LHSIR - Monsters

Blue Jackets
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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	TA	SP	Âge	Contrat	Salaire
1	Charles Hudon		X	X		100.00	82	44	99	74	66	59	64	64	33	57	58	54	75	59	59	62	50	0		0	26	3	650,000$
2	Eric Cornel (R)	X		X		100.00	79	72	96	64	72	79	86	56	70	47	58	66	55	51	51	62	50	0		0	24	3	925,000$
3	Drake Caggiula		X	X		100.00	85	77	77	82	68	61	65	59	34	62	74	67	25	64	64	71	48	0		0	26	1	1,350,000$
4	Nicolas Roy	X				100.00	79	45	90	68	78	59	82	62	72	64	71	63	25	47	47	69	50	0		0	23	1	815,000$
5	Kevin Stenlund (R)	X		X		100.00	67	43	91	65	80	66	81	75	54	61	71	61	25	47	47	69	50	0		0	23	3	925,000$
6	Nick Moutrey (R)	X				100.00	81	80	82	65	80	69	74	49	61	46	47	64	45	44	44	56	50	0		0	25	2	925,000$
7	Pascal Laberge (R)	X				100.00	70	65	82	64	65	52	51	56	70	46	61	60	58	44	44	59	50	0		0	22	3	863,333$
8	Rasmus Asplund (R)	X	X	X		100.00	69	42	92	68	64	57	86	61	55	57	56	85	25	46	46	65	50	0		0	22	3	925,000$
9	Tyler Benson (R)		X			100.00	73	70	79	71	70	75	78	63	50	66	57	63	54	44	44	64	50	0		0	22	3	863,333$
10	Paul Bittner (R)		X			100.00	80	80	79	68	80	66	70	51	50	47	51	64	48	44	44	57	50	0		0	23	3	863,333$
11	Sonny Milano		X	X		100.00	65	42	86	83	73	64	63	66	25	74	64	59	25	52	53	67	50	0		0	24	1	1,263,333$
12	Antoine Morand (R)	X				100.00	71	66	83	67	66	70	75	50	63	49	47	59	45	44	44	55	45	0		0	21	3	927,500$
13	Brendan Guhle				X	100.00	69	42	89	75	69	71	75	57	25	50	54	74	25	58	58	63	50	0		0	22	3	946,083$
14	Cale Fleury (R)				X	100.00	90	46	94	77	74	64	73	53	25	39	47	69	25	47	47	59	50	0		0	21	3	883,333$
15	Gabriel Carlsson				X	100.00	79	75	89	78	75	69	75	50	25	42	41	65	39	52	52	56	50	0		0	23	2	894,166$
16	Slater Koekkoek				X	100.00	80	44	72	76	72	70	59	63	25	55	47	80	25	57	58	62	50	0		0	26	1	800,000$
17	Ben Hutton				X	100.00	71	43	92	81	76	75	84	63	25	53	48	79	25	67	67	64	45	0		0	27	3	1,725,002$
18	Mike Reilly				X	100.00	73	43	84	78	73	75	68	73	25	66	47	67	25	60	60	63	50	0	X	0	26	3	1,500,000$
19	Devon Toews				X	100.00	71	42	91	80	68	81	87	78	25	65	50	65	63	62	63	65	42	0		0	26	2	700,000$
Rayé
1	Michael McCarron	X		X		100.00	78	88	53	65	88	61	62	59	74	50	62	66	59	49	49	61	50	0		0	25	1	1,075,833$
2	Connor Dewar (R)	X	X			100.00	70	63	87	65	63	69	73	54	68	53	50	60	48	44	44	57	50	0		0	21	3	925,000$
3	Ryan Collins (R)				X	100.00	82	81	84	52	81	55	57	48	25	38	42	64	40	44	44	53	50	0		0	24	3	925,000$
4	Markus Nutivaara				X	100.00	73	43	96	82	71	68	76	62	25	52	49	59	25	62	63	60	50	0	X	0	26	3	2,700,000$

