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Washington Capitals
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#	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
1	Mavrik Bourque	0	X				100.00	62	37	92	71	70	92	87	67	77	68	64	65	66	63	65	78	50	66	0
2	Nicolas Aube-Kubel	0	X		X		100.00	78	62	85	66	77	78	80	64	59	61	62	63	62	71	70	58	50	64	0
3	Ben Meyers	0	X	X			100.00	67	36	91	63	71	85	82	64	71	62	63	61	60	67	69	37	50	63	0
4	Reese Johnson	0	X		X		100.00	79	65	74	62	76	77	78	61	64	60	59	66	58	67	69	37	50	63	0
5	Tim Gettinger	0		X	X		100.00	87	51	90	58	96	77	80	59	56	58	57	62	59	67	69	47	50	63	0
6	Nikita Nesterenko	0	X	X			100.00	72	39	83	63	79	78	87	62	66	60	64	61	63	65	66	48	50	63	0
7	Anton Blidh	0		X	X		100.00	70	42	65	61	77	76	85	60	56	59	58	62	57	70	72	39	50	62	0
8	Gage Quinney	0	X	X			100.00	63	36	95	62	72	84	76	59	70	66	57	60	58	70	72	35	50	62	0
9	Curtis Douglas	0	X				100.00	90	82	51	57	99	75	82	55	64	57	56	63	56	65	67	58	50	62	0
10	Joe Snively	0		X			100.00	56	36	89	63	65	80	87	62	66	61	58	57	61	69	71	36	50	61	0
11	Ryder Rolston	0	X	X	X		100.00	63	37	95	59	72	82	83	57	60	59	58	56	57	64	66	55	50	60	0
12	Navrin Mutter	0		X			100.00	72	61	50	55	81	69	71	53	57	54	52	56	53	64	66	43	50	57	0
13	Brandt Clarke	0				X	100.00	68	41	77	73	80	86	87	69	30	76	62	66	53	63	65	87	50	68	0
14	Ben Harpur	0				X	100.00	90	56	65	58	99	68	66	57	30	56	53	63	46	70	72	48	50	64	0
15	Christoffer Sedoff	0				X	100.00	69	39	85	57	78	67	80	55	30	56	53	58	46	63	65	42	50	60	0
16	Ethan Frisch	0				X	100.00	58	38	82	56	71	66	82	54	30	55	53	56	45	65	67	42	50	59	0
17	Leo Loof	0				X	100.00	66	41	75	54	76	61	83	53	30	57	50	55	45	63	65	63	50	58	0
18	Marshall Warren	0				X	100.00	56	37	78	55	66	72	69	54	30	56	53	57	46	64	66	48	50	58	0
Scratches
1	Anthony Richard	0	X	X			100.00	65	38	83	70	68	87	83	67	69	65	66	63	67	69	71	50	50	66	0
2	Ethan Cardwell	0			X		100.00	66	37	79	65	68	90	86	64	67	63	62	65	61	64	65	58	50	64	0
3	Braeden Kressler	0	X				100.00	57	38	75	55	63	81	61	53	61	54	50	52	55	62	64	43	50	55	0

	TEAM AVERAGE					100.00	69	45	79	61	76	78	80	59	54	60	58	60	56	66	68	50	50	62

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#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Vitek Vanecek	100.00	86	82	77	77	85	84	86	85	84	86	85	72	83	61	50	81	0
2	Henrik Tikkanen	99.00	70	80	76	98	69	68	70	69	68	70	69	65	73	47	50	71	0
Scratches

	TEAM AVERAGE	99.50	78	81	77	88	77	76	78	77	76	78	77	69	78	54	50	76

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Jay Leach	68	69	64	65	69	64	80	USA	46	7	1,000,000$

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3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
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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

