Association Québécoise de Hockey Simulé

Association Québécoise de Hockey Simulé - Vandals

Vandals

GP: 12 | W: 7 | L: 3 | OTL: 2 | P: 16
GF: 44 | GA: 37 | PP%: 26.32% | PK%: 78.57%
DG: Pierre-Alexandre Racine | Morale : 90 | Moyenne d'Équipe : 58
Prochain matchs #186 vs Twins

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Seattle Kraken
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Stats d'équipe en Carrière

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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	Denis Gurianov			X		98.00	60	45	91	79	74	66	80	56	30	52	59	55	68	85	75	0	90	62	0
2	Vinnie Hinostroza	X				98.00	50	45	89	85	53	63	40	62	30	68	56	68	69	89	79	0	90	61	0
3	Martin Kaut (R)		X			99.00	60	45	92	80	65	52	43	54	30	49	59	68	66	83	70	0	90	59	0
4	Jaret Anderson-Dolan	X				96.00	76	45	94	80	64	53	56	56	30	49	62	57	67	83	71	0	90	59	0
5	Egor Sokolov (R)			X		98.00	51	45	95	74	83	50	40	49	30	44	54	61	50	82	69	0	90	56	0
6	Shane Bowers (R)	X				100.00	50	45	95	78	63	99	40	45	30	40	50	55	50	83	85	0	90	56	0
7	Aleksi Heponiemi (R)			X		100.00	50	45	92	82	40	50	40	51	30	48	54	55	65	84	71	0	90	54	0
8	Logan Shaw		X			98.00	50	45	95	74	76	50	40	45	30	40	50	55	50	91	78	0	90	54	0
9	Torey Krug				X	99.00	60	48	74	89	52	77	76	68	30	73	64	64	70	92	85	0	90	69	0
10	Ben Hutton				X	100.00	59	45	90	82	67	67	40	58	30	53	62	68	67	89	79	0	90	65	0
11	Calen Addison (R)				X	100.00	52	45	85	90	45	67	75	65	30	74	56	56	70	83	73	0	90	64	0
12	Jordan Oesterle				X	100.00	63	48	85	81	54	65	63	54	30	54	55	64	66	90	80	0	90	63	0
13	Kyle Capobianco				X	100.00	59	45	87	77	65	51	40	51	30	40	62	62	65	85	73	0	90	60	0
14	Samuel Knazko (R)				X	100.00	50	45	95	76	62	65	40	45	30	40	50	65	50	80	70	0	90	59	0
15	Vincent Iorio (R)				X	100.00	50	45	95	76	69	60	40	47	30	44	50	61	50	80	68	0	90	59	0
16	Connor Carrick				X	100.00	50	45	95	76	56	70	40	47	30	44	50	55	50	89	80	0	90	58	0
Rayé
1	Jakub Lauko (R)	X				87.99	90	48	82	81	64	50	40	57	30	51	64	60	67	83	70	0	90	60	0
2	Riley Tufte (R)		X			100.00	52	45	95	72	93	50	40	45	30	40	50	55	50	85	72	0	90	54	0
3	Cam Atkinson			X		100.00	50	45	95	79	46	50	40	45	30	40	50	55	50	94	81	0	90	53	0
4	William Cuylle (R)		X			100.00	54	51	81	74	77	50	40	45	30	40	50	55	50	81	68	0	90	53	0
5	Cameron Hughes (R)	X				100.00	50	45	95	80	44	50	40	45	30	40	50	55	50	87	74	0	90	52	0
6	Tyce Thompson	X				100.00	50	45	95	79	55	50	40	45	30	40	50	55	50	83	70	0	90	52	0
7	Alex Barre-Boulet (R)			X		100.00	50	45	95	78	52	50	40	45	30	40	50	56	50	85	72	0	90	52	0
8	Ryan Merkley (R)				X	100.00	50	45	95	78	54	50	40	45	30	40	50	55	50	83	70	0	90	56	0
9	Nicolas Beaudin (R)				X	100.00	50	45	95	80	43	50	40	45	30	40	50	55	50	84	71	0	90	55	0

