Stanley Cup Winners Hockey League

WINNIPEG Jets
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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	Austin Czarnik	0	X		X		100.00	57	35	75	68	63	77	67	67	72	69	65	61	66	55	51	37	85	65	0
2	Brandon Pirri	0	X	X			100.00	58	35	71	72	72	42	65	71	68	68	74	57	74	60	53	57	88	64	0
3	Justin Bailey	0			X		100.00	62	35	67	68	89	53	55	67	50	62	62	52	63	53	51	69	97	62	0
4	Matt Read	0			X		100.00	52	35	66	68	68	55	56	68	52	62	62	53	63	68	55	26	97	61	0
5	Hudson Fasching	0			X		100.00	58	89	69	69	84	50	50	69	50	62	62	51	62	51	50	58	92	60	0
6	Byron Froese	0	X				100.00	54	89	62	70	78	50	50	70	70	63	63	52	63	54	51	49	97	60	0
7	Connor Brickley	0	X	X	X		100.00	58	53	68	64	75	54	57	64	50	59	58	52	59	53	51	61	97	59	0
8	Alexandre Grenier	0			X		100.00	60	89	61	66	89	50	50	66	50	57	57	50	57	50	50	53	87	59	0
9	Kristian Vesalainen (R)	0		X			100.00	57	35	72	65	85	54	52	65	50	57	57	52	57	50	50	83	92	59	0
10	Jansen Harkins	0	X				100.00	50	89	64	67	74	50	50	67	50	59	59	50	59	50	50	44	97	58	0
11	Reid Boucher	0		X			100.00	50	35	69	70	69	1	50	70	70	70	70	50	70	55	52	60	97	57	0
12	Quinton Howden	0	X	X			100.00	54	37	80	68	73	45	45	58	40	50	54	63	55	62	54	63	97	57	0
13	Roman Lyubimov (R)	0	X	X			100.00	51	35	80	67	76	45	43	57	33	48	54	64	54	62	52	63	97	57	0
14	Jason Garrison	0				X	100.00	59	35	75	61	81	73	58	61	30	53	60	72	66	72	57	23	87	64	0
15	Juuso Valimaki (R)	0				X	100.00	61	35	75	66	83	65	62	66	30	56	53	66	64	51	50	84	88	62	0
16	TJ Brennan	0				X	100.00	57	89	58	70	81	50	50	70	30	50	45	50	55	52	51	62	97	57	0
17	Seth Helgeson	0				X	100.00	64	89	42	58	91	46	50	58	30	46	41	50	51	52	51	48	99	54	0
18	Frank Corrado	0				X	100.00	53	89	69	56	75	50	50	56	30	47	42	50	52	53	51	47	97	53	0
19	Ryan Lindgren (R)	0				X	100.00	53	35	53	58	75	47	52	58	30	45	41	51	51	50	50	73	96	52	0
Rayé
1	Danick Martel	0		X			100.00	61	35	75	56	64	67	54	56	63	57	57	58	57	51	50	42	92	58	0
2	Andrey Pedan	0				X	100.00	67	47	58	50	87	58	69	58	30	46	40	60	57	51	51	65	92	57	0

	MOYENNE D'ÉQUIPE					100.00	57	55	67	65	78	52	54	64	47	56	56	55	60	55	51	56	94	59

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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	Philippe Desrosiers	100.00	74	62	81	76	73	73	74	73	73	73	68	50	62	43	92	64	0
2	Jean-Francois Berube	100.00	51	56	69	69	65	55	58	60	61	57	55	64	55	55	97	55	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	63	59	75	73	69	64	66	67	67	65	62	57	59	49	95	60

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dean Evason	68	68	68	68	76	76	62	CAN	56	2	325,000$

