Carolina Hurricanes
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance

Game Center
	Belleville Senators 3-2-0, 6pts	5	FINAL	2	Chicago Wolves 4-1-0, 8pts

Team Stats
W3	Streak	W1
1-1-0	Home Record	1-1-0
2-1-0	Away Record	3-0-0
3-2-0	Last 10 Games	4-1-0
3.60	Goals Per Game	5.00
3.00	Goals Against Per Game	4.00
41.67%	Power Play Percentage	40.00%
75.00%	Penalty Kill Percentage	66.67%

Chicago Wolves
4-1-0, 8pts

FINAL

Bridgeport Islanders
1-4-0, 2pts

Team Stats
W1	Streak	L4
1-1-0	Home Record	1-2-0
3-0-0	Away Record	0-2-0
4-1-0	Last 10 Games	1-4-0
5.00	Goals Per Game	2.40
4.00	Goals Against Per Game	4.00
40.00%	Power Play Percentage	6.25%
66.67%	Penalty Kill Percentage	80.00%

Chicago Wolves
4-1-0, 8pts

2023-09-21

Belleville Senators
3-2-0, 6pts

Team Stats
W1	Streak	W3
1-1-0	Home Record	1-1-0
3-0-0	Away Record	2-1-0
4-1-0	Last 10 Games	3-2-0
5.00	Goals Per Game	3.60
4.00	Goals Against Per Game	3.60
40.00%	Power Play Percentage	41.67%
66.67%	Penalty Kill Percentage	75.00%

Utica Comets
4-1-0, 8pts

2023-09-22

Chicago Wolves
4-1-0, 8pts

Team Stats
W3	Streak	W1
3-0-0	Home Record	1-1-0
1-1-0	Away Record	3-0-0
4-1-0	Last 10 Games	4-1-0
4.20	Goals Per Game	5.00
3.40	Goals Against Per Game	5.00
16.67%	Power Play Percentage	40.00%
80.00%	Penalty Kill Percentage	66.67%

Wilkes-Barre/Scranton Penguins
2-2-1, 5pts

2023-09-23

Chicago Wolves
4-1-0, 8pts

Team Stats
W1	Streak	W1
0-2-1	Home Record	1-1-0
2-0-0	Away Record	3-0-0
2-2-1	Last 10 Games	4-1-0
4.20	Goals Per Game	5.00
5.60	Goals Against Per Game	5.00
25.00%	Power Play Percentage	40.00%
72.73%	Penalty Kill Percentage	66.67%

Team Leaders
	Goals Arthur Kaliyev 6	Assists Quinton Byfield 6

	Points Arthur Kaliyev 10	Plus/Minus Urho Vaakanainen 8

	Wins Chris Driedger 4	Save Percentage Chris Driedger 0.878

Team Stats
Goals For 25 5.00 GFG	Shots For 213 42.60 Avg	Power Play Percentage 40.0% 6 GF	Offensive Zone Start 43.8%
Goals Against 20 4.00 GAA	Shots Against 164 32.80 Avg	Penalty Kill Percentage 66.7%% 5 GA	Defensive Zone Start 36.2%

Team Info
	General Manager	Chris Floresco
	Coach	Dave Lowry
	Division	Central
	Conference	Western Conference
	Captain	Alex Wennberg
	Assistant #1
	Assistant #2
Arena Info
	Capacity	8,000
	Attendance	0
	Season Tickets	0
Roster Info
	Pro Team	20
	Farm Team	22
	Contract Limit	42 / 45
	Prospects	2