	MOYENNE D'ÉQUIPE					98.92	55	46	91	79	61	58	46	51	30	47	54	59	58	85	74	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	Spencer Knight (R)	99.00	73	55	79	86	74	73	73	73	74	72	70	81	72	0	90	64	0
Rayé

	MOYENNE D'ÉQUIPE	99.00	73	55	79	86	74	73	73	73	74	72	70	81	72	0	90	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Joel Quenneville	65	65	65	65	99	71	42	CAN	65	2	1,250,000$

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Joueur	Nom de l'Équipe	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	GA	TA	P/20	S1	S2	S3
1	Torey Krug	Vandals (SEA)	D	12	5	15	20	4	20	25	20	40	15	24	12.50%	10	275	22.93	2	5	7	8	35	0	14	0	0	0.00%	0	10	21	1.45	1	3	1
2	Vinnie Hinostroza	Vandals (SEA)	C	10	5	9	14	1	6	14	17	45	17	25	11.11%	7	219	21.92	2	3	5	5	25	0	17	0	0	49.28%	209	9	10	1.28	1	0	4
3	Jakub Lauko	Vandals (SEA)	C	12	5	4	9	-3	2	19	19	41	7	22	12.20%	6	200	16.74	2	0	2	4	19	1	12	0	0	43.14%	153	7	5	0.90	1	1	2
4	Calen Addison	Vandals (SEA)	D	12	1	7	8	1	4	4	9	24	6	18	4.17%	12	229	19.09	0	2	2	4	20	0	19	0	0	0.00%	0	3	12	0.70	0	2	0
5	Ben Hutton	Vandals (SEA)	D	12	2	6	8	3	6	6	11	14	6	6	14.29%	15	271	22.63	0	1	1	7	35	0	22	1	1	0.00%	0	3	16	0.59	1	0	1
6	Denis Gurianov	Vandals (SEA)	RW	10	5	3	8	2	2	16	13	23	3	19	21.74%	6	222	22.24	2	1	3	4	24	1	19	0	0	41.51%	53	5	6	0.72	1	0	1
7	Egor Sokolov	Vandals (SEA)	RW	12	5	2	7	-3	0	18	7	17	5	14	29.41%	1	210	17.51	1	1	2	2	21	0	6	2	1	25.00%	12	5	2	0.67	2	0	0
8	Jaret Anderson-Dolan	Vandals (SEA)	C	12	4	3	7	-2	0	12	10	30	5	17	13.33%	5	186	15.52	0	1	1	2	4	0	4	1	1	46.36%	110	5	13	0.75	0	0	0
9	Martin Kaut	Vandals (SEA)	LW	10	2	4	6	-4	0	11	10	17	7	8	11.76%	6	197	19.73	1	2	3	3	24	0	18	1	0	45.45%	22	3	4	0.61	0	0	0
10	Aleksi Heponiemi	Vandals (SEA)	RW	12	3	2	5	2	2	7	5	18	9	7	16.67%	2	172	14.33	0	0	0	0	2	0	0	0	0	55.56%	9	11	4	0.58	0	0	0
11	Samuel Knazko	Vandals (SEA)	D	12	0	2	2	0	2	6	10	7	3	3	0.00%	2	174	14.55	0	0	0	0	0	0	11	0	0	100.00%	1	1	12	0.23	0	0	0
12	Shane Bowers	Vandals (SEA)	C	12	2	0	2	5	0	17	15	9	2	1	22.22%	2	190	15.91	0	0	0	0	0	0	0	0	0	35.56%	45	0	6	0.21	0	1	0
13	Jordan Oesterle	Vandals (SEA)	D	12	0	2	2	1	2	10	8	8	4	2	0.00%	7	227	19.00	0	0	0	2	20	0	21	0	0	0.00%	0	2	15	0.18	0	0	0
14	Kyle Capobianco	Vandals (SEA)	D	11	0	2	2	-1	2	4	9	3	3	2	0.00%	2	158	14.41	0	0	0	0	0	0	1	0	0	100.00%	1	0	5	0.25	0	0	0
15	William Cuylle	Vandals (SEA)	LW	1	0	1	1	1	0	1	1	0	0	0	0.00%	0	6	6.82	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	2.93	0	0	0
16	Logan Shaw	Vandals (SEA)	LW	11	0	1	1	0	2	9	9	3	5	3	0.00%	1	188	17.10	0	0	0	0	18	0	3	0	0	44.44%	9	5	5	0.11	0	0	0
17	Connor Carrick	Vandals (SEA)	D	11	0	0	0	0	2	0	1	0	0	0	0.00%	1	68	6.27	0	0	0	0	0	0	0	0	0	0.00%	0	0	4	0.00	0	0	0
18	Riley Tufte	Vandals (SEA)	LW	1	0	0	0	-3	0	0	1	0	1	1	0.00%	0	17	17.78	0	0	0	0	3	0	0	0	0	0.00%	2	0	2	0.00	0	0	0
19	Vincent Iorio	Vandals (SEA)	D	12	0	0	0	-2	0	0	3	2	0	0	0.00%	3	100	8.40	0	0	0	0	0	0	5	0	0	0.00%	0	1	0	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				197	39	63	102	2	52	179	178	301	98	172	12.96%	88	3318	16.85	10	16	26	41	257	2	179	5	3	45.05%	626	70	142	0.61	7	7	9

