Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Marmots

Marmots

GP: 38 | W: 20 | L: 15 | OTL: 3 | P: 43
GF: 135 | GA: 143 | PP%: 25.45% | PK%: 71.70%
DG: Patrick Gagnon | Morale : 90 | Moyenne d'Équipe : 56
Prochain matchs #583 vs Spartans

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London Spartiates
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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
1	Mason Shaw (R)			X		100.00	80	66	58	82	54	56	71	57	30	54	60	78	67	84	72	0	90	63	0
2	Tanner Pearson			X		100.00	68	48	66	80	68	68	40	55	30	56	54	60	67	90	81	0	90	60	0
3	Hunter McKown (R)	X				100.00	59	45	84	76	70	61	40	49	85	48	50	64	50	80	69	0	90	59	0
4	Nic Petan			X		100.00	50	45	92	81	47	58	40	51	30	48	54	59	65	88	77	0	90	56	0
5	Kristian Reichel (R)	X				100.00	50	45	95	77	66	53	40	47	30	44	50	56	50	84	72	0	90	54	0
6	Mathieu Perreault		X			100.00	50	45	95	77	57	50	40	45	30	40	50	55	50	95	82	0	90	53	0
7	Brian Pinho	X				100.00	50	45	95	77	63	50	40	45	30	40	50	55	50	88	75	0	90	53	0
8	Andrew Poturalski	X				100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	89	76	0	90	53	0
9	Alex Formenton		X			100.00	50	45	95	76	70	50	40	45	30	40	50	55	50	84	71	0	90	53	0
10	Vinni Lettieri	X				100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	88	75	0	90	53	0
11	Kole Sherwood			X		100.00	50	45	95	74	74	50	40	45	30	40	50	55	50	86	73	0	90	53	0
12	Mark Friedman				X	100.00	98	48	77	80	51	60	40	51	30	47	55	76	65	87	75	0	90	64	0
13	Alex Goligoski				X	100.00	62	45	85	81	45	74	56	51	30	47	55	68	65	97	89	0	90	63	0
14	Kevin Gravel				X	100.00	68	45	90	75	71	59	40	47	30	44	50	68	50	91	79	0	90	62	0
15	Dylan McIlrath				X	100.00	61	48	85	71	87	50	40	47	30	44	50	58	50	90	78	0	90	60	0
16	Taylor Fedun				X	100.00	50	45	95	76	63	50	40	45	30	40	50	59	50	94	82	0	90	58	0
17	Brogan Rafferty (R)				X	100.00	50	45	95	76	58	50	40	45	30	40	50	55	50	88	75	0	90	56	0
Rayé
1	Cedric Paquette		X			100.00	50	45	95	75	69	50	40	45	30	40	50	55	50	90	77	0	90	53	0
2	Max McCormick			X		100.00	50	45	95	77	58	50	40	45	30	40	50	55	50	91	78	0	90	53	0
3	Paul Byron		X			100.00	50	45	95	80	40	50	40	45	30	40	50	55	50	94	81	0	90	52	0
4	Sheldon Rempal			X		100.00	50	45	95	80	44	50	40	45	30	40	50	55	50	87	74	0	90	52	0
5	Vitaly Abramov (R)			X		100.00	50	45	95	78	52	50	40	45	30	40	50	55	50	85	72	0	90	52	0

	MOYENNE D'ÉQUIPE					100.00	57	46	89	78	60	54	42	47	33	43	51	59	54	89	77	0	90	56

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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	Ivan Prosvetov (R)	100.00	70	50	77	87	70	70	70	70	70	70	70	83	72	0	90	62	0
2	Nico Daws (R)	100.00	70	40	40	89	65	65	65	65	65	65	65	81	73	0	90	58	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	70	45	59	88	68	68	68	68	68	68	68	82	73	0	90	60

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Tony Granato	65	65	65	65	93	74	54	USA	59	2	700,000$

