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	Riley Nash	0	X		X		100.00	66	41	74	64	75	76	91	63	76	65	62	63	63	69	56	66	81	68	0
2	Andy Andreoff	0	X	X			100.00	76	44	67	69	74	74	62	64	40	65	63	60	66	56	55	55	81	65	0
3	Rocco Grimaldi	0	X		X		100.00	60	35	75	67	62	71	76	66	70	66	64	60	65	54	51	73	83	64	0
4	Ryan Poehling (R)	0	X				100.00	62	35	77	62	77	78	50	62	70	60	61	66	62	50	55	83	88	63	0
5	Marko Dano	0	X	X			100.00	56	68	59	69	75	52	54	69	68	60	60	51	61	56	52	77	81	60	0
6	Mark McNeill	0	X		X		100.00	58	89	65	67	83	50	50	67	70	56	56	50	56	50	50	79	82	58	0
7	Liam O'Brien	0		X			100.00	57	89	46	65	80	50	50	65	50	58	58	50	58	51	50	42	81	58	0
8	Jiri Sekac	0		X			100.00	59	38	80	69	70	46	47	58	31	55	50	59	53	60	49	71	81	57	0
9	Scott Kosmachuk	0			X		100.00	50	89	63	67	69	50	50	67	50	59	59	50	59	50	50	64	81	57	0
10	Lucas Lessio	0		X			100.00	57	37	74	67	75	45	45	57	31	51	54	61	59	58	47	79	81	56	0
11	Louis-Marc Aubry	0	X				100.00	54	41	66	64	84	50	45	54	43	50	51	51	52	64	61	55	81	56	0
12	Sebastian Collberg (R)	0			X		100.00	46	35	80	70	67	45	40	52	30	49	46	50	51	56	51	87	80	53	0
13	Brandon Manning	0				X	100.00	70	56	75	60	78	70	69	60	30	55	57	73	64	60	53	36	86	64	0
14	Gustav Olofsson	0				X	100.00	62	41	81	62	76	73	58	72	30	55	47	66	62	52	51	71	81	62	0
15	Justin Falk	0				X	100.00	74	62	71	59	94	53	55	59	30	49	46	57	56	61	53	47	81	59	0
16	Zach Trotman	0				X	100.00	64	35	70	59	87	59	56	59	30	50	46	58	56	53	51	40	81	58	0
17	Jan Kostalek	0				X	100.00	56	41	75	50	72	52	54	53	30	39	39	60	56	50	50	44	93	52	0
Rayé
1	Cal O'Reilly	0	X				100.00	50	89	70	70	72	50	50	70	70	60	60	50	60	56	52	29	62	59	0
2	Brian Strait	0				X	100.00	55	89	71	50	79	43	50	50	30	45	40	50	50	57	52	52	46	51	0

	MOYENNE D'ÉQUIPE					100.00	60	55	70	64	76	57	55	61	46	55	54	57	58	56	52	61	80	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	Chad Johnson	100.00	71	71	70	83	70	70	71	70	70	70	66	64	68	35	76	64	0
2	Jonas Gustavsson	100.00	65	57	66	81	69	68	66	67	66	74	62	78	72	5	81	62	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	68	64	68	82	70	69	69	69	68	72	64	71	70	20	79	63

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dale Hunter	65	65	65	65	76	76	54	CAN	59	3	82,000$

