LHSDB - Ligue de hockey simulee des debiles barbus

Philadelphia Flyers
Roster
Scoring
Informations
Lines
Stats
Schedule
Finance
Records
Web Lines Editor

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	Alexander Barabanov	0		X	X		100.00	64	34	91	73	69	88	81	72	57	75	66	62	70	71	73	35	50	68	0
2	Logan Shaw	0	X		X		100.00	76	40	85	64	85	95	86	63	70	65	66	64	63	72	77	40	50	68	0
3	Tyson Jost	0	X				100.00	67	40	86	68	72	80	86	66	74	65	60	70	65	68	69	82	50	65	0
4	Cole Guttman	0	X				100.00	62	38	83	68	63	86	82	67	81	65	66	62	68	65	67	48	50	65	0
5	Liam Foudy	0	X		X		100.00	70	38	93	69	79	86	79	65	66	61	63	64	68	66	67	81	50	65	0
6	Riley Nash	0	X				100.00	69	39	78	63	75	83	80	62	70	61	59	65	62	79	77	42	50	64	0
7	Seth Griffith	0	X		X		100.00	58	37	85	64	67	75	86	63	76	68	59	58	61	71	73	45	50	63	0
8	Mike Hardman	0	X	X	X		100.00	77	38	85	63	81	79	84	62	58	56	60	61	59	65	67	42	50	63	0
9	Marian Studenic	0		X	X		100.00	68	37	89	62	75	80	85	57	61	63	58	60	62	66	68	53	50	62	0
10	Matthew Strome	0		X			100.00	79	41	80	59	88	69	75	58	60	57	55	56	54	65	67	58	50	60	0
11	Hayden Hodgson	0			X		100.00	77	55	53	58	82	69	77	57	60	56	55	59	57	68	70	36	50	60	0
12	Cory Conacher	0	X	X	X		100.00	56	40	70	59	65	74	75	58	55	57	56	54	59	75	77	23	50	59	0
13	Nikolai Knyzhov	0				X	100.00	76	40	82	62	88	83	75	61	30	60	59	67	50	66	68	42	50	66	0
14	Adam Ginning	0				X	100.00	73	42	70	63	83	80	85	59	30	58	62	64	50	65	66	69	50	65	0
15	Cameron Crotty	0				X	100.00	79	39	85	59	80	75	82	58	30	57	56	62	51	65	67	62	50	63	0
16	Steven Kampfer	0				X	100.00	63	39	78	61	72	77	79	58	30	63	54	56	47	76	81	30	50	62	0
17	Helge Grans	0				X	100.00	78	40	87	58	87	69	81	56	30	54	52	57	45	62	64	76	50	62	0
18	Nolan Allan (R)	0				X	100.00	70	55	75	58	79	65	70	57	30	56	54	62	46	61	63	77	50	61	0
19	Cameron Gaunce	0				X	100.00	67	42	70	58	76	67	77	54	30	55	52	57	45	74	76	38	50	60	0
20	Artemi Kniazev	0				X	100.00	59	39	82	57	68	80	74	55	30	59	51	54	46	63	65	72	50	59	0
Scratches

	TEAM AVERAGE					100.00	69	41	80	62	77	78	80	60	51	61	58	61	56	68	70	53	50	63

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	Matt Tomkins	100.00	77	76	71	85	76	75	77	76	75	77	76	70	84	51	50	75	0
Scratches

	TEAM AVERAGE	100.00	77	76	71	85	76	75	77	76	75	77	76	70	84	51	50	75

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Mike Vellucci	73	69	72	71	87	81	60	USA	58	8	1,000,000$

