German Fantasy Hockey League - Toronto Maple Leafs

Mississauga Wolves
Formation
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Lignes
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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	Brayden Schenn	0	X	X	X		100.00	84	58	80	85	71	83	98	86	85	85	85	61	56	72	74	0	78	76	0
2	Mikael Granlund	0			X		100.00	67	42	92	87	66	79	96	82	59	90	78	82	41	69	71	0	79	76	0
3	William Karlsson	0	X				100.00	67	42	94	84	67	79	99	80	79	81	95	74	53	65	65	0	79	76	0
4	Mikko Koivu (A)	0	X				100.00	67	43	83	79	80	79	98	82	92	79	70	83	73	84	87	0	79	75	1
5	Kevin Hayes	0	X	X	X		100.00	65	43	91	84	85	76	93	68	90	70	84	83	75	66	68	0	78	74	0
6	David Perron	0		X	X		100.00	82	45	80	77	73	78	93	78	51	95	74	60	63	78	80	0	79	74	0
7	Jakob Silfverberg	0			X		100.00	69	42	92	86	71	78	95	75	37	75	73	83	85	69	72	0	79	73	0
8	Thomas Vanek	0		X	X		100.00	65	43	86	79	79	67	91	71	33	80	81	52	74	85	89	0	79	71	1
9	Jesper Fast	0			X		100.00	83	44	88	85	68	69	87	61	37	73	71	83	25	65	67	0	78	70	0
10	Carl Hagelin	0		X			100.00	79	44	89	94	67	73	88	61	39	71	62	79	25	71	76	0	80	70	0
11	Brian Boyle (A)	0	X	X			100.00	83	57	81	72	92	65	89	77	87	62	71	64	69	77	82	0	76	69	0
12	Tom Wilson	0			X		100.00	97	99	39	81	83	73	97	61	42	72	71	70	25	68	70	0	79	69	0
13	Marc Staal (C)	0				X	100.00	76	44	91	78	78	76	89	60	25	50	47	94	25	79	84	0	78	73	1
14	Marco Scandella	0				X	100.00	76	54	86	82	76	88	94	70	25	56	48	85	25	70	72	0	78	73	0
15	David Savard	0				X	100.00	83	45	87	83	79	78	95	59	25	52	48	87	25	69	70	0	76	73	0
16	Brady Skjei	0				X	100.00	80	55	85	86	78	83	98	68	25	61	48	76	25	61	62	0	79	72	0
17	Dennis Seidenberg	0				X	100.00	88	68	82	74	78	75	68	57	25	54	47	86	25	82	86	0	77	71	1
18	Chris Wideman	0				X	100.00	76	43	88	79	65	58	64	78	25	65	60	57	25	60	60	0	69	64	0
Rayé
1	Tyler Pitlick	0		X	X		100.00	80	44	87	77	73	66	73	61	35	63	71	84	25	59	59	0	37	66	0
2	Luca Sbisa	0				X	100.00	82	66	85	77	74	78	73	56	25	70	49	91	25	71	72	0	73	72	0

	MOYENNE D'ÉQUIPE					100.00	77	51	84	81	75	75	89	70	47	70	67	77	43	71	73	0	76	72

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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	Ryan Miller	100.00	80	71	72	65	86	75	75	80	86	80	77	78	81	0	79	76	2
2	Ondrej Pavelec	100.00	73	53	55	85	80	66	58	72	80	73	67	69	70	0	52	69	2
Rayé
1	Antoine Bibeau	100.00	63	67	84	82	63	69	59	68	66	65	30	44	44	0	55	64	0

	MOYENNE D'ÉQUIPE	100.00	72	64	70	77	76	70	64	73	77	73	58	64	65	0	62	70

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Dave Hakstol	70	77	81	81	63	56	71	USA	49	1	750,000$

