Canadian Hockey League

Nordiques
Home
Roster
Scoring
Contracts
Lines
Team Stats
Schedule
Depth
Career

Team Leaders

Team Stats

Injury / Suspension
No Injury or Suspension.

Team Info
	General Manager	Sebastien Lessard
	Coach	Craig Berube
	Division	Metropolitan
	Conference	Eastern
	Captain	Auston Matthews
	Assistant #1	Dylan Strome
	Assistant #2	Miro Heiskanen
Uniforms

Arena Info
	Name	Philadelphia Coliseum
	Capacity	25,000
	Attendance
	Season Tickets	10,000
Roster Info
	Pro Team	24
	Farm Team	28
	Contract Limit	52 / 50
	Prospects	9
Salary Cap
	Estimated Season Salary Cap	0$
	Available Salary Cap	90,000,000$
	Special Salary Cap Value	0$
	Players In Salary Cap	14
Finance
	Year to Date Revenue	0$
	Year To Date Expenses	0$
	Estimated Season Revenue	0$
	Estimated Season Expenses	0$
	Current Bank Account	264,687,905$
	Projected Bank Account	264,687,905$
Team History
	This Season	0-0-0 (0PTS)
	History	833-678-111 (0.514%)
	Playoff Appearances	11
	Playoff Record (W-L)	44-54
	Stanley Cup	0

Show or Hide Column

Filter Tips

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

#	Player Name	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Auston Matthews (C)	X				100.00	56	56	84	94	76	89	89	93	92	95	90	94	75	78	84	55	20	83	0	27	7	12,500,000$
2	Aliaksei Protas	X				100.00	46	66	85	84	97	82	95	81	40	79	82	89	40	70	76	75	20	77	0	23	0	0$
3	Dylan Strome (A)	X				100.00	47	50	82	92	65	84	99	86	89	93	79	67	59	78	81	55	20	77	0	27	0	0$
4	Conor Garland			X		100.00	54	43	77	89	40	86	98	70	40	71	69	74	79	80	83	50	20	70	0	28	1	5,000,000$
5	Yanni Gourde	X				100.00	85	53	72	87	42	82	82	67	85	75	60	75	73	90	86	25	23	70	0	33	0	0$
6	Brandon Tanev		X			100.00	90	46	86	79	56	77	97	56	40	52	60	81	40	90	84	25	20	67	0	33	0	0$
7	Max Domi	X				100.00	50	60	69	83	62	79	94	63	85	68	59	65	55	82	81	45	20	67	0	29	1	5,000,000$
8	Mike Amadio			X		100.00	75	49	85	80	63	78	92	60	86	58	63	75	40	80	79	50	20	67	0	28	2	2,100,000$
9	Jonny Brodzinski	X				100.00	52	51	88	80	67	74	78	60	83	51	69	66	40	86	80	35	20	65	0	31	1	800,000$
10	Martin Pospisil	X				100.00	99	54	69	80	52	77	98	58	76	61	54	67	40	74	76	65	20	65	0	25	0	0$
11	Miles Wood		X			100.00	70	60	64	76	63	74	68	54	40	49	59	61	40	82	78	45	20	61	0	29	2	2,500,000$
12	Matias Maccelli		X			100.00	43	44	87	81	52	77	81	58	40	55	62	60	40	72	75	70	20	61	0	24	5	6,000,000$
13	Martin Fehervary				X	100.00	80	54	84	78	67	82	98	59	40	60	58	87	40	74	78	65	20	73	0	25	2	2,900,000$
14	Miro Heiskanen (A)				X	100.00	48	50	86	83	64	92	77	68	40	73	62	84	60	74	83	65	20	72	0	25	0	0$
15	Alexandre Carrier				X	100.00	62	41	80	83	46	84	97	59	40	63	55	81	40	80	82	50	29	70	0	28	0	0$
16	Ilya Lyubushkin				X	100.00	65	50	82	75	65	79	98	52	40	53	52	77	40	84	82	40	20	69	0	30	2	3,500,000$
17	J.J. Moser				X	100.00	55	46	82	78	56	81	80	56	40	58	55	86	40	72	77	70	20	69	0	24	6	4,000,000$
18	Zach Whitecloud				X	100.00	77	55	80	75	70	79	94	53	40	50	57	73	40	80	80	50	20	69	0	28	3	3,500,000$
19	Brendan Smith				X	100.00	70	69	69	76	65	72	65	53	40	53	54	67	40	94	83	15	20	65	0	35	1	2,000,000$
Scratches
1	Sheldon Dries	X				100.00	71	50	79	78	45	74	64	50	70	39	62	66	40	84	79	40	20	60	0	30	1	650,000$
2	Luke Schenn				X	100.00	99	70	78	75	78	76	95	49	40	46	52	76	40	94	85	15	20	71	0	35	0	0$
Farm Team
1	Brock McGinn		X			100.00	95	46	90	80	57	74	61	58	40	53	63	81	84	84	79	40	20	66	0	30	0	0$
2	Cameron Hebig	X				100.00	55	47	80	80	50	76	66	54	70	46	62	70	40	78	77	55	20	61	0	27	0	0$
3	Mackenzie MacEachern		X			100.00	72	49	63	78	63	60	50	58	40	61	55	70	40	84	72	40	20	61	0	30	1	650,000$
4	Ross Johnston		X			100.00	99	80	57	75	87	69	72	49	40	46	52	63	40	84	77	40	20	61	0	30	1	725,000$
5	Nicolas Deslauriers		X			100.00	99	73	80	75	72	67	64	49	40	43	55	62	40	90	79	25	20	60	0	33	0	0$
6	Marat Khusnutdinov	X				100.00	57	41	85	79	47	75	94	52	79	48	55	67	40	68	72	80	20	60	0	22	2	925,000$
7	Liam O'Brien	X				100.00	99	85	54	75	71	70	62	48	40	46	50	64	40	84	77	40	20	59	0	30	1	650,000$
8	Stephen Halliday	X				100.00	59	44	76	75	75	80	70	54	70	57	52	50	73	68	74	80	20	59	0	22	2	925,000$
9	Brendan Gaunce	X				100.00	75	56	83	75	77	71	51	48	83	47	50	57	40	84	78	40	20	58	0	30	0	0$
10	Josh Leivo		X			100.00	65	52	80	79	61	60	50	58	40	49	50	54	73	86	73	35	20	57	0	31	0	0$
11	Henri Jokiharju				X	100.00	60	48	85	77	61	79	84	53	40	50	56	74	40	74	77	65	20	66	0	25	0	0$
12	Connor Carrick				X	100.00	63	63	58	81	55	67	62	58	40	50	65	65	40	84	76	40	20	63	0	30	0	0$
13	Chad Ruhwedel				X	100.00	81	45	73	75	50	55	50	41	40	45	37	70	40	92	74	20	20	60	0	34	0	0$
14	Montana Onyebuchi				X	100.00	79	86	55	75	77	68	63	32	40	29	36	66	40	72	70	70	20	60	0	24	0	0$
15	Philip Kemp				X	100.00	82	61	76	75	73	60	55	36	40	27	45	65	40	74	67	65	20	59	0	25	0	0$
16	Nick Cicek				X	100.00	81	64	68	75	67	55	50	36	40	35	37	63	40	72	64	70	20	58	0	24	0	0$
17	Craig Smith	X				100.00	62	50	78	79	65	74	83	58	40	53	63	68	64	94	84	15	20	64	0	35	0	0$
18	Matyas Sapovaliv (R)		X			100.00	76	54	84	80	71	80	70	36	40	29	43	50	99	64	72	90	20	54	0	20	0	0$
19	Jackson Cates		X			100.00	49	46	83	75	56	73	63	35	40	29	42	62	40	78	76	55	20	52	0	27	0	0$
20	Oskar Pettersson			X		100.00	52	39	82	75	70	76	66	34	40	27	41	59	40	68	72	80	20	52	0	22	2	925,000$
21	Coulson Pitre (R)			X		100.00	61	46	84	86	56	70	60	36	40	37	34	53	40	64	67	90	20	52	0	20	0	0$
22	Ostap Safin		X			100.00	83	72	83	75	76	60	50	33	40	29	36	50	40	74	67	65	20	50	0	25	0	0$
23	Artem Guryev				X	100.00	75	70	38	75	79	55	50	32	40	25	38	60	40	66	61	85	20	56	0	21	2	925,000$
24	Artyom Serikov				X	100.00	58	50	81	75	65	55	50	34	40	32	36	50	40	72	64	70	20	53	0	24	0	0$
25	Artem Grushnikov				X	100.00	58	50	82	75	63	65	60	29	40	25	32	50	40	66	66	85	20	53	0	21	2	925,000$