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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	PKG	PKA	PKP	PKS	PKM	GW	FO%	FOT	HT	P/20	S1	S2	S3
1	Byron Froese	Manitoba Moose (WPG)	C	7	7	9	16	14	4	4	7	43	13	27	16.28%	2	86	12.38	0	0	0	0	0	0	0	0	0	0	1	80.43%	92	1	3.69	1	1	0
2	Matt Read	Manitoba Moose (WPG)	RW	7	8	6	14	17	2	4	2	50	4	29	16.00%	0	74	10.69	0	0	0	0	0	0	0	0	1	1	1	80.00%	5	1	3.74	1	2	1
3	Connor Brickley	Manitoba Moose (WPG)	C/LW/RW	7	11	2	13	9	2	13	11	69	17	42	15.94%	6	106	15.23	1	0	1	4	8	0	0	0	0	0	1	100.00%	10	2	2.44	1	0	2
4	TJ Brennan	Manitoba Moose (WPG)	D	7	2	10	12	9	10	18	6	16	9	12	12.50%	8	125	17.90	0	1	1	3	2	0	0	0	1	7	0	0.00%	0	0	1.92	0	1	0
5	Roman Lyubimov	Manitoba Moose (WPG)	C/LW	7	2	5	7	7	0	0	3	28	4	24	7.14%	1	67	9.70	0	0	0	0	0	0	0	0	0	1	0	85.71%	14	0	2.06	0	0	0
6	Quinton Howden	Manitoba Moose (WPG)	C/LW	7	2	4	6	5	0	1	4	24	8	13	8.33%	0	61	8.82	0	0	0	0	0	0	0	0	0	0	1	40.00%	5	0	1.94	0	0	1
7	Jansen Harkins	Manitoba Moose (WPG)	C	7	3	3	6	8	0	6	7	30	8	23	10.00%	0	67	9.64	0	0	0	0	0	0	0	0	0	0	1	75.00%	80	0	1.78	0	1	1
8	Austin Czarnik	Manitoba Moose (WPG)	C/RW	3	0	5	5	4	0	4	6	18	8	22	0.00%	1	62	20.72	0	0	0	0	1	0	1	1	0	6	0	79.45%	73	0	1.61	0	0	0
9	Jason Garrison	Manitoba Moose (WPG)	D	1	1	4	5	8	0	0	0	5	1	6	20.00%	0	23	23.90	0	0	0	0	0	0	0	0	0	1	0	0.00%	0	0	4.18	1	0	0
10	Kristian Vesalainen	Manitoba Moose (WPG)	LW	4	1	4	5	5	2	1	1	17	8	12	5.88%	0	45	11.40	0	0	0	0	0	0	0	0	0	0	0	66.67%	3	0	2.19	0	0	0
11	Hudson Fasching	Manitoba Moose (WPG)	RW	4	2	2	4	3	0	3	1	16	6	8	12.50%	0	49	12.47	0	0	0	0	0	0	0	0	0	0	0	0.00%	1	0	1.60	0	0	0
12	Reid Boucher	Manitoba Moose (WPG)	LW	7	1	3	4	6	0	2	0	5	5	6	20.00%	0	25	3.63	0	0	0	0	0	0	0	0	0	0	0	100.00%	3	0	3.15	0	0	0
13	Brandon Pirri	Manitoba Moose (WPG)	C/LW	2	1	2	3	3	0	2	0	15	14	18	6.67%	0	35	17.78	0	0	0	0	0	0	1	1	0	2	0	100.00%	2	0	1.69	0	0	0
14	Juuso Valimaki	Manitoba Moose (WPG)	D	2	0	3	3	3	0	0	0	5	1	5	0.00%	1	44	22.32	0	0	0	0	0	0	0	0	1	2	0	0.00%	0	0	1.34	0	0	0
15	Justin Bailey	Manitoba Moose (WPG)	RW	4	1	0	1	2	2	2	0	14	3	7	7.14%	1	34	8.52	0	0	0	0	0	0	0	0	0	1	0	100.00%	2	0	0.59	0	0	0
16	Frank Corrado	Manitoba Moose (WPG)	D	7	0	1	1	10	2	4	1	2	2	5	0.00%	1	75	10.76	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.27	0	0	0
17	Seth Helgeson	Manitoba Moose (WPG)	D	2	1	0	1	5	0	2	0	2	1	3	50.00%	0	39	19.51	0	0	0	0	0	1	0	1	1	2	0	0.00%	0	0	0.51	0	0	0
18	Ryan Lindgren	Manitoba Moose (WPG)	D	6	0	1	1	3	2	11	4	4	1	4	0.00%	2	68	11.42	0	0	0	0	0	0	0	0	0	8	0	0.00%	0	0	0.29	0	0	0
19	Alexandre Grenier	Manitoba Moose (WPG)	RW	1	0	0	0	2	0	1	0	7	2	2	0.00%	0	16	16.87	0	0	0	0	0	0	0	0	1	1	0	100.00%	3	0	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				92	43	64	107	123	26	78	53	370	115	268	11.62%	23	1111	12.08	1	1	2	7	11	1	2	3	5	39	5	79.18%	293	4	1.93	4	5	5