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	PKS	PKM	GW	GT	FO%	FOT	GA	TA	P/20	PSS	FL	S1	S2
1	Mikko Koivu	Toronto Maple Leafs	C	5	3	3	6	0	4	0	4	10	18	2	17	16.67%	0	106	21.30	0	0	0	0	8	0	13	0	0	53.70%	108	3	4	1.13	0	0	1	0
2	Brayden Schenn	Toronto Maple Leafs	C/LW/RW	5	2	3	5	-2	4	0	17	9	13	9	15	15.38%	3	105	21.08	1	1	2	1	9	0	0	0	1	28.57%	7	3	0	0.95	0	0	0	1
3	William Karlsson	Toronto Maple Leafs	C	5	2	3	5	-2	0	0	11	9	10	3	8	20.00%	1	106	21.29	0	2	2	0	11	0	0	1	0	51.67%	120	3	0	0.94	0	0	1	0
4	Mikael Granlund	Toronto Maple Leafs	RW	5	0	4	4	-2	0	0	10	5	17	6	10	0.00%	4	106	21.31	0	1	1	2	11	0	0	0	0	27.27%	11	1	1	0.75	0	0	0	0
5	Jesper Fast	Toronto Maple Leafs	RW	5	1	2	3	2	0	0	4	2	3	2	2	33.33%	0	54	10.94	0	0	0	0	0	0	4	0	0	100.00%	1	1	1	1.10	0	0	0	0
6	Carl Hagelin	Toronto Maple Leafs	LW	5	1	2	3	0	2	0	1	0	4	0	2	25.00%	0	39	7.80	0	0	0	0	0	0	0	0	0	100.00%	1	2	0	1.54	0	0	0	0
7	Marc Staal	Toronto Maple Leafs	D	5	1	1	2	-2	4	0	8	7	7	2	2	14.29%	5	130	26.05	1	0	1	1	8	0	11	0	0	0.00%	0	0	2	0.31	1	0	0	0
8	David Perron	Toronto Maple Leafs	LW/RW	5	1	1	2	-4	0	0	4	3	15	1	6	6.67%	3	86	17.31	0	0	0	0	7	0	0	0	0	0.00%	3	1	3	0.46	0	0	0	0
9	Brian Boyle	Toronto Maple Leafs	C/LW	5	0	1	1	-2	2	0	2	3	7	2	5	0.00%	1	66	13.38	0	0	0	0	0	1	7	0	0	41.38%	29	1	3	0.30	0	0	0	0
10	Thomas Vanek	Toronto Maple Leafs	LW/RW	5	0	1	1	1	0	0	7	2	11	5	18	0.00%	0	76	15.30	0	0	0	0	0	1	4	0	0	33.33%	6	3	1	0.26	0	0	0	0
11	David Savard	Toronto Maple Leafs	D	5	0	1	1	2	9	5	6	11	4	2	1	0.00%	7	118	23.75	0	0	0	1	9	0	11	0	0	0.00%	0	0	3	0.17	0	1	0	0
12	Jakob Silfverberg	Toronto Maple Leafs	RW	5	1	0	1	-3	0	0	3	6	21	6	10	4.76%	6	93	18.63	0	0	0	0	0	0	15	0	0	37.50%	8	4	4	0.21	0	0	0	0
13	Dennis Seidenberg	Toronto Maple Leafs	D	5	0	0	0	-7	2	0	7	9	2	3	4	0.00%	8	93	18.79	0	0	0	0	0	0	4	0	0	0.00%	0	0	1	0.00	0	0	0	0
14	Kevin Hayes	Toronto Maple Leafs	C/LW/RW	5	0	0	0	-4	0	0	3	8	9	2	4	0.00%	1	94	18.97	0	0	0	0	7	0	7	0	0	53.57%	28	1	1	0.00	0	0	0	0
15	Brady Skjei	Toronto Maple Leafs	D	5	0	0	0	4	4	0	4	3	4	0	3	0.00%	5	112	22.54	0	0	0	0	8	0	9	0	0	0.00%	0	0	1	0.00	0	0	0	0
16	Chris Wideman	Toronto Maple Leafs	D	4	0	0	0	-3	2	0	3	2	2	1	1	0.00%	1	58	14.65	0	0	0	0	0	2	3	0	0	0.00%	0	0	2	0.00	0	0	0	0
17	Luca Sbisa	Toronto Maple Leafs	D	1	0	0	0	0	0	0	2	1	1	0	0	0.00%	2	16	16.30	0	0	0	0	1	0	1	0	0	0.00%	0	0	1	0.00	0	0	0	0
18	Marco Scandella	Toronto Maple Leafs	D	5	0	0	0	-7	2	0	8	11	8	2	1	0.00%	8	132	26.44	0	0	0	0	9	0	10	0	0	0.00%	0	0	3	0.00	0	0	0	0
19	Tom Wilson	Toronto Maple Leafs	RW	5	0	0	0	-1	0	0	2	4	2	0	0	0.00%	1	27	5.58	0	0	0	0	0	0	0	0	0	50.00%	2	0	0	0.00	0	0	0	0
Stats d'équipe Total ou en Moyenne				90	12	22	34	-30	35	5	106	105	158	48	109	7.59%	56	1627	18.08	2	4	6	5	95	4	107	1	1	49.38%	324	23	31	0.42	1	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	PIM	GA	SA	SAR	ST	BG	S2
1	Ryan Miller	Toronto Maple Leafs	4	1	2	1	0.902	3.29	237	2	13	132	64	3	2	1
2	Ondrej Pavelec	Toronto Maple Leafs	2	0	1	0	0.868	4.57	92	0	7	53	29	2	3	0
Stats d'équipe Total ou en Moyenne			6	1	3	1	0.892	3.64	330	2	20	185	93	5	5	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	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Antoine Bibeau	Toronto Maple Leafs	G	25	01.05.1994	No	210 Lbs	6 ft3	No	No	No	3	Avec Restriction	Pro & Farm	675,000$	675,000$	0$	No	Lien
Brady Skjei	Toronto Maple Leafs	D	25	26.03.1994	No	211 Lbs	6 ft3	No	No	No	2	Avec Restriction	Pro & Farm	6,000,000$	6,000,000$	0$	No	Lien