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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	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Tanner Pearson	Marmots (LON)	RW	34	22	21	43	-11	53	15	66	32	185	55	96	11.89%	22	702	20.67	8	9	17	35	77	5	47	2	1	46.83%	126	39	23	1	1	1.22	2	5	1	1	1	4	2	3
2	Vinni Lettieri	Marmots (LON)	C	35	8	18	26	-6	9	5	28	40	68	20	36	11.76%	7	505	14.44	2	1	3	4	16	2	20	1	0	45.62%	331	16	12	0	0	1.03	0	1	0	0	1	2	1	2
3	Derek Stepan	London Spartiates	C	12	7	15	22	6	2	0	16	29	43	19	28	16.28%	8	281	23.50	2	8	10	9	31	0	24	1	0	60.40%	346	15	18	0	0	1.56	2	4	0	0	0	0	5	1
4	Max McCormick	Marmots (LON)	RW	25	6	14	20	0	4	0	21	31	55	14	32	10.91%	14	395	15.81	0	2	2	5	35	0	8	1	0	42.86%	35	19	8	0	0	1.01	1	1	0	0	0	2	1	2
5	Mathieu Perreault	Marmots (LON)	LW	36	8	7	15	-11	6	0	35	38	71	23	34	11.27%	9	573	15.94	0	1	1	4	47	5	11	1	1	51.43%	35	19	20	0	1	0.52	0	0	0	0	0	2	2	0
6	Hunter McKown	Marmots (LON)	C	19	3	12	15	-7	4	0	22	48	38	13	34	7.89%	8	343	18.08	1	1	2	3	32	1	20	0	0	65.00%	320	8	9	0	0	0.87	0	1	0	0	0	0	1	1
7	Dylan McIlrath	Marmots (LON)	D	34	2	10	12	-10	16	0	31	41	32	19	8	6.25%	35	737	21.69	0	3	3	4	67	1	65	0	0	50.00%	2	17	30	0	0	0.33	0	0	0	0	0	0	0	2
8	Kristian Reichel	Marmots (LON)	C	20	8	4	12	-3	2	0	21	32	44	14	34	18.18%	12	333	16.66	1	2	3	3	34	0	22	1	0	40.15%	269	10	12	0	0	0.72	1	1	0	0	0	1	0	1
9	Mason Shaw	Marmots (LON)	RW	7	5	7	12	-1	11	5	15	10	39	11	20	12.82%	6	148	21.23	2	0	2	5	12	1	15	0	1	40.74%	27	11	4	0	0	1.62	0	1	0	0	1	1	1	0
10	Kevin Gravel	Marmots (LON)	D	34	4	8	12	-7	8	0	43	45	39	17	17	10.26%	44	760	22.36	4	2	6	9	67	1	72	0	0	100.00%	1	13	40	0	0	0.32	0	0	0	0	0	0	1	0
11	Alex Goligoski	Marmots (LON)	D	15	3	7	10	-9	4	0	25	20	27	9	8	11.11%	23	397	26.47	0	2	2	1	37	2	40	0	0	0.00%	0	11	26	0	0	0.50	0	0	0	0	0	0	0	0
12	Alex Formenton	Marmots (LON)	LW	28	7	1	8	8	0	0	19	12	39	9	29	17.95%	10	487	17.41	2	0	2	4	41	0	37	1	0	36.36%	33	5	9	0	0	0.33	0	1	0	0	0	2	0	3
13	Taylor Fedun	Marmots (LON)	D	38	0	7	7	10	9	5	13	42	23	11	11	0.00%	24	635	16.74	0	1	1	1	32	0	31	0	0	50.00%	2	5	36	0	0	0.22	0	0	0	0	1	0	1	0
14	Sheldon Rempal	Marmots (LON)	RW	8	6	1	7	1	2	0	10	10	27	5	12	22.22%	5	114	14.25	0	0	0	0	1	0	0	1	0	71.43%	7	6	2	0	1	1.23	0	0	0	0	0	1	0	0
15	Cedric Paquette	Marmots (LON)	LW	17	4	2	6	0	0	0	8	14	20	8	11	20.00%	3	213	12.56	0	0	0	0	4	1	5	1	0	55.56%	9	8	9	0	0	0.56	0	0	0	0	0	0	1	0
16	Andrew Poturalski	Marmots (LON)	C	25	3	3	6	4	4	0	5	35	32	13	18	9.38%	10	388	15.54	0	0	0	0	10	0	10	0	0	44.79%	163	12	8	0	0	0.31	0	0	0	0	0	0	0	2
17	Nic Petan	Marmots (LON)	RW	10	2	3	5	-1	0	0	7	7	42	11	31	4.76%	4	166	16.70	1	0	1	3	10	1	0	0	0	33.33%	6	12	3	0	0	0.60	0	0	0	0	0	0	0	0
18	Brogan Rafferty	Marmots (LON)	D	28	0	5	5	10	4	0	11	24	23	7	5	0.00%	21	480	17.15	0	0	0	3	27	0	34	0	0	0.00%	0	3	23	0	0	0.21	0	0	0	0	0	0	0	0
19	Mark Friedman	Marmots (LON)	D	15	0	4	4	-9	14	0	33	22	35	9	10	0.00%	35	391	26.11	0	1	1	2	37	0	36	0	0	0.00%	0	6	22	0	0	0.20	0	0	0	0	0	0	0	0
20	Zach Bogosian	London Spartiates	D	8	0	3	3	-1	6	0	12	9	11	5	6	0.00%	9	174	21.76	0	1	1	2	25	0	14	0	0	0.00%	0	5	7	0	0	0.34	0	0	0	0	0	0	0	1
21	Kole Sherwood	Marmots (LON)	RW	9	2	1	3	-3	0	0	6	8	12	3	10	16.67%	3	132	14.67	0	0	0	0	0	0	0	0	0	33.33%	12	5	4	0	0	0.45	0	0	0	0	0	0	0	0
22	Vitaly Abramov	Marmots (LON)	RW	16	1	2	3	-3	0	0	16	10	14	7	12	7.14%	2	204	12.76	0	0	0	0	5	0	0	0	0	0.00%	3	5	6	0	0	0.29	0	0	0	0	0	1	1	0
23	Klim Kostin	London Spartiates	LW	1	2	0	2	1	2	0	1	0	4	1	0	50.00%	0	17	17.27	0	0	0	0	2	0	0	0	0	0.00%	0	0	1	0	0	2.32	0	0	0	0	0	0	0	1
24	Brian Pinho	Marmots (LON)	C	8	0	2	2	-1	2	0	11	12	7	7	7	0.00%	2	131	16.39	0	0	0	0	0	0	0	0	0	37.04%	27	8	2	0	0	0.31	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				482	103	157	260	-43	162	30	475	571	930	310	509	11.08%	316	8716	18.08	23	34	57	97	660	20	519	10	3	50.91%	1754	258	334	1	3	0.60	6	15	1	1	4	16	17	19

