Ligue Hockey General Manager Québec

Roster

Player	#	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Alexander Nylander	92	RW	97.00	63	33	88	66	76	81	71	67	60	60	76	57	71	69	68	0	66	76	27	1,000,000$/1yrs
Cody Glass	0	C/RW	100.00	65	33	87	65	83	79	83	64	79	66	66	60	65	67	66	0	63	75	26	1,250,000$/1yrs
Martin Kaut	0	C/RW	100.00	63	33	95	58	76	73	71	60	59	59	62	55	61	66	65	0	37	70	25	1,000,000$/1yrs
Pavol Regenda	0	LW/RW	99.00	68	34	89	58	86	73	68	56	58	58	57	69	56	66	65	0	60	70	25	950,000$/2yrs
Juha Jaaska	0	LW/RW	98.00	75	40	76	57	76	67	89	55	37	58	57	68	58	68	66	0	64	69	27	850,000$/1yrs
Joakim Kemell (R)	0	RW	100.00	66	39	81	59	71	64	79	57	41	57	58	60	57	56	54	0	69	68	20	918,333$/2yrs
Mathias Laferriere	0	RW	100.00	62	38	87	54	73	63	86	61	65	55	52	65	53	63	61	0	68	67	24	900,000$/2yrs
Corey Andonovski	0	RW	100.00	81	42	55	53	77	63	87	62	39	54	51	66	52	64	60	0	70	67	26	800,000$/2yrs
Noel Gunler	0	LW/RW	100.00	63	38	86	55	72	63	70	60	41	54	55	63	55	61	59	0	68	67	23	862,500$/1yrs
Justin Robidas (R)	0	C	100.00	56	37	92	63	64	68	60	61	67	56	52	61	62	58	57	0	58	67	22	825,000$/2yrs
Sam Morton	0	LW	100.00	61	38	89	54	71	63	67	62	42	49	59	66	54	64	63	0	58	67	25	870,000$/1yrs
Chase Stillman (R)	0	RW	100.00	82	41	55	55	74	62	74	58	35	50	56	62	53	57	53	0	41	66	22	863,333$/2yrs
Ivan Ivan (R)	0	C	100.00	61	38	89	55	74	62	77	59	63	54	53	63	53	59	58	0	26	66	22	845,000$/2yrs
Mike Reilly	6	D	100.00	67	33	84	60	77	84	76	58	30	67	60	58	59	77	75	0	49	75	31	1,200,000$/2yrs
Brett Kulak	0	D	100.00	69	34	85	56	78	83	90	58	30	63	55	67	57	76	75	0	67	73	31	1,850,000$/1yrs
Jack Johnson	0	D	100.00	70	34	86	55	88	84	90	57	30	59	55	69	56	88	87	0	67	73	38	800,000$/1yrs
Alexander Alexeyev	0	D	100.00	69	34	94	55	85	80	76	54	30	58	53	65	54	66	65	0	55	70	25	825,000$/1yrs
Ronnie Attard (R)	0	D	100.00	69	40	78	50	83	66	83	51	30	56	54	67	55	65	62	0	69	68	26	850,000$/1yrs
Maxence Guenette	0	D	100.00	62	39	88	55	79	65	86	51	30	60	50	64	55	61	60	0	73	68	23	800,000$/1yrs
Scratches
Julien Gauthier	0	RW	52.94	79	34	94	61	90	70	78	61	59	58	66	58	63	69	69	0	55	73	27	1,000,000$/1yrs
Max Comtois	0	C/LW	100.00	71	49	60	61	83	78	75	60	61	62	64	55	62	67	63	0	19	72	26	800,000$/1yrs
Austin Wagner	51	LW	100.00	83	40	64	54	77	67	68	63	51	51	61	64	56	68	65	0	20	69	27
Carson Focht (R)	0	C	100.00	63	38	86	52	71	61	66	62	65	45	57	65	51	62	61	0	20	66	25
Jaydon Dureau (R)	0	LW	100.00	58	37	95	48	67	58	68	61	41	47	47	64	47	61	60	0	20	63	24	841,667$/1yrs
Ondrej Pavel	0	C/LW/RW	100.00	64	39	84	53	81	62	72	61	63	44	44	65	52	63	61	0	20	63	24	870,000$/1yrs
Blake McLaughlin (R)	0	LW	100.00	65	38	82	46	63	57	74	62	68	46	45	66	46	62	60	0	19	63	25	950,000$/1yrs
Dmitri Semykin	13	D	100.00	57	39	96	57	83	60	60	55	30	51	49	64	58	61	63	0	20	67	25
Colin Swoyer	0	D	100.00	65	39	83	49	72	61	72	46	30	54	46	67	50	66	64	0	20	65	27
Cole McWard	0	D	100.00	61	38	91	47	76	62	74	46	30	52	50	63	51	61	60	0	22	64	23	900,000$/1yrs
Mikko Kokkonen (R)	0	D	100.00	66	39	81	46	77	60	83	45	30	51	47	64	49	61	59	0	20	63	24	846,667$/1yrs
Anton Malmstrom	0	D	100.00	65	40	83	43	83	58	70	43	30	48	46	65	47	62	61	0	20	62	25	910,000$/1yrs
Luke Krys	0	D	100.00	75	40	66	43	75	59	67	43	30	47	48	65	47	62	59	0	20	62	24	870,000$/1yrs

