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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	Gabriel Landeskog	X	X			100.00	81	55	80	84	79	87	93	97	85	88	91	60	53	73	74	0	92	84	0
2	Mark Scheifele	X				98.99	69	43	86	87	77	89	88	89	83	88	91	67	69	68	70	0	81	84	0
3	Matthew Tkachuk		X	X		99.00	78	57	78	85	75	77	91	87	39	87	89	58	25	60	60	0	86	81	0
4	Rickard Rakell		X			99.00	77	54	88	87	74	79	90	80	37	78	77	67	63	66	68	0	91	77	0
5	Clayton Keller	X	X	X		100.00	59	40	90	89	62	79	99	90	38	80	70	54	25	63	63	0	91	74	0
6	Michael Grabner		X			100.00	69	42	93	88	69	68	78	60	37	63	73	89	25	72	73	0	84	73	0
7	Radek Faksa	X	X			100.00	78	58	81	82	81	74	97	66	89	65	71	86	25	63	64	0	86	73	0
8	William Nylander	X		X		100.00	61	41	90	87	70	72	85	76	83	78	64	56	25	60	61	0	88	70	0
9	Ryan Donato	X	X			100.00	63	41	96	80	67	66	75	75	37	72	71	53	63	50	51	0	91	70	0
10	Conor Garland		X	X		100.00	69	41	91	77	60	63	77	80	53	60	79	54	75	58	58	0	91	69	0
11	Johan Larsson	X				100.00	80	54	85	78	71	68	94	62	90	60	58	90	25	65	65	0	84	68	0
12	Ryan Hartman	X		X		100.00	78	56	75	83	67	64	98	60	32	63	66	69	25	60	61	0	91	67	0
13	Ryan McDonagh (A)				X	100.00	77	44	87	86	78	85	90	63	25	72	51	92	25	73	79	0	88	80	0
14	Josh Manson				X	100.00	90	60	76	82	79	85	94	60	25	54	48	93	25	65	66	0	84	75	0
15	Colton Parayko				X	100.00	81	56	93	87	88	87	98	68	25	58	54	82	45	66	67	0	91	75	0
16	P.K. Subban				X	100.00	73	44	74	90	76	86	90	82	25	67	56	76	25	73	77	0	85	75	0
17	Scott Mayfield				X	100.00	80	78	76	74	86	77	80	62	25	55	48	85	25	57	57	0	92	72	0
18	Mark Borowiecki				X	100.00	99	99	55	68	79	68	70	60	25	48	47	88	25	65	66	0	77	69	0
Rayé
1	Kyle Brodziak	X				100.00	78	54	86	72	77	61	93	61	88	54	59	85	25	81	84	0	23	66	0
2	Stefan Noesen		X	X		100.00	88	46	80	74	75	64	74	64	41	61	58	69	25	55	56	0	31	66	0
3	Vince Dunn				X	100.00	67	52	83	85	73	74	94	77	25	64	58	58	25	54	54	0	71	68	0

	MOYENNE D'ÉQUIPE					99.81	76	53	83	82	74	75	88	72	48	67	66	73	35	64	65	0	81	73

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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	Carey Price	97.00	84	87	85	84	80	89	70	86	86	85	91	75	78	0	83	84	0
2	Marcus Hogberg	100.00	65	67	84	87	64	67	64	71	66	66	30	44	44	0	89	70	0
Rayé

	MOYENNE D'ÉQUIPE	98.50	75	77	85	86	72	78	67	79	76	76	61	60	61	0	86	77

Nom du Coach	PH	DF	OF	PD	EX	LD	PO	CNT	Âge	Contrat	Salaire
Patrick Roy	55	60	85	80	70	70	70	CAN	53	7	2,000,000$

