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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	Joe Thornton	X				100.00	63	43	80	81	86	89	76	75	82	80	71	55	72	99	90	36	61	84	0
2	Sebastian Aho	X	X			100.00	65	42	84	91	61	89	93	83	75	75	81	60	77	56	55	76	61	81	0
3	Clayton Keller	X	X	X		100.00	56	42	84	89	58	89	97	81	78	80	75	60	71	53	52	89	61	79	0
4	Mika Zibanejad	X				100.00	71	41	88	84	84	88	88	72	81	61	81	69	76	66	60	85	61	79	0
5	James van Riemsdyk		X			100.00	60	42	83	76	83	82	97	77	50	57	84	59	79	74	64	73	60	78	0
6	Alexander Steen	X	X	X		100.00	64	42	84	82	75	90	91	80	66	71	67	76	69	85	68	43	61	77	0
7	Kyle Okposo			X		100.00	66	43	81	77	77	87	94	78	69	69	67	57	68	76	63	69	61	77	0
8	Nick Bonino	X	X			100.00	59	41	85	85	72	84	86	75	84	55	63	89	70	69	62	39	61	75	0
9	Travis Konecny		X	X		100.00	70	43	80	84	60	82	97	75	60	62	75	63	72	56	53	81	61	75	0
10	Kevin Hayes	X	X	X		100.00	62	41	86	79	87	87	92	79	81	60	77	72	75	62	58	77	61	73	0
11	Cody Eakin	X				100.00	64	42	84	77	68	82	96	70	82	56	61	84	68	68	59	54	61	72	0
12	Nolan Patrick	X				100.00	63	42	78	79	79	82	89	80	81	58	64	60	70	52	51	93	61	72	0
13	Jaccob Slavin				X	99.00	62	41	92	72	79	91	97	75	30	62	58	91	69	59	60	57	61	76	0
14	Brian Dumoulin				X	100.00	70	42	89	77	82	86	97	71	30	54	55	87	68	59	60	61	61	75	0
15	Darnell Nurse				X	100.00	79	45	80	82	86	89	97	72	30	60	56	80	69	57	58	86	61	75	0
16	Ian Cole				X	100.00	72	45	75	67	79	80	83	75	30	59	57	86	67	66	60	67	61	74	0
17	Sami Vatanen				X	100.00	71	43	85	82	63	90	89	81	30	70	55	79	66	63	57	51	61	74	0
18	Esa Lindell				X	100.00	68	42	89	70	81	90	96	76	30	60	57	79	68	56	55	64	61	73	0
Rayé
1	Valentin Zykov (R)			X		100.00	66	44	68	75	81	61	92	77	50	68	70	60	67	50	50	76	25	73	0
2	Marcus Foligno		X			100.00	84	45	68	71	87	77	93	69	67	56	58	70	66	66	60	52	20	68	0

	MOYENNE D'ÉQUIPE					99.95	67	43	82	79	76	85	92	76	59	64	67	72	70	65	60	66	57	76

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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	Antti Raanta	99.00	84	88	88	79	91	95	94	92	96	82	81	60	72	36	60	84	0
2	Antti Niemi	100.00	76	73	85	86	79	83	83	80	81	74	74	83	80	23	61	78	0
Rayé
1	Alex Stalock	100.00	78	78	86	78	83	83	81	84	82	76	75	57	68	47	20	76	0

	MOYENNE D'ÉQUIPE	99.67	79	80	86	81	84	87	86	85	86	77	77	67	73	35	47	79

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Bruce Cassidy	69	92	93	86	77	62	66	CAN	52	4	4,000,000$

