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	100.00	59	33	89	66	76	81	70	66	61	59	76	55	71	70	69	0	41	75	27	900,000$/2yrs
Julien Gauthier	0	RW	99.00	82	34	90	63	90	72	69	62	59	60	66	62	64	71	70	0	48	74	28	950,000$/3yrs
Martin Pospisil	0	RW	100.00	95	44	55	63	71	78	87	61	60	66	59	60	60	67	63	0	46	73	26	1,000,000$/1yrs
Pavol Regenda	0	LW/RW	100.00	75	42	67	57	87	67	71	64	48	58	58	67	58	68	65	0	49	71	26	950,000$/1yrs
Noel Gunler	0	LW/RW	100.00	68	39	77	56	70	65	67	62	49	55	57	65	56	64	62	0	42	69	24	800,000$/2yrs
Joakim Kemell (R)	0	RW	98.00	64	39	84	59	74	65	71	59	41	58	58	62	58	59	58	0	49	69	21	918,333$/1yrs
Ivan Ivan (R)	0	C	100.00	58	32	92	62	74	72	71	54	72	56	63	51	58	62	61	0	46	68	23	845,000$/1yrs
Jaydon Dureau (R)	0	LW	100.00	62	38	88	52	69	62	65	63	42	53	52	66	52	64	63	0	49	67	24	800,000$/1yrs
Chase Stillman (R)	0	RW	100.00	76	41	64	55	74	63	68	60	40	53	55	64	54	61	57	0	49	67	22	863,333$/1yrs
Justin Robidas (R)	0	C	100.00	56	37	92	63	64	68	60	61	67	56	52	61	62	58	57	0	49	67	22	825,000$/1yrs
Juha Jaaska	0	LW/RW	100.00	69	46	83	55	76	70	68	53	75	65	50	49	51	70	68	0	46	67	27	900,000$/2yrs
Sam Morton	0	LW	100.00	61	38	89	54	71	63	67	62	42	49	59	66	54	64	63	0	33	67	26	850,000$/2yrs
William Lagesson	92	D	100.00	77	44	74	55	82	80	72	53	30	58	50	64	51	73	71	0	49	70	29	800,000$/2yrs
Kevin Connauton	7	D	100.00	82	42	55	50	80	68	67	49	30	55	52	77	54	84	79	0	39	70	35	800,000$/2yrs
Alexander Alexeyev	0	D	100.00	71	34	95	55	86	79	72	52	30	54	54	65	53	67	66	0	48	69	26	1,000,000$/2yrs
Jimmy Schuldt	4	D	100.00	67	40	80	50	80	66	67	49	30	56	53	72	54	75	73	0	42	69	30	800,000$/2yrs
Butrus Ghafari	0	D	100.00	74	40	68	58	75	63	60	58	65	54	48	69	59	68	65	0	42	69	29	800,000$/2yrs
Ronnie Attard	0	D	100.00	76	41	65	50	83	65	68	50	30	55	55	68	55	68	65	0	46	68	26	950,000$/1yrs
Cole McWard	0	D	100.00	60	38	91	50	76	64	67	49	30	56	52	66	54	64	63	0	47	67	24	800,000$/2yrs
Scratches
Max Comtois	0	C/LW	100.00	71	49	60	61	83	78	75	60	61	62	64	55	62	67	63	0	20	72	26
Corey Andonovski	0	RW	100.00	80	42	58	53	82	65	67	64	36	55	53	68	54	68	64	0	20	69	26	800,000$/1yrs
Mathias Laferriere	0	RW	100.00	62	39	88	54	75	64	67	63	39	56	53	67	54	66	65	0	20	68	25	900,000$/1yrs
Ondrej Pavel	0	C/LW/RW	100.00	72	41	71	53	85	64	67	63	37	53	54	67	53	66	63	0	20	68	25	850,000$/2yrs
Blake McLaughlin (R)	0	LW	100.00	62	38	88	52	70	63	65	63	39	54	51	67	52	66	65	0	20	67	25	900,000$/1yrs
Anton Lundmark	0	LW/RW	100.00	55	38	99	56	79	65	89	54	47	55	57	66	56	64	64	0	32	67	24	975,000$/1yrs
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	800,000$/1yrs
Carson Bantle (R)	0	LW	100.00	75	42	66	51	88	61	65	62	36	50	51	65	51	62	59	0	20	66	23	850,000$/2yrs
Maxence Guenette	0	D	100.00	64	40	84	52	83	65	68	51	30	58	54	66	56	65	63	0	20	68	24	850,000$/2yrs
Dmitri Semykin	13	D	100.00	57	39	96	57	83	60	60	55	30	51	49	64	58	61	63	0	20	67	25	900,000$/2yrs
Luke Krys	0	D	100.00	67	39	79	49	75	64	66	48	30	55	52	67	53	66	64	0	20	67	25	800,000$/1yrs
Mikko Kokkonen (R)	0	D	100.00	64	39	85	49	77	63	66	49	30	55	52	66	54	64	63	0	20	66	24	800,000$/1yrs
Anton Malmstrom	0	D	100.00	67	40	80	48	83	63	65	47	30	53	51	67	52	66	64	0	20	66	25	900,000$/2yrs

