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Philadelphia Flyers
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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	Tyson Jost	0	X				100.00	69	39	81	66	70	79	83	64	72	62	61	63	67	69	68	73	50	64	0
2	Cole Guttman	0	X				100.00	62	37	83	66	63	88	86	64	72	65	63	62	64	66	69	47	50	64	0
3	Danil Gushchin	0		X			100.00	61	36	84	67	62	90	84	66	68	63	65	61	69	63	65	67	50	64	0
4	Alex Barre-Boulet	0	X	X	X		100.00	62	36	85	65	68	87	83	64	70	66	62	61	63	68	70	36	50	64	0
5	Egor Sokolov	0		X	X		98.00	79	40	81	64	88	85	87	63	58	60	62	61	63	65	67	64	50	64	0
6	Seth Griffith	0	X		X		100.00	58	38	81	66	67	76	85	65	78	68	61	62	64	72	77	35	50	64	0
7	Jakob Pelletier	0	X	X			100.00	69	35	92	67	63	81	78	66	71	68	63	62	67	64	65	78	50	64	0
8	Thomas Bordeleau	0	X	X	X		98.00	59	37	78	68	66	87	83	66	74	64	63	62	71	64	65	75	50	64	0
9	Mike Hardman	0	X	X	X		100.00	72	38	90	62	81	79	83	61	59	63	60	64	59	66	68	42	50	63	0
10	Arshdeep Bains	0		X			100.00	64	37	85	63	71	77	84	62	70	64	59	61	62	64	65	42	50	62	0
11	Jeffrey Viel	0		X			100.00	74	81	52	60	81	82	87	59	65	60	58	61	57	68	70	36	50	62	0
12	Konsta Helenius	0	X				100.00	59	37	86	65	68	81	71	63	67	60	59	64	62	61	65	86	50	62	0
13	Skyler Brind'Amour	0	X				100.00	67	38	87	62	79	84	83	58	66	56	61	59	62	66	68	47	50	62	0
14	Tristan Broz	0	X				100.00	66	39	79	62	75	83	70	61	67	60	62	61	64	63	65	69	50	62	0
15	Fredrik Karlstrom	0	X				100.00	74	39	93	60	83	81	79	59	62	56	61	58	64	67	69	54	50	62	0
16	Hayden Hodgson	0			X		100.00	78	65	50	59	85	73	77	57	53	58	56	59	57	69	71	36	50	61	0
17	Nolan Allan	0				X	100.00	70	54	73	65	79	82	83	63	30	64	57	66	49	62	64	77	50	65	0
18	Helge Grans	0				X	100.00	74	40	83	61	87	82	84	62	30	63	56	60	49	63	65	76	50	65	0
19	Cameron Crotty	0				X	100.00	71	40	78	62	80	70	83	59	30	60	58	61	49	66	70	61	50	63	0
20	Nikolai Knyzhov	0				X	100.00	79	42	79	58	88	67	74	55	30	57	56	61	47	67	69	37	50	63	0
21	Hardy Haman Aktell	0				X	99.00	73	40	81	63	83	75	76	62	30	64	52	58	48	67	69	51	50	63	0
Scratches
1	Rodrigo Abols	0	X				83.38	76	39	93	65	88	77	72	64	68	61	62	63	65	69	71	40	50	64	0
2	Matthew Strome	0		X			100.00	79	42	80	59	88	75	80	58	54	57	56	55	58	66	68	56	50	60	0
3	Tristen Nielsen	0		X			100.00	60	40	73	59	69	82	84	56	64	59	58	57	56	65	67	42	50	60	0
4	Trevor Kuntar	0	X	X			100.00	66	43	62	57	75	85	83	56	61	55	54	58	59	64	66	62	50	59	0
5	Matthew Sop	0		X			100.00	62	37	90	58	71	73	63	56	61	59	57	55	58	62	64	43	50	58	0
6	Alex Beaucage	0		X	X		100.00	67	38	90	58	76	75	67	57	53	56	54	55	58	64	66	63	50	58	0
7	Zac Funk	0			X		100.00	67	41	72	58	76	89	61	57	59	55	56	54	57	62	64	44	50	58	0
8	Carson Bantle	0		X			100.00	76	43	71	55	85	69	63	54	50	52	53	56	54	63	65	55	50	57	0
9	Trevor Janicke	0	X				100.00	56	36	95	54	69	63	61	53	58	52	50	51	55	65	67	55	50	54	0
10	Anton Malmstrom	0				X	100.00	77	40	82	55	86	63	65	54	30	53	51	57	45	65	67	42	50	60	0
11	Jeremie Biakabutuka	0				X	100.00	77	39	91	54	86	61	62	53	30	52	50	56	45	63	65	44	50	59	0

