LHSIR - Phantoms

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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	Lane Pederson	X				100.00	71	71	70	66	71	68	69	67	80	63	67	63	64	44	44	67	50	0	0	22	3	777,500$
2	Gemel Smith	X	X	X		100.00	69	68	72	72	68	74	76	67	80	59	68	65	65	56	56	67	50	0	0	26	1	1,000,000$
3	Givani Smith		X	X		100.00	85	76	87	66	76	54	78	70	25	55	59	61	25	45	45	63	50	0	0	22	2	913,333$
4	Melker Karlsson	X		X		100.00	67	42	89	78	65	62	87	57	40	60	59	77	75	66	69	65	45	0	0	29	1	2,000,000$
5	Mikkel Boedker		X	X		100.00	67	43	99	85	76	54	63	62	32	60	59	72	61	75	77	64	44	0	0	30	1	1,000,000$
6	Maxim Letunov	X				100.00	77	71	91	62	71	70	72	65	80	66	60	66	57	44	44	65	50	0	0	24	1	1,000,000$
7	Nathan Bastian			X		100.00	77	78	75	62	78	77	81	62	50	58	62	65	59	44	44	64	50	0	0	22	3	992,500$
8	Pontus Aberg		X	X		100.00	73	70	81	76	70	75	78	66	50	62	65	67	62	54	55	67	50	0	0	26	1	1,000,000$
9	Lean Bergmann (R)		X	X		100.00	89	46	89	75	76	51	64	51	26	58	55	56	25	45	45	60	50	0	0	21	1	1,000,000$
10	Jack Studnicka (R)	X				100.00	71	65	85	73	65	75	78	65	80	61	65	63	62	44	44	67	50	0	0	21	3	863,333$
11	Evan Rodrigues	X	X	X		100.00	65	41	90	77	66	59	77	61	65	59	64	70	75	63	63	66	50	0	0	26	1	1,000,000$
12	Valentin Zykov		X	X		100.00	78	45	87	71	80	62	59	64	25	65	58	56	25	48	48	62	50	0	0	25	1	1,000,000$
13	Alex Formenton (R)		X			100.00	72	73	71	76	73	67	68	66	50	61	68	64	65	44	44	67	50	0	0	20	3	888,333$
14	Mark Alt				X	100.00	78	77	81	65	77	70	76	47	25	37	42	62	40	44	44	53	50	0	0	28	1	650,000$
15	Luke Green				X	100.00	75	69	90	60	69	40	40	42	25	28	41	59	39	44	44	48	50	0	0	22	2	838,333$
16	Mark Friedman				X	100.00	71	67	81	64	67	75	81	51	25	47	41	59	39	44	44	54	50	0	0	24	2	825,000$
17	Reece Willcox (R)				X	100.00	77	70	92	62	70	71	78	47	25	39	40	61	38	44	44	53	50	0	0	26	3	675,000$
18	Josh Brook (R)				X	100.00	73	71	79	69	71	73	80	47	25	37	41	59	39	44	44	52	50	0	0	21	3	910,833$
Rayé
1	Cole Bardreau (R)	X		X		100.00	86	45	82	63	66	52	62	54	59	60	59	68	25	55	55	63	50	0	0	26	3	700,000$
2	Jack Kopacka		X			100.00	80	72	98	62	72	56	56	56	50	50	57	65	54	44	44	60	50	0	0	22	2	910,833$
3	Stelio Mattheos			X		100.00	78	72	91	55	72	62	64	55	50	49	57	64	54	44	44	60	50	0	0	21	2	925,000$
4	Danil Yurtaykin (R)		X	X		100.00	69	61	89	71	61	60	62	55	50	60	46	59	44	44	44	56	50	0	0	22	1	1,000,000$
5	Tyrell Goulbourne		X	X		100.00	72	70	78	68	70	69	76	45	50	41	44	58	42	44	44	52	50	0	0	26	1	775,000$

