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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	Claude Giroux (C)	X	X	X		100.00	57	39	84	83	69	85	89	86	87	84	75	72	86	80	93	0	54	74	0
2	Tom Wilson (A)			X		99.00	97	75	56	72	90	83	84	71	58	73	77	84	69	71	76	0	68	72	0
3	James van Riemsdyk		X			100.00	57	42	89	75	87	81	83	74	56	73	78	59	76	79	73	0	51	70	0
4	Jeff Skinner	X	X	X		100.00	56	39	84	82	71	83	86	79	73	71	80	56	82	75	69	0	67	70	0
5	Nazem Kadri	X				100.00	78	52	64	77	73	82	85	74	83	76	75	62	77	78	73	0	68	70	0
6	Micheal Ferland		X	X		100.00	90	62	69	72	81	79	77	71	58	73	70	62	69	75	68	0	67	69	0
7	Tyler Bertuzzi		X	X		100.00	74	56	78	73	77	83	87	72	56	75	74	59	67	69	66	0	69	69	0
8	Cody Eakin	X				100.00	74	39	87	68	71	78	83	67	84	69	70	78	66	77	69	0	67	68	0
9	Ondrej Kase			X		100.00	54	39	89	74	72	83	77	72	56	73	70	62	74	69	65	0	67	67	0
10	Evan Rodrigues	X	X	X		100.00	57	42	85	70	69	77	81	68	79	67	63	70	69	73	68	0	57	66	0
11	Martin Necas	X		X		100.00	63	39	88	71	78	80	77	69	70	68	67	63	72	62	66	0	67	66	0
12	Tobias Rieder	X	X	X		100.00	67	39	83	66	70	73	82	65	68	63	61	76	66	73	67	0	67	65	0
13	Jacob Trouba				X	100.00	84	51	69	73	85	89	91	72	30	80	67	85	56	71	67	0	73	71	0
14	Torey Krug (A)				X	100.00	63	45	74	78	67	87	82	77	30	89	69	61	63	77	72	0	54	71	0
15	Brady Skjei				X	100.00	84	45	75	72	85	87	89	71	30	74	69	80	56	71	67	0	67	70	0
16	Justin Braun				X	100.00	81	42	83	63	81	85	87	62	30	73	56	77	49	82	73	0	67	67	0
17	Devon Toews				X	100.00	62	39	88	69	76	85	81	68	30	76	66	62	54	71	67	0	67	67	0
18	Dylan DeMelo				X	100.00	82	43	79	63	73	85	87	62	30	73	55	78	51	73	67	0	50	66	0
Rayé

	MOYENNE D'ÉQUIPE					99.94	71	46	79	72	76	83	84	71	56	74	69	69	67	74	70	0	64	69

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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	Devan Dubnyk	98.00	91	95	93	97	90	89	91	90	89	91	90	84	88	0	67	76	0
2	Keith Kinkaid	100.00	73	76	74	81	72	71	73	72	71	73	72	79	85	0	67	65	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	82	86	84	89	81	80	82	81	80	82	81	82	87	0	67	71

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
John Tortorella	81	90	82	89	92	85	53	USA	61	1	100,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FW	FT	S1	S2	S3
1	Claude Giroux	Flyers	C/LW/RW	43	11	25	36	-1	0	0	8	110	144	29	118	7.64%	6	853	19.85	2	6	8	33	149	1	1	2	2	109	3	1	51.78%	869	0	0	0.84	0	1	0	0	0	1	3
2	Jacob Trouba	Flyers	D	47	10	24	34	-13	71	15	147	80	88	27	55	11.36%	75	1150	24.49	6	6	12	54	153	1	1	2	2	153	1	0	0.00%	0	0	0	0.59	0	0	2	1	2	1	3
3	Nazem Kadri	Flyers	C	47	14	13	27	-8	31	5	74	88	115	31	68	12.17%	2	815	17.35	3	9	12	24	145	0	0	0	0	7	4	0	49.45%	1001	0	1	0.66	0	1	0	1	4	2	2
4	James van Riemsdyk	Flyers	LW	45	7	19	26	4	2	0	4	43	98	30	68	7.14%	2	775	17.24	2	7	9	19	127	0	0	0	0	6	0	0	35.59%	59	0	0	0.67	0	1	0	0	0	3	1
5	Jeff Skinner	Flyers	C/LW/RW	47	14	12	26	-9	2	0	9	60	92	29	79	15.22%	0	853	18.16	3	5	8	21	154	0	0	0	1	32	4	0	42.50%	80	0	0	0.61	1	2	0	0	1	2	0
6	Tom Wilson	Flyers	RW	47	11	12	23	-4	91	15	156	71	115	40	97	9.57%	25	829	17.65	1	0	1	2	12	0	0	0	7	172	2	2	46.55%	58	0	0	0.55	0	1	1	2	3	2	1
7	Cody Eakin	Flyers	C	47	9	12	21	7	8	0	36	117	78	17	49	11.54%	9	724	15.42	0	0	0	0	0	0	0	0	6	202	0	1	51.80%	1025	0	0	0.58	0	0	0	0	1	1	1
8	Brady Skjei	Flyers	D	47	7	14	21	-4	50	0	88	53	78	23	56	8.97%	46	1036	22.05	2	1	3	41	141	0	0	0	1	157	0	0	0.00%	0	0	0	0.41	0	0	0	0	0	1	0
9	Micheal Ferland	Flyers	LW/RW	47	5	16	21	0	48	0	114	43	99	24	65	5.05%	5	683	14.54	1	9	10	27	96	0	0	0	1	0	2	0	43.48%	46	0	0	0.61	1	1	0	0	1	1	0
10	Torey Krug	Flyers	D	46	3	17	20	-5	29	5	26	56	70	15	42	4.29%	47	1046	22.75	3	6	9	56	151	0	0	0	0	99	1	0	0.00%	0	0	0	0.38	0	0	0	0	2	1	0
11	Devon Toews	Flyers	D	47	5	13	18	7	8	0	28	29	40	11	26	12.50%	47	867	18.45	5	4	9	25	141	0	0	0	0	60	0	1	0.00%	0	0	0	0.42	0	0	0	0	0	1	0
12	Justin Braun	Flyers	D	44	2	13	15	9	48	0	109	47	29	11	22	6.90%	53	743	16.91	0	1	1	2	7	1	0	1	1	129	0	0	0.00%	0	0	0	0.40	0	0	0	0	1	2	0
13	Ondrej Kase	Flyers	RW	47	7	7	14	4	0	0	4	30	80	21	43	8.75%	1	525	11.18	0	1	1	3	19	0	0	0	0	0	0	1	38.71%	31	1	0	0.53	0	0	0	0	0	2	0
14	Martin Necas	Flyers	C/RW	47	7	6	13	-2	8	0	20	21	44	13	44	15.91%	1	425	9.04	0	2	2	5	42	0	0	0	0	0	2	0	48.48%	33	0	0	0.61	0	0	0	0	0	1	1
15	Tyler Bertuzzi	Flyers	LW/RW	47	6	5	11	1	18	10	69	41	66	28	64	9.09%	1	778	16.57	4	0	4	18	148	0	0	0	0	0	2	0	44.64%	56	0	0	0.28	0	0	0	2	0	0	4
16	Evan Rodrigues	Flyers	C/LW/RW	47	2	6	8	0	4	0	7	66	40	9	28	5.00%	7	413	8.81	0	0	0	0	1	0	2	2	1	71	0	0	49.78%	446	0	0	0.39	0	0	0	0	1	0	1
17	Tobias Rieder	Flyers	C/LW/RW	47	2	5	7	1	18	0	42	33	31	12	31	6.45%	8	413	8.79	0	0	0	0	0	0	1	1	2	70	2	0	36.36%	22	0	0	0.34	0	0	0	0	0	0	3
18	Dylan DeMelo	Flyers	D	47	1	6	7	-15	38	0	92	43	18	4	10	5.56%	29	694	14.78	0	0	0	0	2	0	0	0	0	26	0	1	0.00%	0	0	0	0.20	0	0	0	0	0	0	0
19	Joel Farabee	Phantoms (PHI)	LW	4	0	1	1	0	4	0	0	1	6	1	5	0.00%	0	35	8.95	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	1	0	0	0.56	0	0	0	0	0	0	0
20	Dan Hamhuis	Phantoms (PHI)	D	3	0	0	0	0	0	0	7	1	0	0	0	0.00%	9	49	16.59	0	0	0	0	0	0	0	0	0	13	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0
21	Matt Read	Phantoms (PHI)	RW	5	0	0	0	-3	0	0	2	3	2	1	4	0.00%	1	40	8.16	0	0	0	0	0	0	0	0	0	0	0	0	33.33%	3	0	0	0.00	0	0	0	0	0	0	0
22	Michael Paliotta	Phantoms (PHI)	D	1	0	0	0	-1	0	0	1	0	0	0	0	0.00%	0	11	11.35	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0.00	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				849	123	226	349	-32	478	50	1043	1036	1333	376	974	9.23%	374	13769	16.22	32	57	89	330	1496	3	5	8	24	1313	23	7	49.92%	3730	1	1	0.51	2	7	3	6	16	21	20

