Couch Coach Hockey League - Today's Games Farm

Roster

Player	#	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Brandon Sutter	20	C/RW	97.00	56	29	95	83	75	80	83	77	87	66	68	71	73	99	99	1	60	72	35	1,100,000$/1yrs
Ondrej Kase	25	LW/RW	100.00	53	32	93	91	70	77	76	79	26	73	69	75	72	98	92	62	67	72	28	778,000$/1yrs
Evan Rodrigues	0	C/RW	100.00	52	28	94	79	65	90	78	75	80	67	69	78	69	99	99	48	76	72	31	1,245,000$/1yrs
Andy Andreoff	0	C/LW	100.00	83	83	62	78	79	85	79	82	81	59	64	78	66	99	99	34	76	72	33	1,265,000$/1yrs
Sean Malone	37	C	100.00	52	33	94	78	72	69	76	83	77	74	71	74	63	94	98	60	77	72	29	1,340,000$/1yrs
Linden Vey	91	C/RW	97.00	72	47	80	76	70	84	76	81	81	74	69	71	65	99	99	32	75	72	33	1,145,000$/1yrs
Skyler McKenzie	0	LW	97.00	47	39	96	92	59	76	95	78	55	70	78	75	70	69	69	63	77	72	26	900,000$/3yrs
Nils Hoglander	0	LW	100.00	64	43	90	90	67	75	78	80	44	78	82	75	25	64	64	74	76	72	23	1,800,000$/5yrs
Nick Moutrey	0	C	100.00	95	92	53	76	81	59	73	81	75	71	69	73	65	93	89	61	68	71	29	1,000,000$/1yrs
Josh Archibald	0	LW/RW	100.00	50	34	96	76	64	78	82	78	25	69	73	71	67	98	99	38	76	70	31	1,000,000$/2yrs
German Rubtsov	0	C/LW	100.00	52	43	96	88	66	61	75	71	69	68	65	61	64	94	90	65	76	68	26	700,000$/6yrs
Valtteri Puustinen	0	LW/RW	100.00	47	40	94	86	66	77	91	67	60	56	66	68	71	66	66	74	77	66	25	1,063,750$/3yrs
Olivier Nadeau (R)	0	C/RW	100.00	55	52	80	81	77	70	95	68	65	59	66	72	66	50	50	91	20	65	21	925,000$/1yrs
Oliver Kylington	58	D	100.00	80	52	73	81	69	71	72	79	25	70	65	72	58	91	92	67	63	72	27	716,000$/3yrs
Mason Geertsen	0	D	100.00	81	66	62	67	82	69	72	74	25	55	47	77	52	93	93	60	71	70	29	700,000$/1yrs
Alexander Alexeyev	0	D	100.00	75	44	95	71	75	70	70	68	25	52	47	83	25	68	68	75	77	68	25	837,778$/3yrs
Will Borgen	0	D	100.00	98	73	69	61	80	69	58	61	25	39	47	88	25	82	82	55	59	68	27	950,000$/3yrs
Scott Perunovich (A)	0	D	100.00	59	40	89	82	64	67	80	79	25	70	54	73	25	71	71	72	77	68	26	925,000$/1yrs
Scratches
Nolan Foote	0	LW	100.00	77	74	85	76	74	75	78	63	50	56	65	70	62	64	64	75	21	65	23	863,333$/2yrs
Josiah Slavin	0	LW	100.00	66	43	93	74	74	61	79	65	58	61	60	77	25	75	76	68	22	65	25	925,000$/1yrs
Tyce Thompson	0	RW	100.00	64	63	78	70	67	54	51	70	50	69	69	68	62	65	67	74	20	63	25	925,000$/2yrs
William Lockwood	0	RW	100.00	99	93	80	69	64	59	68	57	25	50	55	70	25	72	72	68	20	60	26	700,000$/2yrs
Zakhar Bardakov (R)	0	C/RW	100.00	56	52	76	76	77	54	59	53	65	53	44	65	46	62	62	78	20	57	23	925,000$/2yrs
Jackson Kunz (R)	0	C	100.00	62	60	72	72	84	56	71	46	59	44	39	66	41	59	59	79	20	55	22	925,000$/2yrs
MacKenze Stewart	24	LWD	85.47	81	77	65	73	94	70	71	77	25	59	54	74	57	97	99	55	61	72	29	1,260,000$/1yrs
Vincent Iorio (R)	0	D	100.00	82	77	94	65	77	73	79	60	25	46	40	75	38	58	58	80	22	64	21	925,000$/3yrs
Axel Rindell	0	D	100.00	46	40	95	81	66	68	87	54	25	53	46	59	48	63	63	81	20	61	24	750,000$/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
Keith Petruzzelli	0	99.00	84	78	81	72	79	95	94	94	95	72	69	72	72	73	70	82	25	1,100,000$/5yrs
Luke Opilka	0	99.00	70	73	66	73	70	93	93	94	93	72	74	88	91	44	78	81	27	750,000$/1yrs
Scratches
Mitchell Gibson	0	100.00	57	69	68	72	57	67	62	72	65	63	65	67	67	72	20	65	25	925,000$/2yrs
Daniil Chechelov	0	100.00	44	40	50	71	50	44	45	49	45	45	45	46	46	78	20	48	23	925,000$/2yrs