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	#	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Filip Larsson	29	97.00	75	81	77	75	83	77	76	75	77	75	76	68	76	0	42	80	26	775,000$/1yrs
Yaroslav Askarov	0	100.00	77	89	65	74	71	74	71	76	74	82	71	62	65	0	52	78	22	925,000$/1yrs
Scratches
Dom DiVincentiis	0	100.00	73	79	69	74	70	72	72	73	72	74	72	57	59	0	47	76	21	858,333$/2yrs
Nico Daws	0	100.00	72	67	68	84	69	62	71	74	72	74	71	64	68	0	22	75	24	1,100,000$/2yrs

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Dave Tippett	76	80	84	82	91	84	55	CAN	63	3	1,000,000$

General Manager

Player Stats

Show or Hide Column

Filter Tips

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	SHT	OSB	OSM	SHT%	SB	AMG	PPG	PPA	PPP	PPM	PKP	PKM	GW	GT	FO%	FOT	TA	EG	HT	P/20	PSG	PSS
1	Cody Glass	Bears (WSH)	C/RW	59	21	29	50	1	20	0	65	231	62	144	9.09%	20	20.79	8	10	18	127	0	133	3	1	56.21%	991	0	0	0	0.82	0	2
2	Pavol Regenda	Bears (WSH)	LW/RW	67	22	23	45	0	30	0	94	196	53	176	11.22%	16	19.93	7	7	14	183	0	120	3	1	43.15%	146	0	0	0	0.67	0	0
3	Jack Johnson	Bears (WSH)	D	67	8	32	40	3	30	0	109	75	30	60	10.67%	92	20.27	4	7	11	118	0	139	2	1	0.00%	1	0	0	0	0.59	0	0
4	Alexander Alexeyev	Bears (WSH)	D	61	6	30	36	-11	20	0	64	94	23	50	6.38%	78	21.72	2	12	14	155	0	147	1	0	0.00%	0	0	0	0	0.54	0	0
5	Justin Robidas	Bears (WSH)	C	66	13	23	36	-4	8	0	17	147	42	137	8.84%	7	17.10	4	7	11	114	0	21	4	0	49.82%	1130	0	0	0	0.64	0	0
6	Julien Gauthier	Bears (WSH)	RW	61	18	13	31	2	22	0	81	168	55	124	10.71%	8	18.44	5	4	9	120	0	68	2	4	46.95%	541	0	1	0	0.55	0	2
7	Brett Kulak	Bears (WSH)	D	67	9	21	30	-7	42	0	130	91	31	81	9.89%	91	21.85	5	8	13	148	0	123	0	1	0.00%	0	0	0	0	0.41	0	0
8	Mike Reilly	Bears (WSH)	D	40	8	22	30	-1	26	0	73	61	16	47	13.11%	55	23.62	6	12	18	109	0	104	2	1	0.00%	0	0	0	0	0.63	0	0
9	Juha Jaaska	Bears (WSH)	LW/RW	66	11	19	30	-4	29	5	125	147	37	132	7.48%	23	17.57	2	7	9	130	0	58	0	0	36.14%	285	0	0	0	0.52	0	0
10	Alexander Nylander	Bears (WSH)	RW	37	13	16	29	15	16	0	36	119	46	107	10.92%	6	19.24	4	5	9	85	0	66	2	2	43.15%	584	0	0	0	0.81	0	4
11	Ronnie Attard	Bears (WSH)	D	67	4	22	26	-4	60	0	132	67	19	46	5.97%	90	18.44	1	2	3	123	0	84	2	1	0.00%	0	0	0	0	0.42	0	0
12	Maxence Guenette	Bears (WSH)	D	67	2	24	26	8	13	5	75	61	24	29	3.28%	75	17.95	0	6	6	106	0	125	0	0	0.00%	0	0	0	0	0.43	0	0
13	Corey Andonovski	Bears (WSH)	RW	67	11	12	23	2	42	0	155	101	32	87	10.89%	13	12.28	2	2	4	56	0	0	2	0	36.69%	447	0	0	0	0.56	0	1
14	Joakim Kemell	Bears (WSH)	RW	67	13	10	23	-3	16	0	57	125	36	86	10.40%	8	13.86	1	2	3	75	0	75	4	0	34.19%	234	0	0	0	0.50	0	0
15	Mathias Laferriere	Bears (WSH)	RW	65	5	7	12	5	0	0	11	47	13	37	10.64%	5	6.12	2	2	4	66	0	46	1	0	53.19%	94	0	0	0	0.60	0	2
16	Sam Morton	Bears (WSH)	LW	66	3	6	9	-19	14	0	32	76	18	52	3.95%	8	9.06	0	0	0	0	0	2	0	1	43.63%	463	0	0	0	0.30	0	0
17	Noel Gunler	Bears (WSH)	LW/RW	64	4	4	8	5	2	0	11	67	16	45	5.97%	2	7.73	0	0	0	14	0	21	1	1	29.17%	24	0	0	0	0.32	0	0
18	Martin Kaut	Bears (WSH)	C/RW	26	1	4	5	4	6	0	15	38	12	21	2.63%	2	13.12	0	0	0	2	0	19	0	0	45.83%	48	0	0	0	0.29	0	0
19	Chase Stillman	Bears (WSH)	RW	39	2	3	5	0	0	0	5	5	1	2	40.00%	1	0.94	0	1	1	8	0	0	2	0	25.00%	12	0	0	0	2.74	0	0
20	Max Comtois	Bears (WSH)	C/LW	4	1	1	2	-3	0	0	10	11	2	5	9.09%	3	21.51	0	1	1	10	0	7	0	0	46.32%	95	0	0	0	0.46	0	0
21	Cole McWard	Bears (WSH)	D	5	1	0	1	-1	0	0	5	4	0	4	25.00%	3	17.21	0	0	0	0	0	0	0	0	0.00%	0	0	0	0	0.23	0	0
22	Ivan Ivan	Bears (WSH)	C	22	1	0	1	-1	0	0	0	1	0	0	100.00%	0	0.19	1	0	1	1	0	0	1	0	75.00%	4	0	0	0	4.84	0	0
23	Blake McLaughlin	Bears (WSH)	LW	36	0	0	0	-1	2	0	1	2	1	3	0.00%	0	0.30	0	0	0	4	0	1	0	0	0.00%	2	0	0	0	0.00	0	0
Team Total or Average			1186	177	321	498	-14	398	10	1303	1934	569	1475	9.15%	606	15.20	54	95	149	1765	0	1370	32	14	46.40%	5101	0	1	0	0.55	0	11

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	Yaroslav Askarov	Bears (WSH)	37	19	17	0	0.914	2.73	2065	2	2	94	1087	0	0	1	1.000	3	37	23	4	4	3
2	Dom DiVincentiis	Bears (WSH)	18	8	5	2	0.936	2.23	1022	0	0	38	590	0	2	0	0.600	5	15	23	3	2	0
3	Filip Larsson	Bears (WSH)	6	5	0	1	0.929	2.30	365	2	0	14	196	0	1	0	0.667	3	6	1	1	0	0
Team Total or Average		61	32	22	3	0.922	2.54	3453	4	2	146	1873	0	3	1	0.727	11	58	47	8	6	3

