6	9	2	0.859	3.64	957	0	1	58	412	0	0	0	0.000	3	18	64	0	1	0
Stats d'équipe Total ou en Moyenne		86	51	24	7	0.903	2.41	4936	6	5	198	2050	0	3	0	0.600	20	82	81	8	9	2

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Astuces sur les Filtres (Anglais seulement)

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Link
Alex Petrovic	Pittsburgh	D	23	1992-03-03	No	206 Lbs	6 ft4	No	No	1	Avec Restriction	Pro & Farm	760,000$						Lien
Braydon Coburn	Pittsburgh	D	30	1985-02-27	No	226 Lbs	6 ft5	No	No	3	Sans Restriction	Pro & Farm	3,200,000$	3,200,000$	3,200,000$				Lien
Brian Gionta (Contrat à 1 Volet)	Pittsburgh	RW	36	1979-01-18	No	178 Lbs	5 ft7	No	No	1	Sans Restriction	Pro & Farm	3,500,000$						Lien
Corey Crawford	Pittsburgh	G	30	1984-12-31	No	216 Lbs	6 ft2	Yes	No	6	Sans Restriction	Pro & Farm	4,000,000$	5,000,000$	6,500,000$	6,500,000$	5,000,000$	4,000,000$	Lien
Duncan Keith	Pittsburgh	D	32	1983-07-16	No	192 Lbs	6 ft1	No	No	4	Sans Restriction	Pro & Farm	7,200,000$	7,200,000$	7,200,000$	7,200,000$			Lien
Jay Beagle	Pittsburgh	C/RW	29	1985-10-16	No	210 Lbs	6 ft3	No	No	1	Avec Restriction	Pro & Farm	750,000$						Lien
Joonas Korpisalo	Pittsburgh	G	21	1994-04-28	No	182 Lbs	6 ft3	No	No	4	Contrat d'Entrée	Pro & Farm	743,000$	743,000$	743,000$	743,000$			Lien
Jordan Martinook	Pittsburgh	C/LW	23	1992-07-25	No	202 Lbs	6 ft0	No	No	3	Avec Restriction	Pro & Farm	733,000$	733,000$	733,000$				Lien
Josh Gorges	Pittsburgh	D	31	1984-08-14	No	203 Lbs	6 ft1	Yes	No	4	Sans Restriction	Pro & Farm	3,900,000$	3,900,000$	2,800,000$	2,600,000$			Lien
Josh Jooris	Pittsburgh	C/RW	25	1990-07-14	No	180 Lbs	6 ft0	No	No	3	Avec Restriction	Pro & Farm	925,000$	925,000$	925,000$				Lien
Mark Letestu	Pittsburgh	C	30	1985-02-04	No	197 Lbs	5 ft10	No	No	1	Sans Restriction	Pro & Farm	1,900,000$						Lien
Matt Cullen (Contrat à 1 Volet)	Pittsburgh	C/LW	38	1976-11-02	No	200 Lbs	6 ft1	No	No	1	Sans Restriction	Pro & Farm	2,500,000$						Lien
Matt Duchene	Pittsburgh	C/LW/RW	24	1991-01-16	No	200 Lbs	5 ft11	No	No	2	Avec Restriction	Pro & Farm	5,000,000$	5,000,000$					Lien
Melker Karlsson	Pittsburgh	LW/RW	25	1990-07-18	No	180 Lbs	6 ft0	No	No	3	Avec Restriction	Pro & Farm	825,000$	825,000$	825,000$				Lien
Niklas Hjalmarsson	Pittsburgh	D	28	1987-06-06	No	197 Lbs	6 ft3	Yes	No	2	Avec Restriction	Pro & Farm	2,500,000$	2,500,000$					Lien
Patric Hornqvist	Pittsburgh	LW/RW	28	1987-01-01	No	189 Lbs	5 ft11	No	No	1	Avec Restriction	Pro & Farm	2,500,000$						Lien
Patrik Berglund	Pittsburgh	C/LW	27	1988-06-02	No	217 Lbs	6 ft3	No	No	1	Avec Restriction	Pro & Farm	1,999,999$						Lien
Sean Couturier	Pittsburgh	C	22	1992-12-07	No	211 Lbs	6 ft3	No	No	4	Avec Restriction	Pro & Farm	1,800,000$	2,000,000$	2,300,000$	2,500,000$			Lien
Sean Monahan	Pittsburgh	C	20	1994-10-12	No	195 Lbs	6 ft3	No	No	2	Contrat d'Entrée	Pro & Farm	925,000$	925,000$					Lien
Tobias Enstrom (Sur la Masse Salariale)	Pittsburgh	D	30	1984-11-05	No	180 Lbs	5 ft10	No	No	1	Sans Restriction	Pro & Farm	4,300,000$						Lien
Torrey Mitchell	Pittsburgh	C/LW/RW	30	1985-01-30	No	191 Lbs	5 ft11	No	No	6	Sans Restriction	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	1,000,000$	1,000,000$	1,000,000$	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
21	27.71	198 Lbs	6 ft1	2.57	2,426,714$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
50,960,999$	33,951,000$	26,226,000$	20,543,000$	6,000,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Duchene	Matt Cullen	Patric Hornqvist	40	1	2	2
2	Patrik Berglund	Sean Monahan	Brian Gionta	30	1	2	2
3	Melker Karlsson	Sean Couturier	Jay Beagle	20	1	2	2
4	Jordan Martinook	Mark Letestu	Josh Jooris	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Duncan Keith	Niklas Hjalmarsson	40	1	2	2
2	Braydon Coburn	Tobias Enstrom	30	1	2	2
3	Josh Gorges	Alex Petrovic	20	1	2	2
4	Duncan Keith	Braydon Coburn	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matt Duchene	Sean Monahan	Patric Hornqvist	60	1	2	2
2	Patrik Berglund	Matt Cullen	Brian Gionta	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Duncan Keith	Alex Petrovic	60	1	2	2
2	Braydon Coburn	Tobias Enstrom	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sean Couturier	Jordan Martinook	60	1	2	2
2	Jay Beagle	Josh Jooris	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Josh Gorges	Niklas Hjalmarsson	60	1	2	2
2	Duncan Keith	Braydon Coburn	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Sean Couturier	60	1	2	2	Braydon Coburn	Niklas Hjalmarsson	60	1	2	2
2	Jay Beagle	40	1	2	2	Josh Gorges	Duncan Keith	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sean Monahan	Matt Duchene	60	1	2	2
2	Matt Cullen	Patric Hornqvist	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Duncan Keith	Niklas Hjalmarsson	60	1	2	2
2	Braydon Coburn	Josh Gorges	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matt Duchene	Sean Monahan	Patric Hornqvist	Duncan Keith	Tobias Enstrom

