Ligue de Hockey Simulé du Saguenay

Phantoms
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Points
Informations Joueurs
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Actualité
Historique
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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

#	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	Jeff Carter	X				100.00	76	49	76	80	78	76	78	79	76	82	87	67	80	84	95	23	36	79	1
2	J.T. Miller		X			100.00	72	39	85	78	83	86	82	78	83	88	81	75	79	59	47	59	42	78	1
3	Jordan Nolan	X				100.00	87	61	77	79	89	75	89	83	81	81	74	69	80	71	66	38	43	78	1
4	Jakub Voracek			X		100.00	76	32	84	80	82	85	87	85	83	84	80	65	73	66	56	35	35	78	1
5	Niclas Bergfors			X		100.00	78	34	81	82	78	87	79	84	67	74	86	63	86	69	65	28	26	77	1
6	Drew Miller		X			100.00	74	29	74	78	75	89	79	79	67	80	78	75	71	85	82	19	31	76	1
7	Marcus Kruger			X		100.00	73	39	89	77	76	78	80	80	80	78	82	57	74	61	60	38	42	75	0
8	Chris Mcallister		X			100.00	80	42	75	71	71	77	71	80	50	81	74	78	66	75	62	19	42	74	0
9	Brock Nelson		X			100.00	77	35	85	77	76	76	75	80	74	74	76	63	74	61	57	45	39	73	0
10	Erik Christensen	X				100.00	75	33	74	80	67	73	73	69	78	83	80	57	59	85	85	16	38	73	0
11	Matthew Lombardi (A)	X				100.00	73	43	76	72	70	69	73	81	73	68	68	75	70	80	79	16	40	72	0
12	Ryan Callahan			X		100.00	66	31	75	75	78	74	73	78	73	69	79	69	72	72	66	20	45	72	0
13	Jacob Trouba				X	100.00	80	53	76	79	85	80	68	74	57	77	67	82	63	50	43	62	20	76	0
14	Jeff Woywitka (A)				X	100.00	76	42	84	72	78	76	75	80	63	84	57	78	67	92	77	16	24	76	1
15	Jonathan Ericsson				X	100.00	73	44	82	79	83	79	80	78	58	85	65	72	62	87	71	19	43	76	1
16	Matt Smaby				X	100.00	83	47	75	79	79	76	80	79	61	75	75	74	65	84	72	20	35	76	1
17	Nathan Beaulieu				X	100.00	77	40	84	78	75	76	81	77	67	83	66	74	68	62	52	50	40	75	0
18	Brian Lashoff				X	100.00	80	31	85	76	74	78	76	75	55	77	67	81	65	61	48	35	18	75	0
Rayé
1	Victor Bartley				X	100.00	74	37	71	72	75	71	76	70	63	72	64	71	65	75	64	31	21	71	0

	MOYENNE D'ÉQUIPE					100.00	76	40	79	77	77	78	78	78	69	79	74	71	70	73	66	31	35	75

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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	Steve Mason	100.00	89	80	75	87	87	81	78	83	82	75	86	66	58	33	39	81	1
2	Ilya Sorokin	100.00	56	87	63	71	74	71	71	78	85	65	54	43	44	71	44	71	0
Rayé
1	Ray Emery	100.00	73	69	76	76	78	68	70	70	75	72	76	82	85	15	20	74	1