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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	S2
1	Spencer Knight	Vandals (SEA)	9	6	1	2	0.887	3.10	542	28	248	117	1	9	1
2	Kasimir Kaskisuo	Seattle Kraken	3	1	2	0	0.855	3.00	180	9	62	29	0	3	0
Stats d'équipe Total ou en Moyenne			12	7	3	2	0.881	3.08	722	37	310	146	1	12	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
Aleksi Heponiemi	Vandals (SEA)	RW	24	1999-01-09	Yes	155 Lbs	5 ft10	No	No	No	3	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Alex Barre-Boulet	Vandals (SEA)	RW	26	1997-05-21	Yes	180 Lbs	5 ft10	No	No	No	3	Avec Restriction	Pro & Farm	850,000$	0$	0$	No
Ben Hutton	Vandals (SEA)	D	30	1993-04-20	No	201 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	2,050,000$	0$	0$	No
Calen Addison	Vandals (SEA)	D	23	2000-04-11	Yes	173 Lbs	5 ft11	No	No	No	3	Avec Restriction	Pro & Farm	4,000,000$	0$	0$	No
Cam Atkinson	Vandals (SEA)	RW	34	1989-06-05	No	176 Lbs	5 ft8	No	No	No	5	Sans Restriction	Pro & Farm	4,150,000$	0$	0$	No
Cameron Hughes	Vandals (SEA)	C	26	1996-10-09	Yes	160 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	700,000$	0$	0$	No
Connor Carrick	Vandals (SEA)	D	29	1994-04-13	No	198 Lbs	5 ft10	No	No	No	2	Sans Restriction	Pro & Farm	700,000$	0$	0$	No
Denis Gurianov	Vandals (SEA)	RW	26	1997-06-07	No	205 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	1,500,000$	0$	0$	No
Egor Sokolov	Vandals (SEA)	RW	23	2000-06-07	Yes	222 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	850,000$	0$	0$	No
Jakub Lauko	Vandals (SEA)	C	23	2000-03-28	Yes	196 Lbs	6 ft0	No	No	No	4	Avec Restriction	Pro & Farm	850,000$	0$	0$	No
Jaret Anderson-Dolan	Vandals (SEA)	C	24	1999-09-12	No	200 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	950,000$	0$	0$	No
Jordan Oesterle	Vandals (SEA)	D	31	1992-06-25	No	187 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	2,550,000$	0$	0$	No
Kyle Capobianco	Vandals (SEA)	D	26	1997-08-13	No	201 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Logan Shaw	Vandals (SEA)	LW	30	1992-10-05	No	208 Lbs	6 ft3	No	No	No	3	Sans Restriction	Pro & Farm	2,050,000$	0$	0$	No
Martin Kaut	Vandals (SEA)	LW	23	1999-10-02	Yes	190 Lbs	6 ft2	No	No	No	5	Avec Restriction	Pro & Farm	2,150,000$	0$	0$	No
Nicolas Beaudin	Vandals (SEA)	D	23	1999-10-07	Yes	168 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Riley Tufte	Vandals (SEA)	LW	25	1998-04-10	Yes	230 Lbs	6 ft6	No	No	No	2	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Ryan Merkley	Vandals (SEA)	D	23	2000-08-14	Yes	186 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	950,000$	0$	0$	No