#	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	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Nicolas Aube-Kubel	Bears (Was)	C/RW	50	24	43	67	33	55	5	102	72	237	62	159	10.13%	8	844	16.88	8	15	23	98	215	0	0	0	0	0	7	1	59.76%	82	0	1.59	0	0	0	0	1	5	6	9
2	Anthony Richard	Bears (Was)	C/LW	45	31	31	62	32	16	0	64	102	223	75	173	13.90%	30	1035	23.00	11	6	17	71	188	0	2	2	5	185	5	2	54.21%	107	1	1.20	1	1	0	0	0	8	7	4
3	Reese Johnson	Bears (Was)	C/RW	50	26	22	48	7	92	20	141	104	189	60	130	13.76%	15	930	18.62	10	8	18	75	206	0	0	0	0	36	4	1	61.09%	478	1	1.03	0	0	1	1	2	7	2	3
4	Ethan Cardwell	Bears (Was)	RW	47	22	19	41	26	8	0	56	91	150	47	120	14.67%	11	796	16.94	2	0	2	11	17	0	0	0	0	0	6	1	56.52%	368	1	1.03	1	1	0	0	0	1	8	3
5	Ryder Rolston	Bears (Was)	C/LW/RW	50	18	19	37	22	45	5	66	96	178	57	145	10.11%	21	951	19.03	0	0	0	0	1	0	0	0	0	2	4	2	57.58%	587	0	0.78	0	0	1	0	0	2	3	4
6	Gage Quinney	Bears (Was)	C/LW	50	13	17	30	28	12	0	18	78	101	31	65	12.87%	7	595	11.90	1	0	1	2	4	0	0	0	0	14	2	0	61.81%	529	0	1.01	0	0	0	0	0	3	3	1
7	Christoffer Sedoff	Bears (Was)	D	50	3	18	21	33	72	10	83	50	42	15	35	7.14%	33	963	19.26	2	0	2	17	53	0	0	0	0	33	0	0	41.98%	243	0	0.44	0	0	1	1	0	0	0	3
8	Ethan Frisch	Bears (Was)	D	50	3	14	17	28	22	0	36	23	28	7	26	10.71%	25	789	15.78	1	4	5	7	56	0	1	1	1	48	1	0	0.00%	0	0	0.43	0	0	0	0	0	1	1	0
9	Marshall Warren	Bears (Was)	D	50	3	12	15	18	18	0	36	27	39	8	16	7.69%	26	770	15.41	0	0	0	0	2	0	0	0	0	6	0	0	31.34%	67	0	0.39	0	0	0	0	0	1	1	0
10	Leo Loof	Bears (Was)	D	50	2	12	14	16	54	10	69	26	15	4	12	13.33%	28	633	12.66	0	0	0	2	7	1	0	1	1	30	0	0	0.00%	0	0	0.44	0	0	1	0	1	0	1	2
11	Joe Snively	Bears (Was)	LW	19	4	5	9	1	4	0	11	25	45	19	33	8.89%	4	220	11.59	0	0	0	0	0	0	0	0	0	0	1	0	46.67%	15	0	0.82	0	0	0	0	0	0	0	1
12	Nikita Nesterenko	Bears (Was)	C/LW	11	4	5	9	11	2	0	12	13	30	9	25	13.33%	5	222	20.19	0	1	1	8	27	0	0	0	0	23	0	0	58.42%	101	1	0.81	0	0	0	0	0	1	0	1
13	Brandt Clarke	Bears (Was)	D	5	0	7	7	5	0	0	2	8	9	4	7	0.00%	7	105	21.11	0	1	1	7	22	0	0	0	0	11	0	0	0.00%	0	0	1.33	0	0	0	0	0	0	1	0
14	Hendrix Lapierre	Bears (Was)	C	2	1	3	4	3	0	0	0	1	6	3	5	16.67%	0	21	10.88	0	1	1	2	6	0	0	0	0	0	0	0	72.41%	29	0	3.68	0	0	0	0	0	0	0	0
15	Tim Gettinger	Bears (Was)	LW/RW	6	2	1	3	3	8	0	8	7	11	3	11	18.18%	0	78	13.08	0	0	0	0	0	0	0	0	0	5	0	0	85.71%	7	0	0.76	0	0	0	0	0	0	0	0
16	Anton Blidh	Bears (Was)	LW/RW	8	1	1	2	2	6	0	13	5	12	2	7	8.33%	1	109	13.66	0	0	0	0	0	0	0	0	0	0	0	0	28.57%	7	0	0.37	0	0	0	0	0	0	0	0
17	Ben Harpur	Bears (Was)	D	10	1	1	2	8	23	5	35	5	11	3	7	9.09%	16	209	20.92	1	0	1	6	35	0	0	0	1	34	1	0	0.00%	0	0	0.19	0	0	1	0	0	1	0	0
Team Total or Average				553	158	230	388	276	437	55	752	733	1326	409	976	11.92%	237	9275	16.77	36	36	72	306	845	1	3	4	8	434	31	7	56.87%	2620	4	0.84	2	2	5	2	4	30	33	31