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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	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Devan Dubnyk	Flyers	46	24	21	1	0.904	2.77	2775	8	3	128	1331	1	0.500	8	46	1	5	4	1
2	Keith Kinkaid	Flyers	1	0	1	0	0.889	3.00	60	0	0	3	27	0	0.000	0	1	46	0	0	0
Stats d'équipe Total ou en Moyenne			47	24	22	1	0.904	2.77	2835	8	3	131	1358	1	0.500	8	47	47	5	4	1

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Salaire Année 7	Salaire Année 8	Link
Brady Skjei	Flyers	D	25	1994-03-26	No	210 Lbs	6 ft3	No	No	No	5	Pro & Farm	5,250,000$	5,250,000$	2,307,692$	No	5,250,000$	5,250,000$	5,250,000$	5,250,000$				Lien / Lien NHL
Claude Giroux	Flyers	C/LW/RW	31	1988-01-12	No	185 Lbs	5 ft11	No	No	No	3	Pro & Farm	8,275,000$	8,275,000$	3,637,363$	No	8,275,000$	8,275,000$						Lien / Lien NHL
Cody Eakin	Flyers	C	28	1991-05-24	No	183 Lbs	6 ft0	No	No	No	1	Pro & Farm	3,850,000$	3,850,000$	1,692,308$	No								Lien / Lien NHL
Devan Dubnyk	Flyers	G	33	1986-05-04	No	224 Lbs	6 ft6	No	No	No	2	Pro & Farm	4,333,000$	4,333,000$	1,904,615$	No	4,333,000$							Lien / Lien NHL
Devon Toews	Flyers	D	25	1994-02-21	No	191 Lbs	6 ft1	No	No	No	1	Pro & Farm	700,000$	700,000$	307,692$	No								Lien / Lien NHL
Dylan DeMelo	Flyers	D	26	1993-05-01	No	191 Lbs	6 ft0	No	No	No	1	Pro & Farm	900,000$	900,000$	395,604$	No								Lien / Lien NHL
Evan Rodrigues	Flyers	C/LW/RW	26	1993-07-28	No	184 Lbs	5 ft11	No	No	No	1	Pro & Farm	2,000,000$	2,000,000$	879,121$	No								Lien / Lien NHL
Jacob Trouba	Flyers	D	25	1994-02-26	No	209 Lbs	6 ft3	No	No	No	7	Pro & Farm	8,000,000$	8,000,000$	3,516,484$	No	8,000,000$	8,000,000$	8,000,000$	8,000,000$	8,000,000$	8,000,000$		Lien / Lien NHL
James van Riemsdyk	Flyers	LW	30	1989-05-04	No	217 Lbs	6 ft3	No	No	No	4	Pro & Farm	7,000,000$	7,000,000$	3,076,923$	No	7,000,000$	7,000,000$	7,000,000$					Lien / Lien NHL
Jeff Skinner	Flyers	C/LW/RW	27	1992-05-16	No	195 Lbs	5 ft11	No	No	No	8	Pro & Farm	9,000,000$	9,000,000$	3,956,044$	No	9,000,000$	9,000,000$	9,000,000$	9,000,000$	9,000,000$	9,000,000$	9,000,000$	Lien / Lien NHL
Justin Braun	Flyers	D	32	1987-02-10	No	205 Lbs	6 ft2	No	No	No	1	Pro & Farm	3,800,000$	3,800,000$	1,670,330$	No								Lien / Lien NHL
Keith Kinkaid	Flyers	G	30	1989-07-04	No	186 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,750,000$	1,750,000$	769,231$	No								Lien / Lien NHL
Martin Necas	Flyers	C/RW	20	1999-01-15	No	189 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,431,666$	1,431,666$	629,304$	No	1,431,666$							Lien / Lien NHL
Micheal Ferland	Flyers	LW/RW	27	1992-04-20	No	217 Lbs	6 ft1	No	No	No	4	Pro & Farm	3,500,000$	3,500,000$	1,538,462$	No	3,500,000$	3,500,000$	3,500,000$					Lien / Lien NHL
Nazem Kadri	Flyers	C	29	1990-10-06	No	192 Lbs	6 ft0	No	No	No	3	Pro & Farm	4,500,000$	4,500,000$	1,978,022$	No	4,500,000$	4,500,000$						Lien / Lien NHL
Ondrej Kase	Flyers	RW	23	1995-11-08	No	190 Lbs	6 ft0	No	No	No	2	Pro & Farm	2,600,000$	2,600,000$	1,142,857$	No	2,600,000$							Lien / Lien NHL
Tobias Rieder	Flyers	C/LW/RW	26	1993-01-10	No	186 Lbs	5 ft11	No	No	No	1	Pro & Farm	700,000$	700,000$	307,692$	No								Lien / Lien NHL
Tom Wilson	Flyers	RW	25	1994-03-29	No	220 Lbs	6 ft4	No	No	No	5	Pro & Farm	5,166,666$	5,166,666$	2,271,062$	No	5,166,666$	5,166,666$	5,166,666$	5,166,666$				Lien / Lien NHL
Torey Krug	Flyers	D	28	1991-04-12	No	186 Lbs	5 ft9	No	No	No	1	Pro & Farm	5,250,000$	5,250,000$	2,307,692$	No								Lien / Lien NHL
Tyler Bertuzzi	Flyers	LW/RW	24	1995-02-24	No	199 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,400,000$	1,400,000$	615,385$	No								Lien / Lien NHL