Brayden Schenn	Toronto Maple Leafs	C/LW/RW	27	21.08.1991	No	195 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	5,125,000$	5,125,000$	0$	No	Lien
Brian Boyle	Toronto Maple Leafs	C/LW	34	18.12.1984	No	244 Lbs	6 ft6	No	No	No	3	Sans Restriction	Pro & Farm	1,000,000$	1,000,000$	0$	No	Lien
Carl Hagelin	Toronto Maple Leafs	LW	30	23.08.1988	No	186 Lbs	5 ft11	No	No	No	1	Avec Restriction	Pro & Farm	3,200,000$	3,200,000$	0$	No	Lien
Chris Wideman	Toronto Maple Leafs	D	29	06.01.1990	No	180 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	1,000,000$	1,000,000$	0$	No	Lien
David Perron	Toronto Maple Leafs	LW/RW	31	28.05.1988	No	200 Lbs	6 ft0	No	No	No	3	Sans Restriction	Pro & Farm	4,000,000$	4,000,000$	0$	No	Lien
David Savard	Toronto Maple Leafs	D	28	21.10.1990	No	227 Lbs	6 ft2	No	No	No	3	Avec Restriction	Pro & Farm	4,250,000$	4,250,000$	0$	No	Lien
Dennis Seidenberg	Toronto Maple Leafs	D	37	18.07.1981	No	198 Lbs	6 ft0	No	No	No	1	Sans Restriction	Pro Only	2,250,000$	2,250,000$	0$	No	Lien
Jakob Silfverberg	Toronto Maple Leafs	RW	28	13.10.1990	No	196 Lbs	6 ft2	No	No	No	2	Avec Restriction	Pro & Farm	4,400,000$	4,400,000$	0$	No	Lien
Jesper Fast	Toronto Maple Leafs	RW	27	01.12.1991	No	190 Lbs	6 ft0	No	No	No	3	Avec Restriction	Pro & Farm	1,850,000$	1,850,000$	0$	No	Lien
Kevin Hayes	Toronto Maple Leafs	C/LW/RW	27	07.05.1992	No	215 Lbs	6 ft5	No	No	No	2	Avec Restriction	Pro & Farm	5,200,000$	5,200,000$	0$	No	Lien
Luca Sbisa	Toronto Maple Leafs	D	29	30.01.1990	No	209 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	4,800,000$	4,800,000$	0$	No	Lien
Marc Staal	Toronto Maple Leafs	D	32	12.01.1987	No	209 Lbs	6 ft4	No	No	No	2	Sans Restriction	Pro Only	6,000,000$	6,000,000$	0$	No	Lien
Marco Scandella	Toronto Maple Leafs	D	29	22.02.1990	No	208 Lbs	6 ft3	No	No	No	1	Avec Restriction	Pro & Farm	3,200,000$	3,200,000$	0$	No	Lien
Mikael Granlund	Toronto Maple Leafs	RW	27	25.02.1992	No	184 Lbs	5 ft10	Yes	No	No	5	Avec Restriction	Pro & Farm	4,600,000$	4,600,000$	0$	No	Lien
Mikko Koivu	Toronto Maple Leafs	C	36	11.03.1983	No	215 Lbs	6 ft3	No	No	No	1	Sans Restriction	Pro Only	5,000,000$	5,000,000$	0$	No	Lien
Ondrej Pavelec	Toronto Maple Leafs	G	31	30.08.1987	No	215 Lbs	6 ft3	No	No	No	2	Sans Restriction	Pro Only	3,000,000$	3,000,000$	0$	No	Lien
Ryan Miller	Toronto Maple Leafs	G	38	17.07.1980	No	168 Lbs	6 ft2	No	No	No	1	Sans Restriction	Pro Only	4,000,000$	4,000,000$	0$	No	Lien
Thomas Vanek	Toronto Maple Leafs	LW/RW	35	18.01.1984	No	214 Lbs	6 ft2	No	No	No	2	Sans Restriction	Pro & Farm	1,250,000$	1,250,000$	0$	No	Lien
Tom Wilson	Toronto Maple Leafs	RW	25	29.03.1994	No	217 Lbs	6 ft4	No	No	No	1	Avec Restriction	Pro & Farm	2,200,000$	2,200,000$	0$	No	Lien
Tyler Pitlick	Toronto Maple Leafs	LW/RW	27	31.10.1991	No	202 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	1,800,000$	1,800,000$	0$	No	Lien
William Karlsson	Toronto Maple Leafs	C	26	07.01.1993	No	189 Lbs	6 ft1	No	No	No	1	Avec Restriction	Pro & Farm	1,800,000$	1,800,000$	0$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	29.70	204 Lbs	6 ft2	1.91	3,330,435$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
76,600,000$	44,025,000$	16,375,000$	4,600,000$	4,600,000$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Brayden Schenn	William Karlsson	Mikael Granlund	35	1	2	2
2	David Perron	Mikko Koivu	Kevin Hayes	30	1	2	2
3	Thomas Vanek	Brian Boyle	Jakob Silfverberg	25	1	2	2
4	Carl Hagelin	Mikko Koivu	Jesper Fast	10	1	2	2