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	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Cole Guttman	Phantoms (Phi)	C	55	18	36	54	34	47	5	66	109	168	50	126	10.71%	15	1142	20.78	0	13	13	19	193	0	1	1	5	202	3	2	61.30%	925	0	0.95	2	6	0	0	0	2	8	5
2	Mike Hardman	Phantoms (Phi)	C/LW/RW	60	28	24	52	22	81	5	143	87	216	62	144	12.96%	17	1207	20.12	8	6	14	59	257	1	0	1	2	62	6	3	63.51%	74	1	0.86	0	1	0	0	0	9	0	3
3	Seth Griffith	Phantoms (Phi)	C/RW	60	15	26	41	8	16	0	38	86	167	62	136	8.98%	13	1175	19.59	5	10	15	38	235	0	1	1	5	125	1	0	65.83%	120	0	0.70	0	3	0	0	0	1	3	5
4	Adam Ginning	Phantoms (Phi)	D	58	13	27	40	19	96	10	100	46	102	28	58	12.75%	47	1082	18.66	6	7	13	65	195	0	2	2	1	190	2	1	0.00%	0	0	0.74	0	0	0	0	2	3	3	0
5	Riley Nash	Phantoms (Phi)	C	54	20	20	40	8	42	0	85	107	158	41	120	12.66%	18	1128	20.89	7	9	16	37	209	0	0	0	5	176	0	0	59.15%	1087	0	0.71	2	6	0	0	0	3	2	6
6	Marian Studenic	Phantoms (Phi)	LW/RW	60	12	25	37	12	24	0	77	68	162	41	87	7.41%	14	1066	17.78	5	14	19	41	235	0	0	0	1	39	2	1	51.58%	95	0	0.69	0	0	0	0	0	0	0	4
7	Hayden Hodgson	Phantoms (Phi)	RW	60	10	26	36	15	86	10	121	51	118	35	68	8.47%	14	796	13.28	1	4	5	11	95	0	0	0	1	0	2	0	63.16%	76	0	0.90	0	0	0	0	2	2	1	6
8	Matt Irwin	Philadelphia Flyers	D	40	9	26	35	16	56	10	81	56	68	29	53	13.24%	56	925	23.15	5	8	13	55	187	0	0	0	1	178	3	0	0.00%	0	0	0.76	0	0	0	0	2	3	2	1
9	Tyson Jost	Phantoms (Phi)	C	28	13	20	33	20	15	5	43	111	93	20	80	13.98%	16	698	24.93	0	5	5	28	122	1	0	1	6	138	3	1	63.70%	865	0	0.95	1	4	0	1	0	3	4	2
10	Alexander Barabanov	Phantoms (Phi)	LW/RW	22	13	20	33	35	0	0	13	32	83	28	69	15.66%	3	463	21.07	2	6	8	17	79	0	0	0	1	49	1	0	72.73%	66	0	1.42	1	1	0	0	0	1	3	2
11	Matthew Strome	Phantoms (Phi)	LW	60	19	13	32	8	61	5	72	53	102	34	69	18.63%	10	805	13.43	2	1	3	4	25	0	0	0	0	12	2	0	61.90%	63	1	0.79	0	0	0	0	1	3	4	0
12	Cameron Crotty	Phantoms (Phi)	D	60	8	23	31	22	66	0	87	37	61	19	45	13.11%	49	1118	18.64	3	6	9	34	192	0	1	1	1	197	0	0	0.00%	0	0	0.55	0	0	0	0	0	1	2	1
13	Nikolai Knyzhov	Phantoms (Phi)	D	38	8	18	26	18	44	0	53	39	69	29	44	11.59%	46	858	22.60	5	6	11	42	157	0	0	0	2	179	3	0	0.00%	0	0	0.61	0	0	0	0	0	1	2	2
14	Cory Conacher	Phantoms (Phi)	C/LW/RW	47	11	14	25	12	21	5	16	88	77	27	62	14.29%	4	741	15.78	0	0	0	1	13	0	0	0	2	85	3	1	51.48%	674	1	0.67	0	0	0	0	0	4	3	1
15	Liam Foudy	Phantoms (Phi)	C/RW	21	6	8	14	17	10	0	27	54	61	21	49	9.84%	5	537	25.57	1	1	2	9	79	0	0	0	2	121	1	0	53.79%	515	0	0.52	0	2	0	0	0	1	1	2
16	Nolan Allan	Phantoms (Phi)	D	60	5	7	12	3	38	20	43	32	35	8	27	14.29%	19	493	8.23	0	0	0	0	0	0	0	0	0	7	2	0	39.29%	28	0	0.49	0	0	2	0	2	0	1	0
17	Helge Grans	Phantoms (Phi)	D	44	1	10	11	12	50	0	64	18	12	2	11	8.33%	24	497	11.31	0	0	0	0	6	0	0	0	0	24	1	0	0.00%	2	0	0.44	0	0	0	0	0	0	1	1
18	Steven Kampfer	Phantoms (Phi)	D	37	1	8	9	11	22	0	24	17	18	4	11	5.56%	24	476	12.87	0	0	0	5	15	0	0	0	0	78	0	0	0.00%	0	0	0.38	0	0	0	0	0	0	0	0
19	Artemi Kniazev	Phantoms (Phi)	D	60	0	6	6	2	2	0	5	2	6	0	11	0.00%	5	108	1.82	0	2	2	4	19	0	0	0	0	5	0	0	0.00%	0	0	1.10	0	0	0	0	0	0	1	0
20	Cameron Gaunce	Phantoms (Phi)	D	60	0	3	3	4	22	0	35	9	8	2	7	0.00%	12	301	5.03	0	0	0	0	0	0	0	0	0	2	0	0	0.00%	1	0	0.20	0	0	0	0	0	0	0	0
Team Total or Average				984	210	360	570	298	799	75	1193	1102	1784	542	1277	11.77%	411	15626	15.88	50	98	148	469	2321	2	5	7	35	1876	35	9	58.94%	4591	3	0.73	6	23	2	1	9	37	41	41