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
20	27.00	198 Lbs	6 ft1	2.70	3,970,317$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
79,406,332$	59,056,332$	50,691,666$	37,916,666$	27,416,666$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	James van Riemsdyk	Claude Giroux	Tom Wilson	30	0	2	3
2	Jeff Skinner	Nazem Kadri	Tyler Bertuzzi	30	0	2	3
3	Micheal Ferland	Cody Eakin	Ondrej Kase	25	0	2	3
4	Tobias Rieder	Evan Rodrigues	Martin Necas	15	0	2	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Brady Skjei	Jacob Trouba	30	0	2	3
2	Torey Krug	Justin Braun	30	0	3	2
3	Devon Toews	Dylan DeMelo	25	1	2	2
4	Torey Krug	Jacob Trouba	15	0	2	3

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	James van Riemsdyk	Claude Giroux	Micheal Ferland	60	0	1	4
2	Jeff Skinner	Nazem Kadri	Tyler Bertuzzi	40	0	2	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Jacob Trouba	60	0	2	3
2	Brady Skjei	Devon Toews	40	0	2	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Cody Eakin	Tom Wilson	60	1	4	0
2	Evan Rodrigues	Tobias Rieder	40	1	4	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Brady Skjei	Jacob Trouba	60	1	4	0
2	Torey Krug	Justin Braun	40	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Claude Giroux	60	1	4	0	Brady Skjei	Jacob Trouba	60	1	4	0
2	Cody Eakin	40	1	4	0	Torey Krug	Justin Braun	40	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Claude Giroux	James van Riemsdyk	60	0	2	3
2	Nazem Kadri	Jeff Skinner	40	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Jacob Trouba	60	0	2	3
2	Brady Skjei	Devon Toews	40	0	2	3

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jeff Skinner	Claude Giroux	Tom Wilson	Jacob Trouba	Torey Krug

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Claude Giroux	Cody Eakin	Tom Wilson	Jacob Trouba	Brady Skjei

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ondrej Kase, Martin Necas, Cody Eakin	Ondrej Kase, Martin Necas	Claude Giroux

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Justin Braun, Torey Krug, Brady Skjei	Justin Braun	Devon Toews, Torey Krug

Tirs de Pénalité
Claude Giroux, Jeff Skinner, Nazem Kadri, Cody Eakin, Ondrej Kase

Gardien
#1 : Devan Dubnyk, #2 : Keith Kinkaid

Lignes d'Attaque Perso. en Prol.
Claude Giroux, Tom Wilson, Jeff Skinner, Nazem Kadri, Micheal Ferland, Tyler Bertuzzi, Tyler Bertuzzi, Evan Rodrigues, Cody Eakin, Ondrej Kase, Martin Necas

Lignes de Défense Perso. en Prol.
Jacob Trouba, Brady Skjei, Torey Krug, Devon Toews, Justin Braun