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marc Staal	Marco Scandella	35	1	2	2
2	David Savard	Brady Skjei	30	1	2	2
3	Dennis Seidenberg	Chris Wideman	25	1	2	2
4	Marc Staal	Marco Scandella	10	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Brayden Schenn	William Karlsson	Mikael Granlund	60	1	2	2
2	David Perron	Mikko Koivu	Kevin Hayes	40	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marc Staal	Marco Scandella	60	1	2	2
2	David Savard	Brady Skjei	40	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mikko Koivu	Jakob Silfverberg	60	1	2	2
2	Kevin Hayes	Jesper Fast	40	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marc Staal	Marco Scandella	60	1	2	2
2	David Savard	Brady Skjei	40	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Mikko Koivu	60	1	2	2	Marc Staal	Marco Scandella	60	1	2	2
2	Kevin Hayes	40	1	2	2	David Savard	Brady Skjei	40	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	William Karlsson	Mikael Granlund	60	1	2	2
2	Kevin Hayes	David Perron	40	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Marc Staal	Marco Scandella	60	1	2	2
2	David Savard	Brady Skjei	40	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Brayden Schenn	William Karlsson	Mikael Granlund	Marc Staal	Marco Scandella

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Brayden Schenn	Mikko Koivu	Mikael Granlund	Marc Staal	Marco Scandella

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Tom Wilson, Jakob Silfverberg, Thomas Vanek	Tom Wilson, Jakob Silfverberg	Thomas Vanek

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Dennis Seidenberg, Chris Wideman, David Savard	Dennis Seidenberg	Chris Wideman, David Savard

Tirs de Pénalité
Mikael Granlund, Mikko Koivu, Brayden Schenn, William Karlsson, David Perron

Gardien
#1 : Ryan Miller, #2 : Ondrej Pavelec

Lignes d'Attaque Perso. en Prol.
Mikko Koivu, Mikael Granlund, Brayden Schenn, William Karlsson, Kevin Hayes, David Perron, David Perron, Jakob Silfverberg, Thomas Vanek, Jesper Fast, Tom Wilson

Lignes de Défense Perso. en Prol.
Marc Staal, Marco Scandella, David Savard, Brady Skjei, Dennis Seidenberg