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	98.00	71	62	70	78	71	75	74	71	75	73	74	71	70	0	31	76	27	900,000$/1yrs
Dom DiVincentiis	0	100.00	74	62	70	78	71	75	73	74	75	76	74	60	59	0	49	76	21	858,333$/1yrs
Scratches
Nico Daws	0	100.00	69	70	69	84	78	72	79	83	80	83	79	66	70	0	50	80	25	1,100,000$/1yrs

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Dave Tippett	76	80	84	82	91	84	55	CAN	64	2	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	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS
1	Julien Gauthier	Bears (WSH)	RW	37	12	16	28	-1	30	0	69	151	45	106	7.95%	12	21.40	4	7	11	102	0	0	0	28	4	1	47.54%	61	0	0	0.71	1	5
2	Pavol Regenda	Bears (WSH)	LW/RW	37	10	13	23	5	16	0	110	130	32	67	7.69%	11	19.07	4	1	5	80	0	0	0	28	3	1	61.02%	59	0	0	0.65	0	0
3	Joakim Kemell	Bears (WSH)	RW	37	9	12	21	3	4	0	48	95	25	66	9.47%	7	19.95	3	5	8	95	0	1	1	68	1	1	41.04%	809	0	0	0.57	1	4
4	Alexander Nylander	Bears (WSH)	RW	33	7	13	20	5	2	0	14	96	14	67	7.29%	2	15.24	0	4	4	65	0	0	0	31	1	0	51.10%	182	0	0	0.80	0	1
5	Martin Pospisil	Bears (WSH)	RW	37	9	11	20	-5	57	5	158	110	27	95	8.18%	4	20.22	1	5	6	96	0	0	0	69	1	0	49.35%	77	0	0	0.53	0	4
6	William Lagesson	Bears (WSH)	D	37	4	15	19	6	31	5	62	47	14	27	8.51%	43	22.55	2	5	7	94	0	0	0	85	1	0	0.00%	1	0	0	0.46	0	0
7	Ivan Ivan	Bears (WSH)	C	36	9	6	15	12	2	0	20	49	18	44	18.37%	7	18.98	2	1	3	48	0	0	0	59	5	1	55.88%	519	0	0	0.44	0	0
8	Alexander Alexeyev	Bears (WSH)	D	37	4	9	13	-2	20	0	22	34	17	26	11.76%	62	21.92	1	2	3	52	0	0	0	75	0	1	0.00%	1	0	0	0.32	0	0
9	Ronnie Attard	Bears (WSH)	D	37	2	11	13	-2	16	0	82	37	20	28	5.41%	31	18.72	1	4	5	94	0	0	0	84	0	0	0.00%	0	0	0	0.38	0	0
10	Butrus Ghafari	Bears (WSH)	D	32	2	10	12	0	34	0	80	20	10	16	10.00%	50	17.79	0	0	0	1	0	1	1	52	0	0	0.00%	0	0	0	0.42	0	0
11	Kevin Connauton	Bears (WSH)	D	32	0	11	11	3	42	0	87	67	17	46	0.00%	50	21.50	0	5	5	91	0	0	0	64	0	0	0.00%	0	0	0	0.32	0	0
12	Noel Gunler	Bears (WSH)	LW/RW	32	5	6	11	0	16	0	52	86	19	69	5.81%	4	16.22	1	1	2	36	0	0	0	0	0	1	50.56%	89	0	0	0.42	0	0
13	Justin Robidas	Bears (WSH)	C	37	3	6	9	-8	0	0	6	91	25	64	3.30%	9	18.45	2	3	5	103	0	0	0	82	0	0	54.99%	822	0	0	0.26	0	0
14	Anton Lundmark	Bears (WSH)	LW/RW	18	3	4	7	1	0	0	2	12	2	6	25.00%	1	5.69	2	1	3	9	0	0	0	9	0	0	28.57%	7	0	1	1.37	0	0
15	Jimmy Schuldt	Bears (WSH)	D	32	3	3	6	0	11	5	12	38	20	27	7.89%	38	16.64	2	1	3	66	0	0	0	25	0	0	0.00%	1	0	0	0.23	0	0
16	Juha Jaaska	Bears (WSH)	LW/RW	32	1	4	5	-3	10	10	6	26	11	18	3.85%	4	11.76	0	0	0	0	0	0	0	0	0	0	52.38%	21	0	0	0.27	0	0
17	Chase Stillman	Bears (WSH)	RW	37	2	2	4	1	4	0	11	13	6	11	15.38%	2	4.30	0	0	0	0	0	0	0	0	0	0	41.84%	196	0	0	0.50	0	0
18	Sam Morton	Bears (WSH)	LW	24	2	2	4	-1	0	0	6	19	11	18	10.53%	3	12.00	0	0	0	0	0	0	0	0	0	0	42.95%	298	0	0	0.28	0	0
19	Jaydon Dureau	Bears (WSH)	LW	37	3	0	3	2	0	0	3	7	1	4	42.86%	2	2.10	1	0	1	9	1	0	1	54	0	0	25.00%	8	0	0	0.77	0	0
20	Cole McWard	Bears (WSH)	D	36	1	2	3	2	0	0	2	5	1	2	20.00%	8	3.01	0	1	1	10	0	0	0	17	0	0	0.00%	0	0	0	0.55	0	0
21	Luke Krys	Bears (WSH)	D	5	1	1	2	-1	0	0	1	3	0	1	33.33%	9	18.51	0	1	1	7	0	0	0	15	1	0	0.00%	0	0	0	0.43	0	0
22	Carson Focht	Bears (WSH)	C	5	0	1	1	1	0	0	0	0	0	1	0.00%	0	0.79	0	0	0	0	0	0	0	2	0	0	80.00%	5	0	0	5.06	0	0
23	Carson Bantle	Bears (WSH)	LW	5	0	0	0	-2	0	0	3	14	5	7	0.00%	0	14.30	0	0	0	0	0	0	0	0	0	0	50.00%	4	0	0	0.00	0	0
Team Total or Average			692	92	158	250	16	295	25	856	1150	340	816	8.00%	359	15.58	26	47	73	1067	1	2	3	857	17	6	48.92%	3160	0	1	0.46	2	14