	MOYENNE D'ÉQUIPE					100.00	75	64	85	69	71	64	71	57	46	54	56	63	49	49	49	61	50	0

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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	Anton Forsberg	100.00	55	61	76	78	55	57	50	58	53	52	30	48	48	55	50	0	0
2	Charlie Lindgren	100.00	51	58	73	75	48	53	54	58	52	52	30	46	46	53	50	0	0
Rayé
1	Joseph Woll (R)	100.00	50	64	80	80	45	52	50	55	49	49	30	44	44	52	50	0	0

	MOYENNE D'ÉQUIPE	100.00	52	61	76	78	49	54	51	57	51	51	30	46	46	53	50	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dominique Ducharme	73	72	70	68	69	64	79	CAN	49	3	850,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS	FL	FT	S1	S2	S3
1	Gemel Smith	Phantoms (PHI)	C/LW/RW	46	22	17	39	8	34	0	61	71	114	41	98	19.30%	8	852	18.54	9	4	13	35	203	1	0	1	3	109	6	0	59.92%	504	0	2	0.91	0	0	0	0	6	3	3
2	Pontus Aberg	Phantoms (PHI)	LW/RW	46	9	21	30	-3	42	0	106	71	96	24	64	9.38%	13	954	20.75	2	11	13	28	218	1	1	2	7	254	1	0	47.25%	91	0	0	0.63	2	5	0	0	3	1	4
3	Mikkel Boedker	Phantoms (PHI)	LW/RW	44	15	14	29	-3	8	0	32	95	90	26	49	16.67%	9	932	21.20	5	7	12	24	189	1	1	2	2	226	1	1	40.53%	528	0	0	0.62	0	4	0	0	2	2	3
4	Evan Rodrigues	Phantoms (PHI)	C/LW/RW	46	8	21	29	-4	6	0	23	95	84	29	57	9.52%	8	821	17.86	5	7	12	25	190	1	1	2	1	159	2	0	56.04%	778	0	0	0.71	2	3	0	0	0	1	3
5	Alex Formenton	Phantoms (PHI)	LW	46	8	17	25	13	57	15	43	61	100	23	69	8.00%	3	667	14.50	0	6	6	13	126	0	0	0	1	19	3	1	48.78%	41	0	0	0.75	0	0	2	1	1	4	4
6	Valentin Zykov	Phantoms (PHI)	LW/RW	46	13	10	23	16	24	0	45	38	62	17	46	20.97%	4	669	14.54	2	3	5	16	147	0	0	0	0	0	2	0	29.63%	27	0	0	0.69	0	0	0	0	2	1	1
7	Jack Studnicka	Phantoms (PHI)	C	46	8	14	22	11	24	0	21	85	72	17	59	11.11%	8	665	14.48	0	0	0	4	26	0	0	0	1	52	2	1	58.13%	523	0	0	0.66	0	0	0	0	2	3	1
8	Melker Karlsson	Phantoms (PHI)	C/RW	19	9	11	20	2	8	0	20	30	35	11	22	25.71%	7	354	18.67	3	2	5	12	94	0	1	1	1	55	0	2	45.38%	368	0	0	1.13	1	3	0	0	1	3	2
