Profi League - Monsters

Avalanche
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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	Paul Carey	X	X	X		100.00	82	70	78	78	54	66	68	64	84	38	39	62	56	46	47	0	53	59	0
2	Josh Leivo (R) (A)		X	X		100.00	58	42	66	70	50	57	64	63	60	37	48	57	50	46	46	0	50	54	0
3	Brody Sutter	X				100.00	65	78	63	67	59	66	64	56	68	31	35	60	50	45	45	0	56	54	0
4	Mike Halmo		X	X		100.00	55	72	57	64	55	65	62	60	71	32	39	56	56	45	45	0	53	53	0
5	Turner Elson	X	X			100.00	58	68	60	59	52	66	63	58	69	33	36	56	50	44	44	0	53	52	0
6	Michael Schumacher		X			100.00	64	78	63	61	59	66	65	54	65	27	33	57	50	44	44	0	47	52	0
7	Andrew Crescenzi	X				100.00	60	75	63	64	57	65	63	56	69	32	31	58	50	44	44	0	48	52	0
8	Ryan Haggerty (R)			X		100.00	74	73	75	58	56	64	63	55	64	28	36	55	50	44	44	0	53	52	0
9	Riley Brace		X	X		100.00	67	67	72	62	52	47	55	56	68	35	31	60	50	44	44	0	53	51	0
10	Phil Lane			X		100.00	60	75	62	63	57	63	62	53	64	27	32	56	50	44	44	0	53	51	0
11	Garrett Mitchell			X		100.00	58	68	60	61	52	66	63	57	68	32	34	56	50	44	44	0	53	51	0
12	Mark Barberio (C)				X	100.00	64	42	88	76	69	69	73	72	25	44	40	71	50	69	60	0	53	63	0
13	T.J. Brennan (A)				X	100.00	73	78	72	67	74	80	77	69	25	45	41	66	57	55	55	0	53	63	0
14	Chris Butler				X	100.00	56	72	63	75	59	64	67	63	25	35	30	57	50	68	69	0	56	56	0
15	Gus Young				X	100.00	56	72	63	66	59	68	70	57	25	29	29	56	50	45	45	0	53	52	0
16	Kirill Gotovets (R)				X	100.00	55	64	61	65	55	60	65	57	25	30	27	52	50	44	44	0	53	50	0
17	Jesper Pettersson (R)				X	100.00	55	65	61	63	56	61	66	53	25	24	28	51	50	44	44	0	48	49	0
Rayé
1	Matthew Ford			X		100.00	60	75	63	62	57	69	66	62	77	36	42	58	59	44	44	0	47	55	0
2	Darren Kramer		X			100.00	57	77	58	62	58	66	65	54	65	28	33	53	50	44	44	0	46	51	0
3	Ryan Olsen (R)	X				100.00	58	69	60	61	53	66	64	54	64	29	31	54	50	44	44	0	46	50	0
4	Conor Allen				X	100.00	59	77	66	70	62	69	70	57	25	29	27	58	50	46	46	0	41	54	0
5	Joel Chouinard				X	86.43	60	69	67	62	57	55	57	64	25	34	31	61	50	48	48	0	41	52	0

	MOYENNE D'ÉQUIPE					99.36	62	69	66	65	57	64	65	59	53	33	34	58	51	47	47	0	50	53

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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	Philipp Grubauer	100.00	75	78	68	84	79	73	74	78	76	70	55	69	64	0	50	72	0
2	Sam Brittain (R)	97.00	64	71	82	72	65	70	64	67	63	63	47	55	55	0	50	64	0
Rayé
1	Trevor Cann	100.00	55	57	64	66	67	62	60	62	62	61	59	47	61	0	46	61	0
2	Kent Patterson	100.00	57	50	57	76	70	62	57	57	57	62	66	51	49	0	46	59	0

	MOYENNE D'ÉQUIPE	99.25	63	64	68	75	70	67	64	66	65	64	57	56	57	0	48	64

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Joe Sacco	59	50	41	50	45	45	46	USA	47	5	100,000$