Salary

Player Name	POS	Age	Cap Hit	2020-21	2021-22	2022-23
Alexander Alexeyev	D	25	825,000$	825,000$	RFA
Alexander Nylander	RW	27	1,000,000$	1,000,000$	UFA
Anton Malmstrom	D	25	910,000$	910,000$	RFA
Austin Wagner	LW	27	0$	UFA
Blake McLaughlin	LW	25	950,000$	950,000$	RFA
Brett Kulak	D	31	1,850,000$	1,850,000$	UFA
Carson Focht	C	25	0$	RFA
Chase Stillman	RW	22	863,333$	863,333$	863,333$	RFA
Cody Glass	C/RW	26	1,250,000$	1,250,000$	RFA
Cole McWard	D	23	900,000$	900,000$	RFA
Colin Swoyer	D	27	0$	UFA
Corey Andonovski	RW	26	800,000$	800,000$	800,000$	UFA
Dmitri Semykin	D	25	0$	RFA
Dom DiVincentiis	G	21	858,333$	858,333$	858,333$	RFA
Filip Larsson	G	26	775,000$	775,000$	RFA
Ivan Ivan	C	22	845,000$	845,000$	845,000$	RFA
Jack Johnson	D	38	800,000$	800,000$	UFA
Jaydon Dureau	LW	24	841,667$	841,667$	RFA
Joakim Kemell	RW	20	918,333$	918,333$	918,333$	RFA
Juha Jaaska	LW/RW	27	850,000$	850,000$	UFA
Julien Gauthier	RW	27	1,000,000$	1,000,000$	UFA
Justin Robidas	C	22	825,000$	825,000$	825,000$	RFA
Luke Krys	D	24	870,000$	870,000$	RFA
Martin Kaut	C/RW	25	1,000,000$	1,000,000$	RFA
Mathias Laferriere	RW	24	900,000$	900,000$	900,000$	RFA
Max Comtois	C/LW	26	800,000$	800,000$	RFA
Maxence Guenette	D	23	800,000$	800,000$	RFA
Mike Reilly	D	31	1,200,000$	1,200,000$	1,200,000$	UFA
Mikko Kokkonen	D	24	846,667$	846,667$	RFA
Nico Daws	G	24	1,100,000$	1,100,000$	1,100,000$	RFA
Noel Gunler	LW/RW	23	862,500$	862,500$	RFA
Ondrej Pavel	C/LW/RW	24	870,000$	870,000$	RFA
Pavol Regenda	LW/RW	25	950,000$	950,000$	950,000$	RFA
Ronnie Attard	D	26	850,000$	850,000$	RFA
Sam Morton	LW	25	870,000$	870,000$	RFA
Yaroslav Askarov	G	22	925,000$	925,000$	RFA

Lines

Forward Lines
# - Pavol Regenda	# - Alexander Nylander	# - Martin Kaut
# - Juha Jaaska	# - Justin Robidas	# - Cody Glass
# - Noel Gunler	# - Corey Andonovski	# - Joakim Kemell
# - Sam Morton	# - Alexander Nylander	# - Corey Andonovski

Defensive Pairings
# - Brett Kulak	# - Alexander Alexeyev
# - Jack Johnson	# - Mike Reilly
# - Ronnie Attard	# - Maxence Guenette

1st Power Play Unit
# - Pavol Regenda		# - Alexander Nylander		# - Corey Andonovski
# - Ronnie Attard			# - Mike Reilly

2nd Power Play Unit
# - Juha Jaaska		# - Justin Robidas		# - Mathias Laferriere
# - Jack Johnson			# - Maxence Guenette