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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	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Ivan Prosvetov	Marmots (LON)	19	11	6	2	0.887	3.91	1106	0	72	639	323	0	1	0.667	15	19	1	2	0	0
2	Nico Daws	Marmots (LON)	21	9	9	1	0.879	3.21	1178	2	63	521	280	1	0	1.000	4	19	21	0	2	1
Stats d'équipe Total ou en Moyenne			40	20	15	3	0.884	3.55	2284	2	135	1160	603	1	1	0.737	19	38	22	2	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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial
Alex Formenton	Marmots (LON)	LW	24	1999-09-13	No	195 Lbs	6 ft3	No	No	No	5	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Alex Goligoski	Marmots (LON)	D	38	1985-07-30	No	173 Lbs	5 ft11	No	No	No	1	Sans Restriction	Pro & Farm	4,500,000$	0$	0$	No
Andrew Poturalski	Marmots (LON)	C	29	1994-01-14	No	183 Lbs	5 ft10	No	No	No	5	Sans Restriction	Pro & Farm	775,000$	0$	0$	No
Brian Pinho	Marmots (LON)	C	28	1995-05-11	No	190 Lbs	6 ft1	No	No	No	1	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Brogan Rafferty	Marmots (LON)	D	27	1995-10-12	Yes	195 Lbs	6 ft0	No	No	No	5	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Cedric Paquette	Marmots (LON)	LW	30	1993-08-13	No	205 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	3,500,000$	0$	0$	No
Dylan McIlrath	Marmots (LON)	D	31	1992-04-20	No	232 Lbs	6 ft5	No	No	No	3	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Hunter McKown	Marmots (LON)	C	21	2002-08-18	Yes	205 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	2,650,000$	0$	0$	No
Ivan Prosvetov	Marmots (LON)	G	24	1999-03-05	Yes	195 Lbs	6 ft5	No	No	No	3	Avec Restriction	Pro & Farm	700,000$	0$	0$	No
Kevin Gravel	Marmots (LON)	D	31	1992-03-06	No	205 Lbs	6 ft4	No	No	No	3	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Kole Sherwood	Marmots (LON)	RW	26	1997-01-22	No	212 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Kristian Reichel	Marmots (LON)	C	25	1998-06-11	Yes	192 Lbs	6 ft2	No	No	No	5	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Mark Friedman	Marmots (LON)	D	27	1995-12-25	No	185 Lbs	5 ft11	No	No	No	5	Avec Restriction	Pro & Farm	3,000,000$	0$	0$	No
Mason Shaw	Marmots (LON)	RW	24	1998-11-03	Yes	184 Lbs	5 ft10	No	No	No	2	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Mathieu Perreault	Marmots (LON)	LW	35	1988-01-05	No	189 Lbs	5 ft10	No	No	No	2	Sans Restriction	Pro & Farm	4,000,000$	0$	0$	No
Max McCormick	Marmots (LON)	RW	31	1992-05-01	No	188 Lbs	5 ft11	No	No	No	5	Sans Restriction	Pro & Farm	775,000$	0$	0$	No
Nic Petan	Marmots (LON)	RW	28	1995-03-22	No	175 Lbs	5 ft9	No	No	No	3	Sans Restriction	Pro & Farm	700,000$	0$	0$	No
Nico Daws	Marmots (LON)	G	22	2000-12-22	Yes	205 Lbs	6 ft4	No	No	No	2	Avec Restriction	Pro & Farm	1,100,000$	0$	0$	No
Paul Byron	Marmots (LON)	LW	34	1989-04-27	No	158 Lbs	5 ft9	No	No	No	2	Sans Restriction	Pro & Farm	4,000,000$	0$	0$	No
Sheldon Rempal	Marmots (LON)	RW	28	1995-08-07	No	165 Lbs	5 ft10	No	No	No	5	Sans Restriction	Pro & Farm	775,000$	0$	0$	No
Tanner Pearson	Marmots (LON)	RW	31	1992-08-10	No	201 Lbs	6 ft1	No	No	No	2	Sans Restriction	Pro & Farm	2,500,000$	0$	0$	No
Taylor Fedun	Marmots (LON)	D	35	1988-06-04	No	200 Lbs	6 ft1	No	No	No	3	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Vinni Lettieri	Marmots (LON)	C	28	1995-02-06	No	184 Lbs	5 ft10	No	No	No	4	Sans Restriction	Pro & Farm	900,000$	0$	0$	No
Vitaly Abramov	Marmots (LON)	RW	25	1998-05-08	Yes	180 Lbs	5 ft10	No	No	No	5	Avec Restriction	Pro & Farm	775,000$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
24	28.42	192 Lbs	6 ft0	3.38	1,563,542$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alex Formenton			35	1	2	2
2	Mathieu Perreault	Vinni Lettieri		30	1	2	2
3		Andrew Poturalski		25	1	2	2
4			Vinni Lettieri	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			35	1	2	2
2	Taylor Fedun	Brogan Rafferty	30	1	2	2
3			25	1	2	2
4			10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Alex Formenton			55	1	2	2
2	Mathieu Perreault	Vinni Lettieri		45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			55	1	2	2
2	Vinni Lettieri	Alex Formenton	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		55	1	2	2			55	1	2	2
2		45	1	2	2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			55	1	2	2
2	Vinni Lettieri	Alex Formenton	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1			55	1	2	2
2	Taylor Fedun	Brogan Rafferty	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alex Formenton