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	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Nico Daws	Bears (WSH)	20	10	9	0	0.927	2.42	1165	0	3	47	646	0	0	1.000	3	19	10	3	1	2
2	Dom DiVincentiis	Bears (WSH)	11	6	2	3	0.934	2.03	650	2	2	22	333	0	1	0.625	8	11	25	3	2	0
3	Filip Larsson	Bears (WSH)	7	3	3	1	0.935	1.99	423	0	2	14	217	0	0	0.667	3	7	2	2	0	0
Team Total or Average		38	19	14	4	0.931	2.22	2239	2	7	83	1196	0	1	0.714	14	37	37	8	3	2

Salary

Player Name	POS	Age	Cap Hit	2020-21	2021-22	2022-23	2023-24
Alexander Alexeyev	D	26	1,000,000$	1,000,000$	1,000,000$	UFA
Alexander Nylander	RW	27	900,000$	900,000$	900,000$	UFA
Anton Lundmark	LW/RW	24	975,000$	975,000$	RFA
Anton Malmstrom	D	25	900,000$	900,000$	900,000$	RFA
Blake McLaughlin	LW	25	900,000$	900,000$	RFA
Butrus Ghafari	D	29	800,000$	800,000$	800,000$	UFA
Carson Bantle	LW	23	850,000$	850,000$	850,000$	RFA
Carson Focht	C	25	800,000$	800,000$	RFA
Chase Stillman	RW	22	863,333$	863,333$	RFA
Cole McWard	D	24	800,000$	800,000$	800,000$	RFA
Corey Andonovski	RW	26	800,000$	800,000$	RFA
Dmitri Semykin	D	25	900,000$	900,000$	900,000$	RFA
Dom DiVincentiis	G	21	858,333$	858,333$	RFA
Filip Larsson	G	27	900,000$	900,000$	UFA
Ivan Ivan	C	23	845,000$	845,000$	RFA
Jaydon Dureau	LW	24	800,000$	800,000$	RFA
Jimmy Schuldt	D	30	800,000$	800,000$	800,000$	UFA
Joakim Kemell	RW	21	918,333$	918,333$	RFA
Juha Jaaska	LW/RW	27	900,000$	900,000$	900,000$	UFA
Julien Gauthier	RW	28	950,000$	950,000$	950,000$	950,000$	UFA
Justin Robidas	C	22	825,000$	825,000$	RFA
Kevin Connauton	D	35	800,000$	800,000$	800,000$	UFA
Luke Krys	D	25	800,000$	800,000$	RFA
Martin Pospisil	RW	26	1,000,000$	1,000,000$	RFA
Mathias Laferriere	RW	25	900,000$	900,000$	RFA
Max Comtois	C/LW	26	0$	RFA
Maxence Guenette	D	24	850,000$	850,000$	850,000$	RFA
Mikko Kokkonen	D	24	800,000$	800,000$	RFA
Nico Daws	G	25	1,100,000$	1,100,000$	RFA
Noel Gunler	LW/RW	24	800,000$	800,000$	800,000$	RFA
Ondrej Pavel	C/LW/RW	25	850,000$	850,000$	850,000$	RFA
Pavol Regenda	LW/RW	26	950,000$	950,000$	RFA
Ronnie Attard	D	26	950,000$	950,000$	RFA
Sam Morton	LW	26	850,000$	850,000$	850,000$	UFA
William Lagesson	D	29	800,000$	800,000$	800,000$	UFA

Lines

Forward Lines
# - Pavol Regenda	# - Sam Morton	# - Julien Gauthier
# - Noel Gunler	# - Joakim Kemell	# - Ivan Ivan
# - Juha Jaaska	# - Justin Robidas	# - Martin Pospisil
# - Julien Gauthier	# - Chase Stillman	# - Martin Pospisil

Defensive Pairings
# - Butrus Ghafari	# - Alexander Alexeyev
# - William Lagesson	# - Kevin Connauton
# - Jimmy Schuldt	# - Ronnie Attard

1st Power Play Unit
# - Joakim Kemell		# - Noel Gunler		# - Pavol Regenda
# - Ronnie Attard			# - Jimmy Schuldt

2nd Power Play Unit
# - Martin Pospisil		# - Justin Robidas		# - Julien Gauthier
# - William Lagesson			# - Kevin Connauton

