Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Husky

Husky

GP: 13 | W: 5 | L: 6 | OTL: 2 | P: 12
GF: 44 | GA: 49 | PP%: 27.50% | PK%: 77.27%
DG: René-Karl Poirier | Morale : 90 | Moyenne d'Équipe : 59
Prochain matchs #207 vs Igloos

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Montreal Canadiens
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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	Yakov Trenin		X			100.00	96	48	78	81	70	76	93	58	30	53	63	80	67	86	78	0	90	68	0
2	Kasperi Kapanen			X		100.00	80	45	88	86	65	68	80	66	30	64	69	64	70	86	77	0	90	68	0
3	Yegor Sharangovich		X			100.00	52	45	89	83	68	72	91	61	30	59	64	84	84	84	75	0	90	67	0
4	Parker Kelly (R)			X		100.00	99	54	77	77	61	53	66	48	30	44	51	79	50	83	71	0	90	61	0
5	Jansen Harkins (R)		X			100.00	62	45	80	79	68	54	40	54	30	47	61	65	66	85	73	0	90	59	0
6	Dmitrij Jaskin			X		100.00	50	45	95	73	78	50	40	45	30	40	50	55	50	90	77	0	90	54	0
7	Alexandre Texier (A)		X			100.00	50	45	95	78	61	50	40	45	30	40	50	55	50	84	71	0	90	53	0
8	Michael Sgarbossa	X				100.00	50	45	95	78	56	50	40	45	30	40	50	55	50	91	78	0	90	53	0
9	Nikolay Goldobin			X		100.00	50	45	95	76	62	50	40	45	30	40	50	55	50	88	75	0	90	53	0
10	Jake Gardiner				X	100.00	50	45	95	75	66	50	40	45	30	40	50	55	50	93	80	0	90	57	0
11	Ryan Murphy				X	100.00	50	45	95	78	51	50	40	45	30	40	50	55	50	90	77	0	90	56	0
12	Robbie Russo				X	100.00	50	45	95	77	55	50	40	45	30	40	50	55	50	90	77	0	90	56	0
Rayé
1	Christian Fischer			X		100.00	82	45	88	79	76	74	97	59	30	54	63	79	69	86	78	0	90	68	0
2	Sean Couturier (C)	X				100.00	50	45	95	74	78	50	40	45	30	40	50	55	50	91	78	0	90	54	0
3	Filip Chlapik	X				100.00	50	45	95	77	67	50	40	45	30	40	50	55	50	86	73	0	90	53	0
4	MacKenzie MacEachern		X			100.00	50	45	95	77	67	50	40	45	30	40	50	55	50	89	76	0	90	53	0
5	Jayden Halbgewachs (R)		X			100.00	50	45	95	80	40	50	40	45	30	40	50	55	50	86	73	0	90	52	0
6	Semyon Der-Arguchintsev (R)	X				100.00	50	45	95	79	48	50	40	45	30	40	50	55	50	82	69	0	90	52	0
7	Oliver Ekman-Larsson				X	99.00	70	45	84	86	65	84	65	62	30	70	55	64	69	91	85	0	90	69	0
8	Austin Strand (R)				X	100.00	51	45	92	74	74	52	40	45	30	40	50	58	50	86	74	0	90	58	0
9	Xavier Ouellet				X	100.00	50	45	95	76	60	50	40	45	30	40	50	55	50	90	77	0	90	57	0

	MOYENNE D'ÉQUIPE					99.95	59	46	91	78	64	56	52	49	30	45	54	61	56	87	76	0	90	58

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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	Kaapo Kahkonen	100.00	72	71	88	91	70	75	72	75	70	70	70	86	81	0	90	66	0
2	Mads Sogaard (R)	100.00	71	53	76	89	73	70	71	70	73	70	70	82	73	0	90	63	0
Rayé
1	Chris Driedger	100.00	70	40	40	90	65	65	65	65	65	65	65	87	80	0	90	59	0