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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	GA	TA	HT	P/20	PSG	PSS	FW	S1	S2	S3
1	Clayton Keller	Flyers	C/LW/RW	30	14	26	40	8	12	0	38	31	125	38	85	11.20%	9	628	20.94	7	15	22	34	111	0	0	0	0	41	0	2	45.76%	59	34	9	2	1.27	0	0	0	5	1	4
2	Sebastian Aho	Flyers	C/LW	30	14	26	40	11	10	0	30	22	128	44	74	10.94%	15	566	18.87	6	12	18	24	109	0	0	0	0	4	2	1	44.93%	69	37	9	0	1.41	2	5	0	0	5	2
3	Joe Thornton	Flyers	C	30	14	19	33	4	42	0	45	44	74	15	30	18.92%	9	565	18.86	6	8	14	16	107	0	0	0	0	5	4	0	51.65%	786	9	4	0	1.17	0	1	0	1	3	1
4	Kevin Hayes	Flyers	C/LW/RW	30	8	13	21	14	6	0	37	33	93	30	50	8.60%	6	508	16.94	3	3	6	10	80	0	0	0	3	43	1	1	42.11%	19	24	10	0	0.83	0	5	0	0	0	0
5	Mika Zibanejad	Flyers	C	30	5	16	21	13	10	0	34	41	72	27	50	6.94%	12	481	16.06	1	7	8	10	90	0	0	0	0	2	0	0	56.96%	481	19	9	0	0.87	1	5	0	0	1	1
6	James van Riemsdyk	Flyers	LW	31	9	8	17	3	25	5	38	30	84	18	47	10.71%	7	505	16.29	1	2	3	9	86	0	0	0	1	12	1	1	46.15%	26	8	5	0	0.67	0	1	1	2	3	0
7	Jaccob Slavin	Flyers	D	30	4	11	15	13	4	0	33	57	55	29	12	7.27%	59	866	28.87	2	5	7	9	123	0	1	1	1	121	2	0	0.00%	0	8	29	0	0.35	0	0	0	0	1	0
8	Alexander Steen	Flyers	C/LW/RW	30	5	6	11	3	6	0	37	24	77	22	41	6.49%	16	409	13.64	0	0	0	0	8	1	0	1	4	78	1	1	48.72%	39	12	6	0	0.54	0	0	0	1	0	1
9	Cody Eakin	Flyers	C	30	6	3	9	1	8	0	33	42	39	10	21	15.38%	16	482	16.10	3	0	3	10	71	0	2	2	6	111	1	0	47.24%	381	4	10	0	0.37	0	0	0	0	1	1
10	Sami Vatanen	Flyers	D	30	1	8	9	2	10	0	27	22	36	7	11	2.78%	12	457	15.24	1	5	6	16	121	0	0	0	0	4	0	0	0.00%	0	8	12	0	0.39	0	0	0	0	0	0
11	Darnell Nurse	Flyers	D	30	2	6	8	10	20	0	36	41	33	19	13	6.06%	33	633	21.12	1	0	1	1	7	0	0	0	1	76	0	1	0.00%	0	5	25	0	0.25	0	0	0	0	1	1
12	Brian Dumoulin	Flyers	D	30	2	5	7	8	10	0	25	42	31	21	16	6.45%	43	657	21.92	0	0	0	0	5	0	0	0	3	122	0	0	0.00%	0	2	37	0	0.21	0	0	0	0	0	2
13	Ian Cole	Flyers	D	30	1	5	6	4	28	0	28	28	17	10	8	5.88%	34	510	17.02	0	0	0	0	1	0	0	0	0	66	0	0	0.00%	0	2	15	0	0.23	0	0	0	0	0	0
14	Nick Bonino	Flyers	C/LW	30	3	3	6	1	2	0	22	26	43	20	28	6.98%	16	380	12.67	0	0	0	0	0	1	0	1	6	116	1	0	61.29%	31	14	15	0	0.32	0	0	0	0	1	0
15	Travis Konecny	Flyers	LW/RW	30	1	5	6	3	26	0	37	10	76	10	39	1.32%	3	309	10.32	0	0	0	1	3	0	0	0	0	0	0	0	45.00%	20	18	5	0	0.39	1	3	0	0	0	0
16	Esa Lindell	Flyers	D	30	1	3	4	4	0	0	16	22	20	12	12	5.00%	20	423	14.11	1	0	1	2	71	0	0	0	0	23	0	0	0.00%	0	1	8	0	0.19	0	0	0	0	0	0
17	Kyle Okposo	Flyers	RW	30	3	0	3	-3	26	0	20	9	43	21	23	6.98%	3	261	8.73	0	0	0	1	8	0	0	0	0	0	2	0	60.00%	5	13	0	0	0.23	0	0	0	1	0	0
18	Nolan Patrick	Flyers	C	30	2	1	3	-2	18	0	20	13	28	14	17	7.14%	4	236	7.87	0	0	0	0	0	0	0	0	0	0	1	0	48.18%	110	3	4	0	0.25	0	0	0	0	0	1
19	Valentin Zykov	Flyers	RW	2	0	0	0	0	0	0	1	1	2	0	0	0.00%	0	13	6.62	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0.00	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				543	95	164	259	97	263	5	557	538	1076	367	577	8.83%	317	8896	16.38	32	57	89	143	1008	2	3	5	25	831	16	7	51.38%	2026	221	212	2	0.58	4	20	1	10	17	14

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Antti Raanta	Flyers	26	15	6	5	0.938	2.05	1578	54	874	398	2	1	0.529	17	26	4	6	1	4
2	Antti Niemi	Flyers	4	2	2	0	0.924	2.47	243	10	131	64	0	0	1.000	3	4	26	0	0	1
Stats d'équipe Total ou en Moyenne			30	17	8	5	0.936	2.11	1821	64	1005	462	2	1	0.600	20	30	30	6	1	5