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	Jack McBain	86	X	X			100.00	87	60	77	68	76	69	75	60	65	71	65	73	54	56	58	0	60	69	0	23	1	883,750$
2	Jason Dickinson	81	X	X			100.00	72	48	85	70	77	71	88	62	71	73	62	76	54	65	59	0	60	69	0	28	2	2,650,000$
3	Arthur Kaliyev	17			X		100.00	70	40	87	67	82	64	80	65	51	74	67	67	61	58	58	0	60	68	0	22	2	894,167$
4	Quinton Byfield	49	X				100.00	68	43	77	64	81	65	67	61	68	72	60	68	64	56	57	0	60	66	0	21	2	894,167$
5	Jansen Harkins	20	X	X	X		100.00	63	57	77	63	66	61	69	60	66	64	63	68	54	60	57	0	60	63	0	26	2	850,000$
6	Anders Bjork	27		X	X		100.00	57	48	78	61	69	64	68	59	53	64	59	65	60	62	58	0	60	62	0	27	1	1,600,000$
7	Nathan Smith	58	X		X		100.00	61	52	70	61	65	67	62	57	57	61	60	59	56	58	57	0	60	61	0	24	1	883,750$
8	Pontus Holmberg	80		X	X		100.00	59	49	73	61	69	59	59	59	68	62	59	63	54	57	55	0	60	61	0	24	1	827,500$
9	Oskar Steen	48	X	X	X		100.00	55	57	66	61	60	65	63	59	69	57	59	62	54	60	56	0	60	60	0	25	2	800,000$
10	Topi Ronni (R)	70	X	X			100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	19	4	750,000$
11	Stephen Halliday (R)	82	X	X			100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	21	4	750,000$
12	Braden Schneider	23				X	100.00	70	66	92	70	79	73	79	60	40	71	60	81	54	57	58	0	60	69	0	22	2	925,000$
13	Urho Vaakanainen	28				X	100.00	65	41	91	59	76	76	60	56	40	70	55	78	54	56	58	0	60	66	0	24	2	850,000$
14	Marcus Bjork	72				X	100.00	59	47	63	57	69	66	58	55	38	60	55	64	51	56	54	0	60	59	0	25	1	925,000$
15	Simon Edvinsson	26				X	100.00	54	50	60	56	69	63	59	55	38	56	55	58	51	49	49	0	60	57	0	20	3	925,000$
16	Elias Salomonsson (R)	71				X	100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	19	4	750,000$
Scratches
1	Brayden Pachal	0				X	100.00	59	53	62	60	66	66	64	56	40	58	55	63	54	58	55	0	60	59	0	24	1	750,000$

	TEAM AVERAGE						100.00	61	50	70	60	67	63	64	56	53	62	57	64	54	55	54	0	60	60

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	Akira Schmid	39	100.00	81	65	65	85	77	72	81	72	75	70	77	56	54	0	60	74	0	23	2	850,833$
Scratches
1	Chris Driedger	1	94.00	64	62	62	77	67	60	70	60	62	60	67	66	59	0	60	64	0	29	2	3,500,000$
2	Matt Tomkins	0	100.00	51	51	51	51	51	51	51	51	51	51	51	51	51	0	60	51	0	29	1	750,000$