	MOYENNE D'ÉQUIPE					100.00	76	58	86	72	73	67	72	60	44	54	54	66	39	52	52	62	49	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	Calvin Pickard	100.00	54	58	73	77	53	58	52	58	57	56	30	57	57	56	49	0	0
2	Oscar Dansk	100.00	60	68	85	79	58	65	56	64	61	60	30	44	44	61	51	0	0
Rayé
1	Jakub Skarek (R)	100.00	49	52	65	79	47	48	50	54	48	48	30	44	44	50	50	0	0

	MOYENNE D'ÉQUIPE	100.00	54	59	74	78	53	57	53	59	55	55	30	48	48	56	50	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Rick Tocchet	84	92	78	87	81	76	67	CAN	57	3	1,500,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	EG	P/20	PSG	PSS	FW	FT	S1	S2	S3
1	Devon Toews	Monsters (CLB)	D	41	3	28	31	2	36	0	47	56	35	10	37	8.57%	31	987	24.08	2	5	7	30	195	0	2	2	0	184	0	0	0.00%	0	0	0.63	0	0	0	0	2	1	3
2	Slater Koekkoek	Monsters (CLB)	D	46	6	16	22	-1	70	0	120	61	39	17	34	15.38%	46	950	20.66	5	5	10	35	189	0	1	1	0	166	0	0	0.00%	0	0	0.46	0	0	0	0	0	1	3
3	Nicolas Roy	Monsters (CLB)	C	46	9	12	21	1	36	0	65	78	60	15	44	15.00%	10	876	19.05	1	5	6	14	173	1	0	1	6	117	4	1	55.66%	724	0	0.48	2	3	0	0	4	0	2
4	Kevin Stenlund	Monsters (CLB)	C/RW	46	15	6	21	-1	10	0	18	45	77	23	53	19.48%	5	850	18.49	4	3	7	27	198	1	1	2	2	99	3	0	49.83%	592	1	0.49	2	5	0	0	3	3	1
5	Rasmus Asplund	Monsters (CLB)	C/LW/RW	46	9	12	21	-7	14	0	31	79	65	15	56	13.85%	6	746	16.22	1	3	4	20	164	0	0	0	0	11	1	0	45.02%	211	0	0.56	0	0	0	0	0	5	3
6	Sonny Milano	Monsters (CLB)	LW/RW	46	11	10	21	-1	14	0	16	53	62	17	49	17.74%	6	941	20.48	3	3	6	17	201	2	1	3	5	193	2	2	31.85%	135	0	0.45	1	5	0	0	1	1	0
7	Tyler Benson	Monsters (CLB)	LW	42	7	10	17	-3	30	10	28	67	48	20	43	14.58%	3	668	15.92	0	0	0	0	12	0	0	0	1	101	2	0	45.78%	83	0	0.51	0	0	1	1	3	0	0
8	Brendan Guhle	Monsters (CLB)	D	46	5	11	16	-10	30	0	18	42	23	11	21	21.74%	14	725	15.78	3	2	5	15	59	0	0	0	0	51	0	0	0.00%	0	0	0.44	0	0	0	0	0	2	3
9	Drake Caggiula	Monsters (CLB)	LW/RW	39	8	7	15	-3	77	15	97	50	44	21	51	18.18%	4	809	20.76	1	3	4	12	160	1	1	2	2	167	0	0	36.06%	269	0	0.37	1	4	0	3	1	2	0
10	Mike Reilly	Monsters (CLB)	D	46	3	12	15	2	58	0	80	44	34	15	28	8.82%	28	1001	21.78	3	5	8	32	222	0	2	2	0	190	0	0	0.00%	0	0	0.30	0	0	0	0	0	0	2