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Blackhawks	3	1	1	0	1	0	0	0	6	6	0	1	0	1	0	0	0	0	0	0	3	-3	2	1	0	0	1	0	0	0	6	3	3	4	0.667	6	9	15	0	0	1	1	3	1	71	24	20	26	1	88	31	51	82	8	0	0.00%	18	4	77.78%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	67	44	76	22	37	18
2	Blue Jackets	2	0	2	0	0	0	0	0	2	8	-6	1	0	1	0	0	0	0	0	0	4	-4	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	2	4	6	0	0	0	2	0	0	57	22	16	19	0	54	20	24	49	6	1	16.67%	10	1	90.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	47	32	46	15	26	12
3	Blues	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	6	5	1	2	1.000	6	10	16	0	0	3	0	2	1	31	9	6	15	1	27	9	10	26	3	1	33.33%	4	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	24	15	22	8	14	6
4	Bruins	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	4	8	12	0	0	1	2	1	0	63	19	12	32	0	57	24	21	36	10	4	40.00%	8	1	87.50%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	49	35	44	15	25	12
5	Canadiens	2	1	1	0	0	0	0	0	5	7	-2	0	0	0	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	0	5	7	-2	2	0.500	5	10	15	0	0	1	3	1	0	53	21	17	15	0	59	17	14	43	4	1	25.00%	7	0	100.00%	1	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	46	32	49	13	23	12
6	Canucks	4	1	2	0	1	0	0	0	11	12	-1	3	0	2	0	1	0	0	0	6	9	-3	1	1	0	0	0	0	0	0	5	3	2	4	0.500	11	21	32	1	0	3	2	5	1	119	38	33	47	1	96	23	40	95	16	2	12.50%	19	5	73.68%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	96	68	95	28	48	25
7	Capitals	1	1	0	0	0	0	0	0	3	0	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	0	3	2	1.000	3	5	8	0	1	2	1	0	0	29	4	15	10	0	37	8	6	24	4	1	25.00%	2	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	23	17	24	7	11	5
8	Coyotes	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	0	0	0	1	0	0	32	8	9	15	0	27	6	9	23	4	0	0.00%	2	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	25	18	20	6	13	6
9	Devils	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	5	8	0	0	1	1	1	0	21	5	8	8	0	30	7	4	17	5	1	20.00%	2	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	22	15	24	7	12	5
10	Ducks	2	1	0	0	0	0	0	1	6	6	0	1	0	0	0	0	0	0	1	2	3	-1	1	1	0	0	0	0	0	0	4	3	1	3	0.750	6	11	17	0	0	0	2	4	0	49	9	15	21	6	53	14	14	42	7	1	14.29%	7	1	85.71%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	49	33	48	15	26	12
11	Flames	1	1	0	0	0	0	0	0	5	2	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	2	3	2	1.000	5	9	14	0	0	2	2	1	0	36	10	19	7	0	33	5	12	24	3	0	0.00%	5	1	80.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	22	15	24	7	12	6
12	Golden Knights	1	0	1	0	0	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	4	8	12	0	0	0	1	3	0	24	5	6	13	0	42	8	12	21	1	1	100.00%	6	1	83.33%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	19	13	27	7	13	6
13	Hurricanes	2	0	1	0	1	0	0	0	5	6	-1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	1	0	0	0	5	6	-1	2	0.500	5	8	13	0	0	1	2	1	1	66	17	19	22	8	58	29	14	41	8	2	25.00%	7	2	71.43%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	52	36	45	14	25	12
14	Jets	1	0	0	0	1	0	0	0	5	4	1	1	0	0	0	1	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	10	15	0	0	1	3	0	1	27	10	11	5	1	41	11	16	34	5	1	20.00%	7	2	71.43%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	22	15	26	7	12	5
15	Kings	1	0	0	0	1	0	0	0	4	3	1	1	0	0	0	1	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	6	10	0	0	0	2	1	1	39	9	15	14	1	16	5	4	17	5	2	40.00%	2	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	28	20	18	7	13	7
16	Lightning	3	1	2	0	0	0	0	0	6	8	-2	2	1	1	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	1	4	-3	2	0.333	6	11	17	0	0	1	1	4	0	61	19	23	19	0	86	24	36	72	6	1	16.67%	18	3	83.33%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	65	44	77	22	37	17
17	Maple Leafs	2	2	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	3	0	3	1	1	0	0	0	0	0	0	4	3	1	4	1.000	7	14	21	0	1	2	3	2	0	53	15	17	21	0	62	17	18	31	7	0	0.00%	8	2	75.00%	1	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	47	33	48	15	23	12
18	Oilers	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	1	1	1	0	34	11	16	7	0	29	9	6	8	5	1	20.00%	3	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	27	20	21	6	11	5
19	Panthers	2	1	1	0	0	0	0	0	4	4	0	1	1	0	0	0	0	0	0	3	0	3	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	4	7	11	0	1	2	1	1	0	56	25	16	15	0	58	15	18	47	7	0	0.00%	7	1	85.71%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	52	36	43	14	24	12
20	Penguins	3	1	2	0	0	0	0	0	6	9	-3	1	0	1	0	0	0	0	0	2	3	-1	2	1	1	0	0	0	0	0	4	6	-2	2	0.333	6	7	13	0	0	2	0	4	0	63	28	19	16	0	84	18	29	56	10	1	10.00%	12	4	66.67%	1	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	66	45	75	22	38	19
21	Predators	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	5	8	0	0	1	2	0	0	35	13	8	14	0	27	3	6	26	3	2	66.67%	3	1	66.67%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	26	18	22	7	11	5
22	Rangers	3	1	1	0	0	0	1	0	11	10	1	2	0	1	0	0	0	1	0	6	6	0	1	1	0	0	0	0	0	0	5	4	1	4	0.667	11	19	30	0	0	4	5	1	3	86	31	28	25	7	94	27	52	66	14	5	35.71%	16	3	81.25%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	68	45	78	23	37	19
23	Red Wings	2	1	0	0	1	0	0	0	6	3	3	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	1	0	0	0	6	3	3	4	1.000	6	11	17	0	0	2	2	1	1	78	18	26	32	2	64	28	21	46	6	1	16.67%	8	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	46	32	50	14	23	11
24	Sabres	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	2	0	1	0	61	22	24	15	0	57	22	35	67	8	1	12.50%	11	1	90.91%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	42	27	52	14	25	11
25	Senateurs	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	1	4	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	1	0	0	0	27	11	7	9	0	32	12	8	25	2	0	0.00%	3	1	66.67%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	22	16	26	6	11	6
26	Stars	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	4	7	0	0	2	0	1	0	39	17	10	12	0	21	0	6	21	6	1	16.67%	3	3	0.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	30	22	17	6	11	6
	Total	47	16	22	0	7	0	1	1	126	133	-7	24	5	14	0	3	0	1	1	58	67	-9	23	11	8	0	4	0	0	0	68	66	2	49	0.521	126	222	348	1	3	36	42	40	10	1347	430	432	464	28	1359	399	496	1065	171	31	18.13%	203	37	81.77%	3	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	1121	778	1132	348	585	290
27	Wild	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	0	2	1	0	37	10	17	10	0	27	7	10	26	8	0	0.00%	5	0	100.00%	0	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	27	19	21	7	11	5
	_Since Last GM Reset	47	16	22	0	7	0	1	1	126	133	-7	24	5	14	0	3	0	1	1	58	67	-9	23	11	8	0	4	0	0	0	68	66	2	49	0.521	126	222	348	1	3	36	42	40	10	1347	430	432	464	28	1359	399	496	1065	171	31	18.13%	203	37	81.77%	3	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	1121	778	1132	348	585	290
	_Vs Conference	28	10	15	0	2	0	1	0	66	76	-10	12	3	8	0	0	0	1	0	25	29	-4	16	7	7	0	2	0	0	0	41	47	-6	26	0.464	66	117	183	0	3	22	23	18	5	774	257	247	258	17	832	268	300	620	97	19	19.59%	119	19	84.03%	3	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	653	450	688	209	347	171
	_Vs Division	12	3	7	0	1	0	1	0	30	37	-7	5	0	4	0	0	0	1	0	11	17	-6	7	3	3	0	1	0	0	0	19	20	-1	10	0.417	30	48	78	0	1	10	11	7	4	322	107	105	100	15	357	109	129	253	47	11	23.40%	49	10	79.59%	1	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	280	192	295	91	151	74