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jordan Martinook	Jay Beagle	Josh Jooris	Josh Gorges	Niklas Hjalmarsson

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Matt Cullen, Melker Karlsson, Jay Beagle	Mark Letestu, Matt Cullen	Jordan Martinook

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Alex Petrovic, Josh Gorges, Tobias Enstrom	Tobias Enstrom	Alex Petrovic, Duncan Keith

Tirs de Pénalité
Patric Hornqvist, Matt Cullen, Melker Karlsson, Sean Monahan, Patrik Berglund

Gardien
#1 : Corey Crawford, #2 : Joonas Korpisalo

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	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	2	5	-3	1	1	0	0	0	0	0	0	2	1	1	2	0.500	4	8	12	0	0	1	1	2	0	55	21	19	15	0	40	14	22	41	13	2	15.38%	10	3	70.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	53	38	41	14	24	13
Atlanta	4	3	1	0	0	0	0	0	9	7	2	2	2	0	0	0	0	0	0	5	2	3	2	1	1	0	0	0	0	0	4	5	-1	6	0.750	9	15	24	0	1	5	1	3	0	120	38	34	48	0	96	38	35	64	21	1	4.76%	14	0	100.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	99	70	93	30	47	22
Boston	3	2	1	0	0	0	0	0	6	5	1	2	1	1	0	0	0	0	0	4	4	0	1	1	0	0	0	0	0	0	2	1	1	4	0.667	6	11	17	0	0	4	2	0	0	84	26	35	23	0	94	34	49	51	19	4	21.05%	12	1	91.67%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	79	55	63	22	36	19
Buffalo	3	2	0	0	0	1	0	0	11	9	2	1	1	0	0	0	0	0	0	4	3	1	2	1	0	0	0	1	0	0	7	6	1	5	0.833	11	15	26	0	0	6	2	3	0	76	25	25	26	0	78	17	38	41	15	2	13.33%	19	2	89.47%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	73	49	70	24	40	19
Calgary	2	1	0	0	1	0	0	0	9	5	4	1	0	0	0	1	0	0	0	3	2	1	1	1	0	0	0	0	0	0	6	3	3	4	1.000	9	15	24	0	0	5	0	3	1	44	16	10	17	1	37	16	29	35	7	1	14.29%	12	2	83.33%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	47	31	50	16	26	13
Philadelphie	4	3	0	0	0	1	0	0	12	7	5	2	2	0	0	0	0	0	0	6	2	4	2	1	0	0	0	1	0	0	6	5	1	7	0.875	12	19	31	0	0	4	6	2	0	97	30	40	27	0	78	21	35	63	25	0	0.00%	14	2	85.71%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	99	66	86	32	54	27
Chicago	2	0	2	0	0	0	0	0	3	8	-5	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	1	5	-4	0	0.000	3	5	8	0	0	2	1	0	0	59	20	15	24	0	56	22	48	35	10	2	20.00%	15	4	73.33%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	48	33	47	15	24	12
Colorado	2	0	2	0	0	0	0	0	2	9	-7	1	0	1	0	0	0	0	0	1	5	-4	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	2	4	6	0	0	0	2	0	0	44	13	21	10	0	56	14	28	37	12	1	8.33%	13	3	76.92%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	47	31	46	14	25	13
Kansas City	2	2	0	0	0	0	0	0	8	2	6	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	1	3	4	1.000	8	14	22	0	0	2	3	3	0	55	16	13	26	0	63	20	24	25	13	5	38.46%	11	1	90.91%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	45	30	48	16	26	12
Detroit	3	3	0	0	0	0	0	0	7	3	4	2	2	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	3	1	2	6	1.000	7	13	20	0	1	3	3	1	0	81	22	31	28	0	70	18	39	55	17	2	11.76%	15	1	93.33%	1	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	71	48	68	23	39	19
Edmonton	2	2	0	0	0	0	0	0	7	4	3	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	2	1	1	4	1.000	7	12	19	0	0	4	3	0	0	57	19	27	11	0	65	18	24	38	10	5	50.00%	10	0	100.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	44	29	49	15	25	12
Islanders	4	0	2	0	0	2	0	0	9	15	-6	2	0	0	0	0	2	0	0	7	9	-2	2	0	2	0	0	0	0	0	2	6	-4	2	0.250	9	15	24	0	0	4	3	2	0	116	43	24	46	3	135	30	62	76	22	4	18.18%	24	6	75.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	92	61	99	31	52	25
LA Kings	2	2	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	2	0	2	4	1.000	6	10	16	0	1	2	0	4	0	50	24	8	18	0	41	18	29	29	12	1	8.33%	12	0	100.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	50	34	44	15	24	12
Minnesota	2	1	1	0	0	0	0	0	4	7	-3	1	1	0	0	0	0	0	0	4	3	1	1	0	1	0	0	0	0	0	0	4	-4	2	0.500	4	7	11	0	0	1	2	1	0	57	23	15	19	0	62	25	26	33	10	1	10.00%	11	2	81.82%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	48	34	51	12	20	10
Hartford	5	2	0	0	0	0	2	1	21	14	7	3	0	0	0	0	0	2	1	10	9	1	2	2	0	0	0	0	0	0	11	5	6	9	0.900	21	31	52	0	0	6	4	9	6	155	44	47	57	20	124	27	59	83	36	9	25.00%	24	5	79.17%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	131	88	115	41	68	34
Ottawa	3	1	2	0	0	0	0	0	7	6	1	1	0	1	0	0	0	0	0	1	3	-2	2	1	1	0	0	0	0	0	6	3	3	2	0.333	7	12	19	0	1	3	2	2	0	70	24	26	20	0	59	32	30	56	17	4	23.53%	15	3	80.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	71	47	72	23	36	18