Samuel Knazko	Vandals (SEA)	D	21	2002-08-07	Yes	198 Lbs	6 ft1	No	No	No	4	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Shane Bowers	Vandals (SEA)	C	24	1999-07-30	Yes	186 Lbs	6 ft2	No	No	No	4	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Spencer Knight	Vandals (SEA)	G	22	2001-04-19	Yes	192 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	3,000,000$	0$	0$	No
Torey Krug	Vandals (SEA)	D	32	1991-04-12	No	194 Lbs	5 ft9	No	No	No	1	Sans Restriction	Pro & Farm	5,500,000$	0$	0$	No
Tyce Thompson	Vandals (SEA)	C	24	1999-07-12	No	175 Lbs	6 ft1	No	No	No	3	Avec Restriction	Pro & Farm	700,000$	0$	0$	No
Vincent Iorio	Vandals (SEA)	D	20	2002-11-14	Yes	200 Lbs	6 ft4	No	No	No	4	Avec Restriction	Pro & Farm	775,000$	0$	0$	No
Vinnie Hinostroza	Vandals (SEA)	C	29	1994-04-03	No	183 Lbs	5 ft10	No	No	No	3	Sans Restriction	Pro & Farm	2,550,000$	0$	0$	No
William Cuylle	Vandals (SEA)	LW	21	2002-02-05	Yes	211 Lbs	6 ft3	No	No	No	4	Avec Restriction	Pro & Farm	775,000$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
26	25.46	191 Lbs	6 ft1	2.77	1,630,769$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Martin Kaut	Vinnie Hinostroza	Denis Gurianov	35	1	2	2
2	Logan Shaw		Egor Sokolov	30	1	2	2
3	Shane Bowers	Jaret Anderson-Dolan	Aleksi Heponiemi	25	1	2	2
4	Denis Gurianov	Shane Bowers	Vinnie Hinostroza	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Ben Hutton	35	1	2	2
2	Calen Addison	Jordan Oesterle	30	1	2	2
3	Kyle Capobianco	Samuel Knazko	25	1	2	2
4	Vincent Iorio	Connor Carrick	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Martin Kaut	Vinnie Hinostroza	Denis Gurianov	55	1	2	2
2	Logan Shaw		Egor Sokolov	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Ben Hutton	55	1	2	2
2	Calen Addison	Jordan Oesterle	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Denis Gurianov	Vinnie Hinostroza	55	1	2	2
2		Martin Kaut	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Ben Hutton	55	1	2	2
2	Calen Addison	Jordan Oesterle	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Denis Gurianov	55	1	2	2	Torey Krug	Ben Hutton	55	1	2	2
2	Vinnie Hinostroza	45	1	2	2	Calen Addison	Jordan Oesterle	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Denis Gurianov	Vinnie Hinostroza	55	1	2	2
2		Martin Kaut	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Torey Krug	Ben Hutton	55	1	2	2
2	Calen Addison	Jordan Oesterle	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Martin Kaut	Vinnie Hinostroza	Denis Gurianov	Torey Krug	Ben Hutton