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3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
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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	PS %	PSA	ST	BG	S1	S2	S3
1	Henrik Tikkanen	Bears (Was)	42	27	11	3	0.914	2.18	2396	8	2	87	1012	2	0.667	3	42	50	3	5	1
2	Chris Driedger	Washington Capitals	8	5	2	1	0.911	2.00	479	0	1	16	180	0	0.000	0	8	0	0	1	0
Team Total or Average			50	32	13	4	0.914	2.15	2876	8	3	103	1192	2	0.667	3	50	50	3	6	1

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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`)
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	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Link
Anthony Richard	C/LW	29	1996-12-20	No	185 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Anton Blidh	LW/RW	30	1995-03-14	No	196 Lbs	6 ft1	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ben Harpur	D	31	1995-01-12	No	231 Lbs	6 ft6	No	No	No	2	UFA	Pro & Farm	400,000$	0$	0$	No	Link
Ben Meyers	C/LW	27	1998-11-15	No	194 Lbs	5 ft11	No	No	No	4	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Braeden Kressler	C	23	2003-01-05	No	169 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Brandt Clarke	D	23	2003-02-09	No	200 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Christoffer Sedoff	D	24	2002-02-20	No	201 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Curtis Douglas	C	25	2000-03-06	No	235 Lbs	6 ft9	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ethan Cardwell	RW	23	2002-08-30	No	180 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ethan Frisch	D	25	2000-10-29	No	192 Lbs	5 ft11	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Gage Quinney	C/LW	30	1995-07-29	No	200 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Henrik Tikkanen	G	25	2000-09-28	No	222 Lbs	6 ft8	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Joe Snively	LW	30	1996-01-01	No	176 Lbs	5 ft9	No	No	No	3	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Leo Loof	D	23	2002-04-25	No	176 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Marshall Warren	D	24	2001-04-20	No	170 Lbs	5 ft11	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Mavrik Bourque	C	24	2002-01-08	No	181 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Navrin Mutter	LW	24	2001-03-15	No	190 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nicolas Aube-Kubel	C/RW	29	1996-05-10	No	213 Lbs	6 ft0	No	No	No	1	UFA	Pro & Farm	400,000$	0$	0$	No	Link / NHL Link
Nikita Nesterenko	C/LW	24	2001-09-10	No	195 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Reese Johnson	C/RW	27	1998-07-10	No	193 Lbs	6 ft1	No	No	No	3	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ryder Rolston	C/LW/RW	24	2001-10-31	No	175 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Tim Gettinger	LW/RW	27	1998-04-14	No	220 Lbs	6 ft6	No	No	No	4	UFA	Pro & Farm	400,000$	0$	0$	No	Link / NHL Link
Vitek Vanecek	G	30	1996-01-09	No	184 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	1,250,000$	1,250,000$	310,881$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
23	26.13	195 Lbs	6 ft1	2.26	415,217$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1			Nicolas Aube-Kubel	40	1	2	2
2			Reese Johnson	30	1	2	2
3		Gage Quinney		20	1	2	2
4		Ryder Rolston		10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2	Christoffer Sedoff	Ethan Frisch	30	1	2	2
3	Leo Loof	Marshall Warren	20	1	2	2
4			10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1			Nicolas Aube-Kubel	60	1	2	2
2			Reese Johnson	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2	Christoffer Sedoff	Ethan Frisch	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	Christoffer Sedoff	Ethan Frisch	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	Christoffer Sedoff	Ethan Frisch	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	Christoffer Sedoff	Ethan Frisch	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
		Nicolas Aube-Kubel

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
		Nicolas Aube-Kubel

Extra Forwards
Normal	PowerPlay	Penalty Kill
Reese Johnson, ,	Reese Johnson,	Reese Johnson

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Ethan Frisch, Leo Loof, Marshall Warren	Ethan Frisch	Ethan Frisch, Leo Loof

Penalty Shots
, , , Nicolas Aube-Kubel, Reese Johnson

Goalie
#1 : , #2 : Henrik Tikkanen

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

Custom OT Lines Defensemen
, , , ,

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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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
50	70	W2	171	298	469	1569	1244	348	531	919	0	3

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
50	31	13	1	4	1	0	171	106

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
27	15	7	1	3	1	0	92	55

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
23	16	6	0	1	0	0	79	51

Last 10 Games
W	L	OTW	OTL	SOW	SOL
9	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
264	43	16.29%	222	38	82.88%	2