Rangers	5	2	3	0	0	0	0	0	11	13	-2	2	1	1	0	0	0	0	0	4	4	0	3	1	2	0	0	0	0	0	7	9	-2	4	0.400	11	20	31	0	0	4	6	1	0	127	34	50	43	0	134	46	52	75	24	1	4.17%	26	2	92.31%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	122	82	115	39	62	30
San Jose	2	2	0	0	0	0	0	0	12	4	8	1	1	0	0	0	0	0	0	5	1	4	1	1	0	0	0	0	0	0	7	3	4	4	1.000	12	20	32	0	0	8	2	2	0	38	19	8	11	0	63	12	28	31	5	2	40.00%	14	1	92.86%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	45	30	48	14	25	13
St-Louis	2	0	1	0	0	1	0	0	3	5	-2	1	0	0	0	0	1	0	0	2	3	-1	1	0	1	0	0	0	0	0	1	2	-1	1	0.250	3	6	9	0	0	1	2	0	0	63	19	22	22	0	49	10	19	22	15	1	6.67%	7	2	71.43%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	51	35	44	14	24	13
Tampa Bay	3	1	2	0	0	0	0	0	7	10	-3	2	1	1	0	0	0	0	0	6	6	0	1	0	1	0	0	0	0	0	1	4	-3	2	0.333	7	14	21	0	0	4	3	0	0	86	27	22	37	0	77	21	30	62	14	1	7.14%	15	5	66.67%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	72	49	70	21	36	18
Toronto	3	2	1	0	0	0	0	0	8	8	0	1	1	0	0	0	0	0	0	3	2	1	2	1	1	0	0	0	0	0	5	6	-1	4	0.667	8	14	22	0	0	2	4	2	0	90	25	39	26	0	94	30	37	56	10	3	30.00%	16	4	75.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	68	45	73	23	38	18
Vancouver	2	0	1	0	0	0	1	0	7	8	-1	1	0	0	0	0	0	1	0	4	3	1	1	0	1	0	0	0	0	0	3	5	-2	2	0.500	7	11	18	0	0	1	4	1	1	52	15	22	12	5	57	21	41	42	7	2	28.57%	12	4	66.67%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	45	30	54	16	25	11
Quebec	3	2	1	0	0	0	0	0	11	6	5	2	1	1	0	0	0	0	0	5	4	1	1	1	0	0	0	0	0	0	6	2	4	4	0.667	11	19	30	0	1	5	1	5	0	87	41	23	23	0	58	12	32	40	18	4	22.22%	16	3	81.25%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	75	51	64	22	40	20
Winnipeg	2	2	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	4	1	3	4	1.000	7	11	18	0	0	3	2	2	0	66	20	21	25	0	55	7	28	31	13	3	23.08%	14	1	92.86%	1	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	51	34	42	16	25	13
Nashville	2	1	1	0	0	0	0	0	7	8	-1	1	1	0	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	7	11	18	0	0	2	4	1	0	57	19	22	16	0	59	18	33	35	11	3	27.27%	14	3	78.57%	1	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	48	32	45	14	25	12
Montreal	3	0	2	0	0	0	0	1	6	11	-5	1	0	0	0	0	0	0	1	3	4	-1	2	0	2	0	0	0	0	0	3	7	-4	1	0.167	6	9	15	0	0	4	2	0	1	70	17	22	27	7	79	27	47	54	12	1	8.33%	16	5	68.75%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	72	48	74	23	38	18
Washington	4	4	0	0	0	0	0	0	15	7	8	2	2	0	0	0	0	0	0	8	4	4	2	2	0	0	0	0	0	0	7	3	4	8	1.000	15	28	43	0	0	7	5	3	0	114	45	37	32	0	68	25	40	82	24	8	33.33%	19	1	94.74%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	104	72	82	29	52	28
Caroline	4	4	0	0	0	0	0	0	19	5	14	2	2	0	0	0	0	0	0	9	3	6	2	2	0	0	0	0	0	0	10	2	8	8	1.000	19	37	56	0	0	8	6	5	0	110	31	47	32	0	74	30	38	79	27	7	25.93%	16	0	100.00%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	100	66	87	31	52	27
Las Vegas	2	2	0	0	0	0	0	0	9	4	5	1	1	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	3	2	1	4	1.000	9	17	26	0	0	6	1	2	0	75	23	26	26	0	38	10	14	46	14	2	14.29%	7	2	71.43%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	55	38	38	15	26	14
Vs Division	30	18	6	0	0	3	2	1	96	68	28	15	9	1	0	0	2	2	1	49	33	16	15	9	5	0	0	1	0	0	47	35	12	44	0.733	96	165	261	0	1	38	31	25	6	839	265	279	285	23	709	217	321	522	179	30	16.76%	137	16	88.32%	0	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	749	508	680	235	389	196
Vs Conference	54	31	15	0	0	4	2	2	159	126	33	27	16	5	0	0	2	2	2	79	61	18	27	15	10	0	0	2	0	0	80	65	15	72	0.667	159	272	431	0	4	69	50	38	7	1483	472	502	495	30	1318	408	623	937	301	51	16.94%	261	40	84.67%	1	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	1334	904	1238	420	696	350
Since Last GM Reset	82	47	24	0	1	5	3	2	247	200	47	41	24	8	0	1	3	3	2	129	99	30	41	23	16	0	0	2	0	0	118	101	17	109	0.665	247	423	670	0	5	107	77	59	9	2255	739	751	747	36	2059	633	1016	1417	453	82	18.10%	423	68	83.92%	3	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	2019	1369	1892	633	1047	529
Total	82	47	24	0	1	5	3	2	247	200	47	41	24	8	0	1	3	3	2	129	99	30	41	23	16	0	0	2	0	0	118	101	17	109	0.665	247	423	670	0	5	107	77	59	9	2255	739	751	747	36	2059	633	1016	1417	453	82	18.10%	423	68	83.92%	3	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	2019	1369	1892	633	1047	529

