LHSIR - Wolf Pack

Rangers
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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	Alexander True	X		X		100.00	84	45	94	67	78	55	77	63	65	70	55	56	25	56	56	63	50	0	0
2	Kaapo Kakko (R)			X		100.00	61	41	92	82	72	67	78	74	34	65	68	61	75	52	52	68	50	0	0
3	Rudolfs Balcers		X			100.00	78	43	99	65	61	62	81	73	26	61	58	59	25	49	49	63	50	0	0
4	Johan Larsson	X				100.00	79	44	87	81	70	68	85	63	80	65	59	84	25	67	67	69	50	0	0
5	Jack Hughes (R)	X	X			100.00	59	40	94	82	62	72	75	84	69	68	60	55	48	51	51	65	50	0	0
6	Isac Lundestrom	X				100.00	61	41	99	80	68	66	68	72	76	72	55	64	25	46	46	64	50	0	0
7	Logan Brown	X				100.00	67	44	94	62	85	59	69	72	62	75	56	57	25	46	46	63	50	0	0
8	Sam Lafferty	X	X	X		100.00	84	57	86	67	71	54	80	61	65	62	62	76	25	48	48	67	50	0	0
9	Vitaly Abramov		X	X		100.00	68	61	83	69	61	76	79	65	50	62	64	61	61	44	44	65	50	0	0
10	Gabriel Vilardi (R)	X				100.00	57	41	87	80	76	63	48	68	87	75	75	54	25	44	44	69	50	0	0
11	Vladislav Kamenev	X	X	X		100.00	73	43	92	80	72	52	56	64	62	64	56	61	25	51	51	62	50	0	0
12	Brendan Lemieux		X	X		100.00	93	96	50	83	79	63	78	67	38	65	59	71	75	59	59	67	50	0	0
13	Ethan Bear				X	100.00	71	53	86	85	71	84	79	65	25	57	49	81	25	59	59	65	49	0	0
14	Matt Roy				X	100.00	84	45	95	62	74	75	87	62	25	54	48	75	25	56	56	62	50	0	0
15	Victor Mete				X	100.00	63	41	88	81	65	68	82	60	25	51	49	74	25	60	60	62	50	0	0
16	Adam Boqvist (R)				X	100.00	71	42	94	80	64	69	72	74	25	56	50	60	25	47	47	62	50	0	0
17	Christian Djoos				X	100.00	59	40	99	80	62	77	67	79	25	53	50	70	25	59	61	63	50	0	0
18	Alex Alexeyev (R)				X	100.00	81	77	90	63	77	67	71	51	25	46	41	64	39	44	44	55	50	0	0
Rayé
1	Aleksi Saarela	X				100.00	76	70	91	66	70	76	80	63	79	61	61	66	58	47	48	65	50	0	0
2	Hayden Verbeek	X	X			100.00	72	65	89	54	65	50	52	44	55	38	44	58	42	44	44	50	50	0	0
3	Ryan Poehling (R)	X	X			100.00	79	44	94	77	69	56	67	57	33	54	56	68	25	46	46	62	50	0	0
4	Joachim Blichfeld (R)			X		100.00	73	69	83	66	69	72	75	64	50	59	65	64	62	44	44	65	50	0	0
5	Aleksi Heponiemi (R)	X		X		100.00	66	56	89	61	56	63	67	50	63	50	46	57	44	44	44	53	50	0	0
6	Rem Pitlick (R)	X	X			100.00	74	70	82	65	70	66	68	60	75	53	62	63	59	44	44	62	50	0	0
7	Kody Clark (R)			X		100.00	71	66	83	60	66	59	62	50	50	49	47	59	45	44	44	54	50	0	0
8	Logan Stanley				X	100.00	78	87	56	62	87	68	74	47	25	37	41	62	39	44	44	52	50	0	0