			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
47	49	L1	126	222	348	1347	1359	399	496	1065	1	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
47	16	22	7	0	1	1	126	133

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
24	5	14	3	0	1	1	58	67

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
23	11	8	4	0	0	0	68	66

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	1	0	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
171	31	18.13%	203	37	81.77%	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
430	432	464	28	36	42	40	10

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
815	1624	50.18%	831	1670	49.76%	341	681	50.07%

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
1121	778	1132	348	585	290

Derniers Match Joués 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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	RI	Lien
2 - 2020-10-06	10	Flyers	2	Penguins	5	L				Sommaire du Match
4 - 2020-10-08	28	Sabres	1	Flyers	0	L			R3	Sommaire du Match
6 - 2020-10-10	41	Wild	1	Flyers	3	W				Sommaire du Match
9 - 2020-10-13	64	Canucks	3	Flyers	1	L				Sommaire du Match
11 - 2020-10-15	78	Flyers	3	Red Wings	1	W				Sommaire du Match
13 - 2020-10-17	91	Flyers	2	Bruins	4	L				Sommaire du Match
15 - 2020-10-19	106	Maple Leafs	0	Flyers	3	W				Sommaire du Match
17 - 2020-10-21	124	Canucks	2	Flyers	3	W	X			Sommaire du Match
18 - 2020-10-22	132	Flyers	2	Canadiens	5	L				Sommaire du Match
21 - 2020-10-25	147	Flyers	3	Blackhawks	1	W				Sommaire du Match
23 - 2020-10-27	163	Flyers	6	Blues	5	W	X			Sommaire du Match
25 - 2020-10-29	179	Senateurs	4	Flyers	1	L				Sommaire du Match
28 - 2020-11-01	198	Lightning	2	Flyers	4	W				Sommaire du Match
30 - 2020-11-03	213	Flyers	2	Penguins	1	W				Sommaire du Match
32 - 2020-11-05	230	Blue Jackets	4	Flyers	0	L				Sommaire du Match
35 - 2020-11-08	250	Flyers	1	Panthers	4	L				Sommaire du Match
37 - 2020-11-10	264	Golden Knights	5	Flyers	4	L				Sommaire du Match
40 - 2020-11-13	284	Flyers	3	Capitals	0	W				Sommaire du Match
41 - 2020-11-14	293	Predators	4	Flyers	3	L				Sommaire du Match
44 - 2020-11-17	316	Rangers	3	Flyers	4	W	X	X		Sommaire du Match
47 - 2020-11-20	335	Flyers	2	Blue Jackets	4	L				Sommaire du Match
48 - 2020-11-21	349	Jets	4	Flyers	5	W	X			Sommaire du Match
51 - 2020-11-24	373	Flyers	3	Red Wings	2	W	X			Sommaire du Match
52 - 2020-11-25	378	Penguins	3	Flyers	2	L				Sommaire du Match
55 - 2020-11-28	400	Flyers	1	Coyotes	3	L				Sommaire du Match
56 - 2020-11-29	410	Stars	5	Flyers	3	L				Sommaire du Match
59 - 2020-12-02	430	Flyers	4	Maple Leafs	3	W				Sommaire du Match
60 - 2020-12-03	441	Bruins	3	Flyers	2	L				Sommaire du Match
63 - 2020-12-06	463	Flyers	1	Lightning	4	L				Sommaire du Match
65 - 2020-12-08	472	Kings	3	Flyers	4	W	X			Sommaire du Match
67 - 2020-12-10	487	Flyers	5	Hurricanes	4	W	X			Sommaire du Match
69 - 2020-12-12	498	Flyers	5	Flames	2	W				Sommaire du Match
70 - 2020-12-13	510	Oilers	1	Flyers	3	W				Sommaire du Match
73 - 2020-12-16	531	Devils	4	Flyers	3	L				Sommaire du Match
75 - 2020-12-18	548	Flyers	4	Ducks	3	W				Sommaire du Match
78 - 2020-12-21	565	Rangers	3	Flyers	2	L				Sommaire du Match
80 - 2020-12-23	585	Flyers	3	Canadiens	2	W				Sommaire du Match
82 - 2020-12-25	595	Canucks	4	Flyers	2	L				Sommaire du Match
84 - 2020-12-27	611	Flyers	5	Rangers	4	W				Sommaire du Match
86 - 2020-12-29	625	Blackhawks	3	Flyers	0	L				Sommaire du Match
88 - 2020-12-31	643	Flyers	3	Sabres	2	W			R3	Sommaire du Match
90 - 2021-01-02	657	Ducks	3	Flyers	2	L	X	X		Sommaire du Match
92 - 2021-01-04	668	Flyers	3	Blackhawks	2	W	X			Sommaire du Match
95 - 2021-01-07	690	Lightning	2	Flyers	1	L				Sommaire du Match
98 - 2021-01-10	710	Flyers	5	Canucks	3	W				Sommaire du Match
100 - 2021-01-12	722	Panthers	0	Flyers	3	W				Sommaire du Match
102 - 2021-01-14	740	Flyers	0	Hurricanes	2	L				Sommaire du Match
104 - 2021-01-16	754	Blues	-	Flyers	-
107 - 2021-01-19	778	Maple Leafs	-	Flyers	-
109 - 2021-01-21	786	Flyers	-	Sharks	-
111 - 2021-01-23	801	Flyers	-	Bruins	-
113 - 2021-01-25	814	Hurricanes	-	Flyers	-
116 - 2021-01-28	838	Flyers	-	Oilers	-
118 - 2021-01-30	848	Avalanche	-	Flyers	-
119 - 2021-01-31	860	Flyers	-	Penguins	-
121 - 2021-02-02	875	Flyers	-	Kings	-
123 - 2021-02-04	883	Senateurs	-	Flyers	-
127 - 2021-02-08	908	Wild	-	Flyers	-
129 - 2021-02-10	924	Flyers	-	Senateurs	-
130 - 2021-02-11	936	Canadiens	-	Flyers	-
133 - 2021-02-14	950	Flyers	-	Panthers	-
135 - 2021-02-16	968	Islanders	-	Flyers	-
137 - 2021-02-18	984	Flyers	-	Wild	-
139 - 2021-02-20	996	Flyers	-	Golden Knights	-
140 - 2021-02-21	1005	Blue Jackets	-	Flyers	-
142 - 2021-02-23	1025	Flyers	-	Avalanche	-
144 - 2021-02-25	1035	Capitals	-	Flyers	-
147 - 2021-02-28	1052	Flyers	-	Jets	-
149 - 2021-03-02	1066	Flames	-	Flyers	-
152 - 2021-03-05	1090	Flyers	-	Stars	-
153 - 2021-03-06	1099	Islanders	-	Flyers	-
155 - 2021-03-08	1112	Flyers	-	Blues	-
156 - 2021-03-09	1126	Sharks	-	Flyers	-
159 - 2021-03-12	1151	Coyotes	-	Flyers	-
161 - 2021-03-14	1164	Flyers	-	Devils	-
165 - 2021-03-18	1185	Red Wings	-	Flyers	-
167 - 2021-03-20	1193	Flyers	-	Devils	-
169 - 2021-03-22	1212	Sabres	-	Flyers	-
170 - 2021-03-23	1217	Flyers	-	Islanders	-
172 - 2021-03-25	1223	Flyers	-	Predators	-
177 - 2021-03-30	1247	Capitals	-	Flyers	-
179 - 2021-04-01	1256	Flyers	-	Islanders	-

