Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Marmots

Marmots

GP: 20 | W: 11 | L: 6 | OTL: 3 | P: 25
GF: 75 | GA: 73 | PP%: 28.33% | PK%: 72.00%
DG: Patrick Gagnon | Morale : 90 | Moyenne d'Équipe : 56
Prochain matchs #311 vs Supreme

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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	Patrick Maroon		X			100.00	95	81	44	73	89	52	97	52	30	49	55	55	66	94	81	0	90	62	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	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
5	Mathieu Perreault		X			100.00	50	45	95	77	57	50	40	45	30	40	50	55	50	95	82	0	90	53	0
6	Andrew Poturalski	X				100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	89	76	0	90	53	0
7	Max McCormick			X		100.00	50	45	95	77	58	50	40	45	30	40	50	55	50	91	78	0	90	53	0
8	Alex Formenton		X			100.00	50	45	95	76	70	50	40	45	30	40	50	55	50	84	71	0	90	53	0
9	Vinni Lettieri	X				100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	88	75	0	90	53	0
10	Sheldon Rempal			X		100.00	50	45	95	80	44	50	40	45	30	40	50	55	50	87	74	0	90	52	0
11	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
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	Nic Petan			X		100.00	50	45	92	81	47	58	40	51	30	48	54	59	65	88	77	0	90	56	0
2	Cedric Paquette		X			100.00	50	45	95	75	69	50	40	45	30	40	50	55	50	90	77	0	90	53	0
3	Brian Pinho	X				100.00	50	45	95	77	63	50	40	45	30	40	50	55	50	88	75	0	90	53	0
4	Kole Sherwood			X		100.00	50	45	95	74	74	50	40	45	30	40	50	55	50	86	73	0	90	53	0
5	Paul Byron		X			100.00	50	45	95	80	40	50	40	45	30	40	50	55	50	94	81	0	90	52	0

