LHSIR - Marlies

Maple Leafs
Formation
Points
Informations Joueurs
Lignes
Statistiques d'Équipe
Calendrier
Finance
Client Web pour Lignes

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

#	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	Âge	Contrat	Salaire
1	Bobby Ryan			X		100.00	82	94	74	72	79	65	68	79	56	61	72	54	63	82	84	68	46	0	0	33	1	1,000,000$
2	Brendan Leipsic		X	X		100.00	73	52	92	71	65	53	79	64	38	61	57	63	25	63	63	62	50	0	0	26	4	700,000$
3	Brett Howden	X	X	X		100.00	75	43	87	80	72	64	85	58	75	62	64	81	25	59	59	69	50	0	0	22	2	863,333$
4	Filip Chytil	X	X	X		100.00	59	40	94	82	66	68	89	69	72	62	74	61	25	59	59	70	51	0	0	20	4	1,244,166$
5	Kailer Yamamoto			X		100.00	82	43	86	83	54	76	64	68	25	88	88	61	25	48	48	81	45	0	0	21	3	1,124,166$
6	Gabriel Bourque		X	X		100.00	89	46	95	75	72	52	71	57	35	58	56	66	41	69	71	63	50	0	0	29	2	866,000$
7	Dmytro Timashov (R)		X			100.00	86	45	88	67	69	52	75	59	25	60	59	70	25	57	57	64	50	0	0	23	3	836,111$
8	Jeremy Bracco (R)			X		100.00	74	64	98	60	64	73	77	61	50	71	47	64	45	47	47	60	50	0	0	23	3	925,000$
9	Steven Fogarty	X		X		100.00	79	77	83	62	77	81	86	63	79	62	60	67	57	45	45	65	50	0	0	27	3	708,750$
10	Andrew Nielsen (R)				X	100.00	75	79	67	62	79	56	60	46	25	35	39	63	37	55	55	50	50	0	0	23	3	921,666$
11	Ben Thomas				X	100.00	75	69	88	65	69	72	79	50	25	41	41	64	39	55	55	55	50	0	0	24	2	700,000$
12	Ian McCoshen				X	100.00	76	80	66	60	80	70	77	47	25	37	40	62	38	50	50	51	50	0	0	24	2	1,024,999$
13	Nikita Zadorov				X	100.00	92	58	72	82	87	74	84	60	25	51	48	79	25	65	66	63	50	0	0	25	3	3,200,000$
14	Josh Morrissey				X	100.00	65	42	88	86	71	86	79	72	25	69	49	69	25	64	66	65	50	0	0	25	2	1,363,333$
15	Moritz Seider (R)				X	100.00	80	78	83	67	78	57	59	52	25	50	40	64	38	44	44	55	50	0	0	19	3	1,775,000$
16	Travis Dermott				X	100.00	79	56	81	82	78	72	77	59	25	50	49	72	25	58	59	61	50	0	0	23	2	863,333$
17	Bode Wilde (R)				X	100.00	77	73	85	60	73	56	60	45	25	35	39	61	37	44	44	51	50	0	0	20	3	910,833$
Rayé

	MOYENNE D'ÉQUIPE					100.00	78	61	84	72	73	66	75	59	39	56	54	66	35	57	57	62	50	0

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

#	Nom du Gardien	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Cayden Primeau (R)	100.00	60	65	81	73	58	65	59	65	63	62	30	44	44	62	50	0	0
2	Pheonix Copley	100.00	57	59	74	83	55	58	59	64	59	59	30	46	46	59	50	0	0
Rayé

	MOYENNE D'ÉQUIPE	100.00	59	62	78	78	57	62	59	65	61	61	30	45	45	61	50	0

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Joel Quenneville	72	71	84	81	90	84	55	CAN	63	3	6,000,000$