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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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPS	PPM	PKS	PKM	GW	FO%	FOT	P/20	S1	S2	S3
1	Josh Manson	Flyers	D	2	0	2	2	1	10	3	2	3	0	0	0.00%	1	43	21.71	2	10	0	8	0	0.00%	0	0.92	0	0	0
2	Gabriel Landeskog	Flyers	C/LW	2	1	1	2	2	0	7	12	13	5	7	7.69%	0	37	18.90	3	11	0	0	0	60.61%	66	1.06	0	1	0
3	Radek Faksa	Flyers	C/LW	2	2	0	2	2	0	5	8	4	0	1	50.00%	1	30	15.14	0	0	0	10	1	60.78%	51	1.32	1	0	0
4	Michael Grabner	Flyers	LW	2	0	1	1	2	2	2	6	1	1	2	0.00%	1	30	15.49	0	1	0	10	0	0.00%	0	0.65	0	0	0
5	Rickard Rakell	Flyers	LW	2	1	0	1	1	2	3	3	6	2	5	16.67%	0	40	20.10	2	10	1	10	0	0.00%	4	0.50	0	0	1
6	Scott Mayfield	Flyers	D	2	0	1	1	2	2	1	3	0	0	0	0.00%	2	35	17.77	0	2	0	12	0	0.00%	0	0.56	0	0	0
7	Colton Parayko	Flyers	D	2	0	1	1	0	4	1	2	3	1	2	0.00%	0	47	23.98	1	9	0	11	0	0.00%	0	0.42	0	0	0
8	William Nylander	Flyers	C/RW	2	0	0	0	2	0	0	1	6	1	1	0.00%	0	31	15.61	3	10	0	0	0	0.00%	3	0.00	0	0	0
9	Matthew Tkachuk	Flyers	LW/RW	2	0	0	0	-3	0	5	5	0	1	2	0.00%	0	38	19.23	0	10	0	1	0	0.00%	2	0.00	0	0	0
10	Ryan Hartman	Flyers	C/RW	2	0	0	0	0	2	0	4	0	0	0	0.00%	0	9	4.53	0	1	0	0	0	100.00%	1	0.00	0	0	0
11	Clayton Keller	Flyers	C/LW/RW	2	0	0	0	-2	0	3	3	3	1	6	0.00%	0	35	17.61	1	8	0	0	0	0.00%	2	0.00	0	0	0
12	Ryan McDonagh	Flyers	D	2	0	0	0	-1	2	4	3	3	2	1	0.00%	3	48	24.39	1	10	0	11	0	0.00%	0	0.00	0	0	0
13	Conor Garland	Flyers	LW/RW	2	0	0	0	2	0	0	1	3	0	3	0.00%	0	20	10.20	0	0	0	0	0	100.00%	1	0.00	0	0	0
14	Johan Larsson	Flyers	C	2	0	0	0	0	0	3	5	1	0	1	0.00%	1	18	9.03	0	0	1	11	0	63.64%	22	0.00	0	0	0
15	Mark Scheifele	Flyers	C	2	0	0	0	-3	0	1	12	4	1	5	0.00%	0	31	15.53	1	8	0	0	0	46.51%	43	0.00	0	0	0
16	Mark Borowiecki	Flyers	D	2	0	0	0	2	4	5	2	1	0	2	0.00%	3	24	12.43	0	1	0	1	0	0.00%	0	0.00	0	0	0
17	P.K. Subban	Flyers	D	2	0	0	0	-2	2	4	0	4	1	5	0.00%	1	39	19.62	3	9	0	0	0	0.00%	0	0.00	0	0	0
18	Ryan Donato	Flyers	C/LW	2	0	0	0	0	2	0	1	1	0	0	0.00%	0	6	3.33	0	0	0	0	0	0.00%	0	0.00	0	0	0
Stats d'équipe Total ou en Moyenne				36	4	6	10	5	32	47	73	56	16	43	7.14%	13	569	15.81	17	108	2	90	1	54.87%	195	0.35	1	1	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	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Carey Price	Flyers	2	1	1	0	0.951	1.51	119	0	0	3	61	0	0	0	0.000	0	2	0	0	1	0
Stats d'équipe Total ou en Moyenne			2	1	1	0	0.951	1.51	119	0	0	3	61	0	0	0	0.000	0	2	0	0	1	0

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Astuces sur les Filtres (Anglais seulement)