	TEAM AVERAGE					99.31	69	41	81	61	77	78	77	60	57	60	58	60	58	65	67	54	50	62

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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
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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	Matt Tomkins	97.00	75	83	78	85	74	73	75	74	73	75	74	71	85	50	50	74	0
2	Kevin Mandolese	100.00	71	79	75	82	70	69	71	70	69	71	70	65	73	47	50	70	0
Scratches
1	Luke Cavallin	100.00	66	73	69	80	65	64	66	65	64	66	65	65	71	43	50	66	0

	TEAM AVERAGE	99.00	71	78	74	82	70	69	71	70	69	71	70	67	76	47	50	70

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Mike Vellucci	64	65	69	70	88	82	58	USA	59	7	1,000,000$

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1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
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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	EG	HT	P/20	PSG	PSS	FW	FT	S1	S2	S3
1	Tyson Jost	Phantoms (Phi)	C	36	15	17	32	18	34	0	46	72	134	33	75	11.19%	15	822	22.85	0	5	5	16	132	1	0	1	5	121	4	0	59.28%	894	0	0	0.78	0	0	0	0	5	3	1
2	Jakob Pelletier	Phantoms (Phi)	C/LW	20	12	20	32	15	8	0	25	65	125	40	74	9.60%	15	450	22.55	0	0	0	0	0	0	0	0	0	1	2	0	73.17%	369	0	1	1.42	0	0	0	0	3	1	6
3	Alex Barre-Boulet	Phantoms (Phi)	C/LW/RW	36	12	18	30	3	12	0	15	53	100	31	86	12.00%	7	739	20.55	3	8	11	27	147	0	0	0	0	34	7	0	52.00%	50	0	0	0.81	1	1	0	0	1	3	2
4	Seth Griffith	Phantoms (Phi)	C/RW	36	9	21	30	11	18	0	33	71	92	36	74	9.78%	8	779	21.66	2	5	7	26	136	0	1	1	3	117	2	1	65.45%	628	1	0	0.77	1	1	0	0	2	1	4
5	Danil Gushchin	Phantoms (Phi)	LW	36	14	13	27	17	8	0	25	50	132	32	93	10.61%	11	733	20.36	5	3	8	35	143	0	0	0	4	105	0	1	52.54%	59	0	1	0.74	0	0	0	0	1	4	1
6	Egor Sokolov	Phantoms (Phi)	LW/RW	36	11	16	27	15	50	10	93	28	109	36	77	10.09%	12	812	22.56	4	0	4	29	160	0	1	1	4	103	2	0	58.93%	56	0	0	0.66	0	1	2	0	2	2	3
7	Cole Guttman	Phantoms (Phi)	C	36	8	18	26	15	8	0	25	59	94	28	71	8.51%	5	743	20.66	3	6	9	18	129	0	1	1	1	89	3	0	58.46%	508	0	0	0.70	0	0	0	0	0	2	0
8	Kailer Yamamoto	Philadelphia Flyers	C/LW/RW	27	8	16	24	13	6	0	10	84	66	33	79	12.12%	5	663	24.56	1	4	5	13	128	1	0	1	3	137	0	2	55.31%	687	0	0	0.72	1	3	0	0	1	2	2
9	Hardy Haman Aktell	Phantoms (Phi)	D	36	1	19	20	15	30	0	44	30	21	10	21	4.76%	43	772	21.45	1	1	2	13	114	0	1	1	0	137	0	0	0.00%	2	0	0	0.52	0	0	0	0	0	1	1
