Maple Leafs



		Atlantic Division
		Eastern Conference




		5,000

		5,000

		22
		20
		42 / 55
		32

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	Ivan Miroshnichenko	0		X	X		100.00	81	48	99	67	93	43	67	58	56	71	62	78	43	62	63	0	50	75	0	20	2	950,000$
2	Max Jones	0		X	X		100.00	89	64	99	70	98	45	70	60	58	74	65	69	45	68	69	0	50	75	0	26	1	950,000$
3	Mike Hardman	86		X			100.00	55	50	75	68	80	67	70	68	59	68	65	64	45	66	68	0	50	73	0	25	0	0$
4	Axel Jonsson-Fjallby	0	X	X			100.00	55	50	75	65	80	76	78	65	58	68	61	63	45	67	69	0	50	72	0	26	1	813,750$
5	Aidan McDonough	0		X			100.00	56	52	68	63	88	52	63	69	62	61	62	60	41	67	68	0	50	70	0	24	1	925,000$
6	Travis Barron	0		X			100.00	72	68	75	60	80	79	81	60	61	68	60	50	45	67	69	0	50	69	0	25	2	750,000$
7	Reese Johnson	24	X				100.00	66	62	75	60	80	65	70	60	64	68	60	50	45	67	69	0	50	68	0	25	0	0$
8	Trevor Kuntar	0	X				100.00	76	71	75	60	80	63	70	60	61	68	60	50	45	64	66	0	50	68	0	23	1	867,500$
9	Chase De Leo	58		X			100.00	52	48	71	66	84	55	67	67	65	65	57	48	43	70	72	0	50	67	0	28	0	0$
10	Lane Pederson	18	X				100.00	63	59	68	65	86	52	63	69	71	61	58	45	41	68	70	0	50	67	0	26	1	990,675$
11	William Villeneuve	0				X	100.00	66	62	75	61	81	65	70	66	30	68	60	69	45	63	65	0	50	73	0	22	0	0$
12	Ville Heinola	0				X	100.00	50	45	99	63	88	47	63	54	30	68	59	80	41	64	66	0	50	70	0	23	0	0$
13	Mason Millman	0				X	100.00	55	50	75	60	80	61	70	60	30	68	60	57	45	64	66	0	50	68	0	22	2	818,333$
14	Simon Lundmark	0				X	100.00	55	50	75	60	80	78	79	60	30	68	60	50	45	65	67	0	50	67	0	23	0	0$
15	Mikko Kokkonen	0				X	100.00	55	50	75	60	80	59	70	60	30	68	60	54	45	64	66	0	50	67	0	23	0	0$
16	Santeri Hatakka	0				X	100.00	65	61	69	56	74	54	65	56	30	63	56	46	42	64	66	0	50	63	0	23	2	850,833$

1	Samuel Honzek (R)	0		X			100.00	55	50	75	60	80	61	70	60	60	68	60	57	45	62	63	0	50	68	0	19	0	0$
2	Fabian Wagner (R)	0	X				100.00	55	50	75	60	80	59	70	60	61	68	60	50	45	61	63	0	50	67	0	20	0	0$
3	Brett Budgell	0	X	X	X		100.00	65	61	66	53	83	51	61	53	65	60	53	44	39	64	66	0	50	61	0	23	0	0$
4	Owen Lindmark (R)	0	X				100.00	50	45	68	54	72	52	63	54	58	61	54	45	41	64	66	0	50	60	0	23	0	0$

							100.00	62	55	77	62	82	59	69	61	52	67	60	56	44	65	67	0	50	68

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	Nico Daws	0	100.00	79	73	57	80	77	75	81	88	80	57	50	65	73	0	50	80	0	23	0	0$