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

Nom du Joueur	Nom de l'Équipe	POS	Âge	Date de Naissance	Nouveau Joueur	Poids	Taille	Non-Échange	Disponible pour Échange	Ballotage Forcé	Contrat	Status	Type	Salaire Actuel	Cap Salariale	Cap Salariale Restant	Exclus du Cap Salarial	Link
Carey Price	Flyers	G	32	1987-08-15	No	215 Lbs	6 ft3	No	No	Yes	6	Sans Restriction	Pro & Farm	10,500,000$	10,500,000$	8,250,000$	No	Lien
Clayton Keller	Flyers	C/LW/RW	21	1998-07-29	No	170 Lbs	5 ft10	No	No	No	2	Avec Restriction	Pro & Farm	885,833$	885,833$	696,012$	No	Lien
Colton Parayko	Flyers	D	26	1993-05-12	No	230 Lbs	6 ft6	No	No	Yes	4	Avec Restriction	Pro & Farm	5,500,000$	5,500,000$	4,321,429$	No	Lien
Conor Garland	Flyers	LW/RW	24	1996-03-11	No	165 Lbs	5 ft10	No	No	No	1	Avec Restriction	Pro & Farm	680,000$	680,000$	534,286$	No	Lien
Gabriel Landeskog	Flyers	C/LW	27	1992-11-23	No	215 Lbs	6 ft1	No	No	Yes	3	Sans Restriction	Pro & Farm	5,571,429$	5,571,429$	4,377,551$	No	Lien
Johan Larsson	Flyers	C	27	1992-07-25	No	198 Lbs	5 ft11	No	No	Yes	1	Sans Restriction	Pro & Farm	1,450,000$	1,450,000$	1,139,286$	No	Lien
Josh Manson	Flyers	D	28	1991-10-07	No	213 Lbs	6 ft3	No	No	Yes	4	Sans Restriction	Pro & Farm	4,100,000$	4,100,000$	3,221,429$	No	Lien
Kyle Brodziak	Flyers	C	35	1984-05-25	No	209 Lbs	6 ft2	No	No	Yes	2	Sans Restriction	Pro & Farm	1,150,000$	1,150,000$	903,571$	No	Lien
Marcus Hogberg	Flyers	G	25	1994-11-24	No	209 Lbs	6 ft5	No	No	No	1	Avec Restriction	Pro & Farm	835,000$	835,000$	656,071$	No	Lien
Mark Borowiecki	Flyers	D	30	1989-07-12	No	207 Lbs	6 ft1	No	No	Yes	2	Sans Restriction	Pro & Farm	1,200,000$	1,200,000$	942,857$	No	Lien
Mark Scheifele	Flyers	C	27	1993-03-14	No	207 Lbs	6 ft3	No	No	Yes	6	Sans Restriction	Pro & Farm	6,125,000$	6,125,000$	4,812,500$	No	Lien
Matthew Tkachuk	Flyers	LW/RW	22	1997-12-11	No	202 Lbs	6 ft2	No	No	No	1	Avec Restriction	Pro & Farm	925,000$	925,000$	726,786$	No	Lien
Michael Grabner	Flyers	LW	32	1987-10-05	No	188 Lbs	6 ft1	No	No	Yes	3	Sans Restriction	Pro & Farm	3,350,000$	3,350,000$	2,632,143$	No	Lien
P.K. Subban	Flyers	D	30	1989-05-12	No	210 Lbs	6 ft0	No	No	Yes	4	Sans Restriction	Pro & Farm	9,000,000$	9,000,000$	7,071,429$	No	Lien
Radek Faksa	Flyers	C/LW	26	1994-01-08	No	216 Lbs	6 ft3	No	No	Yes	2	Avec Restriction	Pro & Farm	2,200,000$	2,200,000$	1,728,571$	No	Lien
Rickard Rakell	Flyers	LW	26	1993-05-05	No	198 Lbs	6 ft2	No	No	Yes	4	Avec Restriction	Pro & Farm	3,789,444$	3,789,444$	2,977,420$	No	Lien
Ryan Donato	Flyers	C/LW	24	1996-04-09	No	181 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	900,000$	900,000$	707,143$	No	Lien
Ryan Hartman	Flyers	C/RW	25	1994-09-20	No	181 Lbs	6 ft0	No	No	No	1	Avec Restriction	Pro & Farm	875,000$	875,000$	687,500$	No	Lien
Ryan McDonagh	Flyers	D	30	1989-06-12	No	215 Lbs	6 ft1	No	No	Yes	6	Sans Restriction	Pro & Farm	4,700,000$	4,700,000$	3,692,857$	No	Lien
Scott Mayfield	Flyers	D	27	1992-10-14	No	227 Lbs	6 ft4	No	No	Yes	5	Sans Restriction	Pro & Farm	1,450,000$	1,450,000$	1,139,286$	No	Lien
Stefan Noesen	Flyers	LW/RW	27	1993-02-12	No	205 Lbs	6 ft1	No	No	Yes	1	Sans Restriction	Pro & Farm	1,725,000$	1,725,000$	1,355,357$	No	Lien
Vince Dunn	Flyers	D	23	1996-10-28	No	203 Lbs	6 ft0	No	No	No	2	Avec Restriction	Pro & Farm	722,500$	722,500$	567,679$	No	Lien
William Nylander	Flyers	C/RW	23	1996-05-01	No	191 Lbs	6 ft0	No	No	Yes	6	Avec Restriction	Pro & Farm	10,277,778$	10,277,778$	8,075,397$	No	Lien