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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	PCT	GAA	MP	SO	GA	SA	A	ST	BG	S1
1	Philippe Desrosiers	Manitoba Moose (WPG)	7	5	2	0.920	2.20	382	3	14	176	1	7	0	1
2	Jean-Francois Berube	Manitoba Moose (WPG)	1	0	0	0.929	4.87	37	0	3	42	0	0	7	0
Stats d'équipe Total ou en Moyenne			8	5	2	0.922	2.43	420	3	17	218	1	7	7	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	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Link
Alexandre Grenier	Manitoba Moose (WPG)	RW	27	1991-09-05	No	91 Kg	196 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Andrey Pedan	Manitoba Moose (WPG)	D	26	1993-07-03	No	97 Kg	196 CM	No	No	No	0	Pro & Farm					0$	0$	No					Lien
Austin Czarnik	Manitoba Moose (WPG)	C/RW	26	1992-12-12	No	77 Kg	175 CM	No	No	No	3	Pro & Farm	1,250,000$	1,137,387$	1,250,000$	1,137,387$	0$	0$	No	1,250,000$	1,250,000$			Lien
Brandon Pirri	Manitoba Moose (WPG)	C/LW	28	1991-04-10	No	85 Kg	183 CM	No	No	No	2	Pro & Farm	775,000$	705,180$	775,000$	705,180$	0$	0$	No	775,000$				Lien
Byron Froese	Manitoba Moose (WPG)	C	28	1991-03-12	No	92 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Connor Brickley	Manitoba Moose (WPG)	C/LW/RW	27	1992-02-25	No	92 Kg	183 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Danick Martel	Manitoba Moose (WPG)	LW	24	1994-12-12	No	80 Kg	173 CM	No	No	No	0	Pro & Farm					0$	0$	No					Lien
Frank Corrado	Manitoba Moose (WPG)	D	26	1993-03-26	No	93 Kg	183 CM	No	No	No	3	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$			Lien
Hudson Fasching	Manitoba Moose (WPG)	RW	24	1995-07-28	No	93 Kg	191 CM	No	No	No	1	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No					Lien
Jansen Harkins	Manitoba Moose (WPG)	C	22	1997-05-23	No	83 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No					Lien
Jason Garrison	Manitoba Moose (WPG)	D	34	1984-11-13	No	99 Kg	185 CM	No	No	No	1	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No					Lien
Jean-Francois Berube	Manitoba Moose (WPG)	G	28	1991-07-13	No	80 Kg	185 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$
Justin Bailey	Manitoba Moose (WPG)	RW	24	1995-07-01	No	97 Kg	193 CM	No	No	No	3	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$			Lien
Juuso Valimaki	Manitoba Moose (WPG)	D	20	1998-10-06	Yes	96 Kg	188 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Kristian Vesalainen	Manitoba Moose (WPG)	LW	20	1999-06-01	Yes	94 Kg	191 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Matt Read	Manitoba Moose (WPG)	RW	33	1986-06-14	No	85 Kg	178 CM	No	No	No	4	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$	750,000$		Lien
Philippe Desrosiers	Manitoba Moose (WPG)	G	24	1995-08-16	No	89 Kg	185 CM	No	No	No	3	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$			Lien
Quinton Howden	Manitoba Moose (WPG)	C/LW	27	1992-01-21	No	86 Kg	188 CM	No	No	No	5	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$	750,000$	750,000$
Reid Boucher	Manitoba Moose (WPG)	LW	25	1993-09-08	No	89 Kg	178 CM	No	No	No	1	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No					Lien
Roman Lyubimov	Manitoba Moose (WPG)	C/LW	27	1992-01-06	Yes	94 Kg	188 CM	No	No	No	1	Pro & Farm	950,000$	864,414$	950,000$	864,414$	0$	0$	No
Ryan Lindgren	Manitoba Moose (WPG)	D	21	1998-02-11	Yes	91 Kg	183 CM	No	No	No	2	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$				Lien
Seth Helgeson	Manitoba Moose (WPG)	D	28	1990-10-08	No	100 Kg	193 CM	No	No	No	3	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$			Lien
TJ Brennan	Manitoba Moose (WPG)	D	30	1989-04-03	No	98 Kg	185 CM	No	No	No	4	Pro & Farm	750,000$	682,432$	750,000$	682,432$	0$	0$	No	750,000$	750,000$	750,000$		Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	26.04	90 Kg	185 CM	2.13	716,304$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Justin Bailey	34	1	2	2
2	Kristian Vesalainen	Connor Brickley	Hudson Fasching	27	1	2	2
3	Reid Boucher	Byron Froese	Matt Read	22	1	2	2
4	Quinton Howden	Jansen Harkins	Roman Lyubimov	17	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	TJ Brennan		46	1	2	2
2	Seth Helgeson	Ryan Lindgren	32	1	2	2
3	Frank Corrado		22	1	2	2
4		TJ Brennan	0	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Kristian Vesalainen		Hudson Fasching	60	1	2	2
2	Connor Brickley		Justin Bailey	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		TJ Brennan	60	1	2	2
2	TJ Brennan	Ryan Lindgren	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Roman Lyubimov	Matt Read	55	1	2	2
2		Justin Bailey	45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Lindgren	55	1	2	2
2	TJ Brennan	Seth Helgeson	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		55	1	2	2		Ryan Lindgren	55	1	2	2
2		45	1	2	2	TJ Brennan	Seth Helgeson	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1			55	1	2	2
2	Justin Bailey	Hudson Fasching	45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Ryan Lindgren	55	1	2	2
2	TJ Brennan	Seth Helgeson	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Connor Brickley		TJ Brennan