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	25	200
Assistance	137,573	112,978	45,922	91,014	22,764
Attendance PCT	95.54%	94.15%	95.67%	94.81%	94.85%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
17	17094 - 94.97%	615,642$	14,775,414$	18000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
44,124,973$	79,406,332$	54,456,332$	0$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
79,406,332$	44,068,964$	0$	20	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
10,465,918$	80	436,848$	34,947,840$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Compte Bancaire Actuel	Compte Bancaire Projeté
35,542,240$	30,312,651$	5,236,329$

Cap Salarial de la Saison Éstimé	Cap Salarial Disponible	Cap Salarial Maximum	Au dessus du Plafond Salarial Minimum
79,406,332$	2,093,668$	81,500,000$	19,206,332$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Claude Giroux	AGE:31	PO:0	OV:74
James van Riemsdyk	AGE:30	PO:0	OV:70
Jeff Skinner	AGE:27	PO:0	OV:70
Micheal Ferland	AGE:27	PO:0	OV:69
Tyler Bertuzzi	AGE:24	PO:0	OV:69
Evan Rodrigues	AGE:26	PO:0	OV:66
Tobias Rieder	AGE:26	PO:0	OV:65
Christoffer Ehn	AGE:23	PO:0	OV:64
Joel Farabee	AGE:19	PO:0	OV:64
J.C. Beaudin	AGE:22	PO:0	OV:61

Claude Giroux	AGE:31	PO:0	OV:74
Jeff Skinner	AGE:27	PO:0	OV:70
Nazem Kadri	AGE:29	PO:0	OV:70
Cody Eakin	AGE:28	PO:0	OV:68
Evan Rodrigues	AGE:26	PO:0	OV:66
Martin Necas	AGE:20	PO:0	OV:66
Riley Nash	AGE:30	PO:0	OV:65
Tobias Rieder	AGE:26	PO:0	OV:65
Christoffer Ehn	AGE:23	PO:0	OV:64
Mikhail Vorobyev	AGE:22	PO:0	OV:62
J.C. Beaudin	AGE:22	PO:0	OV:61

Claude Giroux	AGE:31	PO:0	OV:74
Tom Wilson	AGE:25	PO:0	OV:72
Jeff Skinner	AGE:27	PO:0	OV:70
Micheal Ferland	AGE:27	PO:0	OV:69
Tyler Bertuzzi	AGE:24	PO:0	OV:69
Ondrej Kase	AGE:23	PO:0	OV:67
Evan Rodrigues	AGE:26	PO:0	OV:66
Martin Necas	AGE:20	PO:0	OV:66
Riley Nash	AGE:30	PO:0	OV:65
Martin Frk	AGE:26	PO:0	OV:65
Tobias Rieder	AGE:26	PO:0	OV:65
Christian Fischer	AGE:22	PO:0	OV:63
Matt Read	AGE:33	PO:0	OV:63
Keegan Kolesar	AGE:22	PO:0	OV:62

Défense #1

Défense #2

Gardien

Jacob Trouba	AGE:25	PO:0	OV:71
Torey Krug	AGE:28	PO:0	OV:71
Brady Skjei	AGE:25	PO:0	OV:70
Justin Braun	AGE:32	PO:0	OV:67

Devon Toews	AGE:25	PO:0	OV:67
Dylan DeMelo	AGE:26	PO:0	OV:66
Dan Hamhuis	AGE:36	PO:0	OV:64
Michael Paliotta	AGE:26	PO:0	OV:59

Devan Dubnyk	AGE:33	PO:0	OV:76
Hunter Miska	AGE:24	PO:0	OV:65
Keith Kinkaid	AGE:30	PO:0	OV:65
Jon Gillies	AGE:25	PO:0	OV:64

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	Lien
Andrei Markov	Flyers
Arvid Costmar	Flyers	9	124
Bobby Butler	Flyers			Lien
Clinston Franklin	Flyers	4	122
Conner Hurley	Flyers	3	77
Dan Girardi	Flyers			Lien
Dennis Rasmussen	Flyers
Greg Rallo	Flyers
Gustav Possler	Flyers	3	68
Hayden Hawkey	Flyers	4	153
Henri Ikonen	Flyers
Jakub Kindl	Flyers
Joel Vermin	Flyers
Michael Houser	Flyers
Viktor Loov	Flyers