	MOYENNE D'ÉQUIPE					100.00	57	47	89	77	61	54	43	47	33	43	51	58	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	20	14	14	28	-5	33	15	38	21	120	39	65	11.67%	14	409	20.46	4	8	12	22	47	2	22	1	1	55.26%	38	22	8	1	1	1.37	2	4	1	1	1	3	2	1
2	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
3	Hunter McKown	Marmots (LON)	C	13	2	9	11	-3	4	0	17	34	23	7	24	8.70%	5	218	16.82	1	1	2	1	18	0	9	0	0	65.42%	214	6	5	0	0	1.01	0	1	0	0	0	0	1	0
4	Vinni Lettieri	Marmots (LON)	C	17	2	9	11	-3	4	0	19	25	35	8	10	5.71%	4	238	14.02	0	0	0	0	0	1	10	0	0	46.43%	140	6	6	0	0	0.92	0	0	0	0	0	1	0	1
5	Patrick Maroon	Marmots (LON)	LW	11	7	2	9	1	14	0	43	18	32	12	23	21.87%	8	242	22.07	2	1	3	4	28	0	16	2	0	33.33%	15	7	13	0	0	0.74	1	4	0	0	0	1	1	2
6	Dylan McIlrath	Marmots (LON)	D	20	2	6	8	-5	10	0	20	25	25	13	5	8.00%	20	437	21.88	0	1	1	4	39	1	32	0	0	50.00%	2	14	16	0	0	0.37	0	0	0	0	0	0	0	2
7	Alex Goligoski	Marmots (LON)	D	10	2	5	7	-5	4	0	24	18	17	4	7	11.76%	12	260	26.06	0	2	2	1	24	0	21	0	0	0.00%	0	8	12	0	0	0.54	0	0	0	0	0	0	0	0
8	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
9	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
10	Mason Shaw	London Spartiates	RW	2	2	4	6	3	0	0	5	3	7	2	7	28.57%	3	42	21.23	2	0	2	3	3	0	3	0	0	0.00%	1	0	3	0	0	2.83	0	1	0	0	0	1	1	0
11	Mathieu Perreault	Marmots (LON)	LW	18	2	3	5	-6	0	0	17	27	36	14	18	5.56%	3	294	16.35	0	0	0	1	20	3	9	1	0	52.38%	21	10	6	0	0	0.34	0	0	0	0	0	1	0	0
12	Kevin Gravel	Marmots (LON)	D	20	2	3	5	-4	2	0	25	30	20	10	12	10.00%	21	439	22.00	2	0	2	5	39	0	35	0	0	0.00%	0	8	22	0	0	0.23	0	0	0	0	0	0	0	0
13	Max McCormick	Marmots (LON)	RW	10	1	4	5	1	0	0	6	8	22	4	11	4.55%	3	163	16.31	0	0	0	4	21	0	0	0	0	33.33%	6	6	0	0	0	0.61	0	0	0	0	0	0	0	1
14	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
15	Kristian Reichel	Marmots (LON)	C	10	4	0	4	-2	2	0	11	20	24	9	16	16.67%	7	181	18.20	0	0	0	1	15	0	13	0	0	49.54%	109	6	6	0	0	0.44	1	1	0	0	0	0	0	0
16	Taylor Fedun	Marmots (LON)	D	20	0	4	4	10	4	0	7	19	15	6	8	0.00%	14	338	16.91	0	1	1	1	17	0	13	0	0	0.00%	1	2	9	0	0	0.24	0	0	0	0	0	0	0	0
17	Brogan Rafferty	Marmots (LON)	D	10	0	4	4	10	2	0	6	13	8	2	0	0.00%	8	181	18.16	0	0	0	0	12	0	13	0	0	0.00%	0	3	5	0	0	0.44	0	0	0	0	0	0	0	0
18	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
19	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
20	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
21	Andrew Poturalski	Marmots (LON)	C	7	2	0	2	1	2	0	3	10	8	2	3	25.00%	1	103	14.77	0	0	0	0	0	0	0	0	0	33.33%	15	1	1	0	0	0.39	0	0	0	0	0	0	0	0
22	Alex Formenton	Marmots (LON)	LW	10	2	0	2	4	0	0	6	7	14	3	8	14.29%	6	164	16.43	2	0	2	3	16	0	13	1	0	33.33%	15	2	3	0	0	0.24	0	0	0	0	0	0	0	2
23	Mark Friedman	Marmots (LON)	D	10	0	2	2	-5	8	0	20	15	27	7	7	0.00%	23	260	26.00	0	1	1	1	24	0	21	0	0	0.00%	0	6	10	0	0	0.15	0	0	0	0	0	0	0	0
24	Vitaly Abramov	Marmots (LON)	RW	1	0	0	0	-1	0	0	0	0	0	0	0	0.00%	0	6	6.80	0	0	0	0	0	0	0	0	0	0.00%	0	0	1	0	0	0.00	0	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				274	67	93	160	-6	97	15	326	373	588	196	323	11.39%	177	5040	18.39	16	23	39	63	380	9	269	8	1	55.28%	984	161	165	1	2	0.63	6	15	1	1	1	8	11	11

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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	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1
1	Ivan Prosvetov	Marmots (LON)	16	9	5	2	0.894	3.58	923	55	520	264	0	1	0.667	15	16	1	2
2	Nico Daws	Marmots (LON)	6	2	1	1	0.897	2.95	305	15	145	84	1	0	0.000	0	4	17	0
Stats d'équipe Total ou en Moyenne			22	11	6	3	0.895	3.42	1228	70	665	348	1	1	0.667	15	20	18	2