10	Thomas Bordeleau	Phantoms (Phi)	C/LW/RW	20	6	14	20	7	8	0	18	44	75	20	45	8.00%	7	434	21.75	4	3	7	20	90	0	1	1	0	57	0	2	58.90%	163	0	0	0.92	1	1	0	0	2	2	1
11	Rodrigo Abols	Phantoms (Phi)	C	33	9	9	18	8	23	5	29	40	83	24	63	10.84%	2	438	13.28	0	0	0	0	3	0	0	0	1	15	2	0	58.98%	334	0	0	0.82	0	0	0	1	1	0	1
12	Mike Hardman	Phantoms (Phi)	C/LW/RW	36	6	10	16	8	26	0	28	45	60	13	42	10.00%	16	518	14.41	0	0	0	1	5	0	0	0	0	2	2	0	40.00%	10	0	0	0.62	0	0	0	0	1	0	4
13	Cameron Crotty	Phantoms (Phi)	D	36	3	11	14	3	23	5	40	25	34	17	27	8.82%	33	808	22.47	1	5	6	21	132	1	0	1	1	133	0	1	0.00%	1	0	0	0.35	0	0	1	0	0	1	1
14	Helge Grans	Phantoms (Phi)	D	35	3	9	12	8	44	0	55	19	50	17	24	6.00%	45	853	24.39	0	2	2	29	139	1	0	1	2	132	0	0	0.00%	0	0	0	0.28	0	0	0	0	1	1	1
15	Arshdeep Bains	Phantoms (Phi)	LW	36	3	5	8	18	23	5	19	17	26	10	20	11.54%	14	524	14.58	0	0	0	0	3	0	0	0	0	1	0	0	62.50%	16	0	0	0.30	0	0	0	1	1	0	1
16	Anton Malmstrom	Phantoms (Phi)	D	21	2	4	6	9	22	0	20	3	3	1	7	66.67%	17	331	15.78	0	0	0	0	9	0	0	0	0	21	0	0	0.00%	0	0	0	0.36	0	0	0	0	0	0	0
17	Nikolai Knyzhov	Phantoms (Phi)	D	18	2	4	6	10	33	5	35	12	17	2	9	11.76%	14	336	18.68	1	2	3	10	60	0	1	1	0	62	0	0	0.00%	0	0	0	0.36	0	0	0	1	0	2	1
18	Zac Jones	Philadelphia Flyers	D	8	1	3	4	1	6	0	9	11	9	7	15	11.11%	8	205	25.65	1	1	2	7	46	0	0	0	0	35	0	0	0.00%	0	0	0	0.39	0	0	0	0	1	0	0
19	Tristan Broz	Phantoms (Phi)	C	16	1	3	4	2	6	0	7	4	5	5	8	20.00%	0	96	6.00	0	0	0	1	3	0	0	0	0	5	0	0	70.59%	17	0	0	0.83	0	0	0	0	1	0	0
20	Nolan Allan	Phantoms (Phi)	D	2	1	2	3	2	4	0	2	2	10	3	5	10.00%	3	48	24.38	0	1	1	6	9	0	0	0	0	8	0	0	0.00%	0	0	0	1.23	0	0	0	0	0	0	0
21	Hayden Hodgson	Phantoms (Phi)	RW	13	0	3	3	1	24	0	14	11	9	4	8	0.00%	1	137	10.57	0	0	0	2	3	0	0	0	0	0	0	0	25.00%	4	0	0	0.44	0	0	0	0	0	0	0
22	Jeffrey Viel	Phantoms (Phi)	LW	10	1	1	2	3	41	5	17	6	5	3	1	20.00%	7	114	11.46	1	0	1	1	2	0	0	0	0	5	1	0	25.00%	4	0	0	0.35	0	0	0	1	0	0	0
23	Fredrik Karlstrom	Phantoms (Phi)	C	18	0	2	2	1	0	0	10	4	5	1	3	0.00%	0	101	5.65	0	0	0	1	4	0	0	0	0	16	0	0	61.11%	18	0	0	0.39	0	0	0	0	0	0	0
24	Konsta Helenius	Phantoms (Phi)	C	4	0	0	0	-1	0	0	0	0	2	0	0	0.00%	1	23	5.87	0	0	0	0	0	0	0	0	0	2	0	0	27.27%	11	0	0	0.00	0	0	0	0	0	0	0
25	Skyler Brind'Amour	Phantoms (Phi)	C	12	0	0	0	0	2	0	9	5	7	1	3	0.00%	1	115	9.59	0	0	0	0	3	0	0	0	0	2	0	0	50.00%	8	0	0	0.00	0	0	0	0	0	0	0
Team Total or Average				617	128	238	366	202	459	35	628	760	1273	407	930	10.05%	290	11606	18.81	27	46	73	276	1611	4	6	10	24	1351	25	7	60.35%	3839	1	2	0.63	4	7	3	4	23	25	30