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
534	489	542	6	78	42	49	3

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
798	1645	48.51%	644	1492	43.16%	396	736	53.80%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1261	922	1180	341	568	287

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	OT	SO	Link
9 - 2025-08-23	12	Monsters	0	Bears	7	W			BoxScore
10 - 2025-08-24	28	Monsters	1	Bears	8	W			BoxScore
13 - 2025-08-27	30	Bears	2	Islanders	1	W			BoxScore
16 - 2025-08-30	47	Wolves	2	Bears	1	L			BoxScore
17 - 2025-08-31	59	Wolves	1	Bears	2	W			BoxScore
22 - 2025-09-05	75	Bears	4	Bruins	5	L			BoxScore
23 - 2025-09-06	90	Bears	3	Thunderbirds	4	L	X		BoxScore
24 - 2025-09-07	97	Bears	3	Bruins	2	W			BoxScore
27 - 2025-09-10	106	Phantoms	3	Bears	0	L			BoxScore
30 - 2025-09-13	123	Checkers	2	Bears	5	W			BoxScore
31 - 2025-09-14	136	Checkers	6	Bears	7	W			BoxScore
37 - 2025-09-20	159	Thunderbirds	4	Bears	3	L	X		BoxScore
38 - 2025-09-21	170	Thunderbirds	2	Bears	3	W	X	X	BoxScore
40 - 2025-09-23	181	Bears	4	Islanders	0	W			BoxScore
43 - 2025-09-26	191	Islanders	1	Bears	3	W			BoxScore
44 - 2025-09-27	209	Bears	3	Phantoms	4	L			BoxScore
48 - 2025-10-01	223	Bears	7	Marlies	1	W			BoxScore
50 - 2025-10-03	235	Bears	2	Americans	1	W			BoxScore
51 - 2025-10-04	247	Bears	5	Crunch	2	W			BoxScore
55 - 2025-10-08	262	Rocket	4	Bears	2	L			BoxScore
57 - 2025-10-10	271	Bears	3	Phantoms	1	W			BoxScore
58 - 2025-10-11	284	Penguins	1	Bears	2	W			BoxScore
62 - 2025-10-15	304	Bears	2	Penguins	3	L			BoxScore
65 - 2025-10-18	325	Bears	2	Phantoms	1	W			BoxScore
66 - 2025-10-19	336	Phantoms	0	Bears	3	W			BoxScore
69 - 2025-10-22	343	Bears	1	Wolfpack	4	L			BoxScore
71 - 2025-10-24	353	Bears	5	Crunch	2	W			BoxScore
72 - 2025-10-25	364	Checkers	2	Bears	9	W			BoxScore
79 - 2025-11-01	414	Marlies	2	Bears	7	W			BoxScore
80 - 2025-11-02	427	Penguins	1	Bears	0	L			BoxScore
86 - 2025-11-08	441	Penguins	2	Bears	1	L			BoxScore
87 - 2025-11-09	452	Checkers	2	Bears	4	W			BoxScore
93 - 2025-11-15	484	Bruins	3	Bears	4	W	X		BoxScore
94 - 2025-11-16	494	Bruins	3	Bears	2	L			BoxScore
96 - 2025-11-18	501	Phantoms	2	Bears	1	L	X		BoxScore
99 - 2025-11-21	509	Bears	9	Checkers	2	W			BoxScore
100 - 2025-11-22	523	Bears	5	Checkers	1	W			BoxScore
106 - 2025-11-28	559	Senators	2	Bears	1	L	X		BoxScore
108 - 2025-11-30	583	Americans	2	Bears	1	L			BoxScore
111 - 2025-12-03	595	Bears	2	Rocket	3	L			BoxScore
113 - 2025-12-05	605	Bears	3	Senators	2	W			BoxScore
114 - 2025-12-06	617	Bears	2	Senators	1	W			BoxScore
118 - 2025-12-10	638	Bears	2	Penguins	1	W			BoxScore
120 - 2025-12-12	646	Islanders	2	Bears	3	W			BoxScore
121 - 2025-12-13	664	Islanders	2	Bears	3	W			BoxScore
128 - 2025-12-20	695	Crunch	1	Bears	6	W			BoxScore
131 - 2025-12-23	706	Penguins	2	Bears	4	W			BoxScore
135 - 2025-12-27	732	Bears	2	Penguins	6	L			BoxScore
142 - 2026-01-03	778	Bears	4	Checkers	3	W			BoxScore
143 - 2026-01-04	793	Bears	4	Checkers	1	W			BoxScore
149 - 2026-01-10	827	Penguins	-	Bears	-
150 - 2026-01-11	842	Phantoms	-	Bears	-
153 - 2026-01-14	850	Senators	-	Bears	-
Trade Deadline --- Trades can’t be done after this day is simulated!
155 - 2026-01-16	860	Bears	-	Monsters	-
156 - 2026-01-17	872	Bears	-	Monsters	-
160 - 2026-01-21	896	Bears	-	Penguins	-
163 - 2026-01-24	918	Bears	-	Wolves	-
164 - 2026-01-25	929	Bears	-	Wolves	-
167 - 2026-01-28	940	Bears	-	Thunderbirds	-
169 - 2026-01-30	945	Bears	-	Wolfpack	-
170 - 2026-01-31	961	Bears	-	Penguins	-
174 - 2026-02-04	982	Bears	-	Islanders	-
177 - 2026-02-07	1006	Bears	-	Comets	-
178 - 2026-02-08	1022	Comets	-	Bears	-
183 - 2026-02-13	1045	Bears	-	Phantoms	-
184 - 2026-02-14	1053	Wolfpack	-	Bears	-
185 - 2026-02-15	1067	Wolfpack	-	Bears	-
190 - 2026-02-20	1082	Bears	-	Penguins	-
191 - 2026-02-21	1100	Bears	-	Phantoms	-
195 - 2026-02-25	1113	Crunch	-	Bears	-
197 - 2026-02-27	1125	Penguins	-	Bears	-
198 - 2026-02-28	1140	Phantoms	-	Bears	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	51,646	25,244
Attendance PCT	95.64%	93.50%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
9	2848 - 94.93%	71,256$	1,923,917$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
789,825$	92,000$	92,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	64,825$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
641,306$	55	5,460$	300,300$