1	Ales Stezka	0	100.00	67	67	62	71	76	74	74	72	67	67	57	68	81	0	50	71	0	27	0	0$

			100.00	73	70	60	76	77	75	78	80	74	62	54	67	77	0	50	76

	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 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 McDonough	Marlies (TOR)	LW	24	1999-11-06	USA	No	190 Lbs	6 ft3	No	No	Prospect	No	No	1	2024-07-02	False	False	Pro & Farm	925,000$	925,000$	0$	0$	No	Restricted		-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Ales Stezka	Marlies (TOR)	G	27	1997-01-06	CZE	No	190 Lbs	6 ft4	No	No	Free Agent	No	No	0	2025-03-14	False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Axel Jonsson-Fjallby	Marlies (TOR)	C/LW	26	1998-02-10	SWE	No	189 Lbs	6 ft1	No	No	N/A	No	No	1		False	False	Pro & Farm	813,750$	813,750$	0$	0$	No	Unrestricted		-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Brett Budgell	Marlies (TOR)	C/LW/RW	23	2001-06-01	USA	No	185 Lbs	6 ft0	No	No	Free Agent	No	No	0	2024-10-08	False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Chase De Leo	Marlies (TOR)	LW	28	1995-10-25	USA	No	186 Lbs	5 ft9	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Fabian Wagner	Marlies (TOR)	C	20	2004-05-07	SWE	Yes	176 Lbs	6 ft0	No	No	Prospect	No	No	0	2025-07-15	False	False	Pro & Farm			0$	0$	No			-	-	-	-	830,556$	830,556$	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Ivan Miroshnichenko	Marlies (TOR)	LW/RW	20	2004-02-04	RUS	No	185 Lbs	6 ft1	No	No	Prospect	No	No	2	2024-07-02	False	False	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	Restricted	-	-	-	-	950,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Lane Pederson	Marlies (TOR)	C	26	1997-08-04	CAN	No	196 Lbs	6 ft1	No	No	N/A	No	No	1		False	False	Pro & Farm	990,675$	990,675$	0$	0$	No	Unrestricted		-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Mason Millman	Marlies (TOR)	D	22	2001-07-18	CAN	No	174 Lbs	6 ft1	No	No	Prospect	No	No	2	2024-07-02	False	False	Pro & Farm	818,333$	818,333$	0$	0$	No	818,333$	Restricted	-	-	-	-	818,333$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Max Jones	Marlies (TOR)	LW/RW	26	1998-02-17	USA	No	216 Lbs	6 ft3	No	No	Free Agent	No	No	1	2024-10-08	False	False	Pro & Farm	950,000$	950,000$	0$	0$	No	Unrestricted		-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Mike Hardman	Marlies (TOR)	LW	25	1999-02-05	USA	No	205 Lbs	6 ft2	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Mikko Kokkonen	Marlies (TOR)	D	23	2001-01-18	FIN	No	200 Lbs	6 ft0	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Nico Daws	Marlies (TOR)	G	23	2000-12-22	CAN	No	205 Lbs	6 ft4	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Owen Lindmark	Marlies (TOR)	C	23	2001-05-17	USA	Yes	195 Lbs	6 ft0	No	No	Prospect	No	No	0	2025-07-15	False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Reese Johnson	Marlies (TOR)	C	25	1998-07-10	CAN	No	193 Lbs	6 ft1	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Samuel Honzek	Marlies (TOR)	LW	19	2004-11-12	SVK	Yes	186 Lbs	6 ft4	No	No	Draft	No	No	0	2025-07-15	False	False	Pro & Farm			0$	0$	No			-	-	-	-	918,333$	918,333$	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Santeri Hatakka	Marlies (TOR)	D	23	2001-01-15	FIN	No	191 Lbs	6 ft1	No	No	Prospect	No	No	2	2024-07-02	False	False	Pro & Farm	850,833$	850,833$	0$	0$	No	850,833$	Restricted	-	-	-	-	850,833$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Simon Lundmark	Marlies (TOR)	D	23	2000-10-08	SWE	No	193 Lbs	6 ft2	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Travis Barron	Marlies (TOR)	LW	25	1998-11-17	CAN	No	205 Lbs	6 ft1	No	No	Free Agent	No	No	2	2024-10-08	False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	Restricted	-	-	-	-	750,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Trevor Kuntar	Marlies (TOR)	C	23	2001-06-20	USA	No	201 Lbs	6 ft0	No	No	Prospect	No	No	1	2024-07-02	False	False	Pro & Farm	867,500$	867,500$	0$	0$	No	Restricted		-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Ville Heinola	Marlies (TOR)	D	23	2001-03-02	FIN	No	181 Lbs	6 ft0	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
William Villeneuve	Marlies (TOR)	D	22	2002-03-20	CAN	No	183 Lbs	6 ft2	No	No	N/A	No	No	0		False	False	Pro & Farm			0$	0$	No			-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link


