LAAHS - Seattle Thunderbirds

Penguins
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance

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	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	TA	SP
1	Marcus Foligno		X			100.00	89	80	74	73	83	57	96	61	40	64	58	60	25	69	69	64	80	63		0
2	Steve Bernier			X		100.00	81	80	84	67	80	63	65	61	50	50	62	75	59	75	79	65	78	63		0
3	Matt Read (C)	X	X	X		100.00	76	43	96	83	66	58	75	60	36	50	57	76	57	70	71	64	78	63		0
4	Andrew Miller	X		X		100.00	72	65	88	67	65	69	70	69	50	71	63	64	60	44	44	66	66	62		0
5	T.J. Tynan	X		X		100.00	66	58	86	62	58	83	88	64	80	68	57	60	54	44	44	63	76	61		0
6	Rourke Chartier (R)	X				100.00	75	66	97	70	68	70	80	66	73	61	61	61	57	44	44	64	78	61		0
7	Peter Cehlarik		X			100.00	77	75	81	67	75	66	67	62	50	58	62	65	59	45	45	64	72	60		0
8	Emil Pettersson	X				100.00	73	67	86	63	67	74	77	62	78	62	57	63	54	44	44	63	81	60		0
9	Shane Prince	X	X			100.00	69	87	78	76	71	61	56	62	41	57	58	57	25	59	60	60	71	59		0
10	Landon Ferraro	X		X		100.00	73	68	85	65	68	57	57	59	74	53	59	65	56	54	55	61	68	58	X	0
11	Trevor van Riemsdyk				X	100.00	61	41	91	80	70	72	86	59	25	51	48	70	25	64	65	61	78	65		0
12	Rob O'Gara				X	100.00	79	45	93	74	78	67	83	55	25	50	47	79	25	47	47	62	65	65		0
13	Matt Tennyson				X	100.00	73	44	84	70	76	75	76	73	25	40	47	69	25	58	58	59	78	64		0
14	Yannick Weber			X	X	100.00	75	43	89	77	72	59	77	55	25	48	48	62	75	68	69	58	77	62		0
15	Joey LaLeggia				X	100.00	71	64	86	68	64	77	81	61	50	60	58	62	55	44	44	63	79	61		0
16	Jacob MacDonald (R)				X	100.00	77	73	86	61	73	66	68	62	25	52	58	65	55	44	44	63	76	60		0
17	Andrew Campbell				X	100.00	78	78	78	68	78	75	83	45	25	33	40	62	38	47	47	53	67	59		0
18	Vincent LoVerde				X	100.00	78	73	89	60	73	72	78	50	25	37	49	63	47	44	44	57	74	58		0
Scratches
1	Stefan Noesen		X	X		100.00	81	59	85	74	77	65	75	65	38	66	68	69	25	58	58	71	69	64		0
2	Reid Boucher		X	X		100.00	69	42	99	83	68	61	72	70	34	60	68	68	75	59	59	69	70	64		0
3	Brett Sutter	X	X			100.00	73	73	74	63	73	55	55	59	74	56	58	62	55	44	44	60	20	56		0
4	Hampus Gustafsson (R)	X	X			100.00	83	77	97	62	77	55	57	51	64	47	50	65	48	44	44	57	20	54		0
5	Jacob Larsson				X	100.00	70	65	80	65	65	70	80	66	69	49	56	55	39	44	44	54	39	57		0
6	Jamie McBain				X	100.00	73	68	85	65	68	66	70	51	25	47	41	60	39	44	44	54	20	56		0

	TEAM AVERAGE					100.00	75	64	86	69	71	66	74	60	46	54	55	65	47	52	53	61	66	61

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	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP
1	Jack Campbell	100.00	61	71	89	79	61	64	52	63	57	56	30	44	44	60	77	61	0
2	Matej Machovsky (R)	100.00	57	47	59	74	60	57	60	64	60	60	30	44	44	58	40	58	0
Scratches
1	Jake Paterson (R)	100.00	51	56	70	66	49	51	50	56	49	49	30	44	44	51	20	52	0

	TEAM AVERAGE	100.00	56	58	73	73	57	57	54	61	55	55	30	44	44	56	46	57

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
David Bell	59	62	37	48	47	35	48	CAN	41	1	60,000$

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	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKM	GW	GT	FO%	FOT	GA	TA	P/20	FW	FL	FT	S1	S3
1	Rourke Chartier	Seattle Thunderbirds (PIT)	C	5	2	3	5	2	0	0	4	6	26	7	14	7.69%	4	77	15.46	0	0	0	0	1	0	1	0	57.89%	38	1	1	1.29	0	0	0	1	0
2	Matt Read	Seattle Thunderbirds (PIT)	C/LW/RW	5	2	3	5	-5	0	0	6	12	26	8	11	7.69%	5	108	21.68	1	1	2	1	6	9	0	0	39.24%	158	4	4	0.92	0	0	0	0	0
3	Stefan Noesen	Seattle Thunderbirds (PIT)	LW/RW	4	3	1	4	-2	2	0	9	7	24	5	18	12.50%	5	102	25.73	1	1	2	1	5	6	0	0	40.00%	20	12	1	0.78	0	0	0	0	1
4	Trevor van Riemsdyk	Seattle Thunderbirds (PIT)	D	5	0	3	3	-4	0	0	3	7	12	4	0	0.00%	6	125	25.15	0	0	0	1	7	10	0	0	0.00%	0	3	6	0.48	0	0	0	0	0
5	Peter Cehlarik	Seattle Thunderbirds (PIT)	LW	5	2	1	3	0	0	0	4	10	16	10	11	12.50%	5	82	16.48	0	0	0	0	0	5	0	1	40.00%	5	2	1	0.73	0	0	0	0	0
6	Landon Ferraro	Seattle Thunderbirds (PIT)	C/RW	5	2	1	3	2	0	0	4	2	9	6	7	22.22%	5	69	13.93	0	0	0	0	0	0	0	0	0.00%	1	2	2	0.86	0	0	0	0	0
7	T.J. Tynan	Seattle Thunderbirds (PIT)	C/RW	5	0	2	2	0	2	0	6	9	14	0	6	0.00%	1	96	19.21	0	0	0	0	5	2	0	0	20.00%	5	2	2	0.42	0	0	0	0	0
8	Marcus Foligno	Seattle Thunderbirds (PIT)	LW	5	0	2	2	-1	13	5	10	4	10	3	10	0.00%	6	92	18.50	0	0	0	1	5	2	0	0	50.00%	2	1	2	0.43	0	0	1	0	0
9	Shane Prince	Seattle Thunderbirds (PIT)	C/LW	5	1	1	2	2	2	0	2	4	9	0	3	11.11%	1	41	8.39	0	0	0	0	0	1	0	0	100.00%	1	1	0	0.95	0	0	0	0	0
10	Emil Pettersson	Seattle Thunderbirds (PIT)	C	5	0	1	1	1	5	5	1	3	2	1	4	0.00%	1	38	7.79	0	0	0	0	0	1	0	0	72.73%	11	0	1	0.51	1	0	0	0	0
11	Steve Bernier	Seattle Thunderbirds (PIT)	RW	5	0	1	1	-5	2	0	7	6	14	3	3	0.00%	3	103	20.71	0	1	1	0	6	4	0	0	57.14%	7	3	3	0.19	0	0	0	0	0
12	Andrew Campbell	Seattle Thunderbirds (PIT)	D	5	0	1	1	-1	2	0	1	2	0	0	0	0.00%	0	32	6.55	0	0	0	0	0	0	0	0	0.00%	0	0	1	0.61	0	0	0	0	0
13	Andrew Miller	Seattle Thunderbirds (PIT)	C/RW	5	1	0	1	0	10	10	4	9	21	5	7	4.76%	1	88	17.71	0	0	0	0	4	0	0	0	56.45%	62	3	1	0.23	1	0	1	0	0
14	Joey LaLeggia	Seattle Thunderbirds (PIT)	D	5	0	1	1	2	5	5	1	2	3	3	0	0.00%	3	55	11.04	0	0	0	0	0	0	0	0	0.00%	0	1	0	0.36	0	0	1	0	0
15	Matt Tennyson	Seattle Thunderbirds (PIT)	D	5	0	1	1	1	2	0	3	4	3	0	2	0.00%	4	93	18.77	0	0	0	0	5	6	0	0	0.00%	0	1	3	0.21	0	0	0	0	0
16	Rob O'Gara	Seattle Thunderbirds (PIT)	D	5	0	0	0	-4	0	0	5	7	6	2	3	0.00%	5	125	25.11	0	0	0	0	7	10	0	0	0.00%	0	1	8	0.00	0	0	0	0	0
17	Vincent LoVerde	Seattle Thunderbirds (PIT)	D	5	0	0	0	-1	7	5	1	0	0	0	0	0.00%	0	31	6.20	0	0	0	0	0	0	0	0	0.00%	0	0	0	0.00	0	1	0	0	0
18	Yannick Weber	Seattle Thunderbirds (PIT)	RW/D	5	0	0	0	1	0	0	2	3	5	0	1	0.00%	4	94	18.98	0	0	0	0	5	6	0	0	0.00%	0	1	3	0.00	0	0	0	0	0
19	Jacob MacDonald	Seattle Thunderbirds (PIT)	D	5	0	0	0	2	0	0	2	0	4	1	2	0.00%	4	55	11.12	0	0	0	0	0	0	0	0	0.00%	0	0	1	0.00	0	0	0	0	0
Team Total or Average				94	13	22	35	-10	52	30	75	97	204	58	102	6.37%	63	1516	16.14	2	3	5	4	61	68	1	1	46.45%	310	38	40	0.46	2	1	3	1	1

Show or Hide Column

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Jack Campbell	Seattle Thunderbirds (PIT)	5	1	3	1	0.915	3.34	305	0	0	17	200	110	0	0	0.000	0	5	0	0	1	0
Team Total or Average			5	1	3	1	0.915	3.34	305	0	0	17	200	110	0	0	0.000	0	5	0	0	1	0

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	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
Andrew Campbell	Seattle Thunderbirds (PIT)	D	30	1988-02-04	No	205 Lbs	6 ft4	No	No	No	1	UFA	Pro & Farm	650,000$	0$	0$	No	Link
Andrew Miller	Seattle Thunderbirds (PIT)	C/RW	29	1988-09-17	No	181 Lbs	5 ft10	Yes	No	No	1	UFA	Pro & Farm	700,000$	0$	0$	No	Link
Brett Sutter	Seattle Thunderbirds (PIT)	C/LW	31	1987-06-01	No	200 Lbs	6 ft0	Yes	No	No	1	UFA	Pro & Farm	660,000$	0$	0$	No	Link
Emil Pettersson	Seattle Thunderbirds (PIT)	C	24	1994-01-14	No	164 Lbs	6 ft2	No	No	No	1	ELC	Pro & Farm	700,000$	0$	0$	No	Link
Hampus Gustafsson	Seattle Thunderbirds (PIT)	C/LW	24	1993-10-26	Yes	205 Lbs	6 ft4	No	No	No	2	ELC	Pro & Farm	925,000$	0$	0$	No	Link
Jack Campbell	Seattle Thunderbirds (PIT)	G	26	1992-01-08	No	200 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	675,000$	0$	0$	No	Link
Jacob Larsson	Seattle Thunderbirds (PIT)	D	21	1997-04-29	No	191 Lbs	6 ft2	No	No	No	1	ELC	Pro & Farm	400,000$	0$	0$	No	Link
Jacob MacDonald	Seattle Thunderbirds (PIT)	D	25	1993-02-26	Yes	201 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Jake Paterson	Seattle Thunderbirds (PIT)	G	24	1994-05-03	Yes	176 Lbs	6 ft1	No	No	No	1	ELC	Pro & Farm	500,000$	0$	0$	No	Link
Jamie McBain	Seattle Thunderbirds (PIT)	D	30	1988-02-24	No	180 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	715,000$	0$	0$	No	Link
Joey LaLeggia	Seattle Thunderbirds (PIT)	D	26	1992-06-24	No	182 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	675,000$	0$	0$	No	Link
Landon Ferraro	Seattle Thunderbirds (PIT)	C/RW	26	1991-08-07	No	186 Lbs	6 ft0	No	Yes	No	1	RFA	Pro & Farm	700,000$	0$	0$	No	Link
Marcus Foligno	Seattle Thunderbirds (PIT)	LW	26	1991-08-10	No	228 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	2,875,000$	0$	0$	No	Link
Matej Machovsky	Seattle Thunderbirds (PIT)	G	24	1993-07-25	Yes	191 Lbs	6 ft2	No	No	No	1	ELC	Pro & Farm	700,000$	0$	0$	No	Link
Matt Read	Seattle Thunderbirds (PIT)	C/LW/RW	32	1986-06-13	No	185 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	650,000$	0$	0$	No	Link
Matt Tennyson	Seattle Thunderbirds (PIT)	D	28	1990-04-23	No	205 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	650,000$	0$	0$	No	Link
Peter Cehlarik	Seattle Thunderbirds (PIT)	LW	23	1995-05-12	No	202 Lbs	6 ft2	No	No	No	1	ELC	Pro & Farm	742,500$	0$	0$	No	Link
Reid Boucher	Seattle Thunderbirds (PIT)	LW/RW	24	1993-09-08	No	195 Lbs	5 ft10	No	No	No	1	ELC	Pro & Farm	725,000$	0$	0$	No	Link
Rob O'Gara	Seattle Thunderbirds (PIT)	D	24	1993-07-06	No	207 Lbs	6 ft4	No	No	No	1	ELC	Pro & Farm	874,125$	0$	0$	No	Link
Rourke Chartier	Seattle Thunderbirds (PIT)	C	22	1996-04-02	Yes	190 Lbs	5 ft11	No	No	No	2	ELC	Pro & Farm	697,500$	0$	0$	No	Link
Shane Prince	Seattle Thunderbirds (PIT)	C/LW	25	1992-11-16	No	185 Lbs	5 ft11	No	No	No	1	RFA	Pro & Farm	550,000$	0$	0$	No	Link
Stefan Noesen	Seattle Thunderbirds (PIT)	LW/RW	25	1993-02-12	No	205 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	1,725,000$	0$	0$	No	Link
Steve Bernier	Seattle Thunderbirds (PIT)	RW	33	1985-03-31	No	220 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	650,000$	0$	0$	No	Link
T.J. Tynan	Seattle Thunderbirds (PIT)	C/RW	26	1992-02-24	No	165 Lbs	5 ft8	No	No	No	1	RFA	Pro & Farm	650,000$	0$	0$	No	Link
Trevor van Riemsdyk	Seattle Thunderbirds (PIT)	D	26	1991-07-24	No	188 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	2,300,000$	0$	0$	No	Link
Vincent LoVerde	Seattle Thunderbirds (PIT)	D	29	1989-04-13	No	205 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	700,000$	0$	0$	No	Link
Yannick Weber	Seattle Thunderbirds (PIT)	RW/D	29	1988-09-23	No	200 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	675,000$	0$	0$	No	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
27	26.37	194 Lbs	6 ft1	1.30	850,523$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Matt Read	Steve Bernier	40	1	2	2
2	Marcus Foligno	Andrew Miller	T.J. Tynan	30	1	2	2
3	Peter Cehlarik	Rourke Chartier	Landon Ferraro	20	1	2	2
4	Shane Prince	Emil Pettersson		10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Rob O'Gara	Trevor van Riemsdyk	40	1	2	2
2	Matt Tennyson	Yannick Weber	30	1	2	2
3	Joey LaLeggia	Jacob MacDonald	20	1	2	2
4	Andrew Campbell	Vincent LoVerde	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Matt Read	Steve Bernier	60	1	2	2
2	Marcus Foligno	Andrew Miller	T.J. Tynan	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Rob O'Gara	Trevor van Riemsdyk	60	1	2	2
2	Matt Tennyson	Yannick Weber	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1		Matt Read	60	1	2	2
2	Steve Bernier	Marcus Foligno	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Rob O'Gara	Trevor van Riemsdyk	60	1	2	2
2	Matt Tennyson	Yannick Weber	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	Rob O'Gara	Trevor van Riemsdyk	60	1	2	2
2	Matt Read	40	1	2	2	Matt Tennyson	Yannick Weber	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1		Matt Read	60	1	2	2
2	Steve Bernier	Marcus Foligno	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Rob O'Gara	Trevor van Riemsdyk	60	1	2	2
2	Matt Tennyson	Yannick Weber	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
	Matt Read	Steve Bernier	Rob O'Gara	Trevor van Riemsdyk

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
	Matt Read	Steve Bernier	Rob O'Gara	Trevor van Riemsdyk

Extra Forwards
Normal	PowerPlay	Penalty Kill
Rourke Chartier, Emil Pettersson, Peter Cehlarik	Rourke Chartier, Emil Pettersson	Peter Cehlarik

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Joey LaLeggia, Jacob MacDonald, Andrew Campbell	Joey LaLeggia	Jacob MacDonald, Andrew Campbell

Penalty Shots
, Matt Read, Steve Bernier, Marcus Foligno, Yannick Weber

Goalie
#1 : Jack Campbell, #2 : Matej Machovsky

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

Custom OT Lines Defensemen
, , , ,

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

	Overall												Home											Visitor
#	VS Team	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	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
	Total	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	0.200	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48
2	Worcester Sharks	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	0.200	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48
	_Since Last GM Reset	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	0.200	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48
	_Vs Conference	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	0.200	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
5	2	L3	13	22	35	204	200	63	52	75	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	13	17

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	9	10

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	4	7

Last 10 Games
W	L	OTW	OTL	SOW	SOL
1	3	0	1	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
8	2	25.00%	11	4	63.64%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
52	82	67	3	2	7	4	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
50	116	43.10%	54	114	47.37%	40	80	50.00%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
104	57	104	47	98	48

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	Link
1 - 2018-10-05	4	Worcester Sharks	2	Seattle Thunderbirds	4	W		BoxScore
2 - 2018-10-06	12	Worcester Sharks	4	Seattle Thunderbirds	3	L	X	BoxScore
3 - 2018-10-07	20	Seattle Thunderbirds	2	Worcester Sharks	4	L		BoxScore
4 - 2018-10-08	28	Seattle Thunderbirds	2	Worcester Sharks	3	L		BoxScore
5 - 2018-10-09	36	Worcester Sharks	4	Seattle Thunderbirds	2	L		BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	4,962	2,573
Attendance PCT	82.70%	85.77%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
38	2512 - 83.72%	105,425$	316,274$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	2,296,412$	2,171,412$	0$

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

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	2	0$	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
2018	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48
Total Playoff	5	1	4	0	0	0	0	0	13	17	-4	3	1	2	0	0	0	0	0	9	10	-1	2	0	2	0	0	0	0	0	4	7	-3	2	13	22	35	0	0	2	7	4	0	204	52	82	67	3	200	63	52	75	8	2	25.00%	11	4	63.64%	0	50	116	43.10%	54	114	47.37%	40	80	50.00%	104	57	104	47	98	48