			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	109	L1	247	423	670	2255	2059	633	1016	1417	0	5

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	47	24	1	5	3	2	247	200

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	24	8	1	3	3	2	129	99

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	23	16	0	2	0	0	118	101

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
7	2	0	1	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
453	82	18.10%	423	68	83.92%	3

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
739	751	747	36	107	77	59	9

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
1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%

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
2019	1369	1892	633	1047	529

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	12	Washington	2	Pittsburgh	4	W			Sommaire du Match
4 - 2016-10-15	22	Anaheim	5	Pittsburgh	2	L			Sommaire du Match
6 - 2016-10-17	34	Colorado	5	Pittsburgh	1	L			Sommaire du Match
7 - 2016-10-18	41	Pittsburgh	1	Montreal	4	L			Sommaire du Match
9 - 2016-10-20	53	San Jose	1	Pittsburgh	5	W			Sommaire du Match
11 - 2016-10-22	70	Pittsburgh	3	Las Vegas	2	W			Sommaire du Match
14 - 2016-10-25	86	Quebec	4	Pittsburgh	2	L			Sommaire du Match
16 - 2016-10-27	100	Islanders	6	Pittsburgh	5	L	X		Sommaire du Match
18 - 2016-10-29	115	Pittsburgh	3	Philadelphie	4	L	X		Sommaire du Match
22 - 2016-11-02	145	Pittsburgh	2	Anaheim	1	W			Sommaire du Match
23 - 2016-11-03	148	Pittsburgh	2	LA Kings	0	W			Sommaire du Match
25 - 2016-11-05	173	Pittsburgh	7	San Jose	3	W			Sommaire du Match
28 - 2016-11-08	186	Edmonton	3	Pittsburgh	5	W			Sommaire du Match
30 - 2016-11-10	204	Minnesota	3	Pittsburgh	4	W			Sommaire du Match
32 - 2016-11-12	221	Toronto	2	Pittsburgh	3	W			Sommaire du Match
36 - 2016-11-16	243	Pittsburgh	3	Washington	2	W			Sommaire du Match
38 - 2016-11-18	255	Pittsburgh	1	Islanders	2	L			Sommaire du Match
39 - 2016-11-19	268	Pittsburgh	4	Buffalo	5	L	X		Sommaire du Match
41 - 2016-11-21	277	Rangers	3	Pittsburgh	2	L			Sommaire du Match
43 - 2016-11-23	290	Pittsburgh	2	Rangers	3	L			Sommaire du Match
45 - 2016-11-25	310	Pittsburgh	0	Minnesota	4	L			Sommaire du Match
46 - 2016-11-26	317	Hartford	2	Pittsburgh	3	W	X	X	Sommaire du Match
50 - 2016-11-30	343	Pittsburgh	1	Islanders	4	L			Sommaire du Match
51 - 2016-12-01	347	Kansas City	1	Pittsburgh	4	W			Sommaire du Match
53 - 2016-12-03	360	Detroit	0	Pittsburgh	1	W			Sommaire du Match
55 - 2016-12-05	379	Ottawa	3	Pittsburgh	1	L			Sommaire du Match
58 - 2016-12-08	400	Pittsburgh	6	Quebec	2	W			Sommaire du Match
60 - 2016-12-10	411	Pittsburgh	1	Tampa Bay	4	L			Sommaire du Match
62 - 2016-12-12	429	Nashville	4	Pittsburgh	5	W			Sommaire du Match
64 - 2016-12-14	442	Boston	3	Pittsburgh	0	L			Sommaire du Match
66 - 2016-12-16	453	LA Kings	1	Pittsburgh	4	W			Sommaire du Match
67 - 2016-12-17	462	Pittsburgh	1	Toronto	5	L			Sommaire du Match
70 - 2016-12-20	483	Rangers	1	Pittsburgh	2	W			Sommaire du Match
72 - 2016-12-22	497	Pittsburgh	1	Atlanta	4	L			Sommaire du Match
73 - 2016-12-23	511	Hartford	2	Pittsburgh	3	W	X	X	Sommaire du Match
77 - 2016-12-27	517	Pittsburgh	6	Hartford	4	W			Sommaire du Match
78 - 2016-12-28	528	Caroline	2	Pittsburgh	4	W			Sommaire du Match