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Martin Kaut	Vinnie Hinostroza	Denis Gurianov	Torey Krug	Ben Hutton

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Jaret Anderson-Dolan, Aleksi Heponiemi, Egor Sokolov	Jaret Anderson-Dolan, Aleksi Heponiemi	Egor Sokolov

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Kyle Capobianco, Samuel Knazko, Vincent Iorio	Kyle Capobianco	Samuel Knazko, Vincent Iorio

Tirs de Pénalité
Denis Gurianov, Vinnie Hinostroza, , Martin Kaut, Jaret Anderson-Dolan

Gardien
#1 : Spencer Knight, #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	Barracudas	2	1	1	0	0	0	0	0	8	6	2	1	1	0	0	0	0	0	0	6	2	4	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	8	15	23	0	0	6	20	17	1	50	69	131	117	1	38	15	14	44	8	2	25.00%	7	1	85.71%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
2	Bayou	2	2	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	2	2	4	1.000	8	14	22	0	0	6	20	17	1	70	69	131	117	1	38	19	6	41	3	1	33.33%	3	0	100.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
3	Outlaws	1	0	0	0	0	1	0	0	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	4	5	-1	1	0.500	4	5	9	0	0	6	20	17	1	31	69	131	117	1	31	3	4	11	3	1	33.33%	2	1	50.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
4	Predateurs	2	1	1	0	0	0	0	0	8	8	0	1	0	1	0	0	0	0	0	4	5	-1	1	1	0	0	0	0	0	0	4	3	1	2	0.500	8	10	18	0	0	6	20	17	1	54	69	131	117	1	75	21	16	39	7	2	28.57%	8	3	62.50%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
5	Snowbirds	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	1	0	0	0	2	1	1	2	1.000	2	4	6	0	0	6	20	17	1	21	69	131	117	1	32	11	8	16	1	0	0.00%	4	1	75.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
	Total	12	6	3	0	1	2	0	0	44	37	7	6	3	2	0	0	1	0	0	23	18	5	6	3	1	0	1	1	0	0	21	19	2	16	0.667	44	70	114	0	0	6	20	17	1	318	69	131	117	1	310	91	56	203	38	10	26.32%	28	6	78.57%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
7	Twins	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	3	5	0	0	6	20	17	1	29	69	131	117	1	30	6	0	20	5	1	20.00%	0	0	0.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
8	Vipers	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	6	20	17	1	23	69	131	117	1	22	6	4	13	2	0	0.00%	2	0	100.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
9	Wolves	2	2	0	0	0	0	0	0	9	6	3	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	5	4	1	4	1.000	9	14	23	0	0	6	20	17	1	40	69	131	117	1	44	10	4	19	9	3	33.33%	2	0	100.00%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
	_Since Last GM Reset	12	6	3	0	1	2	0	0	44	37	7	6	3	2	0	0	1	0	0	23	18	5	6	3	1	0	1	1	0	0	21	19	2	16	0.667	44	70	114	0	0	6	20	17	1	318	69	131	117	1	310	91	56	203	38	10	26.32%	28	6	78.57%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
	_Vs Conference	12	6	3	0	1	2	0	0	44	37	7	6	3	2	0	0	1	0	0	23	18	5	6	3	1	0	1	1	0	0	21	19	2	16	0.667	44	70	114	0	0	6	20	17	1	318	69	131	117	1	310	91	56	203	38	10	26.32%	28	6	78.57%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
	_Vs Division	11	6	3	0	0	2	0	0	42	36	6	6	3	2	0	0	1	0	0	23	18	5	5	3	1	0	0	1	0	0	19	18	1	14	0.636	42	66	108	0	0	6	20	17	1	297	69	131	117	1	278	80	48	187	37	10	27.03%	24	5	79.17%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115

			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
12	16	OTL1	44	70	114	318	310	91	56	203	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	6	3	1	2	0	0	44	37