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	Detroit Red Wings	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	0.200	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46
	Total	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	0.200	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46
	_Since Last GM Reset	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	0.200	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46
	_Vs Conference	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	0.200	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46
	_Vs Division	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	0.200	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46

			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
5	2	L1	12	22	34	158	185	56	37	106	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	12	20

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	6	8

Matchs Éxtérieurs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	0	3	0	0	0	0	6	12

Derniers 10 Matchs
W	L	OTW	OTL	SOW	SOL
0	3	1	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
11	2	18.18%	17	4	76.47%	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
59	35	57	7	5	0	6	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
58	115	50.43%	59	129	45.74%	43	80	53.75%

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
113	65	123	49	93	46

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
2 - 2018-10-03	6	Toronto Maple Leafs	2	Detroit Red Wings	3	L	X	Sommaire du Match
4 - 2018-10-05	14	Toronto Maple Leafs	1	Detroit Red Wings	5	L		Sommaire du Match
6 - 2018-10-07	22	Detroit Red Wings	5	Toronto Maple Leafs	2	L		Sommaire du Match
8 - 2018-10-09	30	Detroit Red Wings	3	Toronto Maple Leafs	4	W	X	Sommaire du Match
10 - 2018-10-11	38	Toronto Maple Leafs	3	Detroit Red Wings	4	L		Sommaire du Match

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	7300	5000	2000	4000	1000
Prix des Billets	140	80	50	35	250
Assistance	12,748	10,000	3,883	7,748	1,994
Attendance PCT	87.32%	100.00%	97.08%	96.85%	99.70%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
39	18187 - 94.23%	2,129,130$	4,258,260$	19300	100

Dépenses
Dépenses Annuelles à Ce Jour	Salaire Total des Joueurs	Salaire Total Moyen des Joueurs	Salaire des Coachs	Valeur du Cap Salarial Spécial
0$	76,600,000$	68,177,777$	0$	0$

Cap Salarial Par Jour	Cap salarial à ce jour	Taxe de Luxe Totale	Joueurs Inclut dans la Cap Salariale	Joueurs Exclut dans la Cap Salariale
0$	0$	0$	23	0

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

Total de l'Équipe Éstimé
Dépenses de la Saison Éstimées	Cap Salarial de la Saison Éstimé	Compte Bancaire Actuel	Compte Bancaire Projeté
0$	0$	20,560,909$	20,560,909$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Brayden Schenn	AGE:27	PO:0	OV:76
Kevin Hayes	AGE:27	PO:0	OV:74
David Perron	AGE:31	PO:0	OV:74
Thomas Vanek	AGE:35	PO:0	OV:71
Carl Hagelin	AGE:30	PO:0	OV:70
Brian Boyle	AGE:34	PO:0	OV:69
Tyler Pitlick	AGE:27	PO:0	OV:66
Christoph Bertschy	AGE:25	PO:0	OV:60
*Alexander Volkov	AGE:21	PO:0	OV:59
*Anton Karlsson	AGE:22	PO:0	OV:49
*Nikolay Prokhorkin	AGE:25	PO:0	OV:49
Eric Kattelus	AGE:31	PO:0	OV:49
*Niklas Tikkinen	AGE:25	PO:0	OV:48
*Nick Sorensen	AGE:24	PO:0	OV:48
Nicklas Lasu	AGE:29	PO:0	OV:48
Ben Hanowski	AGE:28	PO:0	OV:48

Brayden Schenn	AGE:27	PO:0	OV:76
William Karlsson	AGE:26	PO:0	OV:76
Mikko Koivu	AGE:36	PO:0	OV:75
Kevin Hayes	AGE:27	PO:0	OV:74
Brian Boyle	AGE:34	PO:0	OV:69
*Colin Blackwell	AGE:26	PO:0	OV:61
Christoph Bertschy	AGE:25	PO:0	OV:60
*Eric Cornel	AGE:23	PO:0	OV:58
Max Reinhart	AGE:27	PO:0	OV:57
Connor Jones	AGE:28	PO:0	OV:55
Anton Lander	AGE:28	PO:0	OV:49
Cam Reid	AGE:27	PO:0	OV:49
Eric O'Dell	AGE:28	PO:0	OV:48
Jesper Samuelsson	AGE:30	PO:0	OV:48
*Daniel Pribyl	AGE:26	PO:0	OV:48
*Alexander Ruuttu	AGE:26	PO:0	OV:48

