ASHL - Adirondack Phantoms

Philadelphia Flyers
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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 Moyen
1	Benoit Pouliot		X	X		100.00	75	45	75	73	77	82	77	75	55	72	73	62	76	88	91	70	40	0	0	34	1	1,000,000$
2	Mike Winther (R)	X				100.00	70	40	78	88	71	78	74	78	75	78	77	66	74	71	72	70	34	0	0	26	1	875,000$
3	Fredrik Karlstrom (R)	X	X	X		100.00	63	32	92	81	77	77	77	78	74	78	75	68	73	65	64	70	45	0	0	22	1	900,000$
4	Michael Parks			X		100.00	80	37	76	79	80	81	81	75	62	78	76	69	76	70	70	70	45	0	0	28	2	1,250,000$
5	Vladimir Sobotka	X	X			100.00	83	45	72	77	73	75	74	78	78	76	75	68	77	96	96	70	45	0	0	33	2	1,250,000$
6	Wojtek Wolski		X	X		100.00	69	43	84	72	82	78	78	75	60	75	74	63	77	98	99	70	45	0	0	34	2	800,000$
7	Zach Hamill	X				100.00	56	46	88	76	75	73	72	74	76	73	74	67	73	86	88	70	45	0	0	32	1	800,000$
8	Zach Budish	X		X		100.00	85	45	75	76	84	77	77	75	66	77	76	70	72	83	81	70	45	0	0	29	2	750,000$
9	Alexis Loiseau (R)	X				100.00	74	38	78	81	76	76	76	80	74	79	78	68	74	70	73	70	25	0	0	26	2	1,600,000$
10	Alexandre Mallet	X	X	X		100.00	80	38	77	75	77	74	73	75	74	75	75	66	70	70	72	70	35	0	0	28	2	1,250,000$
11	Sebastian Repo (R)			X		100.00	80	43	75	74	85	78	82	76	70	74	75	71	71	66	65	70	45	0	0	24	2	800,000$
12	Keegan Kolesar (R)			X		100.00	89	50	69	71	88	75	77	76	66	72	75	65	70	64	64	70	45	0	0	23	2	900,000$
13	Alex Plante				X	100.00	82	48	71	70	94	79	73	72	50	73	61	85	57	87	92	70	45	0	0	31	1	1,700,000$
14	Tyler Lewington (R)				X	100.00	88	45	71	76	86	81	80	76	50	76	61	82	63	69	70	70	45	0	0	26	1	1,250,000$
15	Taylor Chorney				X	100.00	75	45	87	73	76	74	71	76	53	78	59	84	66	95	98	70	45	0	0	33	1	1,900,000$
16	Daniel Brickley (R)				X	100.00	87	43	74	72	84	78	75	73	50	77	64	83	61	63	65	70	45	0	0	25	2	1,200,000$
17	Greg Pateryn				X	100.00	87	46	73	73	82	75	73	74	50	77	62	86	62	85	87	70	45	0	0	30	1	1,950,000$
18	Teemu Eronen				X	100.00	70	42	81	80	76	78	73	78	50	79	65	82	68	83	84	70	35	0	0	30	3	1,950,000$
19	Randy Gazzola				X	100.00	76	40	81	76	79	79	75	77	60	78	66	80	63	72	74	70	45	0	0	27	2	1,700,000$
20	Markus Niemelainen (R)				X	100.00	81	38	76	77	80	76	74	72	50	72	57	81	57	57	57	70	45	0	0	22	1	750,000$
Rayé
1	Nikita Popugaev (R)		X	X		100.00	73	35	79	76	85	76	72	73	60	71	71	62	70	54	53	70	32	0	0	22	1	800,000$
2	Chris Martenet (R)				X	100.00	91	52	69	69	90	75	73	66	50	69	58	82	58	66	64	70	35	0	0	24	2	600,000$

	MOYENNE D'ÉQUIPE					100.00	78	43	77	76	81	77	75	75	62	75	69	73	69	75	76	70	41	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	Aaron Dell	99.00	85	81	84	85	89	89	89	88	89	88	90	68	69	70	35	0	0
2	Jakub Kovar	100.00	86	88	85	86	89	86	87	87	88	87	89	64	63	70	25	0	0
Rayé
1	Anthony Brodeur (R)	100.00	84	80	81	79	83	81	82	81	81	80	80	54	54	70	35	0	0