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6
10			PHI	DET
11	PHI	PHI	WIN PHI	PHI	PHI	PHI
12	PHI	PHI	PHI	PHI	PHI	PHI
13	PHI	PHI	PHI	PHI	PHI	PHI
14	PHI	PHI	PHI	PHI	PHI	PHI

[2020-12-17 9:54:56 PM] - TRADE : From Golden Knights to Flyers : James van Riemsdyk (70), Dylan DeMelo (66).
[2020-12-17 9:54:56 PM] - TRADE : From Flyers to Golden Knights : Tyler Johnson (69), Jack Johnson (68).
[2020-11-11 8:28:46 PM] - Matt Read was added to Flyers.
[2020-11-11 8:28:46 PM] - Flyers claimed Matt Read from waivers by Penguins for $0.
[2020-11-11 8:28:37 PM] - Flyers show interest in Matt Read from waiver.
[2020-10-19 7:15:24 PM] - Torey Krug has been selected as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Jeff Skinner is no longer as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Tom Wilson has been selected as assistant for Flyers.
[2020-10-19 7:15:24 PM] - Torey Krug is no longer as assistant for Flyers.
[2020-10-08 7:01:21 PM] - Luke Schenn has been selected as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Dillon Heatherington has been selected as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Phantoms.
[2020-10-08 7:01:21 PM] - Riley Nash has been selected as captain for Phantoms.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer captain for Phantoms.
[2020-10-08 7:01:21 PM] - Torey Krug has been selected as assistant for Flyers.
[2020-10-08 7:01:21 PM] - Unknown Player is no longer as assistant for Flyers.
[2020-09-26 11:21:05 PM] - TRADE : From Flyers to Avalanche : Matt Nieto (66).
[2020-09-26 11:21:05 PM] - TRADE : From Avalanche to Flyers : Ondrej Kase (67).
[2020-07-12 2:48:03 PM] - Flyers drafts Arvid Costmar as the #124 overall pick in the Entry Draft of year 9.
[2020-05-30 7:52:43 PM] - Joel Farabee was added to Flyers.
[2020-05-29 10:11:47 PM] - Flyers are the Playoffs Champions for year 8!

[2021-01-03 11:31:51 PM] Last 30 Days Farm Star : 1 - Ben Street of Devils (20-16-36) / 2 - Matt Puempel of Senators (14-16-30) / 3 - Christoffer Ehn of Phantoms (15-8-23)
[2020-12-25 9:28:44 PM] Christoffer Ehn from Phantoms has scored a Hat Trick!
[2020-12-24 8:50:35 PM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-19 7:38:12 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-19 7:36:31 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-19 7:35:15 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-18 10:43:48 PM] Auto Lines Partial Function has been run for Flyers.
[2020-12-17 9:54:56 PM] TRADE : From Golden Knights to Flyers : James van Riemsdyk (70), Dylan DeMelo (66).
[2020-12-17 9:54:56 PM] TRADE : From Flyers to Golden Knights : Tyler Johnson (69), Jack Johnson (68).
[2020-12-16 7:30:16 PM] Christoffer Ehn from Phantoms has scored a Hat Trick!
[2020-12-14 11:02:34 PM] Wild claimed Luke Schenn from waivers by Flyers for $0.
[2020-12-13 10:14:25 PM] Last 7 Days Farm Star : 1 - Ben Street of Devils (11-2-13) / 2 - Kyle Rau of Senators (9-1-10) / 3 - Christian Fischer of Phantoms (6-2-8)
[2020-12-13 10:14:25 PM] Last 7 Days Pro Star : 1 - Tom Wilson of Flyers (5-1-6) / 2 - Johnny Gaudreau of Canucks (4-4-8) / 3 - Viktor Arvidsson of Canadiens (4-1-5)
[2020-12-13 10:14:24 PM] Matt Read from Phantoms has scored a Hat Trick!
[2020-12-13 10:14:17 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-13 10:14:17 PM] Luke Schenn of Flyers was sent down to farm.
[2020-12-13 10:14:15 PM] Flyers placed Luke Schenn on waivers.
[2020-12-13 1:40:12 AM] Evan Rodrigues from Flyers is back from Right Leg Injury.
[2020-12-13 1:40:10 AM] Game 498 - Evan Rodrigues from Flyers is injured (Right Leg) and is out for 1 days.
[2020-12-13 1:40:00 AM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-10 9:38:34 PM] Successfully loaded Flyers lines done with Web Base Client and SQLite Database.
[2020-12-09 7:34:12 PM] Jack Johnson from Flyers is back from Bruised Right Foot Injury.
[2020-12-08 9:25:05 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-12-02 10:09:59 PM] Auto Lines Partial Function has been run for Flyers.
[2020-12-02 10:09:59 PM] Auto Roster Partial Function has been run for Flyers.
[2020-12-02 10:09:59 PM] Luke Schenn of Flyers was sent to pro.