11	Charles Hudon	Monsters (CLB)	LW/RW	46	8	5	13	-4	40	0	55	24	40	7	38	20.00%	3	799	17.37	0	3	3	12	192	0	0	0	0	36	2	0	21.74%	46	0	0.33	1	1	0	0	1	1	0
12	Ben Hutton	Monsters (CLB)	D	31	1	12	13	-1	8	0	20	38	39	6	27	2.56%	20	671	21.66	1	5	6	31	126	0	0	0	2	131	0	0	0.00%	0	0	0.39	0	0	0	0	0	0	0
13	Eric Cornel	Monsters (CLB)	C/RW	46	4	5	9	3	26	10	35	53	30	14	21	13.33%	3	668	14.54	0	0	0	4	53	0	0	0	0	26	2	0	52.07%	338	0	0.27	0	0	0	2	0	1	1
14	Paul Bittner	Monsters (CLB)	LW	46	5	3	8	0	57	15	47	28	33	2	21	15.15%	5	603	13.11	0	0	0	0	0	0	0	0	0	2	1	0	44.44%	27	0	0.27	0	0	1	2	1	2	1
15	Mirco Mueller	Blue Jackets	D	12	1	6	7	5	8	0	6	15	14	2	4	7.14%	15	253	21.17	1	0	1	10	50	0	0	0	1	41	0	0	0.00%	0	0	0.55	0	0	0	0	0	0	0
16	Cale Fleury	Monsters (CLB)	D	46	0	6	6	-1	107	5	96	25	16	2	8	0.00%	17	698	15.18	0	0	0	4	6	0	0	0	0	73	0	0	0.00%	0	0	0.17	0	0	0	0	0	0	0
17	Joel Eriksson Ek	Blue Jackets	C/LW/RW	8	1	4	5	0	2	0	7	21	13	2	10	7.69%	2	183	22.95	0	2	2	7	38	0	0	0	0	38	0	0	56.99%	193	0	0.54	0	0	0	0	0	1	0
18	Gabriel Carlsson	Monsters (CLB)	D	34	0	3	3	-1	14	0	22	13	2	1	6	0.00%	13	264	7.79	0	0	0	2	6	0	0	0	0	44	0	0	0.00%	0	0	0.23	0	0	0	0	0	0	1
19	Nick Moutrey	Monsters (CLB)	C	45	0	1	1	1	36	10	18	15	5	5	2	0.00%	7	268	5.97	0	0	0	0	22	0	0	0	0	30	0	0	52.20%	182	0	0.07	0	0	1	1	0	0	0
20	Antoine Morand	Monsters (CLB)	C	40	1	0	1	2	0	0	6	8	6	1	3	16.67%	0	121	3.03	1	0	1	3	37	0	0	0	0	13	0	0	65.22%	46	0	0.16	0	0	0	0	0	0	0
21	Pascal Laberge	Monsters (CLB)	C	10	0	0	0	-1	2	0	3	1	4	0	0	0.00%	0	41	4.15	0	0	0	0	0	0	0	0	0	0	0	0	47.06%	34	0	0.00	0	0	0	0	0	0	0
22	Pavel Zacha	Blue Jackets	C/LW	3	0	0	0	-1	0	0	1	10	11	0	5	0.00%	0	68	22.86	0	0	0	4	16	0	0	0	1	12	0	0	54.41%	68	0	0.00	0	0	0	0	0	0	0
23	Connor Dewar	Monsters (CLB)	C/LW	26	0	0	0	-1	4	0	4	13	5	1	1	0.00%	0	97	3.77	0	0	0	1	4	0	0	0	0	9	0	0	57.78%	45	0	0.00	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				837	97	169	266	-20	679	65	840	839	705	207	562	13.76%	238	13299	15.89	26	44	70	280	2133	5	8	13	20	1745	17	3	49.55%	2993	1	0.40	7	18	3	9	16	20	20