	MOYENNE D'ÉQUIPE	99.67	85	83	83	83	87	85	86	85	86	85	86	62	62	70	32	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Claude Noel	90	90	85	85	85	85	70	CAN	65	1	950,000$

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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	PKS	PKM	GW	GT	FO%	FOT	P/20	PSS	S1	S2	S3
1	Alex Plante	Adirondack Phantoms (PHI)	D	25	3	14	17	2	24	36	18	45	11	26	6.67%	35	480	19.23	3	5	8	31	76	0	69	1	0	0.00%	0	0.71	0	2	1	0
2	Daniel Brickley	Adirondack Phantoms (PHI)	D	25	1	14	15	-6	18	31	31	43	6	23	2.33%	44	532	21.30	0	5	5	24	59	1	75	0	0	0.00%	0	0.56	0	0	0	1
3	Sebastian Repo	Adirondack Phantoms (PHI)	RW	25	9	6	15	4	20	70	20	62	25	41	14.52%	5	509	20.38	3	4	7	11	64	0	0	0	0	46.34%	123	0.59	0	2	0	1
4	Tyler Lewington	Adirondack Phantoms (PHI)	D	25	2	10	12	-5	18	37	28	16	5	24	12.50%	20	455	18.24	0	0	0	0	4	0	28	1	0	0.00%	0	0.53	0	0	1	1
5	Greg Pateryn	Adirondack Phantoms (PHI)	D	25	1	11	12	-4	30	67	34	26	6	31	3.85%	53	589	23.56	1	3	4	13	63	0	52	0	0	0.00%	0	0.41	0	0	1	2
6	Zach Budish	Adirondack Phantoms (PHI)	C/RW	25	7	5	12	1	16	56	58	56	21	53	12.50%	4	488	19.55	1	2	3	12	71	0	22	2	1	54.05%	555	0.49	3	3	0	2
7	Fredrik Karlstrom	Adirondack Phantoms (PHI)	C/LW/RW	25	8	3	11	0	0	4	32	68	18	55	11.76%	11	585	23.43	3	2	5	11	69	0	87	0	2	51.11%	225	0.38	3	1	1	0
8	Michael Parks	Adirondack Phantoms (PHI)	RW	25	5	6	11	-13	12	32	26	69	26	45	7.25%	3	557	22.32	3	5	8	17	64	1	51	0	0	46.36%	151	0.39	0	0	0	1
9	Taylor Chorney	Adirondack Phantoms (PHI)	D	25	1	10	11	-2	6	18	38	31	17	32	3.23%	32	604	24.17	1	5	6	14	72	0	75	0	1	0.00%	0	0.36	0	0	1	0
10	Wojtek Wolski	Adirondack Phantoms (PHI)	LW/RW	25	5	3	8	5	4	19	23	43	13	37	11.63%	2	442	17.69	0	0	0	2	28	0	8	0	1	42.86%	420	0.36	0	2	1	1
11	Randy Gazzola	Adirondack Phantoms (PHI)	D	25	1	7	8	1	12	11	18	11	10	7	9.09%	19	330	13.22	0	0	0	0	0	0	0	0	0	0.00%	0	0.48	0	0	0	1
12	Vladimir Sobotka	Adirondack Phantoms (PHI)	C/LW	25	4	3	7	0	10	46	15	54	19	42	7.41%	2	519	20.77	2	2	4	15	72	1	85	2	0	52.73%	55	0.27	1	0	1	0
13	Zach Hamill	Adirondack Phantoms (PHI)	C	25	3	3	6	6	0	3	22	35	12	21	8.57%	4	347	13.90	0	0	0	0	1	0	4	0	0	47.06%	17	0.35	0	0	0	0
14	Alexandre Mallet	Adirondack Phantoms (PHI)	C/LW/RW	16	1	3	4	-8	2	8	14	13	8	15	7.69%	1	185	11.59	1	2	3	6	24	0	12	1	0	56.52%	23	0.43	0	0	0	0
15	Mike Winther	Adirondack Phantoms (PHI)	C	20	2	1	3	-9	0	10	20	35	11	18	5.71%	1	240	12.03	0	0	0	1	10	1	14	2	0	46.48%	256	0.25	1	0	0	0
16	Benoit Pouliot	Adirondack Phantoms (PHI)	LW/RW	14	2	0	2	-2	0	5	16	11	3	12	18.18%	1	202	14.47	0	0	0	1	6	0	13	1	1	42.47%	186	0.20	0	1	0	0
17	Keegan Kolesar	Adirondack Phantoms (PHI)	RW	25	1	1	2	-4	12	29	10	23	4	11	4.35%	2	236	9.44	0	0	0	0	0	0	0	0	0	46.15%	13	0.17	0	0	0	0
18	Teemu Eronen	Adirondack Phantoms (PHI)	D	19	0	1	1	1	0	1	3	3	0	0	0.00%	4	20	1.06	0	0	0	1	0	0	3	0	0	0.00%	0	0.99	0	0	0	0
19	Nick Suzuki	Philadelphia Flyers	C/RW	3	0	1	1	0	0	5	5	6	0	4	0.00%	0	39	13.09	0	0	0	0	0	0	0	0	0	33.33%	3	0.51	0	0	0	0
20	Markus Niemelainen	Adirondack Phantoms (PHI)	D	25	0	0	0	0	0	0	0	1	0	0	0.00%	1	3	0.13	0	0	0	0	0	0	0	0	0	0.00%	0	0.00	0	0	0	0
21	Nikita Popugaev	Adirondack Phantoms (PHI)	LW/RW	12	0	0	0	0	0	0	0	0	0	0	0.00%	0	4	0.41	0	0	0	0	0	0	0	0	0	0.00%	0	0.00	0	0	0	0
22	Chris Martenet	Adirondack Phantoms (PHI)	D	19	0	0	0	0	0	0	0	0	0	0	0.00%	0	2	0.13	0	0	0	0	0	0	0	0	0	0.00%	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				478	56	102	158	-33	184	488	431	651	215	497	8.60%	244	7378	15.44	18	35	53	159	691	4	606	10	6	48.20%	2027	0.43	8	11	7	10