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

#	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	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Gabriel Bourque	Marlies (TOR)	LW/RW	50	13	19	32	-16	70	0	155	118	145	49	105	8.97%	20	1056	21.12	4	12	16	34	191	2	0	2	6	167	1	0	44.83%	58	0.61	0	6	0	0	0	4	1	3
2	Jeremy Bracco	Marlies (TOR)	RW	50	9	18	27	-8	34	0	95	72	85	23	59	10.59%	9	811	16.22	3	6	9	18	184	0	0	0	0	0	0	2	48.89%	45	0.67	1	1	0	0	0	3	1	1
3	Dmytro Timashov	Marlies (TOR)	LW	50	13	13	26	-24	78	0	127	109	140	37	96	9.29%	11	773	15.46	4	1	5	11	54	0	0	0	0	0	1	0	20.00%	25	0.67	0	1	0	0	0	2	3	2
4	Moritz Seider	Marlies (TOR)	D	50	5	21	26	-10	113	15	86	41	50	24	40	10.00%	52	1037	20.76	3	13	16	37	197	0	0	0	0	172	0	0	0.00%	0	0.50	0	1	1	1	1	0	0	1
5	Travis Dermott	Marlies (TOR)	D	40	9	17	26	-7	50	0	70	44	80	28	59	11.25%	42	902	22.56	5	6	11	67	161	0	1	1	0	167	4	0	0.00%	0	0.58	0	0	0	0	0	1	3	1
6	Brendan Leipsic	Marlies (TOR)	LW/RW	50	13	10	23	-10	42	0	75	88	117	30	81	11.11%	8	901	18.04	4	4	8	25	175	0	0	0	1	86	0	2	41.61%	149	0.51	2	6	0	0	0	3	2	4
7	Bode Wilde	Marlies (TOR)	D	50	1	13	14	-16	62	0	85	39	23	10	18	4.35%	41	980	19.61	1	6	7	18	186	0	1	1	0	180	0	1	0.00%	0	0.29	0	1	0	0	0	0	0	2
8	Andrew Nielsen	Marlies (TOR)	D	50	4	7	11	-19	86	10	117	37	43	13	34	9.30%	53	958	19.18	3	2	5	33	185	0	0	0	2	165	0	1	0.00%	0	0.23	1	1	1	1	0	0	0	1
Stats d'équipe Total ou en Moyenne				390	67	118	185	-110	535	25	810	548	683	214	492	9.81%	236	7422	19.03	27	50	77	243	1337	2	2	4	9	940	6	6	41.52%	277	0.50	4	17	2	2	1	13	10	15

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

#	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	Cayden Primeau	Marlies (TOR)	50	11	34	5	0.877	2.93	2866	4	0	140	1136	0	4	0	0.792	24	50	0	0	1	2
Stats d'équipe Total ou en Moyenne			50	11	34	5	0.877	2.93	2866	4	0	140	1136	0	4	0	0.792	24	50	0	0	1	2