9	Nathan Bastian	Phantoms (PHI)	RW	46	7	8	15	3	37	5	40	30	64	16	42	10.94%	5	524	11.41	0	0	0	0	3	0	0	0	0	0	1	0	44.44%	18	0	0	0.57	0	0	0	1	1	0	3
10	Lean Bergmann	Phantoms (PHI)	LW/RW	46	4	8	12	4	44	0	39	33	32	11	16	12.50%	2	489	10.64	0	0	0	1	6	0	0	0	0	0	0	1	38.46%	26	0	0	0.49	0	0	0	0	1	0	0
11	Mark Friedman	Phantoms (PHI)	D	46	1	9	10	2	105	5	88	16	18	7	9	5.56%	29	1066	23.18	0	4	4	9	215	0	0	0	1	202	0	0	0.00%	0	0	0	0.19	0	0	1	0	0	0	1
12	Josh Brook	Phantoms (PHI)	D	36	2	8	10	5	34	0	73	18	14	5	11	14.29%	25	785	21.81	2	2	4	8	149	0	0	0	0	171	0	0	0.00%	0	0	0	0.25	0	0	0	0	0	0	0
13	Reece Willcox	Phantoms (PHI)	D	46	2	7	9	4	66	0	83	19	15	8	11	13.33%	17	768	16.71	0	1	1	2	72	0	0	0	1	96	1	0	0.00%	0	0	0	0.23	0	0	0	0	2	0	0
14	Maxim Letunov	Phantoms (PHI)	C	46	3	5	8	10	10	0	17	33	19	1	18	15.79%	6	369	8.04	0	1	1	0	10	0	0	0	0	91	0	0	59.71%	206	1	0	0.43	0	0	0	0	0	0	1
15	Mark Alt	Phantoms (PHI)	D	40	1	6	7	4	59	5	82	16	19	5	5	5.26%	27	851	21.29	0	1	1	10	174	0	1	1	0	164	0	0	0.00%	0	0	0	0.16	0	0	0	1	0	0	0
16	Givani Smith	Phantoms (PHI)	LW/RW	11	1	5	6	-3	14	0	18	4	12	5	12	8.33%	0	169	15.42	1	1	2	5	50	0	0	0	0	0	0	0	50.00%	10	0	0	0.71	0	0	0	0	0	1	0
17	Lane Pederson	Phantoms (PHI)	C	46	1	4	5	5	19	5	41	15	22	11	16	4.55%	6	367	7.99	0	0	0	2	27	0	0	0	0	13	0	0	54.55%	55	0	0	0.27	0	0	0	0	0	1	0
18	Cole Bardreau	Phantoms (PHI)	C/RW	44	1	2	3	-1	18	0	14	13	23	6	12	4.35%	3	212	4.83	0	0	0	1	13	0	0	0	0	3	0	0	48.94%	47	0	0	0.28	0	0	0	0	0	0	0
19	Luke Green	Phantoms (PHI)	D	24	0	1	1	4	30	0	37	4	4	0	5	0.00%	8	354	14.77	0	0	0	0	9	0	0	0	0	54	0	0	0.00%	0	0	0	0.06	0	0	0	0	0	0	0
20	Jack Kopacka	Phantoms (PHI)	LW	9	0	0	0	-2	0	0	0	0	1	0	1	0.00%	1	26	2.94	0	0	0	1	8	0	0	0	0	10	0	0	20.00%	5	0	0	0.00	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				779	115	188	303	75	639	35	883	747	896	263	622	12.83%	189	11905	15.28	29	50	79	196	1938	4	5	9	18	1688	19	6	52.49%	3227	1	2	0.51	5	15	3	3	21	20	26

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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	SO	GA	SA	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Anton Forsberg	Phantoms (PHI)	46	22	20	4	0.868	2.60	2700	2	117	885	2	0.733	15	46	0	1	1	2
2	Charlie Lindgren	Phantoms (PHI)	4	0	0	0	0.973	0.71	84	0	1	37	0	0.000	0	0	46	0	0	0
Stats d'équipe Total ou en Moyenne			50	22	20	4	0.872	2.54	2785	2	118	922	2	0.733	15	46	46	1	1	2

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Alex Formenton	Phantoms (PHI)	LW	20	1999-09-13	Yes	190 Lbs	6 ft3	No	No	No	3	Pro & Farm	888,333$	365,363$	888,333$	365,363$	0$	0$	No	888,333$	888,333$
Anton Forsberg	Phantoms (PHI)	G	27	1992-11-26	No	192 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Charlie Lindgren	Phantoms (PHI)	G	26	1993-12-17	No	190 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,300,000$	534,677$	1,300,000$	534,677$	0$	0$	No			Lien
Cole Bardreau	Phantoms (PHI)	C/RW	26	1993-07-22	Yes	185 Lbs	5 ft10	No	No	No	3	Pro & Farm	700,000$	287,903$	700,000$	287,903$	0$	0$	No	700,000$	700,000$
Danil Yurtaykin	Phantoms (PHI)	LW/RW	22	1997-07-01	Yes	165 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Evan Rodrigues	Phantoms (PHI)	C/LW/RW	26	1993-07-28	No	182 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Gemel Smith (Contrat à 1 Volet)	Phantoms (PHI)	C/LW/RW	26	1994-04-16	No	190 Lbs	5 ft10	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	100,000$	41,129$	No			Lien
Givani Smith	Phantoms (PHI)	LW/RW	22	1998-02-27	No	204 Lbs	6 ft2	No	No	No	2	Pro & Farm	913,333$	375,645$	913,333$	375,645$	0$	0$	No	913,333$		Lien
Jack Kopacka	Phantoms (PHI)	LW	22	1998-05-05	No	192 Lbs	6 ft2	No	No	No	2	Pro & Farm	910,833$	374,617$	910,000$	374,274$	0$	0$	No	910,833$		Lien
Jack Studnicka	Phantoms (PHI)	C	21	1999-02-17	Yes	171 Lbs	6 ft1	No	No	No	3	Pro & Farm	863,333$	355,081$	863,333$	355,081$	0$	0$	No	863,333$	863,333$	Lien
Joseph Woll	Phantoms (PHI)	G	21	1998-07-12	Yes	200 Lbs	6 ft3	No	No	No	3	Pro & Farm	850,000$	349,597$	800,000$	329,032$	0$	0$	No	800,000$	800,000$	Lien
Josh Brook	Phantoms (PHI)	D	21	1999-06-17	Yes	192 Lbs	6 ft1	No	No	No	3	Pro & Farm	910,833$	374,617$	910,833$	374,617$	0$	0$	No	910,833$	910,833$
Lane Pederson	Phantoms (PHI)	C	22	1997-08-04	No	192 Lbs	6 ft1	No	No	No	3	Pro & Farm	777,500$	319,778$	690,000$	283,790$	0$	0$	No	690,000$	690,000$	Lien
Lean Bergmann	Phantoms (PHI)	LW/RW	21	1998-10-04	Yes	205 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Luke Green	Phantoms (PHI)	D	22	1998-01-11	No	188 Lbs	6 ft1	No	No	No	2	Pro & Farm	838,333$	344,798$	850,000$	349,597$	0$	0$	No	838,333$		Lien
Mark Alt	Phantoms (PHI)	D	28	1991-10-17	No	201 Lbs	6 ft4	No	No	No	1	Pro & Farm	650,000$	267,339$	650,000$	267,339$	0$	0$	No			Lien
Mark Friedman	Phantoms (PHI)	D	24	1995-12-25	No	185 Lbs	5 ft11	No	No	No	2	Pro & Farm	825,000$	339,315$	825,000$	339,315$	0$	0$	No	825,000$		Lien
Maxim Letunov	Phantoms (PHI)	C	24	1996-02-19	No	180 Lbs	6 ft4	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Melker Karlsson	Phantoms (PHI)	C/RW	29	1990-07-18	No	182 Lbs	5 ft10	No	No	No	1	Pro & Farm	2,000,000$	822,581$	2,000,000$	822,581$	0$	0$	No			Lien
Mikkel Boedker	Phantoms (PHI)	LW/RW	30	1989-12-15	No	210 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Nathan Bastian	Phantoms (PHI)	RW	22	1997-12-06	No	205 Lbs	6 ft4	No	No	No	3	Pro & Farm	992,500$	408,206$	905,000$	372,218$	0$	0$	No	905,000$	905,000$	Lien
Pontus Aberg	Phantoms (PHI)	LW/RW	26	1993-09-22	No	196 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien
Reece Willcox	Phantoms (PHI)	D	26	1994-05-20	Yes	183 Lbs	6 ft3	No	No	No	3	Pro & Farm	675,000$	277,621$	675,000$	277,621$	0$	0$	No	675,000$	675,000$
Stelio Mattheos	Phantoms (PHI)	RW	21	1999-06-13	No	198 Lbs	6 ft1	No	No	No	2	Pro & Farm	925,000$	380,444$	925,000$	380,444$	0$	0$	No	925,000$		Lien
Tyrell Goulbourne	Phantoms (PHI)	LW/RW	26	1994-01-25	No	195 Lbs	5 ft11	No	No	No	1	Pro & Farm	775,000$	318,750$	775,000$	318,750$	0$	0$	No			Lien
Valentin Zykov	Phantoms (PHI)	LW/RW	25	1995-05-14	No	224 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,000,000$	411,290$	1,000,000$	411,290$	0$	0$	No			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
26	24.08	192 Lbs	6 ft1	1.81	953,654$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mikkel Boedker	Melker Karlsson	Pontus Aberg	35	1	2	2
2	Evan Rodrigues	Gemel Smith	Givani Smith	30	1	2	2
3	Alex Formenton	Jack Studnicka	Valentin Zykov	25	1	2	2
4	Lean Bergmann	Lane Pederson	Nathan Bastian	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Reece Willcox	35	1	2	2
2	Mark Alt	Josh Brook	30	1	2	2
3	Luke Green	Lane Pederson	25	1	2	2
4	Mark Friedman	Reece Willcox	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Mikkel Boedker	Melker Karlsson	Pontus Aberg	60	1	2	2
2	Evan Rodrigues	Gemel Smith	Givani Smith	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Reece Willcox	60	1	2	2
2	Mark Alt	Josh Brook	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mikkel Boedker	Melker Karlsson	60	1	2	2
2	Pontus Aberg	Gemel Smith	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Reece Willcox	60	1	2	2
2	Mark Alt	Josh Brook	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Mikkel Boedker	60	1	2	2	Mark Friedman	Reece Willcox	60	1	2	2
2	Melker Karlsson	40	1	2	2	Mark Alt	Josh Brook	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mikkel Boedker	Melker Karlsson	60	1	2	2
2	Pontus Aberg	Gemel Smith	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Reece Willcox	60	1	2	2
2	Mark Alt	Josh Brook	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Mikkel Boedker	Melker Karlsson	Pontus Aberg	Mark Friedman	Reece Willcox

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Mikkel Boedker	Melker Karlsson	Pontus Aberg	Mark Friedman	Reece Willcox

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Maxim Letunov, Alex Formenton, Jack Studnicka	Maxim Letunov, Alex Formenton	Jack Studnicka

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Luke Green, Mark Alt, Josh Brook	Luke Green	Mark Alt, Josh Brook

Tirs de Pénalité
Mikkel Boedker, Melker Karlsson, Pontus Aberg, Gemel Smith, Evan Rodrigues

Gardien
#1 : Anton Forsberg, #2 : Charlie Lindgren

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	Admirals	1	0	0	0	0	1	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	1	2	-1	1	0.500	1	2	3	0	0	49	34	37	6	23	334	302	313	28	15	4	28	21	2	0	0.00%	13	0	100.00%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
2	Bruins	2	0	1	0	0	0	1	0	4	6	-2	2	0	1	0	0	0	1	0	4	6	-2	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	5	9	0	0	49	34	37	6	39	334	302	313	28	44	4	22	42	19	2	10.53%	11	3	72.73%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
3	Crunch	1	1	0	0	0	0	0	0	5	4	1	1	1	0	0	0	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	9	14	0	0	49	34	37	6	27	334	302	313	28	22	11	4	23	12	2	16.67%	2	1	50.00%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
4	Flames	1	0	0	0	0	1	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	3	4	-1	1	0.500	3	6	9	0	0	49	34	37	6	18	334	302	313	28	19	8	14	24	6	0	0.00%	7	2	71.43%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
5	Griffins	2	1	1	0	0	0	0	0	9	6	3	2	1	1	0	0	0	0	0	9	6	3	0	0	0	0	0	0	0	0	0	0	0	2	0.500	9	18	27	0	0	49	34	37	6	38	334	302	313	28	44	12	28	48	13	1	7.69%	13	1	92.31%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
6	Marlies	2	2	0	0	0	0	0	0	7	3	4	2	2	0	0	0	0	0	0	7	3	4	0	0	0	0	0	0	0	0	0	0	0	4	1.000	7	11	18	0	0	49	34	37	6	50	334	302	313	28	35	8	29	42	11	1	9.09%	14	3	78.57%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
7	Monarchs	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	1	0	49	34	37	6	28	334	302	313	28	21	4	14	24	6	1	16.67%	5	0	100.00%	1	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
8	Monsters	11	6	3	0	0	0	0	2	31	28	3	4	3	0	0	0	0	0	1	15	10	5	7	3	3	0	0	0	0	1	16	18	-2	14	0.636	31	53	84	0	0	49	34	37	6	226	334	302	313	28	185	50	154	200	69	10	14.49%	68	12	82.35%	1	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
9	Penguins	4	1	3	0	0	0	0	0	5	7	-2	2	1	1	0	0	0	0	0	4	1	3	2	0	2	0	0	0	0	0	1	6	-5	2	0.250	5	8	13	0	1	49	34	37	6	61	334	302	313	28	76	25	65	78	24	2	8.33%	29	2	93.10%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
10	Rampage	3	2	1	0	0	0	0	0	14	9	5	2	1	1	0	0	0	0	0	8	6	2	1	1	0	0	0	0	0	0	6	3	3	4	0.667	14	24	38	0	0	49	34	37	6	85	334	302	313	28	79	23	38	64	19	6	31.58%	18	4	77.78%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
11	Rocket	3	2	1	0	0	0	0	0	7	5	2	2	2	0	0	0	0	0	0	4	1	3	1	0	1	0	0	0	0	0	3	4	-1	4	0.667	7	13	20	0	1	49	34	37	6	54	334	302	313	28	55	18	34	44	15	2	13.33%	16	1	93.75%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
12	Senators	2	0	2	0	0	0	0	0	5	8	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	5	8	13	0	0	49	34	37	6	42	334	302	313	28	37	7	36	35	4	0	0.00%	17	4	76.47%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
13	Soldiers	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	2	1	1	2	1.000	2	3	5	0	0	49	34	37	6	24	334	302	313	28	21	8	20	18	5	0	0.00%	9	1	88.89%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
14	Sound Tigers	5	1	3	0	0	0	1	0	13	15	-2	2	0	2	0	0	0	0	0	3	6	-3	3	1	1	0	0	0	1	0	10	9	1	4	0.400	13	22	35	0	0	49	34	37	6	127	334	302	313	28	137	39	94	118	25	3	12.00%	40	6	85.00%	0	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
	Total	46	19	20	0	0	2	3	2	123	122	1	24	12	10	0	0	0	1	1	68	57	11	22	7	10	0	0	2	2	1	55	65	-10	48	0.522	123	212	335	2	2	49	34	37	6	961	334	302	313	28	924	255	687	928	261	32	12.26%	311	48	84.57%	4	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
15	Wolf Pack	7	2	4	0	0	0	1	0	15	20	-5	3	1	2	0	0	0	0	0	5	7	-2	4	1	2	0	0	0	1	0	10	13	-3	6	0.429	15	26	41	1	0	49	34	37	6	119	334	302	313	28	134	34	107	147	31	2	6.45%	49	8	83.67%	2	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
	_Since Last GM Reset	46	19	20	0	0	2	3	2	123	122	1	24	12	10	0	0	0	1	1	68	57	11	22	7	10	0	0	2	2	1	55	65	-10	48	0.522	123	212	335	2	2	49	34	37	6	961	334	302	313	28	924	255	687	928	261	32	12.26%	311	48	84.57%	4	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
	_Vs Conference	33	14	14	0	0	1	2	2	82	85	-3	17	10	5	0	0	0	1	1	46	35	11	16	4	9	0	0	1	1	1	36	50	-14	35	0.530	82	139	221	1	2	49	34	37	6	636	334	302	313	28	607	165	465	635	191	21	10.99%	213	36	83.10%	3	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270
	_Vs Division	27	9	10	0	0	1	1	2	64	70	-6	11	5	3	0	0	0	0	1	27	24	3	16	4	7	0	0	1	1	1	37	46	-9	23	0.426	64	109	173	1	1	49	34	37	6	533	334	302	313	28	532	148	420	543	149	17	11.41%	186	28	84.95%	3	728	1327	54.86%	651	1291	50.43%	334	655	50.99%	1116	770	1126	343	550	270

			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
46	48	L1	123	212	335	961	924	255	687	928	2	2

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
46	19	20	0	2	3	2	123	122

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
24	12	10	0	0	1	1	68	57

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
22	7	10	0	2	2	1	55	65

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	4	0	2	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
261	32	12.26%	311	48	84.57%	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
334	302	313	28	49	34	37	6

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
728	1327	54.86%	651	1291	50.43%	334	655	50.99%

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
1116	770	1126	343	550	270

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	Lien
1 - 2020-09-27	1	Phantoms	5	Wolf Pack	4	W	X	X	Sommaire du Match
2 - 2020-09-28	13	Monsters	1	Phantoms	3	W			Sommaire du Match
4 - 2020-09-30	30	Phantoms	3	Monsters	1	W			Sommaire du Match
5 - 2020-10-01	37	Monsters	4	Phantoms	3	L	X	X	Sommaire du Match
6 - 2020-10-02	47	Phantoms	0	Monsters	1	L			Sommaire du Match
8 - 2020-10-04	61	Wolf Pack	2	Phantoms	1	L			Sommaire du Match
10 - 2020-10-06	75	Wolf Pack	4	Phantoms	2	L			Sommaire du Match
12 - 2020-10-08	82	Phantoms	3	Monsters	4	L	X	X	Sommaire du Match
15 - 2020-10-11	98	Bruins	2	Phantoms	3	W	X	X	Sommaire du Match
16 - 2020-10-12	104	Phantoms	2	Monsters	4	L			Sommaire du Match
18 - 2020-10-14	114	Phantoms	0	Penguins	3	L			Sommaire du Match
20 - 2020-10-16	129	Sound Tigers	2	Phantoms	0	L			Sommaire du Match
22 - 2020-10-18	137	Monsters	4	Phantoms	6	W			Sommaire du Match
23 - 2020-10-19	149	Phantoms	1	Penguins	3	L			Sommaire du Match
24 - 2020-10-20	156	Phantoms	3	Wolf Pack	2	W			Sommaire du Match
25 - 2020-10-21	168	Rampage	5	Phantoms	4	L			Sommaire du Match
26 - 2020-10-22	178	Phantoms	0	Monsters	3	L			Sommaire du Match
28 - 2020-10-24	190	Monsters	1	Phantoms	3	W			Sommaire du Match
31 - 2020-10-27	206	Senators	3	Phantoms	2	L			Sommaire du Match
32 - 2020-10-28	216	Phantoms	4	Monsters	2	W			Sommaire du Match
34 - 2020-10-30	224	Phantoms	0	Wolf Pack	3	L			Sommaire du Match
36 - 2020-11-01	235	Sound Tigers	4	Phantoms	3	L			Sommaire du Match
38 - 2020-11-03	250	Rocket	0	Phantoms	2	W			Sommaire du Match
40 - 2020-11-05	261	Phantoms	2	Soldiers	1	W			Sommaire du Match
42 - 2020-11-07	269	Marlies	2	Phantoms	5	W			Sommaire du Match
45 - 2020-11-10	287	Wolf Pack	1	Phantoms	2	W			Sommaire du Match
46 - 2020-11-11	301	Phantoms	3	Senators	5	L			Sommaire du Match
48 - 2020-11-13	310	Penguins	0	Phantoms	4	W			Sommaire du Match
50 - 2020-11-15	332	Penguins	1	Phantoms	0	L			Sommaire du Match
51 - 2020-11-16	343	Phantoms	6	Rampage	3	W			Sommaire du Match
53 - 2020-11-18	353	Phantoms	2	Sound Tigers	3	L			Sommaire du Match
54 - 2020-11-19	360	Rampage	1	Phantoms	4	W			Sommaire du Match
55 - 2020-11-20	370	Phantoms	4	Sound Tigers	3	W			Sommaire du Match
56 - 2020-11-21	379	Rocket	1	Phantoms	2	W			Sommaire du Match
58 - 2020-11-23	397	Phantoms	4	Sound Tigers	3	W	X	X	Sommaire du Match
59 - 2020-11-24	407	Monarchs	4	Phantoms	2	L			Sommaire du Match
60 - 2020-11-25	418	Griffins	2	Phantoms	7	W			Sommaire du Match
62 - 2020-11-27	431	Phantoms	3	Flames	4	L	X		Sommaire du Match
63 - 2020-11-28	441	Marlies	1	Phantoms	2	W			Sommaire du Match
64 - 2020-11-29	449	Phantoms	4	Monsters	3	W			Sommaire du Match
66 - 2020-12-01	461	Griffins	4	Phantoms	2	L			Sommaire du Match
68 - 2020-12-03	477	Phantoms	3	Rocket	4	L			Sommaire du Match
69 - 2020-12-04	486	Phantoms	1	Admirals	2	L	X		Sommaire du Match
70 - 2020-12-05	490	Bruins	4	Phantoms	1	L			Sommaire du Match
71 - 2020-12-06	506	Crunch	4	Phantoms	5	W			Sommaire du Match
73 - 2020-12-08	518	Phantoms	2	Wolf Pack	4	L			Sommaire du Match
74 - 2020-12-09	527	Penguins	-	Phantoms	-
75 - 2020-12-10	538	Phantoms	-	Crunch	-
77 - 2020-12-12	544	Phantoms	-	Sound Tigers	-
78 - 2020-12-13	556	Condors	-	Phantoms	-
79 - 2020-12-14	565	Phantoms	-	Griffins	-
80 - 2020-12-15	577	Sharks	-	Phantoms	-
82 - 2020-12-17	591	Penguins	-	Phantoms	-
84 - 2020-12-19	602	Phantoms	-	Moose	-
86 - 2020-12-21	614	Phantoms	-	Stars	-
87 - 2020-12-22	624	Flames	-	Phantoms	-
88 - 2020-12-23	632	Phantoms	-	Marlies	-
90 - 2020-12-25	642	Phantoms	-	Crunch	-
91 - 2020-12-26	649	IceHogs	-	Phantoms	-
93 - 2020-12-28	666	Moose	-	Phantoms	-
95 - 2020-12-30	684	Wolves	-	Phantoms	-
96 - 2020-12-31	695	Phantoms	-	Sharks	-
97 - 2021-01-01	707	Admirals	-	Phantoms	-
98 - 2021-01-02	714	Phantoms	-	Wolves	-
99 - 2021-01-03	725	Soldiers	-	Phantoms	-
101 - 2021-01-05	740	Phantoms	-	Crunch	-
102 - 2021-01-06	748	Wolf Pack	-	Phantoms	-
103 - 2021-01-07	756	Phantoms	-	Crunch	-
105 - 2021-01-09	769	Phantoms	-	Senators	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10	778	Rampage	-	Phantoms	-
107 - 2021-01-11	790	Phantoms	-	Bruins	-
108 - 2021-01-12	796	Stars	-	Phantoms	-
110 - 2021-01-14	814	Sound Tigers	-	Phantoms	-
112 - 2021-01-16	827	Phantoms	-	Condors	-
114 - 2021-01-18	839	Sound Tigers	-	Phantoms	-
115 - 2021-01-19	848	Phantoms	-	Penguins	-
117 - 2021-01-21	860	Monsters	-	Phantoms	-
118 - 2021-01-22	869	Phantoms	-	IceHogs	-
120 - 2021-01-24	883	Monsters	-	Phantoms	-
121 - 2021-01-25	891	Phantoms	-	Penguins	-
122 - 2021-01-26	900	Phantoms	-	Griffins	-
123 - 2021-01-27	902	Phantoms	-	Monarchs	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
17	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,926,697$	2,379,498$	2,358,082$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	1,426,292$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	51	26,044$	1,328,244$

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