Goalies
# - Filip Larsson		# - Dom DiVincentiis

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	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	GF%	SH%	SV%	PDO	PDOBRK
1	Wranglers	2	2	0	0	0	0	5	3	2	4	1.000	5	9	14	0	1	37	24	31	2	71	398	341	405	25	55	17	12	41	9	1	11.11%	6	1	83.33%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	66.7%	7.0%	94.5%	101.6	DULL
2	Phantoms	2	2	0	0	0	0	7	5	2	4	1.000	7	12	19	0	0	37	24	31	2	58	398	341	405	25	83	27	16	45	10	3	30.00%	7	1	85.71%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	12.1%	94.0%	106.0	LUCKY
3	Comets	2	0	1	0	0	1	4	6	-2	1	0.250	4	7	11	0	0	37	24	31	2	74	398	341	405	25	49	15	25	43	10	1	10.00%	9	3	66.67%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	5.4%	87.8%	93.2	Unlucky
4	Senators	1	1	0	0	0	0	4	1	3	2	1.000	4	8	12	0	0	37	24	31	2	26	398	341	405	25	25	4	6	15	5	1	20.00%	2	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	75.0%	15.4%	96.0%	111.4	LUCKY
5	Islanders	5	3	2	0	0	0	15	12	3	6	0.600	15	29	44	0	1	37	24	31	2	188	398	341	405	25	147	39	28	116	18	5	27.78%	13	1	92.31%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	47.6%	8.0%	91.8%	99.8	DULL
6	Wolves	1	1	0	0	0	0	2	0	2	2	1.000	2	4	6	0	1	37	24	31	2	25	398	341	405	25	30	12	12	21	5	0	0.00%	6	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	100.0%	8.0%	100.0%	108.0	DULL
7	Eagles	1	1	0	0	0	0	4	2	2	2	1.000	4	7	11	0	0	37	24	31	2	45	398	341	405	25	31	9	10	23	4	1	25.00%	5	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	60.0%	8.9%	93.5%	102.4	Unlucky
8	Wolf Pack	2	0	0	1	1	0	7	7	0	3	0.750	7	10	17	0	0	37	24	31	2	50	398	341	405	25	63	24	23	54	3	3	100.00%	8	1	87.50%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	40.0%	14.0%	88.9%	102.9	FUN
9	Griffins	1	0	1	0	0	0	3	4	-1	0	0.000	3	4	7	0	0	37	24	31	2	28	398	341	405	25	37	14	8	43	4	0	0.00%	4	2	50.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	60.0%	10.7%	89.2%	99.9	FUN
10	Rocket	2	1	1	0	0	0	2	5	-3	2	0.500	2	4	6	0	1	37	24	31	2	53	398	341	405	25	62	23	14	48	7	1	14.29%	7	2	71.43%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	25.0%	3.8%	91.9%	95.7	DULL
11	Admirals	1	1	0	0	0	0	2	0	2	2	1.000	2	3	5	0	1	37	24	31	2	30	398	341	405	25	25	5	8	38	2	0	0.00%	3	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	100.0%	6.7%	100.0%	106.7	DULL
12	Crunch	2	0	2	0	0	0	4	6	-2	0	0.000	4	8	12	0	0	37	24	31	2	53	398	341	405	25	72	19	16	51	7	2	28.57%	7	2	71.43%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	33.3%	7.5%	91.7%	99.2	DULL
13	Thunderbirds	4	2	1	0	1	0	7	8	-1	6	0.750	7	11	18	0	2	37	24	31	2	120	398	341	405	25	150	45	26	86	12	1	8.33%	12	1	91.67%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	46.2%	5.8%	94.7%	100.5	DULL
14	Bruins	2	0	2	0	0	0	3	6	-3	0	0.000	3	5	8	1	0	37	24	31	2	58	398	341	405	25	90	31	21	38	3	0	0.00%	6	2	66.67%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	42.9%	5.2%	93.3%	98.5	DULL
15	IceHogs	1	0	0	0	0	1	2	3	-1	1	0.500	2	3	5	0	0	37	24	31	2	24	398	341	405	25	30	8	8	21	3	0	0.00%	4	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	40.0%	8.3%	90.0%	98.3	Unlucky
16	Checkers	2	1	0	0	0	1	6	4	2	3	0.750	6	11	17	0	0	37	24	31	2	63	398	341	405	25	52	9	19	41	6	3	50.00%	6	1	83.33%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	9.5%	92.3%	101.8	LUCKY
17	Monsters	1	0	1	0	0	0	1	2	-1	0	0.000	1	1	2	0	0	37	24	31	2	25	398	341	405	25	28	12	4	25	5	0	0.00%	2	1	50.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	4.0%	92.9%	96.9	DULL
18	Moose	1	0	1	0	0	0	2	4	-2	0	0.000	2	4	6	0	0	37	24	31	2	34	398	341	405	25	36	11	12	16	2	0	0.00%	6	2	66.67%	1	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	5.9%	88.9%	94.8	Unlucky
19	Gulls	1	0	1	0	0	0	3	4	-1	0	0.000	3	4	7	0	0	37	24	31	2	36	398	341	405	25	28	14	6	18	3	0	0.00%	3	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	42.9%	8.3%	85.7%	94.0	Unlucky
20	Stars	1	1	0	0	0	0	3	1	2	2	1.000	3	5	8	0	0	37	24	31	2	42	398	341	405	25	30	7	11	27	3	2	66.67%	2	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.0%	7.1%	96.7%	103.8	DULL
21	Penguins	1	1	0	0	0	0	6	1	5	2	1.000	6	10	16	0	0	37	24	31	2	27	398	341	405	25	34	17	14	28	4	2	50.00%	6	1	83.33%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	100.0%	22.2%	97.1%	119.3	LUCKY
22	Barracuda	1	0	1	0	0	0	2	3	-1	0	0.000	2	2	4	0	0	37	24	31	2	25	398	341	405	25	40	9	4	24	4	0	0.00%	2	0	100.00%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	40.0%	8.0%	92.5%	100.5	DULL
	_Vs Division	10	9	5	1	2	1	22	26	-4	24	1.200	22	40	62	1	1	37	24	31	2	281	398	341	405	25	338	100	84	236	32	7	21.88%	32	9	71.88%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	46.9%	7.8%	92.3%	100.1	DULL
	_Vs Conference	27	11	11	1	2	2	69	67	2	29	0.537	69	120	189	1	4	37	24	31	2	823	398	341	405	25	892	279	220	633	94	22	23.40%	89	18	79.78%	0	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	49.0%	8.4%	92.5%	100.9	DULL
	_Since Last GM Reset	37	17	14	1	2	3	94	87	7	42	0.568	94	161	255	1	7	37	24	31	2	1155	398	341	405	25	1197	371	303	862	129	26	20.16%	126	21	83.33%	1	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.7%	8.1%	92.7%	100.9	DULL
	Total	37	17	14	1	2	3	94	87	7	42	0.568	94	161	255	1	7	37	24	31	2	1155	398	341	405	25	1197	371	303	862	129	26	20.16%	126	21	83.33%	1	646	1288	50.16%	646	1328	48.64%	254	517	49.13%	871	583	883	286	489	242	50.7%	8.1%	92.7%	100.9	DULL