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Hudson Fasching	Connor Brickley	Justin Bailey		Ryan Lindgren

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Roman Lyubimov, Reid Boucher, Matt Read	Roman Lyubimov, Reid Boucher	Matt Read

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Ryan Lindgren, TJ Brennan		Frank Corrado, TJ Brennan

Tirs de Pénalité
, , Hudson Fasching, Kristian Vesalainen, Matt Read

Gardien
#1 : Philippe Desrosiers, #2 : Jean-Francois Berube

Lignes d'Attaque Perso. en Prol.
, , Connor Brickley, Hudson Fasching, Justin Bailey, Matt Read, Matt Read, Byron Froese, Reid Boucher, Jansen Harkins, Kristian Vesalainen

Lignes de Défense Perso. en Prol.
, Ryan Lindgren, TJ Brennan, Seth Helgeson, Frank Corrado

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	HOLLYWOOD Oscar	3	3	0	0	0	0	0	0	30	1	29	1	1	0	0	0	0	0	0	9	0	9	2	2	0	0	0	0	0	0	21	1	20	6	1.000	30	50	80	0	2	25	17	3	0	281	129	155	138	0	34	10	6	46	0	0	0.00%	3	0	100.00%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
2	IOWA Wild	2	0	2	0	0	0	0	0	3	14	-11	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	3	14	-11	0	0.000	3	5	8	0	0	25	17	3	0	22	129	155	138	0	133	27	16	22	10	1	10.00%	8	2	75.00%	0	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
3	MONT-LAURIER Sommet	1	1	0	0	0	0	0	0	2	0	2	1	1	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	3	5	0	1	25	17	3	0	23	129	155	138	0	33	3	8	18	5	0	0.00%	4	0	100.00%	0	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
4	Marlies de Toronto	1	1	0	0	0	0	0	0	10	2	8	1	1	0	0	0	0	0	0	10	2	8	0	0	0	0	0	0	0	0	0	0	0	2	1.000	10	16	26	0	0	25	17	3	0	96	129	155	138	0	18	4	0	25	0	0	0.00%	0	0	0.00%	0	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
	Total	7	5	2	0	0	0	0	0	45	17	28	3	3	0	0	0	0	0	0	21	2	19	4	2	2	0	0	0	0	0	24	15	9	10	0.714	45	74	119	0	3	25	17	3	0	422	129	155	138	0	218	44	30	111	15	1	6.67%	15	2	86.67%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
	_Since Last GM Reset	7	5	2	0	0	0	0	0	45	17	28	3	3	0	0	0	0	0	0	21	2	19	4	2	2	0	0	0	0	0	24	15	9	10	0.714	45	74	119	0	3	25	17	3	0	422	129	155	138	0	218	44	30	111	15	1	6.67%	15	2	86.67%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
	_Vs Conference	6	4	2	0	0	0	0	0	35	15	20	2	2	0	0	0	0	0	0	11	0	11	4	2	2	0	0	0	0	0	24	15	9	8	0.667	35	58	93	0	3	25	17	3	0	326	129	155	138	0	200	40	30	86	15	1	6.67%	15	2	86.67%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36

			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
7	10	W2	45	74	119	422	218	44	30	111	0	3

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	5	2	0	0	0	0	45	17

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	3	0	0	0	0	0	21	2

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	2	2	0	0	0	0	24	15

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
5	2	0	0	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
15	1	6.67%	15	2	86.67%	1

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
129	155	138	0	25	17	3	0

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
140	191	73.30%	86	210	40.95%	74	117	63.25%