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	PS %	PSA	ST	BG	S1	S2	S3
1	Matt Tomkins	Phantoms (Phi)	42	28	10	4	0.922	1.79	2551	4	6	76	979	0.824	17	42	0	5	1	2
2	Luke Cavallin	Phantoms (Phi)	5	2	1	2	0.917	2.16	305	0	0	11	133	0.333	3	5	45	0	0	0
Team Total or Average			47	30	11	6	0.922	1.83	2857	4	6	87	1112	0.750	20	47	45	5	1	2

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	Available For Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Link
Adam Ginning	D	25	2000-01-13	No	196 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Alexander Barabanov	LW/RW	30	1994-06-17	No	195 Lbs	5 ft10	No	No	No	3	UFA	Pro & Farm	2,500,000$	0$	0$	No	Link / NHL Link
Artemi Kniazev	D	24	2001-01-04	No	178 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Cameron Crotty	D	25	1999-05-05	No	182 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Cameron Gaunce	D	34	1990-03-19	No	194 Lbs	6 ft1	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Cole Guttman	C	25	1999-04-06	No	167 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Cory Conacher	C/LW/RW	35	1989-12-14	No	185 Lbs	5 ft8	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Hayden Hodgson	RW	29	1996-03-02	No	208 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Helge Grans	D	22	2002-05-10	No	205 Lbs	6 ft4	No	No	No	2	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Liam Foudy	C/RW	25	2000-02-04	No	193 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Logan Shaw	C/RW	32	1992-10-05	No	208 Lbs	6 ft3	No	No	No	3	UFA	Pro & Farm	520,000$	520,000$	79,592$	No	Link / NHL Link
Marian Studenic	LW/RW	26	1998-10-28	No	190 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Matt Tomkins	G	30	1994-06-19	No	191 Lbs	6 ft4	No	No	No	3	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Matthew Strome	LW	26	1999-01-06	No	206 Lbs	6 ft4	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Mike Hardman	C/LW/RW	26	1999-02-05	No	205 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nikolai Knyzhov	D	26	1998-03-20	No	222 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nolan Allan	D	21	2003-04-28	Yes	195 Lbs	6 ft2	No	No	No	4	ELC	Pro & Farm	500,000$	0$	0$	No	NHL Link
Riley Nash	C	35	1989-05-09	No	187 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Seth Griffith	C/RW	32	1993-01-04	No	190 Lbs	5 ft9	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Steven Kampfer	D	36	1988-09-24	No	198 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Tyson Jost	C	27	1998-03-14	No	187 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	780,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
21	28.14	194 Lbs	6 ft1	2.14	580,952$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Mike Hardman	Tyson Jost	Liam Foudy	40	1	2	2
2	Marian Studenic	Riley Nash	Seth Griffith	30	1	2	2
3	Matthew Strome	Cory Conacher	Hayden Hodgson	20	1	2	2
4	Liam Foudy	Tyson Jost	Riley Nash	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Nikolai Knyzhov	Adam Ginning	40	1	2	2
2	Cameron Crotty	Steven Kampfer	30	1	2	2
3	Helge Grans	Nolan Allan	20	1	2	2
4	Cameron Gaunce	Artemi Kniazev	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Mike Hardman	Tyson Jost	Liam Foudy	60	1	2	2
2	Marian Studenic	Riley Nash	Seth Griffith	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Nikolai Knyzhov	Adam Ginning	60	1	2	2
2	Cameron Crotty	Steven Kampfer	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tyson Jost	Liam Foudy	60	1	2	2
2	Riley Nash	Seth Griffith	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Nikolai Knyzhov	Adam Ginning	60	1	2	2
2	Cameron Crotty	Steven Kampfer	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Tyson Jost	60	1	2	2	Nikolai Knyzhov	Adam Ginning	60	1	2	2
2	Liam Foudy	40	1	2	2	Cameron Crotty	Steven Kampfer	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Tyson Jost	Liam Foudy	60	1	2	2
2	Riley Nash	Seth Griffith	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Nikolai Knyzhov	Adam Ginning	60	1	2	2
2	Cameron Crotty	Steven Kampfer	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Mike Hardman	Tyson Jost	Liam Foudy	Nikolai Knyzhov	Adam Ginning