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA	ST	BG	S1
1	Oscar Dansk	Monsters (CLB)	44	19	23	1	0.869	2.48	2543	2	5	105	803	2	0	0.778	18	44	0	4
2	Calvin Pickard	Monsters (CLB)	7	2	1	0	0.884	2.03	237	0	0	8	69	1	1	0.000	0	2	43	0
Stats d'équipe Total ou en Moyenne			51	21	24	1	0.870	2.44	2780	2	5	113	872	3	1	0.778	18	46	43	4

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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
Antoine Morand	Monsters (CLB)	C	21	1999-02-18	Yes	185 Lbs	5 ft10	No	No	No	3	Pro & Farm	927,500$	388,952$	927,500$	388,952$	0$	0$	No	927,500$	927,500$
Ben Hutton	Monsters (CLB)	D	27	1993-04-20	No	207 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,725,002$	723,388$	1,500,000$	629,032$	0$	0$	No	1,500,000$	1,500,000$	Lien
Brendan Guhle	Monsters (CLB)	D	22	1997-07-29	No	186 Lbs	6 ft1	No	No	No	3	Pro & Farm	946,083$	396,744$	888,833$	372,736$	0$	0$	No	888,833$	888,833$	Lien
Cale Fleury	Monsters (CLB)	D	21	1998-11-19	Yes	203 Lbs	6 ft1	No	No	No	3	Pro & Farm	883,333$	370,430$	883,333$	370,430$	0$	0$	No	883,333$	883,333$
Calvin Pickard	Monsters (CLB)	G	28	1992-04-14	No	207 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,000,000$	419,355$	1,000,000$	419,355$	0$	0$	No			Lien
Charles Hudon	Monsters (CLB)	LW/RW	26	1994-06-23	No	188 Lbs	5 ft10	No	No	No	3	Pro & Farm	650,000$	272,581$	725,000$	304,032$	0$	0$	No	650,000$	650,000$	Lien
Connor Dewar	Monsters (CLB)	C/LW	21	1999-06-26	Yes	176 Lbs	5 ft10	No	No	No	3	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$	925,000$
Devon Toews	Monsters (CLB)	D	26	1994-02-20	No	181 Lbs	6 ft1	No	No	No	2	Pro & Farm	700,000$	293,548$	700,000$	293,548$	0$	0$	No	700,000$		Lien
Drake Caggiula	Monsters (CLB)	LW/RW	26	1994-06-20	No	185 Lbs	5 ft10	No	No	No	1	Pro & Farm	1,350,000$	566,129$	1,350,000$	566,129$	0$	0$	No			Lien
Eric Cornel	Monsters (CLB)	C/RW	24	1996-04-11	Yes	194 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$	925,000$
Gabriel Carlsson	Monsters (CLB)	D	23	1997-01-02	No	192 Lbs	6 ft5	No	No	No	2	Pro & Farm	894,166$	374,973$	894,166$	374,973$	0$	0$	No	894,166$		Lien
Jakub Skarek	Monsters (CLB)	G	20	1999-11-10	Yes	196 Lbs	6 ft3	No	No	No	3	Pro & Farm	927,500$	388,952$	927,500$	388,952$	0$	0$	No	927,500$	927,500$
Kevin Stenlund	Monsters (CLB)	C/RW	23	1996-09-20	Yes	210 Lbs	6 ft4	No	No	No	3	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$	925,000$
Markus Nutivaara	Monsters (CLB)	D	26	1994-06-06	No	191 Lbs	6 ft1	No	Yes	No	3	Pro & Farm	2,700,000$	1,132,258$	2,700,000$	1,132,258$	0$	0$	No	2,700,000$	2,700,000$	Lien
Michael McCarron	Monsters (CLB)	C/RW	25	1995-03-06	No	231 Lbs	6 ft6	No	No	No	1	Pro & Farm	1,075,833$	451,156$	1,075,833$	451,156$	0$	0$	No			Lien
Mike Reilly	Monsters (CLB)	D	26	1993-07-12	No	195 Lbs	6 ft2	No	Yes	No	3	Pro & Farm	1,500,000$	629,032$	1,500,000$	629,032$	0$	0$	No	1,500,000$	1,500,000$	Lien
Nick Moutrey	Monsters (CLB)	C	25	1995-06-23	Yes	218 Lbs	6 ft3	No	No	No	2	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$
Nicolas Roy	Monsters (CLB)	C	23	1997-02-05	No	208 Lbs	6 ft4	No	No	No	1	Pro & Farm	815,000$	341,774$	815,000$	341,774$	0$	0$	No			Lien
Oscar Dansk	Monsters (CLB)	G	26	1994-02-28	No	195 Lbs	6 ft3	No	No	No	2	Pro & Farm	675,000$	283,065$	675,000$	283,065$	0$	0$	No	675,000$		Lien
Pascal Laberge	Monsters (CLB)	C	22	1998-04-08	Yes	173 Lbs	6 ft1	No	No	No	3	Pro & Farm	863,333$	362,043$	863,333$	362,043$	0$	0$	No	863,333$	863,333$
Paul Bittner	Monsters (CLB)	LW	23	1996-11-03	Yes	214 Lbs	6 ft4	No	No	No	3	Pro & Farm	863,333$	362,043$	863,333$	362,043$	0$	0$	No	863,333$	863,333$
Rasmus Asplund	Monsters (CLB)	C/LW/RW	22	1997-12-02	Yes	176 Lbs	5 ft11	No	No	No	3	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$	925,000$
Ryan Collins	Monsters (CLB)	D	24	1996-05-06	Yes	212 Lbs	6 ft5	No	No	No	3	Pro & Farm	925,000$	387,903$	925,000$	387,903$	0$	0$	No	925,000$	925,000$
Slater Koekkoek	Monsters (CLB)	D	26	1994-02-18	No	193 Lbs	6 ft2	No	No	No	1	Pro & Farm	800,000$	335,484$	800,000$	335,484$	0$	0$	No			Lien
Sonny Milano	Monsters (CLB)	LW/RW	24	1996-05-11	No	195 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,263,333$	529,785$	1,263,333$	529,785$	0$	0$	No			Lien
Tyler Benson	Monsters (CLB)	LW	22	1998-03-15	Yes	192 Lbs	6 ft0	No	No	No	3	Pro & Farm	863,333$	362,043$	863,333$	362,043$	0$	0$	No	863,333$	863,333$