	TEAM AVERAGE		98.00	65	59	59	71	65	61	67	61	63	60	65	58	55	0	60	63

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Dave Lowry	75	75	75	75	75	75	75	CAN	58	3	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	Team Name	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	S1	S2	S3
1	Arthur Kaliyev	Chicago Wolves (CAR)	RW	5	6	4	10	3	0	8	12	19	6	18	31.58%	1	84	16.90	2	1	3	5	9	0	0	0	1	58.33%	12	1	2.37	2	0	1
2	Quinton Byfield	Chicago Wolves (CAR)	C	5	2	6	8	3	4	12	10	22	6	14	9.09%	0	84	16.99	0	2	2	6	9	0	0	1	0	66.38%	116	0	1.88	1	0	1
3	Jansen Harkins	Chicago Wolves (CAR)	C/LW/RW	5	2	5	7	3	0	12	5	22	5	19	9.09%	3	92	18.48	0	2	2	2	9	1	7	1	0	60.00%	10	0	1.52	0	2	1
4	Nathan Smith	Chicago Wolves (CAR)	C/RW	5	2	5	7	4	2	9	9	21	5	28	9.52%	0	89	17.84	1	1	2	4	10	0	0	0	1	75.00%	4	0	1.57	0	2	0
5	Urho Vaakanainen	Chicago Wolves (CAR)	D	5	0	5	5	8	4	9	3	5	0	2	0.00%	9	85	17.02	0	0	0	0	0	0	3	0	0	0.00%	0	0	1.18	0	0	0
6	Pontus Holmberg	Chicago Wolves (CAR)	LW/RW	5	2	2	4	-1	4	5	9	9	3	12	22.22%	0	60	12.18	0	0	0	0	0	0	0	0	1	71.43%	7	0	1.31	0	0	0
7	Anders Bjork	Chicago Wolves (CAR)	LW/RW	5	3	1	4	-1	0	4	10	23	4	9	13.04%	2	86	17.25	1	1	2	3	11	2	14	1	0	50.00%	6	0	0.93	0	0	0
8	Oskar Steen	Chicago Wolves (CAR)	C/LW/RW	5	1	3	4	-1	0	2	4	12	6	15	8.33%	1	70	14.15	1	1	2	4	8	0	1	0	0	57.50%	80	0	1.13	0	0	0
9	Braden Schneider	Chicago Wolves (CAR)	D	1	0	2	2	1	0	4	2	1	0	3	0.00%	1	21	21.52	0	0	0	1	2	0	5	0	0	0.00%	0	0	1.86	0	0	0
10	Simon Edvinsson	Chicago Wolves (CAR)	D	5	1	0	1	-4	0	5	4	6	1	5	16.67%	4	65	13.15	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.30	0	0	0
11	Jack McBain	Chicago Wolves (CAR)	C/LW	1	1	0	1	1	2	2	3	5	0	4	20.00%	1	19	19.17	0	0	0	1	1	1	4	0	0	50.00%	2	0	1.04	0	0	0
12	Jason Dickinson	Chicago Wolves (CAR)	C/LW	1	0	1	1	1	0	1	5	5	2	8	0.00%	0	20	20.38	0	0	0	1	1	0	5	0	0	60.71%	28	0	0.98	0	0	0
13	Elias Salomonsson	Chicago Wolves (CAR)	D	5	0	0	0	-4	0	8	0	2	1	2	0.00%	0	65	13.15	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0
14	Topi Ronni	Chicago Wolves (CAR)	C/LW	5	0	0	0	-2	0	2	1	0	2	0	0.00%	1	43	8.68	0	0	0	0	0	0	0	0	0	25.00%	4	0	0.00%	0	0	0
15	Marcus Bjork	Chicago Wolves (CAR)	D	5	0	0	0	-2	2	10	2	13	2	6	0.00%	1	43	8.67	0	0	0	0	0	0	0	0	0	33.33%	3	0	0.00%	0	0	0
16	Stephen Halliday	Chicago Wolves (CAR)	C/LW	5	0	0	0	-2	0	2	5	0	0	0	0.00%	0	43	8.68	0	0	0	0	0	0	0	0	0	40.68%	59	0	0.00%	0	0	0
Team Total or Average				68	20	34	54	7	18	95	84	165	43	145	12.12%	24	976	14.36	5	8	13	27	65	4	43	3	3	57.70%	331	1	1.11	3	4	3