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	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	Link
Alex Stalock	Flyers	G	30	1987-07-28	No	191 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro & Farm	750,000$	750,000$	485,294$	No							Lien
Alexander Steen	Flyers	C/LW/RW	33	1984-03-01	No	211 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	5,750,000$	5,750,000$	3,720,588$	No	5,750,000$	5,750,000$					Lien
Antti Niemi	Flyers	G	34	1983-08-29	No	215 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro & Farm	900,000$	900,000$	582,353$	No							Lien
Antti Raanta	Flyers	G	28	1989-05-12	No	195 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	4,250,000$	4,250,000$	2,750,000$	No	4,250,000$	4,250,000$					Lien
Brian Dumoulin	Flyers	D	26	1991-09-06	No	207 Lbs	6 ft4	No	No	No	5	Contrat d'Entrée	Pro & Farm	4,100,000$	4,100,000$	2,652,941$	No	4,100,000$	4,100,000$	4,100,000$	4,100,000$			Lien
Clayton Keller	Flyers	C/LW/RW	19	1998-07-29	No	170 Lbs	5 ft10	No	No	No	2	Contrat d'Entrée	Pro & Farm	885,833$	885,833$	573,186$	No	885,833$						Lien
Cody Eakin	Flyers	C	26	1991-05-24	No	190 Lbs	6 ft0	No	No	No	1	Contrat d'Entrée	Pro & Farm	900,000$	900,000$	582,353$	No							Lien
Darnell Nurse	Flyers	D	22	1995-02-04	No	221 Lbs	6 ft4	No	No	No	2	Contrat d'Entrée	Pro & Farm	3,200,000$	3,200,000$	2,070,588$	No	3,200,000$						Lien
Esa Lindell	Flyers	D	23	1994-05-23	No	213 Lbs	6 ft3	No	No	No	1	Contrat d'Entrée	Pro & Farm	2,200,000$	2,200,000$	1,423,529$	No							Lien
Ian Cole	Flyers	D	28	1989-02-21	No	219 Lbs	6 ft1	No	No	No	3	Sans Restriction	Pro & Farm	4,250,000$	4,250,000$	2,750,000$	No	4,250,000$	4,250,000$					Lien
Jaccob Slavin	Flyers	D	23	1994-05-01	No	205 Lbs	6 ft3	No	No	No	7	Contrat d'Entrée	Pro & Farm	5,300,000$	5,300,000$	3,429,412$	No	5,300,000$	5,300,000$	5,300,000$	5,300,000$	5,300,000$	5,300,000$	Lien
James van Riemsdyk	Flyers	LW	28	1989-05-04	No	217 Lbs	6 ft3	No	No	No	5	Sans Restriction	Pro & Farm	7,000,000$	7,000,000$	4,529,412$	No	7,000,000$	7,000,000$	7,000,000$	7,000,000$			Lien
Joe Thornton	Flyers	C	38	1979-07-02	No	220 Lbs	6 ft4	No	No	No	1	Sans Restriction	Pro & Farm	6,000,000$	6,000,000$	3,882,353$	No							Lien
Kevin Hayes	Flyers	C/LW/RW	25	1992-05-08	No	217 Lbs	6 ft5	No	No	No	1	Contrat d'Entrée	Pro & Farm	5,175,000$	5,175,000$	3,348,529$	No							Lien
Kyle Okposo	Flyers	RW	29	1988-04-16	No	220 Lbs	6 ft0	No	No	No	5	Sans Restriction	Pro & Farm	6,000,000$	6,000,000$	3,882,353$	No	6,000,000$	6,000,000$	6,000,000$	6,000,000$			Lien
Marcus Foligno	Flyers	LW	26	1991-08-10	No	232 Lbs	6 ft3	No	No	No	3	Contrat d'Entrée	Pro & Farm	2,875,000$	2,875,000$	1,860,294$	No	2,875,000$	2,875,000$					Lien
Mika Zibanejad	Flyers	C	24	1993-04-18	No	227 Lbs	6 ft2	No	No	No	4	Contrat d'Entrée	Pro & Farm	5,350,000$	5,350,000$	3,461,765$	No	5,350,000$	5,350,000$	5,350,000$				Lien
Nick Bonino	Flyers	C/LW	29	1988-04-20	No	196 Lbs	6 ft1	No	No	No	2	Sans Restriction	Pro & Farm	4,100,000$	4,100,000$	2,652,941$	No	4,100,000$						Lien
Nolan Patrick	Flyers	C	19	1998-09-19	No	198 Lbs	6 ft2	No	No	No	2	Contrat d'Entrée	Pro & Farm	925,000$	925,000$	598,529$	No	925,000$						Lien
Sami Vatanen	Flyers	D	26	1991-06-03	No	185 Lbs	5 ft10	No	No	No	2	Contrat d'Entrée	Pro & Farm	4,875,000$	4,875,000$	3,154,412$	No	4,875,000$						Lien
Sebastian Aho	Flyers	C/LW	20	1997-07-26	No	172 Lbs	5 ft11	No	No	No	1	Contrat d'Entrée	Pro & Farm	925,000$	925,000$	598,529$	No							Lien
Travis Konecny	Flyers	LW/RW	20	1997-03-11	No	175 Lbs	5 ft10	No	No	No	1	Contrat d'Entrée	Pro & Farm	894,166$	894,166$	578,578$	No							Lien
Valentin Zykov	Flyers	RW	22	1995-05-15	Yes	224 Lbs	6 ft1	No	No	No	1	Contrat d'Entrée	Pro & Farm	750,000$	750,000$	485,294$	No							Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	26.00	205 Lbs	6 ft1	2.48	3,363,261$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
77,354,999$	58,860,833$	44,875,000$	27,750,000$	22,400,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	James van Riemsdyk	Joe Thornton	Clayton Keller	35	0	1	4
2	Sebastian Aho	Mika Zibanejad	Kevin Hayes	30	1	1	3
3	Travis Konecny	Cody Eakin	Alexander Steen	20	2	2	1
4	Nick Bonino	Nolan Patrick	Kyle Okposo	15	1	3	1

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaccob Slavin	Darnell Nurse	40	0	2	3
2	Brian Dumoulin	Ian Cole	30	1	2	2
3	Sami Vatanen	Esa Lindell	20	1	2	2
4	Jaccob Slavin	Darnell Nurse	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	James van Riemsdyk	Joe Thornton	Clayton Keller	60	0	0	5
2	Sebastian Aho	Mika Zibanejad	Kevin Hayes	40	0	0	5

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaccob Slavin	Sami Vatanen	60	0	0	5
2	Cody Eakin	Esa Lindell	40	0	0	5

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Cody Eakin	Nick Bonino	60	1	4	0
2	Alexander Steen	Kevin Hayes	40	1	4	0

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaccob Slavin	Brian Dumoulin	60	1	4	0
2	Ian Cole	Darnell Nurse	40	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Cody Eakin	60	1	4	0	Jaccob Slavin	Brian Dumoulin	60	1	4	0
2	Nick Bonino	40	1	4	0	Esa Lindell	Darnell Nurse	40	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Sebastian Aho	Clayton Keller	60	0	1	4
2	Joe Thornton	James van Riemsdyk	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jaccob Slavin	Brian Dumoulin	60	1	2	2
2	Darnell Nurse	Ian Cole	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
James van Riemsdyk	Sebastian Aho	Clayton Keller	Jaccob Slavin	Sami Vatanen