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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	EG	HT	P/20	PSG	PSS	FW	FL	S1	S2	S3
1	Riley Nash	MANITOBA Moose (WPG)	C/RW	68	57	50	107	80	22	0	53	143	401	74	255	14.21%	22	1429	21.03	3	5	8	32	133	1	2	3	12	221	3	0	62.40%	1665	0	6	1.50	3	5	0	0	7	7	5
2	Andy Andreoff	MANITOBA Moose (WPG)	C/LW	66	35	57	92	65	57	5	169	96	345	104	229	10.14%	16	1330	20.16	4	5	9	49	129	2	0	2	9	203	3	3	53.68%	95	0	2	1.38	2	5	1	0	7	2	4
3	Marko Dano	MANITOBA Moose (WPG)	C/LW	70	32	58	90	62	45	5	104	68	287	80	207	11.15%	12	1052	15.04	4	11	15	26	126	0	1	1	1	24	3	0	72.34%	141	0	2	1.71	0	1	0	1	3	5	6
4	Gustav Olofsson	MANITOBA Moose (WPG)	D	70	19	60	79	62	50	0	132	75	156	47	106	12.18%	91	1647	23.54	7	11	18	45	151	0	3	3	2	202	0	2	0.00%	0	0	0	0.96	1	1	0	0	5	2	4
5	Mark McNeill	MANITOBA Moose (WPG)	C/RW	70	24	51	75	63	47	5	113	66	271	85	215	8.86%	22	1037	14.83	4	9	13	20	129	0	0	0	0	1	1	2	72.31%	65	1	1	1.45	0	0	1	0	2	5	4
6	Rocco Grimaldi	MANITOBA Moose (WPG)	C/RW	45	28	38	66	55	4	0	24	67	220	68	147	12.73%	7	868	19.29	2	3	5	21	82	1	0	1	5	115	3	1	57.79%	199	0	3	1.52	0	2	0	0	4	2	7
7	Cal O'Reilly	MANITOBA Moose (WPG)	C	59	25	39	64	50	21	5	23	57	220	45	154	11.36%	11	741	12.57	0	1	1	2	22	1	0	1	4	31	2	0	70.13%	713	0	1	1.73	1	1	0	0	3	2	1
8	Liam O'Brien	MANITOBA Moose (WPG)	LW	70	27	32	59	65	52	0	113	55	186	54	163	14.52%	24	940	13.43	1	0	1	5	15	0	0	0	1	70	8	0	59.77%	87	0	1	1.25	0	0	0	0	0	3	1
9	Scott Kosmachuk	MANITOBA Moose (WPG)	RW	70	27	31	58	53	16	0	47	45	264	62	163	10.23%	19	818	11.70	0	0	0	1	6	0	0	0	0	1	4	0	67.92%	53	0	1	1.42	1	1	0	0	4	1	2
10	Zach Trotman	MANITOBA Moose (WPG)	D	70	11	37	48	81	54	0	75	35	82	36	65	13.41%	49	1259	18.00	2	4	6	24	109	0	1	1	1	184	1	0	0.00%	0	0	0	0.76	0	0	0	0	0	3	1