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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	SHT	OSB	OSM	SHT%	SB	MP	PPP	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Mark Barberio	Monsters (COL)		D	4	7	6	13	14	0	0	3	19	12	14	36.84%	6	26.:.42	0	2	0	2	14	0	0	0.00%	0	11	7	0	1	2.43	0	0
2	Paul Carey	Monsters (COL)		C/LW/RW	4	2	8	10	10	0	0	7	16	2	8	12.50%	8	23.:.37	0	0	2	2	12	0	0	60.00%	110	11	2	0	0	2.12	0	0
3	T.J. Brennan	Monsters (COL)		D	4	3	6	9	11	17	15	12	14	2	7	21.43%	9	24.:.16	0	0	2	2	13	0	1	0.00%	0	3	7	0	0	1.85	0	0
4	Josh Leivo	Monsters (COL)		LW/RW	4	4	1	5	6	0	0	3	12	7	7	33.33%	1	18.:.47	0	1	0	1	5	3	0	37.50%	8	20	4	0	0	1.33	0	0
5	Chris Butler	Monsters (COL)		D	4	0	2	2	-3	7	5	2	5	4	5	0.00%	4	20.:.02	0	0	0	0	5	0	0	0.00%	0	3	1	0	0	0.50	0	0
6	Mike Halmo	Monsters (COL)		LW/RW	4	0	2	2	0	0	0	4	10	5	11	0.00%	1	18.:.13	0	0	0	0	0	0	0	50.00%	2	15	1	0	0	0.55	0	0
7	Gus Young	Monsters (COL)		D	4	0	2	2	0	2	0	5	3	1	1	0.00%	2	19.:.23	0	0	0	0	1	0	0	0.00%	0	0	3	0	0	0.52	0	0
8	Brody Sutter	Monsters (COL)		C	4	1	1	2	1	39	25	7	11	3	2	9.09%	2	16.:.12	0	0	0	0	3	0	0	51.16%	43	6	3	0	0	0.62	0	0
9	Turner Elson	Monsters (COL)		C/LW	4	0	1	1	-1	0	0	8	7	4	4	0.00%	1	12.:.23	0	0	0	0	3	0	0	55.00%	20	9	1	0	0	0.40	0	0
10	Kirill Gotovets	Monsters (COL)		D	4	0	1	1	2	4	0	2	1	0	2	0.00%	6	16.:.05	0	0	0	0	2	0	0	0.00%	0	0	4	0	0	0.31	0	0
11	Matthew Ford	Monsters (COL)		RW	4	1	0	1	5	45	35	2	2	1	5	50.00%	3	17.:.39	0	0	0	0	14	0	1	100.00%	1	2	3	0	0	0.28	0	0
12	Andrew Crescenzi	Monsters (COL)		C	4	0	1	1	1	17	15	8	9	4	5	0.00%	0	14.:.14	0	0	0	0	0	0	0	70.00%	30	1	1	0	0	0.35	0	0
13	Garrett Mitchell	Monsters (COL)		RW	4	1	0	1	5	2	0	3	4	2	2	25.00%	1	08.:.22	0	0	0	0	1	0	0	0.00%	2	3	0	0	0	0.60	0	0
14	Riley Brace	Monsters (COL)		LW/RW	4	0	0	0	4	0	0	9	5	5	2	0.00%	1	12.:.43	0	0	0	0	0	0	0	50.00%	4	3	3	0	0	0.00	0	0
15	Michael Schumacher	Monsters (COL)		LW	4	0	0	0	0	42	30	4	0	0	1	0.00%	0	05.:.07	0	0	0	0	0	0	0	0.00%	0	0	0	0	0	0.00	0	0
16	Joel Chouinard	Monsters (COL)		D	1	0	0	0	0	0	0	0	0	0	0	0.00%	2	02.:.45	0	0	0	0	0	0	0	0.00%	0	0	1	0	0	0.00	0	0
17	Jesper Pettersson	Monsters (COL)		D	2	0	0	0	1	2	0	1	0	0	2	0.00%	1	15.:.43	0	0	0	0	1	0	0	0.00%	0	0	1	0	0	0.00	0	0
18	Ryan Haggerty	Monsters (COL)		RW	4	0	0	0	0	0	0	9	10	2	7	0.00%	1	18.:.13	0	0	0	0	0	0	0	33.33%	3	0	0	0	0	0.00	0	0
19	Phil Lane	Monsters (COL)		RW	4	0	0	0	2	0	0	1	1	0	2	0.00%	0	08.:.45	0	0	0	0	0	0	0	0.00%	7	0	2	0	0	0.00	0	0
Stats d'équipe Total ou en Moyenne		71	19	31	50	58	177	125	90	118	129	54	87	14.73%	49	1157	16.30	0	15	112	3	4	7	3	80	3	2	55.65%	230	87	44	0	1	0.86	0	0	6	8	11	2	2	3