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Nick Bonino	Cody Eakin	Alexander Steen	Jaccob Slavin	Brian Dumoulin

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
James van Riemsdyk, Travis Konecny, Nick Bonino	James van Riemsdyk, Travis Konecny	Nick Bonino

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Ian Cole, Esa Lindell, Brian Dumoulin	Ian Cole	Esa Lindell, Brian Dumoulin

Tirs de Pénalité
Sebastian Aho, Mika Zibanejad, Kevin Hayes, Travis Konecny, James van Riemsdyk

Gardien
#1 : Antti Raanta, #2 : Antti Niemi

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
1	Blackhawks	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	1	2	0	0	0	1	0	0	27	8	7	12	0	35	13	12	19	5	1	20.00%	6	0	100.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	20	10	22	10	17	8
2	Blue Jackets	2	2	0	0	0	0	0	0	13	3	10	1	1	0	0	0	0	0	0	8	1	7	1	1	0	0	0	0	0	0	5	2	3	4	1.000	13	21	34	0	0	3	4	6	0	75	19	25	31	0	80	13	10	38	11	5	45.45%	5	0	100.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	41	23	42	18	36	16
3	Blues	2	1	0	0	0	0	0	1	6	4	2	0	0	0	0	0	0	0	0	0	0	0	2	1	0	0	0	0	0	1	6	4	2	3	0.750	6	10	16	0	0	2	1	3	1	60	27	17	16	4	50	22	16	52	12	3	25.00%	8	1	87.50%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	45	24	40	18	39	19
4	Bruins	2	0	1	0	0	0	0	1	5	7	-2	1	0	1	0	0	0	0	0	3	4	-1	1	0	0	0	0	0	0	1	2	3	-1	1	0.250	5	10	15	0	0	1	1	3	1	72	20	26	25	5	70	24	16	33	8	1	12.50%	7	2	71.43%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	42	24	46	20	36	16
5	Capitals	3	2	1	0	0	0	0	0	7	6	1	2	1	1	0	0	0	0	0	4	4	0	1	1	0	0	0	0	0	0	3	2	1	4	0.667	7	13	20	0	0	4	1	2	0	105	50	24	31	0	95	20	24	53	12	1	8.33%	12	0	100.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	65	37	62	29	52	24
6	Devils	2	0	1	0	0	1	0	0	2	5	-3	1	0	1	0	0	0	0	0	1	3	-2	1	0	0	0	0	1	0	0	1	2	-1	1	0.250	2	3	5	0	0	0	2	0	0	73	24	29	20	0	69	25	12	37	12	1	8.33%	6	2	66.67%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	44	25	42	15	33	17
7	Flames	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	3	1	2	1.000	4	6	10	0	0	2	0	2	0	31	17	4	10	0	36	12	10	21	2	0	0.00%	5	1	80.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	21	12	22	9	15	6
8	Golden Knights	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	2	4	0	0	1	1	0	0	31	10	13	8	0	41	19	8	26	2	0	0.00%	4	0	100.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	20	10	21	8	17	9
9	Islanders	5	2	2	0	0	0	0	1	10	12	-2	2	1	1	0	0	0	0	0	4	5	-1	3	1	1	0	0	0	0	1	6	7	-1	5	0.500	10	19	29	1	0	3	6	1	1	200	75	59	66	6	178	54	50	83	21	4	19.05%	25	7	72.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	107	66	114	46	82	41
10	Jets	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	1	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	6	10	0	0	1	2	1	0	32	9	12	11	0	39	11	8	23	4	1	25.00%	4	0	100.00%	1	420	801	52.43%	408	792	51.52%	213	416	51.20%	21	13	21	9	16	8
11	Lightning	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	2	1	2	1.000	3	5	8	0	0	0	2	1	0	29	3	13	13	0	40	9	14	16	2	0	0.00%	6	1	83.33%	1	420	801	52.43%	408	792	51.52%	213	416	51.20%	18	9	23	9	18	8
12	Maple Leafs	2	1	0	0	1	0	0	0	10	7	3	1	0	0	0	1	0	0	0	4	3	1	1	1	0	0	0	0	0	0	6	4	2	4	1.000	10	19	29	0	0	1	5	3	1	80	34	20	24	2	68	20	10	32	11	3	27.27%	5	1	80.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	44	27	42	18	33	16
13	Panthers	2	1	1	0	0	0	0	0	10	4	6	0	0	0	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	0	10	4	6	2	0.500	10	20	30	0	0	1	4	5	0	67	22	27	18	0	63	25	14	34	11	4	36.36%	7	1	85.71%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	40	24	46	18	33	16
14	Penguins	3	2	1	0	0	0	0	0	13	6	7	2	2	0	0	0	0	0	0	12	4	8	1	0	1	0	0	0	0	0	1	2	-1	4	0.667	13	20	33	0	0	7	2	4	0	104	31	39	34	0	70	24	39	60	18	7	38.89%	17	3	82.35%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	61	33	63	29	54	26
15	Sharks	1	0	0	0	0	0	0	1	2	3	-1	1	0	0	0	0	0	0	1	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	2	4	6	0	0	0	1	1	0	42	15	11	16	3	29	13	12	11	1	0	0.00%	6	1	83.33%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	20	11	25	10	18	9
16	Stars	1	0	0	0	0	0	1	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	4	3	1	2	1.000	4	5	9	0	0	0	2	1	1	41	13	18	10	3	43	13	8	18	5	1	20.00%	4	2	50.00%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	23	13	21	9	19	9
	Total	30	15	8	0	1	1	1	4	96	69	27	14	7	5	0	1	0	0	1	45	31	14	16	8	3	0	0	1	1	3	51	38	13	39	0.650	96	164	260	1	0	26	35	33	5	1069	377	344	345	23	1006	317	263	556	137	32	23.36%	127	22	82.68%	2	420	801	52.43%	408	792	51.52%	213	416	51.20%	639	368	661	281	525	255
	_Since Last GM Reset	30	15	8	0	1	1	1	4	96	69	27	14	7	5	0	1	0	0	1	45	31	14	16	8	3	0	0	1	1	3	51	38	13	39	0.650	96	164	260	1	0	26	35	33	5	1069	377	344	345	23	1006	317	263	556	137	32	23.36%	127	22	82.68%	2	420	801	52.43%	408	792	51.52%	213	416	51.20%	639	368	661	281	525	255
	_Vs Conference	22	11	7	0	1	1	0	2	73	52	21	10	5	4	0	1	0	0	0	36	24	12	12	6	3	0	0	1	0	2	37	28	9	27	0.614	73	130	203	1	0	20	27	25	3	805	278	262	262	13	733	214	189	386	106	26	24.53%	90	17	81.11%	1	420	801	52.43%	408	792	51.52%	213	416	51.20%	465	271	484	205	380	184
	_Vs Division	15	8	5	0	0	1	0	1	45	32	13	8	5	3	0	0	0	0	0	29	17	12	7	3	2	0	0	1	0	1	16	15	1	18	0.600	45	76	121	1	0	17	15	13	1	557	199	176	182	6	492	136	135	271	74	18	24.32%	65	12	81.54%	0	420	801	52.43%	408	792	51.52%	213	416	51.20%	320	186	326	139	258	126