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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	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Matt Tomkins	Phantoms (Phi)	36	24	12	0	0.927	1.75	2164	4	6	63	862	0	1	0	1.000	2	36	0	6	2	1
Team Total or Average			36	24	12	0	0.927	1.75	2164	4	6	63	862	0	1	0	1.000	2	36	0	6	2	1

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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
Alex Barre-Boulet	C/LW/RW	28	1997-05-21	No	178 Lbs	5 ft10	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Alex Beaucage	LW/RW	24	2001-07-25	No	192 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Anton Malmstrom	D	25	2000-03-18	No	200 Lbs	6 ft4	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Arshdeep Bains	LW	25	2001-01-09	No	184 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Cameron Crotty	D	26	1999-05-05	No	182 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Carson Bantle	LW	23	2002-01-22	No	194 Lbs	6 ft4	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Cole Guttman	C	26	1999-04-06	No	167 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Danil Gushchin	LW	23	2002-02-06	No	165 Lbs	5 ft8	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Egor Sokolov	LW/RW	25	2000-06-07	No	222 Lbs	6 ft3	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Fredrik Karlstrom	C	28	1998-01-12	No	200 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Hardy Haman Aktell	D	27	1998-07-04	No	198 Lbs	6 ft3	No	No	No	3	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Hayden Hodgson	RW	29	1996-03-02	No	221 Lbs	6 ft2	No	No	No	4	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Helge Grans	D	23	2002-05-10	No	205 Lbs	6 ft4	No	No	No	1	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Jakob Pelletier	C/LW	24	2001-03-07	No	170 Lbs	5 ft9	No	No	No	1	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Jeffrey Viel	LW	28	1997-01-28	No	205 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jeremie Biakabutuka	D	23	2002-03-05	No	198 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Kevin Mandolese	G	25	2000-08-22	No	180 Lbs	6 ft4	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Konsta Helenius	C	19	2006-05-11	No	180 Lbs	5 ft11	No	No	No	4	ELC	Pro & Farm	900,000$	0$	0$	No	Link
Luke Cavallin	G	24	2001-04-29	No	196 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Matt Tomkins	G	31	1994-06-19	No	191 Lbs	6 ft4	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Matthew Sop	LW	22	2003-02-04	No	185 Lbs	6 ft0	No	No	No	2	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Matthew Strome	LW	27	1999-01-06	No	206 Lbs	6 ft4	No	No	No	3	UFA	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	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nikolai Knyzhov	D	27	1998-03-20	No	222 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nolan Allan	D	22	2003-04-28	No	195 Lbs	6 ft2	No	No	No	3	ELC	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Rodrigo Abols (Out of Payroll)	C	30	1996-01-05	No	206 Lbs	6 ft4	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	Yes	Link
Seth Griffith	C/RW	33	1993-01-04	No	190 Lbs	5 ft9	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Skyler Brind'Amour	C	26	1999-07-27	No	195 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Thomas Bordeleau	C/LW/RW	24	2002-01-03	No	180 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Trevor Janicke	C	25	2000-12-25	No	193 Lbs	5 ft10	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Trevor Kuntar	C/LW	24	2001-06-20	No	205 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Tristan Broz	C	23	2002-10-10	No	205 Lbs	6 ft0	No	No	No	4	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Tristen Nielsen	LW	25	2000-02-23	No	192 Lbs	5 ft10	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Tyson Jost	C	27	1998-03-14	No	187 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	780,000$	0$	0$	No	Link / NHL Link
Zac Funk	RW	22	2003-07-20	No	210 Lbs	6 ft0	No	No	No	2	ELC	Pro & Farm	300,000$	0$	0$	No	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
35	25.40	194 Lbs	6 ft1	2.17	439,429$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Egor Sokolov	Thomas Bordeleau	Alex Barre-Boulet	40	1	2	2
2	Danil Gushchin	Cole Guttman	Seth Griffith	30	1	2	2
3	Jakob Pelletier	Tyson Jost	Mike Hardman	20	1	2	2
4	Arshdeep Bains	Tristan Broz	Hayden Hodgson	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Helge Grans	Hardy Haman Aktell	40	1	2	2
2	Nikolai Knyzhov	Cameron Crotty	30	1	2	2
3	Tristan Broz	Skyler Brind'Amour	20	1	2	2
4	Helge Grans	Hardy Haman Aktell	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Egor Sokolov	Thomas Bordeleau	Alex Barre-Boulet	60	1	2	2
2	Danil Gushchin	Cole Guttman	Seth Griffith	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Helge Grans	Hardy Haman Aktell	60	1	2	2
2	Nikolai Knyzhov	Cameron Crotty	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Thomas Bordeleau	Egor Sokolov	60	1	2	2
2	Cole Guttman	Danil Gushchin	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Helge Grans	Hardy Haman Aktell	60	1	2	2
2	Nikolai Knyzhov	Cameron Crotty	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Thomas Bordeleau	60	1	2	2	Helge Grans	Hardy Haman Aktell	60	1	2	2
2	Egor Sokolov	40	1	2	2	Nikolai Knyzhov	Cameron Crotty	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Thomas Bordeleau	Egor Sokolov	60	1	2	2
2	Cole Guttman	Danil Gushchin	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Helge Grans	Hardy Haman Aktell	60	1	2	2
2	Nikolai Knyzhov	Cameron Crotty	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Egor Sokolov	Thomas Bordeleau	Alex Barre-Boulet	Helge Grans	Hardy Haman Aktell