	MOYENNE D'ÉQUIPE	100.00	73	79	71	78	80	73	73	77	81	71	72	64	62	40	34	75

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Pat Quinn	82	83	87	73	99	88	37	CAN	68	2	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	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FT	S1	S2	S3
1	Jakub Voracek	Flyers	RW	80	33	51	84	-11	18	0	96	89	256	72	168	12.89%	30	1467	18.34	8	22	30	36	308	0	1	1	2	30	4	3	53.17%	126	57	21	0	1	1.15	1	3	0	8	2	5
2	Jeff Carter	Flyers	C	80	30	50	80	-17	88	0	123	149	252	86	147	11.90%	30	1596	19.96	9	18	27	38	298	0	0	0	0	66	5	1	52.42%	1900	44	29	0	0	1.00	3	8	0	4	5	2
3	Jordan Nolan	Flyers	C	80	33	42	75	-9	40	0	164	141	213	72	139	15.49%	29	1588	19.86	7	18	25	35	289	2	0	2	10	186	1	0	52.06%	1481	51	26	0	0	0.94	1	7	0	3	5	6
4	J.T. Miller	Flyers	LW	80	34	39	73	-17	44	0	115	104	243	76	168	13.99%	47	1589	19.87	8	11	19	45	303	0	0	0	4	100	3	4	50.00%	104	44	25	0	1	0.92	1	8	0	3	3	4
5	Drew Miller	Flyers	LW	74	31	36	67	13	48	0	87	85	209	62	131	14.83%	35	1268	17.14	10	10	20	36	274	0	1	1	3	129	5	0	39.34%	61	38	33	2	0	1.06	0	0	0	4	3	3
6	Marcus Kruger	Flyers	RW	80	20	32	52	-13	6	0	88	51	189	66	114	10.58%	27	1371	17.14	9	10	19	30	264	0	0	0	0	0	3	1	43.37%	83	36	10	0	0	0.76	3	5	0	2	4	1
7	Niclas Bergfors	Flyers	RW	79	25	27	52	11	14	0	134	68	210	71	127	11.90%	29	1238	15.68	6	3	9	27	187	0	0	0	0	32	3	0	37.84%	74	34	19	0	0	0.84	0	7	0	4	4	3
8	Chris Mcallister	Flyers	LW	80	12	26	38	11	28	0	85	70	125	50	77	9.60%	20	934	11.68	0	0	0	0	24	0	1	1	0	169	3	0	43.75%	32	12	20	0	0	0.81	0	0	0	0	2	3
9	Erik Christensen	Flyers	C	80	16	22	38	5	48	0	101	71	113	42	80	14.16%	15	964	12.06	0	0	0	0	8	0	0	0	3	49	0	0	48.27%	663	17	10	0	1	0.79	0	0	0	2	0	3
10	Jeff Woywitka	Flyers	D	80	7	23	30	-7	40	0	69	126	80	34	28	8.75%	96	1853	23.16	2	6	8	14	284	0	0	0	2	205	1	0	0.00%	0	13	63	0	0	0.32	0	0	0	1	0	0
11	Jonathan Ericsson	Flyers	D	80	5	24	29	2	26	0	79	112	72	36	37	6.94%	83	1794	22.43	2	7	9	12	308	0	0	0	0	213	0	1	0.00%	0	26	51	0	0	0.32	0	0	0	0	1	0
12	Matthew Lombardi	Flyers	C	73	12	16	28	21	14	0	43	64	89	13	47	13.48%	18	697	9.56	0	0	0	0	0	2	0	2	6	143	0	1	51.39%	395	12	13	1	0	0.80	0	0	0	3	1	2
13	Matt Smaby	Flyers	D	80	5	19	24	1	60	0	105	81	83	38	32	6.02%	76	1431	17.90	4	2	6	8	84	0	0	0	1	70	1	0	0.00%	0	23	58	0	0	0.34	0	0	0	0	1	0
14	Nathan Beaulieu	Flyers	D	80	3	19	22	-4	24	0	75	86	62	22	29	4.84%	62	1467	18.34	2	5	7	10	249	0	0	0	1	58	1	0	0.00%	0	23	39	0	0	0.30	0	0	0	1	0	1
15	Ryan Callahan	Flyers	RW	71	8	12	20	15	22	0	31	21	78	26	37	10.26%	10	536	7.55	0	0	0	0	7	0	0	0	0	0	1	0	50.00%	14	19	10	0	0	0.75	0	0	0	0	0	2
16	Jacob Trouba	Flyers	D	78	3	15	18	-19	103	5	120	120	90	41	35	3.33%	112	1810	23.21	2	1	3	11	195	0	2	2	3	250	1	1	0.00%	0	11	53	0	0	0.20	0	0	1	1	0	0
17	Brock Nelson	Flyers	LW	80	5	11	16	-10	10	0	71	62	93	28	76	5.38%	18	976	12.20	0	0	0	0	0	0	0	0	2	23	1	0	50.00%	66	19	9	0	0	0.33	0	0	0	0	0	1
18	Brian Lashoff	Flyers	D	53	3	13	16	8	10	0	40	70	35	11	24	8.57%	46	861	16.26	0	0	0	0	5	0	0	0	3	113	0	0	0.00%	0	5	28	0	0	0.37	0	0	0	0	0	0
19	Dylan Olsen	Phantoms (Phi)	D	40	2	5	7	5	12	0	29	36	20	11	12	10.00%	22	526	13.15	0	1	1	0	3	0	0	0	0	52	0	0	0.00%	0	4	14	0	0	0.27	0	0	0	0	0	0
20	Tyler Randell	Phantoms (Phi)	RW	13	0	0	0	-3	0	0	8	3	3	0	2	0.00%	0	70	5.43	0	0	0	0	1	0	0	0	0	0	0	0	66.67%	3	0	0	0	0	0.00	0	0	0	0	0	0
21	Victor Bartley	Flyers	D	6	0	0	0	-2	4	0	9	6	4	0	1	0.00%	6	78	13.08	0	0	0	0	0	0	0	0	0	5	0	0	0.00%	0	0	2	0	0	0.00	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1447	287	482	769	-20	659	5	1672	1615	2519	857	1511	11.39%	811	24124	16.67	69	114	183	302	3100	4	5	9	40	1903	33	12	51.04%	5002	488	533	3	3	0.64	9	38	1	36	31	36

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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	Steve Mason	Flyers	73	30	28	10	0.895	3.28	4174	8	1	228	2166	1006	3	4	0.667	27	72	7	5	5	2
2	Ilya Sorokin	Flyers	5	3	2	0	0.878	3.60	283	0	0	17	139	82	2	0	0.500	4	4	18	0	0	0
3	Ray Emery	Flyers	10	1	5	1	0.853	4.56	382	0	0	29	197	101	1	0	0.000	0	4	55	0	0	0
Stats d'équipe Total ou en Moyenne			88	34	35	11	0.890	3.40	4840	8	1	274	2502	1189	6	4	0.645	31	80	80	5	5	2