			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
30	39	L1	96	164	260	1069	1006	317	263	556	1	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
30	15	8	1	1	1	4	96	69

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
14	7	5	1	0	0	1	45	31

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	8	3	0	1	1	3	51	38

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	0	0	1	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
137	32	23.36%	127	22	82.68%	2

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
377	344	345	23	26	35	33	5

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
420	801	52.43%	408	792	51.52%	213	416	51.20%

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
639	368	661	281	525	255

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
4 - 2018-10-12	15	Penguins	3	Flyers	6	W			Sommaire du Match
6 - 2018-10-14	25	Flyers	5	Blue Jackets	2	W			Sommaire du Match
9 - 2018-10-17	36	Capitals	3	Flyers	2	L			Sommaire du Match
12 - 2018-10-20	52	Islanders	2	Flyers	3	W			Sommaire du Match
15 - 2018-10-23	68	Flyers	1	Penguins	2	L			Sommaire du Match
18 - 2018-10-26	74	Devils	3	Flyers	1	L			Sommaire du Match
20 - 2018-10-28	85	Flyers	1	Devils	2	L	X		Sommaire du Match
23 - 2018-10-31	100	Blue Jackets	1	Flyers	8	W			Sommaire du Match
24 - 2018-11-01	106	Flyers	3	Capitals	2	W			Sommaire du Match
29 - 2018-11-06	122	Flyers	3	Islanders	1	W			Sommaire du Match
31 - 2018-11-08	133	Maple Leafs	3	Flyers	4	W	X		Sommaire du Match
33 - 2018-11-10	139	Flyers	6	Maple Leafs	4	W			Sommaire du Match
36 - 2018-11-13	151	Flyers	5	Blues	2	W			Sommaire du Match
39 - 2018-11-16	162	Sharks	3	Flyers	2	L	X	X	Sommaire du Match
42 - 2018-11-19	173	Flyers	2	Islanders	3	L	X	X	Sommaire du Match
44 - 2018-11-21	186	Islanders	3	Flyers	1	L			Sommaire du Match
46 - 2018-11-23	195	Flyers	3	Lightning	2	W			Sommaire du Match
48 - 2018-11-25	205	Penguins	1	Flyers	6	W			Sommaire du Match
52 - 2018-11-29	219	Flyers	1	Blues	2	L	X	X	Sommaire du Match
54 - 2018-12-01	231	Jets	1	Flyers	4	W			Sommaire du Match
58 - 2018-12-05	241	Flyers	8	Panthers	1	W			Sommaire du Match
62 - 2018-12-09	255	Blackhawks	2	Flyers	1	L			Sommaire du Match
65 - 2018-12-12	269	Flyers	4	Stars	3	W	X	X	Sommaire du Match
68 - 2018-12-15	279	Flyers	4	Flames	3	W			Sommaire du Match
69 - 2018-12-16	285	Capitals	1	Flyers	2	W			Sommaire du Match
73 - 2018-12-20	300	Bruins	4	Flyers	3	L			Sommaire du Match
75 - 2018-12-22	310	Flyers	2	Bruins	3	L	X	X	Sommaire du Match
77 - 2018-12-24	322	Flyers	2	Panthers	3	L			Sommaire du Match
79 - 2018-12-26	329	Golden Knights	1	Flyers	2	W			Sommaire du Match
83 - 2018-12-30	345	Flyers	1	Islanders	3	L			Sommaire du Match
86 - 2019-01-02	355	Oilers	-	Flyers	-
89 - 2019-01-05	369	Flyers	-	Kings	-
91 - 2019-01-07	378	Capitals	-	Flyers	-
94 - 2019-01-10	394	Flyers	-	Oilers	-
97 - 2019-01-13	402	Blues	-	Flyers	-
101 - 2019-01-17	421	Stars	-	Flyers	-
104 - 2019-01-20	429	Flyers	-	Maple Leafs	-
106 - 2019-01-22	441	Flyers	-	Golden Knights	-
109 - 2019-01-25	451	Flyers	-	Devils	-
110 - 2019-01-26	455	Senateurs	-	Flyers	-
114 - 2019-01-30	474	Flyers	-	Predateurs	-
115 - 2019-01-31	479	Lightning	-	Flyers	-
118 - 2019-02-03	491	Flyers	-	Avalanche	-