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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	GA	SA	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Aaron Dell	Adirondack Phantoms (PHI)	25	10	11	4	0.912	2.52	1452	6	61	697	1	1	0.500	8	25	0	1	2	1
2	Anthony Brodeur	Adirondack Phantoms (PHI)	2	0	0	0	1.000	0.00	63	0	0	15	0	0	0.000	0	0	19	0	0	0
Stats d'équipe Total ou en Moyenne			27	10	11	4	0.914	2.42	1515	6	61	712	1	1	0.500	8	25	19	1	2	1

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3
Aaron Dell	Adirondack Phantoms (PHI)	G	31	1988-01-22 13:08:31	No	205 Lbs	6 ft0	No	No	No	2	Pro & Farm	750,000$	522,606$	750,000$	522,606$	0$	0$	No	750,000$
Alex Plante	Adirondack Phantoms (PHI)	D	31	1988-01-22 06:29:38	No	230 Lbs	6 ft4	No	No	No	1	Pro & Farm	1,700,000$	1,184,574$	1,700,000$	1,184,574$	0$	0$	No
Alexandre Mallet	Adirondack Phantoms (PHI)	C/LW/RW	28	1991-01-22 04:34:51	No	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,250,000$	871,010$	1,250,000$	871,010$	0$	0$	No	1,250,000$
Alexis Loiseau	Adirondack Phantoms (PHI)	C	26	1993-01-22 16:01:11	Yes	179 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,600,000$	1,114,893$	1,600,000$	1,114,893$	0$	0$	No	1,600,000$
Anthony Brodeur	Adirondack Phantoms (PHI)	G	25	1994-01-22 07:21:10	Yes	194 Lbs	5 ft10	No	No	No	1	Pro & Farm	650,000$	452,925$	650,000$	452,925$	0$	0$	No
Benoit Pouliot	Adirondack Phantoms (PHI)	LW/RW	34	1985-01-22 12:29:38	No	199 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,000,000$	696,808$	1,000,000$	696,808$	0$	0$	No
Chris Martenet	Adirondack Phantoms (PHI)	D	24	1995-01-22 01:57:24	Yes	216 Lbs	6 ft7	No	No	No	2	Pro & Farm	600,000$	418,085$	600,000$	418,085$	0$	0$	No	600,000$
Daniel Brickley	Adirondack Phantoms (PHI)	D	25	1994-01-22 11:12:14	Yes	205 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,200,000$	836,170$	1,200,000$	836,170$	0$	0$	No	1,200,000$
Fredrik Karlstrom	Adirondack Phantoms (PHI)	C/LW/RW	22	1997-01-22 03:40:25	Yes	185 Lbs	6 ft2	No	No	No	1	Pro & Farm	900,000$	627,127$	900,000$	627,127$	0$	0$	No
Greg Pateryn	Adirondack Phantoms (PHI)	D	30	1989-01-22 09:14:31	No	214 Lbs	6 ft3	No	No	No	1	Pro & Farm	1,950,000$	1,358,776$	1,950,000$	1,358,776$	0$	0$	No
Jakub Kovar	Adirondack Phantoms (PHI)	G	32	1987-01-22 02:33:31	No	201 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,200,000$	836,170$	1,200,000$	836,170$	0$	0$	No	1,200,000$
Keegan Kolesar	Adirondack Phantoms (PHI)	RW	23	1996-01-22 03:29:26	Yes	227 Lbs	6 ft2	No	No	No	2	Pro & Farm	900,000$	627,127$	900,000$	627,127$	0$	0$	No	900,000$
Markus Niemelainen	Adirondack Phantoms (PHI)	D	22	1997-01-22 06:53:24	Yes	190 Lbs	6 ft6	No	No	No	1	Pro & Farm	750,000$	522,606$	750,000$	522,606$	0$	0$	No
Michael Parks	Adirondack Phantoms (PHI)	RW	28	1991-01-22 10:15:43	No	196 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,250,000$	871,010$	1,250,000$	871,010$	0$	0$	No	1,250,000$
Mike Winther	Adirondack Phantoms (PHI)	C	26	1993-01-22 07:52:34	Yes	170 Lbs	5 ft11	No	No	No	1	Pro & Farm	875,000$	609,707$	875,000$	609,707$	0$	0$	No
Nikita Popugaev	Adirondack Phantoms (PHI)	LW/RW	22	1997-01-22 07:00:26	Yes	216 Lbs	6 ft6	No	No	No	1	Pro & Farm	800,000$	557,446$	800,000$	557,446$	0$	0$	No