81 - 2016-12-31	556	Montreal	4	Pittsburgh	3	L	X	X	Sommaire du Match
89 - 2017-01-08	603	Tampa Bay	4	Pittsburgh	3	L			Sommaire du Match
92 - 2017-01-11	622	Pittsburgh	4	Washington	1	W			Sommaire du Match
93 - 2017-01-12	625	Pittsburgh	2	Ottawa	3	L			Sommaire du Match
95 - 2017-01-14	644	Pittsburgh	3	Detroit	1	W			Sommaire du Match
97 - 2017-01-16	661	Washington	2	Pittsburgh	4	W			Sommaire du Match
99 - 2017-01-18	672	Pittsburgh	2	Montreal	3	L			Sommaire du Match
101 - 2017-01-20	687	Pittsburgh	5	Caroline	1	W			Sommaire du Match
103 - 2017-01-22	702	Boston	1	Pittsburgh	4	W			Sommaire du Match
105 - 2017-01-24	717	St-Louis	3	Pittsburgh	2	L	X		Sommaire du Match
107 - 2017-01-26	738	Pittsburgh	2	Boston	1	W			Sommaire du Match
112 - 2017-01-31	748	Las Vegas	2	Pittsburgh	6	W			Sommaire du Match
115 - 2017-02-03	767	Atlanta	0	Pittsburgh	2	W			Sommaire du Match
116 - 2017-02-04	779	Pittsburgh	1	St-Louis	2	L			Sommaire du Match
119 - 2017-02-07	792	Calgary	2	Pittsburgh	3	W	X		Sommaire du Match
121 - 2017-02-09	804	Pittsburgh	1	Colorado	4	L			Sommaire du Match
123 - 2017-02-11	826	Pittsburgh	2	Nashville	4	L			Sommaire du Match
126 - 2017-02-14	837	Vancouver	3	Pittsburgh	4	W	X	X	Sommaire du Match
128 - 2017-02-16	849	Winnipeg	2	Pittsburgh	3	W			Sommaire du Match
129 - 2017-02-17	855	Pittsburgh	3	Atlanta	1	W			Sommaire du Match
131 - 2017-02-19	878	Detroit	2	Pittsburgh	3	W			Sommaire du Match
133 - 2017-02-21	884	Pittsburgh	5	Caroline	1	W			Sommaire du Match
137 - 2017-02-25	909	Philadelphie	1	Pittsburgh	3	W			Sommaire du Match
140 - 2017-02-28	933	Pittsburgh	4	Kansas City	1	W			Sommaire du Match
141 - 2017-03-01	935	Pittsburgh	1	Chicago	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	948	Tampa Bay	2	Pittsburgh	3	W			Sommaire du Match
145 - 2017-03-05	964	Buffalo	3	Pittsburgh	4	W			Sommaire du Match
148 - 2017-03-08	984	Pittsburgh	4	Winnipeg	1	W			Sommaire du Match
150 - 2017-03-10	999	Pittsburgh	2	Edmonton	1	W			Sommaire du Match
151 - 2017-03-11	1000	Pittsburgh	3	Vancouver	5	L			Sommaire du Match
153 - 2017-03-13	1020	Pittsburgh	6	Calgary	3	W			Sommaire du Match
155 - 2017-03-15	1033	Pittsburgh	3	Philadelphie	1	W			Sommaire du Match
157 - 2017-03-17	1050	Hartford	5	Pittsburgh	4	L	X	X	Sommaire du Match
159 - 2017-03-19	1067	Quebec	0	Pittsburgh	3	W			Sommaire du Match
161 - 2017-03-21	1076	Pittsburgh	3	Buffalo	1	W			Sommaire du Match
163 - 2017-03-23	1093	Pittsburgh	4	Ottawa	0	W			Sommaire du Match
164 - 2017-03-24	1101	Islanders	3	Pittsburgh	2	L	X		Sommaire du Match
166 - 2017-03-26	1117	Philadelphie	1	Pittsburgh	3	W			Sommaire du Match
169 - 2017-03-29	1137	Chicago	3	Pittsburgh	2	L			Sommaire du Match
171 - 2017-03-31	1150	Pittsburgh	5	Rangers	2	W			Sommaire du Match
173 - 2017-04-02	1167	Caroline	1	Pittsburgh	5	W			Sommaire du Match
175 - 2017-04-04	1189	Atlanta	2	Pittsburgh	3	W			Sommaire du Match
177 - 2017-04-06	1198	Pittsburgh	5	Hartford	1	W			Sommaire du Match
179 - 2017-04-08	1211	Pittsburgh	4	Toronto	1	W			Sommaire du Match
180 - 2017-04-09	1224	Pittsburgh	0	Rangers	4	L			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	6100	5150	2650	4300	1050
Prix des Billets	160	90	65	35	325
Assistance	161581	149749	70871	145451	36010
Attendance PCT	64.61%	70.92%	65.23%	82.50%	83.65%