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary

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	MP	PPG	PPA	PPP	PPM	PKG	PKA	PKP	PKM	GW	GT	FO%	FOT	EG	HT	P/20	PSG	PSS
1	Linden Vey	Barracuda (SJS)	C/RW	76	23	43	66	30	34	0	136	232	66	174	9.91%	21	19.71	4	8	12	179	1	1	2	125	3	2	58.00%	200	0	1	0.88	1	2
2	Nils Hoglander	Barracuda (SJS)	LW	72	24	35	59	14	14	0	90	278	71	249	8.63%	18	19.06	6	10	16	173	0	0	0	129	5	3	35.35%	297	0	0	0.86	0	3
3	Evan Rodrigues	Barracuda (SJS)	C/RW	74	19	33	52	15	6	0	29	189	45	130	10.05%	23	16.15	2	6	8	99	0	0	0	83	5	1	56.00%	825	0	0	0.87	0	0
4	Andy Andreoff	Barracuda (SJS)	C/LW	77	25	26	51	3	102	10	276	265	63	166	9.43%	22	17.61	2	4	6	122	1	1	2	121	4	2	55.36%	1718	1	0	0.75	0	1
5	Oliver Kylington	Barracuda (SJS)	D	72	12	39	51	23	34	0	115	120	37	93	10.00%	64	22.65	5	5	10	155	0	1	1	142	3	0	0.00%	0	0	0	0.63	0	0
6	Skyler McKenzie	Barracuda (SJS)	LW	77	23	27	50	15	4	0	21	291	83	198	7.90%	16	18.35	2	7	9	150	0	0	0	87	7	1	47.13%	244	0	0	0.71	0	2
7	Brandon Sutter	Barracuda (SJS)	C/RW	65	16	31	47	9	4	0	40	181	51	116	8.84%	16	20.32	1	6	7	121	1	0	1	99	3	2	59.72%	1209	1	0	0.71	0	2
8	Ondrej Kase	Barracuda (SJS)	LW/RW	77	21	25	46	3	2	0	16	223	64	167	9.42%	15	16.88	2	1	3	94	0	0	0	96	3	2	31.15%	459	0	0	0.71	0	0
9	Josh Archibald	Barracuda (SJS)	LW/RW	74	24	17	41	15	4	0	28	190	68	133	12.63%	12	15.61	1	3	4	51	0	0	0	15	5	2	27.27%	88	0	0	0.71	0	0
10	MacKenze Stewart	Barracuda (SJS)	LW/D	69	8	27	35	28	52	0	165	79	26	54	10.13%	95	22.53	4	5	9	151	0	2	2	144	2	0	33.33%	6	0	0	0.45	2	4
11	Sean Malone	Barracuda (SJS)	C	77	14	20	34	-13	4	0	50	144	33	88	9.72%	25	15.83	2	3	5	85	0	0	0	9	0	0	57.49%	828	0	0	0.56	0	0
12	Scott Perunovich	Barracuda (SJS)	D	77	2	29	31	-10	18	0	56	62	18	24	3.23%	71	17.11	1	0	1	50	0	0	0	40	1	0	0.00%	0	0	0	0.47	0	0
13	Mason Geertsen	Barracuda (SJS)	D	77	9	17	26	17	74	10	224	70	29	43	12.86%	86	21.53	4	4	8	182	0	0	0	171	1	0	0.00%	0	0	0	0.31	0	0
14	Nick Moutrey	Barracuda (SJS)	C	75	6	18	24	9	59	5	138	88	23	69	6.82%	8	9.30	0	3	3	31	0	0	0	16	1	0	57.44%	874	0	0	0.69	0	1
15	Alexander Alexeyev	Barracuda (SJS)	D	77	2	22	24	2	14	0	38	79	38	66	2.53%	116	20.80	0	3	3	166	0	0	0	193	1	0	0.00%	0	0	0	0.30	0	0
16	Valtteri Puustinen	Barracuda (SJS)	LW/RW	72	9	12	21	-6	0	0	0	116	29	86	7.76%	8	13.71	0	0	0	0	0	0	0	0	1	0	51.39%	72	0	0	0.43	0	0
17	Will Borgen	Barracuda (SJS)	D	69	5	6	11	-1	48	0	145	39	12	27	12.82%	73	13.01	1	0	1	30	0	0	0	76	0	0	0.00%	0	0	0	0.24	0	0
18	German Rubtsov	Barracuda (SJS)	C/LW	76	3	7	10	-6	4	0	8	50	23	42	6.00%	1	5.85	0	0	0	0	0	0	0	0	0	0	58.97%	39	0	0	0.45	0	0
19	Vincent Iorio	Barracuda (SJS)	D	5	0	1	1	5	4	0	6	2	1	0	0.00%	5	17.33	0	0	0	0	0	0	0	4	0	0	0.00%	0	0	0	0.23	0	0
20	Nolan Foote	Barracuda (SJS)	LW	27	0	1	1	1	2	0	4	1	2	5	0.00%	1	1.84	0	0	0	0	0	0	0	0	0	0	100.00%	1	0	0	0.40	0	0
21	Olivier Nadeau	Barracuda (SJS)	C/RW	18	0	1	1	-2	0	0	0	8	0	2	0.00%	0	3.55	0	0	0	0	0	0	0	0	0	0	25.00%	4	0	0	0.31	0	0
22	Josiah Slavin	Barracuda (SJS)	LW	3	0	0	0	0	0	0	0	0	0	0	0.00%	0	0.00	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0	0.00	0	0
Team Total or Average				1386	245	437	682	151	483	25	1585	2707	782	1932	9.05%	696	16.46	37	68	105	1847	3	5	8	1557	45	15	53.61%	6864	2	1	0.60	3	15