Brayden Schenn	AGE:27	PO:0	OV:76
Mikael Granlund	AGE:27	PO:0	OV:76
Kevin Hayes	AGE:27	PO:0	OV:74
David Perron	AGE:31	PO:0	OV:74
Jakob Silfverberg	AGE:28	PO:0	OV:73
Thomas Vanek	AGE:35	PO:0	OV:71
Jesper Fast	AGE:27	PO:0	OV:70
Tom Wilson	AGE:25	PO:0	OV:69
Tyler Pitlick	AGE:27	PO:0	OV:66
Lee Stempniak	AGE:36	PO:0	OV:63
Christoph Bertschy	AGE:25	PO:0	OV:60
*Alexander Volkov	AGE:21	PO:0	OV:59
*Eric Cornel	AGE:23	PO:0	OV:58
*Anton Karlsson	AGE:22	PO:0	OV:49
*Fabrice Herzog	AGE:24	PO:0	OV:48
Valeri Nichushkin	AGE:24	PO:0	OV:48
*Niklas Tikkinen	AGE:25	PO:0	OV:48
*Nick Sorensen	AGE:24	PO:0	OV:48
Kenny Ryan	AGE:27	PO:0	OV:48
Ben Hanowski	AGE:28	PO:0	OV:48

Défense #1

Défense #2

Gardien

Marc Staal	AGE:32	PO:0	OV:73
Marco Scandella	AGE:29	PO:0	OV:73
David Savard	AGE:28	PO:0	OV:73
Brady Skjei	AGE:25	PO:0	OV:72
Luca Sbisa	AGE:29	PO:0	OV:72
Dennis Seidenberg	AGE:37	PO:0	OV:71
Chris Wideman	AGE:29	PO:0	OV:64
*Brendan Guhle	AGE:21	PO:0	OV:62
Tim Heed	AGE:28	PO:0	OV:61

Julian Melchiori	AGE:27	PO:0	OV:60
Gabriel Carlsson	AGE:22	PO:0	OV:59
Andrey Pedan	AGE:25	PO:0	OV:59
Stuart Percy	AGE:26	PO:0	OV:57
Niklas Hansson	AGE:24	PO:0	OV:56
*Jonatan Nielsen	AGE:25	PO:0	OV:48
*Niklas Tikkinen	AGE:25	PO:0	OV:48
*Santeri Saari	AGE:24	PO:0	OV:48
Scott Valentine	AGE:28	PO:0	OV:48

Ryan Miller	AGE:38	PO:0	OV:76
Ondrej Pavelec	AGE:31	PO:0	OV:69
Antoine Bibeau	AGE:25	PO:0	OV:64
Marek Langhamer	AGE:24	PO:0	OV:64
*Filip Gustavsson	AGE:20	PO:0	OV:62
Matt Hackett	AGE:29	PO:0	OV:49
*Niklas Lundstrom	AGE:26	PO:0	OV:49

Éspoirs

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

Éspoir	Nom de l'Équipe	Année de Repêchage	Choix Total	Information
Brad Morrison	Toronto Maple Leafs	2015	125
Brett Davis	Toronto Maple Leafs	2017	194
Clarke MacArthur	Toronto Maple Leafs	2018		injured
Cole Hults	Toronto Maple Leafs	2017	163
David Hrenak	Toronto Maple Leafs	2018	152
Felix Sandstrom	Toronto Maple Leafs	2015	82
Jordy Stallard	Toronto Maple Leafs	2016	137
Karch Bachman	Toronto Maple Leafs	2015	155
Kevin Elgestal	Toronto Maple Leafs	2017		undrafted UFA 5/5 450.000
Lukas Vejdemo	Toronto Maple Leafs	2015	101
Miska Kukkonen	Toronto Maple Leafs	2018	160
Nate Clurman	Toronto Maple Leafs	2016	167
Nick Campoli	Toronto Maple Leafs	2017	186
Ryan O'Reilly	Toronto Maple Leafs	2018	129
Samuel Ersson	Toronto Maple Leafs	2018	191
Santeri Virtanen	Toronto Maple Leafs	2017	132
Steven Ruggiero	Toronto Maple Leafs	2015	196
Stuart Skinner	Toronto Maple Leafs	2017	101