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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	SAR	A	PS %	PSA	ST	BG	S1	S2	S3
1	Philipp Grubauer	Monsters (COL)	2	2	0	0	95.5%	1.50	120	0	0	3	66	43	0	0.0%	0	2	2	1	0	0
2	Sam Brittain	Monsters (COL)	2	1	1	0	91.8%	3.00	120	0	0	6	73	50	0	0.0%	0	2	2	0	0	0
Stats d'équipe Total ou en Moyenne	4	3	1	0	0.935	2.25	240	0	0	9	139	93	0	0	0.000	4	4	1	0	0

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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	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Année 2	Salaire Année 3	Salaire Année 4	Salaire Année 5	Salaire Année 6	Salaire Année 7	Salaire Année 8	Salaire Année 9	Salaire Année 10	Link
Andrew Crescenzi	C	24	29.07.1992 3:13:26	No	198 Lbs	6 ft4	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$				Lien
Brody Sutter	C	25	26.09.1991 3:19:47	No	203 Lbs	6 ft5	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Chris Butler	D	29	27.10.1986	No	196 Lbs	6 ft1	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Conor Allen	D	26	01.07.1990	No	210 Lbs	6 ft1	No	No	8	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$			Lien
Darren Kramer	LW	24	19.11.1991 4:02:12	No	210 Lbs	6 ft1	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$				Lien
Garrett Mitchell	RW	24	02.09.1992 13:46:10	No	183 Lbs	6 ft1	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$						Lien
Gus Young	D	25	10.07.1991	No	190 Lbs	6 ft2	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Jesper Pettersson	D	22	16.07.1994	Yes	187 Lbs	5 ft9	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Joel Chouinard (Sur la Masse Salariale)	D	26	08.04.1990	No	187 Lbs	6 ft1	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$						Lien
Josh Leivo	LW/RW	23	26.05.1993 2:00:20	Yes	173 Lbs	6 ft1	No	No	1	Pro & Farm	1,100,000$	0$										Lien
Kent Patterson	G	27	15.09.1989 3:26:58	No	180 Lbs	6 ft1	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$
Kirill Gotovets	D	25	25.06.1991	Yes	175 Lbs	5 ft11	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Lien
Mark Barberio	D	26	23.03.1990	No	199 Lbs	6 ft1	No	No	2	Pro & Farm	1,700,000$	0$	1,700,000$									Lien
Matthew Ford	RW	32	09.10.1984	No	207 Lbs	6 ft1	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$						Lien
Michael Schumacher	LW	23	25.08.1993	No	203 Lbs	6 ft5	No	No	8	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$			Lien
Mike Halmo	LW/RW	25	15.05.1991 14:58:15	No	209 Lbs	5 ft10	No	No	1	Pro & Farm	1,000,000$	0$										Lien
Paul Carey	C/LW/RW	28	24.09.1988 3:28:03	No	190 Lbs	6 ft0	No	No	2	Pro & Farm	600,000$	0$	600,000$									Lien
Phil Lane	RW	24	29.05.1992 5:08:04	No	203 Lbs	6 ft2	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$				Lien
Philipp Grubauer (Contrat à 1 Volet)	G	24	25.11.1991 6:32:38	No	184 Lbs	6 ft1	No	No	2	Pro & Farm	1,500,000$	0$	1,500,000$									Lien
Riley Brace	LW/RW	24	07.03.1992	No	185 Lbs	5 ft11	No	No	8	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$			Lien
Ryan Haggerty	RW	23	04.03.1993	Yes	201 Lbs	6 ft0	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Ryan Olsen	C	22	25.03.1994	Yes	187 Lbs	6 ft1	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Lien
Sam Brittain	G	24	10.05.1992	Yes	229 Lbs	6 ft3	No	No	1	Pro & Farm	1,000,000$	0$										Lien
T.J. Brennan	D	27	03.04.1989	No	216 Lbs	6 ft1	No	No	2	Pro & Farm	1,400,000$	0$	1,400,000$									Lien
Trevor Cann	G	27	30.05.1989	No	180 Lbs	5 ft11	No	No	5	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$
Turner Elson	C/LW	24	13.09.1992	No	185 Lbs	6 ft0	No	No	8	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
26	25.12	195 Lbs	6 ft1	5.3461538461538	461,538$