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	13748 - 71.42%	1,551,140$	63,596,742$	19250	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
50,960,999$	52,940,165$	0$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale
52,157,949$	257,796$	51,417,575$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	284,315$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	53,865,559$	109,264,376$	109,264,376$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Matt Duchene	AGE:24	PO:0	OV:71
Patric Hornqvist	AGE:28	PO:0	OV:69
Matt Cullen	AGE:38	PO:0	OV:68
Patrik Berglund	AGE:27	PO:0	OV:63
Pascal Dupuis	AGE:36	PO:0	OV:61
Torrey Mitchell	AGE:30	PO:0	OV:61
Melker Karlsson	AGE:25	PO:0	OV:60
Jordan Martinook	AGE:23	PO:0	OV:59
Michael Blunden	AGE:28	PO:0	OV:54
Craig Cunningham	AGE:25	PO:0	OV:53
T.J. Galiardi	AGE:27	PO:0	OV:50
Turner Elson	AGE:23	PO:0	OV:49
*Mitch Moroz	AGE:21	PO:0	OV:46
*Dylan Sadowy	AGE:19	PO:0	OV:44
Mark Olver	AGE:27	PO:0	OV:42
*Gemel Smith	AGE:21	PO:0	OV:41
*Richard Nejezchleb	AGE:21	PO:0	OV:40