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Type	Salaire Actuel	Salaire Restant	Salaire Moyen	Salaire Moyen Restant	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Salaire Année 2	Salaire Année 3	Salaire Année 4	Link
Andrew Nielsen	Marlies (TOR)	D	23	1996-11-13	Yes	210 Lbs	6 ft3	No	No	No	3	Pro & Farm	921,666$	349,341$	921,666$	349,341$	0$	0$	No	921,666$	921,666$
Ben Thomas	Marlies (TOR)	D	24	1996-05-27	No	187 Lbs	6 ft1	No	No	No	2	Pro & Farm	700,000$	265,323$	700,000$	265,323$	0$	0$	No	700,000$			Lien
Bobby Ryan	Marlies (TOR)	RW	33	1987-03-17	No	209 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,000,000$	379,032$	1,000,000$	379,032$	0$	0$	No				Lien
Bode Wilde	Marlies (TOR)	D	20	2000-01-24	Yes	192 Lbs	6 ft3	No	No	No	3	Pro & Farm	910,833$	345,235$	910,833$	345,235$	0$	0$	No	910,833$	910,833$
Brendan Leipsic	Marlies (TOR)	LW/RW	26	1994-05-19	No	180 Lbs	5 ft10	No	No	No	4	Pro & Farm	700,000$	265,323$	700,000$	265,323$	0$	0$	No	700,000$	700,000$	700,000$	Lien
Brett Howden	Marlies (TOR)	C/LW/RW	22	1998-03-29	No	193 Lbs	6 ft2	No	No	No	2	Pro & Farm	863,333$	327,231$	450,000$	170,565$	0$	0$	No	863,333$			Lien
Cayden Primeau	Marlies (TOR)	G	20	1999-08-11	Yes	181 Lbs	6 ft3	No	No	No	3	Pro & Farm	966,666$	366,398$	966,666$	366,398$	0$	0$	No	966,666$	966,666$
Dmytro Timashov	Marlies (TOR)	LW	23	1996-09-30	Yes	195 Lbs	5 ft10	No	No	No	3	Pro & Farm	836,111$	316,913$	836,111$	316,913$	0$	0$	No	836,111$	836,111$
Filip Chytil	Marlies (TOR)	C/LW/RW	20	1999-09-05	No	178 Lbs	6 ft1	No	No	No	4	Pro & Farm	1,244,166$	471,579$	894,166$	338,918$	0$	0$	No	1,244,166$	1,244,166$	1,244,166$	Lien
Gabriel Bourque	Marlies (TOR)	LW/RW	29	1990-09-23	No	206 Lbs	5 ft10	No	No	No	2	Pro & Farm	866,000$	328,242$	866,000$	328,242$	0$	0$	No	866,000$			Lien
Ian McCoshen	Marlies (TOR)	D	24	1995-08-05	No	217 Lbs	6 ft3	No	No	No	2	Pro & Farm	1,024,999$	388,508$	1,024,999$	388,508$	0$	0$	No	1,024,999$			Lien
Jeremy Bracco	Marlies (TOR)	RW	23	1997-03-17	Yes	180 Lbs	5 ft9	No	No	No	3	Pro & Farm	925,000$	350,605$	925,000$	350,605$	0$	0$	No	925,000$	925,000$
Josh Morrissey	Marlies (TOR)	D	25	1995-03-28	No	195 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,363,333$	516,747$	1,363,333$	516,747$	0$	0$	No	1,363,333$			Lien
Kailer Yamamoto	Marlies (TOR)	RW	21	1998-09-29	No	153 Lbs	5 ft8	No	No	No	3	Pro & Farm	1,124,166$	426,095$	894,166$	338,918$	0$	0$	No	1,124,166$	1,124,166$		Lien
Moritz Seider	Marlies (TOR)	D	19	2001-04-06	Yes	207 Lbs	6 ft4	No	No	No	3	Pro & Farm	1,775,000$	672,782$	1,775,000$	672,782$	0$	0$	No	1,775,000$	1,775,000$
Nikita Zadorov	Marlies (TOR)	D	25	1995-04-15	No	230 Lbs	6 ft5	No	No	No	3	Pro & Farm	3,200,000$	1,212,903$	3,200,000$	1,212,903$	0$	0$	No	3,200,000$	3,200,000$		Lien
Pheonix Copley	Marlies (TOR)	G	28	1992-01-18	No	200 Lbs	6 ft4	No	No	No	2	Pro & Farm	650,000$	246,371$	650,000$	246,371$	0$	0$	No	650,000$			Lien
Steven Fogarty	Marlies (TOR)	C/RW	27	1993-04-18	No	206 Lbs	6 ft3	No	No	No	3	Pro & Farm	708,750$	268,639$	708,750$	268,639$	0$	0$	No	708,750$	708,750$		Lien
Travis Dermott	Marlies (TOR)	D	23	1996-12-21	No	215 Lbs	6 ft0	No	No	No	2	Pro & Farm	863,333$	327,231$	863,333$	327,231$	0$	0$	No	863,333$			Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
19	23.95	197 Lbs	6 ft1	2.63	1,086,492$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Gabriel Bourque	35	1	2	2
2	Brendan Leipsic		Jeremy Bracco	30	1	2	2
3	Dmytro Timashov			25	1	2	2
4	Gabriel Bourque		Brendan Leipsic	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Moritz Seider	35	1	2	2
2	Andrew Nielsen	Bode Wilde	30	1	2	2
3			25	1	2	2
4		Moritz Seider	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1			Gabriel Bourque	60	1	2	2
2	Brendan Leipsic		Jeremy Bracco	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Moritz Seider	60	1	2	2
2	Andrew Nielsen	Bode Wilde	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Gabriel Bourque	60	1	2	2
2	Brendan Leipsic		40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Moritz Seider	60	1	2	2
2	Andrew Nielsen	Bode Wilde	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1		60	1	2	2		Moritz Seider	60	1	2	2
2	Gabriel Bourque	40	1	2	2	Andrew Nielsen	Bode Wilde	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1		Gabriel Bourque	60	1	2	2
2	Brendan Leipsic		40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1		Moritz Seider	60	1	2	2
2	Andrew Nielsen	Bode Wilde	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Gabriel Bourque		Moritz Seider