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	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
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
Patrick Maroon	Marmots (LON)	LW	35	1988-04-23	No	234 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	1,500,000$	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	28.88	194 Lbs	6 ft1	3.33	1,592,708$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Patrick Maroon	Hunter McKown	Tanner Pearson	35	1	2	2
2	Mathieu Perreault	Kristian Reichel	Max McCormick	30	1	2	2
3	Alex Formenton	Andrew Poturalski	Sheldon Rempal	25	1	2	2
4	Patrick Maroon	Vinni Lettieri	Vitaly Abramov	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Alex Goligoski	35	1	2	2
2	Kevin Gravel	Dylan McIlrath	30	1	2	2
3	Taylor Fedun	Brogan Rafferty	25	1	2	2
4	Mark Friedman	Alex Goligoski	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Patrick Maroon	Hunter McKown	Tanner Pearson	55	1	2	2
2	Mathieu Perreault	Kristian Reichel	Max McCormick	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Alex Goligoski	55	1	2	2
2	Kevin Gravel	Dylan McIlrath	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Patrick Maroon	Tanner Pearson	55	1	2	2
2	Hunter McKown	Kristian Reichel	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Alex Goligoski	55	1	2	2
2	Kevin Gravel	Dylan McIlrath	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Patrick Maroon	55	1	2	2	Mark Friedman	Alex Goligoski	55	1	2	2
2	Tanner Pearson	45	1	2	2	Kevin Gravel	Dylan McIlrath	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Patrick Maroon	Tanner Pearson	55	1	2	2
2	Hunter McKown	Kristian Reichel	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Mark Friedman	Alex Goligoski	55	1	2	2
2	Kevin Gravel	Dylan McIlrath	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Patrick Maroon	Hunter McKown	Tanner Pearson	Mark Friedman	Alex Goligoski

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Patrick Maroon	Hunter McKown	Tanner Pearson	Mark Friedman	Alex Goligoski

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Andrew Poturalski, Alex Formenton, Vinni Lettieri	Andrew Poturalski, Alex Formenton	Vinni Lettieri

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

Tirs de Pénalité
Patrick Maroon, Tanner Pearson, Hunter McKown, Kristian Reichel, Andrew Poturalski

Gardien
#1 : Ivan Prosvetov, #2 : Nico Daws

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	12	30	29	7	44	122	257	273	17	75	17	24	56	3	0	0.00%	7	3	57.14%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
2	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	12	30	29	7	62	122	257	273	17	73	33	14	42	8	1	12.50%	7	2	71.43%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
3	Grizzlies	3	2	0	0	0	0	0	1	14	12	2	2	2	0	0	0	0	0	0	10	7	3	1	0	0	0	0	0	0	1	4	5	-1	5	0.833	14	22	36	0	0	12	30	29	7	103	122	257	273	17	85	22	14	62	9	2	22.22%	7	1	85.71%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
4	Husky	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	7	11	0	0	12	30	29	7	27	122	257	273	17	20	8	0	20	6	2	33.33%	0	0	0.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
5	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	12	30	29	7	75	122	257	273	17	76	29	12	42	3	0	0.00%	6	1	83.33%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
6	Raptors	1	1	0	0	0	0	0	0	7	3	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	7	3	4	2	1.000	7	10	17	0	0	12	30	29	7	43	122	257	273	17	38	10	6	17	4	2	50.00%	3	1	66.67%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
7	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	12	30	29	7	42	122	257	273	17	37	13	6	18	6	3	50.00%	3	1	66.67%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
8	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	12	30	29	7	90	122	257	273	17	92	21	10	54	7	3	42.86%	5	2	60.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
9	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	12	30	29	7	88	122	257	273	17	114	50	27	56	10	3	30.00%	11	3	72.73%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
	Total	20	7	6	0	1	1	3	2	75	73	2	10	3	4	0	0	1	1	1	36	44	-8	10	4	2	0	1	0	2	1	39	29	10	25	0.625	75	115	190	1	0	12	30	29	7	653	122	257	273	17	666	216	115	407	60	17	28.33%	50	14	72.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
11	Warriors	2	1	0	0	0	1	0	0	8	5	3	1	0	0	0	0	1	0	0	2	3	-1	1	1	0	0	0	0	0	0	6	2	4	3	0.750	8	15	23	0	0	12	30	29	7	79	122	257	273	17	56	13	2	40	4	1	25.00%	1	0	100.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
	_Since Last GM Reset	20	7	6	0	1	1	3	2	75	73	2	10	3	4	0	0	1	1	1	36	44	-8	10	4	2	0	1	0	2	1	39	29	10	25	0.625	75	115	190	1	0	12	30	29	7	653	122	257	273	17	666	216	115	407	60	17	28.33%	50	14	72.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
	_Vs Conference	19	6	6	0	1	1	3	2	68	70	-2	10	3	4	0	0	1	1	1	36	44	-8	9	3	2	0	1	0	2	1	32	26	6	23	0.605	68	105	173	1	0	12	30	29	7	610	122	257	273	17	628	206	109	390	56	15	26.79%	47	13	72.34%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
	_Vs Division	16	5	4	0	1	1	3	2	59	57	2	8	2	3	0	0	1	1	1	28	34	-6	8	3	1	0	1	0	2	1	31	23	8	21	0.656	59	91	150	1	0	12	30	29	7	539	122	257	273	17	533	181	85	314	47	13	27.66%	40	10	75.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200