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
Regular Season
12	82	44	23	0	2	6	4	3	278	176	102	41	21	13	0	2	2	1	2	132	87	45	41	23	10	0	0	4	3	1	146	89	57	109	278	446	724	0	10	0	108	91	73	2493	0	828	802	838	2069	556	1121	1657	498	88	17.67%	433	67	84.53%	8	1425	2538	56.15%	1282	2504	51.20%	636	1182	53.81%	2234	1673	1832	545	909	462
13	76	39	24	0	2	6	1	4	202	151	51	38	20	14	0	1	2	0	1	93	69	24	38	19	10	0	1	4	1	3	109	82	27	94	202	358	560	0	10	0	74	73	52	1969	0	632	696	625	1707	551	1330	1499	458	74	16.16%	532	67	87.41%	3	1341	2379	56.37%	1162	2351	49.43%	613	1068	57.40%	1912	1329	1783	553	907	461
14	76	33	25	0	5	5	4	4	199	155	44	38	13	12	0	3	4	3	3	101	80	21	38	20	13	0	2	1	1	1	98	75	23	93	199	319	518	1	14	0	72	61	57	2110	0	685	715	681	2111	623	892	1267	358	55	15.36%	337	39	88.43%	1	1110	2273	48.83%	1093	2535	43.12%	508	1012	50.20%	1812	1320	1943	525	863	412
14	76	33	25	0	5	5	4	4	199	155	44	38	13	12	0	3	4	3	3	101	80	21	38	20	13	0	2	1	1	1	98	75	23	93	199	319	518	1	14	0	72	61	57	2110	0	685	715	681	2111	623	892	1267	358	55	15.36%	337	39	88.43%	1	1110	2273	48.83%	1093	2535	43.12%	508	1012	50.20%	1812	1320	1943	525	863	412
14	76	33	25	0	5	5	4	4	199	155	44	38	13	12	0	3	4	3	3	101	80	21	38	20	13	0	2	1	1	1	98	75	23	93	199	319	518	1	14	0	72	61	57	2110	0	685	715	681	2111	623	892	1267	358	55	15.36%	337	39	88.43%	1	1110	2273	48.83%	1093	2535	43.12%	508	1012	50.20%	1812	1320	1943	525	863	412
15	82	40	31	0	2	2	3	4	252	195	57	41	18	19	0	1	1	1	1	127	100	27	41	22	12	0	1	1	2	3	125	95	30	96	252	460	712	3	9	0	97	92	58	2457	0	782	853	804	2181	647	1044	1576	425	74	17.41%	433	68	84.30%	4	1223	2578	47.44%	1029	2546	40.42%	549	1215	45.19%	2084	1508	1922	559	955	482
15	82	40	31	0	2	2	3	4	252	195	57	41	18	19	0	1	1	1	1	127	100	27	41	22	12	0	1	1	2	3	125	95	30	96	252	460	712	3	9	0	97	92	58	2457	0	782	853	804	2181	647	1044	1576	425	74	17.41%	433	68	84.30%	4	1223	2578	47.44%	1029	2546	40.42%	549	1215	45.19%	2084	1508	1922	559	955	482
