Profi League

Capitals
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	SP
1	Chris Tierney (R)	X				100.00	60	41	89	84	76	76	87	64	87	45	43	67	50	58	58	0	56	65	0
2	Brett Connolly		X	X		100.00	76	45	89	78	68	76	75	69	61	45	45	60	50	63	63	0	56	64	0
3	Mike Brown (A)		X	X		100.00	59	99	78	74	74	81	67	65	57	39	39	63	50	69	70	0	55	62	0
4	Mike Santorelli (A)	X	X	X		100.00	62	41	68	78	61	54	85	66	61	43	44	61	61	69	70	0	53	61	0
5	Jack Skille		X	X		100.00	72	55	68	76	59	51	69	65	58	40	43	62	50	66	67	0	53	59	0
6	Frank Vatrano (R)	X	X	X		100.00	70	45	67	82	57	57	67	64	58	39	46	59	50	47	47	0	56	58	0
7	Andrew Copp (R)	X				100.00	69	43	68	76	53	50	61	62	77	40	42	65	50	54	54	0	56	57	0
8	Joonas Kemppainen	X				100.00	63	43	68	73	59	60	60	61	79	40	40	70	50	48	48	0	53	57	0
9	Jason Dickinson (R)	X	X			100.00	75	69	75	68	53	60	61	62	74	38	40	60	56	44	44	0	56	56	0
10	Max McCormick	X	X			100.00	74	99	58	59	54	53	66	63	72	40	41	58	50	45	45	0	54	55	0
11	Pontus Aberg (R)		X	X		100.00	72	67	75	67	52	70	66	60	65	32	39	58	56	44	44	0	56	55	0
12	Yannick Veilleux (R)		X			100.00	62	76	63	63	58	68	66	56	70	32	33	58	50	44	44	0	56	53	0
13	Jeff Schultz (C)				X	100.00	77	88	99	75	96	80	79	50	25	36	33	64	50	80	71	0	59	66	0
14	Tyler Wotherspoon (R)				X	100.00	69	45	92	71	76	67	79	69	25	41	37	73	50	46	47	0	56	62	0
15	Nathan Paetsch				X	100.00	80	72	95	62	80	87	88	51	25	36	32	62	50	61	62	0	50	62	0
16	Julian Melchiori				X	100.00	71	45	96	71	79	63	88	53	25	37	37	70	50	49	45	0	56	60	0
17	Dillon Simpson				X	100.00	60	71	68	68	59	68	69	63	25	34	30	61	50	48	48	0	57	55	0
18	Danny Syvret				X	100.00	61	74	68	62	60	63	67	63	25	30	32	63	50	50	51	0	58	54	0
Scratches
1	Joel Lowry (R)		X			100.00	57	68	59	64	52	50	59	54	64	29	32	53	50	44	44	0	46	49	0
2	Connor Crisp (R)		X			100.00	56	83	56	62	59	50	60	52	65	25	27	50	50	44	44	0	46	48	0
3	Cody Beach			X		100.00	53	75	56	63	56	53	60	53	65	27	31	47	50	44	44	0	46	48	0
4	Dylan Labbe (R)				X	100.00	56	72	63	68	59	60	64	53	25	24	34	54	50	44	44	0	52	51	0
5	Garrett Noonan				X	100.00	61	74	68	64	60	60	64	53	25	24	26	60	50	47	47	0	46	51	0

	TEAM AVERAGE					100.00	66	65	73	70	63	63	70	60	53	35	37	61	51	53	52	0	54	57

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	Mike McKenna	100.00	75	67	66	78	71	70	68	71	71	66	70	69	67	0	53	69	0
2	Anton Forsberg	100.00	67	79	67	75	70	69	70	70	70	66	45	69	66	0	56	67	0
Scratches
1	Cedrick Desjardins	100.00	59	51	64	66	64	63	62	66	66	63	62	49	55	0	46	61	0

	TEAM AVERAGE	100.00	67	66	66	73	68	67	67	69	69	65	59	62	63	0	52	66

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Rob Zettler	56	62	65	66	60	60	74	CAN	48	5	100,000$

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	SHT	OSB	OSM	SHT%	SB	MP	PPG	PPA	PPP	PKG	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS
1	Frank Vatrano	Bears (WSH)		C/LW/RW	4	7	2	9	5	0	0	7	14	9	17	50.00%	2	15.:.59	0	1	1	0	0	0	1	0.00%	3	18	0	0	1	2.81	0	0
2	Andrew Copp	Bears (WSH)		C	4	1	8	9	5	0	0	9	10	9	6	10.00%	2	15.:.46	0	1	1	0	0	0	1	65.96%	47	5	3	0	0	2.85	0	0
3	Brett Connolly	Bears (WSH)		LW/RW	4	2	4	6	6	0	0	12	11	1	12	18.18%	3	19.:.07	0	0	0	0	0	1	1	11.11%	9	14	2	0	0	1.57	0	0
4	Chris Tierney	Bears (WSH)		C	4	1	3	4	6	0	0	4	9	7	5	11.11%	2	20.:.03	0	0	0	0	5	0	0	73.08%	78	10	2	0	0	1.00	0	0
5	Mike Santorelli	Bears (WSH)		C/LW/RW	4	3	1	4	6	6	0	6	14	5	6	21.43%	1	18.:.54	0	0	0	0	0	2	0	0.00%	2	10	2	0	0	1.06	0	0
6	Mike Brown	Bears (WSH)		LW/RW	4	0	3	3	5	10	10	6	9	1	6	0.00%	1	15.:.15	0	0	0	0	5	0	0	0.00%	2	6	1	0	0	0.98	0	0
7	Tyler Wotherspoon	Bears (WSH)		D	4	0	3	3	6	0	0	1	11	8	8	0.00%	8	25.:.59	0	0	0	0	4	0	0	0.00%	0	0	10	0	0	0.58	0	0
8	Jack Skille	Bears (WSH)		LW/RW	4	3	0	3	1	0	0	8	15	3	9	20.00%	0	15.:.50	1	0	1	0	5	1	0	50.00%	2	11	1	0	0	0.95	0	0
9	Joonas Kemppainen	Bears (WSH)		C	4	0	2	2	1	2	0	6	9	1	6	0.00%	2	13.:.52	0	0	0	0	4	0	0	76.92%	39	3	5	0	0	0.72	0	0
10	Nathan Paetsch	Bears (WSH)		D	2	0	1	1	1	0	0	3	2	0	0	0.00%	4	20.:.38	0	0	0	0	1	0	0	0.00%	0	0	1	0	0	0.48	0	0
11	Jason Dickinson	Bears (WSH)		C/LW	4	1	0	1	1	0	0	6	4	2	8	25.00%	1	12.:.17	0	0	0	0	0	0	0	100.00%	1	3	0	0	0	0.41	0	0
12	Danny Syvret	Bears (WSH)		D	4	0	1	1	3	20	20	4	5	3	1	0.00%	5	16.:.33	0	0	0	0	4	0	0	0.00%	0	1	2	0	0	0.30	0	0
13	Max McCormick	Bears (WSH)		C/LW	4	1	0	1	0	20	20	6	11	1	6	9.09%	0	09.:.42	0	0	0	0	0	0	0	57.14%	21	13	0	0	0	0.51	0	0
14	Jeff Schultz	Bears (WSH)		D	4	0	1	1	7	10	10	4	2	8	5	0.00%	9	21.:.29	0	0	0	0	4	0	0	0.00%	0	0	9	0	0	0.23	0	0
15	Julian Melchiori	Bears (WSH)		D	4	0	1	1	4	0	0	3	6	2	3	0.00%	2	22.:.42	0	0	0	0	5	0	0	0.00%	0	1	13	0	0	0.22	0	0
16	Dylan Labbe	Bears (WSH)		D	2	0	0	0	2	7	5	3	0	0	0	0.00%	1	15.:.21	0	0	0	0	0	0	0	0.00%	0	0	0	0	0	0.00	0	0
17	Dillon Simpson	Bears (WSH)		D	4	0	0	0	1	5	5	3	6	0	3	0.00%	3	15.:.19	0	0	0	0	0	0	0	0.00%	0	0	3	0	0	0.00	0	0
18	Yannick Veilleux	Bears (WSH)		LW	4	0	0	0	0	0	0	4	3	0	3	0.00%	1	10.:.12	0	0	0	0	0	0	0	100.00%	1	2	1	0	0	0.00	0	0
19	Pontus Aberg	Bears (WSH)		LW/RW	4	0	0	0	0	0	0	3	5	3	4	0.00%	1	10.:.12	0	0	0	0	0	0	0	100.00%	2	7	1	0	0	0.00	0	0
Team Total or Average		72	19	30	49	60	80	70	98	96	146	63	108	13.01%	48	1189	16.52	1	2	3	10	64	0	3	42	4	3	65.70%	207	104	56	0	1	0.82	0	0	4	3	7	3	3	3

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	PS %	PSA	ST	BG	S1	S2	S3
1	Mike McKenna	Bears (WSH)	2	2	0	0	95.7%	1.00	120	0	0	2	46	30	0	0.0%	0	2	2	0	0	0
2	Anton Forsberg	Bears (WSH)	2	2	0	0	92.7%	2.00	120	2	0	4	55	38	0	0.0%	0	2	2	1	0	0
Team Total or Average	4	4	0	0	0.941	1.50	240	2	0	6	101	68	0	0	0.000	4	4	1	0	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	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Force Waivers	Contract	Type	Current Salary	Salary Remaining	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Link
Andrew Copp	C	22	08.07.1994 23:54:15	Yes	188 Lbs	6 ft1	No	No	3	Pro & Farm	1,100,000$	0$	1,100,000$	1,100,000$								Link
Anton Forsberg	G	23	27.11.1992	No	176 Lbs	6 ft2	No	No	1	Pro & Farm	1,100,000$	0$										Link
Brett Connolly	LW/RW	24	02.05.1992 5:34:25	No	181 Lbs	6 ft2	No	No	1	Pro & Farm	1,300,000$	0$										Link
Cedrick Desjardins	G	31	30.09.1985	No	192 Lbs	6 ft0	No	No	1	Pro & Farm	800,000$	0$
Chris Tierney	C	22	01.07.1994 1:04:35	Yes	195 Lbs	6 ft0	No	No	2	Pro & Farm	1,300,000$	0$	1,300,000$									Link
Cody Beach	RW	24	08.08.1992 5:02:22	No	190 Lbs	6 ft5	No	No	7	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$				Link
Connor Crisp	LW	22	08.04.1994	Yes	226 Lbs	6 ft3	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Link
Danny Syvret	D	31	13.06.1985	No	205 Lbs	6 ft0	No	No	1	Pro & Farm	800,000$	0$										Link
Dillon Simpson	D	23	10.02.1993	No	194 Lbs	6 ft1	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Link
Dylan Labbe	D	21	08.01.1995	Yes	194 Lbs	6 ft2	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Link
Frank Vatrano	C/LW/RW	22	14.03.1994 23:11:12	Yes	215 Lbs	5 ft10	No	No	2	Pro & Farm	1,200,000$	0$	1,200,000$									Link
Garrett Noonan	D	25	28.01.1991	No	205 Lbs	6 ft0	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Link
Jack Skille	LW/RW	29	19.05.1987	No	216 Lbs	6 ft1	No	No	2	Pro & Farm	1,200,000$	0$	1,200,000$									Link
Jason Dickinson	C/LW	21	03.07.1995	Yes	185 Lbs	6 ft1	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Link
Jeff Schultz	D	30	25.02.1986	No	230 Lbs	6 ft6	No	No	1	Pro & Farm	1,700,000$	0$										Link
Joel Lowry	LW	24	14.11.1991	Yes	180 Lbs	6 ft1	No	No	10	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	Link
Joonas Kemppainen	C	28	07.04.1988	No	213 Lbs	6 ft2	No	No	1	Pro & Farm	1,300,000$	0$										Link
Julian Melchiori	D	24	06.12.1991 5:06:52	No	214 Lbs	6 ft5	No	No	1	Pro & Farm	1,000,000$	0$										Link
Max McCormick	C/LW	24	01.05.1992	No	185 Lbs	5 ft11	No	No	1	Pro & Farm	1,000,000$	0$										Link
Mike Brown	LW/RW	31	24.06.1985	No	205 Lbs	5 ft11	No	No	1	Pro & Farm	1,200,000$	0$										Link
Mike McKenna	G	33	11.10.1983	No	190 Lbs	6 ft2	No	No	2	Pro & Farm	1,100,000$	0$	1,100,000$									Link
Mike Santorelli	C/LW/RW	30	14.12.1985	No	189 Lbs	6 ft0	No	No	1	Pro & Farm	1,200,000$	0$										Link
Nathan Paetsch	D	33	30.03.1983	No	195 Lbs	6 ft1	No	No	1	Pro & Farm	700,000$	0$										Link
Pontus Aberg	LW/RW	23	22.09.1993	Yes	189 Lbs	5 ft11	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Link
Tyler Wotherspoon	D	23	12.03.1993 2:02:58	Yes	210 Lbs	6 ft2	No	No	1	Pro & Farm	700,000$	0$										Link
Yannick Veilleux	LW	23	22.02.1993 5:08:43	Yes	206 Lbs	6 ft2	No	No	9	Farm Only	100,000$	0$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$	100,000$		Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
26	25.62	199 Lbs	6 ft1	4.0384615384615	753,846$

5 vs 5 Forward
Line #	Center	Left Wing	Right Wing	Time %	PHY	DF	OF
1	Chris Tierney	Mike Santorelli	Brett Connolly	40	1	1	3
2	Andrew Copp	Mike Brown	Frank Vatrano	31	1	2	2
3	Joonas Kemppainen	Jason Dickinson	Jack Skille	20	1	2	2
4	Max McCormick	Yannick Veilleux	Pontus Aberg	9	1	3	1

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Jeff Schultz	Tyler Wotherspoon	43	1	2	2
2	Julian Melchiori	Nathan Paetsch	36	1	2	2
3	Dillon Simpson	Danny Syvret	21	1	2	2
4	Jeff Schultz	Tyler Wotherspoon	0	1	2	2

Power Play Forward
Line #	Center	Left Wing	Right Wing	Time %	PHY	DF	OF
1	Chris Tierney	Mike Santorelli	Brett Connolly	60	1	2	2
2	Andrew Copp	Jack Skille	Frank Vatrano	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Tyler Wotherspoon	Julian Melchiori	60	1	2	2
2	Jeff Schultz	Nathan Paetsch	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Joonas Kemppainen	Mike Brown	50	1	2	2
2	Chris Tierney	Jack Skille	50	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Jeff Schultz	Tyler Wotherspoon	50	1	2	2
2	Nathan Paetsch	Julian Melchiori	50	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Joonas Kemppainen	60	1	2	2	Jeff Schultz	Tyler Wotherspoon	60	1	2	2
2	Chris Tierney	40	1	2	2	Nathan Paetsch	Julian Melchiori	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Chris Tierney	Mike Santorelli	50	1	2	2
2	Joonas Kemppainen	Mike Brown	50	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Jeff Schultz	Tyler Wotherspoon	50	1	2	2
2	Nathan Paetsch	Julian Melchiori	50	1	2	2

Last Minutes Offensive
Center	Left Wing	Right Wing	Defense	Defense
Chris Tierney	Mike Santorelli	Brett Connolly	Tyler Wotherspoon	Julian Melchiori

Last Minutes Defensive
Center	Left Wing	Right Wing	Defense	Defense
Chris Tierney	Mike Santorelli	Brett Connolly	Tyler Wotherspoon	Julian Melchiori

Extra Forwards
Normal	PowerPlay	Penalty Kill
Brett Connolly, Mike Santorelli, Mike Brown	Frank Vatrano, Brett Connolly	Joonas Kemppainen

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Tyler Wotherspoon, Julian Melchiori, Danny Syvret	Tyler Wotherspoon	Tyler Wotherspoon, Julian Melchiori

Penalty Shots
Mike Santorelli, Jason Dickinson, Pontus Aberg, Brett Connolly, Frank Vatrano

Goalie
#1 : Anton Forsberg, #2 : Mike McKenna

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

#	VS Team	GP	W	GF	GA	Diff	P	PCT	G	A	TP	GP1	GP2	GP3	SHF	SH1	SP2	SP3	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK%	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
1	Senators	1	1	2	1	1	2	1.000	2	2	4	5	6	8	42	55	40	51	22	15	17	38	2	0	0.00%	1	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
2	Wolves	1	1	6	3	3	2	1.000	6	10	16	5	6	8	30	55	40	51	33	19	4	19	2	1	50.00%	2	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
3	IceHogs	1	1	5	1	4	2	1.000	5	8	13	5	6	8	38	55	40	51	22	11	12	23	1	0	0.00%	1	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
4	Monarchs	1	1	6	1	5	2	1.000	6	10	16	5	6	8	36	55	40	51	24	3	49	18	4	0	0.00%	2	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
	Vs Conference	1	1	2	1	1	2	1.000	2	2	4	5	6	8	42	55	40	51	22	15	17	38	2	0	0.00%	1	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
	Since Last GM Reset	4	4	19	6	13	8	1.000	19	30	49	5	6	8	146	55	40	51	101	48	82	98	9	1	11.11%	6	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31
	Total	4	4	19	6	13	8	1.000	19	30	49	5	6	8	146	55	40	51	101	48	82	98	9	1	11.11%	6	100.00%	56	82	68.29%	41	68	60.29%	39	57	68.42%	104	70	74	30	61	31

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
4	8	W4	19	30	49	146	101	48	82	98	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	4	0	0	0	0	0	19	6

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	8	4

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	11	2

Last 10 Games
W	L	OTW	OTL	SOW	SOL
4	0	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
9	1	11.11%	6	0	100.00%	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
55	40	51	0	5	6	8	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
56	82	68.29%	41	68	60.29%	39	57	68.42%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
104	70	74	30	61	31

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

Date		Result	Detail
Trade Deadline --- Trades can’t be done after this day is simulated!
Sun, Apr 20	@	Bears5,IceHogs1	RECAP
Mon, Apr 21	@	Bears6,Monarchs1	RECAP
Thu, Apr 24	@	Senators1,Bears2	RECAP
Fri, Apr 25	@	Wolves3,Bears6	RECAP

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,960,000$	680,000$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date
0$	0$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	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