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

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
Brian Lashoff	Flyers	D	25	1990-01-01	No	212 Lbs	6 ft3	No	No	No	2	Pro Only	1,600,000$	1,600,000$	0$	No	1,900,000$
Brock Nelson	Flyers	LW	24	1991-01-01	No	206 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,500,000$	1,500,000$	0$	No
Chris Mcallister	Flyers	LW	30	1985-01-01	No	250 Lbs	6 ft7	No	No	No	4	Pro Only	2,000,000$	2,000,000$	0$	No	2,000,000$	2,000,000$	2,000,000$
Drew Miller	Flyers	LW	31	1984-01-01	No	178 Lbs	6 ft2	No	No	No	3	Pro Only	3,750,000$	3,750,000$	0$	No	3,250,000$	2,750,000$
Erik Christensen	Flyers	C	32	1983-01-01	No	203 Lbs	6 ft1	No	No	No	1	Pro & Farm	500,000$	500,000$	0$	No
Ilya Sorokin	Flyers	G	19	1996-01-01	No	180 Lbs	6 ft2	No	No	No	1	Pro & Farm	500,000$	500,000$	0$	No
J.T. Miller	Flyers	LW	22	1993-01-01	No	205 Lbs	6 ft1	No	No	No	2	Pro Only	2,700,000$	2,700,000$	0$	No	3,200,000$
Jacob Trouba	Flyers	D	21	1994-01-01	No	187 Lbs	6 ft2	No	No	No	3	Pro Only	2,750,000$	2,750,000$	0$	No	2,750,000$	3,000,000$
Jakub Voracek	Flyers	RW	26	1989-01-01	No	205 Lbs	6 ft1	No	No	No	3	Pro Only	5,000,000$	5,000,000$	0$	No	5,500,000$	6,000,000$
Jeff Carter	Flyers	C	30	1985-01-01	No	200 Lbs	6 ft3	No	No	No	4	Pro Only	5,000,000$	5,000,000$	0$	No	5,000,000$	5,000,000$	5,000,000$
Jeff Woywitka	Flyers	D	32	1983-01-01	No	224 Lbs	6 ft3	No	No	No	2	Pro Only	3,000,000$	3,000,000$	0$	No	2,500,000$
Jonathan Ericsson	Flyers	D	31	1984-01-01	No	220 Lbs	6 ft4	No	No	No	3	Pro Only	3,000,000$	3,000,000$	0$	No	3,000,000$	3,000,000$
Jordan Nolan	Flyers	C	26	1989-01-01	No	221 Lbs	6 ft3	No	No	No	4	Pro Only	4,000,000$	4,000,000$	0$	No	4,000,000$	4,000,000$	4,000,000$
Marcus Kruger	Flyers	RW	25	1990-01-01	No	181 Lbs	6 ft0	No	No	No	4	Pro Only	3,500,000$	3,500,000$	0$	No	3,500,000$	3,500,000$	3,500,000$
Matt Smaby	Flyers	D	31	1984-01-01	No	240 Lbs	6 ft4	No	No	No	3	Pro Only	3,000,000$	3,000,000$	0$	No	3,000,000$	3,000,000$
Matthew Lombardi	Flyers	C	33	1982-01-01	No	195 Lbs	5 ft11	No	No	No	1	Pro Only	1,500,000$	1,500,000$	0$	No
Nathan Beaulieu	Flyers	D	23	1992-01-01	No	205 Lbs	6 ft2	No	No	No	2	Pro Only	1,500,000$	1,500,000$	0$	No	1,750,000$
Niclas Bergfors	Flyers	RW	28	1987-01-01	No	195 Lbs	5 ft11	No	No	No	2	Pro Only	3,500,000$	3,500,000$	0$	No	4,000,000$
Ray Emery	Flyers	G	33	1982-01-01	No	196 Lbs	6 ft2	No	No	No	1	Pro & Farm	500,000$	500,000$	0$	No
Ryan Callahan	Flyers	RW	30	1985-01-01	No	188 Lbs	5 ft11	No	No	No	1	Pro Only	1,200,000$	1,200,000$	0$	No
Steve Mason	Flyers	G	27	1988-01-01	No	211 Lbs	6 ft4	No	No	No	3	Pro Only	4,000,000$	4,000,000$	0$	No	4,000,000$	4,000,000$
Victor Bartley	Flyers	D	27	1988-01-01	No	203 Lbs	6 ft0	No	No	No	1	Pro & Farm	950,000$	950,000$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
22	27.55	205 Lbs	6 ft2	2.32	2,497,727$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
54,950,000$	49,350,000$	36,250,000$	14,500,000$	0$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	J.T. Miller	Jeff Carter	Marcus Kruger	33	0	1	4
2	Brock Nelson	Jordan Nolan	Jakub Voracek	32	0	1	4
3	Drew Miller	Erik Christensen	Niclas Bergfors	25	0	2	3
4	Chris Mcallister	Matthew Lombardi	Ryan Callahan	10	0	4	1

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Trouba	Jonathan Ericsson	30	1	3	1
2	Jeff Woywitka	Nathan Beaulieu	30	1	3	1
3	Brian Lashoff	Matt Smaby	30	1	3	1
4	Jacob Trouba	Jeff Woywitka	10	1	3	1

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	J.T. Miller	Jeff Carter	Marcus Kruger	50	0	1	4
2	Drew Miller	Jordan Nolan	Jakub Voracek	50	0	1	4

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Trouba	Nathan Beaulieu	50	0	2	3
2	Jonathan Ericsson	Jeff Woywitka	50	0	2	3

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Matthew Lombardi	Chris Mcallister	50	0	4	1
2	Jordan Nolan	Drew Miller	50	0	4	1

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Trouba	Brian Lashoff	50	1	4	0
2	Jeff Woywitka	Jonathan Ericsson	50	1	4	0

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Matthew Lombardi	50	0	4	1	Jacob Trouba	Brian Lashoff	50	1	4	0
2	Jordan Nolan	50	0	4	1	Jeff Woywitka	Jonathan Ericsson	50	1	4	0

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Jeff Carter	J.T. Miller	50	0	2	3
2	Jordan Nolan	Jakub Voracek	50	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Jacob Trouba	Nathan Beaulieu	50	1	3	1
2	Jeff Woywitka	Jonathan Ericsson	50	1	3	1

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
J.T. Miller	Jeff Carter	Jakub Voracek	Jacob Trouba	Jeff Woywitka

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Drew Miller	Matthew Lombardi	Niclas Bergfors	Jacob Trouba	Brian Lashoff