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
26	23.92	196 Lbs	6 ft2	2.38	1,037,413$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Drake Caggiula	Kevin Stenlund	Sonny Milano	35	1	2	2
2	Charles Hudon	Nicolas Roy	Rasmus Asplund	30	1	2	2
3	Tyler Benson	Eric Cornel	Paul Bittner	25	1	2	2
4	Paul Bittner	Pascal Laberge	Drake Caggiula	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Devon Toews	Mike Reilly	35	1	2	2
2	Ben Hutton	Slater Koekkoek	30	1	2	2
3	Brendan Guhle	Cale Fleury	25	1	2	2
4	Gabriel Carlsson	Devon Toews	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Drake Caggiula	Kevin Stenlund	Sonny Milano	60	1	2	2
2	Charles Hudon	Nicolas Roy	Rasmus Asplund	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Devon Toews	Mike Reilly	60	1	2	2
2	Ben Hutton	Slater Koekkoek	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Drake Caggiula	Sonny Milano	60	1	2	2
2	Kevin Stenlund	Nicolas Roy	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Devon Toews	Mike Reilly	60	1	2	2
2	Ben Hutton	Slater Koekkoek	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Drake Caggiula	60	1	2	2	Devon Toews	Mike Reilly	60	1	2	2
2	Sonny Milano	40	1	2	2	Ben Hutton	Slater Koekkoek	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Drake Caggiula	Sonny Milano	60	1	2	2
2	Kevin Stenlund	Nicolas Roy	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Devon Toews	Mike Reilly	60	1	2	2
2	Ben Hutton	Slater Koekkoek	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Drake Caggiula	Kevin Stenlund	Sonny Milano	Devon Toews	Mike Reilly

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Drake Caggiula	Kevin Stenlund	Sonny Milano	Devon Toews	Mike Reilly

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Nick Moutrey, Antoine Morand, Tyler Benson	Nick Moutrey, Antoine Morand	Tyler Benson

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Brendan Guhle, Cale Fleury, Gabriel Carlsson	Brendan Guhle	Cale Fleury, Gabriel Carlsson

Tirs de Pénalité
Drake Caggiula, Sonny Milano, Kevin Stenlund, Nicolas Roy, Charles Hudon