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Egor Sokolov	Thomas Bordeleau	Alex Barre-Boulet	Helge Grans	Hardy Haman Aktell

Extra Forwards
Normal	PowerPlay	Penalty Kill
Konsta Helenius, Fredrik Karlstrom, Jeffrey Viel	Konsta Helenius, Fredrik Karlstrom	Jeffrey Viel

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Nikolai Knyzhov, Cameron Crotty, Helge Grans	Nikolai Knyzhov	Cameron Crotty, Helge Grans

Penalty Shots
Thomas Bordeleau, Egor Sokolov, Cole Guttman, Danil Gushchin, Alex Barre-Boulet

Goalie
#1 : Matt Tomkins, #2 : Kevin Mandolese

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

Custom OT Lines Defensemen
, , , ,

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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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7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
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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
36	48	W1	104	189	293	1014	862	272	456	588	0	6

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	22	12	1	0	1	0	104	63

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
17	10	7	0	0	0	0	59	33

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
19	12	5	1	0	1	0	45	30

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	3	1	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
175	22	12.57%	180	17	90.56%	3

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
308	370	334	5	38	38	26	3

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
703	1148	61.24%	627	1076	58.27%	289	486	59.47%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
963	698	782	239	419	221

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	SO	Link
9 - 2025-08-23	16	Wolfpack	2	Phantoms	1	L			BoxScore
15 - 2025-08-29	36	Phantoms	3	Penguins	1	W			BoxScore
16 - 2025-08-30	51	Penguins	4	Phantoms	2	L			BoxScore
22 - 2025-09-05	70	Phantoms	3	Wolfpack	1	W			BoxScore
23 - 2025-09-06	89	Griffins	2	Phantoms	5	W			BoxScore
24 - 2025-09-07	98	Griffins	2	Phantoms	4	W			BoxScore
27 - 2025-09-10	106	Phantoms	3	Bears	0	W			BoxScore
30 - 2025-09-13	129	Phantoms	1	Thunderbirds	5	L			BoxScore
34 - 2025-09-17	144	Phantoms	2	Penguins	0	W			BoxScore
36 - 2025-09-19	152	Penguins	3	Phantoms	1	L			BoxScore
37 - 2025-09-20	163	Comets	1	Phantoms	4	W			BoxScore
41 - 2025-09-24	186	Penguins	0	Phantoms	3	W			BoxScore
43 - 2025-09-26	195	Phantoms	2	Thunderbirds	0	W			BoxScore
44 - 2025-09-27	209	Bears	3	Phantoms	4	W			BoxScore
50 - 2025-10-03	232	Phantoms	1	Bruins	3	L			BoxScore
51 - 2025-10-04	249	Phantoms	3	Bruins	2	W			BoxScore
55 - 2025-10-08	261	Phantoms	4	Wolfpack	3	W	X	X	BoxScore
57 - 2025-10-10	271	Bears	3	Phantoms	1	L			BoxScore
58 - 2025-10-11	287	Rocket	1	Phantoms	4	W			BoxScore
62 - 2025-10-15	303	IceHogs	0	Phantoms	5	W			BoxScore
65 - 2025-10-18	325	Bears	2	Phantoms	1	L			BoxScore