Goalies
# - Filip Larsson		# - Yaroslav Askarov

Team Stats

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

#	VS Team	GP	W	L	OTW	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%	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	GF%	SH%	SV%	PDO	PDOBRK
1	Wranglers	1	1	0	0	0	0	5	3	2	2	1.000	5	10	15	0	0	71	66	55	5	35	664	719	752	31	45	8	12	21	3	1	33.33%	5	1	80.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	66.7%	14.3%	93.3%	107.6	LUCKY
2	Phantoms	5	2	2	0	0	1	12	11	1	5	0.500	12	22	34	0	0	71	66	55	5	130	664	719	752	31	159	45	50	121	19	4	21.05%	18	3	83.33%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	9.2%	93.1%	102.3	LUCKY
3	Comets	2	1	1	0	0	0	5	5	0	2	0.500	5	10	15	0	0	71	66	55	5	72	664	719	752	31	64	18	14	44	6	2	33.33%	7	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	37.5%	6.9%	92.2%	99.1	DULL
4	Senators	2	1	0	1	0	0	5	2	3	4	1.000	5	9	14	0	0	71	66	55	5	43	664	719	752	31	62	23	16	36	4	1	25.00%	8	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	66.7%	11.6%	96.8%	108.4	LUCKY
5	Islanders	2	1	1	0	0	0	4	4	0	2	0.500	4	7	11	0	0	71	66	55	5	77	664	719	752	31	59	24	15	48	7	1	14.29%	5	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	42.9%	5.2%	93.2%	98.4	DULL
6	Wolves	1	1	0	0	0	0	4	1	3	2	1.000	4	7	11	0	0	71	66	55	5	34	664	719	752	31	27	11	0	26	5	0	0.00%	0	0	0.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	80.0%	11.8%	96.3%	108.1	LUCKY
7	Eagles	1	0	1	0	0	0	4	5	-1	0	0.000	4	7	11	0	0	71	66	55	5	28	664	719	752	31	28	10	4	17	5	1	20.00%	2	1	50.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	42.9%	14.3%	82.1%	96.4	FUN
8	Wolf Pack	4	1	1	1	1	0	12	9	3	6	0.750	12	19	31	0	0	71	66	55	5	131	664	719	752	31	142	57	36	95	13	4	30.77%	18	2	88.89%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	53.3%	9.2%	93.7%	102.8	LUCKY
9	Griffins	3	1	2	0	0	0	8	5	3	2	0.333	8	14	22	0	1	71	66	55	5	102	664	719	752	31	102	32	22	66	14	4	28.57%	10	2	80.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	57.1%	7.8%	95.1%	102.9	DULL
10	Rocket	2	2	0	0	0	0	9	6	3	4	1.000	9	16	25	0	0	71	66	55	5	83	664	719	752	31	54	21	10	60	7	3	42.86%	5	1	80.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	54.5%	10.8%	88.9%	99.7	FUN
11	Wild	1	1	0	0	0	0	5	3	2	2	1.000	5	10	15	0	0	71	66	55	5	42	664	719	752	31	29	11	4	24	1	1	100.00%	1	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	57.1%	11.9%	89.7%	101.6	FUN
12	Canucks	1	1	0	0	0	0	4	1	3	2	1.000	4	7	11	0	0	71	66	55	5	35	664	719	752	31	22	3	6	24	3	1	33.33%	3	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	75.0%	11.4%	95.5%	106.9	LUCKY
13	Reign	1	1	0	0	0	0	5	2	3	2	1.000	5	9	14	0	0	71	66	55	5	45	664	719	752	31	20	7	11	22	4	1	25.00%	3	1	66.67%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	80.0%	11.1%	90.0%	101.1	FUN
14	Admirals	1	1	0	0	0	0	3	2	1	2	1.000	3	4	7	0	0	71	66	55	5	27	664	719	752	31	22	8	8	15	3	0	0.00%	4	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	60.0%	11.1%	90.9%	102.0	FUN
15	Crunch	2	1	1	0	0	0	8	6	2	2	0.500	8	15	23	0	0	71	66	55	5	71	664	719	752	31	65	22	8	40	6	2	33.33%	4	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	11.3%	90.8%	102.0	FUN
16	Condors	1	0	1	0	0	0	0	5	-5	0	0.000	0	0	0	0	0	71	66	55	5	24	664	719	752	31	30	7	6	18	1	0	0.00%	3	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	0.0%	0.0%	83.3%	83.3	Unlucky
17	Thunderbirds	4	1	2	1	0	0	13	11	2	4	0.500	13	23	36	0	0	71	66	55	5	126	664	719	752	31	135	38	32	110	15	4	26.67%	14	2	85.71%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	10.3%	91.9%	102.2	LUCKY