	MOYENNE D'ÉQUIPE					100.00	72	55	88	72	70	66	72	64	50	59	55	65	38	50	50	62	50	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 Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Connor Ingram	100.00	69	64	80	76	70	71	72	77	73	73	30	44	44	70	50	0	0
2	Igor Shesterkin (R)	100.00	69	63	60	71	77	62	88	69	77	69	75	45	45	71	45	0	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	69	64	70	74	74	67	80	73	75	71	53	45	45	71	48	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Steve Ott	70	65	60	67	54	50	89	CAN	39	3	975,000$

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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	PKS	PKM	GW	GT	FO%	FOT	P/20	FW	FT	S1	S2	S3
1	Brendan Lemieux	Wolf Pack (NYR)	LW/RW	13	6	6	12	1	27	5	34	25	29	8	19	20.69%	3	260	20.06	1	2	3	12	72	1	39	0	2	21.43%	14	0.92	0	1	3	1	0
2	Jack Hughes	Wolf Pack (NYR)	C/LW	13	5	5	10	2	12	0	11	28	29	15	21	17.24%	2	270	20.81	1	4	5	11	77	0	9	2	0	43.75%	16	0.74	0	0	2	0	1
3	Logan Brown	Wolf Pack (NYR)	C	13	3	7	10	2	2	0	0	27	16	3	11	18.75%	0	220	16.96	1	3	4	3	69	0	0	0	0	52.28%	197	0.91	0	0	1	1	1
4	Christian Djoos	Wolf Pack (NYR)	D	13	6	4	10	0	2	0	4	13	22	11	10	27.27%	7	287	22.14	5	2	7	19	63	0	38	2	0	0.00%	0	0.70	0	0	1	1	0
5	Kaapo Kakko	Wolf Pack (NYR)	RW	13	4	5	9	2	8	0	9	14	30	8	25	13.33%	4	256	19.69	2	1	3	11	75	0	0	0	0	35.71%	14	0.70	0	0	0	0	2
6	Adam Boqvist	Wolf Pack (NYR)	D	13	0	9	9	5	10	0	40	18	8	3	11	0.00%	10	291	22.39	0	2	2	7	60	0	4	0	0	0.00%	0	0.62	0	0	0	2	0
7	Gabriel Vilardi	Wolf Pack (NYR)	C	13	3	5	8	2	2	0	18	24	22	8	23	13.64%	2	257	19.83	0	2	2	5	73	0	0	2	1	64.16%	279	0.62	0	0	1	0	1
8	Johan Larsson	Wolf Pack (NYR)	C	13	4	3	7	7	6	0	11	31	18	7	6	22.22%	3	197	15.17	0	0	0	0	0	0	51	0	0	63.32%	229	0.71	0	0	1	0	0
9	Vitaly Abramov	Wolf Pack (NYR)	LW/RW	13	1	6	7	1	5	5	1	16	21	4	18	4.76%	3	228	17.61	0	3	3	7	76	0	2	0	0	44.44%	9	0.61	1	0	0	0	0
10	Vladislav Kamenev	Wolf Pack (NYR)	C/LW/RW	13	2	4	6	5	4	0	6	7	12	5	10	16.67%	4	180	13.87	0	2	2	0	10	0	25	0	0	42.86%	14	0.67	0	0	0	0	1
11	Matt Roy	Wolf Pack (NYR)	D	13	2	3	5	1	18	0	25	5	6	4	3	33.33%	8	232	17.85	1	2	3	5	18	0	26	1	0	0.00%	0	0.43	0	0	0	0	1
12	Victor Mete	Wolf Pack (NYR)	D	13	0	5	5	2	10	0	12	14	4	0	5	0.00%	13	213	16.38	0	0	0	1	2	0	47	0	0	0.00%	0	0.47	0	0	0	0	0
13	Rudolfs Balcers	Wolf Pack (NYR)	LW	13	0	4	4	5	2	0	6	10	7	1	10	0.00%	0	144	11.09	0	0	0	0	0	0	0	0	0	20.00%	5	0.56	0	0	0	1	0
14	Alex Alexeyev	Wolf Pack (NYR)	D	13	1	3	4	1	8	0	17	5	13	1	1	7.69%	7	246	18.93	1	0	1	10	75	0	13	1	0	0.00%	0	0.33	0	0	0	0	0
15	Isac Lundestrom	Wolf Pack (NYR)	C	13	0	3	3	-2	0	0	0	14	11	0	4	0.00%	2	138	10.67	0	0	0	0	1	1	33	0	0	48.41%	126	0.43	0	0	0	0	0
16	Sam Lafferty	Wolf Pack (NYR)	C/LW/RW	13	3	0	3	-2	10	0	7	5	18	4	5	16.67%	2	128	9.91	1	0	1	2	1	1	25	1	0	66.67%	9	0.47	0	0	0	1	0
17	Alexander True	Wolf Pack (NYR)	C/RW	13	0	1	1	-2	2	0	11	7	1	4	6	0.00%	1	115	8.92	0	0	0	0	12	0	0	0	0	83.33%	12	0.17	0	0	0	0	0
Stats d'équipe Total ou en Moyenne				221	40	73	113	30	128	10	212	263	267	86	188	14.98%	71	3669	16.61	13	23	36	93	691	3	318	9	3	57.36%	924	0.62	1	1	9	7	7