66 - 2025-10-19	336	Phantoms	0	Bears	3	L			BoxScore
68 - 2025-10-21	341	Phantoms	4	Marlies	3	W			BoxScore
70 - 2025-10-23	351	Phantoms	4	Monsters	1	W			BoxScore
72 - 2025-10-25	367	Phantoms	6	Monsters	2	W			BoxScore
76 - 2025-10-29	389	Bruins	4	Phantoms	2	L			BoxScore
78 - 2025-10-31	401	Marlies	1	Phantoms	5	W			BoxScore
79 - 2025-11-01	413	Phantoms	0	Penguins	2	L			BoxScore
85 - 2025-11-07	431	Phantoms	2	Penguins	0	W			BoxScore
86 - 2025-11-08	446	Checkers	2	Phantoms	8	W			BoxScore
89 - 2025-11-11	463	Checkers	1	Phantoms	8	W			BoxScore
92 - 2025-11-14	472	Phantoms	0	Comets	1	L			BoxScore
93 - 2025-11-15	485	Phantoms	3	Crunch	1	W			BoxScore
96 - 2025-11-18	501	Phantoms	2	Bears	1	W	X		BoxScore
99 - 2025-11-21	515	Wolfpack	2	Phantoms	1	L			BoxScore
100 - 2025-11-22	524	Phantoms	2	Wolfpack	1	W			BoxScore
101 - 2025-11-23	538	Phantoms	-	Islanders	-
104 - 2025-11-26	552	Senators	-	Phantoms	-
106 - 2025-11-28	562	Phantoms	-	Americans	-
107 - 2025-11-29	572	Americans	-	Phantoms	-
113 - 2025-12-05	607	Thunderbirds	-	Phantoms	-
114 - 2025-12-06	620	Islanders	-	Phantoms	-
115 - 2025-12-07	629	Phantoms	-	Penguins	-
118 - 2025-12-10	635	Phantoms	-	Islanders	-
127 - 2025-12-19	680	Monsters	-	Phantoms	-
128 - 2025-12-20	698	Wolfpack	-	Phantoms	-
134 - 2025-12-26	724	Phantoms	-	Penguins	-
135 - 2025-12-27	735	Crunch	-	Phantoms	-
136 - 2025-12-28	745	Penguins	-	Phantoms	-
139 - 2025-12-31	760	Phantoms	-	Griffins	-
141 - 2026-01-02	771	Phantoms	-	Griffins	-
142 - 2026-01-03	786	Phantoms	-	IceHogs	-
145 - 2026-01-06	803	Phantoms	-	Admirals	-
148 - 2026-01-09	819	Islanders	-	Phantoms	-
149 - 2026-01-10	833	Islanders	-	Phantoms	-
150 - 2026-01-11	842	Phantoms	-	Bears	-
Trade Deadline --- Trades can’t be done after this day is simulated!
156 - 2026-01-17	871	Phantoms	-	Checkers	-
157 - 2026-01-18	883	Phantoms	-	Checkers	-
162 - 2026-01-23	906	Penguins	-	Phantoms	-
164 - 2026-01-25	925	Penguins	-	Phantoms	-
167 - 2026-01-28	939	Admirals	-	Phantoms	-
169 - 2026-01-30	949	Crunch	-	Phantoms	-
170 - 2026-01-31	967	Bruins	-	Phantoms	-
176 - 2026-02-06	993	Phantoms	-	Senators	-
177 - 2026-02-07	1008	Phantoms	-	Rocket	-
181 - 2026-02-11	1028	Phantoms	-	Islanders	-
183 - 2026-02-13	1045	Bears	-	Phantoms	-
184 - 2026-02-14	1057	Thunderbirds	-	Phantoms	-
190 - 2026-02-20	1080	Phantoms	-	Crunch	-
191 - 2026-02-21	1100	Bears	-	Phantoms	-
197 - 2026-02-27	1128	Monsters	-	Phantoms	-
198 - 2026-02-28	1140	Phantoms	-	Bears	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	32,160	16,350
Attendance PCT	94.59%	96.18%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
19	2854 - 95.12%	70,962$	1,206,348$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
566,975$	148,800$	148,800$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	66,975$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
1,348,271$	100	5,744$	574,400$