	TEAM AVERAGE					100.00	69	55	77	79	64	73	74	53	51	50	54	68	48	79	76	53	20	63

Show or Hide Column

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Logan Thompson	100.00	86	82	88	95	83	85	84	87	86	85	97	78	82	55	20	83	0	27	0	0$
2	Philipp Grubauer	100.00	85	62	62	85	60	56	57	60	61	60	90	90	73	25	26	65	0	33	2	3,000,000$
3	Chris Driedger	100.00	80	50	60	95	50	50	50	50	50	50	90	84	67	40	20	59	0	30	0	0$
Scratches
Farm Team
1	Louis Domingue	100.00	76	54	60	93	50	50	50	50	50	50	40	88	69	30	20	59	0	32	0	0$
2	Arvid Holm	100.00	75	50	60	96	50	50	50	50	50	50	99	76	63	60	20	58	0	26	0	0$
3	Veini Vehvilainen	100.00	76	50	60	82	50	50	50	50	50	50	40	78	64	55	20	57	0	27	0	0$

	TEAM AVERAGE	100.00	80	58	65	91	57	57	57	58	58	58	76	82	70	44	21	64

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Craig Berube	92	92	93	85	95	77	50	CAN	60	4	5,000,000$

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	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	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

Show or Hide Column

Filter Tips

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

Player Name	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Type	2039	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	2040	2041	2042	2043	2044	2045	2046	Link
Alexandre Carrier	Flyers	D	28	1996-10-08	No	174 Lbs	5 ft11	No	No	Yes	0	Pro & Farm	UFA	0$	0$	No								Link / NHL Link
Aliaksei Protas	Flyers	C	23	2001-01-06	No	247 Lbs	6 ft6	No	No	No	0	Pro & Farm	RFA	0$	0$	No								Link / NHL Link
Auston Matthews	Flyers	C	27	1997-09-17	No	217 Lbs	6 ft3	No	No	Yes	7	Pro Only	12,500,000$	12,500,000$	12,500,000$	No	12,500,000$	12,500,000$	12,500,000$	12,500,000$	12,500,000$	12,500,000$	UFA	Link / NHL Link
Brandon Tanev	Flyers	LW	33	1991-12-31	No	189 Lbs	6 ft0	No	No	Yes	0	Pro & Farm	UFA	0$	0$	No								Link / NHL Link
Brendan Smith	Flyers	D	35	1989-02-08	No	200 Lbs	6 ft2	Yes	No	No	1	Pro & Farm	2,000,000$	2,000,000$	2,000,000$	No	UFA							Link / NHL Link
Chris Driedger	Flyers	G	30	1994-05-18	No	204 Lbs	6 ft4	No	No	No	0	Pro & Farm	UFA	0$	0$	No								Link / NHL Link
Conor Garland	Flyers	RW	28	1996-03-11	No	165 Lbs	5 ft10	No	No	Yes	1	Pro Only	5,000,000$	5,000,000$	5,000,000$	No	UFA							Link / NHL Link
Dylan Strome	Flyers	C	27	1997-03-07	No	196 Lbs	6 ft3	No	No	Yes	0	Pro & Farm	RFA	0$	0$	No								Link / NHL Link
Ilya Lyubushkin	Flyers	D	30	1994-04-06	No	200 Lbs	6 ft2	No	No	Yes	2	Pro & Farm	3,500,000$	3,500,000$	3,500,000$	No	3,500,000$	UFA						Link / NHL Link
J.J. Moser	Flyers	D	24	2000-06-06	No	181 Lbs	6 ft2	No	No	Yes	6	Pro & Farm	4,000,000$	4,000,000$	4,000,000$	No	4,000,000$	4,000,000$	4,000,000$	4,000,000$	4,000,000$	UFA		Link / NHL Link
Jonny Brodzinski	Flyers	C	31	1993-06-19	No	211 Lbs	6 ft0	No	No	No	1	Pro & Farm	800,000$	800,000$	800,000$	No	UFA							Link / NHL Link
Logan Thompson	Flyers	G	27	1997-02-25	No	212 Lbs	6 ft4	No	No	Yes	0	Pro & Farm	RFA	0$	0$	No								Link / NHL Link
Luke Schenn	Flyers	D	35	1989-11-02	No	225 Lbs	6 ft2	No	No	No	0	Pro & Farm	UFA	0$	0$	No								Link / NHL Link
Martin Fehervary	Flyers	D	25	1999-10-06	No	203 Lbs	6 ft2	No	No	Yes	2	Pro & Farm	2,900,000$	2,900,000$	2,900,000$	No	2,900,000$	RFA						Link / NHL Link
Martin Pospisil	Flyers	C	25	1999-11-19	No	173 Lbs	6 ft2	No	No	No	0	Pro & Farm	RFA	0$	0$	No								Link / NHL Link
Matias Maccelli	Flyers	LW	24	2000-10-14	No	185 Lbs	5 ft11	No	No	Yes	5	Pro Only	6,000,000$	6,000,000$	6,000,000$	No	6,000,000$	6,000,000$	6,000,000$	6,000,000$	UFA			Link / NHL Link
Max Domi	Flyers	C	29	1995-03-02	No	209 Lbs	5 ft10	No	No	Yes	1	Pro Only	5,000,000$	5,000,000$	5,000,000$	No	UFA							Link / NHL Link
Mike Amadio	Flyers	RW	28	1996-05-13	No	199 Lbs	6 ft1	No	No	Yes	2	Pro & Farm	2,100,000$	2,100,000$	2,100,000$	No	2,100,000$	UFA						Link / NHL Link
Miles Wood	Flyers	LW	29	1995-09-13	No	195 Lbs	6 ft2	No	No	Yes	2	Pro & Farm	2,500,000$	2,500,000$	2,500,000$	No	2,500,000$	UFA						Link / NHL Link
Miro Heiskanen	Flyers	D	25	1999-07-18	No	197 Lbs	6 ft2	No	No	Yes	0	Pro Only	RFA	0$	0$	No								Link / NHL Link
Philipp Grubauer	Flyers	G	33	1991-11-25	No	180 Lbs	6 ft0	No	No	Yes	2	Pro & Farm	3,000,000$	3,000,000$	3,000,000$	No	3,000,000$	UFA						Link / NHL Link
Sheldon Dries	Flyers	C	30	1994-04-23	No	180 Lbs	5 ft9	No	No	No	1	Pro & Farm	650,000$	650,000$	650,000$	No	UFA							Link / NHL Link
Yanni Gourde	Flyers	C	33	1991-12-15	No	174 Lbs	5 ft9	No	No	Yes	0	Pro Only	UFA	0$	0$	No								Link / NHL Link
Zach Whitecloud	Flyers	D	28	1996-11-28	No	210 Lbs	6 ft2	No	No	Yes	3	Pro & Farm	3,500,000$	3,500,000$	3,500,000$	No	3,500,000$	3,500,000$	UFA					Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
24	28.63	197 Lbs	6 ft1	1.50	2,227,083$

Sum Year 1 Salary	Sum Year 2 Salary	Sum Year 3 Salary	Sum Year 4 Salary	Sum Year 5 Salary
53,450,000$	40,000,000$	26,000,000$	22,500,000$	22,500,000$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Auston Matthews	Dylan Strome	36	1	1	3
2	Matias Maccelli	Max Domi	Conor Garland	34	1	1	3
3	Aliaksei Protas	Mike Amadio	Martin Pospisil	20	1	2	2
4	Miles Wood	Brandon Tanev	Jonny Brodzinski	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Miro Heiskanen	J.J. Moser	40	0	2	3
2	Martin Fehervary	Ilya Lyubushkin	30	1	2	2
3	Zach Whitecloud	Brendan Smith	20	1	2	2
4	Miro Heiskanen	J.J. Moser	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Auston Matthews	Dylan Strome	60	1	1	3
2	Matias Maccelli	Max Domi	Conor Garland	40	1	1	3