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
1	Chris Driedger	Chicago Wolves (CAR)	5	4	1	0	0.878	4.00	300	2	0	20	164	0	0	0	0.00%	0	5	0	0	0	0
Team Total or Average			5	4	1	0	0.878	4.00	300	2	0	20	164	0	0	0		0	5	0	0	0	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	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Waiver Possible	Contract	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Link
Akira Schmid	Chicago Wolves (CAR)	G	23	5/12/2000	No	205 Lbs	6 ft5	No	No	No	No	2	Pro & Farm	850,833$	0$	0$	No	850,833$			Link
Anders Bjork (1 Way Contract)	Chicago Wolves (CAR)	LW/RW	27	8/5/1996	No	190 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	1,600,000$	1,600,000$	1,600,000$	No				Link
Arthur Kaliyev	Chicago Wolves (CAR)	RW	22	6/26/2001	No	210 Lbs	6 ft2	No	No	No	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$			Link
Braden Schneider	Chicago Wolves (CAR)	D	22	9/20/2001	No	208 Lbs	6 ft3	No	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Link
Brayden Pachal	Chicago Wolves (CAR)	D	24	8/23/1999	No	203 Lbs	6 ft2	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Chris Driedger (Out of Payroll)	Chicago Wolves (CAR)	G	29	5/18/1994	No	207 Lbs	6 ft4	No	No	No	No	2	Pro & Farm	3,500,000$	0$	0$	No	3,500,000$			Link
Elias Salomonsson	Chicago Wolves (CAR)	D	19	8/31/2004 4:46:17 AM	Yes	183 Lbs	6 ft1	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Jack McBain	Chicago Wolves (CAR)	C/LW	23	1/6/2000	No	201 Lbs	6 ft3	No	No	No	No	1	Pro & Farm	883,750$	0$	0$	No				Link
Jansen Harkins	Chicago Wolves (CAR)	C/LW/RW	26	5/23/1997	No	197 Lbs	6 ft2	No	No	No	No	2	Pro & Farm	850,000$	0$	0$	No	850,000$			Link
Jason Dickinson (1 Way Contract)	Chicago Wolves (CAR)	C/LW	28	7/4/1995	No	200 Lbs	6 ft2	No	No	No	No	2	Pro & Farm	2,650,000$	2,650,000$	2,650,000$	No	2,650,000$			Link
Marcus Bjork	Chicago Wolves (CAR)	D	25	11/24/1997	No	211 Lbs	6 ft4	No	No	No	No	1	Pro & Farm	925,000$	0$	0$	No				Link
Matt Tomkins	Chicago Wolves (CAR)	G	29	6/19/1994	No	194 Lbs	6 ft3	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Nathan Smith	Chicago Wolves (CAR)	C/RW	24	10/19/1998	No	177 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	883,750$	0$	0$	No				Link
Oskar Steen	Chicago Wolves (CAR)	C/LW/RW	25	3/9/1998	No	193 Lbs	5 ft10	No	No	No	No	2	Pro & Farm	800,000$	0$	0$	No	800,000$			Link
Pontus Holmberg	Chicago Wolves (CAR)	LW/RW	24	3/9/1999	No	202 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	827,500$	0$	0$	No				Link
Quinton Byfield	Chicago Wolves (CAR)	C	21	8/19/2002	No	220 Lbs	6 ft5	No	No	No	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$			Link
Simon Edvinsson	Chicago Wolves (CAR)	D	20	2/5/2003	No	209 Lbs	6 ft6	No	No	No	No	3	Pro & Farm	925,000$	0$	0$	No	925,000$	925,000$		Link
Stephen Halliday	Chicago Wolves (CAR)	C/LW	21	7/2/2002 2:32:31 AM	Yes	214 Lbs	6 ft4	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Topi Ronni	Chicago Wolves (CAR)	C/LW	19	5/5/2004 3:39:10 AM	Yes	181 Lbs	6 ft2	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Urho Vaakanainen	Chicago Wolves (CAR)	D	24	1/1/1999	No	200 Lbs	6 ft2	No	No	No	No	2	Pro & Farm	850,000$	0$	0$	No	850,000$			Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
20	23.75	200 Lbs	6 ft2	2.00	1,100,458$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jansen Harkins	Quinton Byfield	Arthur Kaliyev	30	1	2	2
2	Jack McBain	Jason Dickinson	Nathan Smith	30	1	2	2
3	Anders Bjork	Oskar Steen	Pontus Holmberg	25	1	2	2
4	Topi Ronni	Stephen Halliday	Marcus Bjork	15	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Braden Schneider		30	1	2	2
2	Urho Vaakanainen		30	1	2	2
3	Elias Salomonsson	Simon Edvinsson	25	1	3	1
4	Braden Schneider		15	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jansen Harkins	Quinton Byfield	Arthur Kaliyev	60	1	1	3
2	Jack McBain	Jason Dickinson	Nathan Smith	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Braden Schneider	Anders Bjork	60	1	1	3
2	Oskar Steen		40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Jason Dickinson	Anders Bjork	60	1	3	1
2	Jansen Harkins	Jack McBain	40	1	3	1