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Mike Hardman	Tyson Jost	Liam Foudy	Nikolai Knyzhov	Adam Ginning

Extra Forwards
Normal	PowerPlay	Penalty Kill
Hayden Hodgson, Matthew Strome, Cory Conacher	Hayden Hodgson, Matthew Strome	Cory Conacher

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Helge Grans, Nolan Allan, Cameron Gaunce	Helge Grans	Nolan Allan, Cameron Gaunce

Penalty Shots
Tyson Jost, Liam Foudy, Riley Nash, Seth Griffith, Mike Hardman

Goalie
#1 : Matt Tomkins, #2 : Luke Cavallin

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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
60	74	W1	186	330	516	1637	1538	454	806	1194	0	5

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
60	28	20	3	2	3	4	186	149

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
29	13	10	1	2	1	2	87	74

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
31	15	10	2	0	2	2	99	75

Last 10 Games
W	L	OTW	OTL	SOW	SOL
5	5	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
313	48	15.34%	341	51	85.04%	2

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
509	569	537	42	76	57	47	7

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
974	1769	55.06%	959	1837	52.20%	448	861	52.03%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1570	1132	1369	415	700	358

Last Played Games Show or Hide Column

Filter Tips

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

Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	SO	Link
9 - 2024-09-24	16	Wolfpack	3	Phantoms	4	W			BoxScore
15 - 2024-09-30	36	Phantoms	2	Penguins	1	W			BoxScore
16 - 2024-10-01	51	Penguins	1	Phantoms	0	L	X	X	BoxScore
22 - 2024-10-07	70	Phantoms	1	Wolfpack	2	L			BoxScore
23 - 2024-10-08	89	Griffins	2	Phantoms	3	W	X		BoxScore
24 - 2024-10-09	98	Griffins	4	Phantoms	3	L	X		BoxScore
27 - 2024-10-12	106	Phantoms	3	Bears	4	L	X	X	BoxScore
30 - 2024-10-15	129	Phantoms	5	Thunderbirds	1	W			BoxScore
34 - 2024-10-19	144	Phantoms	2	Penguins	1	W			BoxScore
36 - 2024-10-21	152	Penguins	0	Phantoms	1	W			BoxScore
37 - 2024-10-22	163	Comets	3	Phantoms	1	L			BoxScore
41 - 2024-10-26	186	Penguins	3	Phantoms	2	L			BoxScore
43 - 2024-10-28	195	Phantoms	2	Thunderbirds	5	L			BoxScore
44 - 2024-10-29	209	Bears	1	Phantoms	6	W			BoxScore
50 - 2024-11-04	232	Phantoms	1	Bruins	2	L	X	X	BoxScore
51 - 2024-11-05	249	Phantoms	2	Bruins	3	L			BoxScore
55 - 2024-11-09	261	Phantoms	1	Wolfpack	3	L			BoxScore
57 - 2024-11-11	271	Bears	1	Phantoms	6	W			BoxScore
58 - 2024-11-12	287	Rocket	1	Phantoms	4	W			BoxScore
62 - 2024-11-16	303	IceHogs	1	Phantoms	4	W			BoxScore
65 - 2024-11-19	325	Bears	0	Phantoms	7	W			BoxScore
66 - 2024-11-20	336	Phantoms	4	Bears	0	W			BoxScore
68 - 2024-11-22	341	Phantoms	7	Marlies	1	W			BoxScore
70 - 2024-11-24	351	Phantoms	7	Monsters	0	W			BoxScore
72 - 2024-11-26	367	Phantoms	3	Monsters	2	W			BoxScore
76 - 2024-11-30	389	Bruins	4	Phantoms	3	L	X	X	BoxScore