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jeff Carter, Jordan Nolan, Drew Miller	Jeff Carter, Jordan Nolan	Drew Miller

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jacob Trouba, Jeff Woywitka, Jonathan Ericsson	Jacob Trouba	Jacob Trouba, Jeff Woywitka

Tirs de Pénalité
Jeff Carter, Jordan Nolan, J.T. Miller, Marcus Kruger, Jakub Voracek

Gardien
#1 : Steve Mason, #2 : Ilya Sorokin

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	Avalanche	2	0	1	0	0	0	0	1	7	11	-4	1	0	1	0	0	0	0	0	4	7	-3	1	0	0	0	0	0	0	1	3	4	-1	1	0.250	7	13	20	0	0	1	4	2	0	56	12	20	21	6	68	19	16	39	12	2	16.67%	8	1	87.50%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	46	26	42	18	35	17
2	Blackhawks	3	1	2	0	0	0	0	0	9	13	-4	2	1	1	0	0	0	0	0	8	9	-1	1	0	1	0	0	0	0	0	1	4	-3	2	0.333	9	16	25	0	0	3	2	4	0	107	37	38	32	0	78	23	26	59	13	1	7.69%	13	6	53.85%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	66	39	63	27	50	24
3	Blue Jackets	3	1	1	0	0	0	1	0	15	12	3	2	1	0	0	0	0	1	0	12	7	5	1	0	1	0	0	0	0	0	3	5	-2	4	0.667	15	26	41	1	0	2	5	7	1	98	32	37	29	4	104	23	14	67	15	4	26.67%	7	2	71.43%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	73	45	59	25	52	26
4	Blues	3	0	2	0	0	0	0	1	4	10	-6	2	0	1	0	0	0	0	1	3	7	-4	1	0	1	0	0	0	0	0	1	3	-2	1	0.167	4	6	10	0	0	1	2	1	0	95	39	29	26	5	91	35	20	65	6	1	16.67%	10	3	70.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	62	36	68	28	53	26
5	Bruins	2	1	1	0	0	0	0	0	7	8	-1	1	1	0	0	0	0	0	0	5	3	2	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	7	11	18	0	0	1	1	5	0	61	18	14	29	0	65	15	10	40	10	2	20.00%	5	2	60.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	44	25	42	16	33	18
6	Canadiens	6	1	4	0	0	1	0	0	17	22	-5	3	1	2	0	0	0	0	0	9	10	-1	3	0	2	0	0	1	0	0	8	12	-4	3	0.250	17	29	46	2	0	5	7	5	0	187	68	51	66	2	185	68	48	122	25	5	20.00%	24	6	75.00%	1	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	128	73	130	57	105	51
7	Canucks	2	1	1	0	0	0	0	0	7	7	0	1	1	0	0	0	0	0	0	5	2	3	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	7	12	19	0	0	1	3	3	0	63	20	21	22	0	68	19	16	48	9	3	33.33%	8	1	87.50%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	41	22	44	18	34	17
8	Capitals	3	2	1	0	0	0	0	0	10	5	5	1	1	0	0	0	0	0	0	3	1	2	2	1	1	0	0	0	0	0	7	4	3	4	0.667	10	17	27	0	0	3	5	2	0	90	33	32	25	0	89	25	24	60	21	4	19.05%	12	3	75.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	66	35	58	29	55	29
9	Devils	2	0	2	0	0	0	0	0	6	9	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	6	12	18	0	0	0	2	4	0	76	25	19	32	0	67	23	4	40	6	2	33.33%	2	1	50.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	42	24	44	16	33	17
10	Flames	2	2	0	0	0	0	0	0	7	5	2	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	4	3	1	4	1.000	7	13	20	0	0	1	4	2	0	53	17	27	9	0	64	18	12	41	11	2	18.18%	6	0	100.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	42	22	43	19	34	17
11	Golden Knights	2	0	2	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	2	3	5	0	0	1	0	1	0	62	16	26	20	0	57	22	16	37	12	1	8.33%	8	1	87.50%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	45	26	40	17	33	17
12	Islanders	3	0	1	0	0	1	1	0	7	9	-2	2	0	1	0	0	0	1	0	3	4	-1	1	0	0	0	0	1	0	0	4	5	-1	3	0.500	7	8	15	0	0	3	1	2	1	75	27	21	27	3	89	31	12	76	11	2	18.18%	7	0	100.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	66	36	62	31	59	29
13	Jets	7	3	2	0	0	1	1	0	32	28	4	4	2	1	0	0	1	0	0	15	13	2	3	1	1	0	0	0	1	0	17	15	2	9	0.643	32	57	89	0	0	9	10	12	3	207	68	76	61	6	226	77	54	153	34	8	23.53%	27	6	77.78%	1	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	147	81	152	64	124	63
14	Kings	3	1	2	0	0	0	0	0	12	14	-2	1	0	1	0	0	0	0	0	3	6	-3	2	1	1	0	0	0	0	0	9	8	1	2	0.333	12	24	36	0	0	2	3	7	0	101	33	30	38	0	95	28	20	75	17	4	23.53%	10	1	90.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	67	39	61	26	51	25