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
		Gabriel Bourque		Moritz Seider

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dmytro Timashov, Jeremy Bracco,	Dmytro Timashov, Jeremy Bracco

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
, Andrew Nielsen, Bode Wilde		Andrew Nielsen, Bode Wilde

Tirs de Pénalité
, Gabriel Bourque, Brendan Leipsic, , Dmytro Timashov

Gardien
#1 : Cayden Primeau, #2 :

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	Admirals	3	1	2	0	0	0	0	0	7	8	-1	2	1	1	0	0	0	0	0	6	5	1	1	0	1	0	0	0	0	0	1	3	-2	2	0.333	7	13	20	0	0	35	27	31	5	57	302	282	293	31	65	13	43	42	13	1	7.69%	19	4	78.95%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
2	Bruins	5	1	3	0	0	0	1	0	13	14	-1	2	1	1	0	0	0	0	0	6	5	1	3	0	2	0	0	0	1	0	7	9	-2	4	0.400	13	22	35	0	0	35	27	31	5	103	302	282	293	31	105	41	63	96	26	3	11.54%	29	4	86.21%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
3	Crunch	7	0	5	0	0	0	1	1	10	20	-10	4	0	3	0	0	0	0	1	6	13	-7	3	0	2	0	0	0	1	0	4	7	-3	3	0.214	10	16	26	0	0	35	27	31	5	131	302	282	293	31	174	59	86	167	33	3	9.09%	36	5	86.11%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
4	Griffins	6	2	3	0	0	1	0	0	19	21	-2	3	1	2	0	0	0	0	0	10	11	-1	3	1	1	0	0	1	0	0	9	10	-1	5	0.417	19	36	55	0	0	35	27	31	5	96	302	282	293	31	190	43	100	126	26	6	23.08%	46	7	84.78%	2	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
5	Monsters	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	2	-1	0	0.000	1	2	3	0	0	35	27	31	5	13	302	282	293	31	20	6	14	19	6	1	16.67%	6	0	100.00%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
6	Moose	1	0	0	0	0	0	1	0	4	3	1	1	0	0	0	0	0	1	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	6	10	0	0	35	27	31	5	21	302	282	293	31	25	3	10	15	6	2	33.33%	5	0	100.00%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
7	Penguins	2	1	1	0	0	0	0	0	4	4	0	1	0	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	2	1	1	2	0.500	4	6	10	0	0	35	27	31	5	37	302	282	293	31	34	13	18	42	14	1	7.14%	8	0	100.00%	1	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
8	Phantoms	2	0	2	0	0	0	0	0	3	7	-4	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	3	7	-4	0	0.000	3	5	8	0	0	35	27	31	5	35	302	282	293	31	50	21	22	34	14	3	21.43%	11	1	90.91%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
9	Rocket	6	1	4	0	0	0	0	1	6	11	-5	3	1	2	0	0	0	0	0	3	5	-2	3	0	2	0	0	0	0	1	3	6	-3	3	0.250	6	12	18	0	0	35	27	31	5	85	302	282	293	31	111	30	87	100	34	3	8.82%	33	3	90.91%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
10	Senators	6	2	4	0	0	0	0	0	9	15	-6	2	2	0	0	0	0	0	0	5	2	3	4	0	4	0	0	0	0	0	4	13	-9	4	0.333	9	15	24	0	0	35	27	31	5	114	302	282	293	31	142	33	78	117	35	2	5.71%	38	6	84.21%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
11	Soldiers	2	0	2	0	0	0	0	0	3	11	-8	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	2	7	-5	0	0.000	3	5	8	0	0	35	27	31	5	26	302	282	293	31	54	13	25	35	9	1	11.11%	10	0	100.00%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
12	Sound Tigers	3	0	3	0	0	0	0	0	2	9	-7	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	2	3	5	0	0	35	27	31	5	59	302	282	293	31	76	28	32	67	21	2	9.52%	16	3	81.25%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
13	Stars	1	0	0	0	0	0	0	1	3	4	-1	1	0	0	0	0	0	0	1	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0.500	3	6	9	0	0	35	27	31	5	15	302	282	293	31	33	4	10	20	6	1	16.67%	4	1	75.00%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
	Total	50	8	34	0	0	2	3	3	96	148	-52	25	6	16	0	0	0	1	2	55	73	-18	25	2	18	0	0	2	2	1	41	75	-34	27	0.270	96	168	264	0	0	35	27	31	5	884	302	282	293	31	1205	343	647	989	267	33	12.36%	288	38	86.81%	3	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
14	Wolf Pack	3	0	3	0	0	0	0	0	6	11	-5	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	6	10	16	0	0	35	27	31	5	52	302	282	293	31	72	17	30	67	16	3	18.75%	15	1	93.33%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
15	Wolves	2	0	1	0	0	1	0	0	6	8	-2	1	0	1	0	0	0	0	0	3	4	-1	1	0	0	0	0	1	0	0	3	4	-1	1	0.250	6	11	17	0	0	35	27	31	5	40	302	282	293	31	54	19	29	42	8	1	12.50%	12	3	75.00%	0	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
	_Since Last GM Reset	50	8	34	0	0	2	3	3	96	148	-52	25	6	16	0	0	0	1	2	55	73	-18	25	2	18	0	0	2	2	1	41	75	-34	27	0.270	96	168	264	0	0	35	27	31	5	884	302	282	293	31	1205	343	647	989	267	33	12.36%	288	38	86.81%	3	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
	_Vs Conference	32	5	23	0	0	0	2	2	52	84	-32	14	4	9	0	0	0	0	1	26	35	-9	18	1	14	0	0	0	2	1	26	49	-23	16	0.250	52	88	140	0	0	35	27	31	5	570	302	282	293	31	708	220	398	642	178	19	10.67%	176	20	88.64%	1	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274
	_Vs Division	30	4	16	0	0	0	2	2	57	81	-24	14	4	6	0	0	0	0	1	30	36	-6	16	0	10	0	0	0	2	1	27	45	-18	14	0.233	57	101	158	0	0	35	27	31	5	529	302	282	293	31	722	206	414	606	154	17	11.04%	182	25	86.26%	2	511	1329	38.45%	574	1572	36.51%	251	677	37.08%	1078	731	1371	378	586	274

			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
50	27	L3	96	168	264	884	1205	343	647	989	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
50	8	34	0	2	3	3	96	148

