LHSDB - Ligue de hockey simulee des debiles barbus

San Jose Sharks
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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	Kieffer Bellows	0		X			100.00	75	40	73	64	76	87	81	63	65	61	64	60	63	67	68	71	50	64	0
2	Lucas Condotta	0		X			100.00	71	41	73	63	81	73	86	62	65	60	61	64	62	68	72	36	50	63	0
3	Jan Jenik	0	X	X	X		100.00	70	42	69	64	80	79	81	63	67	60	58	64	61	65	67	63	50	63	0
4	Sam Morton	0	X				100.00	76	37	92	65	71	86	75	64	61	62	63	60	64	66	67	42	50	63	0
5	Mason Shaw	0	X	X			100.00	66	69	61	64	67	83	79	63	72	61	60	62	64	67	69	53	50	62	0
6	Jan Mysak	0	X	X			100.00	57	36	90	60	67	85	84	58	65	60	59	61	58	63	65	72	50	61	0
7	Eduard Sale	0		X			100.00	66	38	92	64	75	79	69	63	57	60	56	58	61	62	65	84	50	61	0
8	Shane Bowers	0	X		X		100.00	68	38	91	59	78	76	82	57	66	58	56	55	59	66	68	76	50	60	0
9	Kyle McDonald	0			X		100.00	82	42	84	56	91	73	79	55	56	53	57	58	56	63	65	44	50	60	0
10	Danil Zhilkin	0	X				100.00	66	38	88	56	76	73	78	55	60	54	53	57	55	62	64	66	50	58	0
11	Daylan Kuefler	0		X			100.00	70	51	67	56	79	85	66	55	58	54	52	57	53	63	65	49	50	58	0
12	Ryder Korczak	0	X				100.00	58	37	88	58	67	75	81	57	62	56	55	53	54	63	65	67	50	58	0
13	Aleksandr Kisakov	0	X	X			100.00	60	37	86	57	60	80	67	56	55	54	58	53	57	63	65	70	50	57	0
14	Daniil Misyul	0				X	100.00	69	41	70	59	80	76	79	58	30	57	55	60	48	65	67	64	50	62	0
15	Ville Heinola	0				X	100.00	61	39	84	63	71	82	71	64	30	63	58	60	50	64	66	80	50	62	0
16	Aidan Fulp	0				X	100.00	81	41	89	53	90	63	75	52	30	55	51	59	45	65	67	42	50	61	0
17	Jack Matier	0				X	100.00	84	41	90	53	93	64	70	52	30	54	51	59	45	62	64	59	50	61	0
18	Reilly Walsh	0				X	100.00	62	38	87	60	71	70	84	57	30	61	55	56	47	66	68	61	50	61	0
19	Vsevolod Komarov	0				X	100.00	68	43	67	59	77	75	72	58	30	57	52	62	45	61	63	57	50	61	0
20	Michael Karow	0				X	100.00	71	42	74	56	80	66	86	54	30	55	52	57	45	67	69	50	50	61	0
Scratches

	TEAM AVERAGE					100.00	69	42	81	59	77	77	77	58	51	58	56	59	55	64	66	60	50	61

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Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
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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	Trent Miner	100.00	77	82	78	74	76	75	77	76	75	77	76	64	71	58	50	73	0
2	Cooper Black	100.00	73	74	70	98	72	71	73	72	71	73	72	64	71	43	50	72	0
Scratches
1	Adam Scheel	100.00	74	81	77	82	73	72	74	73	72	74	73	66	75	42	50	72	0

	TEAM AVERAGE	100.00	75	79	75	85	74	73	75	74	73	75	74	65	72	48	50	72

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Nolan Pratt	65	71	78	68	75	70	76	CAN	50	7	1,000,000$