Matt Duchene	AGE:24	PO:0	OV:71
Sean Monahan	AGE:20	PO:0	OV:70
Matt Cullen	AGE:38	PO:0	OV:68
Sean Couturier	AGE:22	PO:0	OV:67
Mark Letestu	AGE:30	PO:0	OV:63
Patrik Berglund	AGE:27	PO:0	OV:63
Jay Beagle	AGE:29	PO:0	OV:61
Torrey Mitchell	AGE:30	PO:0	OV:61
Josh Jooris	AGE:25	PO:0	OV:60
Jordan Martinook	AGE:23	PO:0	OV:59
Craig Cunningham	AGE:25	PO:0	OV:53
T.J. Galiardi	AGE:27	PO:0	OV:50
Turner Elson	AGE:23	PO:0	OV:49
*Zach Nastasiuk	AGE:20	PO:0	OV:45
Mark Olver	AGE:27	PO:0	OV:42
*Gemel Smith	AGE:21	PO:0	OV:41
*Cameron Darcy	AGE:21	PO:0	OV:39
Scott Timmins	AGE:26	PO:0	OV:37
Joonas Nattinen	AGE:24	PO:0	OV:37

Matt Duchene	AGE:24	PO:0	OV:71
Brian Gionta	AGE:36	PO:0	OV:69
Patric Hornqvist	AGE:28	PO:0	OV:69
Jay Beagle	AGE:29	PO:0	OV:61
Pascal Dupuis	AGE:36	PO:0	OV:61
Torrey Mitchell	AGE:30	PO:0	OV:61
Josh Jooris	AGE:25	PO:0	OV:60
Melker Karlsson	AGE:25	PO:0	OV:60
Michael Blunden	AGE:28	PO:0	OV:54
Craig Cunningham	AGE:25	PO:0	OV:53
Anthony Peluso	AGE:26	PO:0	OV:52
Kurtis Gabriel	AGE:22	PO:0	OV:47
*Zach Nastasiuk	AGE:20	PO:0	OV:45
*Richard Nejezchleb	AGE:21	PO:0	OV:40

Défense #1

Défense #2

Gardien

Duncan Keith	AGE:32	PO:0	OV:73
Niklas Hjalmarsson	AGE:28	PO:0	OV:70
Braydon Coburn	AGE:30	PO:0	OV:67
Josh Gorges	AGE:31	PO:0	OV:66
Tobias Enstrom	AGE:30	PO:0	OV:64
Alex Petrovic	AGE:23	PO:0	OV:62
Brett Bellemore	AGE:27	PO:0	OV:59
*Joel Edmundson	AGE:22	PO:0	OV:56
Ryan Stanton	AGE:26	PO:0	OV:56

Ryan Wilson	AGE:28	PO:0	OV:55
Steve Oleksy	AGE:29	PO:0	OV:54
*Ben Harpur	AGE:20	PO:0	OV:52
Alex Grant	AGE:26	PO:0	OV:52
*Alex Lintuniemi	AGE:20	PO:0	OV:46
*Cody Corbett	AGE:21	PO:0	OV:45
*Jerome Gauthier-Leduc	AGE:23	PO:0	OV:43
Cameron Gaunce	AGE:25	PO:0	OV:39

Corey Crawford	AGE:30	PO:0	OV:83
Joonas Korpisalo	AGE:21	PO:0	OV:62
Niklas Treutle	AGE:24	PO:0	OV:47
*Spencer Martin	AGE:20	PO:0	OV:45
Allen York	AGE:26	PO:0	OV:44
*Linus Soderstrom	AGE:19	PO:0	OV:42

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 Helewka	Pittsburgh	2015	70
Andrew Mangiapane	Pittsburgh	2015	129
Dysin Mayo	Pittsburgh	2015	116
Gabriel Gagne	Pittsburgh	2015	45
Thomas Schemitsch	Pittsburgh	2015	128