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Alex Formenton

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Andrew Poturalski, ,	Andrew Poturalski,

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Taylor Fedun, Brogan Rafferty,	Taylor Fedun	Brogan Rafferty,

Tirs de Pénalité
, , Vinni Lettieri, Alex Formenton,

Gardien
#1 : Nico Daws, #2 :

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	Bandits	2	0	2	0	0	0	0	0	5	11	-6	1	0	1	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	5	7	12	0	0	23	49	56	10	44	233	399	481	25	75	17	24	56	3	0	0.00%	7	3	57.14%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
2	Chiwawa	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	4	7	0	0	23	49	56	10	35	233	399	481	25	39	11	8	13	3	0	0.00%	4	1	75.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
3	CoolFm	1	0	0	0	0	0	1	0	3	2	1	1	0	0	0	0	0	1	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	3	6	0	0	23	49	56	10	24	233	399	481	25	21	12	2	23	4	1	25.00%	1	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
4	Farmers	2	0	0	0	0	0	2	0	8	6	2	1	0	0	0	0	0	1	0	5	4	1	1	0	0	0	0	0	1	0	3	2	1	4	1.000	8	8	16	0	0	23	49	56	10	62	233	399	481	25	73	33	14	42	8	1	12.50%	7	2	71.43%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
5	Goons	1	0	1	0	0	0	0	0	3	6	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	3	4	7	0	0	23	49	56	10	28	233	399	481	25	40	12	6	14	1	1	100.00%	3	2	33.33%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
6	Grizzlies	4	3	0	0	0	0	0	1	16	13	3	2	2	0	0	0	0	0	0	10	7	3	2	1	0	0	0	0	0	1	6	6	0	7	0.875	16	26	42	0	0	23	49	56	10	120	233	399	481	25	95	24	18	72	11	3	27.27%	9	1	88.89%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
7	Hunters	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	1	2	2	1.000	3	6	9	0	0	23	49	56	10	15	233	399	481	25	14	5	6	4	3	0	0.00%	3	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
8	Husky	2	1	0	0	1	0	0	0	10	7	3	1	1	0	0	0	0	0	0	4	2	2	1	0	0	0	1	0	0	0	6	5	1	4	1.000	10	17	27	0	0	23	49	56	10	59	233	399	481	25	56	19	8	41	13	3	23.08%	4	1	75.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
9	Marlies	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	2	3	5	0	0	23	49	56	10	75	233	399	481	25	76	29	12	42	3	0	0.00%	6	1	83.33%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
10	Outlaws	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	1	2	3	0	0	23	49	56	10	11	233	399	481	25	27	10	4	5	0	0	0.00%	2	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
11	Predateurs	2	0	2	0	0	0	0	0	7	13	-6	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	7	-4	0	0.000	7	11	18	0	0	23	49	56	10	73	233	399	481	25	86	31	22	34	5	2	40.00%	11	4	63.64%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
12	Raptors	2	2	0	0	0	0	0	0	11	4	7	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	7	3	4	4	1.000	11	18	29	0	0	23	49	56	10	68	233	399	481	25	51	12	8	28	6	2	33.33%	4	1	75.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
13	Rockets	1	0	0	0	0	0	0	1	5	6	-1	1	0	0	0	0	0	0	1	5	6	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	5	8	13	0	0	23	49	56	10	42	233	399	481	25	37	13	6	18	6	3	50.00%	3	1	66.67%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