78 - 2024-12-02	401	Marlies	1	Phantoms	3	W			BoxScore
79 - 2024-12-03	413	Phantoms	1	Penguins	2	L			BoxScore
85 - 2024-12-09	431	Phantoms	4	Penguins	3	W	X		BoxScore
86 - 2024-12-10	446	Checkers	1	Phantoms	6	W			BoxScore
89 - 2024-12-13	463	Checkers	1	Phantoms	3	W			BoxScore
92 - 2024-12-16	472	Phantoms	3	Comets	2	W	X		BoxScore
93 - 2024-12-17	485	Phantoms	7	Crunch	3	W			BoxScore
96 - 2024-12-20	501	Phantoms	4	Bears	1	W			BoxScore
99 - 2024-12-23	515	Wolfpack	4	Phantoms	3	L			BoxScore
100 - 2024-12-24	524	Phantoms	3	Wolfpack	2	W	X	X	BoxScore
101 - 2024-12-25	538	Phantoms	3	Islanders	2	W	X	X	BoxScore
104 - 2024-12-28	552	Senators	2	Phantoms	3	W	X	X	BoxScore
106 - 2024-12-30	562	Phantoms	2	Americans	1	W			BoxScore
107 - 2024-12-31	572	Americans	5	Phantoms	0	L			BoxScore
113 - 2025-01-06	607	Thunderbirds	3	Phantoms	2	L	X		BoxScore
114 - 2025-01-07	620	Islanders	2	Phantoms	1	L			BoxScore
115 - 2025-01-08	629	Phantoms	4	Penguins	2	W			BoxScore
118 - 2025-01-11	635	Phantoms	1	Islanders	7	L			BoxScore
127 - 2025-01-20	680	Monsters	3	Phantoms	6	W			BoxScore
128 - 2025-01-21	698	Wolfpack	5	Phantoms	2	L			BoxScore
134 - 2025-01-27	724	Phantoms	1	Penguins	3	L			BoxScore
135 - 2025-01-28	735	Crunch	3	Phantoms	6	W			BoxScore
136 - 2025-01-29	745	Penguins	6	Phantoms	2	L			BoxScore
139 - 2025-02-01	760	Phantoms	2	Griffins	5	L			BoxScore
141 - 2025-02-03	771	Phantoms	0	Griffins	4	L			BoxScore
142 - 2025-02-04	786	Phantoms	6	IceHogs	4	W			BoxScore
145 - 2025-02-07	803	Phantoms	2	Admirals	6	L			BoxScore
148 - 2025-02-10	819	Islanders	5	Phantoms	3	L			BoxScore
149 - 2025-02-11	833	Islanders	5	Phantoms	1	L			BoxScore
150 - 2025-02-12	842	Phantoms	8	Bears	2	W			BoxScore
156 - 2025-02-18	871	Phantoms	4	Checkers	1	W			BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
157 - 2025-02-19	883	Phantoms	4	Checkers	0	W			BoxScore
162 - 2025-02-24	906	Penguins	3	Phantoms	0	L			BoxScore
164 - 2025-02-26	925	Penguins	1	Phantoms	2	W			BoxScore
167 - 2025-03-01	939	Admirals	-	Phantoms	-
169 - 2025-03-03	949	Crunch	-	Phantoms	-
170 - 2025-03-04	967	Bruins	-	Phantoms	-
176 - 2025-03-10	993	Phantoms	-	Senators	-
177 - 2025-03-11	1008	Phantoms	-	Rocket	-
181 - 2025-03-15	1028	Phantoms	-	Islanders	-
183 - 2025-03-17	1045	Bears	-	Phantoms	-
184 - 2025-03-18	1057	Thunderbirds	-	Phantoms	-
190 - 2025-03-24	1080	Phantoms	-	Crunch	-
191 - 2025-03-25	1100	Bears	-	Phantoms	-
197 - 2025-03-31	1128	Monsters	-	Phantoms	-
198 - 2025-04-01	1140	Phantoms	-	Bears	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	54,862	27,453
Attendance PCT	94.59%	94.67%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
7	2838 - 94.61%	70,763$	2,052,131$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
909,583$	119,800$	0$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	75,392$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
495,342$	33	5,627$	185,691$