15	Lightning	2	0	2	0	0	0	0	0	10	13	-3	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	6	7	-1	0	0.000	10	17	27	1	0	3	3	4	0	72	29	8	35	0	64	14	16	27	9	2	22.22%	8	1	87.50%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	42	24	43	18	34	16
16	Maple Leafs	5	2	1	0	1	1	0	0	19	16	3	2	0	1	0	1	0	0	0	6	9	-3	3	2	0	0	0	1	0	0	13	7	6	7	0.700	19	34	53	0	0	4	7	7	1	170	58	46	65	1	146	49	22	106	21	3	14.29%	11	3	72.73%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	112	67	104	42	85	43
17	Oilers	7	5	2	0	0	0	0	0	27	20	7	3	2	1	0	0	0	0	0	11	7	4	4	3	1	0	0	0	0	0	16	13	3	10	0.714	27	42	69	0	0	9	4	14	0	208	71	50	87	0	207	69	64	136	22	4	18.18%	32	3	90.63%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	148	85	151	66	119	58
18	Panthers	2	1	1	0	0	0	0	0	7	7	0	1	0	1	0	0	0	0	0	3	6	-3	1	1	0	0	0	0	0	0	4	1	3	2	0.500	7	11	18	0	0	4	2	1	0	61	19	22	20	0	55	19	16	38	10	0	0.00%	8	2	75.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	42	23	41	18	35	18
19	Penguins	2	2	0	0	0	0	0	0	10	5	5	1	1	0	0	0	0	0	0	6	3	3	1	1	0	0	0	0	0	0	4	2	2	4	1.000	10	18	28	0	0	0	4	6	0	70	26	27	17	0	81	20	8	32	3	0	0.00%	4	0	100.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	42	24	44	17	32	16
20	Predators	3	1	2	0	0	0	0	0	5	9	-4	1	0	1	0	0	0	0	0	1	3	-2	2	1	1	0	0	0	0	0	4	6	-2	2	0.333	5	10	15	0	0	1	3	1	0	73	25	25	23	0	96	37	30	54	17	0	0.00%	15	3	80.00%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	61	33	67	28	51	25
21	Rangers	2	2	0	0	0	0	0	0	10	2	8	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	5	0	5	4	1.000	10	16	26	0	1	3	5	2	0	75	29	23	23	0	51	14	18	29	11	1	9.09%	9	2	77.78%	2	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	47	29	37	17	35	18
22	Red Wings	6	1	3	0	0	0	0	2	26	32	-6	3	1	2	0	0	0	0	0	13	15	-2	3	0	1	0	0	0	0	2	13	17	-4	4	0.333	26	49	75	0	0	7	11	8	3	174	61	60	51	11	215	69	62	124	20	2	10.00%	31	10	67.74%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	123	68	139	56	107	52
23	Senateurs	2	1	0	0	0	0	0	1	7	5	2	1	0	0	0	0	0	0	1	3	4	-1	1	1	0	0	0	0	0	0	4	1	3	3	0.750	7	9	16	0	0	1	3	3	1	65	17	18	28	8	59	19	14	40	12	4	33.33%	7	1	85.71%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	43	22	42	20	39	19
24	Sharks	4	2	1	0	0	1	0	0	13	8	5	2	1	0	0	0	1	0	0	9	4	5	2	1	1	0	0	0	0	0	4	4	0	5	0.625	13	23	36	0	0	4	4	5	0	117	34	31	52	0	123	29	32	75	29	6	20.69%	16	1	93.75%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	82	42	85	37	71	37
25	Stars	2	0	1	0	0	1	0	0	6	8	-2	1	0	0	0	0	1	0	0	4	5	-1	1	0	1	0	0	0	0	0	2	3	-1	1	0.250	6	10	16	0	0	0	2	4	0	70	24	18	28	0	63	23	14	40	7	0	0.00%	7	1	85.71%	0	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	44	27	42	17	33	17
	Total	80	30	35	0	1	6	3	5	282	283	-1	40	15	17	0	1	3	2	2	141	141	0	40	15	18	0	0	3	1	3	141	142	-1	79	0.494	282	486	768	4	1	69	97	112	10	2486	838	769	866	46	2506	788	588	1623	363	63	17.36%	295	60	79.66%	4	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	1731	984	1716	737	1402	706
	_Since Last GM Reset	80	30	35	0	1	6	3	5	282	283	-1	40	15	17	0	1	3	2	2	141	141	0	40	15	18	0	0	3	1	3	141	142	-1	79	0.494	282	486	768	4	1	69	97	112	10	2486	838	769	866	46	2506	788	588	1623	363	63	17.36%	295	60	79.66%	4	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	1731	984	1716	737	1402	706
	_Vs Conference	53	20	22	0	1	5	3	2	192	188	4	26	10	11	0	1	2	2	0	93	88	5	27	10	11	0	0	3	1	2	99	100	-1	55	0.519	192	335	527	3	0	52	62	74	9	1607	547	497	556	27	1653	528	408	1107	245	43	17.55%	205	44	78.54%	2	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	1143	647	1137	492	934	468
	_Vs Division	26	10	11	0	0	2	1	2	102	102	0	13	6	6	0	0	1	0	0	48	45	3	13	4	5	0	0	1	1	2	54	57	-3	26	0.500	102	177	279	2	0	30	32	39	6	776	268	237	265	19	833	283	228	535	101	19	18.81%	114	25	78.07%	2	981	1926	50.93%	969	1856	52.21%	603	1203	50.12%	547	309	575	243	457	226

			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
80	79	OTL1	282	486	768	2486	2506	788	588	1623	4	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
80	30	35	1	6	3	5	282	283

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
40	15	17	1	3	2	2	141	141

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
40	15	18	0	3	1	3	141	142

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	2	0	4	1	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
363	63	17.36%	295	60	79.66%	4

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
838	769	866	46	69	97	112	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
981	1926	50.93%	969	1856	52.21%	603	1203	50.12%

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
1731	984	1716	737	1402	706

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 - 2020-10-10	8	Jets	2	Flyers	5	W			R1	Sommaire du Match
3 - 2020-10-11	15	Flyers	3	Oilers	1	W			R1	Sommaire du Match
6 - 2020-10-14	28	Flyers	6	Oilers	5	W				Sommaire du Match
8 - 2020-10-16	41	Red Wings	8	Flyers	6	L			R1	Sommaire du Match
13 - 2020-10-21	62	Oilers	2	Flyers	6	W			R1	Sommaire du Match
15 - 2020-10-23	69	Flyers	4	Maple Leafs	2	W				Sommaire du Match
18 - 2020-10-26	86	Jets	2	Flyers	4	W			R1	Sommaire du Match
20 - 2020-10-28	99	Flyers	6	Jets	7	L				Sommaire du Match
21 - 2020-10-29	107	Flyers	5	Red Wings	6	L	X	X	R1	Sommaire du Match
22 - 2020-10-30	111	Flyers	4	Canadiens	5	L	X			Sommaire du Match
25 - 2020-11-02	124	Canadiens	3	Flyers	1	L				Sommaire du Match
29 - 2020-11-06	146	Blues	3	Flyers	2	L	X	X		Sommaire du Match
31 - 2020-11-08	160	Flyers	3	Kings	4	L				Sommaire du Match
33 - 2020-11-10	173	Maple Leafs	6	Flyers	2	L				Sommaire du Match
34 - 2020-11-11	182	Flyers	2	Sharks	3	L				Sommaire du Match
37 - 2020-11-14	199	Flyers	3	Canadiens	5	L				Sommaire du Match
39 - 2020-11-16	205	Blue Jackets	3	Flyers	7	W				Sommaire du Match
42 - 2020-11-19	223	Stars	5	Flyers	4	L	X			Sommaire du Match
45 - 2020-11-22	240	Flyers	4	Penguins	2	W				Sommaire du Match
47 - 2020-11-24	248	Flyers	2	Canucks	5	L				Sommaire du Match
48 - 2020-11-25	256	Rangers	2	Flyers	5	W				Sommaire du Match
51 - 2020-11-28	272	Flyers	6	Kings	4	W				Sommaire du Match
53 - 2020-11-30	281	Kings	6	Flyers	3	L				Sommaire du Match
57 - 2020-12-04	300	Flyers	3	Avalanche	4	L	X	X		Sommaire du Match
59 - 2020-12-06	305	Flyers	6	Capitals	2	W			R1	Sommaire du Match
61 - 2020-12-08	312	Senateurs	4	Flyers	3	L	X	X		Sommaire du Match
63 - 2020-12-10	328	Flyers	1	Golden Knights	2	L			R1	Sommaire du Match
64 - 2020-12-11	335	Penguins	3	Flyers	6	W				Sommaire du Match
67 - 2020-12-14	349	Flyers	6	Lightning	7	L				Sommaire du Match
70 - 2020-12-17	363	Predators	3	Flyers	1	L			R1	Sommaire du Match
72 - 2020-12-19	375	Flyers	4	Predators	3	W				Sommaire du Match
75 - 2020-12-22	387	Capitals	1	Flyers	3	W			R1	Sommaire du Match
77 - 2020-12-24	401	Flyers	0	Predators	3	L				Sommaire du Match
79 - 2020-12-26	413	Sharks	1	Flyers	7	W				Sommaire du Match
81 - 2020-12-28	421	Flyers	5	Rangers	0	W				Sommaire du Match
84 - 2020-12-31	436	Flyers	4	Devils	6	L				Sommaire du Match
85 - 2021-01-01	441	Flames	2	Flyers	3	W				Sommaire du Match
90 - 2021-01-06	464	Bruins	3	Flyers	5	W				Sommaire du Match
93 - 2021-01-09	477	Flyers	1	Canadiens	2	L				Sommaire du Match
95 - 2021-01-11	490	Blue Jackets	4	Flyers	5	W	X	X		Sommaire du Match
97 - 2021-01-13	501	Flyers	3	Blue Jackets	5	L				Sommaire du Match
99 - 2021-01-15	513	Flyers	4	Flames	3	W				Sommaire du Match
101 - 2021-01-17	520	Golden Knights	3	Flyers	1	L			R1	Sommaire du Match
103 - 2021-01-19	527	Flyers	4	Panthers	1	W				Sommaire du Match
105 - 2021-01-21	544	Canadiens	3	Flyers	6	W				Sommaire du Match
110 - 2021-01-26	565	Flyers	2	Stars	3	L				Sommaire du Match
111 - 2021-01-27	571	Devils	3	Flyers	2	L				Sommaire du Match
116 - 2021-02-01	594	Canadiens	4	Flyers	2	L				Sommaire du Match
120 - 2021-02-05	611	Flyers	2	Red Wings	3	L	X	X	R1	Sommaire du Match
122 - 2021-02-07	620	Islanders	1	Flyers	2	W	X	X		Sommaire du Match
124 - 2021-02-09	635	Flyers	1	Blues	3	L				Sommaire du Match
126 - 2021-02-11	641	Flyers	4	Senateurs	1	W				Sommaire du Match
128 - 2021-02-13	648	Flyers	1	Blackhawks	4	L				Sommaire du Match
129 - 2021-02-14	653	Avalanche	7	Flyers	4	L				Sommaire du Match
132 - 2021-02-17	670	Flyers	1	Capitals	2	L			R1	Sommaire du Match
133 - 2021-02-18	675	Islanders	3	Flyers	1	L				Sommaire du Match
136 - 2021-02-21	691	Flyers	6	Red Wings	8	L			R1	Sommaire du Match
137 - 2021-02-22	702	Panthers	6	Flyers	3	L				Sommaire du Match
141 - 2021-02-26	725	Canucks	2	Flyers	5	W				Sommaire du Match
144 - 2021-03-01	738	Flyers	2	Bruins	5	L				Sommaire du Match
147 - 2021-03-04	752	Jets	4	Flyers	2	L			R1	Sommaire du Match
150 - 2021-03-07	773	Oilers	3	Flyers	1	L			R1	Sommaire du Match
151 - 2021-03-08	781	Flyers	2	Sharks	1	W				Sommaire du Match
154 - 2021-03-11	798	Oilers	2	Flyers	4	W			R1	Sommaire du Match
157 - 2021-03-14	815	Flyers	5	Jets	3	W				Sommaire du Match
159 - 2021-03-16	826	Maple Leafs	3	Flyers	4	W	X			Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
163 - 2021-03-20	849	Lightning	6	Flyers	4	L				Sommaire du Match
167 - 2021-03-24	872	Blackhawks	2	Flyers	3	W				Sommaire du Match
169 - 2021-03-26	884	Flyers	2	Oilers	4	L			R1	Sommaire du Match
171 - 2021-03-28	896	Blackhawks	7	Flyers	5	L				Sommaire du Match
172 - 2021-03-29	898	Flyers	6	Jets	5	W	X	X	R1	Sommaire du Match
174 - 2021-03-31	909	Flyers	7	Maple Leafs	2	W				Sommaire du Match
178 - 2021-04-04	928	Sharks	3	Flyers	2	L	X			Sommaire du Match
181 - 2021-04-07	948	Blues	4	Flyers	1	L				Sommaire du Match
183 - 2021-04-09	958	Flyers	2	Maple Leafs	3	L	X			Sommaire du Match
186 - 2021-04-12	975	Jets	5	Flyers	4	L	X		R1	Sommaire du Match
188 - 2021-04-14	982	Flyers	5	Oilers	3	W			R1	Sommaire du Match
193 - 2021-04-19	1005	Red Wings	3	Flyers	5	W				Sommaire du Match
195 - 2021-04-21	1020	Red Wings	4	Flyers	2	L			R1	Sommaire du Match
197 - 2021-04-23	1030	Flyers	4	Islanders	5	L	X			Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité	6000	5000	2000	4000	1000
Prix des Billets	125	75	50	40	250
Assistance	172,626	143,076	56,360	99,417	25,739
Attendance PCT	71.93%	71.54%	70.45%	62.14%	64.35%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité	Popularité de l'Équipe
0	12430 - 69.06%	1,309,228$	52,369,138$	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
57,575,000$	54,950,000$	52,350,000$	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
274,750$	54,610,000$	23,651,609$	22	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	287,250$	0$

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	6,606,851$	6,606,851$

Cap Salarial de la Saison Éstimé	Cap Salarial Disponible	Cap Salarial Maximum	Au dessus du Plafond Salarial Minimum
54,610,000$	1,390,000$	56,000,000$	21,610,000$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

J.T. Miller	AGE:22	PO:59	OV:78
Drew Miller	AGE:31	PO:19	OV:76
Chris Mcallister	AGE:30	PO:19	OV:74
Brock Nelson	AGE:24	PO:45	OV:73
Michael Bournival (R)	AGE:23	PO:45	OV:71
Brandon McMillan (R)	AGE:25	PO:37	OV:68
Morgan Klimchuk (R)	AGE:20	PO:54	OV:63
Erik Nystrom (R)	AGE:22	PO:41	OV:63
Brendan Leipsic (R)	AGE:21	PO:48	OV:60
A.J. Greer (R)	AGE:19	PO:56	OV:55
Justin Kirkland (R)	AGE:19	PO:57	OV:52

Jeff Carter	AGE:30	PO:23	OV:79
Jordan Nolan	AGE:26	PO:38	OV:78
Erik Christensen	AGE:32	PO:16	OV:73
Matthew Lombardi	AGE:33	PO:16	OV:72
Calle Jarnkrok (R)	AGE:24	PO:42	OV:70
Tyler Brenner	AGE:27	PO:30	OV:70
Nick Shore (R)	AGE:23	PO:43	OV:65
Cristoval Nieves (R)	AGE:21	PO:50	OV:64
David Kampf (R)	AGE:20	PO:64	OV:61
Lucas Wallmarkk (R)	AGE:19	PO:64	OV:61
Laurent Dauphin (R)	AGE:20	PO:57	OV:59
Anthony Angello (R)	AGE:19	PO:58	OV:56
Cooper Marody (R)	AGE:19	PO:63	OV:53

Jakub Voracek	AGE:26	PO:35	OV:78
Niclas Bergfors	AGE:28	PO:28	OV:77
Marcus Kruger	AGE:25	PO:38	OV:75
Tyler Randell (R)	AGE:24	PO:40	OV:72
Ryan Callahan	AGE:30	PO:20	OV:72
Tomas Kubalik	AGE:25	PO:39	OV:70
Travis Konecny (R)	AGE:18	PO:77	OV:66
Sven Andrighetto (R)	AGE:22	PO:53	OV:66
Nick Sorensen (R)	AGE:21	PO:57	OV:59
JC Lipon (R)	AGE:22	PO:48	OV:57

Défense #1

Défense #2

Gardien

Jacob Trouba	AGE:21	PO:62	OV:76
Matt Smaby	AGE:31	PO:20	OV:76
Jonathan Ericsson	AGE:31	PO:19	OV:76
Jeff Woywitka	AGE:32	PO:16	OV:76
Nathan Beaulieu	AGE:23	PO:50	OV:75
Brian Lashoff	AGE:25	PO:35	OV:75
Dylan Olsen (R)	AGE:24	PO:38	OV:73
Victor Bartley	AGE:27	PO:31	OV:71