14	Scorpions	1	1	0	0	0	0	0	0	5	3	2	1	1	0	0	0	0	0	0	5	3	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	7	12	0	0	23	49	56	10	35	233	399	481	25	30	8	4	12	5	1	20.00%	2	1	50.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
15	Smirnoff Ice	3	0	1	0	1	0	1	0	9	9	0	1	0	1	0	0	0	0	0	1	3	-2	2	0	0	0	1	0	1	0	8	6	2	4	0.667	9	11	20	1	0	23	49	56	10	90	233	399	481	25	92	21	10	54	7	3	42.86%	5	2	60.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
16	Snowbirds	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	4	2	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	4	8	0	0	23	49	56	10	25	233	399	481	25	20	9	8	14	3	1	33.33%	4	1	75.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
17	Supreme	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	23	49	56	10	16	233	399	481	25	36	9	4	10	0	0	0.00%	2	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
18	Thugs	1	0	0	0	1	0	0	0	6	5	1	1	0	0	0	1	0	0	0	6	5	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	6	10	16	0	0	23	49	56	10	45	233	399	481	25	34	22	11	25	1	0	0.00%	3	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
19	TigersCats	3	2	1	0	0	0	0	0	13	12	1	1	0	1	0	0	0	0	0	4	7	-3	2	2	0	0	0	0	0	0	9	5	4	4	0.667	13	24	37	0	0	23	49	56	10	88	233	399	481	25	114	50	27	56	10	3	30.00%	11	3	72.73%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
	Total	38	13	15	0	3	1	4	2	135	143	-8	18	7	6	0	1	1	2	1	68	72	-4	20	6	9	0	2	0	2	1	67	71	-4	43	0.566	135	206	341	1	0	23	49	56	10	1118	233	399	481	25	1177	393	242	657	110	28	25.45%	106	30	71.70%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
21	Twins	1	0	1	0	0	0	0	0	3	8	-5	1	0	1	0	0	0	0	0	3	8	-5	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	4	7	0	0	23	49	56	10	23	233	399	481	25	24	3	9	8	0	0	0.00%	2	2	0.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
22	Warriors	3	1	1	0	0	1	0	0	12	13	-1	1	0	0	0	0	1	0	0	2	3	-1	2	1	1	0	0	0	0	0	10	10	0	3	0.500	12	21	33	0	0	23	49	56	10	107	233	399	481	25	94	26	21	61	7	2	28.57%	8	4	50.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
23	Wolves	2	1	1	0	0	0	0	0	5	5	0	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	5	6	11	0	0	23	49	56	10	33	233	399	481	25	43	17	10	25	11	2	18.18%	5	0	100.00%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
	_Since Last GM Reset	38	13	15	0	3	1	4	2	135	143	-8	18	7	6	0	1	1	2	1	68	72	-4	20	6	9	0	2	0	2	1	67	71	-4	43	0.566	135	206	341	1	0	23	49	56	10	1118	233	399	481	25	1177	393	242	657	110	28	25.45%	106	30	71.70%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
	_Vs Conference	25	8	8	0	2	1	4	2	89	93	-4	11	3	4	0	0	1	2	1	39	46	-7	14	5	4	0	2	0	2	1	50	47	3	31	0.620	89	138	227	1	0	23	49	56	10	754	233	399	481	25	787	261	154	483	76	20	26.32%	67	20	70.15%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
	_Vs Division	18	6	5	0	1	1	3	2	65	66	-1	8	2	3	0	0	1	1	1	28	34	-6	10	4	2	0	1	0	2	1	37	32	5	23	0.639	65	101	166	1	0	23	49	56	10	584	233	399	481	25	581	196	108	345	52	15	28.85%	49	14	71.43%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344