			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
20	25	L1	75	115	190	653	666	216	115	407	1	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
20	7	6	1	1	3	2	75	73

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	3	4	0	1	1	1	36	44

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	4	2	1	0	2	1	39	29

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
5	2	1	0	2	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
60	17	28.33%	50	14	72.00%	0

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
122	257	273	17	12	30	29	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
236	422	55.92%	238	447	53.24%	163	299	54.52%

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
411	216	418	194	399	200

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	-	Supreme	-
31 - 2024-05-06	329	Wolves	-	Marmots	-
33 - 2024-05-08	348	Marmots	-	Predateurs	-
34 - 2024-05-09	359	Marmots	-	Husky	-
35 - 2024-05-10	369	Thugs	-	Marmots	-
36 - 2024-05-11	386	Marmots	-	Wolves	-
38 - 2024-05-13	398	Scorpions	-	Marmots	-
40 - 2024-05-15	419	Marmots	-	Goons	-
41 - 2024-05-16	432	Predateurs	-	Marmots	-
43 - 2024-05-18	453	CoolFm	-	Marmots	-
44 - 2024-05-19	470	Marmots	-	Warriors	-
46 - 2024-05-21	485	Snowbirds	-	Marmots	-
47 - 2024-05-22	503	Twins	-	Marmots	-
48 - 2024-05-23	516	Marmots	-	Chiwawa	-
50 - 2024-05-25	534	Raptors	-	Marmots	-
51 - 2024-05-26	547	Marmots	-	Grizzlies	-
52 - 2024-05-27	555	Marmots	-	Hunters	-
53 - 2024-05-28	571	Marmots	-	Outlaws	-
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	9,756	5,332
Assistance PCT	48.78%	53.32%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
28	1509 - 50.29%	106,999$	1,069,992$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,162,343$	3,822,500$	3,822,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	982,697$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
2,995,978$	84	40,022$	3,361,848$

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	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	20	7	6	0	1	1	3	2	75	73	2	10	3	4	0	0	1	1	1	36	44	-8	10	4	2	0	1	0	2	1	39	29	10	25	75	115	190	1	0	12	30	29	7	653	122	257	273	17	666	216	115	407	60	17	28.33%	50	14	72.00%	0	236	422	55.92%	238	447	53.24%	163	299	54.52%	411	216	418	194	399	200
Total Saison Régulière	184	66	77	0	10	9	12	10	662	680	-18	92	33	36	0	3	6	7	7	332	343	-11	92	33	41	0	7	3	5	3	330	337	-7	195	662	1069	1731	4	2	117	249	274	36	5285	1227	1993	2021	122	5752	1777	1263	2988	556	158	28.42%	506	127	74.90%	8	1608	3450	46.61%	1670	3700	45.14%	1435	2941	48.79%	3388	1836	4618	1607	3176	1582

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