Capitals



		Metropolitan Division
		Eastern Conference




		5,000

		5,000

		21
		20
		41 / 55
		30

Priority		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

#		#	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	Walker Duehr	0			X		100.00	72	51	97	78	83	38	55	83	40	74	71	41	77	83	77	0	50	76	0	26	2	783,750$
2	Georgii Merkulov (R)	0	X				100.00	45	64	84	74	76	79	91	79	65	61	68	40	73	25	40	0	50	72	0	23	2	925,000$
3	Joona Koppanen	0		X			100.00	45	62	83	72	75	75	87	77	36	58	67	40	72	25	40	0	50	71	0	26	1	750,000$
4	William Dufour (R)	0	X	X	X		100.00	46	65	82	72	76	81	94	77	36	58	67	40	72	25	40	0	50	71	0	22	1	859,167$
5	Jackson Cates	0	X	X	X		100.00	45	63	84	72	75	76	88	76	65	57	67	40	72	25	40	0	50	70	0	26	2	750,000$
6	Luke Philp	0			X		100.00	45	60	84	71	76	71	82	77	65	57	67	40	72	25	40	0	50	70	0	28	3	806,000$
7	Tanner Fritz	0	X	X	X		100.00	45	64	84	71	75	79	91	76	65	58	66	40	71	25	40	0	50	70	0	32	1	750,000$
8	Matej Pekar (R)	0	X	X	X		100.00	49	37	78	72	77	58	45	77	65	60	66	40	71	25	40	0	50	70	0	24	3	750,000$
9	Jared Davidson (R)	0	X	X	X		100.00	46	49	81	72	76	58	51	77	65	57	67	40	72	25	40	0	50	69	0	21	1	750,000$
10	Josh Lopina (R)	0	X				100.00	45	60	83	71	75	69	80	76	65	56	67	40	72	25	40	0	50	69	0	23	1	925,000$
11	Blake McLaughlin (R)	0		X			100.00	46	42	82	70	75	58	45	75	36	56	66	40	71	25	40	0	50	68	0	24	3	830,725$
12	Josh Bloom (R)	0		X			100.00	44	37	84	70	75	58	45	75	36	56	66	40	71	25	40	0	50	68	0	21	3	836,667$
13	Marc Del Gaizo (R)	0				X	100.00	46	66	83	72	76	83	97	77	36	60	66	51	72	25	40	0	50	75	0	24	1	925,000$
14	Josh Healey	0				X	100.00	63	36	56	70	75	58	45	75	36	56	66	40	71	25	40	0	50	71	0	29	1	750,000$
15	Quinn Schmiemann	0				X	100.00	47	46	81	71	75	58	45	76	36	57	66	47	71	25	40	0	50	71	0	22	1	750,000$
16	Markus Niemelainen	0				X	100.00	46	48	83	71	75	58	47	76	36	56	66	43	71	25	40	0	50	70	0	26	1	750,000$
17	Aidan Fulp	0				X	100.00	45	55	84	70	75	59	68	75	36	56	66	40	71	25	40	0	50	69	0	24	1	750,000$
18	Chris Jandric	0				X	100.00	48	36	79	70	75	58	45	75	36	55	66	40	71	25	40	0	50	69	0	25	1	750,000$

1	Benjamin Berard	0	X	X	X		100.00	45	45	84	71	75	58	45	75	65	56	66	40	71	25	40	0	50	68	0	25	1	750,000$

							100.00	48	52	82	72	76	65	66	77	48	58	67	41	72	28	42	0	50	70

Priority		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

#		#	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Benjamin Kraws	0	100.00	60	55	53	59	57	53	59	54	56	74	56	25	55	0	50	65	0	23	1	750,000$
2	Cooper Black	0	100.00	55	55	53	55	59	53	55	50	53	65	54	25	55	0	50	62	0	23	1	750,000$