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	GS	W	L	OTL	PCT	GAA	GSAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Keith Petruzzelli	Barracuda (SJS)	64	64	37	18	7	0.919	2.63	7.8	3772	6	4	165	2033	0	2	1	0.571	14	64	13	7	3	6
2	Luke Opilka	Barracuda (SJS)	16	13	9	4	2	0.924	2.70	4.7	888	0	0	40	526	0	1	1	0.000	0	13	64	1	4	0
Team Total or Average		80	46	22	9	0.920	2.64	4661	6	4	205	2559	0	3	2	0.571	14	77	77	8	7	6

Salary

Player Name	POS	Age	2017-18	2018-19	2019-20	2020-21	2021-22	2022-23
Alexander Alexeyev	D	25	$863,333	$825,000	$825,000
Andy Andreoff	C/LW	33	$1,265,000
Axel Rindell	D	24	$750,000
Brandon Sutter	C/RW	35	$1,100,000
Daniil Chechelov	G	23	$925,000	$925,000
Evan Rodrigues	C/RW	31	$1,245,000
German Rubtsov	C/LW	26	$700,000	$700,000	$700,000	$700,000	$700,000	$700,000
Jackson Kunz	C	22	$925,000	$925,000
Josh Archibald	LW/RW	31	$1,000,000	$1,000,000
Josiah Slavin	LW	25	$925,000
Keith Petruzzelli	G	25	$1,100,000	$1,100,000	$1,100,000	$1,100,000	$1,100,000
Linden Vey	C/RW	33	$1,145,000
Luke Opilka	G	27	$750,000
MacKenze Stewart	LW/D	29	$1,260,000
Mason Geertsen	D	29	$700,000
Mitchell Gibson	G	25	$925,000	$925,000
Nick Moutrey	C	29	$1,000,000
Nils Hoglander	LW	23	$1,800,000	$1,800,000	$1,800,000	$1,800,000	$1,800,000
Nolan Foote	LW	23	$863,333	$863,333
Oliver Kylington	D	27	$716,000	$716,000	$716,000
Olivier Nadeau	C/RW	21	$925,000
Ondrej Kase	LW/RW	28	$778,000
Scott Perunovich	D	26	$925,000
Sean Malone	C	29	$1,340,000
Skyler McKenzie	LW	26	$900,000	$900,000	$900,000
Tyce Thompson	RW	25	$762,500	$762,500
Valtteri Puustinen	LW/RW	25	$1,063,750	$1,063,750	$1,063,750
Vincent Iorio	D	21	$925,000	$925,000	$925,000
Will Borgen	D	27	$950,000	$950,000	$950,000
William Lockwood	RW	26	$700,000	$700,000
Zakhar Bardakov	C/RW	23	$925,000	$925,000