			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
38	43	L1	135	206	341	1118	1177	393	242	657	1	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
38	13	15	3	1	4	2	135	143

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
18	7	6	1	1	2	1	68	72

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
20	6	9	2	0	2	1	67	71

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
4	5	0	0	1	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
110	28	25.45%	106	30	71.70%	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
233	399	481	25	23	49	56	10

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
379	717	52.86%	388	771	50.32%	296	587	50.43%

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
745	412	874	348	697	344

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 - 2024-04-06	3	Grizzlies	3	Marmots	4	W			Sommaire du Match
2 - 2024-04-07	19	Marmots	4	Grizzlies	5	L	X	X	Sommaire du Match
4 - 2024-04-09	37	Marmots	1	Bandits	3	L			Sommaire du Match
6 - 2024-04-11	49	Rockets	6	Marmots	5	L	X	X	Sommaire du Match
7 - 2024-04-12	70	Smirnoff Ice	3	Marmots	1	L			Sommaire du Match
8 - 2024-04-13	80	Marmots	1	Marlies	3	L			Sommaire du Match
9 - 2024-04-14	85	Marmots	3	Farmers	2	W	X	X	Sommaire du Match
10 - 2024-04-15	104	Marmots	6	Warriors	2	W			Sommaire du Match
12 - 2024-04-17	122	Marlies	4	Marmots	1	L			Sommaire du Match
14 - 2024-04-19	143	Warriors	3	Marmots	2	L	X		Sommaire du Match
16 - 2024-04-21	164	Farmers	4	Marmots	5	W	X	X	Sommaire du Match
17 - 2024-04-22	174	Marmots	3	TigersCats	1	W			Sommaire du Match
18 - 2024-04-23	192	TigersCats	7	Marmots	4	L			Sommaire du Match
19 - 2024-04-24	203	Marmots	3	Smirnoff Ice	2	W	X		Sommaire du Match
21 - 2024-04-26	225	Grizzlies	4	Marmots	6	W			Sommaire du Match
22 - 2024-04-27	235	Marmots	6	TigersCats	4	W			Sommaire du Match
24 - 2024-04-29	254	Husky	2	Marmots	4	W			Sommaire du Match
25 - 2024-04-30	270	Marmots	7	Raptors	3	W			Sommaire du Match
27 - 2024-05-02	286	Marmots	5	Smirnoff Ice	4	W	X	X	Sommaire du Match
28 - 2024-05-03	300	Bandits	8	Marmots	4	L			Sommaire du Match
30 - 2024-05-05	311	Marmots	1	Supreme	4	L			Sommaire du Match
31 - 2024-05-06	329	Wolves	1	Marmots	3	W			Sommaire du Match
33 - 2024-05-08	348	Marmots	3	Predateurs	7	L			Sommaire du Match
34 - 2024-05-09	359	Marmots	6	Husky	5	W	X		Sommaire du Match
35 - 2024-05-10	369	Thugs	5	Marmots	6	W	X		Sommaire du Match
36 - 2024-05-11	386	Marmots	2	Wolves	4	L			Sommaire du Match
38 - 2024-05-13	398	Scorpions	3	Marmots	5	W			Sommaire du Match
40 - 2024-05-15	419	Marmots	3	Goons	6	L			Sommaire du Match
41 - 2024-05-16	432	Predateurs	6	Marmots	4	L			Sommaire du Match
43 - 2024-05-18	453	CoolFm	2	Marmots	3	W	X	X	Sommaire du Match
44 - 2024-05-19	470	Marmots	4	Warriors	8	L			Sommaire du Match
46 - 2024-05-21	485	Snowbirds	2	Marmots	4	W			Sommaire du Match
47 - 2024-05-22	503	Twins	8	Marmots	3	L			Sommaire du Match
48 - 2024-05-23	516	Marmots	3	Chiwawa	4	L			Sommaire du Match
50 - 2024-05-25	534	Raptors	1	Marmots	4	W			Sommaire du Match
51 - 2024-05-26	547	Marmots	2	Grizzlies	1	W			Sommaire du Match
52 - 2024-05-27	555	Marmots	3	Hunters	1	W			Sommaire du Match
53 - 2024-05-28	571	Marmots	1	Outlaws	2	L			Sommaire du Match
55 - 2024-05-30	583	Spartans	-	Marmots	-
57 - 2024-06-01	608	Marmots	-	Marlies	-
58 - 2024-06-02	614	Rockets	-	Marmots	-
61 - 2024-06-05	642	Farmers	-	Marmots	-
62 - 2024-06-06	657	TigersCats	-	Marmots	-
63 - 2024-06-07	667	Marmots	-	Igloos	-
65 - 2024-06-09	688	Marmots	-	Xpress	-
66 - 2024-06-10	698	Smirnoff Ice	-	Marmots	-
67 - 2024-06-11	719	Marmots	-	Barracudas	-
68 - 2024-06-12	730	Bayou	-	Marmots	-
70 - 2024-06-14	745	Marmots	-	Snowbirds	-
71 - 2024-06-15	762	Marmots	-	Vandals	-
72 - 2024-06-16	769	Warriors	-	Marmots	-
73 - 2024-06-17	784	Marmots	-	Thugs	-
74 - 2024-06-18	800	Goons	-	Marmots	-
76 - 2024-06-20	822	Marlies	-	Marmots	-
77 - 2024-06-21	840	Marmots	-	Saguenéens	-
78 - 2024-06-22	849	Marmots	-	Scorpions	-
79 - 2024-06-23	862	Supreme	-	Marmots	-
82 - 2024-06-26	888	Vandals	-	Marmots	-
83 - 2024-06-27	903	Marmots	-	Bandits	-
85 - 2024-06-29	920	Outlaws	-	Marmots	-
87 - 2024-07-01	937	Marmots	-	Spartans	-
88 - 2024-07-02	952	Hunters	-	Marmots	-
89 - 2024-07-03	965	Marmots	-	Farmers	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
91 - 2024-07-05	979	Marmots	-	Twins	-
92 - 2024-07-06	991	Igloos	-	Marmots	-
93 - 2024-07-07	1009	Marmots	-	Vipers	-
95 - 2024-07-09	1022	Chiwawa	-	Marmots	-
96 - 2024-07-10	1040	Vipers	-	Marmots	-
98 - 2024-07-12	1058	Marmots	-	Bayou	-
99 - 2024-07-13	1066	Marmots	-	CoolFm	-
101 - 2024-07-15	1079	Barracudas	-	Marmots	-
103 - 2024-07-17	1097	Marmots	-	Rockets	-
105 - 2024-07-19	1112	Saguenéens	-	Marmots	-
108 - 2024-07-22	1143	Xpress	-	Marmots	-
111 - 2024-07-25	1162	Xpress	-	Marmots	-
112 - 2024-07-26	1169	Marmots	-	Rockets	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	75	30
Assistance	17,394	9,696
Assistance PCT	48.32%	53.87%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
20	1505 - 50.17%	106,362$	1,914,516$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
2,167,229$	3,752,500$	3,752,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	1,832,722$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
2,127,240$	59	39,403$	2,324,777$