18	Roadrunners	1	0	0	0	0	1	2	3	-1	1	0.500	2	3	5	0	0	71	66	55	5	31	664	719	752	31	38	13	8	20	1	0	0.00%	4	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	40.0%	6.5%	92.1%	98.6	DULL
19	Bruins	3	1	2	0	0	0	8	11	-3	2	0.333	8	16	24	0	0	71	66	55	5	89	664	719	752	31	106	14	20	69	5	2	40.00%	10	2	80.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	40.0%	9.0%	89.6%	98.6	FUN
20	Americans	3	1	2	0	0	0	4	8	-4	2	0.333	4	7	11	0	0	71	66	55	5	76	664	719	752	31	103	30	18	61	10	1	10.00%	9	1	88.89%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	30.0%	5.3%	92.2%	97.5	DULL
21	IceHogs	1	0	1	0	0	0	1	2	-1	0	0.000	1	1	2	0	0	71	66	55	5	28	664	719	752	31	36	9	4	18	6	0	0.00%	2	1	50.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	3.6%	94.4%	98.0	DULL
22	Checkers	4	4	0	0	0	0	10	4	6	8	1.000	10	17	27	0	1	71	66	55	5	125	664	719	752	31	118	31	37	81	14	4	28.57%	14	1	92.86%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	66.7%	8.0%	96.6%	104.6	DULL
23	Monsters	5	2	3	0	0	0	11	17	-6	4	0.400	11	19	30	0	0	71	66	55	5	163	664	719	752	31	167	55	33	108	22	4	18.18%	12	3	75.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	33.3%	6.7%	89.8%	96.6	Unlucky
24	Moose	1	1	0	0	0	0	5	2	3	2	1.000	5	9	14	0	0	71	66	55	5	27	664	719	752	31	31	16	2	19	0	0	0.00%	1	1	0.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	83.3%	18.5%	93.5%	112.1	LUCKY
25	Gulls	4	1	3	0	0	0	14	15	-1	2	0.250	14	24	38	0	0	71	66	55	5	135	664	719	752	31	170	35	28	101	15	4	26.67%	14	3	78.57%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	45.5%	10.4%	91.2%	101.5	LUCKY
26	Stars	1	0	1	0	0	0	1	2	-1	0	0.000	1	2	3	0	0	71	66	55	5	21	664	719	752	31	32	4	6	27	2	0	0.00%	3	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	33.3%	4.8%	93.8%	98.5	DULL
27	Marlies	2	2	0	0	0	0	8	6	2	4	1.000	8	15	23	0	0	71	66	55	5	78	664	719	752	31	63	25	18	44	11	3	27.27%	9	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	45.5%	10.3%	90.5%	100.7	FUN
28	Penguins	4	1	1	1	0	1	9	10	-1	5	0.625	9	15	24	1	0	71	66	55	5	140	664	719	752	31	114	36	23	86	13	2	15.38%	6	1	83.33%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	43.8%	6.4%	91.2%	97.7	DULL
29	Barracuda	2	1	1	0	0	0	9	7	2	2	0.500	9	16	25	0	0	71	66	55	5	64	664	719	752	31	57	12	12	42	10	4	40.00%	5	2	60.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	14.1%	87.7%	101.8	FUN
30	Silver Knights	1	1	0	0	0	0	4	1	3	2	1.000	4	8	12	0	0	71	66	55	5	37	664	719	752	31	25	8	6	27	5	3	60.00%	2	1	50.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	100.0%	10.8%	96.0%	106.8	LUCKY
31	Firebirds	1	1	0	0	0	0	5	2	3	2	1.000	5	8	13	0	0	71	66	55	5	35	664	719	752	31	26	7	6	18	5	3	60.00%	3	0	100.00%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	50.0%	14.3%	92.3%	106.6	LUCKY
	_Vs Division	21	11	9	3	1	2	60	48	12	32	0.762	60	109	169	0	2	71	66	55	5	667	664	719	752	31	673	198	149	457	71	20	28.17%	69	7	89.86%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	49.4%	9.0%	92.9%	101.9	LUCKY
	_Vs Conference	47	22	18	4	1	2	126	115	11	56	0.596	126	224	350	1	2	71	66	55	5	1506	664	719	752	31	1513	471	352	1069	166	41	24.70%	149	18	87.92%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	46.7%	8.4%	92.4%	100.8	DULL
	_Since Last GM Reset	67	33	26	4	1	3	197	171	26	79	0.590	197	349	546	1	2	71	66	55	5	2154	664	719	752	31	2151	640	475	1508	235	60	25.53%	204	29	85.78%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	49.1%	9.1%	92.1%	101.2	LUCKY
	Total	67	33	26	4	1	3	197	171	26	79	0.590	197	349	546	1	2	71	66	55	5	2154	664	719	752	31	2151	640	475	1508	235	60	25.53%	204	29	85.78%	1145	2393	47.85%	1099	2407	45.66%	498	1042	47.79%	1597	1080	1565	514	889	441	49.1%	9.1%	92.1%	101.2	LUCKY