Show or Hide Column

	Overall											Home											Visitor
Year	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Regular Season
12	82	52	19	0	3	4	1	3	260	123	137	41	30	7	0	1	1	0	2	154	55	99	41	22	12	0	2	3	1	1	106	68	38	119	260	477	737	0	18	0	96	77	83	2406	0	749	810	838	1588	471	1527	1837	517	74	14.31%	603	52	91.38%	7	1695	2732	62.04%	1368	2286	59.84%	744	1164	63.92%	2302	1643	1674	573	979	526
13	76	46	21	0	2	1	4	2	227	137	90	38	26	11	0	0	0	1	0	123	80	43	38	20	10	0	2	1	3	2	104	57	47	107	227	410	637	0	15	0	82	78	61	2003	0	664	653	672	1513	452	1415	1644	459	78	16.99%	538	59	89.03%	5	1301	2405	54.10%	1185	2141	55.35%	528	1034	51.06%	2139	1532	1560	524	896	483
14	76	34	26	0	1	4	8	3	195	146	49	38	18	14	0	0	2	2	2	100	78	22	38	16	12	0	1	2	6	1	95	68	27	93	195	342	537	1	8	0	64	50	72	1922	0	618	655	633	1696	490	951	1460	360	61	16.94%	361	48	86.70%	1	1379	2420	56.98%	1181	2174	54.32%	569	1092	52.11%	2054	1474	1648	521	919	478
15	82	37	36	0	0	2	5	2	249	220	29	41	23	16	0	0	0	2	0	143	104	39	41	14	20	0	0	2	3	2	106	116	-10	88	249	443	692	0	3	0	92	76	76	2576	0	874	815	874	1931	626	934	1553	429	70	16.32%	372	56	84.95%	1	1530	2746	55.72%	1218	2296	53.05%	680	1232	55.19%	2098	1505	1881	579	976	496
16	82	51	17	0	3	4	5	2	279	150	129	41	28	6	0	1	2	4	0	163	65	98	41	23	11	0	2	2	1	2	116	85	31	124	279	506	785	1	14	0	117	93	61	2383	0	802	808	760	1789	545	1015	1511	418	65	15.55%	408	55	86.52%	3	1573	2597	60.57%	1357	2317	58.57%	689	1164	59.19%	2283	1672	1719	550	964	512
17	72	38	20	0	5	3	3	3	238	141	97	36	17	11	0	4	1	1	2	112	64	48	36	21	9	0	1	2	2	1	126	77	49	98	238	447	685	0	13	0	109	69	52	2152	0	740	703	682	1598	448	820	1360	365	60	16.44%	352	42	88.07%	3	1413	2278	62.03%	1186	2050	57.85%	611	1019	59.96%	2021	1473	1492	479	850	457
18	72	31	32	0	4	2	0	3	230	214	16	36	18	14	0	0	1	0	3	123	98	25	36	13	18	0	4	1	0	0	107	116	-9	75	230	420	650	0	3	0	101	75	50	2134	0	726	685	707	1649	463	862	1306	361	59	16.34%	349	71	79.66%	3	1375	2258	60.89%	1039	1731	60.02%	670	1069	62.68%	2055	1510	1432	463	853	463
19	60	28	20	0	3	2	3	4	186	149	37	29	13	10	0	1	2	1	2	87	74	13	31	15	10	0	2	0	2	2	99	75	24	74	186	330	516	0	5	76	57	47	7	1637	509	569	537	42	1538	454	806	1194	313	48	15.34%	341	51	85.04%	2	974	1769	55.06%	959	1837	52.20%	448	861	52.03%	1570	1132	1369	415	700	358
Total Regular Season	602	317	191	0	21	22	29	22	1864	1280	584	300	173	89	0	7	9	11	11	1005	618	387	302	144	102	0	14	13	18	11	859	662	197	778	1864	3375	5239	2	79	76	718	565	462	17213	509	5742	5666	5208	13302	3949	8330	11865	3222	515	15.98%	3324	434	86.94%	25	11240	19205	58.53%	9493	16832	56.40%	4939	8635	57.20%	16524	11946	12779	4109	7141	3778
Playoff
11	24	16	8	0	0	0	0	0	58	44	14	11	6	5	0	0	0	0	0	26	22	4	13	10	3	0	0	0	0	0	32	22	10	32	58	100	158	0	3	0	15	19	20	587	0	177	185	178	534	146	448	523	193	23	11.92%	198	20	89.90%	2	429	813	52.77%	434	810	53.58%	167	343	48.69%	626	424	614	202	316	155
12	9	5	4	0	0	0	0	0	21	19	2	4	3	1	0	0	0	0	0	9	8	1	5	2	3	0	0	0	0	0	12	11	1	10	21	39	60	0	0	0	7	7	7	222	0	56	67	76	204	47	193	199	92	10	10.87%	74	6	91.89%	1	188	338	55.62%	163	308	52.92%	88	145	60.69%	257	174	220	78	125	65
13	5	1	4	0	0	0	0	0	10	12	-2	2	0	2	0	0	0	0	0	3	5	-2	3	1	2	0	0	0	0	0	7	7	0	2	10	18	28	0	0	0	2	6	2	121	0	48	40	33	114	26	99	107	42	3	7.14%	46	9	80.43%	0	99	172	57.56%	81	175	46.29%	23	57	40.35%	117	79	123	40	59	28
16	11	6	5	0	0	0	0	0	25	27	-2	6	4	2	0	0	0	0	0	16	15	1	5	2	3	0	0	0	0	0	9	12	-3	12	25	44	69	0	0	0	8	6	7	267	0	84	88	78	267	67	125	190	71	5	7.04%	58	8	86.21%	0	175	363	48.21%	171	353	48.44%	76	158	48.10%	273	189	278	86	142	69
17	6	2	4	0	0	0	0	0	13	20	-7	3	0	3	0	0	0	0	0	4	10	-6	3	2	1	0	0	0	0	0	9	10	-1	4	13	26	39	0	0	0	5	5	3	138	0	55	41	42	169	49	116	100	29	3	10.34%	47	7	85.11%	0	80	183	43.72%	85	188	45.21%	37	81	45.68%	125	82	162	47	72	33
Total Playoff	55	30	25	0	0	0	0	0	127	122	5	26	13	13	0	0	0	0	0	58	60	-2	29	17	12	0	0	0	0	0	69	62	7	60	127	227	354	0	3	0	37	43	39	1335	0	420	421	407	1288	335	981	1119	427	44	10.30%	423	50	88.18%	3	971	1869	51.95%	934	1834	50.93%	391	784	49.87%	1400	949	1400	454	716	353