Reid McNeill (R)	AGE:23	PO:43	OV:69
Jake Dotchin (R)	AGE:21	PO:51	OV:68
Mark Alt (R)	AGE:24	PO:34	OV:66
Ivan Provorov (R)	AGE:18	PO:85	OV:65
Brenden Kichton (R)	AGE:23	PO:38	OV:64
Blake Heinrich (R)	AGE:20	PO:53	OV:63
Rinat Valiev (R)	AGE:20	PO:62	OV:62
Devon Teows (R)	AGE:21	PO:56	OV:62

Steve Mason	AGE:27	PO:33	OV:81
Ray Emery	AGE:33	PO:15	OV:74
Ilya Sorokin	AGE:19	PO:71	OV:71
Anton Forsberg	AGE:23	PO:44	OV:71
Zachary Fucale	AGE:20	PO:55	OV:66
Jason Kasdorf	AGE:23	PO:46	OV:64
Scott Wedgewood	AGE:23	PO:36	OV:63

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	Information	Lien

Choix au Repêchage

Année	R1	R2	R3	R4	R5
14
15
16
17
18

[2021-04-01 6:54:31 PM] - Team Name Change : Harfangs changed name to Phantoms
[2021-03-14 7:58:03 PM] - TRADE : From Flyers to Kings : Mats Zuccarello (74), Oliver Ekman-Larsson (81), Ryan Hartman (68), Y:14-RND:2-Phi, Y:3-RND:0-.
[2021-03-14 7:58:03 PM] - TRADE : From Kings to Flyers : Jacob Trouba (76), Niclas Bergfors (77), Travis Konecny (66).
[2020-12-01 9:06:53 PM] - Flyers hired Pat Quinn for $2,500,000 for 2 year(s).
[2020-12-01 8:23:38 PM] - Harfangs hired Randy Cunneyworth for $250,000 for 0 year(s).
[2020-12-01 8:23:38 PM] - Harfangs fired Mike Sullivan.
[2020-10-14 7:12:31 PM] - Erik Christensen signed with Flyers for $500,000 for 1 year(s).
[2020-10-14 7:12:31 PM] - Erik Christensen was added to Flyers.
[2020-10-14 7:12:18 PM] - Ray Emery signed with Flyers for $500,000 for 1 year(s).
[2020-10-14 7:12:18 PM] - Ray Emery was added to Flyers.

[2021-05-11 7:05:51 PM] Auto Lines Function has been run for Phantoms.
[2021-05-10 6:58:55 PM] Auto Lines Function has been run for Phantoms.
[2021-05-07 8:01:37 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-05-06 7:07:04 PM] Auto Lines Function has been run for Phantoms.
[2021-05-05 7:01:44 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-05-03 9:58:16 PM] Erik Nystrom from Phantoms is back from Bruised Left Arm Injury.
[2021-05-03 9:58:16 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-05-02 8:13:06 PM] Tyler Randell from Phantoms has scored a Hat Trick!
[2021-05-02 8:12:49 PM] Auto Lines Function has been run for Phantoms.
[2021-04-29 7:00:38 PM] Morgan Klimchuk from Phantoms is back from Strained Left Knee Injury.
[2021-04-29 7:00:36 PM] Game 972 - Morgan Klimchuk from Phantoms is injured (Strained Left Knee) and is out for 5 days.
[2021-04-29 7:00:29 PM] Auto Lines Function has been run for Phantoms.
[2021-04-28 7:26:34 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-04-27 7:31:10 PM] Auto Lines Function has been run for Phantoms.
[2021-04-26 7:18:48 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-04-25 9:05:06 PM] Game 948 - Erik Nystrom from Phantoms is injured (Bruised Left Arm) and is out for 2 weeks.
[2021-04-23 7:09:14 PM] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2021-04-23 7:07:52 PM] Successfully loaded Flyers lines done with STHS Client - 3.2.7.7
[2021-04-23 7:07:52 PM] Victor Bartley of Flyers was sent to pro.
[2021-04-21 7:20:56 PM] Both Flyers and Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-20 7:04:12 PM] Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-18 7:20:18 PM] Both Flyers and Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-15 7:15:09 PM] Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-15 7:15:09 PM] Last 7 Days Pro Star : 1 - Drew Miller of Flyers (4-4-8) / 2 - Niclas Bergfors of Flyers (3-4-7) / 3 - Evgeni Malkin of Canadiens (4-3-7)
[2021-04-13 7:01:12 PM] Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-13 7:01:09 PM] Tyler Brenner from Phantoms has scored a Hat Trick!
[2021-04-08 7:24:05 PM] Phantoms lines for next game are empty. Current rosters/lines are not erased.
[2021-04-08 7:23:39 PM] Auto Lines Function has been run for Phantoms.
[2021-04-08 7:23:39 PM] Auto Roster Farm Only Function has been run for Flyers.
[2021-04-07 7:33:46 PM] J.T. Miller from Flyers has scored a Hat Trick!
[2021-04-05 7:46:35 PM] Jake Dotchin from Phantoms is back from Strained Right Elbow Injury.
[2021-04-05 7:46:24 PM] Auto Lines Function has been run for Phantoms.
[2021-04-05 7:46:24 PM] Auto Roster Farm Only Function has been run for Flyers.

Pas de Blessure ou de Suspension.

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	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

	Flyers
	GP: 80 \| W: 34 \| L: 35 \| OTL: 11 \| P: 79 GF: 282 \| GA: 283 \| PP%: 17.36% \| PK%: 79.66% DG: Simon de Champlain \| Morale : 21 \| Moyenne d'Équipe : 75