	MOYENNE D'ÉQUIPE	100.00	71	55	68	90	69	70	69	70	69	68	68	85	78	0	90	63

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Jeff Blashill	65	65	65	65	84	78	72	CAN	50	2	1,000,000$

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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	GA	TA	EG	HT	P/20	FT	S1	S2	S3
1	Yakov Trenin	Husky (MTL)	LW	13	7	13	20	4	18	0	32	21	51	23	26	13.73%	8	283	21.83	2	2	4	11	30	1	0	1	2	23	1	0	41.67%	48	15	17	1	0	1.41	0	2	1	2
2	Christian Fischer	Husky (MTL)	RW	12	8	12	20	5	8	0	20	27	30	12	28	26.67%	11	255	21.26	1	5	6	3	26	0	0	0	0	29	0	0	31.08%	74	8	12	0	0	1.57	0	3	2	1
3	Michael Sgarbossa	Husky (MTL)	C	13	5	7	12	-2	6	0	13	16	17	2	7	29.41%	5	231	17.78	2	1	3	8	27	0	0	0	0	5	2	0	37.17%	191	2	6	0	0	1.04	0	0	1	2
4	Kasperi Kapanen	Husky (MTL)	RW	13	5	7	12	-6	12	0	24	23	44	10	28	11.36%	7	251	19.32	2	3	5	9	25	1	1	2	1	28	0	2	38.89%	18	7	8	0	0	0.96	0	1	1	0
5	Yegor Sharangovich	Husky (MTL)	LW	13	6	5	11	-4	4	0	16	26	41	12	20	14.63%	6	245	18.87	1	2	3	5	24	1	0	1	3	27	0	0	8.33%	12	8	11	0	0	0.90	0	0	3	1
6	Oliver Ekman-Larsson	Husky (MTL)	D	13	1	10	11	3	16	0	31	20	28	14	9	3.57%	14	323	24.85	1	3	4	6	33	0	2	2	2	33	0	0	0.00%	2	8	19	0	0	0.68	0	0	1	1
7	Jansen Harkins	Husky (MTL)	LW	13	7	1	8	-3	4	0	14	20	38	8	25	18.42%	7	207	15.95	0	0	0	0	3	0	0	0	2	15	2	0	43.75%	32	14	7	0	1	0.77	0	1	1	0
8	Dmitrij Jaskin	Husky (MTL)	RW	13	0	5	5	-4	5	5	14	12	8	1	5	0.00%	2	209	16.12	0	0	0	1	13	0	0	0	0	0	0	0	41.82%	110	5	5	0	0	0.48	1	0	0	0
9	Robbie Russo	Husky (MTL)	D	13	1	2	3	-5	5	5	9	7	9	2	6	11.11%	8	229	17.62	0	0	0	1	13	0	0	0	0	20	0	0	0.00%	1	1	13	0	0	0.26	1	0	0	0
10	Parker Kelly	Husky (MTL)	RW	13	0	2	2	-4	8	0	22	19	22	7	15	0.00%	5	195	15.07	0	0	0	0	6	0	0	0	0	2	0	0	25.00%	8	4	11	0	0	0.20	0	0	0	0
11	Sean Couturier	Husky (MTL)	C	6	1	1	2	-2	2	0	5	9	7	2	7	14.29%	2	123	20.52	1	0	1	4	9	0	0	0	0	3	0	0	31.40%	121	1	4	0	0	0.32	0	0	0	0
12	Jake Gardiner	Husky (MTL)	D	13	0	1	1	-1	0	0	1	11	12	3	4	0.00%	13	266	20.48	0	0	0	2	24	0	0	0	0	29	0	0	0.00%	0	0	7	0	0	0.08	0	0	0	0
13	Austin Strand	Husky (MTL)	D	7	0	1	1	1	4	0	5	10	11	2	5	0.00%	7	171	24.48	0	1	1	0	14	0	0	0	0	12	0	0	0.00%	0	0	6	0	0	0.12	0	0	0	0
14	Ryan Murphy	Husky (MTL)	D	13	0	1	1	-6	0	0	1	11	6	4	1	0.00%	10	202	15.59	0	0	0	0	2	0	0	0	0	9	0	0	0.00%	0	1	13	0	0	0.10	0	0	0	0
15	Xavier Ouellet	Husky (MTL)	D	11	0	1	1	-5	0	0	10	19	11	4	6	0.00%	11	248	22.63	0	0	0	0	26	0	0	0	0	37	0	0	100.00%	1	1	18	0	0	0.08	0	0	0	0
16	Nikolay Goldobin	Husky (MTL)	RW	13	0	1	1	-2	2	0	5	10	4	0	5	0.00%	2	140	10.77	0	0	0	0	4	0	0	0	0	9	0	0	33.85%	65	1	4	0	0	0.14	0	0	0	0
17	Filip Chlapik	Husky (MTL)	C	1	1	0	1	1	0	0	1	3	2	0	0	50.00%	0	19	19.45	0	0	0	0	2	0	0	0	0	0	0	0	44.44%	27	0	0	0	0	1.03	0	0	0	0
18	Alexandre Texier	Husky (MTL)	LW	13	0	0	0	0	0	0	4	5	6	3	0	0.00%	4	136	10.47	0	0	0	0	0	0	0	0	0	1	0	0	22.22%	9	2	5	0	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				206	42	70	112	-30	94	10	227	269	347	109	197	12.10%	122	3739	18.15	10	17	27	50	290	3	3	6	10	290	5	2	36.02%	719	78	166	1	1	0.60	2	7	10	7