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
2017				Edm Pit	Tor Mon Pit	Tor Pit	Col Win Ana
2018		Pit	Car Pit	Pit	Mon Pit	Pit	Edm
2019	Pit	Pit	Pit	Pit	Pit	Pit	Pit
2020	Pit	Pit	Pit	Pit	Pit	Pit	Pit
2021	Pit	Pit	Pit	Pit	Pit	Pit	Pit

[2016-09-16 21:12:51] - Niklas Treutle was added to Pittsburgh.
[2016-09-16 21:12:57] - Turner Elson was added to Pittsburgh.
[2016-09-17 10:10:16] - Unknown Player is no longer captain for Manchots.
[2016-09-17 10:10:16] - Linden Vey has been selected as captain for Manchots.
[2016-09-25 23:57:41] - Manchots hired Guy Boucher for 500 000 $ for 4 year(s).
[2016-10-10 13:10:14] - Brian Gionta is no longer as assistant for Pittsburgh.
[2016-10-10 13:10:14] - Duncan Keith has been selected as assistant for Pittsburgh.
[2016-10-10 13:10:14] - Niklas Hjalmarsson is no longer as assistant for Pittsburgh.
[2016-10-10 13:10:14] - Brian Gionta has been selected as assistant for Pittsburgh.
[2016-10-17 20:00:17] - Unknown Player is no longer captain for Manchots.
[2016-10-17 20:00:17] - Linden Vey has been selected as captain for Manchots.
[2016-10-17 20:00:17] - Unknown Player is no longer as assistant for Manchots.
[2016-10-17 20:00:17] - Michael Blunden has been selected as assistant for Manchots.
[2016-10-17 20:00:17] - Unknown Player is no longer as assistant for Manchots.
[2016-10-17 20:00:17] - Mitch Moroz has been selected as assistant for Manchots.
[2016-11-14 22:29:46] - Matt Cullen was added to Pittsburgh.
[2016-11-14 22:29:47] - TRADE : From Hartford to Pittsburgh : Matt Cullen (68).
[2016-11-14 22:29:47] - TRADE : From Pittsburgh to Hartford : Zack Smith (63), Y:2017-RND:5-Win.
[2016-11-25 20:00:22] - New Record for Team's Most Shots Blocked (17) in 1 Game for Pittsburgh!
[2016-12-05 20:00:23] - New Record for Team's Most Shots Blocked (18) in 1 Game for Pittsburgh!
[2016-12-27 20:00:23] - New Record for Team's Most Shots (49) in 1 Game for Pittsburgh!
[2017-01-22 20:00:12] - Unknown Player is no longer captain for Manchots.
[2017-01-22 20:00:12] - Ryan Wilson has been selected as captain for Manchots.
[2017-01-22 20:00:12] - Michael Blunden is no longer as assistant for Manchots.
[2017-01-22 20:00:12] - Joel Edmundson has been selected as assistant for Manchots.
[2017-01-22 20:00:12] - Mitch Moroz is no longer as assistant for Manchots.
[2017-01-22 20:00:12] - Michael Blunden has been selected as assistant for Manchots.
[2017-01-31 06:01:07] - Torrey Mitchell was added to Pittsburgh.
[2017-01-31 06:01:08] - TRADE : From Pittsburgh to Caroline : Nikita Nesterov (55).
[2017-01-31 06:01:08] - TRADE : From Caroline to Pittsburgh : Torrey Mitchell (61).
[2017-02-02 20:54:36] - TRADE : From Pittsburgh to Washington : Linden Vey (57).
[2017-02-28 20:20:19] - Jay Beagle was added to Pittsburgh.
[2017-02-28 20:20:20] - TRADE : From Caroline to Pittsburgh : Jay Beagle (61), Y:2018-RND:3-Car.
[2017-02-28 20:20:20] - TRADE : From Pittsburgh to Caroline : Y:2017-RND:4-Har, Y:2017-RND:3-Pit.

Brett Bellemore est suspendu indéfiniement.

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	47	24	0	1	5	3	2	247	200	47	41	24	8	0	1	3	3	2	129	99	30	41	23	16	0	0	2	0	0	118	101	17	94	247	423	670	0	5	107	77	59	9	2255	739	751	747	36	2059	633	1016	1417	453	82	18.10%	423	68	83.92%	3	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	2019	1369	1892	633	1047	529
Total Saison Régulière	82	47	24	0	1	5	3	2	247	200	47	41	24	8	0	1	3	3	2	129	99	30	41	23	16	0	0	2	0	0	118	101	17	94	247	423	670	0	5	107	77	59	9	2255	739	751	747	36	2059	633	1016	1417	453	82	18.10%	423	68	83.92%	3	1436	2847	50.44%	1396	2675	52.19%	621	1215	51.11%	2019	1369	1892	633	1047	529