Gardien
#1 : Oscar Dansk, #2 : Calvin Pickard

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	1	0	0	0	0	0	0	3	0	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	0	3	2	1.000	3	5	8	0	1	39	31	27	7	18	211	220	268	24	8	6	14	13	10	0	0.00%	6	0	100.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
2	Bruins	3	1	2	0	0	0	0	0	2	5	-3	1	1	0	0	0	0	0	0	2	1	1	2	0	2	0	0	0	0	0	0	4	-4	2	0.333	2	4	6	0	0	39	31	27	7	36	211	220	268	24	50	16	36	58	21	0	0.00%	17	3	82.35%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
3	Condors	2	0	1	0	0	0	1	0	3	5	-2	1	0	0	0	0	0	1	0	2	1	1	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	3	3	6	0	0	39	31	27	7	34	211	220	268	24	41	8	29	43	8	0	0.00%	12	3	75.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
4	Crunch	3	1	2	0	0	0	0	0	6	6	0	2	1	1	0	0	0	0	0	2	1	1	1	0	1	0	0	0	0	0	4	5	-1	2	0.333	6	11	17	0	1	39	31	27	7	49	211	220	268	24	67	14	66	48	24	2	8.33%	20	3	85.00%	1	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
5	Flames	1	0	1	0	0	0	0	0	0	3	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	3	-3	0	0.000	0	0	0	0	0	39	31	27	7	14	211	220	268	24	12	4	6	14	6	0	0.00%	3	1	66.67%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
6	Griffins	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	2	3	0	0	39	31	27	7	8	211	220	268	24	18	3	12	24	5	0	0.00%	5	2	60.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
7	Marlies	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	4	6	0	0	39	31	27	7	20	211	220	268	24	13	8	14	18	6	0	0.00%	6	1	83.33%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
8	Moose	1	0	0	0	0	0	0	1	2	3	-1	1	0	0	0	0	0	0	1	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	2	3	5	0	0	39	31	27	7	13	211	220	268	24	19	9	25	27	3	0	0.00%	3	0	100.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
9	Penguins	6	2	4	0	0	0	0	0	5	17	-12	2	0	2	0	0	0	0	0	0	6	-6	4	2	2	0	0	0	0	0	5	11	-6	4	0.333	5	8	13	0	1	39	31	27	7	85	211	220	268	24	111	34	97	114	33	1	3.03%	39	4	89.74%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
10	Phantoms	11	3	6	0	0	0	2	0	28	31	-3	7	3	3	0	0	0	1	0	18	16	2	4	0	3	0	0	0	1	0	10	15	-5	10	0.455	28	42	70	1	2	39	31	27	7	185	211	220	268	24	226	50	176	188	68	12	17.65%	69	10	85.51%	2	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
11	Senators	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	6	1	5	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	11	17	0	0	39	31	27	7	23	211	220	268	24	14	5	8	18	7	3	42.86%	4	0	100.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
12	Sharks	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	4	6	0	0	39	31	27	7	15	211	220	268	24	16	2	10	17	7	1	14.29%	4	0	100.00%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
13	Sound Tigers	5	3	1	0	0	0	1	0	22	16	6	3	2	0	0	0	0	1	0	15	10	5	2	1	1	0	0	0	0	0	7	6	1	8	0.800	22	38	60	0	0	39	31	27	7	86	211	220	268	24	105	26	66	98	21	2	9.52%	31	5	83.87%	1	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
14	Stars	4	2	2	0	0	0	0	0	10	9	1	2	1	1	0	0	0	0	0	6	5	1	2	1	1	0	0	0	0	0	4	4	0	4	0.500	10	18	28	0	0	39	31	27	7	52	211	220	268	24	82	25	59	92	20	3	15.00%	23	2	91.30%	1	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
	Total	46	17	24	0	0	0	4	1	101	115	-14	24	12	8	0	0	0	3	1	61	50	11	22	5	16	0	0	0	1	0	40	65	-25	43	0.467	101	169	270	1	5	39	31	27	7	705	211	220	268	24	873	238	683	841	254	26	10.24%	271	40	85.24%	5	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
15	Wolf Pack	5	1	4	0	0	0	0	0	9	13	-4	2	1	1	0	0	0	0	0	4	4	0	3	0	3	0	0	0	0	0	5	9	-4	2	0.200	9	16	25	0	0	39	31	27	7	67	211	220	268	24	91	28	65	69	15	2	13.33%	29	6	79.31%	0	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
	_Since Last GM Reset	46	17	24	0	0	0	4	1	101	115	-14	24	12	8	0	0	0	3	1	61	50	11	22	5	16	0	0	0	1	0	40	65	-25	43	0.467	101	169	270	1	5	39	31	27	7	705	211	220	268	24	873	238	683	841	254	26	10.24%	271	40	85.24%	5	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
	_Vs Conference	31	10	19	0	0	0	2	0	58	77	-19	16	8	7	0	0	0	1	0	34	30	4	15	2	12	0	0	0	1	0	24	47	-23	24	0.387	58	96	154	1	4	39	31	27	7	479	211	220	268	24	584	159	468	527	180	20	11.11%	187	28	85.03%	3	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295
	_Vs Division	27	6	15	0	0	0	2	0	64	77	-13	14	4	6	0	0	0	1	0	37	36	1	13	2	9	0	0	0	1	0	27	41	-14	16	0.296	64	104	168	1	3	39	31	27	7	423	211	220	268	24	533	138	404	469	137	17	12.41%	168	25	85.12%	3	619	1178	52.55%	556	1215	45.76%	336	653	51.45%	1133	773	1079	338	571	295