22	23.59	192 Lbs	6 ft1	0.59	359,822$



1	Ivan Miroshnichenko	Reese Johnson		30	1	2	2
2	Max Jones	Lane Pederson	Mike Hardman	30	1	2	2
3	Axel Jonsson-Fjallby	Trevor Kuntar	Chase De Leo	20	1	2	2
4	Chase De Leo	Ivan Miroshnichenko	Max Jones	20	1	2	2



1		Simon Lundmark	30	1	2	2
2	Mason Millman	Ville Heinola	30	1	2	2
3	William Villeneuve	Mikko Kokkonen	20	1	2	2
4	William Villeneuve	Ville Heinola	20	1	2	2



1	Ivan Miroshnichenko	Reese Johnson		50	1	2	2
2	Max Jones	Lane Pederson	Axel Jonsson-Fjallby	50	1	2	2



1	Mikko Kokkonen	William Villeneuve	50	1	2	2
2	Simon Lundmark	Ville Heinola	50	1	2	2



1	Ivan Miroshnichenko	Max Jones	50	1	2	2
2	Reese Johnson	Axel Jonsson-Fjallby	50	1	2	2



1	William Villeneuve	Mikko Kokkonen	50	1	2	2
2		Ville Heinola	50	1	2	2



1	Ivan Miroshnichenko	50	1	2	2	William Villeneuve	Mikko Kokkonen	50	1	2	2
2	Max Jones	50	1	2	2		Ville Heinola	50	1	2	2



1	Ivan Miroshnichenko	Max Jones	50	1	2	2
2	Reese Johnson	Axel Jonsson-Fjallby	50	1	2	2



1	Mikko Kokkonen	William Villeneuve	50	1	2	2
2	Mason Millman	Ville Heinola	50	1	2	2



Ivan Miroshnichenko	Reese Johnson		William Villeneuve	Ville Heinola



Ivan Miroshnichenko	Reese Johnson		William Villeneuve	Ville Heinola



Mike Hardman, Travis Barron, Aidan McDonough	Mike Hardman, Travis Barron	Aidan McDonough



William Villeneuve, Mikko Kokkonen, Ville Heinola	William Villeneuve	Mikko Kokkonen, William Villeneuve


Ivan Miroshnichenko, Max Jones, Reese Johnson, Axel Jonsson-Fjallby, Chase De Leo


#1 : Nico Daws, #2 :


Ivan Miroshnichenko, Max Jones, Reese Johnson, Axel Jonsson-Fjallby, Chase De Leo, Lane Pederson, Lane Pederson, Trevor Kuntar, , Mike Hardman, Travis Barron


Simon Lundmark, Mikko Kokkonen, Mason Millman, Ville Heinola, William Villeneuve

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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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Priority	Type	Description
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2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
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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.
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10	text	Any text entered in the filter will match text found within the column

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$	7,916,091$	7,916,091$	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$	0	0$	0$

Marlies 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

Marlies 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

Marlies 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

Marlies 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

Marlies 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

	Marlies
	GP: 0 \| W: 0 \| L: 0 \| OTL: 0 \| P: 0 GF: 0 \| GA: 0 \| PP%: 0% \| PK%: 0% \| 50 \| 69