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
2	82	41	31	0	2	2	3	3	257	214	43	41	20	17	0	0	1	3	0	134	112	22	41	21	14	0	2	1	0	3	123	102	21	82	257	456	713	4	6	84	81	87	8	2799	919	940	920	38	2275	623	834	1518	368	71	19.29%	324	46	85.80%	2	1663	3164	52.56%	1426	2710	52.62%	664	1268	52.37%	2085	1472	1849	596	1027	525
3	82	35	25	0	7	1	6	8	230	195	35	41	17	11	0	4	0	3	6	117	103	14	41	18	14	0	3	1	3	2	113	92	21	70	230	404	634	3	8	83	66	68	22	2578	851	836	848	93	2105	621	1031	1623	345	46	13.33%	349	46	86.82%	3	1555	3015	51.58%	1336	2661	50.21%	601	1203	49.96%	2089	1470	1886	591	1030	522
4	82	40	30	0	0	7	3	2	226	207	19	41	26	11	0	0	3	0	1	128	99	29	41	14	19	0	0	4	3	1	98	108	-10	80	226	398	624	0	5	77	78	68	4	2354	746	764	834	25	2150	623	672	1796	247	38	15.38%	256	55	78.52%	1	1411	2758	51.16%	1384	2662	51.99%	657	1231	53.37%	1998	1397	1903	605	1055	521
5	82	47	23	0	4	3	3	2	285	205	80	41	24	12	0	2	2	1	0	138	91	47	41	23	11	0	2	1	2	2	147	114	33	94	285	510	795	3	6	92	90	96	8	2677	855	863	940	39	2221	600	564	1634	273	56	20.51%	229	40	82.53%	0	1593	2974	53.56%	1396	2636	52.96%	741	1346	55.05%	2054	1432	1831	597	1072	547
6	82	31	34	0	6	6	3	2	231	252	-21	41	14	16	0	5	3	3	0	125	128	-3	41	17	18	0	1	3	0	2	106	124	-18	62	231	425	656	2	0	79	74	69	11	2631	865	880	855	54	2586	688	683	1935	306	54	17.65%	273	58	78.75%	1	1568	2973	52.74%	1538	2901	53.02%	679	1263	53.76%	2037	1447	1916	581	1013	510
7	82	46	19	0	5	8	2	2	258	206	52	41	27	6	0	2	3	2	1	136	94	42	41	19	13	0	3	5	0	1	122	112	10	92	258	460	718	1	4	84	84	83	8	2649	843	894	888	41	2392	689	624	1874	281	54	19.22%	260	52	80.00%	2	1540	2930	52.56%	1447	2736	52.89%	614	1196	51.34%	2070	1484	1888	568	1000	509
8	82	37	27	0	4	2	6	6	224	194	30	41	22	11	0	2	2	2	2	119	90	29	41	15	16	0	2	0	4	4	105	104	1	102	224	405	629	1	3	75	59	80	16	2315	792	732	735	102	2251	658	813	1940	376	70	18.62%	347	49	85.88%	2	1531	2840	53.91%	1428	2793	51.13%	614	1194	51.42%	2036	1411	1913	615	1046	525
8	82	37	27	0	4	2	6	6	224	194	30	41	22	11	0	2	2	2	2	119	90	29	41	15	16	0	2	0	4	4	105	104	1	102	224	405	629	1	3	75	59	80	16	2315	792	732	735	102	2251	658	813	1940	376	70	18.62%	347	49	85.88%	2	1531	2840	53.91%	1428	2793	51.13%	614	1194	51.42%	2036	1411	1913	615	1046	525
9	47	16	22	0	7	0	1	1	126	133	-7	24	5	14	0	3	0	1	1	58	67	-9	23	11	8	0	4	0	0	0	68	66	2	49	126	222	348	1	3	36	42	40	10	1347	430	432	464	28	1359	399	496	1065	171	31	18.13%	203	37	81.77%	3	815	1624	50.18%	831	1670	49.76%	341	681	50.07%	1121	778	1132	348	585	290
Total Saison Régulière	703	330	238	0	39	31	33	32	2061	1800	261	352	177	109	0	20	16	17	13	1074	874	200	351	153	129	0	19	15	16	19	987	926	61	733	2061	3685	5746	16	38	685	633	671	103	21665	7093	7073	7219	522	19590	5559	6530	15325	2743	490	17.86%	2588	432	83.31%	16	13207	25118	52.58%	12214	23562	51.84%	5525	10576	52.24%	17532	12303	16235	5120	8878	4479
Séries
2	25	16	9	0	0	0	0	0	80	69	11	11	7	4	0	0	0	0	0	38	27	11	14	9	5	0	0	0	0	0	42	42	0	32	80	146	226	0	2	23	32	22	3	849	208	289	254	98	864	268	297	520	115	22	19.13%	101	16	84.16%	0	501	980	51.12%	508	1000	50.80%	194	391	49.62%	678	476	645	204	346	172
3	17	10	7	0	0	0	0	0	44	41	3	9	4	5	0	0	0	0	0	24	28	-4	8	6	2	0	0	0	0	0	20	13	7	20	44	80	124	0	1	8	20	15	1	462	122	159	165	16	428	122	242	369	90	8	8.89%	66	8	87.88%	0	307	616	49.84%	272	559	48.66%	115	239	48.12%	447	312	383	124	213	110
4	4	0	4	0	0	0	0	0	9	13	-4	2	0	2	0	0	0	0	0	5	7	-2	2	0	2	0	0	0	0	0	4	6	-2	0	9	16	25	0	0	4	1	4	0	101	28	33	39	1	116	28	30	101	8	1	12.50%	9	1	88.89%	0	64	127	50.39%	59	122	48.36%	38	65	58.46%	98	69	93	28	54	27
5	24	13	11	0	0	0	0	0	63	59	4	13	6	7	0	0	0	0	0	36	39	-3	11	7	4	0	0	0	0	0	27	20	7	26	63	112	175	1	4	24	19	19	1	828	251	246	244	87	819	236	188	462	77	15	19.48%	78	13	83.33%	0	519	956	54.29%	483	942	51.27%	197	379	51.98%	611	426	614	190	328	160
7	20	16	4	0	0	0	0	0	77	46	31	11	8	3	0	0	0	0	0	40	26	14	9	8	1	0	0	0	0	0	37	20	17	32	77	139	216	0	0	30	21	23	3	701	221	209	256	15	588	157	138	447	63	11	17.46%	56	11	80.36%	0	384	723	53.11%	363	700	51.86%	175	337	51.93%	503	360	473	142	253	129
8	27	16	11	0	0	0	0	0	77	75	2	13	8	5	0	0	0	0	0	36	30	6	14	8	6	0	0	0	0	0	41	45	-4	32	77	137	214	1	0	28	20	23	6	830	248	250	272	60	822	227	332	634	115	22	19.13%	131	22	83.21%	1	521	1050	49.62%	566	1033	54.79%	224	432	51.85%	691	471	687	220	373	184
Total Séries	117	71	46	0	0	0	0	0	350	303	47	59	33	26	0	0	0	0	0	179	157	22	58	38	20	0	0	0	0	0	171	146	25	142	350	630	980	2	7	117	113	106	14	3771	1078	1186	1230	277	3637	1038	1227	2533	468	79	16.88%	441	71	83.90%	1	2296	4452	51.57%	2251	4356	51.68%	943	1843	51.17%	3030	2116	2897	911	1569	785