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
2019				STL	TOR	TOR
2020		TOR	TOR	TOR	TOR	TOR	TOR CAR
2021	TOR	TOR	TOR	TOR	TOR	TOR	CAR TOR
2022	TOR	TOR	TOR	TOR	TOR	TOR	TOR
2023	TOR	TOR	TOR	TOR	TOR	TOR	TOR

[23.04.2019 23:13:35] - Toronto Maple Leafs was eliminated at round 1 of year 2018.
[08.04.2019 23:05:15] - Mississauga Wolves didn't make playoff for year 2018.
[11.02.2019 08:23:10] - Mikko Koivu has been selected as assistant for Toronto Maple Leafs.
[11.02.2019 08:23:10] - Unknown Player is no longer as assistant for Toronto Maple Leafs.
[11.02.2019 08:23:10] - Brian Boyle has been selected as assistant for Toronto Maple Leafs.
[11.02.2019 08:23:10] - Unknown Player is no longer as assistant for Toronto Maple Leafs.
[11.02.2019 08:23:10] - Marc Staal has been selected as captain for Toronto Maple Leafs.
[11.02.2019 08:23:10] - Unknown Player is no longer captain for Toronto Maple Leafs.
[28.01.2019 23:05:41] - TRADE : From Toronto Maple Leafs to Carolina Hurricanes : Nino Niederreiter (71), Thomas Hickey (71).
[28.01.2019 23:05:41] - TRADE : From Carolina Hurricanes to Toronto Maple Leafs : Brayden Schenn (76), Dennis Seidenberg (71), Y:2021-RND:7-CAR.
[18.12.2018 22:48:53] - TRADE : From Toronto Maple Leafs to Boston Bruins : Antoine Vermette (68), Ivan Morozov (P), Joey Keane (P), Y:2019-RND:7-TOR.
[18.12.2018 22:48:53] - TRADE : From Boston Bruins to Toronto Maple Leafs : David Perron (74).
[12.12.2018 21:34:42] - TRADE : From Toronto Maple Leafs to Boston Bruins : David Perron (74).
[12.12.2018 21:34:42] - TRADE : From Boston Bruins to Toronto Maple Leafs : Ivan Morozov (P), Joey Keane (P).
[12.12.2018 21:21:50] - TRADE : From Toronto Maple Leafs to Boston Bruins : Joey Keane (P), Ivan Morozov (P).
[12.12.2018 21:21:50] - TRADE : From Boston Bruins to Toronto Maple Leafs : David Perron (74).
[08.11.2018 21:34:03] - TRADE : From Toronto Maple Leafs to Montreal Canadiens : Greg Carey (63).
[08.11.2018 21:34:03] - TRADE : From Montreal Canadiens to Toronto Maple Leafs : 200.000 € (Money).
[05.11.2018 23:13:26] - TRADE : From Toronto Maple Leafs to New York Islanders : Jan Jenik (P), Y:2019-RND:3-CAR.
[05.11.2018 23:13:26] - TRADE : From New York Islanders to Toronto Maple Leafs : Mikko Koivu (76).
[14.10.2018 00:00:55] - TRADE : From Toronto Maple Leafs to Boston Bruins : Y:2019-RND:4-TOR, Y:2019-RND:4-NYR.
[14.10.2018 00:00:55] - TRADE : From Boston Bruins to Toronto Maple Leafs : Thomas Vanek (71).
[02.10.2018 18:41:31] - Mississauga Wolves hired Lindy Ruff for 250.000 € for 1 year(s).
[22.09.2018 12:02:31] - Toronto Maple Leafs hired Dave Hakstol for 750.000 € for 1 year(s).
[22.09.2018 12:02:17] - Toronto Maple Leafs fired Lindy Ruff.
[20.09.2018 17:32:26] - TRADE : From Toronto Maple Leafs to Detroit Red Wings : Fredrik Claesson (66), Joe Cannata (66).
[20.09.2018 17:32:26] - TRADE : From Detroit Red Wings to Toronto Maple Leafs : Y:2019-RND:4-STL.
[17.09.2018 08:11:37] - TRADE : From Toronto Maple Leafs to Winnipeg Jets : Laurent Dauphin (61).
[17.09.2018 08:11:37] - TRADE : From Winnipeg Jets to Toronto Maple Leafs : David Hrenak (P), Kevin Elgestal (P).
[13.09.2018 19:12:13] - Ryan Miller signed with Toronto Maple Leafs for 4.000.000 € for 1 year(s) with 0 € in bonus.
[13.09.2018 19:12:13] - Ryan Miller was added to Toronto Maple Leafs.