	Puck Time
Offensive Zone	23
Neutral Zone	13
Defensive Zone	23

	Puck Time
Offensive Zone Start	2393
Neutral Zone Start	1042
Defensive Zone Start	2407

	Puck Time
With Puck	30
Without Puck	30

	Faceoffs
Faceoffs Won	2742
Faceoffs Lost	3100

	Team Average Shots after	League Average Shots after
1st Period	9.9	9.57
2nd Period	20.6	20.31
3rd Period	31.9	30.68
Overtime	32.3	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.1	0.64
2nd Period	2.0	1.65
3rd Period	2.9	2.67
Overtime	2.9	2.83


Even Strenght Goal	136
PP Goal	60
PK Goal	0
Empty Net Goal	1

	Home	Away
Win	20	18
Lost	11	15
Overtime Lost	2	1


PP Attempt	235
PP Goal	60
PK Attempt	204
PK Goal Against	29

	Home
Shots For	32.1
Shots Against	32.1
Goals For	2.9
Goals Against	2.6
Hits	22.5
Shots Blocked	9.6
Pim	7.1

Schedule

Date	Matchup			Result	Detail
2024-10-07	Bears	@	Gulls	Bears8,Gulls5	RECAP
2024-10-09	Bears	@	Monsters	Bears0,Monsters4	RECAP
2024-10-10	Phantoms	@	Bears	Phantoms3,Bears1	RECAP
2024-10-12	Bears	@	Monsters	Bears3,Monsters4	RECAP
2024-10-15	Checkers	@	Bears	Checkers2,Bears4	RECAP
2024-10-18	Checkers	@	Bears	Checkers1,Bears3	RECAP
2024-10-20	Bears	@	Americans	Bears2,Americans4	RECAP
2024-10-24	Bears	@	Checkers	Bears1,Checkers0	RECAP
2024-10-25	Wolf Pack	@	Bears	Wolf Pack4,Bears3	RECAP
2024-10-28	Islanders	@	Bears	Islanders3,Bears2	RECAP
2024-10-30	Bears	@	Bruins	Bears2,Bruins6	RECAP
2024-10-31	Bears	@	Penguins	Bears2,Penguins1 (OT)	RECAP
2024-11-02	Bears	@	Thunderbirds	Bears2,Thunderbirds4	RECAP
2024-11-03	Barracuda	@	Bears	Barracuda5,Bears3	RECAP
2024-11-06	Bruins	@	Bears	Bruins1,Bears3	RECAP
2024-11-08	Bears	@	Monsters	Bears3,Monsters2	RECAP
2024-11-10	Bears	@	Crunch	Bears5,Crunch1	RECAP
2024-11-12	Monsters	@	Bears	Monsters3,Bears4	RECAP
2024-11-14	Bears	@	Wolves	Bears4,Wolves1	RECAP
2024-11-16	Rocket	@	Bears	Rocket2,Bears4	RECAP
2024-11-18	Bears	@	IceHogs	Bears1,IceHogs2	RECAP
2024-11-19	Griffins	@	Bears	Griffins3,Bears1	RECAP
2024-11-22	Bears	@	Rocket	Bears5,Rocket4	RECAP
2024-11-23	Bears	@	Americans	Bears0,Americans3	RECAP
2024-11-24	Barracuda	@	Bears	Barracuda2,Bears6	RECAP
2024-11-27	Bears	@	Comets	Bears2,Comets3	RECAP
2024-11-28	Condors	@	Bears	Condors5,Bears0	RECAP
2024-12-01	Bears	@	Monsters	Bears1,Monsters4	RECAP