			100.00	58	55	53	57	58	53	57	52	55	70	55	25	55	0	50	64

	PH	DF	OF	PD	EX	LD	PO	CNT

Priority		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

#		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

Priority		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

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

Priority		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	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Salary Cap Year 2	Salary Cap Year 3	Salary Cap Year 4	Salary Cap Year 5	Salary Cap Year 6	Salary Cap Year 7	Salary Cap Year 8	Salary Cap Year 9	Salary Cap Year 10	No Trade Year 2	No Trade Year 3	No Trade Year 4	No Trade Year 5	No Trade Year 6	No Trade Year 7	No Trade Year 8	No Trade Year 9	No Trade Year 10	Link
Aidan Fulp	Bears (WAS)	D	24	2000-02-29	USA	No	210 Lbs	6 ft3	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	870,000$	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Benjamin Berard	Bears (WAS)	C/LW/RW	25	1999-02-13	CAN	No	192 Lbs	6 ft0	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Benjamin Kraws	Bears (WAS)	G	23	2000-08-02	USA	No	195 Lbs	6 ft5	No	No	Free Agent	No	No	1	2025-03-12	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Blake McLaughlin	Bears (WAS)	LW	24	2000-02-14	USA	Yes	173 Lbs	6 ft0	No	No	Free Agent	No	No	3	2024-10-07	False	False	Pro & Farm	830,725$	296,688$	0$	0$	No	830,725$	830,725$	Restricted	-	-	-	-	830,725$	830,725$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Chris Jandric	Bears (WAS)	D	25	1998-10-03	CAN	No	181 Lbs	5 ft11	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Cooper Black	Bears (WAS)	G	23	2001-06-14	USA	No	223 Lbs	6 ft8	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Georgii Merkulov	Bears (WAS)	C	23	2000-10-10	RUS	Yes	176 Lbs	5 ft11	No	No	N/A	No	No	2		False	False	Pro & Farm	925,000$	330,357$	0$	0$	No	925,000$	Restricted		-	-	-	-	925,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Jackson Cates	Bears (WAS)	C/LW/RW	26	1997-09-26	USA	No	190 Lbs	6 ft0	No	No	Free Agent	No	No	2	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	750,000$	Unrestricted		-	-	-	-	750,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Jared Davidson	Bears (WAS)	C/LW/RW	21	2002-07-07	CAN	Yes	183 Lbs	6 ft0	No	No	Prospect	No	No	1	2024-07-02	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Joona Koppanen	Bears (WAS)	LW	26	1998-02-25	FIN	No	216 Lbs	6 ft5	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Unrestricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Josh Bloom	Bears (WAS)	LW	21	2003-06-08	CAN	Yes	182 Lbs	6 ft2	No	No	Prospect	No	No	3	2024-07-02	False	False	Pro & Farm	836,667$	298,810$	0$	0$	No	836,667$	836,667$	Restricted	-	-	-	-	836,667$	836,667$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Josh Healey	Bears (WAS)	D	29	1994-07-12	CAN	No	206 Lbs	6 ft1	No	No	Free Agent	No	No	1	2025-03-09	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Unrestricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Josh Lopina	Bears (WAS)	C	23	2001-02-16	USA	Yes	199 Lbs	6 ft2	No	No	N/A	No	No	1		False	False	Pro & Farm	925,000$	330,357$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Luke Philp	Bears (WAS)	RW	28	1995-11-06	CAN	No	181 Lbs	5 ft10	No	No	Free Agent	No	No	3	2024-10-07	False	False	Pro & Farm	806,000$	287,857$	0$	0$	No	806,000$	806,000$	Unrestricted	-	-	-	-	806,000$	806,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Marc Del Gaizo	Bears (WAS)	D	24	1999-10-11	USA	Yes	188 Lbs	5 ft11	No	No	N/A	No	No	1		False	False	Farm Only	925,000$	330,357$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Markus Niemelainen	Bears (WAS)	D	26	1998-06-08	FIN	No	190 Lbs	6 ft6	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Matej Pekar	Bears (WAS)	C/LW/RW	24	2000-02-10	CZE	Yes	185 Lbs	6 ft1	No	No	Free Agent	No	No	3	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	750,000$	750,000$	Restricted	-	-	-	-	750,000$	750,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Quinn Schmiemann	Bears (WAS)	D	22	2001-07-27	CAN	No	185 Lbs	6 ft2	No	No	Free Agent	No	No	1	2024-12-03	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Tanner Fritz	Bears (WAS)	C/LW/RW	32	1991-08-20	CAN	No	192 Lbs	5 ft11	No	No	Free Agent	No	No	1	2024-10-07	False	False	Pro & Farm	750,000$	267,857$	0$	0$	No	Unrestricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Walker Duehr	Bears (WAS)	RW	26	1997-11-23	USA	No	210 Lbs	6 ft2	No	No	Free Agent	No	No	2	2024-10-07	False	False	Pro & Farm	783,750$	279,911$	0$	0$	No	783,750$	Unrestricted		-	-	-	-	783,750$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
William Dufour	Bears (WAS)	C/LW/RW	22	2002-01-28	CAN	Yes	215 Lbs	6 ft2	No	No	N/A	No	No	1		False	False	Pro & Farm	859,167$	306,845$	0$	0$	No	Restricted			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link


21	24.62	194 Lbs	6 ft2	1.52	792,443$



1	Joona Koppanen	Georgii Merkulov	Walker Duehr	30	1	2	2
2	Tanner Fritz	Jackson Cates	Luke Philp	30	1	2	2
3	Jared Davidson	Matej Pekar	William Dufour	20	1	2	2
4	Josh Bloom	Josh Lopina	Walker Duehr	20	1	2	2



1	Marc Del Gaizo	Quinn Schmiemann	30	1	2	2
2	Josh Healey	Markus Niemelainen	30	1	2	2
3	Chris Jandric	Aidan Fulp	20	1	2	2
4	Marc Del Gaizo	Quinn Schmiemann	20	1	2	2



1	Joona Koppanen	Georgii Merkulov	Walker Duehr	50	1	2	2
2	Tanner Fritz	Jackson Cates	Luke Philp	50	1	2	2



1	Marc Del Gaizo	Quinn Schmiemann	50	1	2	2
2	Chris Jandric	Markus Niemelainen	50	1	2	2



1	Walker Duehr	Georgii Merkulov	50	1	2	2
2	Joona Koppanen	Jackson Cates	50	1	2	2



1	Marc Del Gaizo	Chris Jandric	50	1	2	2
2	Quinn Schmiemann	Markus Niemelainen	50	1	2	2



1	Walker Duehr	50	1	2	2	Marc Del Gaizo	Quinn Schmiemann	50	1	2	2
2	Georgii Merkulov	50	1	2	2	Aidan Fulp	Markus Niemelainen	50	1	2	2



1	Walker Duehr	Georgii Merkulov	50	1	2	2
2	Joona Koppanen	Jackson Cates	50	1	2	2



1	Marc Del Gaizo	Aidan Fulp	50	1	2	2
2	Quinn Schmiemann	Markus Niemelainen	50	1	2	2



Joona Koppanen	Georgii Merkulov	Walker Duehr	Marc Del Gaizo	Quinn Schmiemann



Joona Koppanen	Georgii Merkulov	Walker Duehr	Marc Del Gaizo	Quinn Schmiemann



Blake McLaughlin, Matej Pekar, Josh Lopina	Blake McLaughlin, Matej Pekar	Josh Lopina



Chris Jandric, Aidan Fulp, Marc Del Gaizo	Chris Jandric	Aidan Fulp, Marc Del Gaizo


Walker Duehr, Georgii Merkulov, Joona Koppanen, Jackson Cates, Luke Philp


#1 : Benjamin Kraws, #2 : Cooper Black


Walker Duehr, Georgii Merkulov, Joona Koppanen, Jackson Cates, Luke Philp, Tanner Fritz, Tanner Fritz, Matej Pekar, Josh Lopina, Jared Davidson, Josh Bloom


Marc Del Gaizo, Aidan Fulp, Quinn Schmiemann, Markus Niemelainen, Chris Jandric

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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%	0	0	0%	0	0	0	0%	0	0	0%	0	0	0%	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%	0	0	0%	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%	0	0	0%	0	0	0%

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

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Day	Game	Visitor	Score	Home	Score	ST	OT	SO	RI	Link

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	3500	1500
Ticket Price	50	25
Attendance	0%	0%
Attendance PCT	0%	0%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
41	0 - 0%	0$	0$	5000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
0$	16,641,309$	16,641,309$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	0$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	10	0$	0$

Bears Players Stat Leaders (Regular Season)

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#	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

Bears Goalies Stat Leaders (Regular Season)

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#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Bears Career Team Stats

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	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

Bears Players Stat Leaders (Play-Off)

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#	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

Bears Goalies Stat Leaders (Play-Off)

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#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Bears
	GP: 0 \| W: 0 \| L: 0 GF: 0 \| GA: 0 \| PP%: 0% \| PK%: 0% \| 50 \| 70