Joueurs Total	Âge Moyen	Poids Moyen	Taille Moyenne	Contrat Moyen	Salaire Moyen 1e Année
23	26.83	202 Lbs	6 ft1	2.96	3,387,478$

Somme Salaire 1e Année	Somme Salaire 2e Année	Somme Salaire 3e Année	Somme Salaire 4e Année	Somme Salaire 5e Année
77,911,984$	70,521,984$	64,363,651$	55,442,222$	33,052,778$

Attaque à 5 contre 5
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Clayton Keller	Mark Scheifele	Matthew Tkachuk	32	1	2	2
2	Rickard Rakell	Gabriel Landeskog	William Nylander	31	1	2	2
3	Michael Grabner	Radek Faksa	Conor Garland	26	1	2	2
4	Ryan Donato	Johan Larsson	Ryan Hartman	11	1	1	3

Défense à 5 contre 5
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	P.K. Subban	Ryan McDonagh	33	1	2	2
2	Josh Manson	Colton Parayko	33	1	2	2
3	Mark Borowiecki	Scott Mayfield	29	1	2	2
4	Mark Borowiecki	Scott Mayfield	5	1	2	2

Attaque en Avantage Numérique
Ligne #	Ailier Gauche	Centre	Ailier Droit	% Temps	PHY	DF	OF
1	Rickard Rakell	Mark Scheifele	Matthew Tkachuk	50	1	2	2
2	Clayton Keller	Gabriel Landeskog	William Nylander	50	1	2	2

Défense en Avantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	P.K. Subban	Colton Parayko	50	1	2	2
2	Josh Manson	Ryan McDonagh	50	1	2	2

Attaque à 4 en Désavantage Numérique
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Radek Faksa	Michael Grabner	50	1	2	2
2	Johan Larsson	Rickard Rakell	50	1	2	2

Défense à 4 en Désavantage Numérique
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Colton Parayko	Ryan McDonagh	50	1	2	2
2	Josh Manson	Scott Mayfield	50	1	2	2

3 joueurs en Désavantage Numérique
Ligne #	Ailier	% Temps	PHY	DF	OF	Défense	Défense	% Temps	PHY	DF	OF
1	Michael Grabner	50	1	2	2	Colton Parayko	Ryan McDonagh	50	1	2	2
2	Radek Faksa	50	1	2	2	Josh Manson	Scott Mayfield	50	1	2	2

Attaque à 4 contre 4
Ligne #	Centre	Ailier	% Temps	PHY	DF	OF
1	Mark Scheifele	Matthew Tkachuk	50	1	2	2
2	Gabriel Landeskog	Clayton Keller	50	1	2	2

Défense à 4 contre 4
Ligne #	Défense	Défense	% Temps	PHY	DF	OF
1	Josh Manson	Ryan McDonagh	50	1	2	2
2	P.K. Subban	Colton Parayko	50	1	2	2

Attaque Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Gabriel Landeskog	Mark Scheifele	Matthew Tkachuk	P.K. Subban	Colton Parayko

Défense Dernière Minute
Ailier Gauche	Centre	Ailier Droit	Défense	Défense
Michael Grabner	Johan Larsson	Radek Faksa	Josh Manson	Ryan McDonagh

Attaquants Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
Mark Scheifele, Gabriel Landeskog, Matthew Tkachuk	Mark Scheifele, Gabriel Landeskog	Michael Grabner

Défenseurs Supplémentaires
Normal	Avantage Numérique	Désavantage Numérique
P.K. Subban, Ryan McDonagh, Colton Parayko	P.K. Subban	Colton Parayko, Ryan McDonagh

Tirs de Pénalité
Conor Garland, Mark Scheifele, Rickard Rakell, Ryan Donato, Gabriel Landeskog

Gardien
#1 : Carey Price, #2 : Marcus Hogberg

Lignes d'Attaque Perso. en Prol.
Mark Scheifele, Matthew Tkachuk, Gabriel Landeskog, Clayton Keller, Rickard Rakell, William Nylander, William Nylander, Conor Garland, Ryan Donato, Michael Grabner, Radek Faksa

Lignes de Défense Perso. en Prol.
P.K. Subban, Ryan McDonagh, Josh Manson, Colton Parayko, Scott Mayfield

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	Rangers	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12
	Total	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12
	_Since Last GM Reset	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12
	_Vs Conference	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12
	_Vs Division	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	0.500	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12

			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
2	2	W1	4	6	10	56	61	13	32	47	0	0

Tous les Matchs
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	4	3

Matchs locaux
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	4	3

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

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

Tentatives en Avantage Numérique	Buts en Avantage Numérique	% en Avantage Numérique	Tentatives en Désavantage Numérique	Buts Contre en Désavantage Numérique	% en Désavantage Numérique	Buts Pour en Désavantage Numérique
13	0	0.00%	13	0	100.00%	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
13	24	19	0	0	1	3	0

Mises en Jeu
Gagnées en Zone Offensive	Total en Zone Offensive	% Gagnées en Zone Offensive	Gagnées en Zone Défensive	Total en Zone Défensive	% Gagnées en Zone Défensive	Gagnées en Zone Neutre	Total en Zone Neutre	% Gagnées en Zone Neutre
44	85	51.76%	46	79	58.23%	17	31	54.84%

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
52	34	42	14	25	12

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	Lien
1 - 2019-09-19	4	Rangers	1	Flyers	0	L	Sommaire du Match
3 - 2019-09-21	12	Rangers	2	Flyers	4	W	Sommaire du Match
5 - 2019-09-23	20	Flyers	-	Rangers	-
7 - 2019-09-25	28	Flyers	-	Rangers	-
9 - 2019-09-27	36	Rangers	-	Flyers	-
11 - 2019-09-29	44	Flyers	-	Rangers	-
13 - 2019-10-01	52	Rangers	-	Flyers	-

Capacité de l'Aréna - Tendance du Prix des Billets - %
	Niveau 1	Niveau 2	Niveau 3	Niveau 4	Luxe
Capacité de l'Aréna	6000	5000	2000	4000	1000
Prix des Billets	100	60	35	25	200
Assistance	12,000	10,000	4,000	8,000	2,000
Attendance PCT	100.00%	100.00%	100.00%	100.00%	100.00%

Revenus
Matchs à domicile Restants	Assistance Moyenne - %	Revenus Moyen par Match	Revenus Annuels à ce Jour	Capacité de l'Aréna	Popularité de l'Équipe
39	18000 - 100.00%	1,892,300$	3,784,600$	18000	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$	77,911,984$	77,111,983$	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$	11	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$	5,207,502$	5,207,502$

Charte de Profondeur

Ailier Gauche

Centre

Ailier Droit

Gabriel Landeskog	AGE:27	PO:0	OV:84
Matthew Tkachuk	AGE:22	PO:0	OV:81
Rickard Rakell	AGE:26	PO:0	OV:77
Clayton Keller	AGE:21	PO:0	OV:74
Michael Grabner	AGE:32	PO:0	OV:73
Radek Faksa	AGE:26	PO:0	OV:73
Ryan Donato	AGE:24	PO:0	OV:70
Conor Garland	AGE:24	PO:0	OV:69
*Carl Grundstrom	AGE:22	PO:0	OV:68
Stefan Noesen	AGE:27	PO:0	OV:66
Brendan Lemieux	AGE:24	PO:0	OV:65
Warren Foegele	AGE:24	PO:0	OV:65
*Victor Olofsson	AGE:24	PO:0	OV:59
Dominic Turgeon	AGE:24	PO:0	OV:52

Gabriel Landeskog	AGE:27	PO:0	OV:84
Mark Scheifele	AGE:27	PO:0	OV:84
Clayton Keller	AGE:21	PO:0	OV:74
Radek Faksa	AGE:26	PO:0	OV:73
William Nylander	AGE:23	PO:0	OV:70
Ryan Donato	AGE:24	PO:0	OV:70
Johan Larsson	AGE:27	PO:0	OV:68
Ryan Hartman	AGE:25	PO:0	OV:67
Kyle Brodziak	AGE:35	PO:0	OV:66
Steven Fogarty	AGE:26	PO:0	OV:57
Dominic Turgeon	AGE:24	PO:0	OV:52

Matthew Tkachuk	AGE:22	PO:0	OV:81
Clayton Keller	AGE:21	PO:0	OV:74
William Nylander	AGE:23	PO:0	OV:70
Conor Garland	AGE:24	PO:0	OV:69
*Carl Grundstrom	AGE:22	PO:0	OV:68
Ryan Hartman	AGE:25	PO:0	OV:67
Stefan Noesen	AGE:27	PO:0	OV:66
Brendan Lemieux	AGE:24	PO:0	OV:65
Warren Foegele	AGE:24	PO:0	OV:65
Brett Ritchie	AGE:26	PO:0	OV:63
*Kailer Yamamoto	AGE:21	PO:0	OV:63
*Victor Olofsson	AGE:24	PO:0	OV:59
Steven Fogarty	AGE:26	PO:0	OV:57

Défense #1

Défense #2

Gardien

Ryan McDonagh	AGE:30	PO:0	OV:80
Josh Manson	AGE:28	PO:0	OV:75
Colton Parayko	AGE:26	PO:0	OV:75
P.K. Subban	AGE:30	PO:0	OV:75
Scott Mayfield	AGE:27	PO:0	OV:72

Mark Borowiecki	AGE:30	PO:0	OV:69
Vince Dunn	AGE:23	PO:0	OV:68
Rasmus Andersson	AGE:23	PO:0	OV:65
Philippe Myers	AGE:23	PO:0	OV:63

Carey Price	AGE:32	PO:0	OV:84
Marcus Hogberg	AGE:25	PO:0	OV:70
Thatcher Demko	AGE:24	PO:0	OV:65

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
Adam Fox	Flyers	2016	66
Alexandre Carrier	Flyers
Andrei Mironov	Flyers
Antoine Waked	Flyers
Anton Karlsson	Flyers	2014	87	W
Arsen Khisamutdinov	Flyers	13	182
Arttu Ruostsalainen	Flyers
Beau Starrett	Flyers	2014	88	LW
Cale Fleury	Flyers
Carl Neill	Flyers	2015	144
Christopher Wilkie	Flyers	2015	162
Cole Fonstad	Flyers	12	136
Dylan Sadowy	Flyers
Egor Afanasyev	Flyers	13	40
Ilya Nikolaev	Flyers	13	74
Ivan Morozov	Flyers	12	69
Jack Drury	Flyers	12	49
Jack McBain	Flyers	12	61
Jake Evans	Flyers
James Greenway	Flyers	2016	72	D
Jason Robertson	Flyers	2017	39
Jeremiah Addison	Flyers	2015	207
John St. Ivany	Flyers	12	114
Jon Gillies	Flyers
Jonathan Davidson	Flyers
Josh Norris	Flyers	2017	19
Julius Bergman	Flyers
K'Andre Miller	Flyers	12	18
Kaapo Kahkonen	Flyers
Kale Howarth	Flyers
Kieran Ruscheinski	Flyers	13	186
Liam Coughlin	Flyers	2014	130
Linus Hultstrom	Flyers			D
Logan Hutsko	Flyers	12	111
Logan Neaton	Flyers	13	181
Marcus Kallionkieli	Flyers	13	180
Marshall Warren	Flyers	13	185
Matias Maccelli	Flyers	13	118
Michael McNiven	Flyers
Mikhael Berdin	Flyers	12	198
Mikko Kokkonen	Flyers	13	87
Nick Abruzzese	Flyers	13	157
Niklas Nordgren	Flyers	12	76
Nolan Foote	Flyers	13	24
Oleg Sosunov	Flyers
Patrick Bajkov	Flyers
Peyton Krebs	Flyers	13	17
Rasmus Asplund	Flyers
Rem Pitlick	Flyers	2016	76
Roman Bychkov	Flyers	13	166
Ronnie Attard	Flyers	13	81
Ryan MacInnis	Flyers
Sampo Ranta	Flyers	12	80
Samuel Fagemo	Flyers	13	55
Scott Reedy	Flyers
Shane Bowers	Flyers	2017	28
Stephane Leblanc	Flyers
Timothy Liljegren	Flyers
Ty Emberson	Flyers	12	85
Ty Ronning	Flyers
Vladislav Yeryomenko	Flyers	12	170
Ziyat Paigin	Flyers	2015	209	D

Choix au Repêchage

Année	R1	R2	R3	R4	R5	R6	R7
14	PHI CLB	PHI WSH COL ARZ PIT	PHI	PHI	WIN	PHI STL	PHI NJD NYI CHI
15	PHI	PHI	PHI	PHI DET	PHI EDM	PHI	PHI
16	PHI	PHI	PHI	PHI	PHI NYR	PHI	PHI
17	PHI	PHI	PHI	PHI	PHI	PHI	PHI
18	PHI	PHI	PHI	PHI	PHI	PHI	PHI

[2020-04-03 09:21:30] - New Record for Team's Most Penalties Minutes (61) in 1 Game for Flyers!
[2020-03-22 12:42:19] - TRADE : From Sharks to Flyers : Stefan Noesen (66).
[2020-02-21 14:01:29] - TRADE : From Flyers to Oilers : Tage Thompson (65), Carter Verhaeghe (P), Igor Rykov (P).
[2020-02-21 14:01:29] - TRADE : From Oilers to Flyers : Radek Faksa (73), Y:15-RND:5-EDM.
[2020-01-21 08:45:21] - New Record for Team's Most Hits (52) in 1 Game for Flyers!
[2019-12-05 00:06:42] - TRADE : From Rangers to Flyers : Y:16-RND:5-NYR.
[2019-12-05 00:06:42] - TRADE : From Flyers to Rangers : Charlie Lindgren (59).
[2019-11-22 13:04:29] - Kyle Brodziak was added to Flyers.
[2019-11-22 13:04:29] - Flyers claimed Kyle Brodziak from waivers by Stars for 0 $.
[2019-11-22 13:04:15] - Flyers show interest in Kyle Brodziak from waiver.
[2019-10-14 19:52:50] - TRADE : From Flyers to Golden Knights : Michael McCarron (P).
[2019-10-14 19:52:50] - TRADE : From Golden Knights to Flyers : Brett Ritchie (63).
[2019-10-09 21:36:21] - TRADE : From Red Wings to Flyers : Y:15-RND:4-DET.
[2019-10-09 21:36:21] - TRADE : From Flyers to Red Wings : Pontus Aberg (69).
[2019-09-30 20:26:16] - Nikolas Koberstein has been deleted from Flyers.
[2019-09-30 20:26:08] - Liam Hawel has been deleted from Flyers.
[2019-09-30 20:25:58] - Tyler Boland has been deleted from Flyers.
[2019-09-30 20:25:51] - Simon Bourque has been deleted from Flyers.
[2019-09-30 20:25:42] - Olivier LeBlanc has been deleted from Flyers.
[2019-09-30 20:25:32] - Brendan Burke has been deleted from Flyers.
[2019-09-30 20:25:26] - Alexis Vanier has been deleted from Flyers.
[2019-09-24 21:32:07] - TRADE : From Flyers to Avalanche : Nick Foligno (76).
[2019-09-24 21:32:07] - TRADE : From Avalanche to Flyers : Y:14-RND:2-COL.
[2019-09-19 23:06:31] - TRADE : From Flyers to Capitals : Brent Burns (82), Y:14-RND:5-PHI.
[2019-09-19 23:06:31] - TRADE : From Capitals to Flyers : P.K. Subban (75), Y:14-RND:2-WSH.
[2019-07-10 19:22:07] - Arttu Ruostsalainen has been added to Flyers.
[2019-07-05 16:23:59] - TRADE : From Flyers to Wild : Arseny Gritsyuk (P).
[2019-07-05 16:23:59] - TRADE : From Wild to Flyers : Arsen Khisamutdinov (P).
[2019-07-05 16:23:27] - Flyers drafts Arseny Gritsyuk as the #211 overall pick in the Entry Draft of year 13.
[2019-07-04 22:09:01] - Josh Wesley has been deleted from Flyers.
[2019-07-04 22:08:52] - Radovan Bondra has been deleted from Flyers.
[2019-07-04 22:08:40] - Hunter Smith has been deleted from Flyers.
[2019-07-04 21:37:55] - Flyers drafts Kieran Ruscheinski as the #186 overall pick in the Entry Draft of year 13.
[2019-07-04 21:37:46] - Flyers drafts Marshall Warren as the #185 overall pick in the Entry Draft of year 13.
[2019-07-03 23:22:47] - Flyers drafts Logan Neaton as the #181 overall pick in the Entry Draft of year 13.
[2019-07-03 23:22:35] - Flyers drafts Marcus Kallionkieli as the #180 overall pick in the Entry Draft of year 13.
[2019-07-03 23:17:30] - Flyers drafts Roman Bychkov as the #166 overall pick in the Entry Draft of year 13.
[2019-07-03 16:56:46] - Flyers drafts Nick Abruzzese as the #157 overall pick in the Entry Draft of year 13.
[2019-07-01 21:03:17] - TRADE : From Flyers to Jets : Y:13-RND:5-PHI, Y:13-RND:7-BUF.
[2019-07-01 21:03:17] - TRADE : From Jets to Flyers : Y:13-RND:6-ANA, Y:13-RND:6-CLB, Y:13-RND:6-OTT.
[2019-06-30 22:28:37] - Flyers drafts Matias Maccelli as the #118 overall pick in the Entry Draft of year 13.
[2019-06-28 22:47:11] - Flyers drafts Mikko Kokkonen as the #87 overall pick in the Entry Draft of year 13.
[2019-06-28 22:46:11] - Flyers drafts Ronnie Attard as the #81 overall pick in the Entry Draft of year 13.
[2019-06-28 22:44:20] - Flyers drafts Ilya Nikolaev as the #74 overall pick in the Entry Draft of year 13.
[2019-06-27 22:45:19] - Flyers drafts Samuel Fagemo as the #55 overall pick in the Entry Draft of year 13.
[2019-06-26 22:59:50] - Flyers drafts Egor Afanasyev as the #40 overall pick in the Entry Draft of year 13.