Randy Gazzola	Adirondack Phantoms (PHI)	D	27	1992-01-22 18:09:29	No	201 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,700,000$	1,184,574$	1,700,000$	1,184,574$	0$	0$	No	1,700,000$
Sebastian Repo	Adirondack Phantoms (PHI)	RW	24	1995-01-22 03:08:53	Yes	212 Lbs	6 ft3	No	No	No	2	Pro & Farm	800,000$	557,446$	800,000$	557,446$	0$	0$	No	800,000$
Taylor Chorney	Adirondack Phantoms (PHI)	D	33	1986-01-22 18:29:38	No	193 Lbs	6 ft0	No	No	No	1	Pro & Farm	1,900,000$	1,323,936$	1,900,000$	1,323,936$	0$	0$	No
Teemu Eronen	Adirondack Phantoms (PHI)	D	30	1989-01-22 20:03:05	No	180 Lbs	5 ft10	No	No	No	3	Pro & Farm	1,950,000$	1,358,776$	1,950,000$	1,358,776$	0$	0$	No	1,950,000$	1,950,000$
Tyler Lewington	Adirondack Phantoms (PHI)	D	26	1993-01-22 04:11:09	Yes	194 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,250,000$	871,010$	1,250,000$	871,010$	0$	0$	No
Vladimir Sobotka	Adirondack Phantoms (PHI)	C/LW	33	1986-01-22 18:29:38	No	183 Lbs	5 ft10	No	No	No	2	Pro & Farm	1,250,000$	871,010$	1,250,000$	871,010$	0$	0$	No	1,250,000$
Wojtek Wolski	Adirondack Phantoms (PHI)	LW/RW	34	1985-01-22 12:29:38	No	215 Lbs	6 ft3	No	No	No	2	Pro & Farm	800,000$	557,446$	800,000$	557,446$	0$	0$	No	800,000$
Zach Budish	Adirondack Phantoms (PHI)	C/RW	29	1990-01-22 06:02:20	No	214 Lbs	6 ft3	No	No	No	2	Pro & Farm	750,000$	522,606$	750,000$	522,606$	0$	0$	No	750,000$
Zach Hamill	Adirondack Phantoms (PHI)	C	32	1987-01-22 00:29:38	No	180 Lbs	5 ft11	No	No	No	1	Pro & Farm	800,000$	557,446$	800,000$	557,446$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
25	27.88	200 Lbs	6 ft2	1.60	1,143,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Fredrik Karlstrom	Zach Budish	Vladimir Sobotka	25	1	2	2
2	Keegan Kolesar	Benoit Pouliot	Michael Parks	25	1	2	2
3	Sebastian Repo	Wojtek Wolski	Zach Hamill	25	1	2	2
4	Fredrik Karlstrom	Michael Parks	Sebastian Repo	25	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Plante	Taylor Chorney	25	1	2	2
2	Greg Pateryn	Randy Gazzola	25	1	2	2
3	Tyler Lewington	Daniel Brickley	25	1	2	2
4	Greg Pateryn	Taylor Chorney	25	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Fredrik Karlstrom	Zach Budish	Vladimir Sobotka	60	1	2	2
2	Wojtek Wolski	Sebastian Repo	Michael Parks	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Plante	Taylor Chorney	60	1	2	2
2	Greg Pateryn	Daniel Brickley	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Fredrik Karlstrom	Vladimir Sobotka	60	1	2	2
2	Zach Budish	Michael Parks	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Daniel Brickley	Taylor Chorney	60	1	2	2
2	Greg Pateryn	Alex Plante	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Michael Parks	60	1	2	2	Daniel Brickley	Taylor Chorney	60	1	2	2
2	Fredrik Karlstrom	40	1	2	2	Greg Pateryn	Alex Plante	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Fredrik Karlstrom	Zach Budish	60	1	2	2
2	Vladimir Sobotka	Michael Parks	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Alex Plante	Taylor Chorney	60	1	2	2
2	Greg Pateryn	Tyler Lewington	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Fredrik Karlstrom	Zach Budish	Vladimir Sobotka	Alex Plante	Taylor Chorney

