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Chicago Wolves
0-0-0, 0pts

2025-09-14

Moose
0-0-0, 0pts

Team Stats
N/A	Streak	N/A
0-0-0	Home Record	0-0-0
0-0-0	Away Record	0-0-0
0-0-0	Last 10 Games	0-0-0
0	Goals Per Game	0
0	Goals Against Per Game	0
0%	Power Play Percentage	0%
0%	Penalty Kill Percentage	0%

Chicago Wolves
0-0-0, 0pts

2025-09-17

Charlotte Checkers
0-0-0, 0pts

Team Stats
N/A	Streak	N/A
0-0-0	Home Record	0-0-0
0-0-0	Away Record	0-0-0
0-0-0	Last 10 Games	0-0-0
0	Goals Per Game	0
0	Goals Against Per Game	0
0%	Power Play Percentage	0%
0%	Penalty Kill Percentage	0%

Phantoms
0-0-0, 0pts

2025-09-21

Chicago Wolves
0-0-0, 0pts

Team Stats
N/A	Streak	N/A
0-0-0	Home Record	0-0-0
0-0-0	Away Record	0-0-0
0-0-0	Last 10 Games	0-0-0
0	Goals Per Game	0
0	Goals Against Per Game	0
0%	Power Play Percentage	0%
0%	Penalty Kill Percentage	0%

Team Leaders

Team Stats

Team Info
	General Manager	Xavier Berard
	Coach	Ryan Parent
	Division	Metropolitan
	Conference	Eastern Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance
	Season Tickets	300
Roster Info
	Pro Team	28
	Farm Team	21
	Contract Limit	49 / 55
	Prospects	7

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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

#	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	Brett Murray	0		X			100.00	82	74	83	62	95	78	83	63	68	60	62	64	61	67	69	0	40	65	0	28	3	1,000,000$
2	Tanner Laczynski	0	X				100.00	66	38	84	65	78	84	78	66	72	63	64	62	66	68	70	0	40	65	0	29	3	1,000,000$
3	Garrett Pilon	0	X				100.00	64	39	82	63	73	82	84	62	70	66	62	60	63	67	72	0	40	64	0	28	3	1,000,000$
4	Jake Leschyshyn	0	X				100.00	65	38	81	63	72	73	82	62	67	60	63	64	62	66	68	0	40	63	0	27	3	1,000,000$
5	Jake Wise	0	X				100.00	59	37	88	62	68	79	80	63	67	62	63	61	60	65	67	0	40	63	0	26	3	1,000,000$
6	Wilmer Skoog	0	X				100.00	71	40	80	59	80	86	82	57	63	56	60	58	57	66	68	0	40	62	0	27	3	1,000,000$
7	Caedan Bankier	0	X				100.00	70	40	84	59	79	84	82	57	63	56	62	55	59	62	64	0	40	61	0	23	1	1,000,000$
8	Jacob Quillan (R)	0	X				100.00	68	38	83	58	78	77	73	56	66	57	59	59	56	63	65	0	40	61	0	24	3	1,000,000$
9	Nathan Gaucher	0	X				100.00	76	50	69	58	85	73	84	55	62	56	61	59	58	62	64	0	40	61	0	22	1	1,000,000$
10	Anthony Vincent	0			X		100.00	63	42	66	58	72	80	76	57	59	55	60	54	58	67	70	0	40	60	0	29	3	1,000,000$
11	Adam Boqvist	0				X	100.00	60	35	95	73	71	87	72	70	30	75	62	64	53	66	68	0	40	67	0	26	3	1,000,000$
12	Jordan Harris	0				X	100.00	64	34	90	66	70	86	76	63	30	71	62	72	52	66	67	0	40	65	0	26	1	925,000$
13	Scott Morrow (R)	0				X	100.00	70	41	78	67	82	86	72	66	30	68	60	64	52	63	65	0	40	65	0	23	1	1,000,000$
14	Andreas Englund	0				X	100.00	80	73	69	63	86	82	83	58	30	66	57	67	46	69	71	0	40	64	0	30	3	1,000,000$
15	Matthew Robertson	0				X	100.00	76	42	74	61	89	85	84	59	30	60	60	62	49	64	66	0	40	63	0	25	3	1,000,000$
16	Cade Webber (R)	0				X	100.00	89	53	81	58	98	63	70	56	30	54	56	61	45	64	66	0	40	62	0	25	3	1,000,000$
Scratches
1	Gerry Mayhew	0	X				100.00	61	37	82	63	65	84	83	62	68	61	60	62	63	73	75	0	40	63	0	33	3	1,000,000$
2	Garrett Wilson	0		X			100.00	78	72	50	55	87	76	83	56	62	57	62	59	56	74	79	0	40	62	0	35	3	1,000,000$
3	Vincent Desharnais	0				X	100.00	76	80	75	64	99	86	84	61	30	67	56	79	48	69	71	0	40	66	0	30	1	2,000,000$
4	Donovan Sebrango	0				X	100.00	70	44	60	61	85	74	76	59	30	58	59	60	52	63	65	0	40	61	0	24	1	999,999$
5	Tobie Paquette-Bisson	0				X	100.00	73	40	81	56	82	65	84	55	30	57	58	58	46	68	70	0	40	61	0	29	3	1,000,000$
6	Corson Ceulemans	0				X	100.00	71	40	84	58	80	71	74	56	30	55	57	57	45	62	64	0	40	60	0	23	1	925,000$
7	Zachary Hayes	0				X	100.00	78	44	69	56	87	63	68	55	30	54	57	58	45	66	68	0	40	60	0	27	3	1,000,000$
8	Tyrel Bauer	0				X	100.00	76	56	61	54	85	64	81	53	30	52	55	56	45	63	65	0	40	59	0	24	3	1,000,000$
9	Jakub Dvorak (R)	0				X	100.00	81	42	81	55	90	62	68	54	30	52	54	57	45	60	62	0	40	59	0	21	1	1,000,000$