Attaque à 5 contre 5
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Paul Carey	Josh Leivo		40	1	2	2
2	Brody Sutter	Mike Halmo	Ryan Haggerty	30	1	2	2
3	Andrew Crescenzi	Turner Elson	Riley Brace	20	1	2	2
4	Paul Carey	Michael Schumacher	Garrett Mitchell	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	T.J. Brennan	Mark Barberio	40	1	2	2
2	Chris Butler	Gus Young	30	1	2	2
3	Kirill Gotovets	Jesper Pettersson	20	1	2	2
4	T.J. Brennan	Mark Barberio	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Centre	Ailier Gauche	Ailier Droit	% Temps	PHY	DF	OF
1	Paul Carey	Josh Leivo		60	1	2	2
2	Brody Sutter	Mike Halmo	Ryan Haggerty	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	T.J. Brennan	Mark Barberio	60	1	2	2
2	Chris Butler	Gus Young	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Paul Carey		60	1	2	2
2	Josh Leivo	Brody Sutter	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	T.J. Brennan	Mark Barberio	60	1	2	2
2	Chris Butler	Gus Young	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Paul Carey	60	1	2	2	T.J. Brennan	Mark Barberio	60	1	2	2
2		40	1	2	2	Chris Butler	Gus Young	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Paul Carey		60	1	2	2
2	Josh Leivo	Brody Sutter	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	T.J. Brennan	Mark Barberio	60	1	2	2
2	Chris Butler	Gus Young	40	1	2	2

Attaque Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Paul Carey	Josh Leivo		T.J. Brennan	Mark Barberio

Défense Dernière Minute
Centre	Ailier Gauche	Ailier Droit	Défense	Défense
Paul Carey	Josh Leivo		T.J. Brennan	Mark Barberio

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Phil Lane, Andrew Crescenzi, Turner Elson	Phil Lane, Andrew Crescenzi	Turner Elson

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Kirill Gotovets, Jesper Pettersson, Chris Butler	Kirill Gotovets	Jesper Pettersson, Chris Butler

Tirs de Pénalité
Paul Carey, , Josh Leivo, Brody Sutter, Ryan Haggerty

Gardien
#1 : Sam Brittain, #2 : Philipp Grubauer

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

#	VS Équipe	GP	W	L	GF	GA	Diff	P	PCT	G	A	TP	GP1	GP2	GP3	SHF	SH1	SP2	SP3	SHA	SHB	Pim	Hit	PPA	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	Penguins	1	1	0	2	1	1	2	1.000	2	3	5	6	9	4	33	33	53	43	33	11	29	29	4	0.00%	2	0	100.00%	1	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
2	Bruins	1	1	0	11	2	9	2	1.000	11	19	30	6	9	4	38	33	53	43	33	16	76	15	2	0.00%	3	1	66.67%	1	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
3	Americans	1	0	1	1	3	-2	0	0.000	1	1	2	6	9	4	27	33	53	43	36	12	28	23	2	0.00%	4	0	100.00%	1	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
4	Pirates	1	1	0	5	3	2	2	1.000	5	8	13	6	9	4	31	33	53	43	37	10	44	23	3	0.00%	2	1	50.00%	0	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
	Vs Division	1	1	0	5	3	2	2	1.000	5	8	13	6	9	4	31	33	53	43	37	10	44	23	3	0.00%	2	1	50.00%	0	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
	Vs Conference	1	1	0	5	3	2	2	1.000	5	8	13	6	9	4	31	33	53	43	37	10	44	23	3	0.00%	2	1	50.00%	0	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
	Since Last GM Reset	4	3	1	19	9	10	6	0.750	19	31	50	6	9	4	129	33	53	43	139	49	177	90	11	0.00%	11	2	81.82%	3	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32
	Total	4	3	1	19	9	10	6	0.750	19	31	50	6	9	4	129	33	53	43	139	49	177	90	11	0.00%	11	2	81.82%	3	48	84	57.14%	45	85	52.94%	35	61	57.38%	78	46	94	36	66	32

			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
4	6	W1	19	31	50	129	139	49	177	90	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	1	0	0	0	0	19	9

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	13	3

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	6	6

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
3	1	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
11	0	0.00%	11	2	81.82%	3

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
33	53	43	0	6	9	4	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
48	84	57.14%	45	85	52.94%	35	61	57.38%

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
78	46	94	36	66	32

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

Date		Result	Detail
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
Wed, Apr 23	@	Penguins1,Monsters2	RECAP
Thu, Apr 24	@	Bruins2,Monsters11	RECAP
Sun, Apr 27	@	Monsters1,Americans3	RECAP
Mon, Apr 28	@	Monsters5,Pirates3	RECAP

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
0	0 - 0.00%	0$	0$	3000	100

Dépenses
Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
1,030,000$	520,000$	0$

Dépenses Annuelles à Ce Jour	Cap Salarial Par Jour	Cap salarial à ce jour
0$	0$	0$

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	0	0$	0$

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