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Fredrik Karlstrom	Zach Budish	Vladimir Sobotka	Alex Plante	Taylor Chorney

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Michael Parks, Fredrik Karlstrom, Zach Budish	Michael Parks, Fredrik Karlstrom	Michael Parks

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Taylor Chorney, Greg Pateryn, Daniel Brickley	Taylor Chorney	Taylor Chorney, Daniel Brickley

Tirs de Pénalité
Fredrik Karlstrom, Zach Budish, Vladimir Sobotka, Michael Parks, Wojtek Wolski

Gardien
#1 : Aaron Dell, #2 : Jakub Kovar

Lignes d'Attaque Perso. en Prol.
Zach Budish, Benoit Pouliot, Wojtek Wolski, Michael Parks, Zach Hamill, Vladimir Sobotka, Vladimir Sobotka, Keegan Kolesar, Fredrik Karlstrom, Sebastian Repo, Alexis Loiseau

Lignes de Défense Perso. en Prol.
Tyler Lewington, Taylor Chorney, Greg Pateryn, Alex Plante, Daniel Brickley

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	Albany Devils	5	1	2	0	0	0	0	2	10	16	-6	4	1	1	0	0	0	0	2	8	12	-4	1	0	1	0	0	0	0	0	2	4	-2	4	0.400	10	17	27	0	0	28	14	14	0	141	222	211	212	14	124	45	36	114	21	3	14.29%	17	1	94.12%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
2	Bridgeport Sound Tigers	1	0	1	0	0	0	0	0	0	2	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	0	0	0	0	0	28	14	14	0	22	222	211	212	14	31	11	10	18	2	0	0.00%	5	0	100.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
3	CCCP Red Army	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	3	6	9	0	0	28	14	14	0	27	222	211	212	14	32	7	4	19	2	0	0.00%	2	0	100.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
4	Charlotte Checkers	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	1	0	28	14	14	0	25	222	211	212	14	32	16	2	20	2	1	50.00%	1	1	0.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
5	Chicago Wolves	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	2	1	2	1.000	3	5	8	0	0	28	14	14	0	22	222	211	212	14	42	18	8	22	3	1	33.33%	4	1	75.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
6	Connecticut Whale	1	1	0	0	0	0	0	0	5	1	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	1	4	2	1.000	5	9	14	0	0	28	14	14	0	22	222	211	212	14	24	10	4	15	5	2	40.00%	2	0	100.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
7	Gatineau Olympiques	2	2	0	0	0	0	0	0	7	2	5	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	4	1	3	4	1.000	7	14	21	0	0	28	14	14	0	43	222	211	212	14	63	20	20	43	5	2	40.00%	10	0	100.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
8	Lake Erie Monsters	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	28	14	14	0	29	222	211	212	14	28	8	10	19	9	2	22.22%	5	2	60.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
9	Manitoba Moose	2	2	0	0	0	0	0	0	6	4	2	2	2	0	0	0	0	0	0	6	4	2	0	0	0	0	0	0	0	0	0	0	0	4	1.000	6	11	17	0	0	28	14	14	0	50	222	211	212	14	48	15	16	42	5	2	40.00%	8	3	62.50%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
10	Mercer Island Hafgufa	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	6	9	0	0	28	14	14	0	20	222	211	212	14	30	9	14	17	2	2	100.00%	7	1	85.71%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