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Astuces sur les Filtres (Anglais seulement)

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

#	Nom du Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Igor Shesterkin	Wolf Pack (NYR)	13	9	3	1	0.883	2.23	834	0	1	31	266	0	1	0	0.000	0	13	0	0	0	0
Stats d'équipe Total ou en Moyenne			13	9	3	1	0.883	2.23	834	0	1	31	266	0	1	0	0.000	0	13	0	0	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	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 Moyen	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Link
Adam Boqvist	Wolf Pack (NYR)	D	19	2000-08-14	Yes	179 Lbs	5 ft11	No	No	No	3	Pro & Farm	1,744,167$	1,744,167$	0$	0$	No	1,744,167$	1,744,167$
Aleksi Heponiemi	Wolf Pack (NYR)	C/RW	21	1999-01-09	Yes	150 Lbs	5 ft10	No	No	No	3	Pro & Farm	1,775,000$	1,775,000$	0$	0$	No	1,775,000$	1,775,000$
Aleksi Saarela	Wolf Pack (NYR)	C	23	1997-01-07	No	198 Lbs	5 ft11	No	No	No	3	Pro & Farm	1,152,500$	902,500$	0$	0$	No	902,500$	902,500$	Lien
Alex Alexeyev	Wolf Pack (NYR)	D	20	1999-11-15	Yes	201 Lbs	6 ft4	No	No	No	3	Pro & Farm	894,167$	450,000$	0$	0$	No	894,167$	894,167$
Alexander True	Wolf Pack (NYR)	C/RW	22	1997-07-17	No	201 Lbs	6 ft5	No	No	No	3	Pro & Farm	1,050,000$	800,000$	0$	0$	No	800,000$	800,000$	Lien
Brendan Lemieux	Wolf Pack (NYR)	LW/RW	24	1996-03-14	No	210 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,039,167$	1,039,167$	0$	0$	No			Lien
Christian Djoos	Wolf Pack (NYR)	D	25	1994-08-06	No	169 Lbs	6 ft0	No	No	No	1	Pro & Farm	650,000$	650,000$	0$	0$	No			Lien
Connor Ingram	Wolf Pack (NYR)	G	23	1997-03-31	No	204 Lbs	6 ft1	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$		Lien
Ethan Bear	Wolf Pack (NYR)	D	23	1997-06-26	No	198 Lbs	5 ft11	No	No	No	1	Pro & Farm	720,000$	720,000$	0$	0$	No			Lien
Gabriel Vilardi	Wolf Pack (NYR)	C	20	1999-08-15	Yes	201 Lbs	6 ft3	No	No	No	3	Pro & Farm	1,627,000$	1,627,000$	0$	0$	No	1,627,000$	1,627,000$
Hayden Verbeek	Wolf Pack (NYR)	C/LW	22	1997-10-17	No	183 Lbs	5 ft10	No	No	No	3	Pro & Farm	776,666$	776,666$	0$	0$	No	776,666$	776,666$	Lien
Igor Shesterkin	Wolf Pack (NYR)	G	24	1995-12-30	Yes	187 Lbs	6 ft1	No	No	No	2	Pro & Farm	3,775,000$	3,775,000$	0$	0$	No	3,775,000$
Isac Lundestrom	Wolf Pack (NYR)	C	20	1999-11-06	No	185 Lbs	6 ft0	No	No	No	2	Pro & Farm	925,000$	450,000$	0$	0$	No	925,000$		Lien
Jack Hughes	Wolf Pack (NYR)	C/LW	19	2001-05-13	Yes	171 Lbs	5 ft10	No	No	No	3	Pro & Farm	3,775,000$	3,775,000$	0$	0$	No	3,775,000$	3,775,000$
Joachim Blichfeld	Wolf Pack (NYR)	RW	21	1998-07-16	Yes	180 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,290,000$	790,000$	0$	0$	No	790,000$	790,000$	Lien
Johan Larsson	Wolf Pack (NYR)	C	27	1992-07-25	No	198 Lbs	5 ft11	No	No	No	3	Pro & Farm	1,475,000$	1,475,000$	0$	0$	No	1,475,000$	1,475,000$	Lien
Kaapo Kakko	Wolf Pack (NYR)	RW	19	2001-02-13	Yes	190 Lbs	6 ft2	No	No	No	3	Pro & Farm	3,575,000$	3,575,000$	0$	0$	No	3,575,000$	3,575,000$
Kody Clark	Wolf Pack (NYR)	RW	20	1999-10-12	Yes	179 Lbs	6 ft1	No	No	No	3	Pro & Farm	894,167$	894,167$	0$	0$	No	894,167$	894,167$
Logan Brown	Wolf Pack (NYR)	C	22	1998-03-04	No	220 Lbs	6 ft6	No	No	No	2	Pro & Farm	1,573,333$	1,573,333$	0$	0$	No	1,573,333$		Lien
Logan Stanley	Wolf Pack (NYR)	D	22	1998-05-25	No	228 Lbs	6 ft7	No	No	No	2	Pro & Farm	1,075,833$	1,075,833$	0$	0$	No	1,075,833$		Lien
Matt Roy	Wolf Pack (NYR)	D	25	1995-02-28	No	200 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,200,000$	700,000$	0$	0$	No	700,000$	700,000$	Lien
Rem Pitlick	Wolf Pack (NYR)	C/LW	23	1997-04-01	Yes	196 Lbs	5 ft11	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$
Rudolfs Balcers	Wolf Pack (NYR)	LW	23	1997-04-08	No	165 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$		Lien
Ryan Poehling	Wolf Pack (NYR)	C/LW	21	1999-01-02	Yes	183 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,491,667$	1,491,667$	0$	0$	No	1,491,667$	1,491,667$
Sam Lafferty	Wolf Pack (NYR)	C/LW/RW	25	1995-03-06	No	194 Lbs	6 ft1	No	No	No	3	Pro & Farm	975,000$	925,000$	0$	0$	No	925,000$	925,000$	Lien
Victor Mete	Wolf Pack (NYR)	D	22	1998-06-07	No	184 Lbs	5 ft10	No	No	No	1	Pro & Farm	870,000$	870,000$	0$	0$	No			Lien
Vitaly Abramov	Wolf Pack (NYR)	LW/RW	22	1998-05-08	No	172 Lbs	5 ft9	No	No	No	2	Pro & Farm	880,000$	880,000$	0$	0$	No	880,000$		Lien
Vladislav Kamenev	Wolf Pack (NYR)	C/LW/RW	23	1996-08-12	No	194 Lbs	6 ft2	No	No	No	3	Pro & Farm	800,000$	750,000$	0$	0$	No	750,000$	750,000$	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
28	22.14	190 Lbs	6 ft1	2.46	1,384,952$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jack Hughes	Gabriel Vilardi	Kaapo Kakko	35	0	1	4
2	Brendan Lemieux	Logan Brown	Vitaly Abramov	30	0	1	4
3	Rudolfs Balcers	Johan Larsson	Vladislav Kamenev	25	0	2	3
4	Sam Lafferty	Isac Lundestrom	Alexander True	10	0	2	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Adam Boqvist	35	0	2	3
2	Matt Roy	Christian Djoos	30	0	2	3
3	Alex Alexeyev	Victor Mete	25	0	3	2
4		Adam Boqvist	10	0	3	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Jack Hughes	Gabriel Vilardi	Kaapo Kakko	60	0	2	3
2	Brendan Lemieux	Logan Brown	Vitaly Abramov	40	0	2	3

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Adam Boqvist	Christian Djoos	60	0	3	2
2		Alex Alexeyev	40	0	3	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Johan Larsson	Brendan Lemieux	60	0	3	2
2	Isac Lundestrom	Sam Lafferty	40	0	3	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Victor Mete	60	0	3	2
2	Christian Djoos	Matt Roy	40	0	3	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Johan Larsson	60	0	4	1		Victor Mete	60	0	4	1
2	Sam Lafferty	40	0	4	1	Alex Alexeyev	Matt Roy	40	0	4	1

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Gabriel Vilardi	Jack Hughes	60	0	2	3
2	Logan Brown	Isac Lundestrom	40	0	2	3

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Matt Roy	60	0	2	3
2	Christian Djoos	Victor Mete	40	0	2	3

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Jack Hughes	Gabriel Vilardi	Kaapo Kakko	Adam Boqvist	Christian Djoos

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Brendan Lemieux	Johan Larsson	Vitaly Abramov	Matt Roy

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Isac Lundestrom, Johan Larsson, Alexander True	Alexander True, Vladislav Kamenev	Vladislav Kamenev

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Alex Alexeyev, Christian Djoos, Victor Mete	Matt Roy	Christian Djoos, Victor Mete

Tirs de Pénalité
Kaapo Kakko, Brendan Lemieux, Jack Hughes, Vitaly Abramov, Logan Brown

Gardien
#1 : Igor Shesterkin, #2 : Connor Ingram

Lignes d'Attaque Perso. en Prol.
, , , , , , , , , ,

Lignes de Défense Perso. en Prol.
, , , ,

Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

	Ligue												Domicile											Visiteur
#	VS Équipe	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Bruins	5	3	2	0	0	0	0	0	14	14	0	3	2	1	0	0	0	0	0	11	9	2	2	1	1	0	0	0	0	0	3	5	-2	6	0.600	14	26	40	0	0	9	12	18	1	111	74	81	84	28	109	31	68	81	46	8	17.39%	27	7	74.07%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
2	Penguins	5	3	2	0	0	0	0	0	14	12	2	3	1	2	0	0	0	0	0	7	9	-2	2	2	0	0	0	0	0	0	7	3	4	6	0.600	14	24	38	0	0	9	12	18	1	105	74	81	84	28	108	31	46	85	29	2	6.90%	22	2	90.91%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
3	Phantoms	3	3	0	0	0	0	0	0	12	5	7	2	2	0	0	0	0	0	0	8	5	3	1	1	0	0	0	0	0	0	4	0	4	6	1.000	12	23	35	0	1	9	12	18	1	51	74	81	84	28	49	11	14	46	19	3	15.79%	7	2	71.43%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
	Total	13	9	4	0	0	0	0	0	40	31	9	8	5	3	0	0	0	0	0	26	23	3	5	4	1	0	0	0	0	0	14	8	6	18	0.692	40	73	113	0	1	9	12	18	1	267	74	81	84	28	266	73	128	212	94	13	13.83%	56	11	80.36%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
	_Since Last GM Reset	13	9	4	0	0	0	0	0	40	31	9	8	5	3	0	0	0	0	0	26	23	3	5	4	1	0	0	0	0	0	14	8	6	18	0.692	40	73	113	0	1	9	12	18	1	267	74	81	84	28	266	73	128	212	94	13	13.83%	56	11	80.36%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
	_Vs Conference	8	6	2	0	0	0	0	0	26	19	7	5	4	1	0	0	0	0	0	19	14	5	3	2	1	0	0	0	0	0	7	5	2	12	0.750	26	49	75	0	1	9	12	18	1	162	74	81	84	28	158	42	82	127	65	11	16.92%	34	9	73.53%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
	_Vs Division	3	3	0	0	0	0	0	0	12	5	7	2	2	0	0	0	0	0	0	8	5	3	1	1	0	0	0	0	0	0	4	0	4	6	1.000	12	23	35	0	1	9	12	18	1	51	74	81	84	28	49	11	14	46	19	3	15.79%	7	2	71.43%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85

			Total Pour les Joueurs
Matchs Joués	Points	Séquence	Buts	Passes	Points	Tirs Pour	Tirs Contre	Tirs Bloqués	Minutes de Pénalité	Mises en Échec	Buts en Filet Désert	Blanchissage
13	18	W3	40	73	113	267	266	73	128	212	0	1

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
13	9	4	0	0	0	0	40	31

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
8	5	3	0	0	0	0	26	23

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	4	1	0	0	0	0	14	8

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
6	3	0	1	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
94	13	13.83%	56	11	80.36%	0

Tirs en 1e Période	Tirs en 2e Période	Tirs en 3e Période	Tirs en 4e Période	Buts en 1e Période	Buts en 2e Période	Buts en 3e Période	Buts en 4e Période
74	81	84	28	9	12	18	1

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
217	381	56.96%	204	347	58.79%	109	196	55.61%

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
344	244	323	98	166	85

Derniers Match Joués Afficher ou Masquer des Colonnes

Astuces sur les Filtres (Anglais seulement)

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

Jour	Match	Équipe Visiteuse	Score	Équipe Locale	Score	ST	OT	Lien
1 - 2020-06-22	1	Phantoms	2	Wolf Pack	4	W		Sommaire du Match
2 - 2020-06-23	5	Phantoms	3	Wolf Pack	4	W		Sommaire du Match
3 - 2020-06-24	9	Wolf Pack	4	Phantoms	0	W		Sommaire du Match
6 - 2020-06-27	21	Bruins	3	Wolf Pack	2	L	X	Sommaire du Match
7 - 2020-06-28	23	Bruins	3	Wolf Pack	4	W		Sommaire du Match
8 - 2020-06-29	25	Wolf Pack	0	Bruins	3	L		Sommaire du Match
9 - 2020-06-30	27	Wolf Pack	3	Bruins	2	W	X	Sommaire du Match
10 - 2020-07-01	29	Bruins	3	Wolf Pack	5	W		Sommaire du Match
11 - 2020-07-02	31	Penguins	2	Wolf Pack	0	L		Sommaire du Match
12 - 2020-07-03	32	Penguins	4	Wolf Pack	0	L		Sommaire du Match
13 - 2020-07-04	33	Wolf Pack	3	Penguins	1	W		Sommaire du Match
14 - 2020-07-05	34	Wolf Pack	4	Penguins	2	W		Sommaire du Match
15 - 2020-07-06	35	Penguins	3	Wolf Pack	7	W		Sommaire du Match

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
-8	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
0$	3,877,868$	3,625,951$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	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
2020	13	9	4	0	0	0	0	0	40	31	9	8	5	3	0	0	0	0	0	26	23	3	5	4	1	0	0	0	0	0	14	8	6	18	40	73	113	0	1	9	12	18	1	267	74	81	84	28	266	73	128	212	94	13	13.83%	56	11	80.36%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85
Total Séries	13	9	4	0	0	0	0	0	40	31	9	8	5	3	0	0	0	0	0	26	23	3	5	4	1	0	0	0	0	0	14	8	6	18	40	73	113	0	1	9	12	18	1	267	74	81	84	28	266	73	128	212	94	13	13.83%	56	11	80.36%	0	217	381	56.96%	204	347	58.79%	109	196	55.61%	344	244	323	98	166	85