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	2	0	1	0	0	23	18

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	3	1	1	1	0	0	21	19

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
5	2	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
38	10	26.32%	28	6	78.57%	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
69	131	117	1	6	20	17	1

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
109	241	45.23%	109	233	46.78%	76	166	45.78%

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
214	105	289	101	218	115

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	2	Vandals	5	Wolves	4	W		Sommaire du Match
3 - 2024-04-08	22	Predateurs	5	Vandals	4	L		Sommaire du Match
5 - 2024-04-10	43	Vipers	4	Vandals	3	L	X	Sommaire du Match
6 - 2024-04-11	54	Vandals	4	Predateurs	3	W		Sommaire du Match
7 - 2024-04-12	66	Vandals	2	Snowbirds	1	W	X	Sommaire du Match
8 - 2024-04-13	78	Barracudas	2	Vandals	6	W		Sommaire du Match
10 - 2024-04-15	99	Vandals	4	Bayou	2	W		Sommaire du Match
11 - 2024-04-16	110	Vandals	2	Barracudas	4	L		Sommaire du Match
12 - 2024-04-17	121	Twins	4	Vandals	2	L		Sommaire du Match
14 - 2024-04-19	148	Bayou	1	Vandals	4	W		Sommaire du Match
16 - 2024-04-21	166	Wolves	2	Vandals	4	W		Sommaire du Match
17 - 2024-04-22	179	Vandals	4	Outlaws	5	L	X	Sommaire du Match
18 - 2024-04-23	186	Vandals	-	Twins	-
20 - 2024-04-25	205	Outlaws	-	Vandals	-
22 - 2024-04-27	227	Predateurs	-	Vandals	-
23 - 2024-04-28	238	Vandals	-	Marlies	-
24 - 2024-04-29	255	Hunters	-	Vandals	-
25 - 2024-04-30	266	Vandals	-	TigersCats	-
27 - 2024-05-02	281	Vandals	-	Bandits	-
28 - 2024-05-03	298	Igloos	-	Vandals	-
30 - 2024-05-05	318	Spartans	-	Vandals	-
31 - 2024-05-06	328	Vandals	-	Husky	-
32 - 2024-05-07	345	Goons	-	Vandals	-
34 - 2024-05-09	354	Vandals	-	Wolves	-
35 - 2024-05-10	370	Vandals	-	Bayou	-
37 - 2024-05-12	391	Vandals	-	Chiwawa	-
38 - 2024-05-13	400	Thugs	-	Vandals	-
39 - 2024-05-14	415	Vandals	-	Outlaws	-
41 - 2024-05-16	433	Scorpions	-	Vandals	-
43 - 2024-05-18	448	Vandals	-	Smirnoff Ice	-
44 - 2024-05-19	464	CoolFm	-	Vandals	-
45 - 2024-05-20	480	Chiwawa	-	Vandals	-
47 - 2024-05-22	497	Vandals	-	Snowbirds	-
48 - 2024-05-23	512	Xpress	-	Vandals	-
50 - 2024-05-25	533	Grizzlies	-	Vandals	-
51 - 2024-05-26	548	Vandals	-	Farmers	-
52 - 2024-05-27	565	Raptors	-	Vandals	-
53 - 2024-05-28	574	Vandals	-	Barracudas	-
56 - 2024-05-31	597	Farmers	-	Vandals	-
58 - 2024-06-02	611	Vandals	-	Thugs	-
59 - 2024-06-03	628	Predateurs	-	Vandals	-
60 - 2024-06-04	633	Vandals	-	Xpress	-
62 - 2024-06-06	656	Vandals	-	Saguenéens	-
63 - 2024-06-07	671	Outlaws	-	Vandals	-
64 - 2024-06-08	686	Vandals	-	CoolFm	-
66 - 2024-06-10	701	Rockets	-	Vandals	-
67 - 2024-06-11	720	Bandits	-	Vandals	-
68 - 2024-06-12	724	Vandals	-	Scorpions	-
69 - 2024-06-13	743	Vandals	-	Rockets	-
71 - 2024-06-15	762	Marmots	-	Vandals	-
72 - 2024-06-16	781	Twins	-	Vandals	-
74 - 2024-06-18	797	Vandals	-	Spartans	-
75 - 2024-06-19	810	Vandals	-	Goons	-
76 - 2024-06-20	825	Saguenéens	-	Vandals	-
77 - 2024-06-21	842	TigersCats	-	Vandals	-
78 - 2024-06-22	851	Vandals	-	Igloos	-
81 - 2024-06-25	876	Barracudas	-	Vandals	-
82 - 2024-06-26	888	Vandals	-	Marmots	-
83 - 2024-06-27	900	Vandals	-	Supreme	-
85 - 2024-06-29	916	Bayou	-	Vandals	-
87 - 2024-07-01	941	Vandals	-	Raptors	-
88 - 2024-07-02	950	Vandals	-	Grizzlies	-
89 - 2024-07-03	960	Vipers	-	Vandals	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
91 - 2024-07-05	980	Vandals	-	Hunters	-
92 - 2024-07-06	990	Warriors	-	Vandals	-
93 - 2024-07-07	1012	Supreme	-	Vandals	-
95 - 2024-07-09	1030	Marlies	-	Vandals	-
96 - 2024-07-10	1035	Vandals	-	Warriors	-
97 - 2024-07-11	1051	Vandals	-	Vipers	-
100 - 2024-07-14	1075	Smirnoff Ice	-	Vandals	-
103 - 2024-07-17	1098	Husky	-	Vandals	-
106 - 2024-07-20	1123	Wolves	-	Vandals	-
107 - 2024-07-21	1131	Vandals	-	Vipers	-
109 - 2024-07-23	1149	Snowbirds	-	Vandals	-
110 - 2024-07-24	1159	Vandals	-	Twins	-
112 - 2024-07-26	1178	Vandals	-	Predateurs	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	40	20
Assistance	11,717	4,910
Assistance PCT	97.64%	81.83%