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Sam Morton	Barracuda (San)	C	72	45	66	111	79	30	0	108	165	341	91	243	13.20%	19	1495	20.78	11	20	31	76	219	0	0	0	23	8	4	68.36%	1650	3	1.48	0	0	0	0	0	11	7	6
2	Matej Blumel	San Jose Sharks	LW/RW	69	40	69	109	52	26	0	141	136	334	97	232	11.98%	32	1565	22.69	15	17	32	89	250	1	1	11	256	9	1	65.33%	274	1	1.39	1	3	0	0	0	8	9	10
3	Rocco Grimaldi	San Jose Sharks	LW/RW	64	42	49	91	52	20	0	80	123	276	75	218	15.22%	13	1302	20.36	12	20	32	68	237	0	0	6	100	9	1	67.26%	168	2	1.40	3	3	0	0	0	9	5	8
4	Eduard Sale	Barracuda (San)	LW	72	31	33	64	59	26	0	39	73	190	57	143	16.32%	26	1069	14.85	0	0	0	1	1	0	0	0	8	5	0	75.00%	80	2	1.20	0	0	0	0	0	6	4	4
5	Daniil Misyul	Barracuda (San)	D	72	11	52	63	77	44	0	106	47	129	44	103	8.53%	77	1723	23.94	4	15	19	70	227	0	0	1	207	1	0	56.25%	16	0	0.73	0	0	0	0	0	2	5	3
6	Ville Heinola	Barracuda (San)	D	53	17	46	63	48	34	0	98	53	127	35	82	13.39%	41	1291	24.37	9	10	19	58	173	0	0	0	170	6	1	49.84%	315	1	0.98	0	0	0	0	0	3	9	3
7	Riley Stillman	San Jose Sharks	D	61	15	39	54	51	116	20	137	66	115	37	77	13.04%	49	1410	23.12	10	11	21	63	196	0	0	1	162	1	1	50.00%	8	0	0.77	0	0	1	1	2	1	1	2
8	Jan Jenik	Barracuda (San)	C/LW/RW	41	23	26	49	46	35	5	86	74	148	57	92	15.54%	6	892	21.78	7	6	13	26	116	0	0	8	118	1	1	68.60%	414	2	1.10	0	1	0	0	1	4	5	2
9	Kieffer Bellows	Barracuda (San)	LW	61	16	32	48	46	24	0	91	64	164	54	142	9.76%	8	779	12.78	1	5	6	16	32	0	0	0	8	2	0	70.37%	81	0	1.23	0	1	0	0	0	4	0	1
10	Lucas Condotta	Barracuda (San)	LW	39	13	34	47	30	33	5	51	53	140	30	94	9.29%	8	643	16.51	3	11	14	23	111	0	0	2	18	3	2	68.18%	88	0	1.46	1	1	1	0	0	5	0	1
11	Kyle McDonald	Barracuda (San)	RW	72	22	25	47	56	87	5	155	54	159	40	137	13.84%	13	1057	14.68	1	0	1	2	1	0	0	0	0	4	0	67.44%	86	1	0.89	0	0	1	0	0	4	2	3
12	Shane Bowers	Barracuda (San)	C/RW	72	15	26	41	63	26	0	62	46	116	32	66	12.93%	20	1203	16.71	0	1	1	2	16	0	0	0	2	3	0	73.05%	141	0	0.68	0	0	0	0	0	0	3	2
13	Jan Mysak	Barracuda (San)	C/LW	58	8	26	34	39	12	0	15	70	117	24	91	6.84%	17	847	14.61	0	0	0	0	3	0	0	0	0	1	1	61.28%	594	0	0.80	0	0	0	0	0	0	2	4
14	Roman Schmidt	San Jose Sharks	D	51	8	16	24	41	89	15	133	28	43	7	28	18.60%	38	874	17.14	1	1	2	4	26	0	0	3	78	1	0	44.44%	9	0	0.55	0	0	0	2	1	0	0	4
15	Michael Karow	Barracuda (San)	D	41	3	13	16	38	20	0	24	8	19	9	10	15.79%	22	646	15.76	0	0	0	0	12	0	0	0	24	0	0	0.00%	0	0	0.50	0	0	0	0	0	0	0	0
16	Reilly Walsh	Barracuda (San)	D	41	4	11	15	32	16	0	38	10	27	14	28	14.81%	45	868	21.18	3	3	6	11	129	0	0	3	165	1	0	0.00%	1	0	0.35	0	0	0	0	0	0	2	0
17	Mason Shaw	Barracuda (San)	C/LW	23	8	6	14	18	16	0	29	31	48	14	31	16.67%	2	256	11.14	0	0	0	0	0	0	0	0	0	2	0	67.72%	254	0	1.09	0	0	0	0	0	1	2	0
18	Jansen Harkins	San Jose Sharks	C/LW/RW	3	3	0	3	3	4	0	10	6	21	4	12	14.29%	0	63	21.33	1	0	1	4	14	0	0	1	7	1	0	79.49%	78	0	0.94	0	0	0	0	0	1	0	1
Team Total or Average				965	324	569	893	830	658	50	1403	1107	2514	721	1829	12.89%	436	17992	18.65	78	120	198	513	1770	1	1	36	1353	58	12	66.10%	4257	12	0.99	5	9	3	3	4	59	56	54