2024-12-04	Penguins	@	Bears	Penguins3,Bears1	RECAP
2024-12-06	Bears	@	Firebirds	Bears5,Firebirds2	RECAP
2024-12-10	Thunderbirds	@	Bears	Thunderbirds3,Bears2	RECAP
2024-12-13	Bears	@	Wolf Pack	Bears2,Wolf Pack1 (SO)	RECAP
2024-12-14	Stars	@	Bears	Stars2,Bears1	RECAP
2024-12-21	Bears	@	Eagles	Bears4,Eagles5	RECAP
2024-12-23	Wolf Pack	@	Bears	Wolf Pack3,Bears4 (OT)	RECAP
2024-12-27	Reign	@	Bears	Reign2,Bears5	RECAP
2024-12-29	Bears	@	Bruins	Bears3,Bruins4	RECAP
2025-01-01	Islanders	@	Bears	Islanders1,Bears2	RECAP
2025-01-05	Wranglers	@	Bears	Wranglers3,Bears5	RECAP
2025-01-07	Bears	@	Griffins	Bears7,Griffins0	RECAP
2025-01-09	Silver Knights	@	Bears	Silver Knights1,Bears4	RECAP
2025-01-13	Bears	@	Checkers	Bears2,Checkers1	RECAP
2025-01-16	Crunch	@	Bears	Crunch5,Bears3	RECAP
2025-01-18	Wild	@	Bears	Wild3,Bears5	RECAP
2025-01-22	Bears	@	Canucks	Bears4,Canucks1	RECAP
2025-01-24	Bears	@	Penguins	Bears2,Penguins3 (SO)	RECAP
2025-01-25	Bears	@	Gulls	Bears2,Gulls3	RECAP
2025-01-26	Moose	@	Bears	Moose2,Bears5	RECAP
2025-01-29	Penguins	@	Bears	Penguins3,Bears4	RECAP
2025-02-01	Senators	@	Bears	Senators1,Bears2 (OT)	RECAP
2025-02-02	Bears	@	Senators	Bears3,Senators1	RECAP
2025-02-06	Bears	@	Wolf Pack	Bears3,Wolf Pack1	RECAP
2025-02-09	Americans	@	Bears	Americans1,Bears2	RECAP
2025-02-12	Gulls	@	Bears	Gulls4,Bears2	RECAP
2025-02-14	Bears	@	Admirals	Bears3,Admirals2	RECAP
2025-02-15	Bears	@	Griffins	Bears0,Griffins2	RECAP
2025-02-17	Comets	@	Bears	Comets2,Bears3	RECAP
2025-02-22	Roadrunners	@	Bears	Roadrunners3,Bears2 (SO)	RECAP
2025-02-26	Thunderbirds	@	Bears	Thunderbirds3,Bears4 (OT)	RECAP
2025-02-27	Bears	@	Phantoms	Bears0,Phantoms1	RECAP
2025-03-02	Phantoms	@	Bears	Phantoms1,Bears4	RECAP
2025-03-03	Bears	@	Gulls	Bears2,Gulls3	RECAP
2025-03-06	Bears	@	Thunderbirds	Bears5,Thunderbirds1	RECAP
2025-03-07	Marlies	@	Bears	Marlies3,Bears4	RECAP
Trade Deadline --- Trades can�t be done after this day is simulated!
2025-03-11	Bears	@	Marlies	Bears4,Marlies3	RECAP
2025-03-14	Phantoms	@	Bears	Phantoms3,Bears2 (SO)	RECAP
2025-03-16	Bears	@	Phantoms	Bears5,Phantoms3	RECAP
2025-03-20	Bruins	@	Bears
2025-03-24	Checkers	@	Bears
2025-03-25	Bears	@	Islanders
2025-03-29	Bears	@	Islanders
2025-03-31	Checkers	@	Bears