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
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
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
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	70	33	22	0	3	2	6	4	224	172	52	35	17	11	0	1	2	2	2	113	85	28	35	16	11	0	2	0	4	2	111	87	24	90	224	391	615	0	5	0	97	66	52	1949	0	639	669	613	1788	517	953	1381	375	59	15.73%	405	58	85.68%	2	1174	2093	56.09%	1130	2139	52.83%	533	1005	53.03%	1848	1334	1590	482	815	418
20	36	22	12	0	1	0	1	0	104	63	41	17	10	7	0	0	0	0	0	59	33	26	19	12	5	0	1	0	1	0	45	30	15	48	104	189	293	0	6	38	38	26	3	1014	308	370	334	5	862	272	456	588	175	22	12.57%	180	17	90.56%	3	703	1148	61.24%	627	1076	58.27%	289	486	59.47%	963	698	782	239	419	221
Total Regular Season	882	449	293	0	24	32	54	30	2645	1878	767	440	246	141	0	7	13	18	15	1433	922	511	442	203	152	0	17	19	36	15	1212	956	256	1116	2645	4752	7397	4	104	38	1016	786	730	24959	308	8292	8257	7924	19737	5890	11769	17113	4608	740	16.06%	4662	610	86.92%	31	16431	28263	58.14%	13871	24854	55.81%	7131	12681	56.23%	23972	17303	18961	6039	10491	5514
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
19	24	15	9	0	0	0	0	0	75	59	16	11	8	3	0	0	0	0	0	45	27	18	13	7	6	0	0	0	0	0	30	32	-2	30	75	133	208	0	0	0	29	26	18	632	0	196	224	199	654	213	333	464	119	21	17.65%	133	19	85.71%	3	272	734	37.06%	261	797	32.75%	119	367	32.43%	537	373	638	180	284	132
Total Playoff	79	45	34	0	0	0	0	0	202	181	21	37	21	16	0	0	0	0	0	103	87	16	42	24	18	0	0	0	0	0	99	94	5	90	202	360	562	0	3	0	66	69	57	1967	0	616	645	606	1942	548	1314	1583	546	65	11.90%	556	69	87.59%	6	1243	2603	47.75%	1195	2631	45.42%	510	1151	44.31%	1937	1322	2038	635	1001	485