11	Norfolk Admirals	1	0	1	0	0	0	0	0	1	4	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	1	1	2	0	0	28	14	14	0	38	222	211	212	14	24	9	2	9	2	0	0.00%	1	0	100.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
12	Peoria Rivermen	2	0	2	0	0	0	0	0	2	6	-4	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	2	6	-4	0	0.000	2	4	6	0	0	28	14	14	0	58	222	211	212	14	68	11	16	42	4	1	25.00%	8	2	75.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
13	Providence Bruins	1	0	0	0	0	1	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	2	3	-1	1	0.500	2	3	5	0	0	28	14	14	0	25	222	211	212	14	36	11	8	18	5	0	0.00%	2	2	0.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
14	San Antonio Rampage	2	1	1	0	0	0	0	0	5	5	0	2	1	1	0	0	0	0	0	5	5	0	0	0	0	0	0	0	0	0	0	0	0	2	0.500	5	9	14	0	0	28	14	14	0	39	222	211	212	14	56	18	20	31	4	0	0.00%	9	2	77.78%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
	Total	25	10	11	0	0	1	0	3	56	65	-9	13	6	4	0	0	0	0	3	30	33	-3	12	4	7	0	0	1	0	0	26	32	-6	24	0.480	56	102	158	1	0	28	14	14	0	651	222	211	212	14	713	244	190	488	82	18	21.95%	89	17	80.90%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
15	Trois-Rivières Draveurs	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	0	0	28	14	14	0	35	222	211	212	14	29	14	6	24	3	0	0.00%	2	1	50.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
16	Wilkes-Barre/Scranton Penguins	2	1	0	0	0	0	0	1	4	4	0	1	0	0	0	0	0	0	1	1	2	-1	1	1	0	0	0	0	0	0	3	2	1	3	0.750	4	7	11	0	0	28	14	14	0	55	222	211	212	14	46	22	14	35	8	2	25.00%	6	1	83.33%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
	_Since Last GM Reset	25	10	11	0	0	1	0	3	56	65	-9	13	6	4	0	0	0	0	3	30	33	-3	12	4	7	0	0	1	0	0	26	32	-6	24	0.480	56	102	158	1	0	28	14	14	0	651	222	211	212	14	713	244	190	488	82	18	21.95%	89	17	80.90%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
	_Vs Conference	18	6	8	0	0	1	0	3	39	50	-11	10	4	3	0	0	0	0	3	22	27	-5	8	2	5	0	0	1	0	0	17	23	-6	16	0.444	39	69	108	1	0	28	14	14	0	479	222	211	212	14	482	178	122	345	59	10	16.95%	55	11	80.00%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161
	_Vs Division	11	3	3	0	0	0	0	3	23	30	-7	5	1	1	0	0	0	0	3	9	14	-5	6	2	2	0	0	0	0	0	14	16	-2	9	0.409	23	41	64	1	0	28	14	14	0	292	222	211	212	14	289	111	70	221	40	8	20.00%	33	3	90.91%	0	387	811	47.72%	414	839	49.34%	176	361	48.75%	593	406	599	187	322	161

			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
25	24	W3	56	102	158	651	713	244	190	488	1	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
25	10	11	0	1	0	3	56	65

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
13	6	4	0	0	0	3	30	33

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	4	7	0	1	0	0	26	32

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
6	3	0	0	0	1

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
82	18	21.95%	89	17	80.90%	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
222	211	212	14	28	14	14	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
387	811	47.72%	414	839	49.34%	176	361	48.75%