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
Saison Régulière
45	82	28	41	0	2	2	4	5	298	331	-33	41	14	19	0	0	1	2	5	150	163	-13	41	14	22	0	2	1	2	0	148	168	-20	75	298	479	777	2	1	55	108	129	11	2350	565	847	914	60	2619	774	585	1332	251	66	26.29%	239	57	76.15%	5	629	1505	41.79%	706	1653	42.71%	604	1345	44.91%	1433	760	2170	704	1373	678
46	82	31	30	0	7	6	5	3	289	276	13	41	16	13	0	3	4	4	1	146	136	10	41	15	17	0	4	2	1	2	143	140	3	95	289	475	764	1	1	50	111	116	18	2282	540	889	834	45	2467	787	563	1249	245	75	30.61%	217	56	74.19%	3	743	1523	48.79%	726	1600	45.38%	668	1297	51.50%	1544	858	2029	708	1403	703
47	38	13	15	0	3	1	4	2	135	143	-8	18	7	6	0	1	1	2	1	68	72	-4	20	6	9	0	2	0	2	1	67	71	-4	43	135	206	341	1	0	23	49	56	10	1118	233	399	481	25	1177	393	242	657	110	28	25.45%	106	30	71.70%	0	379	717	52.86%	388	771	50.32%	296	587	50.43%	745	412	874	348	697	344
Total Saison Régulière	202	72	86	0	12	9	13	10	722	750	-28	100	37	38	0	4	6	8	7	364	371	-7	102	35	48	0	8	3	5	3	358	379	-21	213	722	1160	1882	4	2	128	268	301	39	5750	1338	2135	2229	130	6263	1954	1390	3238	606	169	27.89%	562	143	74.56%	8	1751	3745	46.76%	1820	4024	45.23%	1568	3229	48.56%	3722	2031	5074	1761	3475	1726

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