11	Brandon Manning	MANITOBA Moose (WPG)	D	48	14	32	46	58	65	5	135	43	118	37	83	11.86%	66	1181	24.61	3	1	4	19	79	0	0	0	4	132	3	0	0.00%	0	0	0	0.78	0	0	1	0	0	4	3
12	Louis-Marc Aubry	MANITOBA Moose (WPG)	C	70	14	23	37	23	22	0	48	50	126	26	90	11.11%	6	705	10.07	0	0	0	0	1	0	0	0	0	2	1	0	61.49%	683	0	0	1.05	0	0	0	0	0	0	0
13	Justin Falk	MANITOBA Moose (WPG)	D	70	5	32	37	83	78	0	164	34	74	30	46	6.76%	62	1412	20.18	3	3	6	19	104	0	1	1	3	161	2	1	0.00%	0	0	0	0.52	0	0	0	0	0	0	2
14	Jiri Sekac	MANITOBA Moose (WPG)	LW	70	14	22	36	20	18	0	54	48	175	48	107	8.00%	17	714	10.21	0	0	0	0	2	0	0	0	0	4	2	0	62.22%	45	0	0	1.01	0	0	0	0	0	0	0
15	Sebastian Collberg	MANITOBA Moose (WPG)	RW	60	9	14	23	12	0	0	10	23	82	19	58	10.98%	8	597	9.96	0	0	0	0	1	0	0	0	0	0	0	0	48.28%	29	0	0	0.77	0	0	0	0	0	1	0
16	Jan Kostalek	MANITOBA Moose (WPG)	D	33	0	22	22	61	16	0	46	6	43	13	31	0.00%	26	565	17.13	0	0	0	4	16	0	0	0	0	38	0	0	0.00%	0	0	0	0.78	0	0	0	0	0	0	0
17	Ryan Poehling	MANITOBA Moose (WPG)	C	19	11	10	21	20	6	0	12	27	92	31	59	11.96%	8	345	18.19	0	3	3	7	34	0	0	0	6	48	3	0	70.10%	311	0	1	1.21	0	0	0	0	2	1	0
18	Tommy Wingels	WINNIPEG Jets	C/RW	6	4	14	18	18	4	0	22	5	60	16	53	6.67%	0	145	24.26	0	0	0	2	5	0	0	0	7	21	0	0	79.73%	148	0	0	2.47	0	0	0	0	2	2	0
19	Lucas Lessio	MANITOBA Moose (WPG)	LW	70	5	9	14	19	4	0	10	12	41	16	24	12.20%	5	217	3.11	0	0	0	1	19	0	0	0	1	31	1	0	40.00%	20	0	0	1.29	0	1	0	0	0	1	0
20	Sean Kuraly	WINNIPEG Jets	C	5	5	6	11	6	4	0	9	9	33	8	24	15.15%	0	91	18.24	0	1	1	0	2	0	0	0	0	5	0	0	65.12%	86	0	0	2.41	0	0	0	0	1	1	0
21	Brian Strait	MANITOBA Moose (WPG)	D	18	2	8	10	40	12	0	19	3	13	6	9	15.38%	6	297	16.53	0	0	0	0	2	0	0	0	0	22	0	0	0.00%	0	0	0	0.67	0	0	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				1127	368	645	1013	996	597	25	1382	967	3289	905	2288	11.19%	477	17401	15.44	33	57	90	277	1176	5	8	13	56	1526	40	9	64.61%	4340	1	18	1.16	8	17	3	1	40	42	40

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Chad Johnson	MANITOBA Moose (WPG)	70	44	23	3	0.911	2.11	4162	10	14	146	1647	5	2	0.750	20	70	0	5	1	2
2	Jonas Gustavsson	MANITOBA Moose (WPG)	2	0	0	0	0.977	0.91	66	0	0	1	44	0	0	0.000	0	0	70	0	0	0
Stats d'équipe Total ou en Moyenne			72	44	23	3	0.913	2.09	4228	10	14	147	1691	5	2	0.750	20	70	70	5	1	2

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Andy Andreoff	MANITOBA Moose (WPG)	C/LW	28	1991-05-17	No	92 Kg	185 CM	No	No	No	1	Sans Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Brandon Manning	MANITOBA Moose (WPG)	D	29	1990-06-04	No	93 Kg	185 CM	No	No	No	4	Sans Restriction	Pro & Farm	2,250,000$	0$	0$	No	Lien
Brian Strait	MANITOBA Moose (WPG)	D	31	1988-01-04	No	94 Kg	185 CM	No	No	No	1	Sans Restriction	Pro & Farm	650,000$	0$	0$	No	Lien
Cal O'Reilly	MANITOBA Moose (WPG)	C	32	1986-09-30	No	85 Kg	183 CM	No	No	No	4	Sans Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Chad Johnson	MANITOBA Moose (WPG)	G	33	1986-06-10	No	90 Kg	191 CM	No	No	No	4	Sans Restriction	Pro & Farm	1,500,000$	0$	0$	No	Lien
Gustav Olofsson	MANITOBA Moose (WPG)	D	24	1994-12-01	No	89 Kg	191 CM	No	No	No	6	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Jan Kostalek	MANITOBA Moose (WPG)	D	24	1995-02-17	No	89 Kg	185 CM	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Jiri Sekac	MANITOBA Moose (WPG)	LW	27	1992-06-10	No	84 Kg	185 CM	No	No	No	2	Avec Restriction	Pro & Farm	1,000,000$	0$	0$	No
Jonas Gustavsson	MANITOBA Moose (WPG)	G	34	1984-10-24	No	91 Kg	193 CM	No	No	No	5	Sans Restriction	Pro & Farm	750,000$	0$	0$	No
Justin Falk	MANITOBA Moose (WPG)	D	30	1988-10-11	No	101 Kg	196 CM	No	No	No	3	Sans Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Liam O'Brien	MANITOBA Moose (WPG)	LW	25	1994-07-29	No	98 Kg	185 CM	No	No	No	1	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Louis-Marc Aubry	MANITOBA Moose (WPG)	C	27	1991-11-11	No	99 Kg	193 CM	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Lucas Lessio	MANITOBA Moose (WPG)	LW	26	1993-01-23	No	96 Kg	185 CM	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No
Mark McNeill	MANITOBA Moose (WPG)	C/RW	26	1993-02-22	No	97 Kg	188 CM	No	No	No	5	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Marko Dano	MANITOBA Moose (WPG)	C/LW	24	1994-11-30	No	96 Kg	180 CM	No	No	No	4	Avec Restriction	Pro & Farm	950,000$	0$	0$	No	Lien
Riley Nash	MANITOBA Moose (WPG)	C/RW	30	1989-05-09	No	86 Kg	185 CM	No	No	No	1	Sans Restriction	Pro & Farm	900,000$	0$	0$	No	Lien
Rocco Grimaldi	MANITOBA Moose (WPG)	C/RW	26	1993-02-08	No	82 Kg	168 CM	No	No	No	2	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Ryan Poehling	MANITOBA Moose (WPG)	C	20	1999-01-03	Yes	83 Kg	188 CM	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Scott Kosmachuk	MANITOBA Moose (WPG)	RW	25	1994-01-24	No	84 Kg	180 CM	No	No	No	4	Avec Restriction	Pro & Farm	750,000$	0$	0$	No	Lien
Sebastian Collberg	MANITOBA Moose (WPG)	RW	25	1994-02-23	Yes	89 Kg	180 CM	No	No	No	6	Avec Restriction	Pro & Farm	925,000$	0$	0$	No
Zach Trotman	MANITOBA Moose (WPG)	D	29	1990-08-26	No	99 Kg	191 CM	No	No	No	4	Sans Restriction	Pro & Farm	750,000$	0$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
21	27.38	91 Kg	185 CM	3.48	889,286$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Andy Andreoff	Riley Nash		31	1	2	2
2	Marko Dano		Mark McNeill	26	1	2	2
3	Liam O'Brien		Scott Kosmachuk	23	1	2	2
4	Jiri Sekac	Louis-Marc Aubry	Sebastian Collberg	20	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Gustav Olofsson	31	1	2	2
2	Justin Falk	Zach Trotman	26	1	2	2
3			23	1	2	2
4	Gustav Olofsson	Justin Falk	20	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Andy Andreoff	Riley Nash		55	1	2	2
2	Marko Dano		Mark McNeill	45	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Gustav Olofsson	55	1	2	2
2	Justin Falk	Zach Trotman	45	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Riley Nash	Andy Andreoff	55	1	2	2
2			45	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Gustav Olofsson	55	1	2	2
2	Justin Falk	Zach Trotman	45	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Riley Nash	55	1	2	2		Gustav Olofsson	55	1	2	2
2	Andy Andreoff	45	1	2	2	Justin Falk	Zach Trotman	45	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Riley Nash	Andy Andreoff	55	1	2	2
2			45	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Gustav Olofsson	55	1	2	2
2	Justin Falk	Zach Trotman	45	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Andy Andreoff	Riley Nash			Gustav Olofsson

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Andy Andreoff	Riley Nash			Gustav Olofsson

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Lucas Lessio, , Liam O'Brien	Lucas Lessio,	Liam O'Brien

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Zach Trotman,		Zach Trotman,

Tirs de Pénalité
Riley Nash, Andy Andreoff, , , Marko Dano

Gardien
#1 : Chad Johnson, #2 : Jonas Gustavsson

Lignes d'Attaque Perso. en Prol.
Riley Nash, Andy Andreoff, , , Marko Dano, , , Mark McNeill, Liam O'Brien, Jiri Sekac, Scott Kosmachuk

Lignes de Défense Perso. en Prol.
, Gustav Olofsson, Justin Falk, Zach Trotman,

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	BELLEVILLE Senators	3	3	0	0	0	0	0	0	14	5	9	1	1	0	0	0	0	0	0	6	3	3	2	2	0	0	0	0	0	0	8	2	6	6	1.000	14	24	38	0	0	189	104	68	10	183	1037	1057	1144	45	65	20	14	109	1	1	100.00%	7	0	100.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
2	BRIDGEPORT Sound Tigers	2	1	0	0	0	0	0	1	7	5	2	1	0	0	0	0	0	0	1	3	4	-1	1	1	0	0	0	0	0	0	4	1	3	3	0.750	7	13	20	0	0	189	104	68	10	56	1037	1057	1144	45	62	21	20	34	7	0	0.00%	7	0	100.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
3	BROOKLYN Wolfpack	2	2	0	0	0	0	0	0	22	0	22	1	1	0	0	0	0	0	0	10	0	10	1	1	0	0	0	0	0	0	12	0	12	4	1.000	22	42	64	0	2	189	104	68	10	150	1037	1057	1144	45	6	0	6	34	0	0	0.00%	3	0	100.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
4	CHICAGO Wolves	2	2	0	0	0	0	0	0	10	4	6	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	5	2	3	4	1.000	10	16	26	0	0	189	104	68	10	68	1037	1057	1144	45	78	20	35	49	6	0	0.00%	14	1	92.86%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
5	CLEVELAND Monsters	2	2	0	0	0	0	0	0	21	1	20	1	1	0	0	0	0	0	0	10	0	10	1	1	0	0	0	0	0	0	11	1	10	4	1.000	21	38	59	0	1	189	104	68	10	154	1037	1057	1144	45	17	5	4	47	1	1	100.00%	2	0	100.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
6	COLORADO Eagles	2	0	2	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	2	4	6	0	0	189	104	68	10	50	1037	1057	1144	45	52	13	16	43	10	2	20.00%	8	1	87.50%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
7	CORNWALL Aces	3	3	0	0	0	0	0	0	34	2	32	1	1	0	0	0	0	0	0	13	1	12	2	2	0	0	0	0	0	0	21	1	20	6	1.000	34	62	96	0	1	189	104	68	10	283	1037	1057	1144	45	40	4	12	50	2	1	50.00%	6	0	100.00%	1	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
8	HERSEY Bears	2	0	2	0	0	0	0	0	1	7	-6	1	0	1	0	0	0	0	0	0	4	-4	1	0	1	0	0	0	0	0	1	3	-2	0	0.000	1	2	3	0	0	189	104	68	10	74	1037	1057	1144	45	50	17	26	34	6	0	0.00%	11	2	81.82%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
9	HOLLYWOOD Oscar	4	4	0	0	0	0	0	0	39	3	36	2	2	0	0	0	0	0	0	21	1	20	2	2	0	0	0	0	0	0	18	2	16	8	1.000	39	67	106	0	2	189	104	68	10	373	1037	1057	1144	45	30	9	14	59	0	0	0.00%	6	0	100.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
10	IOWA Wild	4	1	1	0	1	0	1	0	18	8	10	2	0	0	0	1	0	1	0	6	4	2	2	1	1	0	0	0	0	0	12	4	8	6	0.750	18	30	48	0	0	189	104	68	10	161	1037	1057	1144	45	97	39	42	91	10	4	40.00%	19	2	89.47%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
11	LAVAL Rockets	3	0	3	0	0	0	0	0	8	14	-6	2	0	2	0	0	0	0	0	6	10	-4	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	8	14	22	0	0	189	104	68	10	77	1037	1057	1144	45	122	30	26	65	19	4	21.05%	12	2	83.33%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
12	LEHIGH VALLEY Phantoms	4	1	3	0	0	0	0	0	8	13	-5	2	1	1	0	0	0	0	0	5	6	-1	2	0	2	0	0	0	0	0	3	7	-4	2	0.250	8	14	22	1	0	189	104	68	10	90	1037	1057	1144	45	156	37	38	77	10	0	0.00%	16	3	81.25%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
13	MILWAUKEE Admirals	2	1	1	0	0	0	0	0	6	7	-1	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	3	5	-2	2	0.500	6	11	17	0	0	189	104	68	10	45	1037	1057	1144	45	58	14	24	29	8	2	25.00%	11	2	81.82%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
14	MONT-LAURIER Sommet	2	1	0	0	0	0	1	0	11	5	6	2	1	0	0	0	0	1	0	11	5	6	0	0	0	0	0	0	0	0	0	0	0	4	1.000	11	17	28	0	0	189	104	68	10	72	1037	1057	1144	45	63	14	35	42	9	2	22.22%	14	1	92.86%	1	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
15	PROVIDENCE Bruins	2	0	2	0	0	0	0	0	2	9	-7	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	0	5	-5	0	0.000	2	4	6	0	0	189	104	68	10	49	1037	1057	1144	45	59	26	18	28	7	1	14.29%	6	2	66.67%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
16	PV Sharapovas	3	1	1	0	0	1	0	0	5	11	-6	2	1	1	0	0	0	0	0	2	7	-5	1	0	0	0	0	1	0	0	3	4	-1	3	0.500	5	8	13	0	0	189	104	68	10	67	1037	1057	1144	45	107	30	39	60	15	3	20.00%	13	1	92.31%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
17	ROCKFORD IceHogs	4	1	1	0	1	0	1	0	11	9	2	2	1	1	0	0	0	0	0	4	4	0	2	0	0	0	1	0	1	0	7	5	2	6	0.750	11	18	29	0	0	189	104	68	10	95	1037	1057	1144	45	101	36	40	65	15	4	26.67%	13	1	92.31%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
18	SAN DIEGO Gulls	2	2	0	0	0	0	0	0	15	0	15	1	1	0	0	0	0	0	0	8	0	8	1	1	0	0	0	0	0	0	7	0	7	4	1.000	15	24	39	0	2	189	104	68	10	172	1037	1057	1144	45	10	2	0	61	0	0	0.00%	0	0	0.00%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
19	STOCKTON Flames	4	2	2	0	0	0	0	0	23	9	14	2	1	1	0	0	0	0	0	13	4	9	2	1	1	0	0	0	0	0	10	5	5	4	0.500	23	44	67	0	1	189	104	68	10	188	1037	1057	1144	45	64	25	28	100	7	1	14.29%	14	4	71.43%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
20	SYRACUSE Crunch	3	1	1	0	0	0	1	0	17	7	10	2	1	1	0	0	0	0	0	14	5	9	1	0	0	0	0	0	1	0	3	2	1	4	0.667	17	29	46	0	1	189	104	68	10	167	1037	1057	1144	45	63	21	18	38	7	1	14.29%	8	3	62.50%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
21	TORONTO Marlies	3	3	0	0	0	0	0	0	23	3	20	1	1	0	0	0	0	0	0	7	1	6	2	2	0	0	0	0	0	0	16	2	14	6	1.000	23	43	66	0	1	189	104	68	10	157	1037	1057	1144	45	72	16	30	75	4	2	50.00%	13	1	92.31%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
22	TUSCON Roadrunners	2	0	2	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	2	3	5	1	0	189	104	68	10	58	1037	1057	1144	45	70	25	24	39	6	0	0.00%	12	1	91.67%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
	Total	70	38	23	0	2	2	4	1	367	150	217	36	20	12	0	1	0	2	1	188	80	108	34	18	11	0	1	2	2	0	179	70	109	91	0.650	367	647	1014	2	14	189	104	68	10	3265	1037	1057	1144	45	1693	490	625	1436	173	33	19.08%	264	33	87.50%	5	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
24	UTICA Comets	2	2	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	4	1	3	4	1.000	7	13	20	0	0	189	104	68	10	48	1037	1057	1144	45	75	24	26	41	6	1	16.67%	12	2	83.33%	0	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
25	VICTORIAVILLE Tigres	4	1	2	0	0	1	0	0	14	13	1	2	1	1	0	0	0	0	0	8	5	3	2	0	1	0	0	1	0	0	6	8	-2	3	0.375	14	22	36	0	0	189	104	68	10	98	1037	1057	1144	45	146	37	66	106	15	3	20.00%	25	4	84.00%	1	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
26	WILKIES-BARRIE Penguins	4	4	0	0	0	0	0	0	47	1	46	2	2	0	0	0	0	0	0	25	0	25	2	2	0	0	0	0	0	0	22	1	21	8	1.000	47	85	132	0	3	189	104	68	10	330	1037	1057	1144	45	30	5	24	60	2	0	0.00%	12	0	100.00%	2	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
	_Since Last GM Reset	70	38	23	0	2	2	4	1	367	150	217	36	20	12	0	1	0	2	1	188	80	108	34	18	11	0	1	2	2	0	179	70	109	91	0.650	367	647	1014	2	14	189	104	68	10	3265	1037	1057	1144	45	1693	490	625	1436	173	33	19.08%	264	33	87.50%	5	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
	_Vs Conference	41	25	10	0	1	2	3	0	253	80	173	21	13	5	0	1	0	2	0	131	42	89	20	12	5	0	0	2	1	0	122	38	84	60	0.732	253	445	698	1	9	189	104	68	10	2169	1037	1057	1144	45	933	257	360	867	82	18	21.95%	153	19	87.58%	5	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
	_Vs Division	20	10	8	0	1	1	2	0	103	51	52	10	6	3	0	1	0	2	0	50	31	19	10	4	5	0	0	1	0	0	53	20	33	27	0.675	103	184	287	0	3	189	104	68	10	983	1037	1057	1144	45	528	147	157	425	55	13	23.64%	65	9	86.15%	1	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405

			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
70	91	W2	367	647	1014	3265	1693	490	625	1436	2	14

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
70	38	23	2	2	4	1	367	150

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	20	12	1	0	2	1	188	80

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
34	18	11	1	2	2	0	179	70

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
6	4	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
173	33	19.08%	264	33	87.50%	5

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
1037	1057	1144	45	189	104	68	10

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%

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
2088	1630	1390	394	752	405

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	SO	RI	Lien
1 - 2019-07-30	4	MANITOBA Moose	8	STOCKTON Flames	1	W				Sommaire du Match
2 - 2019-07-31	17	MONT-LAURIER Sommet	4	MANITOBA Moose	9	W				Sommaire du Match
3 - 2019-08-01	39	SYRACUSE Crunch	0	MANITOBA Moose	12	W				Sommaire du Match
4 - 2019-08-02	49	MANITOBA Moose	11	WILKIES-BARRIE Penguins	0	W				Sommaire du Match
6 - 2019-08-04	60	MANITOBA Moose	10	TORONTO Marlies	2	W				Sommaire du Match
7 - 2019-08-05	71	MANITOBA Moose	12	HOLLYWOOD Oscar	2	W				Sommaire du Match
8 - 2019-08-06	78	STOCKTON Flames	0	MANITOBA Moose	12	W				Sommaire du Match
10 - 2019-08-08	93	ROCKFORD IceHogs	2	MANITOBA Moose	0	L				Sommaire du Match
11 - 2019-08-09	108	TORONTO Marlies	1	MANITOBA Moose	7	W				Sommaire du Match
12 - 2019-08-10	122	MANITOBA Moose	10	IOWA Wild	1	W				Sommaire du Match
14 - 2019-08-12	141	MANITOBA Moose	4	BELLEVILLE Senators	1	W				Sommaire du Match
15 - 2019-08-13	146	MANITOBA Moose	13	CORNWALL Aces	0	W				Sommaire du Match
16 - 2019-08-14	154	VICTORIAVILLE Tigres	1	MANITOBA Moose	7	W			R3	Sommaire du Match
18 - 2019-08-16	178	WILKIES-BARRIE Penguins	0	MANITOBA Moose	12	W				Sommaire du Match
20 - 2019-08-18	195	MANITOBA Moose	3	ROCKFORD IceHogs	2	W	X			Sommaire du Match
21 - 2019-08-19	201	HOLLYWOOD Oscar	0	MANITOBA Moose	8	W				Sommaire du Match
22 - 2019-08-20	212	MANITOBA Moose	1	HERSEY Bears	3	L				Sommaire du Match
24 - 2019-08-22	229	MANITOBA Moose	4	BELLEVILLE Senators	1	W				Sommaire du Match
25 - 2019-08-23	237	WILKIES-BARRIE Penguins	0	MANITOBA Moose	13	W				Sommaire du Match
26 - 2019-08-24	250	COLORADO Eagles	2	MANITOBA Moose	1	L				Sommaire du Match
27 - 2019-08-25	261	MANITOBA Moose	11	WILKIES-BARRIE Penguins	1	W				Sommaire du Match
28 - 2019-08-26	278	STOCKTON Flames	4	MANITOBA Moose	1	L				Sommaire du Match
29 - 2019-08-27	291	CLEVELAND Monsters	0	MANITOBA Moose	10	W				Sommaire du Match
30 - 2019-08-28	307	MANITOBA Moose	4	BRIDGEPORT Sound Tigers	1	W				Sommaire du Match
31 - 2019-08-29	320	MONT-LAURIER Sommet	1	MANITOBA Moose	2	W	X	X		Sommaire du Match
32 - 2019-08-30	333	MANITOBA Moose	6	HOLLYWOOD Oscar	0	W				Sommaire du Match
34 - 2019-09-01	346	MANITOBA Moose	3	MILWAUKEE Admirals	5	L				Sommaire du Match
35 - 2019-09-02	352	IOWA Wild	1	MANITOBA Moose	2	W	X			Sommaire du Match
36 - 2019-09-03	369	MANITOBA Moose	1	COLORADO Eagles	3	L				Sommaire du Match
37 - 2019-09-04	384	MILWAUKEE Admirals	2	MANITOBA Moose	3	W				Sommaire du Match
39 - 2019-09-06	399	HOLLYWOOD Oscar	1	MANITOBA Moose	13	W				Sommaire du Match
40 - 2019-09-07	409	MANITOBA Moose	12	BROOKLYN Wolfpack	0	W				Sommaire du Match
42 - 2019-09-09	419	MANITOBA Moose	0	PROVIDENCE Bruins	5	L				Sommaire du Match
43 - 2019-09-10	434	MANITOBA Moose	1	LEHIGH VALLEY Phantoms	3	L				Sommaire du Match
44 - 2019-09-11	440	SAN DIEGO Gulls	0	MANITOBA Moose	8	W				Sommaire du Match
46 - 2019-09-13	462	MANITOBA Moose	11	CLEVELAND Monsters	1	W				Sommaire du Match
47 - 2019-09-14	469	PV Sharapovas	1	MANITOBA Moose	2	W				Sommaire du Match
48 - 2019-09-15	487	MANITOBA Moose	2	IOWA Wild	3	L				Sommaire du Match
49 - 2019-09-16	495	SYRACUSE Crunch	5	MANITOBA Moose	2	L				Sommaire du Match
50 - 2019-09-17	514	BROOKLYN Wolfpack	0	MANITOBA Moose	10	W				Sommaire du Match
51 - 2019-09-18	526	MANITOBA Moose	2	STOCKTON Flames	4	L				Sommaire du Match
53 - 2019-09-20	536	IOWA Wild	3	MANITOBA Moose	4	W	X	X		Sommaire du Match
54 - 2019-09-21	551	MANITOBA Moose	0	TUSCON Roadrunners	2	L				Sommaire du Match
55 - 2019-09-22	563	MANITOBA Moose	2	LAVAL Rockets	4	L				Sommaire du Match
57 - 2019-09-24	568	UTICA Comets	2	MANITOBA Moose	3	W				Sommaire du Match
59 - 2019-09-26	591	LEHIGH VALLEY Phantoms	2	MANITOBA Moose	3	W				Sommaire du Match
61 - 2019-09-28	608	MANITOBA Moose	8	CORNWALL Aces	1	W				Sommaire du Match
62 - 2019-09-29	613	VICTORIAVILLE Tigres	4	MANITOBA Moose	1	L			R3	Sommaire du Match
64 - 2019-10-01	626	MANITOBA Moose	3	SYRACUSE Crunch	2	W	X	X		Sommaire du Match
66 - 2019-10-03	639	MANITOBA Moose	4	UTICA Comets	1	W				Sommaire du Match
67 - 2019-10-04	649	BRIDGEPORT Sound Tigers	4	MANITOBA Moose	3	L	X	X		Sommaire du Match
68 - 2019-10-05	666	HERSEY Bears	4	MANITOBA Moose	0	L				Sommaire du Match
70 - 2019-10-07	677	MANITOBA Moose	4	ROCKFORD IceHogs	3	W	X	X		Sommaire du Match
72 - 2019-10-09	694	ROCKFORD IceHogs	2	MANITOBA Moose	4	W				Sommaire du Match
73 - 2019-10-10	708	MANITOBA Moose	2	LEHIGH VALLEY Phantoms	4	L				Sommaire du Match
74 - 2019-10-11	717	LAVAL Rockets	5	MANITOBA Moose	4	L				Sommaire du Match
75 - 2019-10-12	731	MANITOBA Moose	3	VICTORIAVILLE Tigres	4	L			R3	Sommaire du Match
77 - 2019-10-14	745	PV Sharapovas	6	MANITOBA Moose	0	L				Sommaire du Match
78 - 2019-10-15	755	MANITOBA Moose	3	PV Sharapovas	4	L	X			Sommaire du Match
79 - 2019-10-16	766	MANITOBA Moose	3	VICTORIAVILLE Tigres	4	L	X		R3	Sommaire du Match
80 - 2019-10-17	776	PROVIDENCE Bruins	4	MANITOBA Moose	2	L				Sommaire du Match
82 - 2019-10-19	798	LAVAL Rockets	5	MANITOBA Moose	2	L				Sommaire du Match
84 - 2019-10-21	817	MANITOBA Moose	5	CHICAGO Wolves	2	W				Sommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
85 - 2019-10-22	825	MANITOBA Moose	7	SAN DIEGO Gulls	0	W				Sommaire du Match
86 - 2019-10-23	836	CHICAGO Wolves	2	MANITOBA Moose	5	W				Sommaire du Match
87 - 2019-10-24	850	LEHIGH VALLEY Phantoms	4	MANITOBA Moose	2	L				Sommaire du Match
89 - 2019-10-26	867	BELLEVILLE Senators	3	MANITOBA Moose	6	W				Sommaire du Match
90 - 2019-10-27	882	TUSCON Roadrunners	4	MANITOBA Moose	2	L				Sommaire du Match
92 - 2019-10-29	896	MANITOBA Moose	6	TORONTO Marlies	0	W				Sommaire du Match
93 - 2019-10-30	911	CORNWALL Aces	1	MANITOBA Moose	13	W				Sommaire du Match
94 - 2019-10-31	912	MANITOBA Moose	-	STOCKTON Flames	-
95 - 2019-11-01	926	MANITOBA Moose	-	MONT-LAURIER Sommet	-
98 - 2019-11-04	950	BELLEVILLE Senators	-	MANITOBA Moose	-
100 - 2019-11-06	964	TORONTO Marlies	-	MANITOBA Moose	-
101 - 2019-11-07	971	MANITOBA Moose	-	MONT-LAURIER Sommet	-
103 - 2019-11-09	990	MANITOBA Moose	-	PV Sharapovas	-
104 - 2019-11-10	996	MANITOBA Moose	-	SYRACUSE Crunch	-
106 - 2019-11-12	1010	CORNWALL Aces	-	MANITOBA Moose	-

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
3	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
1,653,820$	1,867,500$	1,867,500$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	1,582,501$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	14	18,220$	255,080$

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
32	70	38	23	0	2	2	4	1	367	150	217	36	20	12	0	1	0	2	1	188	80	108	34	18	11	0	1	2	2	0	179	70	109	91	367	647	1014	2	14	189	104	68	10	3265	1037	1057	1144	45	1693	490	625	1436	173	33	19.08%	264	33	87.50%	5	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405
Total Saison Régulière	70	38	23	0	2	2	4	1	367	150	217	36	20	12	0	1	0	2	1	188	80	108	34	18	11	0	1	2	2	0	179	70	109	91	367	647	1014	2	14	189	104	68	10	3265	1037	1057	1144	45	1693	490	625	1436	173	33	19.08%	264	33	87.50%	5	1293	2197	58.85%	944	1881	50.19%	675	1111	60.76%	2088	1630	1390	394	752	405