	TEAM AVERAGE						100.00	71	47	77	61	81	77	78	59	47	60	60	61	54	66	68	0	40	62

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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

#	Goalie Name	#	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Dennis Hildeby	0	100.00	77	86	82	98	76	75	77	76	75	77	76	64	71	0	40	67	0	25	1	999,999$
2	Cooper Black	0	100.00	73	74	70	98	72	71	73	72	71	73	72	64	71	0	40	65	0	25	1	950,000$
Scratches
1	Waltteri Ignatjew	0	100.00	71	76	72	83	70	69	71	70	69	71	70	66	75	0	40	64	0	26	3	1,000,000$

	TEAM AVERAGE		100.00	74	79	75	93	73	72	74	73	72	74	73	65	72	0	40	65

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Ryan Parent	67	68	65	69	59	55	87	CAN	38	3	2,500,000$

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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

#	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

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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

#	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

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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

Player Name	Team Name	POS	Age	Birthday	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Last Trade Date	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	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
Adam Boqvist	Hurricanes	D	26	2000-08-15	SWE	No	191 Lbs	183 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Andreas Englund	Hurricanes	D	30	1996-01-21	SWE	No	200 Lbs	193 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Anthony Vincent	Hurricanes	RW	29	1997-08-12	USA	No	190 Lbs	183 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Brett Murray	Hurricanes	LW	28	1998-07-20	CAN	No	228 Lbs	196 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Cade Webber	Hurricanes	D	25	2001-01-05	USA	Yes	212 Lbs	201 CM	No	No	Fantasy Draft		No	No	3	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Caedan Bankier	Hurricanes	C	23	2003-01-26	CAN	No	192 Lbs	188 CM	No	No	Fantasy Draft		No	No	1	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Cooper Black	Hurricanes	G	25	2001-06-14	USA	No	223 Lbs	203 CM	No	No	Fantasy Draft		No	No	1	2025-08-17	False	False	Pro & Farm	950,000$	950,000$	950,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Corson Ceulemans	Hurricanes	D	23	2003-05-05	CAN	No	198 Lbs	188 CM	No	No	Trade	2025-08-31	No	No	1	2025-08-17	False	False	Pro & Farm	925,000$	925,000$	925,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Dennis Hildeby	Hurricanes	G	25	2001-08-19	SWE	No	224 Lbs	201 CM	No	No	Fantasy Draft		No	No	1	2025-08-23	False	False	Pro & Farm	999,999$	999,999$	999,999$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Donovan Sebrango	Hurricanes	D	24	2002-01-12	CAN	No	221 Lbs	188 CM	No	No	Fantasy Draft		No	No	1	2025-08-23	False	False	Pro & Farm	999,999$	999,999$	999,999$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Garrett Pilon	Hurricanes	C	28	1998-04-13	CAN	No	191 Lbs	183 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Garrett Wilson	Hurricanes	LW	35	1991-03-16	CAN	No	218 Lbs	191 CM	No	No	Fantasy Draft		Yes	Yes	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Gerry Mayhew	Hurricanes	C	33	1992-12-31	USA	No	161 Lbs	175 CM	No	No	Fantasy Draft		Yes	Yes	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Jacob Quillan	Hurricanes	C	24	2002-02-02	CAN	Yes	204 Lbs	185 CM	No	No	Fantasy Draft		No	No	3	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Jake Leschyshyn	Hurricanes	C	27	1999-03-10	CAN	No	198 Lbs	180 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Jake Wise	Hurricanes	C	26	2000-02-28	USA	No	189 Lbs	178 CM	No	No	Fantasy Draft		No	No	3	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Jakub Dvorak	Hurricanes	D	21	2005-05-25	CZE	Yes	203 Lbs	196 CM	No	No	Fantasy Draft		No	No	1	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Jordan Harris	Hurricanes	D	26	2000-07-07	USA	No	187 Lbs	180 CM	No	No	Fantasy Draft		No	No	1	2025-08-17	False	False	Pro & Farm	925,000$	925,000$	925,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Matthew Robertson	Hurricanes	D	25	2001-03-09	CAN	No	211 Lbs	193 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Nathan Gaucher	Hurricanes	C	22	2003-11-06	CAN	No	207 Lbs	191 CM	No	No	Fantasy Draft		No	No	1	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Scott Morrow	Hurricanes	D	23	2002-11-01	USA	Yes	210 Lbs	188 CM	No	No	Fantasy Draft		No	No	1	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Tanner Laczynski	Hurricanes	C	29	1997-06-01	USA	No	205 Lbs	185 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Tobie Paquette-Bisson	Hurricanes	D	29	1997-02-01	CAN	No	194 Lbs	191 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Tyrel Bauer	Hurricanes	D	24	2002-03-23	CAN	No	206 Lbs	191 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Vincent Desharnais (1 Way Contract)	Hurricanes	D	30	1996-05-29	CAN	No	226 Lbs	201 CM	No	No	Trade	2025-08-31	Yes	Yes	1	2025-08-17	False	False	Pro & Farm	2,000,000$	2,000,000$	2,000,000$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link / NHL Link
Waltteri Ignatjew	Hurricanes	G	26	1999-12-03	FIN	No	200 Lbs	191 CM	No	No	Fantasy Draft		No	No	3	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Wilmer Skoog	Hurricanes	C	27	1999-07-17	SWE	No	196 Lbs	188 CM	No	No	Fantasy Draft		No	No	3	2025-07-09	False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link
Zachary Hayes	Hurricanes	D	27	1999-04-24	CAN	No	219 Lbs	191 CM	No	No	Fantasy Draft		No	No	3		False	False	Pro & Farm	1,000,000$	1,000,000$	1,000,000$	No	1,000,000$	1,000,000$	-	-	-	-	-	-	-	1,000,000$	1,000,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
28	26.43	204 Lbs	191 CM	2.29	1,028,571$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2			30	1	2	2
3			20	1	2	2
4			10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				60	1	2	2
2				40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	1	2	2			60	1	2	2
2		40	1	2	2			40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense

Extra Forwards
Normal	PowerPlay	Penalty Kill
, ,	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

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	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.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
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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.
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10	text	Any text entered in the filter will match text found within the column

Day	Game	Visitor Team	Score	Home Team	Score
1 - 2025-09-14	2	Chicago Wolves	-	Moose	-
4 - 2025-09-17	20	Chicago Wolves	-	Charlotte Checkers	-
8 - 2025-09-21	42	Phantoms	-	Chicago Wolves	-
11 - 2025-09-24	54	Texas Stars	-	Chicago Wolves	-
13 - 2025-09-26	65	Tucson Roadrunners	-	Chicago Wolves	-
15 - 2025-09-28	78	Henderson Silver Knights	-	Chicago Wolves	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	0%	0%
Attendance PCT	0%	0%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
3	0 - 0%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
0$	0$	0$	2,500,000$0$

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$	19	0$	0$

Chicago Wolves 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

Chicago Wolves 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

Chicago Wolves 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

Chicago Wolves 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

Chicago Wolves 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

	Chicago Wolves
	GP: 0 \| W: 0 \| L: 0 \| OTL: 0 \| P: 0 GF: 0 \| GA: 0 \| PP%: 0% \| PK%: 0% GM : Xavier Berard \| Morale : 40 \| Team Overall : N/A Next Games #2 vs Moose