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
220	183	133	30	65	36

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	Lien
1 - 2020-01-15	8	Manitoba Moose	10	HOLLYWOOD Oscar	0	W	Sommaire du Match
2 - 2020-01-16	21	Marlies de Toronto	2	Manitoba Moose	10	W	Sommaire du Match
3 - 2020-01-17	33	MONT-LAURIER Sommet	0	Manitoba Moose	2	W	Sommaire du Match
4 - 2020-01-18	42	Manitoba Moose	2	IOWA Wild	8	L	Sommaire du Match
5 - 2020-01-19	60	Manitoba Moose	1	IOWA Wild	6	L	Sommaire du Match
7 - 2020-01-21	66	HOLLYWOOD Oscar	0	Manitoba Moose	9	W	Sommaire du Match
9 - 2020-01-23	81	Manitoba Moose	11	HOLLYWOOD Oscar	1	W	Sommaire du Match
11 - 2020-01-25	98	Manitoba Moose	-	WILKIES-BARRIE Penguins	-
13 - 2020-01-27	108	BELLEVILLE Senators	-	Manitoba Moose	-
15 - 2020-01-29	121	CORNWALL Aces	-	Manitoba Moose	-
17 - 2020-01-31	137	Binghampton Devils	-	Manitoba Moose	-
19 - 2020-02-02	151	Manitoba Moose	-	STOCKTON Flames	-
21 - 2020-02-04	160	ROCKFORD IceHogs	-	Manitoba Moose	-
22 - 2020-02-05	174	Manitoba Moose	-	PV Sharapovas	-
24 - 2020-02-07	191	Manitoba Moose	-	IOWA Wild	-
25 - 2020-02-08	203	MONT-LAURIER Sommet	-	Manitoba Moose	-
26 - 2020-02-09	216	BROOKLYN Wolfpack	-	Manitoba Moose	-
28 - 2020-02-11	239	HOLLYWOOD Oscar	-	Manitoba Moose	-
29 - 2020-02-12	249	Manitoba Moose	-	TUSCON Roadrunners	-
31 - 2020-02-14	261	PROVIDENCE Bruins	-	Manitoba Moose	-
32 - 2020-02-15	279	Manitoba Moose	-	TUSCON Roadrunners	-
33 - 2020-02-16	288	Manitoba Moose	-	LEHIGH VALLEY Phantoms	-
34 - 2020-02-17	295	Manitoba Moose	-	SAN DIEGO Gulls	-
35 - 2020-02-18	306	BRIDGEPORT Sound Tigers	-	Manitoba Moose	-
37 - 2020-02-20	320	ROCKFORD IceHogs	-	Manitoba Moose	-
38 - 2020-02-21	339	Manitoba Moose	-	MONT-LAURIER Sommet	-
39 - 2020-02-22	350	Manitoba Moose	-	HERSEY Bears	-
40 - 2020-02-23	358	Manitoba Moose	-	BROOKLYN Wolfpack	-
41 - 2020-02-24	364	CORNWALL Aces	-	Manitoba Moose	-
43 - 2020-02-26	384	COLORADO Eagles	-	Manitoba Moose	-
44 - 2020-02-27	400	SAN DIEGO Gulls	-	Manitoba Moose	-
45 - 2020-02-28	412	Manitoba Moose	-	PROVIDENCE Bruins	-
46 - 2020-02-29	427	CHICAGO Wolves	-	Manitoba Moose	-
48 - 2020-03-02	444	Manitoba Moose	-	PV Sharapovas	-
49 - 2020-03-03	453	UTICA Comets	-	Manitoba Moose	-
50 - 2020-03-04	470	Manitoba Moose	-	CORNWALL Aces	-
52 - 2020-03-06	477	LEHIGH VALLEY Phantoms	-	Manitoba Moose	-
53 - 2020-03-07	495	Manitoba Moose	-	IOWA Wild	-
54 - 2020-03-08	503	IOWA Wild	-	Manitoba Moose	-
56 - 2020-03-10	522	STOCKTON Flames	-	Manitoba Moose	-
57 - 2020-03-11	531	Manitoba Moose	-	BELLEVILLE Senators	-
59 - 2020-03-13	539	Manitoba Moose	-	Syracruse Crunch	-
60 - 2020-03-14	556	Manitoba Moose	-	Marlies de Toronto	-
61 - 2020-03-15	566	MILWAUKEE Admirals	-	Manitoba Moose	-
62 - 2020-03-16	582	PV Sharapovas	-	Manitoba Moose	-
63 - 2020-03-17	598	Manitoba Moose	-	CHICAGO Wolves	-
64 - 2020-03-18	606	Manitoba Moose	-	VICTORIAVILLE Tigres	-
65 - 2020-03-19	615	IOWA Wild	-	Manitoba Moose	-
67 - 2020-03-21	631	PV Sharapovas	-	Manitoba Moose	-
68 - 2020-03-22	642	Manitoba Moose	-	CORNWALL Aces	-
69 - 2020-03-23	660	Manitoba Moose	-	LEHIGH VALLEY Phantoms	-
70 - 2020-03-24	666	WILKIES-BARRIE Penguins	-	Manitoba Moose	-
71 - 2020-03-25	684	Manitoba Moose	-	BELLEVILLE Senators	-
72 - 2020-03-26	693	VICTORIAVILLE Tigres	-	Manitoba Moose	-
73 - 2020-03-27	704	Manitoba Moose	-	WILKIES-BARRIE Penguins	-
75 - 2020-03-29	719	HERSEY Bears	-	Manitoba Moose	-
76 - 2020-03-30	739	Binghampton Devils	-	Manitoba Moose	-
77 - 2020-03-31	751	Manitoba Moose	-	HOLLYWOOD Oscar	-
78 - 2020-04-01	761	BELLEVILLE Senators	-	Manitoba Moose	-
80 - 2020-04-03	775	Manitoba Moose	-	ROCKFORD IceHogs	-
81 - 2020-04-04	787	LEHIGH VALLEY Phantoms	-	Manitoba Moose	-
82 - 2020-04-05	800	Manitoba Moose	-	VICTORIAVILLE Tigres	-
83 - 2020-04-06	813	Manitoba Moose	-	COLORADO Eagles	-
84 - 2020-04-07	824	VICTORIAVILLE Tigres	-	Manitoba Moose	-
85 - 2020-04-08	829	Manitoba Moose	-	MILWAUKEE Admirals	-
86 - 2020-04-09	847	Manitoba Moose	-	STOCKTON Flames	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
88 - 2020-04-11	858	Marlies de Toronto	-	Manitoba Moose	-
89 - 2020-04-12	874	WILKIES-BARRIE Penguins	-	Manitoba Moose	-
91 - 2020-04-14	889	Manitoba Moose	-	MONT-LAURIER Sommet	-
92 - 2020-04-15	903	TUSCON Roadrunners	-	Manitoba Moose	-
93 - 2020-04-16	918	LAVAL Rockets	-	Manitoba Moose	-
94 - 2020-04-17	931	Manitoba Moose	-	Binghampton Devils	-
95 - 2020-04-18	945	Manitoba Moose	-	Syracruse Crunch	-
96 - 2020-04-19	953	STOCKTON Flames	-	Manitoba Moose	-
97 - 2020-04-20	962	Manitoba Moose	-	UTICA Comets	-
99 - 2020-04-22	981	Syracruse Crunch	-	Manitoba Moose	-
100 - 2020-04-23	997	Syracruse Crunch	-	Manitoba Moose	-
102 - 2020-04-25	1009	Manitoba Moose	-	LAVAL Rockets	-
105 - 2020-04-28	1027	Marlies de Toronto	-	Manitoba Moose	-
106 - 2020-04-29	1033	Manitoba Moose	-	Binghampton Devils	-
108 - 2020-05-01	1047	MONT-LAURIER Sommet	-	Manitoba Moose	-
109 - 2020-05-02	1060	Manitoba Moose	-	BRIDGEPORT Sound Tigers	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2
Capacité de l'Aréna	2000	1000
Prix des Billets	35	15
Assistance	0	0
Assistance PCT	0.00%	0.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
38	0 - 0.00%	0$	0$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
157,273$	1,647,500$	1,647,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	127,993$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	101	17,770$	1,794,770$

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
33	7	5	2	0	0	0	0	0	45	17	28	3	3	0	0	0	0	0	0	21	2	19	4	2	2	0	0	0	0	0	24	15	9	10	45	74	119	0	3	25	17	3	0	422	129	155	138	0	218	44	30	111	15	1	6.67%	15	2	86.67%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
Total Saison Régulière	7	5	2	0	0	0	0	0	45	17	28	3	3	0	0	0	0	0	0	21	2	19	4	2	2	0	0	0	0	0	24	15	9	10	45	74	119	0	3	25	17	3	0	422	129	155	138	0	218	44	30	111	15	1	6.67%	15	2	86.67%	1	140	191	73.30%	86	210	40.95%	74	117	63.25%	220	183	133	30	65	36
Séries
32	20	12	8	0	0	0	0	0	48	48	0	10	6	4	0	0	0	0	0	28	25	3	10	6	4	0	0	0	0	0	20	23	-3	24	48	84	132	0	1	18	13	16	1	583	180	195	188	20	599	203	203	338	81	13	16.05%	87	12	86.21%	0	373	660	56.52%	389	711	54.71%	150	292	51.37%	471	325	520	151	249	124
Total Séries	20	12	8	0	0	0	0	0	48	48	0	10	6	4	0	0	0	0	0	28	25	3	10	6	4	0	0	0	0	0	20	23	-3	24	48	84	132	0	1	18	13	16	1	583	180	195	188	20	599	203	203	338	81	13	16.05%	87	12	86.21%	0	373	660	56.52%	389	711	54.71%	150	292	51.37%	471	325	520	151	249	124