Lines

Forward Lines
#25 - Ondrej Kase	#0 - Nick Moutrey	#91 - Linden Vey
#20 - Brandon Sutter	#0 - Evan Rodrigues	#0 - Josh Archibald
#0 - Skyler McKenzie	#0 - Andy Andreoff	#0 - Valtteri Puustinen
#0 - German Rubtsov	#37 - Sean Malone	#20 - Brandon Sutter

Defensive Pairings
#58 - Oliver Kylington	#0 - Mason Geertsen
#0 - Alexander Alexeyev	#0 - Will Borgen
#0 - Scott Perunovich	#37 - Sean Malone

1st Power Play Unit
#20 - Brandon Sutter		#0 - Skyler McKenzie		#91 - Linden Vey
#0 - Scott Perunovich			#0 - Mason Geertsen

2nd Power Play Unit
#0 - Andy Andreoff		#0 - Evan Rodrigues		#0 - Josh Archibald
#0 - Alexander Alexeyev			#0 - Will Borgen

Goalies

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	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	6	2	2	1	1	0	0	18	17	1	7	0.583	18	32	50	0	1	93	75	72	8	237	900	913	857	52	188	55	40	129	14	1	7.14%	20	5	75.00%	1	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	58.6%	7.6%	91.0%	98.6	Unlucky
2	Phantoms	1	0	0	0	0	0	1	2	3	-1	1	0.500	2	4	6	0	0	93	75	72	8	44	900	913	857	52	34	11	11	18	5	1	20.00%	3	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	25.0%	4.5%	91.2%	95.7	DULL
3	Senators	1	1	0	0	0	0	0	3	1	2	2	1.000	3	5	8	0	0	93	75	72	8	45	900	913	857	52	39	5	12	36	3	1	33.33%	4	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	66.7%	6.7%	97.4%	104.1	DULL
4	Islanders	1	0	0	1	0	0	0	3	2	1	2	1.000	3	5	8	0	0	93	75	72	8	23	900	913	857	52	35	10	6	21	2	0	0.00%	3	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	60.0%	13.0%	94.3%	107.3	LUCKY
5	Checkers	1	0	1	0	0	0	0	6	7	-1	0	0.000	6	12	18	0	0	93	75	72	8	32	900	913	857	52	41	15	8	18	3	0	0.00%	4	1	75.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	50.0%	18.8%	82.9%	101.7	FUN
6	Canucks	8	5	1	1	0	0	1	25	17	8	13	0.813	25	42	67	0	2	93	75	72	8	293	900	913	857	52	228	66	50	142	31	5	16.13%	24	3	87.50%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	58.8%	8.5%	92.5%	101.1	DULL
7	Wolf Pack	1	0	1	0	0	0	0	3	4	-1	0	0.000	3	6	9	0	0	93	75	72	8	48	900	913	857	52	27	8	2	21	2	2	100.00%	1	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	20.0%	6.3%	85.2%	91.4	Unlucky
8	Griffins	1	1	0	0	0	0	0	4	1	3	2	1.000	4	8	12	0	0	93	75	72	8	28	900	913	857	52	40	12	10	19	6	3	50.00%	5	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	50.0%	14.3%	97.5%	111.8	LUCKY
9	Rocket	1	1	0	0	0	0	0	4	2	2	2	1.000	4	7	11	0	0	93	75	72	8	28	900	913	857	52	49	10	16	27	1	0	0.00%	8	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	66.7%	14.3%	95.9%	110.2	LUCKY
10	Bears	1	1	0	0	0	0	0	6	2	4	2	1.000	6	10	16	0	0	93	75	72	8	38	900	913	857	52	38	16	4	22	1	0	0.00%	2	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	75.0%	15.8%	94.7%	110.5	LUCKY
11	Wild	2	2	0	0	0	0	0	11	7	4	4	1.000	11	18	29	0	0	93	75	72	8	80	900	913	857	52	58	12	6	48	5	2	40.00%	2	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	56.3%	13.8%	87.9%	101.7	FUN
12	Eagles	2	0	1	1	0	0	0	4	5	-1	2	0.500	4	6	10	0	0	93	75	72	8	53	900	913	857	52	84	20	10	48	7	0	0.00%	5	1	80.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	50.0%	7.5%	94.0%	101.6	DULL
13	Reign	6	3	3	0	0	0	0	20	22	-2	6	0.500	20	34	54	0	0	93	75	72	8	243	900	913	857	52	208	68	51	136	10	4	40.00%	17	4	76.47%	1	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	47.1%	8.2%	89.4%	97.7	Unlucky
14	Admirals	2	0	2	0	0	0	0	1	7	-6	0	0.000	1	2	3	0	0	93	75	72	8	68	900	913	857	52	84	27	22	50	4	0	0.00%	11	3	72.73%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	20.0%	1.5%	91.7%	93.1	DULL
15	Crunch	2	0	1	0	0	0	1	6	8	-2	1	0.250	6	11	17	0	0	93	75	72	8	72	900	913	857	52	60	13	12	42	8	1	12.50%	5	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	38.5%	8.3%	86.7%	95.0	Unlucky
16	Condors	6	1	1	0	3	1	0	19	21	-2	7	0.583	19	32	51	0	0	93	75	72	8	189	900	913	857	52	233	54	30	112	16	5	31.25%	15	1	93.33%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	41.2%	10.1%	91.0%	101.0	FUN