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	2771 - 92.37%	113,376$	680,256$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
817,788$	4,240,000$	4,240,000$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	629,734$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
3,628,032$	96	48,584$	4,664,064$

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	33	0	5	6	6	4	286	306	-20	41	15	14	0	3	2	4	3	147	143	4	41	13	19	0	2	4	2	1	139	163	-24	88	286	438	724	1	1	60	107	108	16	2143	510	845	764	61	2548	835	517	1325	249	75	30.12%	222	67	69.82%	7	644	1489	43.25%	726	1629	44.57%	494	1252	39.46%	1349	638	2192	708	1449	755
46	82	14	50	0	6	6	3	3	238	354	-116	41	8	24	0	2	4	2	1	120	172	-52	41	6	26	0	4	2	1	2	118	182	-64	55	238	371	609	1	0	38	94	97	13	2102	469	790	830	35	2595	843	447	1445	229	63	27.51%	194	71	63.40%	5	635	1498	42.39%	709	1595	44.45%	537	1242	43.24%	1419	693	2055	721	1497	766
47	12	6	3	0	1	2	0	0	44	37	7	6	3	2	0	0	1	0	0	23	18	5	6	3	1	0	1	1	0	0	21	19	2	16	44	70	114	0	0	6	20	17	1	318	69	131	117	1	310	91	56	203	38	10	26.32%	28	6	78.57%	0	109	241	45.23%	109	233	46.78%	76	166	45.78%	214	105	289	101	218	115
Total Saison Régulière	176	48	86	0	12	14	9	7	568	697	-129	88	26	40	0	5	7	6	4	290	333	-43	88	22	46	0	7	7	3	3	278	364	-86	159	568	879	1447	2	1	104	221	222	30	4563	1048	1766	1711	97	5453	1769	1020	2973	516	148	28.68%	444	144	67.57%	12	1388	3228	43.00%	1544	3457	44.66%	1107	2660	41.62%	2984	1437	4536	1531	3165	1637

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