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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	ST	BG	S1
1	Kaapo Kahkonen	Husky (MTL)	12	5	5	2	0.886	3.40	706	40	352	172	2	12	1	1
2	Mads Sogaard	Husky (MTL)	2	0	1	0	0.812	6.84	79	9	48	24	0	1	12	0
Stats d'équipe Total ou en Moyenne			14	5	6	2	0.877	3.74	786	49	400	196	2	13	13	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
Alexandre Texier	Husky (MTL)	LW	24	1999-09-13	No	186 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	1,200,000$	0$	0$	No
Austin Strand	Husky (MTL)	D	26	1997-02-17	Yes	215 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	850,000$	0$	0$	No
Chris Driedger	Husky (MTL)	G	29	1994-05-18	No	208 Lbs	6 ft4	No	No	No	4	Sans Restriction	Pro & Farm	850,000$	0$	0$	No
Christian Fischer	Husky (MTL)	RW	26	1997-04-15	No	212 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	1,025,000$	0$	0$	No
Dmitrij Jaskin	Husky (MTL)	RW	30	1993-03-23	No	216 Lbs	6 ft2	No	No	No	3	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Filip Chlapik	Husky (MTL)	C	26	1997-06-03	No	194 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Jake Gardiner	Husky (MTL)	D	33	1990-07-04	No	203 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	900,000$	0$	0$	No
Jansen Harkins	Husky (MTL)	LW	26	1997-05-23	Yes	197 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	0$	0$	No
Jayden Halbgewachs	Husky (MTL)	LW	26	1997-03-22	Yes	160 Lbs	5 ft8	No	No	No	2	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Kaapo Kahkonen	Husky (MTL)	G	27	1996-08-16	No	217 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	1,500,000$	0$	0$	No
Kasperi Kapanen	Husky (MTL)	RW	27	1996-07-23	No	194 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	1,750,000$	0$	0$	No
MacKenzie MacEachern	Husky (MTL)	LW	29	1994-03-09	No	193 Lbs	6 ft2	No	No	No	4	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Mads Sogaard	Husky (MTL)	G	22	2000-12-13	Yes	196 Lbs	6 ft7	No	No	No	3	Avec Restriction	Pro & Farm	1,025,000$	0$	0$	No
Michael Sgarbossa	Husky (MTL)	C	31	1992-07-25	No	179 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Nikolay Goldobin	Husky (MTL)	RW	27	1995-10-07	No	196 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Oliver Ekman-Larsson	Husky (MTL)	D	32	1991-07-17	No	200 Lbs	6 ft2	No	No	No	4	Sans Restriction	Pro & Farm	2,500,000$	0$	0$	No
Parker Kelly	Husky (MTL)	RW	24	1999-05-14	Yes	190 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	900,000$	0$	0$	No
Robbie Russo	Husky (MTL)	D	29	1993-10-12	No	189 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Ryan Murphy	Husky (MTL)	D	29	1993-10-12	No	185 Lbs	5 ft11	No	No	No	2	Sans Restriction	Pro & Farm	800,000$	0$	0$	No
Sean Couturier	Husky (MTL)	C	30	1992-12-07	No	211 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro & Farm	7,000,000$	0$	0$	No
Semyon Der-Arguchintsev	Husky (MTL)	C	23	2000-09-15	Yes	173 Lbs	5 ft10	No	No	No	4	Avec Restriction	Pro & Farm	800,000$	0$	0$	No
Xavier Ouellet	Husky (MTL)	D	30	1993-07-29	No	199 Lbs	6 ft0	No	No	No	2	Sans Restriction	Pro & Farm	900,000$	0$	0$	No
Yakov Trenin	Husky (MTL)	LW	26	1997-01-13	No	201 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	1,500,000$	0$	0$	No
Yegor Sharangovich	Husky (MTL)	LW	25	1998-06-06	No	196 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	2,000,000$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
24	27.38	196 Lbs	6 ft1	2.46	1,330,208$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Yakov Trenin	Michael Sgarbossa	Kasperi Kapanen	35	1	2	2
2	Yegor Sharangovich	Nikolay Goldobin	Parker Kelly	30	1	2	2
3	Jansen Harkins	Alexandre Texier	Dmitrij Jaskin	25	1	2	2
4	Alexandre Texier	Kasperi Kapanen	Nikolay Goldobin	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Jake Gardiner	35	1	2	2
2	Robbie Russo	Ryan Murphy	30	1	2	2
3			25	1	2	2
4		Jake Gardiner	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Yakov Trenin	Michael Sgarbossa	Kasperi Kapanen	55	1	2	2
2	Yegor Sharangovich	Nikolay Goldobin	Parker Kelly	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Jake Gardiner	55	1	2	2
2	Robbie Russo	Ryan Murphy	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Kasperi Kapanen	Yakov Trenin	55	1	2	2
2	Yegor Sharangovich	Parker Kelly	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Jake Gardiner	55	1	2	2
2	Robbie Russo	Ryan Murphy	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Kasperi Kapanen	55	1	2	2		Jake Gardiner	55	1	2	2
2	Yakov Trenin	45	1	2	2	Robbie Russo	Ryan Murphy	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Kasperi Kapanen	Yakov Trenin	55	1	2	2
2	Yegor Sharangovich	Parker Kelly	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Jake Gardiner	55	1	2	2
2	Robbie Russo	Ryan Murphy	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Yakov Trenin	Michael Sgarbossa	Kasperi Kapanen		Jake Gardiner