16	82	16	57	0	1	3	1	4	249	395	-146	41	9	28	0	0	1	1	2	127	198	-71	41	7	29	0	1	2	0	2	122	197	-75	43	249	408	657	2	0	0	100	79	68	2454	0	792	845	800	2766	832	1063	1719	382	56	14.66%	449	131	70.82%	4	907	2477	36.62%	852	2353	36.21%	532	1354	39.29%	1834	1315	2227	556	891	418
17	72	17	52	0	1	0	0	2	216	360	-144	36	10	25	0	0	0	0	1	115	175	-60	36	7	27	0	1	0	0	1	101	185	-84	38	216	361	577	1	0	0	87	79	49	2403	0	735	825	836	2744	773	755	1491	294	27	9.18%	325	75	76.92%	1	803	2148	37.38%	749	2213	33.85%	440	1210	36.36%	1472	1056	2077	492	782	340
18	72	20	51	0	0	1	0	0	176	352	-176	36	10	25	0	0	1	0	0	90	172	-82	36	10	26	0	0	0	0	0	86	180	-94	41	176	336	512	0	2	0	74	55	47	1881	0	606	619	656	3030	877	735	1248	292	38	13.01%	301	66	78.07%	2	743	1809	41.07%	849	2478	34.26%	409	1145	35.72%	1257	867	2296	503	767	326
19	70	9	54	0	2	2	1	2	161	359	-198	34	4	28	0	0	1	1	0	74	166	-92	36	5	26	0	2	1	0	2	87	193	-106	28	161	293	454	0	0	0	61	57	40	1871	0	607	582	665	2981	870	669	1248	307	38	12.38%	271	77	71.59%	0	574	1846	31.09%	659	2376	27.74%	362	1139	31.78%	1193	817	2271	507	763	313
20	50	31	13	0	1	4	1	0	171	106	65	27	15	7	0	1	3	1	0	92	55	37	23	16	6	0	0	1	0	0	79	51	28	70	171	298	469	0	3	78	42	49	3	1569	534	489	542	6	1244	348	531	919	264	43	16.29%	222	38	82.88%	2	798	1645	48.51%	644	1492	43.16%	396	736	53.80%	1261	922	1180	341	568	287
Total Regular Season	896	355	411	0	28	41	26	35	2554	2754	-200	449	164	214	0	15	24	15	17	1280	1362	-82	447	191	197	0	13	17	11	18	1274	1392	-118	894	2554	4377	6931	12	85	78	956	850	619	25884	534	8308	8762	8077	27236	7970	10968	16734	4419	677	15.32%	4410	774	82.45%	31	12367	26817	46.12%	11534	28464	40.52%	6010	13300	45.19%	20773	14961	23345	6195	10092	4814
Playoff
12	4	0	4	0	0	0	0	0	3	13	-10	2	0	2	0	0	0	0	0	3	5	-2	2	0	2	0	0	0	0	0	0	8	-8	0	3	5	8	0	0	0	1	2	0	49	0	15	13	21	111	29	56	85	21	2	9.52%	27	4	85.19%	0	47	89	52.81%	69	152	45.39%	32	51	62.75%	88	60	107	30	47	23
Total Playoff	4	0	4	0	0	0	0	0	3	13	-10	2	0	2	0	0	0	0	0	3	5	-2	2	0	2	0	0	0	0	0	0	8	-8	0	3	5	8	0	0	0	1	2	0	49	0	15	13	21	111	29	56	85	21	2	9.52%	27	4	85.19%	0	47	89	52.81%	69	152	45.39%	32	51	62.75%	88	60	107	30	47	23