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
593	406	599	187	322	161

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
3 - 2020-10-30	17	Albany Devils	2	Adirondack Phantoms	1	L	X	X	Sommaire du Match
5 - 2020-11-01	34	Adirondack Phantoms	5	Connecticut Whale	1	W			Sommaire du Match
6 - 2020-11-02	47	Adirondack Phantoms	1	Charlotte Checkers	3	L			Sommaire du Match
8 - 2020-11-04	58	Albany Devils	4	Adirondack Phantoms	3	L	X	X	Sommaire du Match
10 - 2020-11-06	78	Albany Devils	4	Adirondack Phantoms	1	L			Sommaire du Match
12 - 2020-11-08	93	Adirondack Phantoms	0	Bridgeport Sound Tigers	2	L			Sommaire du Match
15 - 2020-11-11	115	San Antonio Rampage	1	Adirondack Phantoms	3	W			Sommaire du Match
17 - 2020-11-13	126	Adirondack Phantoms	2	Albany Devils	4	L			Sommaire du Match
19 - 2020-11-15	147	Manitoba Moose	2	Adirondack Phantoms	3	W			Sommaire du Match
20 - 2020-11-16	151	Adirondack Phantoms	3	CCCP Red Army	4	L			Sommaire du Match
23 - 2020-11-19	174	Trois-Rivières Draveurs	4	Adirondack Phantoms	2	L			Sommaire du Match
25 - 2020-11-21	187	Adirondack Phantoms	1	Norfolk Admirals	4	L			Sommaire du Match
29 - 2020-11-25	211	Albany Devils	2	Adirondack Phantoms	3	W			Sommaire du Match
31 - 2020-11-27	228	Adirondack Phantoms	2	Providence Bruins	3	L	X		Sommaire du Match
32 - 2020-11-28	233	Adirondack Phantoms	1	Peoria Rivermen	3	L			Sommaire du Match
34 - 2020-11-30	253	Wilkes-Barre/Scranton Penguins	2	Adirondack Phantoms	1	L	X	X	Sommaire du Match
37 - 2020-12-03	271	Adirondack Phantoms	3	Wilkes-Barre/Scranton Penguins	2	W			Sommaire du Match
39 - 2020-12-05	285	Lake Erie Monsters	3	Adirondack Phantoms	2	L			Sommaire du Match
41 - 2020-12-07	303	Adirondack Phantoms	3	Chicago Wolves	2	W			Sommaire du Match
43 - 2020-12-09	317	San Antonio Rampage	4	Adirondack Phantoms	2	L			Sommaire du Match
46 - 2020-12-12	340	Manitoba Moose	2	Adirondack Phantoms	3	W			Sommaire du Match
50 - 2020-12-16	368	Adirondack Phantoms	1	Peoria Rivermen	3	L			Sommaire du Match
52 - 2020-12-18	377	Mercer Island Hafgufa	2	Adirondack Phantoms	3	W			Sommaire du Match
54 - 2020-12-20	396	Adirondack Phantoms	4	Gatineau Olympiques	1	W			Sommaire du Match
56 - 2020-12-22	409	Gatineau Olympiques	1	Adirondack Phantoms	3	W			Sommaire du Match
59 - 2020-12-25	428	Adirondack Phantoms	-	Oklahoma City Barons	-
60 - 2020-12-26	442	Manitoba Moose	-	Adirondack Phantoms	-
65 - 2020-12-31	471	Roberval Dwarfs	-	Adirondack Phantoms	-
67 - 2021-01-02	487	Adirondack Phantoms	-	Charlotte Checkers	-
69 - 2021-01-04	502	Roberval Dwarfs	-	Adirondack Phantoms	-
71 - 2021-01-06	518	Adirondack Phantoms	-	Providence Bruins	-
73 - 2021-01-08	534	Laval Chiefs	-	Adirondack Phantoms	-
75 - 2021-01-10	546	Adirondack Phantoms	-	Houston Aeros	-
78 - 2021-01-13	565	Adirondack Phantoms	-	Manitoba Moose	-
79 - 2021-01-14	574	Bridgeport Sound Tigers	-	Adirondack Phantoms	-
82 - 2021-01-17	602	Trois-Rivières Draveurs	-	Adirondack Phantoms	-
84 - 2021-01-19	612	Adirondack Phantoms	-	San Antonio Rampage	-
86 - 2021-01-21	624	Adirondack Phantoms	-	Norfolk Admirals	-
88 - 2021-01-23	638	Adirondack Phantoms	-	Chicoutimi Saguenéens	-
89 - 2021-01-24	646	Springfield Falcons	-	Adirondack Phantoms	-
