Ligue Canadienne de Hockey Simulé

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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	Matthew Tkachuk (R)		X			100.00	70	44	68	82	81	88	93	81	67	79	84	80	61	59	58	88	74	75	0
2	J.T. Compher (R)			X		100.00	61	41	75	75	73	88	79	70	83	71	72	82	53	74	55	73	67	70	0
3	Artturi Lehkonen (R)			X		100.00	72	35	75	74	70	84	95	69	64	68	67	76	67	59	53	68	71	68	0
4	Jesperi Kotkaniemi (R)	X				100.00	65	35	72	70	77	82	92	69	82	70	66	68	67	53	51	91	74	67	0
5	Brett Howden (R)	X				100.00	67	35	79	68	82	82	79	67	83	69	64	75	66	53	51	80	62	66	0
6	Colin Mcdonald			X		100.00	75	49	67	62	78	76	74	75	60	66	72	50	67	90	84	52	61	66	0
7	Tom Kuhnhackl (R)		X			100.00	70	35	75	65	80	79	86	64	56	64	64	80	58	64	52	51	71	66	0
8	Brian Flynn		X			100.00	41	28	95	70	72	69	73	63	87	57	56	81	64	99	87	58	68	65	0
9	Andy Andreoff (R)		X			100.00	80	48	63	65	75	71	71	66	74	67	64	59	56	68	57	53	72	63	0
10	Travis Boyd (R)	X				100.00	58	35	76	68	69	73	68	68	68	69	64	66	52	66	51	47	31	63	0
11	Sam Steel (R)	X				100.00	53	35	72	70	70	59	61	70	70	66	67	67	54	51	50	78	61	62	0
12	Micheal Haley (R)		X			100.00	75	65	56	63	73	70	58	62	65	62	61	62	61	69	53	26	25	60	0
13	Zach Werenski (R)				X	100.00	65	35	83	73	82	92	95	72	30	78	93	71	56	77	60	87	59	73	0
14	Derek Forbort (R)				X	100.00	70	35	75	66	90	86	95	64	30	67	64	80	56	64	58	79	68	70	0
15	Mark Borowiecki (R)				X	100.00	86	40	76	62	77	64	69	80	30	74	78	72	56	74	72	43	69	69	0
16	Dylan Olsen				X	100.00	68	19	99	60	80	72	72	82	50	75	72	68	67	80	76	53	71	69	0
17	Brandon Manning (R)				X	100.00	79	48	73	64	76	78	83	74	30	68	76	72	58	72	67	35	69	69	0
18	Matt Tennyson (R)				X	100.00	70	50	67	63	77	73	93	87	44	81	65	70	58	64	65	42	77	69	0
Rayé
1	Iiro Pakarinen (R)			X		100.00	72	41	81	62	77	71	79	55	54	58	60	72	55	74	71	40	53	62	0
2	Michael Latta	X				100.00	68	50	58	61	76	43	89	62	82	59	58	65	62	79	74	47	19	61	0
3	Mikhail Vorobyev (R)	X				100.00	53	35	67	69	79	56	57	69	69	58	59	60	54	51	50	62	20	59	0
4	Jyrki Jokipakka (R)				X	100.00	67	35	96	68	75	70	71	79	25	60	62	72	63	61	61	46	20	66	0
5	Jacob Larsson (R)				X	100.00	62	35	76	61	80	70	84	61	30	59	56	61	58	52	51	80	20	61	0

	MOYENNE D'ÉQUIPE					100.00	67	39	75	67	77	74	79	70	58	67	67	70	60	68	61	60	56	66

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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	Michael Garnett	100.00	64	50	77	80	72	99	99	99	99	78	93	99	99	23	63	81	0
2	Collin Delia (R)	100.00	80	76	94	82	79	83	85	84	83	79	51	74	66	42	71	79	0
Rayé
1	Jason Bacashihua	100.00	71	50	71	74	70	95	95	95	95	73	84	93	99	26	19	78	0
2	Alex Lyon (R)	100.00	76	68	97	78	75	79	81	80	79	75	51	70	64	37	20	75	0

	MOYENNE D'ÉQUIPE	100.00	73	61	85	79	74	89	90	90	89	76	70	84	82	32	43	78

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Terry Murray	88	76	77	79	99	98	80	CAN	69	1	600,000$

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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	GA	TA	HT	P/20	FT	S1	S2	S3
1	Artturi Lehkonen	Flyers (PHI)	RW	6	3	4	7	3	2	0	11	6	27	9	9	11.11%	2	118	19.75	1	1	2	4	18	3	11	0	0	83.33%	6	4	3	0	1.18	0	0	0	1
2	Matthew Tkachuk	Flyers (PHI)	LW	6	1	6	7	3	25	5	20	19	28	10	21	3.57%	7	132	22.11	1	3	4	7	23	1	23	0	0	55.10%	49	8	0	0	1.06	1	0	1	0
3	Jesperi Kotkaniemi	Flyers (PHI)	C	6	4	1	5	3	6	0	12	12	10	3	3	40.00%	1	119	19.97	2	1	3	4	23	1	10	1	1	55.73%	131	1	1	1	0.83	0	1	0	0
4	Brett Howden	Flyers (PHI)	C	6	2	2	4	3	4	0	7	13	12	6	9	16.67%	8	113	18.94	0	1	1	2	18	0	5	0	0	55.10%	98	4	3	0	0.70	0	0	0	0
5	Travis Boyd	Flyers (PHI)	C	6	1	2	3	-4	2	0	5	6	7	0	7	14.29%	4	70	11.74	0	0	0	0	0	0	0	1	0	48.84%	43	1	1	0	0.85	0	0	0	0
6	Colin Mcdonald	Flyers (PHI)	RW	6	1	2	3	-4	8	0	12	2	19	3	9	5.26%	1	71	11.94	0	0	0	1	1	0	0	0	0	66.67%	3	1	1	0	0.84	0	0	0	0
7	Matt Tennyson	Flyers (PHI)	D	6	0	3	3	-1	9	5	10	23	8	4	6	0.00%	7	132	22.12	0	0	0	0	16	0	18	0	0	0.00%	0	4	3	0	0.45	1	0	0	0
8	Derek Forbort	Flyers (PHI)	D	6	0	2	2	-1	6	0	14	17	7	2	3	0.00%	4	155	25.92	0	0	0	3	26	0	28	0	0	0.00%	0	2	8	0	0.26	0	0	0	0
9	J.T. Compher	Flyers (PHI)	RW	6	1	1	2	3	4	0	11	18	22	6	16	4.55%	3	139	23.28	0	0	0	0	24	2	27	0	0	45.45%	11	6	6	0	0.29	0	0	0	0
10	Zach Werenski	Flyers (PHI)	D	6	1	1	2	-1	0	0	14	15	12	7	5	8.33%	17	158	26.41	1	0	1	5	27	0	31	0	0	0.00%	0	3	7	0	0.25	0	0	0	0
11	Dylan Olsen	Flyers (PHI)	D	6	0	2	2	2	0	0	6	7	6	3	1	0.00%	4	89	14.87	0	0	0	0	0	0	0	0	0	0.00%	0	0	4	0	0.45	0	0	0	0
12	Brian Flynn	Flyers (PHI)	LW	6	2	0	2	-4	0	0	3	11	13	3	5	15.38%	1	84	14.10	0	0	0	0	0	1	13	0	0	58.82%	17	2	2	0	0.47	0	0	1	0
13	Tom Kuhnhackl	Flyers (PHI)	LW	6	1	1	2	3	10	0	14	11	17	2	9	5.88%	2	106	17.80	0	0	0	4	18	2	0	0	0	28.57%	14	1	2	0	0.37	0	0	0	0
14	Mark Borowiecki	Flyers (PHI)	D	6	0	1	1	2	4	0	8	13	7	6	3	0.00%	4	91	15.17	0	0	0	0	0	0	3	0	0	0.00%	0	3	2	0	0.22	0	0	0	0
15	Andy Andreoff	Flyers (PHI)	LW	6	0	0	0	-2	2	0	4	1	6	3	5	0.00%	0	50	8.47	0	0	0	0	1	0	7	0	0	100.00%	1	0	0	0	0.00	0	0	0	0
16	Sam Steel	Flyers (PHI)	C	6	0	0	0	-2	0	0	0	5	6	3	4	0.00%	1	38	6.37	0	0	0	0	0	0	0	0	0	66.67%	12	1	1	0	0.00	0	0	0	0
17	Micheal Haley	Flyers (PHI)	LW	6	0	0	0	-2	4	0	11	3	3	1	2	0.00%	1	44	7.43	0	0	0	1	3	0	1	0	0	50.00%	2	0	0	0	0.00	0	0	0	0
18	Brandon Manning	Flyers (PHI)	D	6	0	0	0	-1	0	0	11	8	10	4	3	0.00%	14	138	23.04	0	0	0	0	17	0	19	0	0	0.00%	0	1	5	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				108	17	28	45	0	86	10	173	190	220	75	120	7.73%	81	1856	17.19	5	6	11	31	223	10	199	2	1	54.52%	387	42	49	1	0.48	2	1	2	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 Gardien	Nom de l'Équipe	GP	W	L	OTL	PCT	GAA	MP	GA	SA	SAR	A	ST	BG	S2
1	Collin Delia	Flyers (PHI)	4	2	2	0	0.906	2.99	261	13	138	72	1	4	2	0
2	Michael Garnett	Flyers (PHI)	2	0	1	1	0.896	3.50	120	7	67	26	0	2	4	1
Stats d'équipe Total ou en Moyenne			6	2	3	1	0.902	3.15	381	20	205	98	1	6	6	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	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3
Alex Lyon	Flyers (PHI)	G	27	1992-12-09 07:25:34	Yes	201 Lbs	6 ft1	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$
Andy Andreoff	Flyers (PHI)	LW	29	1991-05-17 23:11:13	Yes	203 Lbs	6 ft1	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$
Artturi Lehkonen	Flyers (PHI)	RW	24	1995-07-04 08:48:34	Yes	177 Lbs	6 ft0	No	No	No	1	Pro & Farm	839,167$	0$	0$	No
Brandon Manning	Flyers (PHI)	D	30	1990-06-04 17:11:13	Yes	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	900,000$	0$	0$	No
Brett Howden	Flyers (PHI)	C	22	1998-03-29 03:03:41	Yes	195 Lbs	6 ft3	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$
Brian Flynn	Flyers (PHI)	LW	31	1988-07-26 05:11:13	No	184 Lbs	6 ft1	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$
Colin Mcdonald	Flyers (PHI)	RW	35	1984-09-30 05:11:13	No	215 Lbs	6 ft1	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$
Collin Delia	Flyers (PHI)	G	25	1994-06-20 07:49:44	Yes	208 Lbs	6 ft2	No	No	No	3	Pro & Farm	1,000,000$	0$	0$	No	1,000,000$	1,000,000$
Derek Forbort	Flyers (PHI)	D	28	1992-03-04 05:11:13	Yes	219 Lbs	6 ft4	No	No	No	3	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$	1,250,000$
Dylan Olsen	Flyers (PHI)	D	29	1991-01-03 11:11:13	No	225 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$
Iiro Pakarinen	Flyers (PHI)	RW	28	1991-08-25 23:11:13	Yes	212 Lbs	6 ft1	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$
J.T. Compher	Flyers (PHI)	RW	25	1995-04-08 08:55:06	Yes	193 Lbs	6 ft0	No	No	No	1	Pro & Farm	925,000$	0$	0$	No
Jacob Larsson	Flyers (PHI)	D	23	1997-04-29 08:51:10	Yes	197 Lbs	6 ft2	No	No	No	1	Pro & Farm	894,166$	0$	0$	No
Jason Bacashihua	Flyers (PHI)	G	37	1982-09-20 17:11:14	No	189 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,500,000$	0$	0$	No
Jesperi Kotkaniemi	Flyers (PHI)	C	19	2000-07-06 03:08:04	Yes	184 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$
Jyrki Jokipakka	Flyers (PHI)	D	28	1991-08-20 23:11:13	Yes	196 Lbs	6 ft3	No	No	No	2	Pro & Farm	700,000$	0$	0$	No	700,000$
Mark Borowiecki	Flyers (PHI)	D	30	1989-07-12 11:11:13	Yes	211 Lbs	6 ft2	No	No	No	1	Pro & Farm	900,000$	0$	0$	No
Matt Tennyson	Flyers (PHI)	D	30	1990-04-23 17:11:13	Yes	205 Lbs	6 ft2	No	No	No	1	Pro & Farm	800,000$	0$	0$	No
Matthew Tkachuk	Flyers (PHI)	LW	22	1997-12-11 08:57:18	Yes	202 Lbs	6 ft2	No	No	No	1	Pro & Farm	925,000$	0$	0$	No
Michael Garnett	Flyers (PHI)	G	37	1982-11-25 17:11:14	No	217 Lbs	6 ft1	No	No	No	3	Pro & Farm	1,500,000$	0$	0$	No	1,500,000$	1,500,000$
Michael Latta	Flyers (PHI)	C	29	1991-05-25 23:11:13	No	215 Lbs	6 ft0	No	No	No	1	Pro & Farm	575,000$	0$	0$	No
Micheal Haley	Flyers (PHI)	LW	34	1986-03-30 06:40:13	Yes	205 Lbs	5 ft11	No	No	No	3	Pro & Farm	575,000$	0$	0$	No	575,000$	575,000$
Mikhail Vorobyev	Flyers (PHI)	C	23	1997-01-05 08:21:53	Yes	194 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$
Sam Steel	Flyers (PHI)	C	22	1998-02-03 03:05:49	Yes	186 Lbs	5 ft11	No	No	No	3	Pro & Farm	863,333$	0$	0$	No	863,333$	863,333$
Tom Kuhnhackl	Flyers (PHI)	LW	28	1992-01-21 17:39:57	Yes	196 Lbs	6 ft2	No	No	No	3	Pro & Farm	600,000$	0$	0$	No	600,000$	600,000$
Travis Boyd	Flyers (PHI)	C	26	1993-09-14 07:33:39	Yes	185 Lbs	5 ft11	No	No	No	3	Pro & Farm	800,000$	0$	0$	No	800,000$	800,000$
Zach Werenski	Flyers (PHI)	D	22	1997-07-19 08:59:11	Yes	209 Lbs	6 ft2	No	No	No	1	Pro & Farm	925,000$	0$	0$	No

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
27	27.52	201 Lbs	6 ft1	2.00	872,099$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matthew Tkachuk	Jesperi Kotkaniemi	J.T. Compher	35	1	2	2
2	Tom Kuhnhackl	Brett Howden	Artturi Lehkonen	35	1	2	2
3	Brian Flynn	Travis Boyd	Colin Mcdonald	25	1	2	2
4	Andy Andreoff	Sam Steel	Micheal Haley	5	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Zach Werenski	Derek Forbort	35	1	2	2
2	Brandon Manning	Matt Tennyson	35	1	2	2
3	Dylan Olsen	Mark Borowiecki	30	1	2	2
4	Zach Werenski	Derek Forbort	0	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Matthew Tkachuk	Jesperi Kotkaniemi	J.T. Compher	60	1	2	2
2	Tom Kuhnhackl	Brett Howden	Artturi Lehkonen	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Zach Werenski	Derek Forbort	60	1	2	2
2	Brandon Manning	Matt Tennyson	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Matthew Tkachuk	J.T. Compher	60	1	2	2
2	Artturi Lehkonen	Jesperi Kotkaniemi	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Zach Werenski	Derek Forbort	60	1	2	2
2	Brandon Manning	Matt Tennyson	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Matthew Tkachuk	60	1	2	2	Zach Werenski	Derek Forbort	60	1	2	2
2	J.T. Compher	40	1	2	2	Brandon Manning	Matt Tennyson	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Matthew Tkachuk	J.T. Compher	60	1	2	2
2	Artturi Lehkonen	Jesperi Kotkaniemi	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Zach Werenski	Derek Forbort	60	1	2	2
2	Brandon Manning	Matt Tennyson	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matthew Tkachuk	Jesperi Kotkaniemi	J.T. Compher	Zach Werenski	Derek Forbort

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Matthew Tkachuk	Jesperi Kotkaniemi	J.T. Compher	Zach Werenski	Derek Forbort

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Micheal Haley, Colin Mcdonald, Brian Flynn	Micheal Haley, Colin Mcdonald	Brian Flynn

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dylan Olsen, Mark Borowiecki, Brandon Manning	Dylan Olsen	Mark Borowiecki, Brandon Manning

Tirs de Pénalité
Matthew Tkachuk, J.T. Compher, Artturi Lehkonen, Jesperi Kotkaniemi, Brett Howden

Gardien
#1 : Collin Delia, #2 : Michael Garnett

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
	Total	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	0.333	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54
	_Since Last GM Reset	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	0.333	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54
	_Vs Conference	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	0.333	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54
	_Vs Division	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	0.333	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54

			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
6	4	L1	17	28	45	220	205	81	86	173	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
6	2	4	0	0	0	0	17	20

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	2	1	0	0	0	0	13	13

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	4	7

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	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
28	5	17.86%	33	8	75.76%	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
76	65	68	11	4	6	5	2

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
87	157	55.41%	71	145	48.97%	53	84	63.10%

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
138	78	134	57	109	54

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 - 2019-10-06	4	Devils	5	Flyers	6	W	X	Sommaire du Match
3 - 2019-10-08	12	Devils	5	Flyers	3	L		Sommaire du Match
5 - 2019-10-10	20	Flyers	1	Devils	2	L	X	Sommaire du Match
7 - 2019-10-12	28	Flyers	1	Devils	2	L		Sommaire du Match
9 - 2019-10-14	36	Devils	3	Flyers	4	W	X	Sommaire du Match
11 - 2019-10-16	44	Flyers	2	Devils	3	L		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	45	25
Assistance	4,850	2,979
Assistance PCT	80.83%	99.30%

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	2610 - 86.99%	107,332$	321,997$	3000	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs
0$	2,354,667$	1,622,167$	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
14	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54
Total Séries	6	2	4	0	0	0	0	0	17	20	-3	3	2	1	0	0	0	0	0	13	13	0	3	0	3	0	0	0	0	0	4	7	-3	4	17	28	45	0	0	4	6	5	2	220	76	65	68	11	205	81	86	173	28	5	17.86%	33	8	75.76%	0	87	157	55.41%	71	145	48.97%	53	84	63.10%	138	78	134	57	109	54