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Miro Heiskanen	Brendan Smith	60	1	2	2
2	J.J. Moser	Zach Whitecloud	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Auston Matthews	Brandon Tanev	60	1	2	2
2	Aliaksei Protas	Conor Garland	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Miro Heiskanen	Brendan Smith	60	1	2	2
2	Ilya Lyubushkin	J.J. Moser	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Auston Matthews	60	1	3	1	Miro Heiskanen	Brendan Smith	60	1	3	1
2	Aliaksei Protas	40	1	3	1	Ilya Lyubushkin	J.J. Moser	40	1	3	1

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Auston Matthews	Dylan Strome	60	0	2	3
2	Conor Garland		40	0	2	3

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Miro Heiskanen	J.J. Moser	60	1	2	2
2	Brendan Smith	Zach Whitecloud	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Max Domi	Auston Matthews	Dylan Strome	Miro Heiskanen	J.J. Moser

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Max Domi	Auston Matthews	Dylan Strome	Miro Heiskanen	J.J. Moser

Extra Forwards
Normal	PowerPlay	Penalty Kill
Martin Pospisil, Aliaksei Protas, Miles Wood	Mike Amadio, Martin Pospisil	Dylan Strome

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Ilya Lyubushkin, Martin Fehervary, Zach Whitecloud	Martin Fehervary	Zach Whitecloud, Martin Fehervary

Penalty Shots
Conor Garland, , Auston Matthews, Max Domi, Dylan Strome

Goalie
#1 : Logan Thompson, #2 : Chris Driedger

Custom OT Lines Forwards
, , , , , , , , , ,

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

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

	Overall												Home											Visitor
#	VS Team	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
	Total	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
0	0	N/A	0	0	0	0	0	0	0	0	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Last 10 Games
W	L	OTW	OTL	SOW	SOL
0	0	0	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
0	0	0.00%	0	0	0.00%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
0	0	0	0	0	0	0	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
0	0	0.00%	0	0	0.00%	0	0	0.00%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
0	0	0	0	0	0

Last Played Games Show or Hide Column

Filter Tips

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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	RI	Link

Depth Chart

Left Wing

Center

Right Wing

Brandon Tanev

AGE:33
SK:		79
EN:		77
DU:		97
PH:		56
PA:		52
SC:		60
DF:		81
Brock McGinn

AGE:30
SK:		80
EN:		74
DU:		61
PH:		58
PA:		53
SC:		63
DF:		81
Matias Maccelli

AGE:24
SK:		81
EN:		77
DU:		81
PH:		58
PA:		55
SC:		62
DF:		60
Miles Wood

AGE:29
SK:		76
EN:		74
DU:		68
PH:		54
PA:		49
SC:		59
DF:		61
Mackenzie MacEachern

AGE:30
SK:		78
EN:		60
DU:		50
PH:		58
PA:		61
SC:		55
DF:		70
Ross Johnston

AGE:30
SK:		75
EN:		69
DU:		72
PH:		49
PA:		46
SC:		52
DF:		63
Nicolas Deslauriers

AGE:33
SK:		75
EN:		67
DU:		64
PH:		49
PA:		43
SC:		55
DF:		62
Josh Leivo

AGE:31
SK:		79
EN:		60
DU:		50
PH:		58
PA:		49
SC:		50
DF:		54
Matyas Sapovaliv (R)

AGE:20
SK:		80
EN:		80
DU:		70
PH:		36
PA:		29
SC:		43
DF:		50
Jackson Cates

AGE:27
SK:		75
EN:		73
DU:		63
PH:		35
PA:		29
SC:		42
DF:		62
Ostap Safin

AGE:25
SK:		75
EN:		60
DU:		50
PH:		33
PA:		29
SC:		36
DF:		50

Auston Matthews

AGE:27
SK:		94
EN:		89
DU:		89
PH:		93
PA:		95
SC:		90
DF:		94
Aliaksei Protas

AGE:23
SK:		84
EN:		82
DU:		95
PH:		81
PA:		79
SC:		82
DF:		89
Dylan Strome

AGE:27
SK:		92
EN:		84
DU:		99
PH:		86
PA:		93
SC:		79
DF:		67
Yanni Gourde

AGE:33
SK:		87
EN:		82
DU:		82
PH:		67
PA:		75
SC:		60
DF:		75
Max Domi

AGE:29
SK:		83
EN:		79
DU:		94
PH:		63
PA:		68
SC:		59
DF:		65
Martin Pospisil

AGE:25
SK:		80
EN:		77
DU:		98
PH:		58
PA:		61
SC:		54
DF:		67
Jonny Brodzinski

AGE:31
SK:		80
EN:		74
DU:		78
PH:		60
PA:		51
SC:		69
DF:		66
Craig Smith

AGE:35
SK:		79
EN:		74
DU:		83
PH:		58
PA:		53
SC:		63
DF:		68
Cameron Hebig

AGE:27
SK:		80
EN:		76
DU:		66
PH:		54
PA:		46
SC:		62
DF:		70
Marat Khusnutdinov

AGE:22
SK:		79
EN:		75
DU:		94
PH:		52
PA:		48
SC:		55
DF:		67
Sheldon Dries

AGE:30
SK:		78
EN:		74
DU:		64
PH:		50
PA:		39
SC:		62
DF:		66
Stephen Halliday

AGE:22
SK:		75
EN:		80
DU:		70
PH:		54
PA:		57
SC:		52
DF:		50
Liam O'Brien

AGE:30
SK:		75
EN:		70
DU:		62
PH:		48
PA:		46
SC:		50
DF:		64
Brendan Gaunce

AGE:30
SK:		75
EN:		71
DU:		51
PH:		48
PA:		47
SC:		50
DF:		57

Conor Garland

AGE:28
SK:		89
EN:		86
DU:		98
PH:		70
PA:		71
SC:		69
DF:		74
Mike Amadio

AGE:28
SK:		80
EN:		78
DU:		92
PH:		60
PA:		58
SC:		63
DF:		75
Coulson Pitre (R)

AGE:20
SK:		86
EN:		70
DU:		60
PH:		36
PA:		37
SC:		34
DF:		53
Oskar Pettersson

AGE:22
SK:		75
EN:		76
DU:		66
PH:		34
PA:		27
SC:		41
DF:		59

Defense #1

Defense #2

Goalie

Martin Fehervary

AGE:25
SK:		78
EN:		82
DU:		98
PH:		59
PA:		60
SC:		58
DF:		87
Miro Heiskanen

AGE:25
SK:		83
EN:		92
DU:		77
PH:		68
PA:		73
SC:		62
DF:		84
Luke Schenn

AGE:35
SK:		75
EN:		76
DU:		95
PH:		49
PA:		46
SC:		52
DF:		76
Alexandre Carrier

AGE:28
SK:		83
EN:		84
DU:		97
PH:		59
PA:		63
SC:		55
DF:		81
J.J. Moser

AGE:24
SK:		78
EN:		81
DU:		80
PH:		56
PA:		58
SC:		55
DF:		86
Zach Whitecloud

AGE:28
SK:		75
EN:		79
DU:		94
PH:		53
PA:		50
SC:		57
DF:		73
Ilya Lyubushkin

AGE:30
SK:		75
EN:		79
DU:		98
PH:		52
PA:		53
SC:		52
DF:		77
Henri Jokiharju

AGE:25
SK:		77
EN:		79
DU:		84
PH:		53
PA:		50
SC:		56
DF:		74
Brendan Smith

AGE:35
SK:		76
EN:		72
DU:		65
PH:		53
PA:		53
SC:		54
DF:		67

Connor Carrick

AGE:30
SK:		81
EN:		67
DU:		62
PH:		58
PA:		50
SC:		65
DF:		65
Montana Onyebuchi

AGE:24
SK:		75
EN:		68
DU:		63
PH:		32
PA:		29
SC:		36
DF:		66
Chad Ruhwedel

AGE:34
SK:		75
EN:		55
DU:		50
PH:		41
PA:		45
SC:		37
DF:		70
Philip Kemp

AGE:25
SK:		75
EN:		60
DU:		55
PH:		36
PA:		27
SC:		45
DF:		65
Nick Cicek

AGE:24
SK:		75
EN:		55
DU:		50
PH:		36
PA:		35
SC:		37
DF:		63
Artem Guryev

AGE:21
SK:		75
EN:		55
DU:		50
PH:		32
PA:		25
SC:		38
DF:		60
Artem Grushnikov

AGE:21
SK:		75
EN:		65
DU:		60
PH:		29
PA:		25
SC:		32
DF:		50
Artyom Serikov

AGE:24
SK:		75
EN:		55
DU:		50
PH:		34
PA:		32
SC:		36
DF:		50

Logan Thompson

AGE:27
SK:		86
AG:		83
RB:		85
SC:		84
HS:		87
RT:		86
DF:		85
Philipp Grubauer

AGE:33
SK:		85
AG:		60
RB:		56
SC:		57
HS:		60
RT:		61
DF:		60
Chris Driedger

AGE:30
SK:		80
AG:		50
RB:		50
SC:		50
HS:		50
RT:		50
DF:		50
Louis Domingue

AGE:32
SK:		76
AG:		50
RB:		50
SC:		50
HS:		50
RT:		50
DF:		50
Arvid Holm

AGE:26
SK:		75
AG:		50
RB:		50
SC:		50
HS:		50
RT:		50
DF:		50
Veini Vehvilainen

AGE:27
SK:		76
AG:		50
RB:		50
SC:		50
HS:		50
RT:		50
DF:		50

Prospects

Show or Hide Column

Filter Tips

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

Prospect	Team Name	Draft Year	Overall Pick
Cameron Macdonald	Flyers	2035	194
Connor Clattenburg	Flyers	2038	176
Hoyt Stanley	Flyers	2037	137
Kasper Pikkarainen	Flyers	2038	114
Ludvig Lafton	Flyers	2038	207
Sergei Ivanov	Flyers	2036	161
Vadim Moroz	Flyers	2037	106
Viktor Norringer	Flyers	2038	145
Will Skahan	Flyers	2038	83

Draft Picks

Draft Picks
Year	R1	R2	R3	R4	R5	R6	R7
2039
2040
2041
2042

Flyers Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Auston Matthews	494	361	354	715	104	237	578	1939	2630	13.73%	209	12129	24.55	104	107	211	653	12	9	21	78	61	15	53.32%	16	1.18	12	36
2	Alexei Semenov	1575	249	420	669	-1	1539	2124	2029	2593	9.60%	953	27071	17.19	40	67	107	291	6	15	21	69	35	23	49.89%	2	0.49	13	43
3	Jason Spezza	580	275	388	663	102	174	361	1573	2210	12.44%	200	13365	23.04	73	143	216	520	10	4	14	60	35	14	55.78%	9	0.99	20	58
4	Clayton Keller	460	182	269	451	30	62	164	1033	1664	10.94%	116	9274	20.16	45	92	137	392	3	5	8	34	22	8	34.62%	4	0.97	5	28
5	Kyle Okposo	703	174	263	437	6	527	1052	925	1736	10.02%	124	13943	19.83	51	115	166	441	1	1	2	26	19	16	40.07%	2	0.63	11	43

Flyers Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA
1	Cory Schneider	201	107	71	11	0.909	2.89	11557	24	11	557	6119	10	5	0.786	103
2	Logan Thompson	174	95	58	11	0.904	3.05	10061	16	6	512	5334	7	0	0.800	25
3	Jaroslav Halak	210	89	100	11	0.896	3.12	11926	16	14	621	5953	7	3	0.833	90
4	Ben Bishop	126	69	41	10	0.900	3.00	7258	25	5	363	3617	6	1	0.667	24
5	Chris Driedger	158	67	67	10	0.904	3.17	8757	24	6	463	4833	14	1	0.695	59

Flyers Career Team Stats

Show or Hide Column

	Overall											Home											Visitor
Year	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
Regular Season
2017	82	30	31	0	1	7	7	6	227	245	-18	41	15	16	0	1	2	3	4	113	119	-6	41	15	15	0	0	5	4	2	114	126	-12	69	227	353	580	1	2	0	69	63	87	2242	0	718	704	796	2410	834	1241	1813	257	25	9.73%	264	40	84.85%	6	933	1830	50.98%	1032	1962	52.60%	665	1306	50.92%	1769	961	1801	843	1586	815
2018	82	39	26	0	4	1	5	7	266	211	55	41	17	14	0	3	0	2	5	133	112	21	41	22	12	0	1	1	3	2	133	99	34	87	266	425	691	0	4	0	73	76	108	2524	0	839	801	857	2434	776	1167	2012	218	42	19.27%	233	35	84.98%	11	1007	1957	51.46%	1008	1961	51.40%	688	1347	51.08%	1799	1026	1669	744	1523	772
2019	82	37	28	0	4	3	8	2	236	206	30	41	17	14	0	2	2	6	0	117	109	8	41	20	14	0	2	1	2	2	119	97	22	85	236	359	595	2	6	0	59	83	82	2251	0	640	766	819	2328	791	856	1777	232	36	15.52%	177	26	85.31%	5	986	1826	54.00%	979	1867	52.44%	575	1113	51.66%	1747	949	1625	769	1604	823
2020	82	28	35	0	1	5	6	7	216	243	-27	41	15	20	0	0	1	1	4	106	121	-15	41	13	15	0	1	4	5	3	110	122	-12	63	216	340	556	5	2	0	63	67	79	2305	0	684	730	863	2357	839	1148	1746	222	41	18.47%	237	48	79.75%	4	997	1923	51.85%	921	1886	48.83%	616	1175	52.43%	1685	892	1684	787	1620	821
2021	82	44	19	0	2	3	9	5	283	205	78	41	27	9	0	1	0	2	2	151	97	54	41	17	10	0	1	3	7	3	132	108	24	95	283	486	769	3	11	0	96	94	82	2652	0	852	907	857	2145	710	959	1710	448	80	17.86%	403	69	82.88%	3	1711	3134	54.59%	1423	2755	51.65%	684	1257	54.42%	2160	1532	1824	587	1018	534
2022	82	27	41	0	1	4	7	2	206	245	-39	41	15	19	0	1	3	2	1	110	124	-14	41	12	22	0	0	1	5	1	96	121	-25	60	206	351	557	0	7	0	75	70	53	2298	0	790	736	754	2450	702	1026	1847	415	61	14.70%	419	87	79.24%	5	1536	2879	53.35%	1535	2942	52.18%	673	1235	54.49%	2057	1440	1892	596	1026	517
2023	82	42	28	0	2	4	4	2	302	257	45	41	20	11	0	1	3	4	2	156	126	30	41	22	17	0	1	1	0	0	146	131	15	92	302	527	829	1	2	0	112	87	97	2684	0	861	862	938	2418	694	910	1729	460	97	21.09%	418	93	77.75%	3	1653	3042	54.34%	1508	2903	51.95%	697	1330	52.41%	2018	1409	1924	607	1019	511
2024	82	41	32	0	2	1	3	3	318	260	58	41	19	19	0	1	0	1	1	159	129	30	41	22	13	0	1	1	2	2	159	131	28	96	318	562	880	5	7	0	111	109	93	2711	0	904	910	873	2560	736	930	1713	474	112	23.63%	393	82	79.13%	3	1692	3117	54.28%	1520	2997	50.72%	670	1342	49.93%	2060	1451	1886	600	1010	510
2025	82	49	23	0	1	4	1	4	309	236	73	41	26	10	0	1	2	1	1	163	116	47	41	23	13	0	0	2	0	3	146	120	26	110	309	550	859	0	3	0	114	96	97	2537	0	799	906	822	2459	675	979	1732	459	109	23.75%	407	87	78.62%	6	1668	3065	54.42%	1505	2885	52.17%	720	1331	54.09%	2076	1441	1844	604	1029	522
2026	82	39	33	0	0	2	6	2	272	274	-2	41	19	20	0	0	0	2	0	122	134	-12	41	20	13	0	0	2	4	2	150	140	10	94	272	468	740	3	0	0	100	101	65	2435	0	829	811	778	2647	712	1117	1811	420	78	18.57%	443	98	77.88%	5	1495	2903	51.50%	1486	3135	47.40%	629	1355	46.42%	1981	1383	1971	609	1009	499
2027	82	39	35	0	1	2	3	2	280	267	13	41	21	16	0	0	0	3	1	145	130	15	41	18	19	0	1	2	0	1	135	137	-2	90	280	507	787	0	3	0	93	114	69	2357	0	767	813	768	2647	748	1077	1978	402	104	25.87%	451	100	77.83%	5	1210	2769	43.70%	1252	3121	40.12%	566	1353	41.83%	1982	1371	1943	603	1020	510
2030	82	34	31	0	2	0	11	4	250	241	9	41	20	12	0	2	0	4	3	133	114	19	41	14	19	0	0	0	7	1	117	127	-10	98	250	435	685	2	8	0	82	73	82	2538	0	831	809	867	2654	795	965	1845	395	84	21.27%	436	81	81.42%	0	1534	3046	50.36%	1406	3133	44.88%	622	1254	49.60%	1955	1332	2000	622	1042	518
2031	82	35	35	0	0	0	5	7	275	277	-2	41	16	21	0	0	0	3	1	131	143	-12	41	19	14	0	0	0	2	6	144	134	10	87	275	474	749	3	3	0	96	91	83	2486	0	783	852	830	2750	808	897	1875	396	79	19.95%	415	78	81.20%	3	1308	2923	44.75%	1388	3204	43.32%	604	1334	45.28%	1903	1297	2050	625	1026	498
2032	82	31	39	0	1	1	6	4	263	293	-30	41	16	20	0	0	1	3	1	122	138	-16	41	15	19	0	1	0	3	3	141	155	-14	81	263	457	720	0	1	0	102	81	73	2444	0	801	828	784	2854	842	952	1864	385	74	19.22%	398	73	81.66%	2	1291	2895	44.59%	1451	3292	44.08%	606	1330	45.56%	1839	1238	2108	626	1028	493
2033	82	16	57	0	0	4	3	2	225	324	-99	41	11	26	0	0	2	2	0	127	166	-39	41	5	31	0	0	2	1	2	98	158	-60	44	225	399	624	0	3	0	88	63	71	2174	0	728	664	769	2706	799	1024	1862	394	67	17.01%	451	98	78.27%	6	1295	2711	47.77%	1412	3068	46.02%	630	1349	46.70%	1862	1243	2052	626	1037	509
2034	82	24	44	0	3	0	6	5	268	306	-38	41	12	21	0	1	0	4	3	133	154	-21	41	12	23	0	2	0	2	2	135	152	-17	71	268	449	717	1	3	0	95	86	78	2638	0	893	826	888	2937	807	879	1760	387	74	19.12%	374	80	78.61%	2	1523	2976	51.18%	1598	3240	49.32%	715	1367	52.30%	1810	1220	2127	631	1040	502
2035	82	27	44	0	3	0	4	4	230	279	-49	41	15	20	0	3	0	2	1	111	128	-17	41	12	24	0	0	0	2	3	119	151	-32	72	230	400	630	1	3	0	86	74	63	2389	0	752	828	788	2751	792	1004	1853	354	61	17.23%	443	82	81.49%	4	1451	2798	51.86%	1567	3148	49.78%	695	1348	51.56%	1873	1263	2045	626	1046	509
2036	82	33	35	0	4	5	2	3	307	315	-8	41	18	15	0	4	3	0	1	164	159	5	41	15	20	0	0	2	2	2	143	156	-13	86	307	519	826	0	4	0	111	98	92	2803	0	892	933	948	2689	787	1092	1838	399	83	20.80%	480	113	76.46%	5	1690	3095	54.60%	1528	2952	51.76%	727	1403	51.82%	1968	1359	1965	606	1028	505
2037	82	47	27	0	1	3	3	1	316	254	62	41	26	12	0	0	3	0	0	154	121	33	41	21	15	0	1	0	3	1	162	133	29	106	316	547	863	0	1	115	104	93	5	2620	870	876	859	28	2599	744	1019	1747	395	84	21.27%	436	79	81.88%	4	1493	2912	51.27%	1580	3003	52.61%	716	1330	53.83%	1939	1324	1977	617	1032	505
2038	82	33	35	0	4	6	2	2	250	258	-8	41	20	13	0	2	4	2	0	136	114	22	41	13	22	0	2	2	0	2	114	144	-30	86	250	439	689	0	2	99	75	70	9	2385	797	750	803	47	2602	777	975	1766	389	67	17.22%	419	87	79.24%	5	1385	2698	51.33%	1546	2952	52.37%	642	1273	50.43%	1957	1355	1979	616	1024	506
Total Regular Season	1640	695	678	0	37	55	101	74	5299	5196	103	820	365	328	0	23	26	47	31	2686	2554	132	820	330	350	0	14	29	54	43	2613	2642	-29	1672	5299	9047	14346	27	75	214	1804	1689	1468	49473	1667	15989	16348	15074	51397	15368	20217	36278	7501	1458	19.44%	7697	1536	80.04%	87	27858	54499	51.12%	27645	56406	49.01%	13140	26132	50.28%	38452	25495	38374	12951	22778	11390
Playoff
2017	9	5	4	0	0	0	0	0	21	21	0	4	2	2	0	0	0	0	0	8	9	-1	5	3	2	0	0	0	0	0	13	12	1	10	21	34	55	0	0	0	6	4	9	266	0	65	90	103	222	81	145	213	28	2	7.14%	38	6	84.21%	0	115	217	53.00%	119	216	55.09%	62	128	48.44%	196	108	1979	932	177	84
2018	10	4	6	0	0	0	0	0	25	30	-5	5	2	3	0	0	0	0	0	12	16	-4	5	2	3	0	0	0	0	0	13	14	-1	8	25	38	63	0	1	0	8	10	7	282	0	75	108	96	291	92	117	249	34	5	14.71%	24	6	75.00%	0	144	256	56.25%	129	226	57.08%	81	151	53.64%	223	125	191	91	187	95
2019	5	1	4	0	0	0	0	0	6	9	-3	3	0	3	0	0	0	0	0	4	8	-4	2	1	1	0	0	0	0	0	2	1	1	2	6	12	18	0	1	0	1	3	2	107	0	18	42	35	121	32	30	95	2	0	0.00%	14	3	78.57%	0	53	84	63.10%	55	100	55.00%	34	52	65.38%	103	51	92	51	115	58
2021	23	14	9	0	0	0	0	0	70	66	4	12	8	4	0	0	0	0	0	36	30	6	11	6	5	0	0	0	0	0	34	36	-2	28	70	123	193	0	3	0	18	25	24	682	0	206	229	218	582	194	264	490	109	24	22.02%	115	24	79.13%	0	448	847	52.89%	393	760	51.71%	168	344	48.84%	602	428	546	168	285	145
2023	5	1	4	0	0	0	0	0	12	15	-3	3	1	2	0	0	0	0	0	8	9	-1	2	0	2	0	0	0	0	0	4	6	-2	2	12	22	34	0	0	0	8	2	2	177	0	58	55	64	170	46	74	122	32	3	9.38%	28	5	82.14%	1	119	208	57.21%	109	205	53.17%	42	80	52.50%	113	77	128	37	59	28
2024	5	1	4	0	0	0	0	0	16	15	1	3	1	2	0	0	0	0	0	12	9	3	2	0	2	0	0	0	0	0	4	6	-2	2	16	29	45	0	0	0	9	4	3	143	0	57	37	49	143	33	64	124	25	6	24.00%	26	6	76.92%	1	90	187	48.13%	91	181	50.28%	35	71	49.30%	117	80	118	38	63	31
2025	18	11	7	0	0	0	0	0	50	56	-6	10	6	4	0	0	0	0	0	28	33	-5	8	5	3	0	0	0	0	0	22	23	-1	22	50	92	142	0	0	0	17	16	15	498	0	148	170	165	636	171	270	397	96	17	17.71%	109	21	80.73%	0	308	626	49.20%	401	747	53.68%	146	267	54.68%	460	319	422	140	233	116
2026	5	1	4	0	0	0	0	0	17	24	-7	2	0	2	0	0	0	0	0	7	9	-2	3	1	2	0	0	0	0	0	10	15	-5	2	17	30	47	1	0	0	8	6	3	141	0	57	37	46	201	67	74	115	25	3	12.00%	31	9	70.97%	1	83	184	45.11%	114	233	48.93%	50	90	55.56%	112	75	133	40	62	30
2027	7	3	4	0	0	0	0	0	22	24	-2	3	2	1	0	0	0	0	0	11	10	1	4	1	3	0	0	0	0	0	11	14	-3	6	22	38	60	0	0	0	5	8	7	204	0	59	68	47	256	90	111	168	30	7	23.33%	50	9	82.00%	0	111	250	44.40%	134	301	44.52%	37	107	34.58%	179	120	199	58	96	46
2030	7	3	4	0	0	0	0	0	17	25	-8	3	2	1	0	0	0	0	0	7	9	-2	4	1	3	0	0	0	0	0	10	16	-6	6	17	30	47	0	0	0	5	5	6	163	0	47	63	51	245	72	114	142	31	4	12.90%	46	9	80.43%	0	91	210	43.33%	124	308	40.26%	54	119	45.38%	156	105	185	54	83	37
2037	4	0	4	0	0	0	0	0	12	17	-5	2	0	2	0	0	0	0	0	6	8	-2	2	0	2	0	0	0	0	0	6	9	-3	0	12	20	32	0	0	5	1	6	0	121	42	39	40	0	144	47	46	85	21	5	23.81%	17	6	64.71%	0	72	143	50.35%	89	165	53.94%	29	65	44.62%	88	60	101	31	50	23
Total Playoff	98	44	54	0	0	0	0	0	268	302	-34	50	24	26	0	0	0	0	0	139	150	-11	48	20	28	0	0	0	0	0	129	152	-23	88	268	468	736	1	5	5	86	89	78	2784	42	829	939	874	3011	925	1309	2200	433	76	17.55%	498	104	79.12%	3	1634	3212	50.87%	1758	3442	51.07%	738	1474	50.07%	2354	1553	4100	1643	1415	699

Flyers Stat Leaders (Play-Off)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20
1	Jason Spezza	61	21	37	58	1	15	34	142	171	12.28%	6	1317	21.60	4	15	19	41	0	2	2	0	5	0	54.37%	0	0.88
2	Brad Stuart	162	21	34	55	21	145	213	165	266	7.89%	81	2678	16.53	2	2	4	9	0	0	0	11	5	0	52.76%	0	0.41
3	Evgeni Malkin	38	14	23	37	-4	18	55	88	142	9.86%	3	900	23.70	4	9	13	40	2	0	2	6	1	1	48.47%	1	0.82
4	Joe Thornton	33	9	22	31	3	13	34	76	76	11.84%	9	640	19.40	4	8	12	19	0	0	0	0	2	1	54.51%	1	0.97
5	Chris Pronger	33	5	19	24	-7	33	37	44	52	9.62%	52	843	25.55	3	7	10	26	0	0	0	2	1	0	0.00%	0	0.57

Flyers Goalies Stat Leaders (Play-Off)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A
1	Jaroslav Halak	24	14	8	1	0.884	2.83	1420	0	3	67	578	0	1
2	Ben Bishop	22	12	9	1	0.914	2.86	1320	6	0	63	734	0	1
3	Cory Schneider	16	6	6	3	0.903	3.46	970	4	0	56	576	0	0
4	Jaroslav Halak	9	5	2	2	0.905	2.28	552	4	0	21	222	82	0
5	Pekka Rinne	15	5	6	4	0.905	2.56	913	0	2	39	412	165	0