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Braden Schneider		60	1	4	0
2	Urho Vaakanainen		40	1	4	0

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Jason Dickinson	60	1	4	0	Braden Schneider		60	1	4	0
2	Jansen Harkins	40	1	4	0	Urho Vaakanainen		40	1	4	0

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Quinton Byfield	Arthur Kaliyev	60	1	2	2
2	Jason Dickinson	Nathan Smith	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Braden Schneider		60	1	2	2
2	Urho Vaakanainen		40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Jack McBain	Quinton Byfield	Arthur Kaliyev	Braden Schneider

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jack McBain	Jason Dickinson	Anders Bjork	Braden Schneider

Extra Forwards
Normal	PowerPlay	Penalty Kill
Jason Dickinson, Jack McBain, Nathan Smith	Jack McBain, Nathan Smith	Jansen Harkins

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, Urho Vaakanainen, Simon Edvinsson		Urho Vaakanainen,

Penalty Shots
Arthur Kaliyev, Jack McBain, Nathan Smith, Quinton Byfield, Jansen Harkins

Goalie
#1 : , #2 : Akira Schmid

Custom OT Lines Forwards
Arthur Kaliyev, Jansen Harkins, Quinton Byfield, Jack McBain, Nathan Smith, Jason Dickinson, Jason Dickinson, Anders Bjork, Oskar Steen, Pontus Holmberg, Stephen Halliday

Custom OT Lines Defensemen
Braden Schneider, , Urho Vaakanainen, , Elias Salomonsson

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
1	Belleville Senators	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	2	5	-3	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	11	6	8	0	35	65	76	72	0	37	10	6	26	0	0	0.00%	3	2	33.33%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32
2	Bridgeport Islanders	1	1	0	0	0	0	0	0	5	2	3	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	2	3	2	1.000	5	9	14	0	0	11	6	8	0	36	65	76	72	0	33	7	14	24	2	0	0.00%	7	1	85.71%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32
3	Laval Rocket	2	2	0	0	0	0	0	0	13	9	4	1	1	0	0	0	0	0	0	6	4	2	1	1	0	0	0	0	0	0	7	5	2	4	1.000	13	23	36	0	0	11	6	8	0	90	65	76	72	0	63	22	6	56	7	3	42.86%	3	1	66.67%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32
4	Lehigh Valley Phantoms	1	1	0	0	0	0	0	0	5	4	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	5	4	1	2	1.000	5	9	14	0	0	11	6	8	0	52	65	76	72	0	31	10	4	26	6	3	50.00%	2	1	50.00%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32
	Total	5	4	1	0	0	0	0	0	25	20	5	2	1	1	0	0	0	0	0	8	9	-1	3	3	0	0	0	0	0	0	17	11	6	8	0.800	25	45	70	0	0	11	6	8	0	213	65	76	72	0	164	49	30	132	15	6	40.00%	15	5	66.67%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32
	_Since Last GM Reset	5	4	1	0	0	0	0	0	25	20	5	2	1	1	0	0	0	0	0	8	9	-1	3	3	0	0	0	0	0	0	17	11	6	8	0.800	25	45	70	0	0	11	6	8	0	213	65	76	72	0	164	49	30	132	15	6	40.00%	15	5	66.67%	0	114	195	58.46%	90	161	55.90%	48	89	53.93%	129	93	108	32	62	32

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
5	8	W1	25	45	70	213	164	49	30	132	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	4	1	0	0	0	0	25	20

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	8	9

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	3	0	0	0	0	0	17	11

Last 10 Games
W	L	OTW	OTL	SOW	SOL
4	1	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
15	6	40.00%	15	5	66.67%	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
65	76	72	0	11	6	8	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
114	195	58.46%	90	161	55.90%	48	89	53.93%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
129	93	108	32	62	32

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	Link
1 - 2023-09-15	9	Laval Rocket	4	Chicago Wolves	6	BW	BoxScore
2 - 2023-09-16	23	Chicago Wolves	5	Lehigh Valley Phantoms	4	AW	BoxScore
4 - 2023-09-18	36	Chicago Wolves	7	Laval Rocket	5	AW	BoxScore
5 - 2023-09-19	55	Belleville Senators	5	Chicago Wolves	2	BL	BoxScore
6 - 2023-09-20	77	Chicago Wolves	5	Bridgeport Islanders	2	AW	BoxScore
7 - 2023-09-21	83	Chicago Wolves	-	Belleville Senators	-
8 - 2023-09-22	97	Utica Comets	-	Chicago Wolves	-
9 - 2023-09-23	114	Wilkes-Barre/Scranton Penguins	-	Chicago Wolves	-
11 - 2023-09-25	137	Syracuse Crunch	-	Chicago Wolves	-
13 - 2023-09-27	150	Chicago Wolves	-	Wilkes-Barre/Scranton Penguins	-
15 - 2023-09-29	172	Charlotte Checkers	-	Chicago Wolves	-
17 - 2023-10-01	189	Chicago Wolves	-	Toronto Marlies	-
19 - 2023-10-03	202	Cleveland Monsters	-	Chicago Wolves	-
21 - 2023-10-05	218	Chicago Wolves	-	Rochester Americans	-
23 - 2023-10-07	238	Lehigh Valley Phantoms	-	Chicago Wolves	-
24 - 2023-10-08	246	Chicago Wolves	-	Cleveland Monsters	-
25 - 2023-10-09	270	Chicago Wolves	-	Springfield Thunderbirds	-
26 - 2023-10-10	283	Rochester Americans	-	Chicago Wolves	-
27 - 2023-10-11	293	Providence Bruins	-	Chicago Wolves	-
29 - 2023-10-13	315	Chicago Wolves	-	Hershey Bears	-
30 - 2023-10-14	334	Abbotsford Canucks	-	Chicago Wolves	-
32 - 2023-10-16	353	Chicago Wolves	-	Providence Bruins	-
33 - 2023-10-17	361	Chicago Wolves	-	Abbotsford Canucks	-
34 - 2023-10-18	371	Hartford Wolf Pack	-	Chicago Wolves	-
35 - 2023-10-19	391	Chicago Wolves	-	Syracuse Crunch	-
36 - 2023-10-20	402	Toronto Marlies	-	Chicago Wolves	-
Trade Deadline --- Trades can’t be done after this day is simulated!
38 - 2023-10-22	431	Hershey Bears	-	Chicago Wolves	-
39 - 2023-10-23	450	Springfield Thunderbirds	-	Chicago Wolves	-
41 - 2023-10-25	470	Chicago Wolves	-	Hartford Wolf Pack	-
43 - 2023-10-27	483	Bridgeport Islanders	-	Chicago Wolves	-
44 - 2023-10-28	487	Chicago Wolves	-	Charlotte Checkers	-
45 - 2023-10-29	502	Chicago Wolves	-	Utica Comets	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	4500	3500
Ticket Price	35	0
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
14	0 - 0.00%	0$	0$	8000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,425,917$	1,200,917$	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$	41	0$	0$

Chicago Wolves Players 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

Chicago Wolves Goalies Stat Leaders (Regular Season)

Show or Hide Column

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

Chicago Wolves 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

Chicago Wolves Players 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	PSG	PSS

Chicago Wolves Goalies Stat Leaders (Play-Off)

Show or Hide Column

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

	Chicago Wolves
	GP: 5 \| W: 4 \| L: 1 \| OTL: 0 \| P: 8 GF: 25 \| GA: 20 \| PP%: 40.00% \| PK%: 66.67% GM : Chris Floresco \| Morale : 60 \| Team Overall : 61 Next Games #83 vs Belleville Senators