			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	43	W1	101	169	270	705	873	238	683	841	1	5

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
46	17	24	0	0	4	1	101	115

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
24	12	8	0	0	3	1	61	50

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
22	5	16	0	0	1	0	40	65

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	5	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
254	26	10.24%	271	40	85.24%	5

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
211	220	268	24	39	31	27	7

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
619	1178	52.55%	556	1215	45.76%	336	653	51.45%

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
1133	773	1079	338	571	295

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	10	Marlies	1	Monsters	2	W			Sommaire du Match
2 - 2020-09-28	13	Monsters	1	Phantoms	3	L			Sommaire du Match
4 - 2020-09-30	30	Phantoms	3	Monsters	1	L			Sommaire du Match
5 - 2020-10-01	37	Monsters	4	Phantoms	3	W	X	X	Sommaire du Match
6 - 2020-10-02	47	Phantoms	0	Monsters	1	W			Sommaire du Match
9 - 2020-10-05	63	Monsters	0	Bruins	3	L			Sommaire du Match
10 - 2020-10-06	73	Monsters	1	Penguins	0	W			Sommaire du Match
12 - 2020-10-08	82	Phantoms	3	Monsters	4	W	X	X	Sommaire du Match
14 - 2020-10-10	91	Monsters	3	Wolf Pack	5	L			Sommaire du Match
16 - 2020-10-12	104	Phantoms	2	Monsters	4	W			Sommaire du Match
18 - 2020-10-14	116	Monsters	4	Sound Tigers	1	W			Sommaire du Match
20 - 2020-10-16	124	Penguins	3	Monsters	0	L			Sommaire du Match
22 - 2020-10-18	137	Monsters	4	Phantoms	6	L			Sommaire du Match
23 - 2020-10-19	146	Sound Tigers	4	Monsters	5	W			Sommaire du Match
24 - 2020-10-20	159	Stars	4	Monsters	3	L			Sommaire du Match
26 - 2020-10-22	178	Phantoms	0	Monsters	3	W			Sommaire du Match
27 - 2020-10-23	182	Monsters	0	Flames	3	L			Sommaire du Match
28 - 2020-10-24	190	Monsters	1	Phantoms	3	L			Sommaire du Match
30 - 2020-10-26	202	Sound Tigers	2	Monsters	3	W	X	X	Sommaire du Match
32 - 2020-10-28	216	Phantoms	4	Monsters	2	L			Sommaire du Match
34 - 2020-10-30	222	Monsters	3	Admirals	0	W			Sommaire du Match
37 - 2020-11-02	238	Monsters	0	Penguins	2	L			Sommaire du Match
38 - 2020-11-03	248	Monsters	1	Penguins	7	L			Sommaire du Match
40 - 2020-11-05	258	Senators	1	Monsters	6	W			Sommaire du Match
43 - 2020-11-08	274	Bruins	1	Monsters	2	W			Sommaire du Match
45 - 2020-11-10	290	Sound Tigers	4	Monsters	7	W			Sommaire du Match
46 - 2020-11-11	295	Monsters	1	Wolf Pack	2	L			Sommaire du Match
48 - 2020-11-13	309	Monsters	1	Wolf Pack	2	L			Sommaire du Match
49 - 2020-11-14	317	Crunch	0	Monsters	2	W			Sommaire du Match
50 - 2020-11-15	329	Monsters	0	Bruins	1	L			Sommaire du Match
51 - 2020-11-16	336	Monsters	3	Penguins	2	W			Sommaire du Match