92 - 2021-01-27	670	Adirondack Phantoms	-	Milwaukee Admirals	-
93 - 2021-01-28	679	Albany Devils	-	Adirondack Phantoms	-
97 - 2021-02-01	707	CCCP Red Army	-	Adirondack Phantoms	-
99 - 2021-02-03	720	Adirondack Phantoms	-	Wilkes-Barre/Scranton Penguins	-
101 - 2021-02-05	738	Binghamton Senators	-	Adirondack Phantoms	-
103 - 2021-02-07	761	Adirondack Phantoms	-	Henderson Silver Knights	-
104 - 2021-02-08	770	Connecticut Whale	-	Adirondack Phantoms	-
107 - 2021-02-11	783	Adirondack Phantoms	-	Roberval Dwarfs	-
109 - 2021-02-13	803	Charlotte Checkers	-	Adirondack Phantoms	-
111 - 2021-02-15	813	Adirondack Phantoms	-	Albany Devils	-
114 - 2021-02-18	835	Adirondack Phantoms	-	CCCP Red Army	-
115 - 2021-02-19	843	Wilkes-Barre/Scranton Penguins	-	Adirondack Phantoms	-
120 - 2021-02-24	873	Norfolk Admirals	-	Adirondack Phantoms	-
122 - 2021-02-26	887	Adirondack Phantoms	-	Bridgeport Sound Tigers	-
124 - 2021-02-28	902	Adirondack Phantoms	-	CCCP Red Army	-
125 - 2021-03-01	911	Norfolk Admirals	-	Adirondack Phantoms	-
128 - 2021-03-04	935	Adirondack Phantoms	-	Connecticut Whale	-
129 - 2021-03-05	944	Joliette Sportif	-	Adirondack Phantoms	-
132 - 2021-03-08	966	Adirondack Phantoms	-	Trois-Rivières Draveurs	-
133 - 2021-03-09	975	Rockford IceHogs	-	Adirondack Phantoms	-
137 - 2021-03-13	1004	Grand Rapids Griffins	-	Adirondack Phantoms	-
138 - 2021-03-14	1011	Adirondack Phantoms	-	The Nuuk Vikings	-
141 - 2021-03-17	1034	Bridgeport Sound Tigers	-	Adirondack Phantoms	-
145 - 2021-03-21	1062	Adirondack Phantoms	-	Rochester Americans	-
146 - 2021-03-22	1069	Providence Bruins	-	Adirondack Phantoms	-
149 - 2021-03-25	1087	Adirondack Phantoms	-	Grand Rapids Griffins	-
151 - 2021-03-27	1103	Rochester Americans	-	Adirondack Phantoms	-
153 - 2021-03-29	1116	Adirondack Phantoms	-	Albany Devils	-
155 - 2021-03-31	1132	Adirondack Phantoms	-	Rochester Americans	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
157 - 2021-04-02	1141	Adirondack Phantoms	-	Connecticut Whale	-
158 - 2021-04-03	1150	Las Vegas Gamblers	-	Adirondack Phantoms	-
161 - 2021-04-06	1173	Connecticut Whale	-	Adirondack Phantoms	-
163 - 2021-04-08	1185	Adirondack Phantoms	-	Bridgeport Sound Tigers	-
166 - 2021-04-11	1204	Rouyn-Noranda Huskies	-	Adirondack Phantoms	-
169 - 2021-04-14	1223	Adirondack Phantoms	-	Grand Rapids Griffins	-
171 - 2021-04-16	1240	Adirondack Phantoms	-	Binghamton Senators	-
172 - 2021-04-17	1249	Chicoutimi Saguenéens	-	Adirondack Phantoms	-
177 - 2021-04-22	1269	Rouyn-Noranda Huskies	-	Adirondack Phantoms	-
184 - 2021-04-29	1302	Chicoutimi Saguenéens	-	Adirondack Phantoms	-
185 - 2021-04-30	1308	Adirondack Phantoms	-	Binghamton Senators	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	100	60
Assistance	19,387	12,155
Assistance PCT	74.57%	93.50%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
27	2426 - 80.88%	191,115$	2,484,500$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,099,220$	2,857,500$	2,857,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
15,199$	808,495$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
5,160,115$	131	20,253$	2,653,143$

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