[23.04.2019 23:13:35] Luca Sbisa from Toronto Maple Leafs is back from Sore Right Knee Injury.
[23.04.2019 23:13:25] Auto Lines Partial Function has been run for Toronto Maple Leafs.
[23.04.2019 23:13:25] Auto Roster Partial Function has been run for Toronto Maple Leafs.
[23.04.2019 23:13:25] Toronto Maple Leafs roster errors : Not enough Goalie available in Pro Team! 1 Dressed. 2 Required. Some errors will be automatically fixed.
[22.04.2019 22:32:30] Ondrej Pavelec from Toronto Maple Leafs is back from Exhaustion.
[17.04.2019 21:43:57] Ondrej Pavelec from Toronto Maple Leafs injured (Exhaustion)
[17.04.2019 21:43:57] Game 30 - Ondrej Pavelec from Toronto Maple Leafs is injured (Bruised Right Foot) and is out for 3 days.
[15.04.2019 22:55:24] Successfully loaded Toronto Maple Leafs lines done with STHS Client - 3.1.7.7
[14.04.2019 21:24:21] Chris Wideman from Toronto Maple Leafs is back from Right Knee Injury.
[14.04.2019 00:24:33] Game 14 - Chris Wideman from Toronto Maple Leafs is injured (Right Knee) and is out for 1 week.
[14.04.2019 00:24:27] Auto Lines Partial Function has been run for Toronto Maple Leafs.
[14.04.2019 00:24:27] Auto Roster Partial Function has been run for Toronto Maple Leafs.
[14.04.2019 00:24:27] Chris Wideman of Toronto Maple Leafs was sent to pro.
[14.04.2019 00:24:27] Toronto Maple Leafs roster errors : Not enough Defenseman available in Pro Team! 5 Dressed. 6 Required. Not enough Players available in Pro Team! 17 Dressed. 18 Required. Some errors will be automatically fixed.
[11.04.2019 22:32:32] Game 6 - Luca Sbisa from Toronto Maple Leafs is injured (Sore Right Knee) and is out for 2 weeks.
[11.04.2019 22:32:28] Auto Lines Partial Function has been run for Toronto Maple Leafs.
[11.04.2019 22:32:28] Auto Roster Partial Function has been run for Toronto Maple Leafs.
[11.04.2019 22:32:28] Toronto Maple Leafs roster errors : Not enough Defenseman available in Pro Team! 5 Dressed. 6 Required. Not enough Players available in Pro Team! 17 Dressed. 18 Required. Some errors will be automatically fixed.
[08.04.2019 23:05:40] Brian Boyle from Toronto Maple Leafs is back from Bruised Right Arm Injury.
[08.04.2019 23:04:19] Marc Staal from Toronto Maple Leafs is back from Exhaustion.
[07.04.2019 22:43:11] Marc Staal from Toronto Maple Leafs is injured from Exhaustion.
[07.04.2019 22:42:59] Auto Lines Partial Function has been run for Toronto Maple Leafs.
[07.04.2019 22:42:59] Auto Roster Partial Function has been run for Toronto Maple Leafs.
[07.04.2019 22:42:59] Toronto Maple Leafs roster errors : Not enough Defenseman available in Pro Team! 5 Dressed. 6 Required. Not enough Players available in Pro Team! 17 Dressed. 18 Required. Some errors will be automatically fixed.
[06.04.2019 23:05:44] Marc Staal from Toronto Maple Leafs is back from Exhaustion.
[05.04.2019 22:44:47] Marc Staal from Toronto Maple Leafs is injured from Exhaustion.
[02.04.2019 21:16:51] Ryan Miller from Toronto Maple Leafs is back from Exhaustion.

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	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
2018	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46
Total Séries	5	1	4	0	0	0	0	0	12	20	-8	2	1	1	0	0	0	0	0	6	8	-2	3	0	3	0	0	0	0	0	6	12	-6	2	12	22	34	0	0	5	0	6	1	158	59	35	57	7	185	56	37	106	11	2	18.18%	17	4	76.47%	0	58	115	50.43%	59	129	45.74%	43	80	53.75%	113	65	123	49	93	46