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Michael Dipietro	San Jose Sharks	16	12	3	0	0.940	1.36	928	2	4	21	350	0	0	0	0.000	0	15	70	0	2	0
Team Total or Average			16	12	3	0	0.940	1.36	928	2	4	21	350	0	0	0	0.000	0	15	70	0	2	0

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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	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
Adam Scheel	G	26	1999-05-01	No	192 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Aidan Fulp	D	26	2000-02-29	No	216 Lbs	6 ft4	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Aleksandr Kisakov	C/LW	23	2002-11-01	No	150 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Cooper Black	G	24	2001-06-14	No	223 Lbs	6 ft8	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Daniil Misyul	D	25	2000-10-20	No	176 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Danil Zhilkin	C	22	2003-12-19	No	192 Lbs	6 ft1	No	No	No	3	ELC	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Daylan Kuefler	LW	24	2002-02-10	No	195 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Eduard Sale	LW	21	2005-03-10	No	174 Lbs	6 ft2	No	No	No	4	ELC	Pro & Farm	900,000$	0$	0$	No	Link
Jack Matier	D	23	2003-04-08	No	205 Lbs	6 ft6	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jan Jenik	C/LW/RW	25	2000-09-15	No	199 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jan Mysak	C/LW	23	2002-06-04	No	175 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Kieffer Bellows	LW	27	1998-06-10	No	195 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Kyle McDonald	RW	24	2002-02-05	No	221 Lbs	6 ft4	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Lucas Condotta	LW	28	1997-11-06	No	218 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	400,000$	0$	0$	No	Link / NHL Link
Mason Shaw	C/LW	27	1998-11-03	No	184 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Michael Karow	D	27	1998-12-18	No	200 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Reilly Walsh	D	26	1999-04-21	No	185 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ryder Korczak	C	23	2002-09-23	No	171 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Sam Morton	C	26	1999-07-28	No	185 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Shane Bowers	C/RW	26	1999-07-30	No	186 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Trent Miner	G	25	2001-02-05	No	185 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Ville Heinola	D	25	2001-03-02	No	181 Lbs	6 ft0	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Vsevolod Komarov	D	22	2004-01-11	No	182 Lbs	6 ft2	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
23	24.70	191 Lbs	6 ft2	2.22	373,913$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	2	2
2		Sam Morton		30	1	2	2
3			Shane Bowers	20	1	2	2
4	Eduard Sale		Kyle McDonald	10	1	2	2

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

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

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

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

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

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

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

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

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
				Daniil Misyul

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
				Daniil Misyul

Extra Forwards
Normal	PowerPlay	Penalty Kill
, , Sam Morton	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

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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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
72	124	OTW1	343	621	964	2711	1680	475	684	1488	0	13

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
72	57	9	2	1	2	1	343	116

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	26	6	0	1	2	1	157	62

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	31	3	2	0	0	0	186	54

Last 10 Games
W	L	OTW	OTL	SOW	SOL
8	1	1	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
332	84	25.30%	294	37	87.41%	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
875	908	918	19	147	105	87	7

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1480	2451	60.38%	1093	1983	55.12%	701	1072	65.39%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
2207	1674	1327	421	806	459