120 - 2019-02-05	498	Flyers	-	Senateurs	-
122 - 2019-02-07	504	Canadiens	-	Flyers	-
125 - 2019-02-10	517	Flyers	-	Devils	-
127 - 2019-02-12	526	Lightning	-	Flyers	-
129 - 2019-02-14	540	Flyers	-	Ducks	-
133 - 2019-02-18	552	Avalanche	-	Flyers	-
138 - 2019-02-23	574	Sharks	-	Flyers	-
142 - 2019-02-27	593	Flyers	-	Penguins	-
143 - 2019-02-28	598	Kings	-	Flyers	-
147 - 2019-03-04	618	Predateurs	-	Flyers	-
149 - 2019-03-06	625	Flyers	-	Capitals	-
152 - 2019-03-09	640	Flyers	-	Penguins	-
153 - 2019-03-10	646	Canadiens	-	Flyers	-
157 - 2019-03-14	660	Flyers	-	Blue Jackets	-
159 - 2019-03-16	669	Ducks	-	Flyers	-
161 - 2019-03-18	679	Flyers	-	Canadiens	-
163 - 2019-03-20	692	Flyers	-	Jets	-
165 - 2019-03-22	696	Flames	-	Flyers	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
167 - 2019-03-24	702	Flyers	-	Sharks	-
170 - 2019-03-27	718	Devils	-	Flyers	-
173 - 2019-03-30	729	Flyers	-	Blue Jackets	-
176 - 2019-04-02	741	Flyers	-	Bruins	-
177 - 2019-04-03	744	Islanders	-	Flyers	-
180 - 2019-04-06	765	Panthers	-	Flyers	-
187 - 2019-04-13	788	Bruins	-	Flyers	-
189 - 2019-04-15	799	Flyers	-	Canadiens	-
193 - 2019-04-19	813	Blues	-	Flyers	-
197 - 2019-04-23	827	Flyers	-	Senateurs	-
199 - 2019-04-25	836	Senateurs	-	Flyers	-
201 - 2019-04-27	845	Flyers	-	Lightning	-
206 - 2019-05-02	858	Penguins	-	Flyers	-
208 - 2019-05-04	865	Flyers	-	Blackhawks	-
211 - 2019-05-07	878	Flyers	-	Sharks	-
213 - 2019-05-09	888	Maple Leafs	-	Flyers	-
217 - 2019-05-13	910	Devils	-	Flyers	-
222 - 2019-05-18	931	Panthers	-	Flyers	-
227 - 2019-05-23	947	Flyers	-	Capitals	-
230 - 2019-05-26	958	Blue Jackets	-	Flyers	-
235 - 2019-05-31	974	Blue Jackets	-	Flyers	-

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	160	100	75	50	300
Assistance	44,913	37,853	13,111	28,174	7,710
Attendance PCT	53.47%	54.08%	46.83%	50.31%	55.07%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
27	9412 - 52.29%	1,478,061$	20,692,855$	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
28,765,023$	77,354,999$	76,786,249$	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
77,354,999$	27,353,235$	0$	23	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
39,907,649$	154	341,828$	52,641,512$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
53,665,541$	77,354,999$	-2,478,864$	-16,236,756$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Sebastian Aho	AGE:20	PO:76	OV:81
Clayton Keller	AGE:19	PO:89	OV:79
James van Riemsdyk	AGE:28	PO:73	OV:78
Alexander Steen	AGE:33	PO:43	OV:77
Travis Konecny	AGE:20	PO:81	OV:75
Nick Bonino	AGE:29	PO:39	OV:75
Kevin Hayes	AGE:25	PO:77	OV:73
Marcus Foligno	AGE:26	PO:52	OV:68
Jordan Weal	AGE:25	PO:63	OV:67

Joe Thornton	AGE:38	PO:36	OV:84
Sebastian Aho	AGE:20	PO:76	OV:81
Clayton Keller	AGE:19	PO:89	OV:79
Mika Zibanejad	AGE:24	PO:85	OV:79
Alexander Steen	AGE:33	PO:43	OV:77
Nick Bonino	AGE:29	PO:39	OV:75
Kevin Hayes	AGE:25	PO:77	OV:73
Nolan Patrick	AGE:19	PO:93	OV:72
Cody Eakin	AGE:26	PO:54	OV:72
Jordan Weal	AGE:25	PO:63	OV:67

Clayton Keller	AGE:19	PO:89	OV:79
Kyle Okposo	AGE:29	PO:69	OV:77
Alexander Steen	AGE:33	PO:43	OV:77
Travis Konecny	AGE:20	PO:81	OV:75
Kevin Hayes	AGE:25	PO:77	OV:73
*Valentin Zykov	AGE:22	PO:76	OV:73
Jordan Weal	AGE:25	PO:63	OV:67

Défense #1

Défense #2

Gardien

Jaccob Slavin	AGE:23	PO:57	OV:76
Darnell Nurse	AGE:22	PO:86	OV:75
Brian Dumoulin	AGE:26	PO:61	OV:75
Ian Cole	AGE:28	PO:67	OV:74
Sami Vatanen	AGE:26	PO:51	OV:74

Esa Lindell	AGE:23	PO:64	OV:73
Thomas Chabot	AGE:20	PO:83	OV:70
Troy Stecher	AGE:23	PO:43	OV:68
Jordan Schmaltz	AGE:23	PO:78	OV:60
*Philippe Myers	AGE:20	PO:44	OV:60

Antti Raanta	AGE:28	PO:36	OV:84
Antti Niemi	AGE:34	PO:23	OV:78
Alex Stalock	AGE:30	PO:47	OV:76

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 Ruzicka	Flyers	2018	109
Antoine Morand	Flyers	2018	85
Benoit-Olivier Groulx	Flyers	2018	37
Cayden Primeau	Flyers	2018	119
Elias Petersson	Flyers	2017	5
Filip Johansson	Flyers	2018	47
Glen Gawdin	Flyers
Hudson Elynuik	Flyers	2018	107
Ilya Samsonov	Flyers	2015	22
Jack Studnicka	Flyers	2018	61
Joe Veleno	Flyers	2018	18
Maksim Sushko	Flyers	2018	95
Maksim Zhukov	Flyers	2018	83
Morgan Frost	Flyers	2017	27
Quinn Hughues	Flyers	2018	10
Ryan Merkley	Flyers	2018	35
Tye Smith	Flyers	2018	15
Tyler Benson	Flyers	2018	71
Vitaly Abramov	Flyers	2016	65

Choix au Repêchage

Année	R1	R2	R3	R4	R5
3	PHI FLA ANA	PHI NHS ANA	PHI ANA DAL	PHI ANA DAL	PHI ANA DAL
4	PHI EDM	PHI FLA	PHI	PHI	PHI
5	PHI	PHI	PHI	PHI	PHI
6	PHI	PHI	PHI	PHI	PHI
7	PHI	PHI	PHI	PHI	PHI

[2018-11-21 21:48:09] - New Record for Team's Most Points (24) in 1 Game for Flyers!
[2018-11-21 21:48:09] - New Record for Team's Most Assists (16) in 1 Game for Flyers!
[2018-11-21 21:48:09] - New Record for Team's Most Points (24) in 1 Game for Flyers!
[2018-11-21 21:48:09] - New Record for Team's Most Assists (16) in 1 Game for Flyers!
[2018-11-16 22:19:02] - New Record for Team's Most Hits (31) in 1 Game for Flyers!
[2018-10-28 00:36:55] - New Record for Team's Most Points (23) in 1 Game for Flyers!
[2018-10-28 00:36:55] - New Record for Team's Most Assists (15) in 1 Game for Flyers!
[2018-10-28 00:36:55] - New Record for Team's Most Goals (8) in 1 Game for Flyers!
[2018-10-16 22:00:19] - TRADE : From Penguins to Flyers : James van Riemsdyk (78), Alex Stalock (77).
[2018-10-16 22:00:19] - TRADE : From Flyers to Penguins : Brandon Saad (71), Michal Neuvirth (78), Y:3-RND:2-DAL.
[2018-10-03 20:42:40] - Cody Eakin was added to Flyers.
[2018-10-03 20:42:22] - Antti Niemi was added to Flyers.
[2018-10-01 23:41:34] - Nick Bonino was added to Flyers.
[2018-10-01 23:41:26] - Joe Thornton was added to Flyers.
[2018-09-24 22:25:17] - TRADE : From Stars to Flyers : Clayton Keller (79).
[2018-09-24 22:25:17] - TRADE : From Flyers to Stars : Cale Makar (P), Jake Bean (P).
[2018-09-23 19:32:02] - TRADE : From Flyers to Penguins : John Carlson (80).
[2018-09-23 19:32:02] - TRADE : From Penguins to Flyers : Darnell Nurse (75), Y:4-RND:1-EDM, Y:3-RND:2-NHS.
[2018-09-10 13:05:23] - Troy Brouwer was released.
[2018-09-10 13:05:23] - Flyers paid 0 $ to release Troy Brouwer.
[2018-09-10 13:05:18] - Shawn Matthias was released.
[2018-09-10 13:05:18] - Flyers paid 0 $ to release Shawn Matthias.
[2018-09-10 13:05:07] - Jori Lehtera was released.
[2018-09-10 13:05:07] - Flyers paid 0 $ to release Jori Lehtera.
[2018-09-10 13:05:02] - Chris Kunitz was released.
[2018-09-10 13:05:02] - Flyers paid 0 $ to release Chris Kunitz.
[2018-09-10 13:04:23] - Jeff Glass was released.
[2018-09-10 13:04:23] - Flyers paid 0 $ to release Jeff Glass.
[2018-09-10 13:04:19] - Jared Boll was released.
[2018-09-10 13:04:19] - Flyers paid 0 $ to release Jared Boll.
[2018-09-10 13:04:14] - Ales Hemsky was released.
[2018-09-10 13:04:14] - Flyers paid 0 $ to release Ales Hemsky.
[2018-09-08 20:46:10] - TRADE : From Stars to Flyers : John Carlson (80), Y:3-RND:1-FLA, Y:4-RND:2-FLA.
[2018-09-08 20:46:10] - TRADE : From Flyers to Stars : Brandon Carlo (73), Ryan Kesler (74), Y:3-RND:1-DAL.
[2018-08-29 21:33:01] - Valentin Zykov was added to Flyers.
[2018-08-29 21:31:09] - Philippe Myers was added to Flyers.
[2018-08-29 20:48:40] - Cayden Primeau has been added to Flyers.
[2018-08-29 20:47:46] - Adam Ruzicka has been added to Flyers.
[2018-08-29 20:47:11] - Hudson Elynuik has been added to Flyers.
[2018-08-29 20:35:42] - Maksim Sushko has been added to Flyers.
[2018-08-29 20:35:19] - Antoine Morand has been added to Flyers.
[2018-08-29 20:34:59] - Maksim Zhukov has been added to Flyers.
[2018-08-29 20:21:46] - Tyler Benson has been added to Flyers.
[2018-08-29 20:21:10] - Jack Studnicka has been added to Flyers.
[2018-08-29 20:20:43] - Phillippe Myers has been added to Flyers.
[2018-08-19 21:51:03] - Filip Johansson has been added to Flyers.
[2018-08-19 21:50:31] - Benoit-Olivier Groulx has been added to Flyers.
[2018-08-19 21:49:50] - Ryan Merkley has been added to Flyers.
[2018-08-19 21:34:53] - Joe Veleno has been added to Flyers.
[2018-08-19 21:34:37] - Tye Smith has been added to Flyers.
[2018-08-19 21:31:44] - Quinn Hughues has been added to Flyers.
[2018-06-18 18:08:00] - Phantoms was eliminated at round 4 of year 1.
[2018-05-28 20:21:26] - Flyers was eliminated at round 1 of year 1.
[2018-05-09 23:40:32] - New Record for Team's Most Shots (50) in 1 Game for Flyers!
[2018-04-30 22:26:10] - New Record for Team's Most Penalties Minutes (25) in 1 Game for Flyers!

[2018-12-10 20:52:58] Current fund for Flyers is under 0 $.
[2018-12-10 12:10:58] Current fund for Flyers is under 0 $.
[2018-12-10 12:05:55] Current fund for Flyers is under 0 $.
[2018-12-09 23:09:50] Current fund for Flyers is under 0 $.
[2018-12-07 22:27:01] Current fund for Flyers is under 0 $.
[2018-12-07 22:22:14] Thomas Chabot from Phantoms has scored a Hat Trick!
[2018-12-06 22:35:09] Current fund for Flyers is under 0 $.
[2018-12-05 21:04:09] Current fund for Flyers is under 0 $.
[2018-12-05 20:52:35] Current fund for Flyers is under 0 $.
[2018-12-05 20:52:34] Successfully loaded Flyers lines done with STHS Client - 3.1.5.5
[2018-12-05 20:52:28] Current fund for Flyers is under 0 $.
[2018-12-04 23:45:01] Current fund for Flyers is under 0 $.
[2018-12-04 23:44:27] Thomas Chabot from Phantoms has scored a Hat Trick!
[2018-12-03 21:39:33] Current fund for Flyers is under 0 $.
[2018-12-02 22:58:47] Current fund for Flyers is under 0 $.
[2018-11-30 21:20:15] Current fund for Flyers is under 0 $.
[2018-11-30 21:19:41] Jordan Schmaltz from Phantoms has scored a Hat Trick!
[2018-11-29 22:38:41] Current fund for Flyers is under 0 $.
[2018-11-28 21:17:26] Current fund for Flyers is under 0 $.
[2018-11-27 22:50:24] Current fund for Flyers is under 0 $.
[2018-11-26 20:48:02] Successfully loaded Flyers lines done with STHS Client - 3.1.5.5
[2018-11-23 23:34:37] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2018-11-22 22:43:42] Current fund for Flyers is under 0 $.
[2018-11-22 22:43:18] Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2018-11-22 22:43:18] Game 250 - Philippe Myers from Phantoms is injured (Broken Bone (Right Ankle)) and is out for 2 months.
[2018-11-21 21:48:09] Phantoms lines for next game are empty. Current rosters/lines are not erased. But, Flyers lines for next game are NOT empty. Current pro rosters/lines are moved and might impact farm rosters/lines.
[2018-11-21 21:48:09] New Record for Team's Most Points (24) in 1 Game for Flyers!
[2018-11-21 21:48:09] New Record for Team's Most Assists (16) in 1 Game for Flyers!
[2018-11-21 21:48:09] New Record for Team's Most Points (24) in 1 Game for Flyers!
[2018-11-21 21:48:09] New Record for Team's Most Assists (16) in 1 Game for Flyers!
[2018-11-21 21:48:09] Clayton Keller from Flyers has scored a Hat Trick!
[2018-11-16 22:19:02] New Record for Team's Most Hits (31) in 1 Game for Flyers!

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
2	30	15	8	0	1	1	1	4	96	69	27	14	7	5	0	1	0	0	1	45	31	14	16	8	3	0	0	1	1	3	51	38	13	39	96	164	260	1	0	26	35	33	5	1069	377	344	345	23	1006	317	263	556	137	32	23.36%	127	22	82.68%	2	420	801	52.43%	408	792	51.52%	213	416	51.20%	639	368	661	281	525	255
Total Saison Régulière	30	15	8	0	1	1	1	4	96	69	27	14	7	5	0	1	0	0	1	45	31	14	16	8	3	0	0	1	1	3	51	38	13	39	96	164	260	1	0	26	35	33	5	1069	377	344	345	23	1006	317	263	556	137	32	23.36%	127	22	82.68%	2	420	801	52.43%	408	792	51.52%	213	416	51.20%	639	368	661	281	525	255