52 - 2020-11-17	347	Wolf Pack	1	Monsters	2	W			Sommaire du Match
54 - 2020-11-19	362	Wolf Pack	3	Monsters	2	L			Sommaire du Match
55 - 2020-11-20	376	Crunch	1	Monsters	0	L			Sommaire du Match
56 - 2020-11-21	383	Monsters	4	Crunch	5	L			Sommaire du Match
57 - 2020-11-22	391	Monsters	1	Griffins	4	L			Sommaire du Match
58 - 2020-11-23	403	Sharks	1	Monsters	2	W			Sommaire du Match
59 - 2020-11-24	409	Monsters	1	Stars	2	L			Sommaire du Match
61 - 2020-11-26	426	Penguins	3	Monsters	0	L			Sommaire du Match
63 - 2020-11-28	436	Monsters	3	Sound Tigers	5	L			Sommaire du Match
64 - 2020-11-29	449	Phantoms	4	Monsters	3	L			Sommaire du Match
66 - 2020-12-01	464	Moose	3	Monsters	2	L	X	X	Sommaire du Match
67 - 2020-12-02	473	Monsters	3	Stars	2	W			Sommaire du Match
68 - 2020-12-03	485	Stars	1	Monsters	3	W			Sommaire du Match
71 - 2020-12-06	500	Monsters	1	Condors	4	L			Sommaire du Match
72 - 2020-12-07	510	Condors	1	Monsters	2	W	X	X	Sommaire du Match
73 - 2020-12-08	519	Monsters	-	Sound Tigers	-
74 - 2020-12-09	530	Monarchs	-	Monsters	-
77 - 2020-12-12	549	Monsters	-	Bruins	-
78 - 2020-12-13	555	Flames	-	Monsters	-
79 - 2020-12-14	567	Monsters	-	Moose	-
80 - 2020-12-15	576	Senators	-	Monsters	-
82 - 2020-12-17	589	Monsters	-	Senators	-
84 - 2020-12-19	598	Marlies	-	Monsters	-
86 - 2020-12-21	613	Monsters	-	Sound Tigers	-
87 - 2020-12-22	622	Griffins	-	Monsters	-
88 - 2020-12-23	634	Monsters	-	Flames	-
90 - 2020-12-25	644	Admirals	-	Monsters	-
92 - 2020-12-27	659	Monsters	-	Sharks	-
93 - 2020-12-28	665	Rocket	-	Monsters	-
95 - 2020-12-30	681	Monsters	-	Rampage	-
96 - 2020-12-31	690	Bruins	-	Monsters	-
97 - 2021-01-01	705	Wolf Pack	-	Monsters	-
98 - 2021-01-02	712	Monsters	-	Wolf Pack	-
100 - 2021-01-04	728	Sound Tigers	-	Monsters	-
101 - 2021-01-05	741	Monsters	-	Marlies	-
102 - 2021-01-06	747	Penguins	-	Monsters	-
104 - 2021-01-08	758	Monsters	-	IceHogs	-
105 - 2021-01-09	772	Rampage	-	Monsters	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10	780	Monsters	-	Monarchs	-
108 - 2021-01-12	793	Penguins	-	Monsters	-
110 - 2021-01-14	813	Wolves	-	Monsters	-
111 - 2021-01-15	818	Monsters	-	Soldiers	-
113 - 2021-01-17	837	IceHogs	-	Monsters	-
114 - 2021-01-18	840	Monsters	-	Rocket	-
116 - 2021-01-20	858	Soldiers	-	Monsters	-
117 - 2021-01-21	860	Monsters	-	Phantoms	-
118 - 2021-01-22	874	Monsters	-	Griffins	-
119 - 2021-01-23	882	Wolf Pack	-	Monsters	-
120 - 2021-01-24	883	Monsters	-	Phantoms	-
121 - 2021-01-25	888	Monsters	-	Rocket	-
122 - 2021-01-26	901	Monsters	-	Wolves	-

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
2,423,430$	2,697,273$	2,676,548$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	1,552,448$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	52	33,849$	1,760,148$

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