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Yakov Trenin	Michael Sgarbossa	Kasperi Kapanen		Jake Gardiner

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jansen Harkins, Dmitrij Jaskin, Michael Sgarbossa	Jansen Harkins, Dmitrij Jaskin	Michael Sgarbossa

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Robbie Russo, Ryan Murphy,	Robbie Russo	Ryan Murphy,

Tirs de Pénalité
Kasperi Kapanen, Yakov Trenin, Yegor Sharangovich, Parker Kelly, Jansen Harkins

Gardien
#1 : Mads Sogaard, #2 : Kaapo Kahkonen

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	6	14	-8	2	0	2	0	0	0	0	0	6	14	-8	0	0	0	0	0	0	0	0	0	0	0	0	0.000	6	11	17	0	0	11	13	17	3	61	92	111	129	17	68	18	32	50	3	0	0.00%	11	6	45.45%	1	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
2	CoolFm	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	3	6	9	0	0	11	13	17	3	36	92	111	129	17	28	9	4	22	5	2	40.00%	2	1	50.00%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
3	Goons	2	1	0	0	1	0	0	0	12	5	7	1	1	0	0	0	0	0	0	8	2	6	1	0	0	0	1	0	0	0	4	3	1	4	1.000	12	19	31	0	0	11	13	17	3	56	92	111	129	17	76	30	18	41	6	3	50.00%	9	2	77.78%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
4	Hunters	2	0	1	0	0	1	0	0	4	6	-2	1	0	0	0	0	1	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	3	-1	1	0.250	4	6	10	0	0	11	13	17	3	49	92	111	129	17	44	14	22	21	11	1	9.09%	11	1	90.91%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
5	Igloos	2	0	1	0	1	0	0	0	6	7	-1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	1	0	0	0	6	7	-1	2	0.500	6	8	14	0	0	11	13	17	3	36	92	111	129	17	63	10	11	30	3	1	33.33%	3	0	100.00%	2	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
6	Smirnoff Ice	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	6	9	0	0	11	13	17	3	19	92	111	129	17	26	12	4	18	4	1	25.00%	2	0	100.00%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
	Total	13	2	6	0	3	2	0	0	44	49	-5	6	2	2	0	0	2	0	0	22	24	-2	7	0	4	0	3	0	0	0	22	25	-3	12	0.462	44	71	115	0	0	11	13	17	3	349	92	111	129	17	400	126	103	238	40	11	27.50%	44	10	77.27%	3	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
8	Wolves	1	0	0	0	0	1	0	0	3	4	-1	1	0	0	0	0	1	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	3	5	8	0	0	11	13	17	3	27	92	111	129	17	28	11	6	10	4	1	25.00%	3	0	100.00%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
9	Xpress	2	0	1	0	1	0	0	0	7	8	-1	0	0	0	0	0	0	0	0	0	0	0	2	0	1	0	1	0	0	0	7	8	-1	2	0.500	7	10	17	0	0	11	13	17	3	65	92	111	129	17	67	22	6	46	4	2	50.00%	3	0	100.00%	0	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
	_Since Last GM Reset	13	2	6	0	3	2	0	0	44	49	-5	6	2	2	0	0	2	0	0	22	24	-2	7	0	4	0	3	0	0	0	22	25	-3	12	0.462	44	71	115	0	0	11	13	17	3	349	92	111	129	17	400	126	103	238	40	11	27.50%	44	10	77.27%	3	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
	_Vs Conference	12	2	6	0	3	1	0	0	41	45	-4	5	2	2	0	0	1	0	0	19	20	-1	7	0	4	0	3	0	0	0	22	25	-3	11	0.458	41	66	107	0	0	11	13	17	3	322	92	111	129	17	372	115	97	228	36	10	27.78%	41	10	75.61%	3	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
	_Vs Division	11	1	6	0	3	1	0	0	38	44	-6	4	1	2	0	0	1	0	0	16	19	-3	7	0	4	0	3	0	0	0	22	25	-3	9	0.409	38	60	98	0	0	11	13	17	3	303	92	111	129	17	346	103	93	210	32	9	28.13%	39	10	74.36%	3	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121

			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
13	12	L1	44	71	115	349	400	126	103	238	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
13	2	6	3	2	0	0	44	49

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	2	2	0	2	0	0	22	24

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	0	4	3	0	0	0	22	25

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	5	1	2	0	0

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
40	11	27.50%	44	10	77.27%	3

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
92	111	129	17	11	13	17	3

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
88	244	36.07%	104	275	37.82%	68	193	35.23%

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
219	102	332	116	237	121

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	Lien
1 - 2024-04-06	7	Bandits	10	Husky	3	L		Sommaire du Match
2 - 2024-04-07	13	Husky	4	Xpress	3	W	X	Sommaire du Match
4 - 2024-04-09	36	Husky	4	Igloos	3	W	X	Sommaire du Match
5 - 2024-04-10	44	Husky	3	Xpress	5	L		Sommaire du Match
7 - 2024-04-12	60	Wolves	4	Husky	3	L	X	Sommaire du Match
8 - 2024-04-13	76	Husky	3	CoolFm	4	L		Sommaire du Match
9 - 2024-04-14	88	Bandits	4	Husky	3	L		Sommaire du Match
11 - 2024-04-16	114	Smirnoff Ice	1	Husky	3	W		Sommaire du Match
13 - 2024-04-18	131	Hunters	3	Husky	2	L	X	Sommaire du Match
15 - 2024-04-20	152	Husky	2	Hunters	3	L		Sommaire du Match
16 - 2024-04-21	162	Husky	4	Goons	3	W	X	Sommaire du Match
17 - 2024-04-22	171	Goons	2	Husky	8	W		Sommaire du Match
18 - 2024-04-23	189	Husky	2	Igloos	4	L		Sommaire du Match
20 - 2024-04-25	207	Igloos	-	Husky	-
21 - 2024-04-26	224	TigersCats	-	Husky	-
22 - 2024-04-27	232	Husky	-	Bandits	-
24 - 2024-04-29	254	Husky	-	Marmots	-
25 - 2024-04-30	265	Husky	-	Vipers	-
26 - 2024-05-01	276	Snowbirds	-	Husky	-
28 - 2024-05-03	294	Husky	-	Barracudas	-
29 - 2024-05-04	306	Farmers	-	Husky	-
31 - 2024-05-06	328	Vandals	-	Husky	-
32 - 2024-05-07	341	Husky	-	Xpress	-
34 - 2024-05-09	359	Marmots	-	Husky	-
35 - 2024-05-10	377	Chiwawa	-	Husky	-
37 - 2024-05-12	394	Husky	-	Predateurs	-
38 - 2024-05-13	404	Husky	-	CoolFm	-
40 - 2024-05-15	418	Vipers	-	Husky	-
42 - 2024-05-17	441	Husky	-	Snowbirds	-
43 - 2024-05-18	449	Hunters	-	Husky	-
44 - 2024-05-19	469	Husky	-	Igloos	-
45 - 2024-05-20	482	Wolves	-	Husky	-
46 - 2024-05-21	492	Husky	-	Chiwawa	-
47 - 2024-05-22	505	Husky	-	Farmers	-
49 - 2024-05-24	525	Spartans	-	Husky	-
51 - 2024-05-26	544	Husky	-	Twins	-
52 - 2024-05-27	554	Scorpions	-	Husky	-
54 - 2024-05-29	579	Bandits	-	Husky	-
55 - 2024-05-30	589	Husky	-	Thugs	-
57 - 2024-06-01	602	Husky	-	Bandits	-
58 - 2024-06-02	616	Predateurs	-	Husky	-
60 - 2024-06-04	639	Supreme	-	Husky	-
62 - 2024-06-06	653	Husky	-	Outlaws	-
63 - 2024-06-07	666	Husky	-	Warriors	-
64 - 2024-06-08	678	Marlies	-	Husky	-
66 - 2024-06-10	697	Twins	-	Husky	-
67 - 2024-06-11	712	Husky	-	Marlies	-
68 - 2024-06-12	731	CoolFm	-	Husky	-
69 - 2024-06-13	741	Husky	-	Bayou	-
70 - 2024-06-14	752	Husky	-	Spartans	-
72 - 2024-06-16	770	Thugs	-	Husky	-
73 - 2024-06-17	793	Grizzlies	-	Husky	-
74 - 2024-06-18	804	Husky	-	Smirnoff Ice	-
75 - 2024-06-19	819	Husky	-	Wolves	-
77 - 2024-06-21	831	Xpress	-	Husky	-
78 - 2024-06-22	854	Husky	-	Grizzlies	-
79 - 2024-06-23	865	Husky	-	TigersCats	-
81 - 2024-06-25	875	Raptors	-	Husky	-
83 - 2024-06-27	894	Saguenéens	-	Husky	-
85 - 2024-06-29	917	Rockets	-	Husky	-
87 - 2024-07-01	938	CoolFm	-	Husky	-
88 - 2024-07-02	953	Husky	-	Scorpions	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
90 - 2024-07-04	968	Husky	-	Supreme	-
91 - 2024-07-05	983	Barracudas	-	Husky	-
93 - 2024-07-07	1002	Husky	-	Raptors	-
94 - 2024-07-08	1013	Outlaws	-	Husky	-
95 - 2024-07-09	1029	Husky	-	Hunters	-
96 - 2024-07-10	1041	Husky	-	Goons	-
98 - 2024-07-12	1052	Xpress	-	Husky	-
100 - 2024-07-14	1074	Husky	-	Rockets	-
101 - 2024-07-15	1080	Warriors	-	Husky	-
103 - 2024-07-17	1098	Husky	-	Vandals	-
104 - 2024-07-18	1103	Husky	-	Saguenéens	-
105 - 2024-07-19	1116	Igloos	-	Husky	-
108 - 2024-07-22	1145	Bayou	-	Husky	-
111 - 2024-07-25	1168	Goons	-	Husky	-

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	11,885	6,000
Assistance PCT	99.04%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
32	2981 - 99.36%	101,195$	607,170$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
704,938$	3,192,500$	3,192,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	536,788$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
3,238,240$	94	37,102$	3,487,588$

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	30	38	0	3	3	3	5	272	306	-34	41	16	19	0	1	2	2	1	138	152	-14	41	14	19	0	2	1	1	4	134	154	-20	80	272	460	732	1	2	51	100	115	9	2268	565	777	911	44	2340	771	598	1240	238	42	17.65%	252	77	69.44%	4	638	1477	43.20%	697	1511	46.13%	582	1338	43.50%	1826	1202	1905	642	1233	607
46	82	40	32	0	4	5	1	0	297	281	16	41	18	18	0	2	2	1	0	150	150	0	41	22	14	0	2	3	0	0	147	131	16	95	297	518	815	2	2	52	120	120	5	2141	492	799	831	22	2234	755	762	1168	238	64	26.89%	260	63	75.77%	8	715	1373	52.08%	748	1522	49.15%	674	1293	52.13%	1913	1292	1804	631	1225	607
47	13	2	6	0	3	2	0	0	44	49	-5	6	2	2	0	0	2	0	0	22	24	-2	7	0	4	0	3	0	0	0	22	25	-3	12	44	71	115	0	0	11	13	17	3	349	92	111	129	17	400	126	103	238	40	11	27.50%	44	10	77.27%	3	88	244	36.07%	104	275	37.82%	68	193	35.23%	219	102	332	116	237	121
Total Saison Régulière	177	72	76	0	10	10	4	5	613	636	-23	88	36	39	0	3	6	3	1	310	326	-16	89	36	37	0	7	4	1	4	303	310	-7	187	613	1049	1662	3	4	114	233	252	17	4758	1149	1687	1871	83	4974	1652	1463	2646	516	117	22.67%	556	150	73.02%	15	1441	3094	46.57%	1549	3308	46.83%	1324	2824	46.88%	3959	2597	4042	1390	2696	1336

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