17	Thunderbirds	2	2	0	0	0	0	0	8	5	3	4	1.000	8	14	22	0	0	93	75	72	8	66	900	913	857	52	60	16	10	28	6	1	16.67%	5	1	80.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	63.6%	12.1%	91.7%	103.8	LUCKY
18	Grizzlies	2	2	0	0	0	0	0	14	5	9	4	1.000	14	27	41	0	0	93	75	72	8	69	900	913	857	52	67	15	8	51	5	0	0.00%	4	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	73.7%	20.3%	92.5%	112.8	LUCKY
19	Bruins	1	1	0	0	0	0	0	4	3	1	2	1.000	4	8	12	0	0	93	75	72	8	41	900	913	857	52	30	8	6	21	4	1	25.00%	3	1	66.67%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	60.0%	9.8%	90.0%	99.8	FUN
20	Americans	2	2	0	0	0	0	0	7	3	4	4	1.000	7	13	20	0	0	93	75	72	8	77	900	913	857	52	65	31	16	44	2	1	50.00%	8	0	100.00%	1	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	66.7%	9.1%	95.4%	104.5	LUCKY
21	IceHogs	5	3	2	0	0	0	0	11	13	-2	6	0.600	11	18	29	1	1	93	75	72	8	174	900	913	857	52	167	44	23	105	12	2	16.67%	9	1	88.89%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	42.9%	6.3%	92.2%	98.5	DULL
22	Citadelles	1	1	0	0	0	0	0	3	2	1	2	1.000	3	5	8	0	0	93	75	72	8	19	900	913	857	52	28	9	8	18	3	1	33.33%	4	1	75.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	66.7%	15.8%	92.9%	108.6	LUCKY
23	Monsters	1	1	0	0	0	0	0	3	1	2	2	1.000	3	6	9	0	0	93	75	72	8	30	900	913	857	52	24	8	4	18	2	0	0.00%	2	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	75.0%	10.0%	95.8%	105.8	LUCKY
24	Moose	2	2	0	0	0	0	0	6	4	2	4	1.000	6	11	17	0	0	93	75	72	8	69	900	913	857	52	66	15	8	35	8	1	12.50%	4	1	75.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	62.5%	8.7%	93.9%	102.6	DULL
25	Gulls	5	3	1	1	0	0	0	16	10	6	8	0.800	16	26	42	0	0	93	75	72	8	162	900	913	857	52	167	45	26	92	11	1	9.09%	13	1	92.31%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	62.5%	9.9%	94.0%	103.9	LUCKY
26	Stars	2	0	2	0	0	0	0	4	9	-5	0	0.000	4	8	12	1	0	93	75	72	8	60	900	913	857	52	51	10	12	36	8	0	0.00%	5	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	30.8%	6.7%	82.4%	89.0	Unlucky
27	Marlies	1	1	0	0	0	0	0	3	1	2	2	1.000	3	6	9	0	0	93	75	72	8	25	900	913	857	52	33	5	8	22	1	0	0.00%	3	0	100.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	75.0%	12.0%	97.0%	109.0	LUCKY
28	Penguins	2	0	2	0	0	0	0	3	5	-2	0	0.000	3	6	9	0	0	93	75	72	8	59	900	913	857	52	51	17	10	30	3	0	0.00%	4	2	50.00%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	50.0%	5.1%	90.2%	95.3	Unlucky
29	Firebirds	5	2	1	0	1	0	1	16	17	-1	6	0.600	16	30	46	0	0	93	75	72	8	186	900	913	857	52	164	39	31	95	14	2	14.29%	13	3	76.92%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	50.0%	8.6%	89.6%	98.2	Unlucky
30	Silver Knights	4	3	1	0	0	0	0	13	7	6	6	0.750	13	25	38	0	0	93	75	72	8	149	900	913	857	52	142	32	29	101	14	2	14.29%	12	1	91.67%	0	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	64.7%	8.7%	95.1%	103.8	DULL
	_Vs Division	40	11	11	3	5	1	1	127	111	16	36	0.450	127	221	348	0	3	93	75	72	8	1459	900	913	857	52	1330	359	257	807	110	20	18.18%	114	18	84.21%	2	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	53.5%	8.7%	91.7%	100.4	DULL
	_Vs Conference	49	24	15	3	5	1	1	155	144	11	62	0.633	155	272	427	2	2	93	75	72	8	1714	900	913	857	52	1661	440	291	1002	128	22	17.19%	130	21	83.85%	2	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	52.0%	9.0%	91.3%	100.4	LUCKY
	_Since Last GM Reset	77	40	22	5	5	1	4	246	211	35	101	0.656	246	437	683	2	4	93	75	72	8	2707	900	913	857	52	2561	696	489	1585	211	37	17.54%	218	30	86.24%	3	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	53.6%	9.1%	91.8%	100.8	LUCKY
	Total	77	40	22	5	5	1	4	246	211	35	101	0.656	246	437	683	2	4	93	75	72	8	2707	900	913	857	52	2561	696	489	1585	211	37	17.54%	218	30	86.24%	3	1582	2846	55.59%	1468	2776	52.88%	630	1161	54.26%	1889	1329	1796	552	980	489	53.6%	9.1%	91.8%	100.8	LUCKY