	Puck Time
Offensive Zone	23
Neutral Zone	13
Defensive Zone	23

	Puck Time
Offensive Zone Start	1288
Neutral Zone Start	517
Defensive Zone Start	1328

	Puck Time
With Puck	30
Without Puck	30

	Faceoffs
Faceoffs Won	1546
Faceoffs Lost	1587

	Team Average Shots after	League Average Shots after
1st Period	10.8	9.57
2nd Period	20.0	20.31
3rd Period	30.9	30.68
Overtime	31.6	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.0	0.64
2nd Period	1.6	1.65
3rd Period	2.5	2.67
Overtime	2.5	2.83


Even Strenght Goal	66
PP Goal	26
PK Goal	1
Empty Net Goal	1

	Home	Away
Win	10	9
Lost	5	9
Overtime Lost	2	2


PP Attempt	129
PP Goal	26
PK Attempt	126
PK Goal Against	21

	Home
Shots For	31.2
Shots Against	32.4
Goals For	2.5
Goals Against	2.4
Hits	23.3
Shots Blocked	10.0
Pim	8.2

Schedule

Date	Matchup			Result	Detail
2025-10-09	Bears	@	Phantoms	Bears4,Phantoms3	RECAP
2025-10-11	Islanders	@	Bears	Islanders3,Bears5	RECAP
2025-10-12	Bears	@	Islanders	Bears1,Islanders2	RECAP
2025-10-16	Bears	@	Bruins	Bears1,Bruins2	RECAP
2025-10-17	Penguins	@	Bears	Penguins1,Bears6	RECAP
2025-10-19	Thunderbirds	@	Bears	Thunderbirds1,Bears3	RECAP
2025-10-22	Bears	@	Checkers	Bears5,Checkers2	RECAP
2025-10-24	Wolf Pack	@	Bears	Wolf Pack4,Bears3 (OT)	RECAP
2025-10-25	Bears	@	Islanders	Bears5,Islanders3	RECAP
2025-10-28	Comets	@	Bears	Comets3,Bears2 (SO)	RECAP
2025-10-30	Bears	@	Phantoms	Bears3,Phantoms2	RECAP
2025-10-31	Bruins	@	Bears	Bruins4,Bears2	RECAP
2025-11-03	Bears	@	Checkers	Bears1,Checkers2 (SO)	RECAP
2025-11-05	Bears	@	Rocket	Bears0,Rocket5	RECAP
2025-11-06	Bears	@	Thunderbirds	Bears1,Thunderbirds0 (SO)	RECAP
2025-11-08	Thunderbirds	@	Bears	Thunderbirds0,Bears1	RECAP
2025-11-09	Bears	@	Wolf Pack	Bears4,Wolf Pack3 (SO)	RECAP
2025-11-13	Bears	@	Gulls	Bears3,Gulls4	RECAP
2025-11-14	Wranglers	@	Bears	Wranglers3,Bears4	RECAP
2025-11-17	Bears	@	Monsters	Bears1,Monsters2	RECAP
2025-11-18	Islanders	@	Bears	Islanders4,Bears2	RECAP
2025-11-21	Bears	@	Wranglers	Bears1,Wranglers0	RECAP
2025-11-22	Wolves	@	Bears	Wolves0,Bears2	RECAP
2025-11-28	Bears	@	Crunch	Bears1,Crunch2	RECAP
2025-11-29	Senators	@	Bears	Senators1,Bears4	RECAP
2025-12-02	Bears	@	Islanders	Bears2,Islanders0	RECAP
2025-12-03	Stars	@	Bears	Stars1,Bears3	RECAP
2025-12-06	Bears	@	Moose	Bears2,Moose4	RECAP
2025-12-08	Bears	@	Thunderbirds	Bears2,Thunderbirds7	RECAP
2025-12-09	Crunch	@	Bears	Crunch4,Bears3	RECAP
2025-12-12	Bears	@	Barracuda	Bears2,Barracuda3	RECAP
2025-12-13	Admirals	@	Bears	Admirals0,Bears2	RECAP
2025-12-19	Griffins	@	Bears	Griffins4,Bears3	RECAP
2025-12-21	Bears	@	IceHogs	Bears2,IceHogs3 (SO)	RECAP
2025-12-23	Bears	@	Eagles	Bears4,Eagles2	RECAP
2025-12-24	Rocket	@	Bears	Rocket0,Bears2	RECAP
2025-12-28	Comets	@	Bears	Comets3,Bears2	RECAP
2025-12-30	Bears	@	Phantoms
2026-01-02	Wolves	@	Bears
2026-01-04	Bears	@	Rocket
2026-01-08	Phantoms	@	Bears
2026-01-11	Condors	@	Bears
2026-01-14	Bears	@	Checkers
2026-01-17	Firebirds	@	Bears
2026-01-20	Bears	@	Reign
2026-01-22	Wild	@	Bears
2026-01-27	Bears	@	Wolf Pack
2026-01-28	Phantoms	@	Bears
2026-02-01	Checkers	@	Bears
2026-02-03	Bears	@	Senators
2026-02-04	Islanders	@	Bears
2026-02-08	Canucks	@	Bears
2026-02-12	Bears	@	Penguins
2026-02-14	Bruins	@	Bears
2026-02-16	Bears	@	Griffins
2026-02-18	Bears	@	Comets
2026-02-19	Monsters	@	Bears
2026-02-22	Bears	@	Wolf Pack
2026-02-24	Wolf Pack	@	Bears
2026-02-26	Bears	@	Marlies
2026-03-01	Marlies	@	Bears
2026-03-04	Bears	@	Penguins
2026-03-06	Bears	@	Americans
2026-03-07	Americans	@	Bears
Trade Deadline --- Trades can�t be done after this day is simulated!
2026-03-09	Bears	@	Bruins
2026-03-11	Silver Knights	@	Bears
2026-03-13	Bears	@	Roadrunners
2026-03-16	Penguins	@	Bears
2026-03-21	Penguins	@	Bears
2026-03-26	Thunderbirds	@	Bears
2026-03-31	Checkers	@	Bears
2026-04-01	Bears	@	Bruins

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
2,283,499$	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
19	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
2,283,499$	2,283,499$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
1,507,823$	12,686$	1,046,692$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	109	18,242$	1,769,474$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
1,769,474$	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

Robby Fabbri is suspended for 60 more games.
Max Comtois is suspended for 45 more games.
Dmitri Semykin is suspended for 45 more games.
Mathias Laferriere is suspended for 45 more games.
Mikko Kokkonen is suspended for 45 more games.
Corey Andonovski is suspended for 45 more games.
Maxence Guenette is suspended for 45 more games.
Anton Malmstrom is suspended for 45 more games.
Ondrej Pavel is suspended for 45 more games.
Blake McLaughlin is suspended for 45 more games.

Game Center

Rocket19-14-2, 40pts

02Final

Bears19-14-4, 42pts

Comets17-14-2, 36pts

32Final

Bears19-14-4, 42pts

Comets17-14-2, 36pts

Mon, Dec 29

Bears19-14-4, 42pts

Islanders21-12-3, 45pts

Sun, Oct 12

Bears19-14-4, 42pts

Mon, Oct 13

Islanders21-12-3, 45pts

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 Julien Gauthier Bears	12 GOALS
POINTS Julien Gauthier Bears	28 POINTS
WINS Nico Daws Bears	10 WINS
Expanded Player Leaderboard

Team Stats

Goals For 94 2.54 GFG	Goals Against 87 2.35 GAA
Power Play Percentage 20.2% 26 GF	Penalty Kill Percentage 83.3% 21 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain