Ligue Canadienne de Hockey Simulé

Flyers
Accueil
Formation
Points
Informations joueurs
Lignes
Statistiques d’équipe
Calendrier
Finance

Centre de jeu
	Flyers 1-4-0, 2pts	2	FINAL	4	Islanders 5-5-0, 10pts

Team Stats
L4	Streak	L1
1-2-0	Home Record	3-1-0
0-2-0	Away Record	2-4-0
1-4-0	Last 10 Games	5-4-1
2.20	Goals Per Game	2.70
3.20	Goals Against Per Game	2.70
10.53%	Power Play Percentage	10.26%
100.00%	Penalty Kill Percentage	80.00%

Islanders
5-5-0, 10pts

FINAL

Flyers
1-4-0, 2pts

Team Stats
L1	Streak	L4
3-1-0	Home Record	1-2-0
2-4-0	Away Record	0-2-0
5-4-1	Last 10 Games	1-4-0
2.70	Goals Per Game	2.20
2.70	Goals Against Per Game	3.20
10.26%	Power Play Percentage	10.53%
80.00%	Penalty Kill Percentage	100.00%

Meneurs d'équipe




	Victoires Scott Darling 1	Pourcentage d’arrêts Scott Darling 0.906

Statistiques d’équipe
Buts pour 11 2.20 GFG	Tirs pour 166 33.20 Avg	Pourcentage en avantage numérique 10.5% 2 GF	Début de zone offensive 43.2%
Buts contre 16 3.20 GAA	Tirs contre 158 31.60 Avg	Pourcentage en désavantage numérique 100.0% 0 GA	Début de la zone défensive 34.3%

Information d’équipe
	Directeur général	Libre
	Entraîneur	Dave Hakstol
	Division	Métropolitaine
	Conférence	Est
	Capitaine
	Assistant #1
	Assistant #2
Informations de l’aréna
	Capacité	3,000
	Assistance	2,670
	Billets de saison	1,800
Information formation
	Équipe Pro	29
	Équipe Mineure	18
	Limite contact	47 / 60
	Espoirs	28

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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	Âge	Contrat	Salaire
1	Artturi Lehkonen (R)		X			100.00	81	39	83	68	70	84	89	73	58	75	68	89	67	69	70	68	69	72	0	25	3	800,000$
2	Andreas Johnsson (R)			X		100.00	69	39	82	76	69	82	81	81	56	79	76	74	70	71	67	48	70	72	0	26	2	925,000$
3	Brett Howden (R)	X				100.00	69	42	85	68	81	76	76	73	84	78	70	86	66	63	64	80	63	71	0	23	2	925,000$
4	Jesperi Kotkaniemi (R)	X				100.00	65	35	72	70	73	76	92	81	83	81	73	72	67	55	53	89	70	71	0	20	2	925,000$
5	Daniel Winnik		X			100.00	55	38	83	69	77	77	98	69	71	72	70	82	66	87	72	23	69	71	0	36	1	1,400,000$
6	Colin Mcdonald			X		100.00	75	49	67	62	77	73	74	83	61	73	77	60	67	95	89	47	69	70	0	36	1	575,000$
7	Adam Gaudette (R)	X				100.00	61	42	80	72	71	75	85	76	78	76	68	74	72	67	65	53	70	69	0	24	2	916,666$
8	Tom Kuhnhackl (R)			X		100.00	67	42	83	64	81	83	72	71	54	70	67	85	58	75	66	53	69	69	0	29	2	600,000$
9	Brian Flynn		X			100.00	41	28	95	70	71	65	73	69	87	62	58	91	64	99	91	54	70	68	0	32	1	575,000$
10	Travis Boyd (R)	X				100.00	59	39	87	64	72	75	68	70	70	74	66	75	64	73	67	52	66	67	0	27	2	800,000$
11	Andy Andreoff (R)		X			100.00	64	53	83	62	78	73	77	68	56	71	65	67	62	77	74	52	69	66	0	30	1	575,000$
12	Gerald Mayhew (R)			X		100.00	54	46	85	64	65	83	79	69	58	67	66	66	64	75	68	46	69	65	0	28	3	700,000$
13	Derek Forbort (R)				X	100.00	70	35	75	66	85	87	95	74	30	76	71	93	56	67	61	76	70	75	0	29	2	1,250,000$
14	Matt Tennyson (R)				X	100.00	68	45	87	64	83	81	80	78	30	93	75	74	45	78	68	54	61	73	0	31	3	900,000$
15	Dylan Olsen				X	100.00	68	19	99	60	80	65	72	91	50	83	77	75	67	82	78	51	58	72	0	30	1	1,250,000$
16	Brandon Manning (R)				X	100.00	80	48	72	64	76	79	83	80	30	73	78	77	58	74	69	33	69	71	0	31	3	700,000$
17	Nate Prosser (R)				X	100.00	67	40	82	63	76	62	73	78	30	71	73	76	66	90	83	20	61	69	0	35	3	700,000$
18	Jyrki Jokipakka (R)				X	100.00	67	35	96	68	76	67	71	84	25	64	63	78	63	63	63	44	61	68	0	29	1	700,000$
Rayé
1	Sam Steel (R)	X				100.00	56	39	85	67	70	79	73	73	83	76	67	68	67	63	64	78	16	67	0	23	2	863,333$
2	Mikhail Vorobyev (R)	X				100.00	62	46	87	61	79	78	77	69	71	66	62	70	62	65	63	62	19	64	0	24	2	925,000$
3	Micheal Haley (R)		X			100.00	79	67	59	56	73	65	72	61	66	66	62	70	56	84	74	25	19	63	0	35	2	575,000$
4	Iiro Pakarinen (R)			X		100.00	71	41	81	62	77	68	79	56	53	58	57	76	55	76	73	38	19	63	0	29	1	575,000$
5	Dalton Smith (R)		X			100.00	64	52	78	59	82	77	75	65	51	63	59	67	59	75	68	64	20	63	0	29	3	700,000$
6	Jacob Larsson (R)				X	100.00	62	42	87	64	78	82	79	70	30	68	60	72	52	65	62	80	19	66	0	24	3	575,000$
7	Mikey Anderson (R)				X	100.00	60	42	90	62	74	83	73	66	30	64	60	70	48	61	63	62	19	64	0	22	3	925,000$

	MOYENNE D’ÉQUIPE					100.00	65	42	83	65	76	76	79	73	56	72	68	75	62	74	69	54	53	68

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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	Scott Darling	100.00	80	85	85	89	88	98	97	99	99	80	80	85	81	56	70	87	0
2	Collin Delia (R)	100.00	83	76	94	85	84	86	88	87	86	82	51	78	70	38	69	82	0
Rayé
1	Jason Bacashihua	100.00	74	50	71	77	75	94	94	94	94	76	84	96	99	23	20	80	0
2	Alex Lyon (R)	100.00	78	69	74	81	79	78	80	79	78	78	74	75	81	57	19	76	0

	MOYENNE D’ÉQUIPE	100.00	79	70	81	83	82	89	90	90	89	79	72	84	83	44	45	81

Nom de l’entraîneur	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dave Hakstol	45	43	56	58	64	64	59	CAN	50	2	5,000,000$

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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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKM	GW	FO%	FOT	GA	TA	EG	P/20	S1	S2	S3
1	Daniel Winnik	Flyers (PHI)	LW	5	1	4	5	-1	2	5	5	12	3	9	8.33%	2	86	17.33	0	1	1	1	15	4	0	33.33%	6	2	2	0	1.15	0	0	0
2	Brett Howden	Flyers (PHI)	C	5	3	1	4	-1	0	12	14	18	9	5	16.67%	2	86	17.32	1	0	1	3	15	3	1	59.72%	72	0	1	0	0.92	0	0	1
3	Colin Mcdonald	Flyers (PHI)	RW	5	1	3	4	-1	4	13	3	17	4	10	5.88%	2	82	16.43	0	1	1	1	15	0	0	100.00%	2	2	1	0	0.97	0	0	0
4	Jesperi Kotkaniemi	Flyers (PHI)	C	5	2	1	3	-2	2	9	15	11	6	9	18.18%	4	91	18.23	0	1	1	3	19	4	0	55.74%	122	6	1	1	0.66	0	0	0
5	Derek Forbort	Flyers (PHI)	D	5	0	2	2	0	2	15	9	5	1	1	0.00%	6	122	24.42	0	0	0	1	22	10	0	0.00%	0	1	6	0	0.33	1	0	0
6	Adam Gaudette	Flyers (PHI)	C	5	0	2	2	-1	0	5	5	18	1	8	0.00%	3	70	14.18	0	0	0	1	1	0	0	43.86%	57	0	0	0	0.56	0	0	0
7	Dylan Olsen	Flyers (PHI)	D	5	1	0	1	-3	0	4	9	6	2	2	16.67%	0	104	20.93	1	0	1	2	13	8	0	0.00%	0	5	4	0	0.19	0	0	0
8	Andreas Johnsson	Flyers (PHI)	RW	5	0	1	1	-3	4	9	7	13	7	13	0.00%	7	96	19.35	0	0	0	2	19	8	0	36.36%	22	4	3	0	0.21	0	0	0
9	Jyrki Jokipakka	Flyers (PHI)	D	5	0	1	1	-3	0	6	6	6	1	2	0.00%	5	78	15.74	0	0	0	0	0	1	0	0.00%	0	0	0	0	0.25	0	0	0
10	Brian Flynn	Flyers (PHI)	LW	5	1	0	1	0	0	3	9	11	3	7	9.09%	2	74	14.92	0	0	0	0	0	5	0	44.44%	9	1	2	0	0.27	0	0	0
11	Nate Prosser	Flyers (PHI)	D	5	1	0	1	-5	4	6	5	7	3	5	14.29%	4	69	13.94	0	0	0	0	0	0	0	0.00%	0	4	0	0	0.29	0	0	0
12	Tom Kuhnhackl	Flyers (PHI)	RW	5	1	0	1	-1	0	11	5	5	0	4	20.00%	3	71	14.22	0	0	0	0	1	0	0	75.00%	4	1	2	0	0.28	0	1	0
13	Andy Andreoff	Flyers (PHI)	LW	5	0	0	0	-2	2	5	5	3	2	0	0.00%	1	44	8.87	0	0	0	0	0	4	0	0.00%	2	1	0	0	0.00	0	0	0
14	Travis Boyd	Flyers (PHI)	C	5	0	0	0	-2	0	4	1	6	3	3	0.00%	0	39	7.90	0	0	0	0	0	0	0	50.00%	16	0	0	0	0.00	0	0	0
15	Artturi Lehkonen	Flyers (PHI)	LW	5	0	0	0	-3	2	7	6	12	1	4	0.00%	4	98	19.67	0	0	0	1	19	9	0	0.00%	3	4	0	0	0.00	0	0	0
16	Brandon Manning	Flyers (PHI)	D	5	0	0	0	-4	0	16	12	5	1	2	0.00%	5	104	20.88	0	0	0	0	13	8	0	0.00%	0	1	2	0	0.00	0	0	0
17	Matt Tennyson	Flyers (PHI)	D	5	0	0	0	0	0	9	10	11	1	3	0.00%	2	119	23.83	0	0	0	2	22	11	0	0.00%	0	4	1	0	0.00	0	0	0
18	Gerald Mayhew	Flyers (PHI)	RW	5	0	0	0	-3	0	0	1	0	0	1	0.00%	2	39	7.80	0	0	0	0	0	0	0	0.00%	0	1	1	0	0.00	0	0	0
Statistiques d’équipe totales ou en moyenne				90	11	15	26	-35	22	139	127	166	48	88	6.63%	54	1479	16.44	2	3	5	17	182	80	1	51.75%	315	37	26	1	0.35	1	1	1

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 gardien	Nom de l’équipe	GP	W	L	PCT	GAA	MP	GA	SA	SAR	ST	BG
1	Scott Darling	Flyers (PHI)	4	1	3	0.906	2.77	238	11	117	49	4	1
2	Collin Delia	Flyers (PHI)	1	0	1	0.878	5.00	60	5	41	19	1	4
Statistiques d’équipe totales ou en moyenne			5	1	4	0.899	3.22	298	16	158	68	5	5

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	Plafond salarial	Plafond salarial restant	Exclus du plafond salarial	Salaire annuel 2	Salaire annuel 3	Salaire annuel 4
Adam Gaudette	Flyers (PHI)	C	24	1996-10-03 05:10:31	Yes	170 Lbs	6 ft1	No	No	No	2	Pro & Farm	916,666$	0$	0$	No	916,666$
Alex Lyon	Flyers (PHI)	G	28	1992-12-09 07:25:34	Yes	201 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	0$	0$	No
Andreas Johnsson	Flyers (PHI)	RW	26	1994-11-21 05:30:22	Yes	181 Lbs	5 ft10	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$
Andy Andreoff	Flyers (PHI)	LW	30	1991-05-17 23:11:13	Yes	203 Lbs	6 ft1	No	No	No	1	Pro & Farm	575,000$	0$	0$	No
Artturi Lehkonen	Flyers (PHI)	LW	25	1995-07-04 08:48:34	Yes	177 Lbs	6 ft0	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$
Brandon Manning	Flyers (PHI)	D	31	1990-06-04 17:11:13	Yes	205 Lbs	6 ft1	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$
Brett Howden	Flyers (PHI)	C	23	1998-03-29 03:03:41	Yes	195 Lbs	6 ft3	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$
Brian Flynn	Flyers (PHI)	LW	32	1988-07-26 05:11:13	No	184 Lbs	6 ft1	No	No	No	1	Pro & Farm	575,000$	0$	0$	No
Colin Mcdonald	Flyers (PHI)	RW	36	1984-09-30 05:11:13	No	215 Lbs	6 ft1	No	No	No	1	Pro & Farm	575,000$	0$	0$	No
Collin Delia	Flyers (PHI)	G	27	1994-06-20 07:49:44	Yes	208 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$
Dalton Smith	Flyers (PHI)	LW	29	1992-06-30 12:49:11	Yes	205 Lbs	6 ft2	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$
Daniel Winnik	Flyers (PHI)	LW	36	1985-03-06 11:11:13	No	210 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,400,000$	0$	0$	No
Derek Forbort	Flyers (PHI)	D	29	1992-03-04 05:11:13	Yes	219 Lbs	6 ft4	No	No	No	2	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$
Dylan Olsen	Flyers (PHI)	D	30	1991-01-03 11:11:13	No	225 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,250,000$	0$	0$	No
Gerald Mayhew	Flyers (PHI)	RW	28	1992-12-31 11:44:27	Yes	170 Lbs	5 ft10	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$
Iiro Pakarinen	Flyers (PHI)	RW	29	1991-08-25 23:11:13	Yes	212 Lbs	6 ft1	No	No	No	1	Pro & Farm	575,000$	0$	0$	No
Jacob Larsson	Flyers (PHI)	D	24	1997-04-29 08:51:10	Yes	197 Lbs	6 ft2	No	No	No	3	Pro & Farm	575,000$	0$	0$	No	575,000$	575,000$
Jason Bacashihua	Flyers (PHI)	G	38	1982-09-20 17:11:14	No	189 Lbs	5 ft11	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$
Jesperi Kotkaniemi	Flyers (PHI)	C	20	2000-07-06 03:08:04	Yes	184 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$
Jyrki Jokipakka	Flyers (PHI)	D	29	1991-08-20 23:11:13	Yes	196 Lbs	6 ft3	No	No	No	1	Pro & Farm	700,000$	0$	0$	No
Matt Tennyson	Flyers (PHI)	D	31	1990-04-23 17:11:13	Yes	205 Lbs	6 ft2	No	No	No	3	Pro & Farm	900,000$	0$	0$	No	900,000$	900,000$
Micheal Haley	Flyers (PHI)	LW	35	1986-03-30 06:40:13	Yes	205 Lbs	5 ft11	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$
Mikey Anderson	Flyers (PHI)	D	22	1999-05-25 12:51:39	Yes	196 Lbs	6 ft0	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$
Mikhail Vorobyev	Flyers (PHI)	C	24	1997-01-05 08:21:53	Yes	194 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$
Nate Prosser	Flyers (PHI)	D	35	1986-05-07 17:11:13	Yes	201 Lbs	6 ft2	No	No	No	3	Pro & Farm	700,000$	0$	0$	No	700,000$	700,000$
Sam Steel	Flyers (PHI)	C	23	1998-02-03 03:05:49	Yes	186 Lbs	5 ft11	No	No	No	2	Pro & Farm	863,333$	0$	0$	No	863,333$
Scott Darling	Flyers (PHI)	G	32	1988-12-22 05:11:14	No	232 Lbs	6 ft6	No	No	No	4	Pro & Farm	3,000,000$	0$	0$	No	3,000,000$	3,000,000$	3,000,000$
Tom Kuhnhackl	Flyers (PHI)	RW	29	1992-01-21 17:39:57	Yes	196 Lbs	6 ft2	No	No	No	2	Pro & Farm	600,000$	0$	0$	No	600,000$
Travis Boyd	Flyers (PHI)	C	27	1993-09-14 07:33:39	Yes	185 Lbs	5 ft11	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$