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	21	Barracuda	6	Reign	1	W			BoxScore
10 - 2025-08-24	29	Barracuda	7	Reign	0	W			BoxScore
16 - 2025-08-30	56	Wild	0	Barracuda	2	W			BoxScore
17 - 2025-08-31	63	Wild	1	Barracuda	8	W			BoxScore
20 - 2025-09-03	68	Barracuda	8	Silver Knights	1	W			BoxScore
22 - 2025-09-05	69	Barracuda	4	Silver Knights	3	W			BoxScore
27 - 2025-09-10	109	Firebirds	3	Barracuda	2	L			BoxScore
30 - 2025-09-13	128	Barracuda	7	Wild	1	W			BoxScore
31 - 2025-09-14	135	Barracuda	8	Wild	1	W			BoxScore
37 - 2025-09-20	167	Eagles	1	Barracuda	2	W			BoxScore
38 - 2025-09-21	176	Eagles	2	Barracuda	3	W			BoxScore
41 - 2025-09-24	189	Gulls	5	Barracuda	2	L			BoxScore
44 - 2025-09-27	213	Wranglers	1	Barracuda	10	W			BoxScore
45 - 2025-09-28	219	Wranglers	0	Barracuda	4	W			BoxScore
51 - 2025-10-04	242	Barracuda	6	Marlies	0	W			BoxScore
52 - 2025-10-05	256	Barracuda	7	Marlies	2	W			BoxScore
57 - 2025-10-10	278	Canucks	3	Barracuda	4	W			BoxScore
58 - 2025-10-11	290	Canucks	3	Barracuda	4	W			BoxScore
62 - 2025-10-15	306	Gulls	2	Barracuda	4	W			BoxScore
65 - 2025-10-18	330	Firebirds	1	Barracuda	0	L			BoxScore
66 - 2025-10-19	338	Firebirds	2	Barracuda	3	W			BoxScore
70 - 2025-10-23	352	Barracuda	3	Firebirds	2	W			BoxScore
72 - 2025-10-25	370	Barracuda	2	Gulls	1	W			BoxScore
73 - 2025-10-26	381	Barracuda	5	Reign	1	W			BoxScore
76 - 2025-10-29	396	Barracuda	3	Firebirds	1	W			BoxScore
78 - 2025-10-31	408	Barracuda	5	Condors	0	W			BoxScore
79 - 2025-11-01	420	Condors	0	Barracuda	6	W			BoxScore
86 - 2025-11-08	439	Barracuda	6	Silver Knights	1	W			BoxScore
87 - 2025-11-09	454	Barracuda	5	Silver Knights	2	W			BoxScore
90 - 2025-11-12	468	Barracuda	3	Gulls	2	W			BoxScore
93 - 2025-11-15	492	Eagles	1	Barracuda	6	W			BoxScore
94 - 2025-11-16	497	Eagles	1	Barracuda	6	W			BoxScore
99 - 2025-11-21	522	Condors	0	Barracuda	4	W			BoxScore
100 - 2025-11-22	534	Barracuda	4	Condors	1	W			BoxScore
107 - 2025-11-29	578	Barracuda	6	Canucks	0	W			BoxScore
108 - 2025-11-30	587	Barracuda	6	Canucks	1	W			BoxScore
111 - 2025-12-03	599	Firebirds	4	Barracuda	3	L	X		BoxScore
114 - 2025-12-06	613	Marlies	2	Barracuda	3	W	X	X	BoxScore
115 - 2025-12-07	632	Marlies	3	Barracuda	2	L	X	X	BoxScore
120 - 2025-12-12	660	Silver Knights	3	Barracuda	1	L			BoxScore
121 - 2025-12-13	672	Silver Knights	1	Barracuda	2	W	X	X	BoxScore
127 - 2025-12-19	689	Roadrunners	1	Barracuda	6	W			BoxScore
128 - 2025-12-20	692	Roadrunners	2	Barracuda	9	W			BoxScore
131 - 2025-12-23	709	Barracuda	7	Eagles	3	W			BoxScore
132 - 2025-12-24	717	Barracuda	7	Eagles	2	W			BoxScore
135 - 2025-12-27	741	Barracuda	6	Condors	0	W			BoxScore
136 - 2025-12-28	749	Barracuda	3	Gulls	1	W			BoxScore
139 - 2025-12-31	764	Reign	2	Barracuda	6	W			BoxScore
142 - 2026-01-03	788	Barracuda	7	Reign	1	W			BoxScore
143 - 2026-01-04	801	Barracuda	4	Firebirds	2	W			BoxScore
146 - 2026-01-07	812	Condors	2	Barracuda	8	W			BoxScore
149 - 2026-01-10	837	Silver Knights	1	Barracuda	2	W			BoxScore
150 - 2026-01-11	844	Silver Knights	5	Barracuda	1	L			BoxScore
153 - 2026-01-14	858	Gulls	3	Barracuda	1	L			BoxScore
155 - 2026-01-16	868	Barracuda	8	Canucks	2	W			BoxScore
156 - 2026-01-17	882	Barracuda	6	Canucks	2	W			BoxScore
163 - 2026-01-24	923	Barracuda	2	Roadrunners	1	W	X		BoxScore
164 - 2026-01-25	932	Barracuda	1	Roadrunners	3	L			BoxScore
167 - 2026-01-28	936	Gulls	4	Barracuda	5	W			BoxScore
170 - 2026-01-31	970	Barracuda	7	Condors	0	W			BoxScore
171 - 2026-02-01	978	Condors	0	Barracuda	7	W			BoxScore
174 - 2026-02-04	990	Barracuda	1	Gulls	2	L			BoxScore
176 - 2026-02-06	1001	Canucks	1	Barracuda	5	W			BoxScore
177 - 2026-02-07	1003	Canucks	1	Barracuda	6	W			BoxScore
181 - 2026-02-11	1037	Reign	0	Barracuda	5	W			BoxScore
183 - 2026-02-13	1047	Barracuda	7	Eagles	1	W			BoxScore
184 - 2026-02-14	1061	Barracuda	6	Eagles	1	W			BoxScore
188 - 2026-02-18	1078	Barracuda	2	Firebirds	3	L			BoxScore
190 - 2026-02-20	1090	Reign	1	Barracuda	9	W			BoxScore
191 - 2026-02-21	1102	Reign	0	Barracuda	6	W			BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
197 - 2026-02-27	1123	Barracuda	5	Wranglers	4	W			BoxScore
199 - 2026-03-01	1152	Barracuda	6	Wranglers	5	W	X		BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	67,928	34,354
Attendance PCT	94.34%	95.43%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	2841 - 94.71%	70,713$	2,545,654$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,108,445$	86,000$	86,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	108,445$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	5,430$	0$

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	46	24	0	2	5	5	0	234	149	85	41	24	11	0	1	3	2	0	119	70	49	41	22	13	0	1	2	3	0	115	79	36	111	234	417	651	0	10	0	83	84	60	2092	0	708	683	686	1780	550	1486	1843	490	75	15.31%	600	67	88.83%	8	1391	2492	55.82%	1342	2499	53.70%	625	1153	54.21%	2229	1581	1752	585	981	516
13	68	50	12	0	0	1	4	1	261	130	131	34	26	7	0	0	1	0	0	118	68	50	34	24	5	0	0	0	4	1	143	62	81	110	261	463	724	2	10	0	90	88	79	1977	0	610	658	702	1320	432	923	1295	454	90	19.82%	360	40	88.89%	7	1346	2176	61.86%	1025	1759	58.27%	602	997	60.38%	1937	1407	1358	459	810	445
14	68	42	11	0	6	2	3	4	262	126	136	34	19	7	0	4	1	3	0	125	56	69	34	23	4	0	2	1	0	4	137	70	67	108	262	480	742	1	9	0	91	85	77	2273	0	687	744	821	1394	393	593	1103	308	58	18.83%	241	32	86.72%	7	1491	2253	66.18%	1143	1716	66.61%	669	1001	66.83%	2066	1543	1257	420	808	455
14	68	42	11	0	6	2	3	4	262	126	136	34	19	7	0	4	1	3	0	125	56	69	34	23	4	0	2	1	0	4	137	70	67	108	262	480	742	1	9	0	91	85	77	2273	0	687	744	821	1394	393	593	1103	308	58	18.83%	241	32	86.72%	7	1491	2253	66.18%	1143	1716	66.61%	669	1001	66.83%	2066	1543	1257	420	808	455
14	68	42	11	0	6	2	3	4	262	126	136	34	19	7	0	4	1	3	0	125	56	69	34	23	4	0	2	1	0	4	137	70	67	108	262	480	742	1	9	0	91	85	77	2273	0	687	744	821	1394	393	593	1103	308	58	18.83%	241	32	86.72%	7	1491	2253	66.18%	1143	1716	66.61%	669	1001	66.83%	2066	1543	1257	420	808	455
15	82	38	29	0	1	3	8	3	236	204	32	41	20	12	0	0	1	6	2	121	89	32	41	18	17	0	1	2	2	1	115	115	0	100	236	381	617	0	3	0	85	72	70	2320	0	733	815	743	2444	690	801	1589	433	87	20.09%	342	48	85.96%	2	866	2413	35.89%	890	2770	32.13%	401	1186	33.81%	1906	1377	2146	567	929	447
15	82	38	29	0	1	3	8	3	236	204	32	41	20	12	0	0	1	6	2	121	89	32	41	18	17	0	1	2	2	1	115	115	0	100	236	381	617	0	3	0	85	72	70	2320	0	733	815	743	2444	690	801	1589	433	87	20.09%	342	48	85.96%	2	866	2413	35.89%	890	2770	32.13%	401	1186	33.81%	1906	1377	2146	567	929	447
16	82	44	28	0	1	3	4	2	280	223	57	41	25	13	0	1	0	1	1	149	110	39	41	19	15	0	0	3	3	1	131	113	18	103	280	507	787	1	1	0	95	90	90	2199	0	679	768	739	2064	627	1228	1608	405	75	18.52%	537	76	85.85%	3	1459	2458	59.36%	1430	2454	58.27%	732	1262	58.00%	2046	1443	1932	575	974	496
17	72	45	18	0	3	5	0	1	268	151	117	36	23	9	0	1	3	0	0	129	72	57	36	22	9	0	2	2	0	1	139	79	60	102	268	488	756	0	9	0	87	99	79	2045	0	606	707	721	1772	466	1065	1578	347	81	23.34%	461	69	85.03%	9	1294	2194	58.98%	1150	2167	53.07%	606	1022	59.30%	2041	1506	1492	463	813	434
18	72	44	23	0	2	3	0	0	313	215	98	36	20	13	0	2	1	0	0	153	119	34	36	24	10	0	0	2	0	0	160	96	64	95	313	557	870	1	4	0	142	91	78	2627	0	903	834	883	1805	481	820	1479	309	59	19.09%	348	67	80.75%	5	1560	2297	67.91%	1067	1676	63.66%	792	1143	69.29%	2226	1715	1321	396	782	444
19	70	53	5	0	5	2	3	2	330	145	185	36	28	1	0	2	2	2	1	175	69	106	34	25	4	0	3	0	1	1	155	76	79	126	330	568	898	1	9	0	138	98	86	2739	0	882	826	1011	1744	477	686	1573	306	82	26.80%	309	39	87.38%	1	1260	2246	56.10%	945	1885	50.13%	584	1061	55.04%	2177	1691	1328	392	734	410
20	72	57	9	0	2	1	2	1	343	116	227	36	26	6	0	0	1	2	1	157	62	95	36	31	3	0	2	0	0	0	186	54	132	124	343	621	964	0	13	147	105	87	7	2711	875	908	918	19	1680	475	684	1488	332	84	25.30%	294	37	87.41%	2	1480	2451	60.38%	1093	1983	55.12%	701	1072	65.39%	2207	1674	1327	421	806	459
Total Regular Season	886	541	210	0	35	32	43	25	3287	1915	1372	444	269	105	0	19	16	28	7	1617	916	701	442	272	105	0	16	16	15	18	1670	999	671	1295	3287	5823	9110	8	89	147	1183	1036	850	27849	875	8823	9256	8710	21235	6067	10273	17351	4433	894	20.17%	4316	587	86.40%	60	15995	27899	57.33%	13261	25111	52.81%	7451	13085	56.94%	24876	18403	18579	5689	10188	5469
Playoff
11	10	5	5	0	0	0	0	0	25	17	8	6	2	4	0	0	0	0	0	14	14	0	4	3	1	0	0	0	0	0	11	3	8	10	25	43	68	0	3	0	12	8	5	252	0	71	72	100	167	54	154	223	97	11	11.34%	61	7	88.52%	0	169	340	49.71%	141	284	49.65%	59	138	42.75%	267	186	218	78	126	65
12	6	2	4	0	0	0	0	0	6	14	-8	3	1	2	0	0	0	0	0	3	6	-3	3	1	2	0	0	0	0	0	3	8	-5	4	6	11	17	0	1	0	1	3	1	102	0	43	21	28	159	49	120	147	43	4	9.30%	47	5	89.36%	0	83	191	43.46%	83	210	39.52%	33	86	38.37%	144	93	172	52	81	38
13	11	5	6	0	0	0	0	0	21	25	-4	5	3	2	0	0	0	0	0	12	10	2	6	2	4	0	0	0	0	0	9	15	-6	10	21	36	57	0	0	0	7	5	8	241	0	81	68	85	227	63	167	201	86	11	12.79%	65	7	89.23%	1	182	355	51.27%	188	338	55.62%	81	160	50.63%	265	178	268	87	141	72
14	5	1	4	0	0	0	0	0	7	10	-3	3	0	3	0	0	0	0	0	3	7	-4	2	1	1	0	0	0	0	0	4	3	1	2	7	14	21	0	0	0	2	1	4	132	0	34	42	44	116	34	43	86	32	2	6.25%	17	5	70.59%	0	93	186	50.00%	96	181	53.04%	39	77	50.65%	140	95	126	44	71	36
15	6	2	4	0	0	0	0	0	8	10	-2	3	1	2	0	0	0	0	0	3	4	-1	3	1	2	0	0	0	0	0	5	6	-1	4	8	15	23	0	1	0	2	4	2	136	0	51	44	37	179	38	65	96	28	5	17.86%	30	4	86.67%	0	46	158	29.11%	43	212	20.28%	16	70	22.86%	110	76	187	43	67	28
16	5	1	4	0	0	0	0	0	8	12	-4	2	1	1	0	0	0	0	0	4	4	0	3	0	3	0	0	0	0	0	4	8	-4	2	8	13	21	1	0	0	4	2	2	114	0	35	36	37	118	31	68	93	29	3	10.34%	34	3	91.18%	0	89	167	53.29%	89	170	52.35%	35	67	52.24%	128	88	130	38	64	32
17	11	4	7	0	0	0	0	0	20	26	-6	5	2	3	0	0	0	0	0	7	10	-3	6	2	4	0	0	0	0	0	13	16	-3	8	20	35	55	0	0	0	7	9	4	248	0	70	88	80	315	90	168	246	66	9	13.64%	77	14	81.82%	0	118	349	33.81%	127	382	33.25%	44	146	30.14%	254	172	305	84	131	64
18	7	3	4	0	0	0	0	0	24	27	-3	3	1	2	0	0	0	0	0	8	9	-1	4	2	2	0	0	0	0	0	16	18	-2	6	24	43	67	0	0	0	9	8	7	233	0	77	67	87	198	51	119	143	20	7	35.00%	46	10	78.26%	0	175	227	77.09%	113	170	66.47%	84	108	77.78%	214	162	130	37	77	44
19	5	1	4	0	0	0	0	0	16	27	-11	3	1	2	0	0	0	0	0	9	15	-6	2	0	2	0	0	0	0	0	7	12	-5	2	16	27	43	0	0	0	5	4	7	127	0	52	40	35	203	54	50	111	27	6	22.22%	24	8	66.67%	0	36	129	27.91%	36	152	23.68%	28	93	30.11%	99	68	143	35	56	26
Total Playoff	66	24	42	0	0	0	0	0	135	168	-33	33	12	21	0	0	0	0	0	63	79	-16	33	12	21	0	0	0	0	0	72	89	-17	48	135	237	372	1	5	0	49	44	40	1585	0	514	478	533	1682	464	954	1346	428	58	13.55%	401	63	84.29%	1	991	2102	47.15%	916	2099	43.64%	419	945	44.34%	1624	1122	1684	503	818	409