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
2,810,583$	0$	0$	75,000,000$

Arena	About us
	Name
	City	Hershey
	Capacity	3000
	Season Ticket Holders	0%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	2000	1000
Ticket Price	35$	0$	$	$	$
Attendance	0	0
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
3	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
2,810,583$	2,810,583$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
3,663,953$	15,443$	2,762,871$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	32	20,937$	376,866$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
376,866$	0$	0$	0$

Sponsors
TV Rights	Primary Sponsor	Secondary Sponsor	Secondary Sponsor

Depth Chart

Rookie

Injured

Cold Streak

Hot Streak

Left Wing

Center

Right Wing

Defense #1

Defense #2

Goalie

Transactions

Injuries

Max Comtois is suspended for 19 more games.

Julien Gauthier is out for 1 month because of a Strained Right Knee Injury.
Marc Staal is suspended for 15 more games.

Game Center

Phantoms41-22-5, 87pts

32Final

Bears38-26-3, 79pts

53Final

Phantoms41-22-5, 87pts

Bears38-26-3, 79pts

Mon, Mar 17

Phantoms41-22-5, 87pts

Bears38-26-3, 79pts

Thu, Oct 10

Monsters48-13-7, 103pts

Phantoms41-22-5, 87pts

Fri, Oct 11

Bears38-26-3, 79pts

TRANSACTIONS

Team Info


	Head Coach	Dave Tippett
	Division	Atlantic
	City	Hershey
	Stadium Capacity	3,000

Bears Affiliation


	General Manager	Kevin Mancheron
	Head Coach	Patrick Roy
	Stadium	Capital One Arena
	Capacity	18,000

Team Leaders

GOALS Pavol Regenda Bears	22 GOALS
POINTS Cody Glass Bears	50 POINTS
WINS Yaroslav Askarov Bears	19 WINS
Expanded Player Leaderboard

Team Stats

Goals For 197 2.94 GFG	Goals Against 171 2.55 GAA
Power Play Percentage 25.5% 60 GF	Penalty Kill Percentage 85.8% 29 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain