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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	Jansen Harkins	0	X	X			100.00	73	41	82	66	80	79	83	63	71	64	65	62	63	67	69	0	75	65	0
2	Walker Duehr	0			X		100.00	73	38	87	66	82	75	80	63	61	65	62	64	66	68	69	0	75	65	0
3	Angus Crookshank (R)	0		X			100.00	65	38	77	66	69	87	85	64	63	61	66	60	62	65	67	0	75	64	0
4	Jack Finley (R)	0	X				100.00	87	42	79	63	96	77	82	58	67	60	59	64	63	62	65	0	75	64	0
5	Vinni Lettieri	0	X		X		100.00	68	37	81	65	67	81	79	64	71	62	66	63	64	70	71	0	75	64	0
6	Olle Lycksell (R)	0	X	X	X		100.00	61	35	91	65	63	84	82	64	68	66	63	62	67	65	68	0	75	64	0
7	Philippe Maillet (R)	0	X				100.00	56	36	94	64	66	81	72	63	73	65	62	60	64	72	74	0	75	63	0
8	Tristen Nielsen (R)	0	X				100.00	60	40	73	63	69	85	83	62	64	61	60	63	62	64	66	0	75	62	0
9	Mikhail Abramov (R)	0	X				100.00	57	37	90	63	66	79	81	62	68	61	59	56	62	64	65	0	75	61	0
10	Brayden Tracey (R)	0		X			100.00	62	38	81	58	70	73	82	56	61	59	57	55	58	63	65	0	75	60	0
11	Antti Saarela (R)	0	X				100.00	60	37	93	56	69	67	64	53	58	54	55	52	57	63	65	0	75	58	0
12	Carson Golder	0			X		100.00	65	40	87	57	74	69	61	53	58	56	54	55	57	62	64	0	75	58	0
13	Keean Washkurak (R)	0	X				100.00	56	40	71	57	67	71	80	56	59	54	55	52	53	64	65	0	75	58	0
14	Olen Zellweger (R)	0				X	100.00	59	36	91	73	66	90	72	69	30	70	62	63	53	61	64	0	75	65	0
15	Grant Hutton	0				X	100.00	75	40	85	59	85	71	77	58	30	56	57	60	49	69	71	0	75	62	0
16	Griffin Mendel	0				X	100.00	87	42	83	56	96	65	81	53	30	55	54	58	45	65	67	0	75	61	0
17	Andy Welinski	0				X	100.00	69	38	92	58	78	75	76	55	30	57	54	56	46	71	73	0	75	60	0
18	Brady Keeper	0				X	100.00	71	47	62	56	80	65	70	55	30	54	53	57	45	68	70	0	75	59	0
19	Lleyton Moore	0				X	100.00	55	37	87	58	64	65	61	57	30	55	56	52	47	62	64	0	75	58	0
Scratches
1	Jackson Cates (R)	0	X				82.57	63	37	93	57	72	80	85	58	63	59	60	56	58	67	69	0	75	61	0
2	Kim Nousiainen (R)	0				X	100.00	63	36	89	56	63	61	76	55	30	54	51	52	45	64	66	0	75	57	0

	TEAM AVERAGE					99.17	66	39	84	61	73	75	77	59	53	59	59	58	56	66	67	0	75	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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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	Collin Delia	100.00	76	82	77	82	75	74	76	75	74	76	75	71	84	0	75	67	0
2	Malcolm Subban	100.00	75	84	79	83	74	73	75	74	73	75	74	72	85	0	75	66	0
Scratches

	TEAM AVERAGE	100.00	76	83	78	83	75	74	76	75	74	76	75	72	85	0	75	67

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
John MacLean	72	74	71	74	90	84	56	CAN	60	3	750,000$

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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	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	GT	FO%	FOT	EG	HT	P/20	S1	S2	S3
1	Olen Zellweger	Griffins (DET)	D	22	8	22	30	-2	6	12	55	52	14	25	15.38%	40	511	23.25	5	7	12	30	65	1	40	0	0	0.00%	0	0	0	1.17	2	0	0
2	Jack Finley	Griffins (DET)	C	22	9	18	27	7	8	65	48	68	16	47	13.24%	6	464	21.13	2	4	6	10	56	0	31	3	1	48.80%	584	0	0	1.16	0	2	2
3	Walker Duehr	Griffins (DET)	RW	22	9	16	25	-7	8	55	62	82	30	62	10.98%	8	528	24.02	3	3	6	22	58	0	60	3	0	41.90%	179	1	0	0.95	1	1	2
4	Angus Crookshank	Griffins (DET)	LW	22	10	14	24	4	4	18	33	78	20	58	12.82%	5	425	19.33	2	5	7	10	57	0	12	1	2	41.18%	34	0	0	1.13	1	1	3
5	Vinni Lettieri	Griffins (DET)	C/RW	22	12	11	23	3	4	15	47	86	25	66	13.95%	8	444	20.19	1	3	4	15	56	0	32	0	0	51.61%	31	0	0	1.04	1	1	3
6	Olle Lycksell	Griffins (DET)	C/LW/RW	20	9	8	17	-4	2	15	37	52	19	53	17.31%	4	394	19.70	1	2	3	7	50	0	36	0	1	42.25%	71	0	0	0.86	1	1	0
7	Philippe Maillet	Griffins (DET)	C	22	6	9	15	-3	0	5	51	60	19	35	10.00%	3	322	14.67	0	0	0	0	0	0	0	0	0	53.21%	389	0	0	0.93	0	1	0
8	Jansen Harkins	Griffins (DET)	C/LW	20	6	7	13	-3	18	37	38	55	13	50	10.91%	5	331	16.57	1	1	2	4	13	0	9	1	0	50.00%	78	0	0	0.78	0	0	0
9	Grant Hutton	Griffins (DET)	D	22	2	10	12	0	16	56	16	29	6	14	6.90%	39	531	24.16	2	3	5	17	62	0	51	0	0	0.00%	0	0	0	0.45	2	0	0
10	Brayden Tracey	Griffins (DET)	LW	22	3	6	9	-3	6	13	19	33	12	22	9.09%	2	325	14.80	0	0	0	1	1	0	1	0	0	43.48%	23	0	1	0.55	0	1	0
11	Griffin Mendel	Griffins (DET)	D	22	2	7	9	-2	40	68	20	25	7	18	8.00%	27	457	20.78	1	1	2	6	48	0	36	0	1	0.00%	0	0	0	0.39	0	0	0
12	Jackson Cates	Griffins (DET)	C	20	3	6	9	-8	8	16	37	33	11	25	9.09%	3	360	18.03	0	1	1	10	50	0	11	1	0	46.07%	471	0	0	0.50	0	0	0
13	Tristen Nielsen	Griffins (DET)	C	22	2	6	8	-4	8	18	26	18	9	20	11.11%	17	327	14.87	0	0	0	0	0	0	0	0	0	38.89%	36	0	0	0.49	0	0	1
14	Andy Welinski	Griffins (DET)	D	14	0	5	5	1	2	11	8	8	1	4	0.00%	15	287	20.51	0	0	0	2	29	0	25	0	0	0.00%	0	0	0	0.35	0	0	0
15	Carson Golder	Griffins (DET)	RW	9	1	2	3	-1	2	5	7	6	2	6	16.67%	0	56	6.25	0	0	0	0	0	0	0	0	1	25.00%	4	0	0	1.07	0	0	0
16	Lleyton Moore	Griffins (DET)	D	16	0	3	3	-1	0	0	4	8	3	7	0.00%	10	181	11.34	0	1	1	6	22	0	27	0	0	0.00%	0	0	0	0.33	0	0	0
17	Brady Keeper	Griffins (DET)	D	14	1	1	2	3	6	32	5	6	2	6	16.67%	15	240	17.16	0	1	1	0	3	0	32	0	0	0.00%	0	0	0	0.17	0	0	0
18	Keean Washkurak	Griffins (DET)	C	22	1	1	2	-1	0	2	5	1	0	3	100.00%	2	42	1.93	0	0	0	0	0	0	23	1	0	56.25%	32	0	0	0.94	0	0	0
19	Mikhail Abramov	Griffins (DET)	C	22	2	0	2	-5	0	5	8	13	7	11	15.38%	0	121	5.52	0	0	0	1	7	0	0	1	0	55.56%	18	0	0	0.33	0	1	0
20	Kim Nousiainen	Griffins (DET)	D	8	0	1	1	-7	4	15	4	1	2	4	0.00%	12	121	15.13	0	1	1	1	2	0	7	0	0	0.00%	0	0	0	0.17	0	0	0
21	Antti Saarela	Griffins (DET)	C	22	0	0	0	0	0	0	0	1	0	2	0.00%	0	11	0.51	0	0	0	1	2	0	7	0	0	50.00%	4	0	0	0.00	0	0	0
Team Total or Average				407	86	153	239	-33	142	463	530	715	218	538	12.03%	221	6485	15.93	18	33	51	143	591	1	448	11	6	48.00%	1954	1	1	0.74	8	9	11

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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	GA	SA	ST	BG
1	Collin Delia	Griffins (DET)	22	11	10	1	0.886	4.16	1268	88	772	22	0
2	Malcolm Subban	Griffins (DET)	2	0	0	0	0.964	1.15	52	1	28	0	22
Team Total or Average			24	11	10	1	0.889	4.04	1321	89	800	22	22

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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	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
Andy Welinski	D	31	1993-04-27	No	201 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Angus Crookshank	LW	25	1999-10-02	Yes	181 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Antti Saarela	C	23	2001-06-27	Yes	183 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No
Brady Keeper	D	28	1996-06-05	No	197 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Brayden Tracey	LW	23	2001-05-28	Yes	177 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Carson Golder	RW	21	2002-10-29	No	196 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	999,999$	0$	0$	No	Link
Collin Delia	G	30	1994-06-20	No	208 Lbs	6 ft2	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Grant Hutton	D	29	1995-07-25	No	206 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Griffin Mendel	D	25	1999-02-18	No	220 Lbs	6 ft6	No	No	No	1	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Jack Finley	C	22	2002-09-02	Yes	220 Lbs	6 ft6	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Jackson Cates (Out of Payroll)	C	27	1997-09-26	Yes	190 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	Yes	Link / NHL Link
Jansen Harkins	C/LW	27	1997-05-23	No	197 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Keean Washkurak	C	23	2001-08-16	Yes	184 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Kim Nousiainen	D	23	2000-11-14	Yes	170 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Lleyton Moore	D	22	2002-02-27	No	178 Lbs	5 ft8	No	No	No	3	RFA	Pro & Farm	999,999$	0$	0$	No	Link
Malcolm Subban	G	30	1993-12-21	No	215 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	775,000$	0$	0$	No	Link / NHL Link
Mikhail Abramov	C	23	2001-03-26	Yes	160 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Olen Zellweger	D	21	2003-09-10	Yes	182 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No
Olle Lycksell	C/LW/RW	25	1999-08-24	Yes	163 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Philippe Maillet	C	31	1992-11-07	Yes	174 Lbs	5 ft10	No	No	No	3	UFA	Pro & Farm	950,000$	0$	0$	No	Link
Tristen Nielsen	C	24	2000-02-23	Yes	192 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Vinni Lettieri	C/RW	29	1995-02-06	No	184 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	970,000$	0$	0$	No	Link / NHL Link
Walker Duehr	RW	26	1997-11-23	No	210 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
23	25.57	191 Lbs	6 ft0	1.91	919,348$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Mikhail Abramov	Olle Lycksell	Walker Duehr	40	1	2	2
2	Angus Crookshank	Jack Finley	Vinni Lettieri	30	1	2	2
3	Brayden Tracey	Philippe Maillet	Jansen Harkins	20	1	2	2
4	Walker Duehr	Tristen Nielsen	Jack Finley	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Olen Zellweger	Grant Hutton	40	1	2	2
2	Griffin Mendel	Andy Welinski	30	1	2	2
3	Brady Keeper	Tristen Nielsen	20	1	2	2
4	Griffin Mendel	Grant Hutton	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jansen Harkins	Mikhail Abramov	Walker Duehr	60	1	2	2
2	Angus Crookshank	Jack Finley	Vinni Lettieri	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Olen Zellweger	Grant Hutton	60	1	2	2
2	Griffin Mendel	Andy Welinski	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Walker Duehr	Jansen Harkins	60	1	2	2
2	Jack Finley	Vinni Lettieri	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Andy Welinski	Grant Hutton	60	1	2	2
2	Griffin Mendel	Brady Keeper	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Walker Duehr	60	1	2	2	Olen Zellweger	Grant Hutton	60	1	2	2
2	Jack Finley	40	1	2	2	Griffin Mendel	Brady Keeper	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Walker Duehr	Angus Crookshank	60	1	2	2
2	Jack Finley	Vinni Lettieri	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Brady Keeper	Grant Hutton	60	1	2	2
2	Griffin Mendel	Andy Welinski	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Jansen Harkins	Jack Finley	Walker Duehr	Olen Zellweger	Grant Hutton

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jansen Harkins	Jack Finley	Walker Duehr	Olen Zellweger	Grant Hutton

Extra Forwards
Normal	PowerPlay	Penalty Kill
Walker Duehr, Mikhail Abramov, Keean Washkurak	Jack Finley, Mikhail Abramov	Keean Washkurak

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Grant Hutton, Griffin Mendel, Andy Welinski	Grant Hutton	Griffin Mendel, Grant Hutton

Penalty Shots
Walker Duehr, Angus Crookshank, Jack Finley, Vinni Lettieri, Mikhail Abramov

Goalie
#1 : Collin Delia, #2 : Malcolm Subban

Custom OT Lines Forwards
Walker Duehr, Keean Washkurak, Jack Finley, Vinni Lettieri, Jansen Harkins, Angus Crookshank, Angus Crookshank, Philippe Maillet, Tristen Nielsen, Olle Lycksell, Mikhail Abramov

Custom OT Lines Defensemen
Olen Zellweger, Grant Hutton, Griffin Mendel, Andy Welinski, Brady Keeper

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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.
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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.
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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
22	23	W1	86	153	239	715	800	221	142	463	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
22	9	10	2	1	0	0	86	89

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	7	3	1	0	0	0	49	38

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
11	2	7	1	1	0	0	37	51

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	4	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
72	18	25.00%	67	15	77.61%	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
214	240	259	2	33	26	25	2

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
355	753	47.14%	400	831	48.13%	183	366	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
496	339	542	167	285	139

Last Played Games Show or Hide Column

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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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	Link
7 - 2024-10-10	14	Penguins	2	Griffins	7	W		BoxScore
9 - 2024-10-12	28	Admirals	5	Griffins	6	W		BoxScore
11 - 2024-10-14	45	Griffins	3	Wolf Pack	5	L		BoxScore
14 - 2024-10-17	63	Wolf Pack	5	Griffins	6	W	X	BoxScore
16 - 2024-10-19	76	Griffins	1	Admirals	5	L		BoxScore
19 - 2024-10-22	98	Griffins	3	Sound Tigers	7	L		BoxScore
21 - 2024-10-24	111	Devils	4	Griffins	2	L		BoxScore
23 - 2024-10-26	122	Griffins	4	Americans	5	L		BoxScore
24 - 2024-10-27	136	Condors	4	Griffins	1	L		BoxScore
27 - 2024-10-30	156	Moose	2	Griffins	6	W		BoxScore
30 - 2024-11-02	179	Americans	4	Griffins	5	W		BoxScore
34 - 2024-11-06	206	Griffins	3	IceHogs	4	L	X	BoxScore
36 - 2024-11-08	220	Griffins	4	Marlies	3	W		BoxScore
37 - 2024-11-09	228	Wolf Pack	3	Griffins	5	W		BoxScore
41 - 2024-11-13	252	Griffins	1	Penguins	4	L		BoxScore
43 - 2024-11-15	271	Griffins	3	Gulls	5	L		BoxScore
44 - 2024-11-16	282	Griffins	7	Reign	6	W	X	BoxScore
46 - 2024-11-18	293	Griffins	5	Barracuda	2	W		BoxScore
49 - 2024-11-21	308	Sound Tigers	3	Griffins	5	W		BoxScore
51 - 2024-11-23	324	Bruins	2	Griffins	1	L		BoxScore
53 - 2024-11-25	341	Griffins	3	Sound Tigers	5	L		BoxScore
55 - 2024-11-27	350	Wranglers	4	Griffins	5	W		BoxScore
57 - 2024-11-29	365	Devils	-	Griffins	-
59 - 2024-12-01	388	Comets	-	Griffins	-
61 - 2024-12-03	396	Griffins	-	Bruins	-
63 - 2024-12-05	412	Griffins	-	Senators	-
65 - 2024-12-07	432	Eagles	-	Griffins	-
67 - 2024-12-09	443	Griffins	-	Americans	-
70 - 2024-12-12	462	Griffins	-	Phantoms	-
72 - 2024-12-14	479	Marlies	-	Griffins	-
76 - 2024-12-18	507	Phantoms	-	Griffins	-
78 - 2024-12-20	522	Rocket	-	Griffins	-
79 - 2024-12-21	533	Griffins	-	Rocket	-
81 - 2024-12-23	548	Thunderbirds	-	Griffins	-
85 - 2024-12-27	559	Marlies	-	Griffins	-
87 - 2024-12-29	579	Bears	-	Griffins	-
89 - 2024-12-31	593	Penguins	-	Griffins	-
91 - 2025-01-02	606	Griffins	-	Monsters	-
93 - 2025-01-04	621	Griffins	-	Moose	-
96 - 2025-01-07	642	Senators	-	Griffins	-
99 - 2025-01-10	664	IceHogs	-	Griffins	-
101 - 2025-01-12	684	Firebirds	-	Griffins	-
103 - 2025-01-14	694	Barracuda	-	Griffins	-
105 - 2025-01-16	710	Griffins	-	Checkers	-
107 - 2025-01-18	727	Griffins	-	Crunch	-
108 - 2025-01-19	739	Griffins	-	Stars	-
110 - 2025-01-21	751	Griffins	-	Phantoms	-
112 - 2025-01-23	762	Rocket	-	Griffins	-
114 - 2025-01-25	781	Crunch	-	Griffins	-
116 - 2025-01-27	794	Reign	-	Griffins	-
119 - 2025-01-30	819	Griffins	-	Condors	-
121 - 2025-02-01	834	Griffins	-	Wranglers	-
122 - 2025-02-02	842	Griffins	-	Comets	-
124 - 2025-02-04	857	Griffins	-	Firebirds	-
128 - 2025-02-08	877	Crunch	-	Griffins	-
142 - 2025-02-22	894	Wild	-	Griffins	-
143 - 2025-02-23	908	Gulls	-	Griffins	-
145 - 2025-02-25	928	Griffins	-	Wild	-
147 - 2025-02-27	935	Monsters	-	Griffins	-
149 - 2025-03-01	948	Griffins	-	Monsters	-
152 - 2025-03-04	975	Wolves	-	Griffins	-
154 - 2025-03-06	988	Roadrunners	-	Griffins	-
155 - 2025-03-07	998	Griffins	-	Bears	-
158 - 2025-03-10	1022	Griffins	-	Senators	-
160 - 2025-03-12	1036	Americans	-	Griffins	-
162 - 2025-03-14	1049	Griffins	-	Wolves	-
164 - 2025-03-16	1066	Silver Knights	-	Griffins	-
166 - 2025-03-18	1081	Griffins	-	Bears	-
170 - 2025-03-22	1115	Griffins	-	Silver Knights	-
172 - 2025-03-24	1128	Griffins	-	Roadrunners	-
173 - 2025-03-25	1136	Griffins	-	Eagles	-
175 - 2025-03-27	1144	Senators	-	Griffins	-
Trade Deadline --- Trades can’t be done after this day is simulated!
177 - 2025-03-29	1166	Bruins	-	Griffins	-
180 - 2025-04-01	1187	Griffins	-	Thunderbirds	-
183 - 2025-04-04	1206	Wolves	-	Griffins	-
185 - 2025-04-06	1225	Checkers	-	Griffins	-
187 - 2025-04-08	1236	Griffins	-	Rocket	-
189 - 2025-04-10	1251	Griffins	-	Checkers	-
190 - 2025-04-11	1261	Griffins	-	Crunch	-
193 - 2025-04-14	1286	Stars	-	Griffins	-
195 - 2025-04-16	1303	Griffins	-	Devils	-
196 - 2025-04-17	1308	Griffins	-	Marlies	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	16,851	10,902
Attendance PCT	76.60%	99.11%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
-1	2523 - 84.10%	85,604$	941,644$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
780,262$	2,019,500$	2,019,500$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	566,825$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
-85,604$	141	14,130$	1,992,330$

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	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
5	80	36	31	0	2	2	6	3	260	242	18	40	21	15	0	0	1	1	2	122	120	2	40	15	16	0	2	1	5	1	138	122	16	93	260	415	675	0	6	0	72	98	82	2727	0	872	953	874	2711	995	889	2336	167	43	25.75%	211	46	78.20%	7	772	1599	48.28%	794	1637	48.50%	568	1239	45.84%	1567	744	1856	964	1713	840
6	80	36	31	0	2	4	3	4	244	251	-7	40	19	13	0	1	2	3	2	126	123	3	40	17	18	0	1	2	0	2	118	128	-10	90	244	389	633	0	4	0	68	95	76	2099	0	655	780	656	2456	894	630	2049	167	38	22.75%	192	47	75.52%	4	678	1413	47.98%	854	1737	49.17%	568	1173	48.42%	1469	641	3846	1980	1758	891
7	76	20	45	0	2	6	0	3	217	292	-75	38	11	22	0	0	3	0	2	105	141	-36	38	9	23	0	2	3	0	1	112	151	-39	53	217	355	572	0	4	0	49	83	83	1938	0	521	659	743	2216	700	625	2132	188	39	20.74%	173	50	71.10%	8	691	1358	50.88%	566	1242	45.57%	540	1135	47.58%	1402	606	1482	784	1705	861
8	76	22	40	0	3	1	4	6	200	257	-57	38	12	17	0	2	0	2	5	104	123	-19	38	10	23	0	1	1	2	1	96	134	-38	65	200	326	526	2	3	0	36	78	79	1931	0	535	700	675	2462	834	1013	1871	187	32	17.11%	205	51	75.12%	9	733	1454	50.41%	797	1602	49.75%	511	1043	48.99%	1395	595	1543	787	1671	861
9	80	24	37	0	6	5	5	3	233	261	-28	40	11	18	0	4	1	4	2	108	118	-10	40	13	19	0	2	4	1	1	125	143	-18	78	233	364	597	1	5	0	59	76	87	2275	0	661	789	790	2490	856	829	1811	190	46	24.21%	159	52	67.30%	3	804	1591	50.53%	789	1591	49.59%	530	1118	47.41%	1506	681	1598	810	1754	903
10	80	25	33	0	5	4	4	9	209	235	-26	40	12	17	0	4	2	1	4	101	114	-13	40	13	16	0	1	2	3	5	108	121	-13	81	209	333	542	3	5	0	40	70	90	2071	0	530	762	753	2609	889	845	1847	167	41	24.55%	210	60	71.43%	2	766	1525	50.23%	851	1803	47.20%	486	1032	47.09%	1459	622	1621	837	1790	914
11	80	14	45	0	4	7	4	6	201	288	-87	40	7	24	0	2	4	1	2	92	132	-40	40	7	21	0	2	3	3	4	109	156	-47	57	201	329	530	2	1	0	25	90	78	2101	0	544	752	769	2544	858	625	2234	177	46	25.99%	247	83	66.40%	7	687	1514	45.38%	747	1705	43.81%	432	1038	41.62%	1455	625	1634	857	1774	871
12	76	10	48	0	6	3	3	6	175	304	-129	38	6	23	0	1	2	1	5	91	152	-61	38	4	25	0	5	1	2	1	84	152	-68	47	175	282	457	4	0	0	32	68	66	1677	0	393	621	635	2623	838	600	1424	166	56	33.73%	208	72	65.38%	6	590	1250	47.20%	719	1561	46.06%	441	987	44.68%	1278	498	1608	806	1728	879
13	80	23	40	0	7	4	3	3	190	253	-63	40	11	19	0	2	3	2	3	99	135	-36	40	12	21	0	5	1	1	0	91	118	-27	73	190	306	496	5	5	0	36	74	70	1982	0	446	775	721	2612	855	558	1559	165	49	29.70%	199	60	69.85%	2	694	1459	47.57%	833	1730	48.15%	496	998	49.70%	1373	557	1666	849	1804	910
14	80	8	54	0	3	6	4	5	193	378	-185	40	4	27	0	0	2	4	3	92	184	-92	40	4	27	0	3	4	0	2	101	194	-93	41	193	299	492	0	1	0	38	80	68	2303	0	653	835	791	2777	926	926	2100	186	41	22.04%	274	100	63.50%	2	818	1542	53.05%	794	1547	51.33%	587	1180	49.75%	1482	667	1671	834	1700	845
15	80	16	51	0	5	1	4	3	216	340	-124	40	8	22	0	3	1	4	2	114	159	-45	40	8	29	0	2	0	0	1	102	181	-79	54	216	361	577	4	0	0	42	86	79	2597	0	736	988	837	2760	965	839	1934	160	39	24.38%	261	93	64.37%	3	935	1787	52.32%	714	1487	48.02%	604	1160	52.07%	1574	776	1617	804	1658	823
16	76	6	59	0	0	2	3	6	187	355	-168	38	5	29	0	0	1	2	1	88	168	-80	38	1	30	0	0	1	1	5	99	187	-88	26	187	333	520	0	1	0	73	56	55	2158	0	678	715	747	2552	694	531	1588	238	42	17.65%	227	62	72.69%	2	1201	2421	49.61%	1008	2148	46.93%	619	1291	47.95%	1726	1157	1880	578	999	486
17	80	17	45	0	1	7	5	5	203	315	-112	40	11	22	0	1	2	2	2	102	151	-49	40	6	23	0	0	5	3	3	101	164	-63	58	203	354	557	4	1	0	77	63	57	2288	0	759	769	741	2827	848	471	1570	256	43	16.80%	193	49	74.61%	1	1275	2529	50.42%	1266	2429	52.12%	680	1343	50.63%	1791	1203	2015	609	1063	518
18	76	21	39	0	2	5	2	7	229	276	-47	38	14	18	0	1	1	0	4	117	121	-4	38	7	21	0	1	4	2	3	112	155	-43	62	229	410	639	2	4	0	78	82	65	2335	0	770	772	780	2469	720	263	1324	240	47	19.58%	110	24	78.18%	0	1217	2439	49.90%	1061	2271	46.72%	636	1299	48.96%	1702	1160	1913	566	997	485
19	82	22	50	0	0	0	4	6	181	286	-105	41	11	24	0	0	0	3	3	87	130	-43	41	11	26	0	0	0	1	3	94	156	-62	58	181	319	500	3	1	0	69	56	52	1949	0	646	663	617	2772	757	377	1491	200	36	18.00%	174	30	82.76%	1	1071	2298	46.61%	1080	2487	43.43%	601	1335	45.02%	1793	1185	2083	623	1093	526
20	82	11	52	0	7	2	5	5	185	313	-128	41	6	25	0	6	2	2	0	98	143	-45	41	5	27	0	1	0	3	5	87	170	-83	53	185	316	501	1	1	0	62	73	38	1887	0	604	636	598	3188	901	599	1960	249	54	21.69%	263	58	77.95%	1	941	2293	41.04%	1164	3086	37.72%	500	1288	38.82%	1728	1146	2191	631	1065	509
21	82	42	28	0	5	2	3	2	286	262	24	41	21	13	0	4	1	1	1	143	127	16	41	21	15	0	1	1	2	1	143	135	8	104	286	504	790	2	4	0	94	99	85	3111	0	1014	969	1089	2847	821	551	2036	243	58	23.87%	246	44	82.11%	2	1725	3096	55.72%	1609	2947	54.60%	713	1326	53.77%	2037	1435	1889	575	1026	516
22	82	31	41	0	4	3	1	2	270	292	-22	41	16	18	0	3	2	0	2	135	145	-10	41	15	23	0	1	1	1	0	135	147	-12	77	270	489	759	3	1	0	100	81	84	2950	0	962	957	1008	2959	882	585	2047	244	57	23.36%	253	58	77.08%	1	1636	3126	52.34%	1563	3027	51.64%	705	1376	51.24%	1964	1353	1930	588	1054	526
23	82	34	34	0	9	1	2	2	297	293	4	41	21	16	0	2	1	1	0	146	135	11	41	13	18	0	7	0	1	2	151	158	-7	93	297	531	828	0	1	106	95	85	13	3137	1046	1047	998	58	3006	915	586	1933	242	48	19.83%	251	52	79.28%	1	1674	3130	53.48%	1617	3046	53.09%	716	1370	52.26%	1963	1374	1964	592	1043	521
2022	82	23	50	0	4	4	1	0	305	430	-125	41	16	21	0	2	2	0	0	169	202	-33	41	7	29	0	2	2	1	0	136	228	-92	60	305	535	840	3	0	109	108	83	5	2983	975	967	1019	25	3404	1014	522	2144	230	45	19.57%	239	69	71.13%	5	1197	2914	41.08%	1247	3001	41.55%	637	1541	41.34%	1844	1289	2084	582	1016	487
2023	82	37	33	0	3	3	3	3	307	289	18	41	17	16	0	0	2	3	3	137	134	3	41	20	17	0	3	1	0	0	170	155	15	92	307	558	865	0	1	110	99	92	8	3019	993	984	1007	62	2995	897	583	2010	273	65	23.81%	245	52	78.78%	1	1547	2974	52.02%	1620	3069	52.79%	655	1369	47.85%	1998	1396	1921	588	1047	530
2024	22	9	10	0	2	1	0	0	86	89	-3	11	7	3	0	1	0	0	0	49	38	11	11	2	7	0	1	1	0	0	37	51	-14	23	86	153	239	0	0	33	26	25	2	715	214	240	259	2	800	221	142	463	72	18	25.00%	67	15	77.61%	0	355	753	47.14%	400	831	48.13%	183	366	50.00%	496	339	542	167	285	139
Total Regular Season	1696	487	896	0	82	73	69	89	4874	6301	-1427	848	267	422	0	39	35	37	48	2425	2995	-570	848	220	474	0	43	38	32	41	2449	3306	-857	1438	4874	8261	13135	39	49	358	1378	1693	1322	50233	3228	15217	17378	13971	58079	18280	13589	39863	4407	983	22.31%	4607	1227	73.37%	68	22007	44465	49.49%	22093	45984	48.04%	12408	26007	47.71%	35010	20058	40562	16421	29754	14850
Playoff
5	4	0	4	0	0	0	0	0	9	23	-14	2	0	2	0	0	0	0	0	7	11	-4	2	0	2	0	0	0	0	0	2	12	-10	0	9	16	25	0	0	0	3	4	2	126	0	49	33	44	205	75	38	99	2	0	0.00%	16	4	75.00%	1	40	97	41.24%	50	128	39.06%	42	73	57.53%	71	34	1945	1003	78	37
21	9	4	5	0	0	0	0	0	27	29	-2	4	1	3	0	0	0	0	0	12	15	-3	5	3	2	0	0	0	0	0	15	14	1	8	27	48	75	0	0	0	9	8	7	317	0	103	100	105	362	116	93	202	30	3	10.00%	46	9	80.43%	2	144	341	42.23%	180	409	44.01%	59	135	43.70%	198	133	250	70	114	55
2023	5	1	4	0	0	0	0	0	14	22	-8	2	1	1	0	0	0	0	0	5	8	-3	3	0	3	0	0	0	0	0	9	14	-5	2	14	27	41	0	0	3	5	6	0	165	39	51	62	13	198	66	47	99	13	2	15.38%	20	3	85.00%	0	105	202	51.98%	103	192	53.65%	43	81	53.09%	122	80	134	40	68	33
Total Playoff	18	5	13	0	0	0	0	0	50	74	-24	8	2	6	0	0	0	0	0	24	34	-10	10	3	7	0	0	0	0	0	26	40	-14	10	50	91	141	0	0	3	17	18	9	608	39	203	195	162	765	257	178	400	45	5	11.11%	82	16	80.49%	3	289	640	45.16%	333	729	45.68%	144	289	49.83%	392	248	2331	1115	261	126