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
25	6	16	0	0	1	2	55	73

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
25	2	18	0	2	2	1	41	75

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
2	7	0	0	0	1

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
267	33	12.36%	288	38	86.81%	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
302	282	293	31	35	27	31	5

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
511	1329	38.45%	574	1572	36.51%	251	677	37.08%

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
1078	731	1371	378	586	274

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	Lien
1 - 2020-09-27	10	Marlies	1	Monsters	2	L			Sommaire du Match
2 - 2020-09-28	18	Crunch	4	Marlies	3	L			Sommaire du Match
4 - 2020-09-30	28	Marlies	2	Griffins	3	L	X		Sommaire du Match
5 - 2020-10-01	35	Rocket	2	Marlies	1	L			Sommaire du Match
6 - 2020-10-02	51	Marlies	1	Senators	3	L			Sommaire du Match
8 - 2020-10-04	56	Griffins	5	Marlies	2	L			Sommaire du Match
10 - 2020-10-06	71	Senators	1	Marlies	2	W			Sommaire du Match
13 - 2020-10-09	87	Marlies	1	Crunch	3	L			Sommaire du Match
14 - 2020-10-10	95	Marlies	0	Senators	2	L			Sommaire du Match
16 - 2020-10-12	101	Rocket	1	Marlies	2	W			Sommaire du Match
18 - 2020-10-14	119	Griffins	3	Marlies	1	L			Sommaire du Match
21 - 2020-10-17	130	Marlies	1	Rocket	2	L			Sommaire du Match
22 - 2020-10-18	141	Crunch	4	Marlies	0	L			Sommaire du Match
23 - 2020-10-19	151	Marlies	3	Bruins	2	W	X	X	Sommaire du Match
24 - 2020-10-20	161	Admirals	3	Marlies	2	L			Sommaire du Match
25 - 2020-10-21	166	Marlies	1	Rocket	2	L			Sommaire du Match
27 - 2020-10-23	184	Penguins	3	Marlies	2	L			Sommaire du Match
28 - 2020-10-24	195	Marlies	3	Wolves	4	L	X		Sommaire du Match
30 - 2020-10-26	205	Marlies	2	Penguins	1	W			Sommaire du Match
32 - 2020-10-28	214	Soldiers	4	Marlies	1	L			Sommaire du Match
34 - 2020-10-30	228	Marlies	1	Rocket	2	L	X	X	Sommaire du Match
36 - 2020-11-01	236	Moose	3	Marlies	4	W	X	X	Sommaire du Match
38 - 2020-11-03	249	Admirals	2	Marlies	4	W			Sommaire du Match
40 - 2020-11-05	260	Marlies	2	Wolf Pack	4	L			Sommaire du Match
42 - 2020-11-07	269	Marlies	2	Phantoms	5	L			Sommaire du Match
44 - 2020-11-09	280	Wolf Pack	4	Marlies	2	L			Sommaire du Match
45 - 2020-11-10	285	Marlies	1	Admirals	3	L			Sommaire du Match
46 - 2020-11-11	299	Rocket	2	Marlies	0	L			Sommaire du Match
48 - 2020-11-13	315	Bruins	4	Marlies	2	L			Sommaire du Match
50 - 2020-11-15	325	Marlies	0	Sound Tigers	2	L			Sommaire du Match
51 - 2020-11-16	337	Marlies	2	Crunch	1	W	X	X	Sommaire du Match
52 - 2020-11-17	349	Sound Tigers	5	Marlies	1	L			Sommaire du Match
54 - 2020-11-19	363	Crunch	3	Marlies	2	L	X	X	Sommaire du Match
55 - 2020-11-20	374	Marlies	1	Senators	4	L			Sommaire du Match
56 - 2020-11-21	381	Griffins	3	Marlies	7	W			Sommaire du Match
57 - 2020-11-22	395	Marlies	2	Bruins	3	L			Sommaire du Match
58 - 2020-11-23	404	Marlies	4	Griffins	3	W			Sommaire du Match
59 - 2020-11-24	413	Wolves	4	Marlies	3	L			Sommaire du Match
61 - 2020-11-26	429	Sound Tigers	2	Marlies	1	L			Sommaire du Match
63 - 2020-11-28	441	Marlies	1	Phantoms	2	L			Sommaire du Match
64 - 2020-11-29	450	Crunch	2	Marlies	1	L			Sommaire du Match
66 - 2020-12-01	462	Bruins	1	Marlies	4	W			Sommaire du Match
67 - 2020-12-02	470	Marlies	1	Crunch	3	L			Sommaire du Match
68 - 2020-12-03	476	Marlies	2	Bruins	4	L			Sommaire du Match
70 - 2020-12-05	491	Senators	1	Marlies	3	W			Sommaire du Match
71 - 2020-12-06	505	Marlies	2	Soldiers	7	L			Sommaire du Match
72 - 2020-12-07	514	Stars	4	Marlies	3	L	X	X	Sommaire du Match
74 - 2020-12-09	529	Wolf Pack	3	Marlies	2	L			Sommaire du Match
75 - 2020-12-10	537	Marlies	3	Griffins	4	L			Sommaire du Match
77 - 2020-12-12	547	Marlies	2	Senators	4	L			Sommaire du Match
78 - 2020-12-13	558	Griffins	-	Marlies	-
79 - 2020-12-14	568	Marlies	-	Flames	-
80 - 2020-12-15	579	Flames	-	Marlies	-
82 - 2020-12-17	592	Marlies	-	Griffins	-
84 - 2020-12-19	598	Marlies	-	Monsters	-
85 - 2020-12-20	610	Penguins	-	Marlies	-
86 - 2020-12-21	621	Marlies	-	Sharks	-
88 - 2020-12-23	632	Phantoms	-	Marlies	-
90 - 2020-12-25	645	Marlies	-	Penguins	-
91 - 2020-12-26	655	Bruins	-	Marlies	-
93 - 2020-12-28	669	Sharks	-	Marlies	-
94 - 2020-12-29	678	Marlies	-	Moose	-
95 - 2020-12-30	685	Marlies	-	Bruins	-
96 - 2020-12-31	696	Marlies	-	Rampage	-
97 - 2021-01-01	703	Rampage	-	Marlies	-
99 - 2021-01-03	718	Marlies	-	Sound Tigers	-
100 - 2021-01-04	727	IceHogs	-	Marlies	-
101 - 2021-01-05	741	Monsters	-	Marlies	-
103 - 2021-01-07	752	Marlies	-	Stars	-
104 - 2021-01-08	763	Admirals	-	Marlies	-
105 - 2021-01-09	775	Condors	-	Marlies	-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10	785	Marlies	-	Crunch	-
108 - 2021-01-12	799	Monarchs	-	Marlies	-
109 - 2021-01-13	808	Marlies	-	Monarchs	-
111 - 2021-01-15	817	Marlies	-	Rocket	-
112 - 2021-01-16	826	Bruins	-	Marlies	-
114 - 2021-01-18	841	Marlies	-	IceHogs	-
115 - 2021-01-19	850	Rocket	-	Marlies	-
117 - 2021-01-21	862	Marlies	-	Condors	-
118 - 2021-01-22	870	Senators	-	Marlies	-
120 - 2021-01-24	887	Senators	-	Marlies	-
121 - 2021-01-25	890	Marlies	-	Admirals	-

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
16	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
4,940,458$	2,064,336$	1,965,003$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	1,214,600$	0	0

Éstimation
Revenus de la Saison Éstimés	Jours Restants de la Saison	Dépenses Par Jour	Dépenses de la Saison Éstimées
0$	47	65,035$	3,056,645$

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