[2020-04-14 07:14:08] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-12 12:29:12] Mark Scheifele from Flyers is back from Groin Injury.
[2020-04-12 12:29:12] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-12 12:29:12] Game 4 - Mark Scheifele from Flyers is injured (Groin) and is out for 4 days.
[2020-04-12 12:24:08] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-04-12 12:24:08] Stefan Noesen of Flyers was sent to pro.
[2020-04-12 12:24:08] Brett Ritchie of Flyers was sent down to farm.
[2020-04-08 13:09:29] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-07 08:29:30] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-07 08:29:27] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-03 09:21:31] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-04-03 09:21:30] New Record for Team's Most Penalties Minutes (61) in 1 Game for Flyers!
[2020-04-03 09:21:15] Successfully loaded Flyers lines done with STHS Client - 3.2.0.5
[2020-04-02 09:37:32] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-03-31 09:55:33] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-03-29 13:41:18] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-03-29 13:41:18] Last 7 Days Pro Star : 1 - Mark Scheifele of Flyers (6-0-6) / 2 - Matt Murray of Coyotes (0,965) / 3 - Reilly Smith of Senateurs (3-2-5)
[2020-03-29 13:41:17] Mark Scheifele from Flyers has scored a Hat Trick!
[2020-03-26 10:45:11] Flyers lines for next game are empty. Current rosters/lines are not erased.
[2020-03-25 10:07:10] Flyers lines for next game are empty. Current rosters/lines are not erased.

Pas de Blessure ou de Suspension.

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
Saison Régulière
12	82	41	26	0	4	5	4	2	261	229	32	41	22	11	0	2	1	4	1	135	106	29	41	19	15	0	2	4	0	1	126	123	3	82	261	462	723	2	4	90	81	82	16	2679	854	894	901	53	2584	745	859	2020	269	46	17.10%	356	65	81.74%	7	1524	2925	52.10%	1462	2832	51.62%	677	1286	52.64%	2054	1477	1927	575	988	495
13	82	47	26	0	5	1	1	2	264	218	46	41	24	14	0	2	1	0	0	120	104	16	41	23	12	0	3	0	1	2	144	114	30	109	264	452	716	1	5	104	83	71	8	2350	821	758	755	24	2251	643	1025	2151	364	72	19.78%	423	66	84.40%	2	1429	2730	52.34%	1402	2803	50.02%	671	1279	52.46%	1985	1369	1928	604	1031	513
Total Saison Régulière	164	88	52	0	9	6	5	4	525	447	78	82	46	25	0	4	2	4	1	255	210	45	82	42	27	0	5	4	1	3	270	237	33	191	525	914	1439	3	9	194	164	153	24	5029	1675	1652	1656	77	4835	1388	1884	4171	633	118	18.64%	779	131	83.18%	9	2953	5655	52.22%	2864	5635	50.83%	1348	2565	52.55%	4039	2847	3856	1180	2020	1009
Séries
12	11	6	5	0	0	0	0	0	30	32	-2	5	3	2	0	0	0	0	0	15	19	-4	6	3	3	0	0	0	0	0	15	13	2	12	30	52	82	0	1	10	10	10	0	325	95	114	116	0	348	91	208	349	58	8	13.79%	64	11	82.81%	1	214	418	51.20%	196	401	48.88%	67	159	42.14%	255	178	275	78	128	60
13	2	1	1	0	0	0	0	0	4	3	1	2	1	1	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	2	4	6	10	0	0	0	1	3	0	56	13	24	19	0	61	13	32	47	13	0	0.00%	13	0	100.00%	0	44	85	51.76%	46	79	58.23%	17	31	54.84%	52	34	42	14	25	12
Total Séries	13	7	6	0	0	0	0	0	34	35	-1	7	4	3	0	0	0	0	0	19	22	-3	6	3	3	0	0	0	0	0	15	13	2	14	34	58	92	0	1	10	11	13	0	381	108	138	135	0	409	104	240	396	71	8	11.27%	77	11	85.71%	1	258	503	51.29%	242	480	50.42%	84	190	44.21%	308	213	317	93	154	72