Nombre de joueurs	Âge moyen	Poids moyen	Taille moyenne	Contrat moyen	Salaire moyen 1e année
29	28.69	198 Lbs	6 ft1	2.10	893,276$

Attaque à 5 contre 5
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Artturi Lehkonen	Jesperi Kotkaniemi	Andreas Johnsson	30	1	2	2
2	Daniel Winnik	Brett Howden	Colin Mcdonald	30	1	2	2
3	Brian Flynn	Adam Gaudette	Tom Kuhnhackl	30	1	2	2
4	Andy Andreoff	Travis Boyd	Gerald Mayhew	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Derek Forbort	Matt Tennyson	34	1	2	2
2	Dylan Olsen	Brandon Manning	34	1	2	2
3	Nate Prosser	Jyrki Jokipakka	32	1	2	2
4	Derek Forbort	Matt Tennyson	0	1	2	2

Attaque en svantage numérique
Ligne #	Ailier gauche	Centre	Ailier droit	% temps	PHY	DF	OF
1	Artturi Lehkonen	Jesperi Kotkaniemi	Andreas Johnsson	60	1	2	2
2	Daniel Winnik	Brett Howden	Colin Mcdonald	40	1	2	2

Défense en svantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Derek Forbort	Matt Tennyson	60	1	2	2
2	Dylan Olsen	Brandon Manning	40	1	2	2

Attaque à 4 en désavantage numérique
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Andreas Johnsson	Artturi Lehkonen	60	1	2	2
2	Jesperi Kotkaniemi	Daniel Winnik	40	1	2	2

Défense à 4 en désavantage numérique
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Derek Forbort	Matt Tennyson	60	1	2	2
2	Dylan Olsen	Brandon Manning	40	1	2	2

3 joueurs en désavantage numérique
Ligne #	Ailier	% temps	PHY	DF	OF	Défense	Défense	% temps	PHY	DF	OF
1	Andreas Johnsson	60	1	2	2	Derek Forbort	Matt Tennyson	60	1	2	2
2	Artturi Lehkonen	40	1	2	2	Dylan Olsen	Brandon Manning	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% temps	PHY	DF	OF
1	Andreas Johnsson	Artturi Lehkonen	60	1	2	2
2	Jesperi Kotkaniemi	Daniel Winnik	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% temps	PHY	DF	OF
1	Derek Forbort	Matt Tennyson	60	1	2	2
2	Dylan Olsen	Brandon Manning	40	1	2	2

Attaque dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Artturi Lehkonen	Jesperi Kotkaniemi	Andreas Johnsson	Derek Forbort	Matt Tennyson

Défense dernière minute
Ailier gauche	Centre	Ailier droit	Défense	Défense
Artturi Lehkonen	Jesperi Kotkaniemi	Andreas Johnsson	Derek Forbort	Matt Tennyson

Attaquants supplémentaires
Normal	Avantage numérique	Désavantage numérique
Adam Gaudette, Tom Kuhnhackl, Brian Flynn	Adam Gaudette, Tom Kuhnhackl	Brian Flynn

Défenseurs supplémentaires
Normal	Avantage numérique	Désavantage numérique
Nate Prosser, Jyrki Jokipakka, Dylan Olsen	Nate Prosser	Jyrki Jokipakka, Dylan Olsen

Tirs de pénalité
Andreas Johnsson, Artturi Lehkonen, Jesperi Kotkaniemi, Daniel Winnik, Brett Howden

Gardien
#1 : Collin Delia, #2 : Scott Darling

Lignes d’attaque personnalisées en prolongation
Andreas Johnsson, Artturi Lehkonen, Jesperi Kotkaniemi, Daniel Winnik, Brett Howden, Colin Mcdonald, Colin Mcdonald, Adam Gaudette, Tom Kuhnhackl, Brian Flynn, Travis Boyd

Lignes de défense personnalisées en prolongation
Derek Forbort, Matt Tennyson, Dylan Olsen, Brandon Manning, Nate Prosser

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

	Total												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	Islanders	5	1	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	6	-3	2	0.200	11	15	26	0	0	0	6	5	0	166	37	64	65	0	158	54	22	139	19	2	10.53%	11	0	100.00%	0	69	136	50.74%	55	108	50.93%	39	71	54.93%	112	65	102	43	84	43
	Total	5	1	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	6	-3	2	0.200	11	15	26	0	0	0	6	5	0	166	37	64	65	0	158	54	22	139	19	2	10.53%	11	0	100.00%	0	69	136	50.74%	55	108	50.93%	39	71	54.93%	112	65	102	43	84	43
	_Since Last GM Reset	5	1	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	6	-3	2	0.200	11	15	26	0	0	0	6	5	0	166	37	64	65	0	158	54	22	139	19	2	10.53%	11	0	100.00%	0	69	136	50.74%	55	108	50.93%	39	71	54.93%	112	65	102	43	84	43
	_Vs Conference	5	1	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	6	-3	2	0.200	11	15	26	0	0	0	6	5	0	166	37	64	65	0	158	54	22	139	19	2	10.53%	11	0	100.00%	0	69	136	50.74%	55	108	50.93%	39	71	54.93%	112	65	102	43	84	43
	_Vs Division	5	1	4	0	0	0	0	0	11	16	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	3	6	-3	2	0.200	11	15	26	0	0	0	6	5	0	166	37	64	65	0	158	54	22	139	19	2	10.53%	11	0	100.00%	0	69	136	50.74%	55	108	50.93%	39	71	54.93%	112	65	102	43	84	43

			Total pour les joueurs
Matchs joués	Points	Séquence	Buts	Passes	Points	Tirs pour	Tirs contre	Tirs bloqués	Minutes de pénalités	Mises en échec	Buts en filet désert	Blanchissages
5	2	L4	11	15	26	166	158	54	22	139	0	0

Tous les matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	11	16

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	8	10

Matchs extérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	3	6

Derniers 10 matchs
W	L	OTW	OTL	SOW	SOL
1	4	0	0	0	0

Tentatives en avantage numérique	Buts en avantage numérique	% en avantage numérique	Tentatives en désavantage numérique	Buts contre en désavantage numérique	% en désavantage numérique	Buts pour en désavantage numérique
19	2	10.53%	11	0	100.00%	0

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
37	64	65	0	0	6	5	0

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
69	136	50.74%	55	108	50.93%	39	71	54.93%

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
112	65	102	43	84	43

Derniers matchs 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	RI	Lien
1 - 2020-12-17	4	Islanders	1	Flyers	3	W	R5	Sommaire du match
3 - 2020-12-19	12	Islanders	4	Flyers	3	L		Sommaire du match
5 - 2020-12-21	20	Flyers	1	Islanders	2	L	R5	Sommaire du match
7 - 2020-12-23	28	Flyers	2	Islanders	4	L		Sommaire du match
9 - 2020-12-25	36	Islanders	5	Flyers	2	L	R5	Sommaire du match

Capacité de l’aréna - Tendance du prix des billets - %
	Niveau 1	Niveau 2
Capacité	2000	1000
Prix des billets	45	25
Assistance	5,011	3,000
Assistance PCT	83.52%	100.00%

Revenu
Matchs à domicile restants	Assistance moyenne - %	Revenu moyen par match	Revenu annuel à ce jour	Capacité	Popularité de l’équipe
38	2670 - 89.01%	135,223$	405,668$	3000	100

Dépenses
Dépenses annuelles à ce jour	Salaire total des joueurs	Salaire total moyen des joueurs	Salaire des entraineurs
0$	2,590,500$	1,590,500$	0$

Plafond salarial par jour	Plafond salarial à ce jour	Joueurs Inclus dans le plafond salarial	Joueurs exclut du plafond Salarial
0$	0$	0	0

Estimation
Revenus de la saison estimés	Jours restants de la saison	Dépenses par jour	Dépenses de la saison estimées
0$	0	0$	0$

Afficher ou masquer des colonnes

	Total											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: 5 \| W: 1 \| L: 4 GF: 11 \| GA: 16 \| PP%: 10.53% \| PK%: 100.00% DG: Libre \| Morale : 27 \| Moyenne d’équipe : 70