	Puck Time
Offensive Zone	24
Neutral Zone	12
Defensive Zone	23

	Puck Time
Offensive Zone Start	2846
Neutral Zone Start	1161
Defensive Zone Start	2776

	Puck Time
With Puck	30
Without Puck	29

	Faceoffs
Faceoffs Won	3680
Faceoffs Lost	3103

	Team Average Shots after	League Average Shots after
1st Period	11.7	9.57
2nd Period	23.5	20.31
3rd Period	34.7	30.68
Overtime	35.4	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	1.2	0.64
2nd Period	2.2	1.65
3rd Period	3.1	2.67
Overtime	3.2	2.83


Even Strenght Goal	204
PP Goal	37
PK Goal	3
Empty Net Goal	2

	Home	Away
Win	27	19
Lost	10	12
Overtime Lost	2	7


PP Attempt	211
PP Goal	37
PK Attempt	218
PK Goal Against	30

	Home
Shots For	35.2
Shots Against	33.3
Goals For	3.2
Goals Against	2.7
Hits	20.6
Shots Blocked	9.0
Pim	6.4

Schedule

Date	Matchup			Result	Detail
Mon, Jun 24	SJB	@	CVF	SJB4,CVF5 (OT)	RECAP
Tue, Jun 25	RCK	@	SJB	RCK2,SJB3	RECAP
Thu, Jun 27	SJB	@	ONT	SJB4,ONT2	RECAP
Sun, Jun 30	ABB	@	SJB	ABB4,SJB5	RECAP
Tue, Jul 2	HEN	@	SJB	HEN1,SJB5	RECAP
Wed, Jul 3	SJB	@	HEN	SJB5,HEN2	RECAP
Sat, Jul 6	SJB	@	ABB	SJB5,ABB4 (OT)	RECAP
Sun, Jul 7	CGY	@	SJB	CGY3,SJB5	RECAP
Tue, Jul 9	SJB	@	BAK	SJB3,BAK5	RECAP
Wed, Jul 10	SJB	@	SDG	SJB3,SDG2	RECAP
Fri, Jul 12	ABB	@	SJB	ABB0,SJB3	RECAP
Tue, Jul 16	CVF	@	SJB	CVF4,SJB5	RECAP
Thu, Jul 18	BAK	@	SJB	BAK1,SJB3	RECAP
Sun, Jul 21	RCK	@	SJB	RCK0,SJB1	RECAP
Mon, Jul 22	SJB	@	WBS	SJB2,WBS3	RECAP
Tue, Jul 23	SJB	@	ABB	SJB4,ABB1	RECAP
Thu, Jul 25	SJB	@	CGY	SJB1,CGY2 (OT)	RECAP
Sat, Jul 27	ABB	@	SJB	ABB1,SJB3	RECAP
Tue, Jul 30	BAK	@	SJB	BAK4,SJB3 (OT)	RECAP
Thu, Aug 1	BRP	@	SJB	BRP2,SJB3 (OT)	RECAP
Sat, Aug 3	SJB	@	MIL	SJB1,MIL4	RECAP
Mon, Aug 5	HEN	@	SJB	HEN1,SJB2	RECAP
Tue, Aug 6	SJB	@	ABB	SJB1,ABB0	RECAP
Fri, Aug 9	SDG	@	SJB	SDG2,SJB3 (OT)	RECAP
Sun, Aug 11	SJB	@	ONT	SJB5,ONT1	RECAP
Mon, Aug 12	SJB	@	BAK	SJB4,BAK3 (SO)	RECAP
Wed, Aug 14	RCH	@	SJB	RCH1,SJB4	RECAP
Sat, Aug 17	SJB	@	WBS	SJB1,WBS2	RECAP
Sun, Aug 18	RCK	@	SJB	RCK2,SJB4	RECAP
Tue, Aug 20	SJB	@	TOR	SJB3,TOR1	RECAP
Thu, Aug 22	SJB	@	GRP	SJB4,GRP1	RECAP
Sat, Aug 24	SDG	@	SJB	SDG1,SJB6	RECAP
Mon, Aug 26	CGY	@	SJB	CGY4,SJB3	RECAP
Wed, Aug 28	SJB	@	RCK	SJB2,RCK4	RECAP
Thu, Aug 29	SDG	@	SJB	SDG2,SJB4	RECAP
Sat, Aug 31	SJB	@	CVF	SJB3,CVF4 (SO)	RECAP
Mon, Sep 2	RCH	@	SJB	RCH2,SJB3	RECAP
Thu, Sep 5	CVF	@	SJB	CVF1,SJB0	RECAP
Fri, Sep 6	SJB	@	CLE	SJB3,CLE1	RECAP
Sun, Sep 8	SJB	@	LAV	SJB4,LAV2	RECAP
Tue, Sep 10	HER	@	SJB	HER2,SJB6	RECAP
Fri, Sep 13	ONT	@	SJB	ONT3,SJB5	RECAP
Sat, Sep 14	SJB	@	CVF	SJB4,CVF3	RECAP
Mon, Sep 16	UTA	@	SJB	UTA2,SJB5	RECAP
Wed, Sep 18	SJB	@	BAK	SJB3,BAK4 (OT)	RECAP
Fri, Sep 20	SJB	@	HFD	SJB3,HFD4	RECAP
Sat, Sep 21	SJB	@	COL	SJB2,COL4	RECAP
Mon, Sep 23	ONT	@	SJB	ONT4,SJB2	RECAP
Wed, Sep 25	IOW	@	SJB	IOW3,SJB4	RECAP
Fri, Sep 27	SYR	@	SJB	SYR4,SJB3	RECAP
Sun, Sep 29	SJB	@	QUE	SJB3,QUE2	RECAP
Tue, Oct 1	SJB	@	ONT	SJB0,ONT7	RECAP
Thu, Oct 3	ONT	@	SJB	ONT5,SJB4	RECAP
Sat, Oct 5	SJB	@	LVP	SJB2,LVP3 (SO)	RECAP
Sun, Oct 6	CHA	@	SJB	CHA7,SJB6	RECAP
Wed, Oct 9	CGY	@	SJB	CGY3,SJB4 (OT)	RECAP
Fri, Oct 11	SJB	@	CGY	SJB2,CGY0	RECAP
Sun, Oct 13	PRO	@	SJB	PRO3,SJB4	RECAP
Mon, Oct 14	SJB	@	IOW	SJB7,IOW4	RECAP
Wed, Oct 16	SJB	@	TEX	SJB0,TEX3	RECAP
Fri, Oct 18	RCK	@	SJB	RCK5,SJB1	RECAP
Mon, Oct 21	SJB	@	SYR	SJB3,SYR4 (SO)	RECAP
Tue, Oct 22	TEX	@	SJB	TEX6,SJB4	RECAP
Thu, Oct 24	SJB	@	ABB	SJB2,ABB3 (SO)	RECAP
Sat, Oct 26	BAK	@	SJB	BAK4,SJB3 (OT)	RECAP
Mon, Oct 28	SJB	@	SPR	SJB4,SPR2	RECAP
Trade Deadline --- Trades can�t be done after this day is simulated!
Wed, Oct 30	SPR	@	SJB	SPR3,SJB4	RECAP
Fri, Nov 1	BEL	@	SJB	BEL1,SJB3	RECAP
Sun, Nov 3	SJB	@	CGY	SJB3,CGY5	RECAP
Tue, Nov 5	MAN	@	SJB	MAN2,SJB3	RECAP
Thu, Nov 7	SJB	@	MAN	SJB3,MAN2	RECAP
Fri, Nov 8	SJB	@	HEN	SJB1,HEN3	RECAP
Sun, Nov 10	SJB	@	UTA	SJB9,UTA3	RECAP
Tue, Nov 12	COL	@	SJB	COL1,SJB2 (OT)	RECAP
Thu, Nov 14	MIL	@	SJB	MIL3,SJB0	RECAP
Mon, Nov 18	ABB	@	SJB	ABB4,SJB2	RECAP
Tue, Nov 19	SJB	@	SDG	SJB0,SDG3	RECAP
Thu, Nov 21	SJB	@	SDG
Sat, Nov 23	HEN	@	SJB
Mon, Nov 25	SJB	@	HEN
Wed, Nov 27	CVF	@	SJB
Sat, Nov 30	SJB	@	UTI

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
$2,889,191	$0	$0	$75,000,000

Arena	About us
	Name	SAP Center
	City	San Jose
	Capacity	9000
	Season Ticket Holders	30%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	6000	3000
Ticket Price	$25	$12	$	$	$
Attendance	189828	94452
Attendance PCT	81.12%	80.73%	0.00%	0.00%	0.00%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
2	7289 - 80.99%	$180,896	$7,054,949	9000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
$2,889,191	$2,902,886	$0	$0

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
$2,750,622	$0	$2,750,622	$0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
$361,792	11	$17,835	$196,185

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
$196,185	$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

MacKenze Stewart is out for 1 week because of a Left Foot Injury.

Game Center

Canucks31-38-9, 71pts

42Final

Barracuda46-22-9, 101pts

03Final

Gulls27-44-6, 60pts

Barracuda46-22-9, 101pts

Wed, Nov 20

Gulls27-44-6, 60pts

IceHogs40-32-6, 86pts

Wed, Jun 26

Barracuda46-22-9, 101pts

Fri, Jun 28

Reign39-29-9, 87pts

TRANSACTIONS

Team Info


	Head Coach
	Division	PACIFIC DIVISION
	City	San Jose
	Stadium Capacity	9,000

Barracuda Affiliation


	General Manager	Graham Burns
	Head Coach
	Stadium	SAP Center
	Capacity	18,500

Team Leaders

GOALS Andy Andreoff Barracuda	25 GOALS
POINTS Linden Vey Barracuda	66 POINTS
WINS Keith Petruzzelli Barracuda	37 WINS
Expanded Player Leaderboard

Team Stats

Goals For 246 3.19 GFG	Goals Against 211 2.74 GAA
Power Play Percentage 17.5% 37 GF	Penalty Kill Percentage 86.2% 30 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain