Ligue de Hockey Virtuelle de l'Outaouais

Roster

Player	#	POS	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Kyle MacLean	0	C/LW	100.00	80	54	79	74	78	81	76	70	63	66	64	69	69	59	50	1	50	68	27	2,000,000$/4yrs
Phil Di Giuseppe	0	LW	100.00	71	47	73	73	76	83	78	69	43	65	63	66	68	84	74	1	50	68	32	2,400,000$/1yrs
Cole Reinhardt	0	LW	100.00	74	51	77	71	77	75	74	68	50	64	65	65	68	63	56	1	50	66	26	1,500,000$/2yrs
Curtis Douglas	0	C/LW/RW	100.00	77	79	54	62	88	71	68	65	54	61	59	64	62	54	50	1	50	63	26	1,400,000$/3yrs
Juha Jaaska	0	LW	100.00	55	42	67	64	73	69	54	59	49	57	54	57	59	51	50	1	50	58	28	1,000,000$/1yrs
Joe Fleming	0	RW	100.00	61	61	52	60	67	63	61	57	41	53	51	56	56	51	50	1	50	56	23	1,000,000$/1yrs
Sam Bitten	0	LW	100.00	60	55	56	57	69	67	65	56	41	51	52	51	55	54	50	1	50	55	26	975,000$/3yrs
Lukas Rousek	0	RW	100.00	52	41	61	59	54	63	61	56	42	59	51	54	55	54	50	1	50	55	27	975,000$/2yrs
Keaton Mastrodonato	0	C/LW/RW	100.00	56	40	64	54	59	55	53	52	40	50	50	51	52	52	50	1	50	52	25	1,000,000$/1yrs
Max Crozier	0	D	100.00	63	57	61	72	76	77	67	68	40	66	61	72	67	57	50	1	50	67	26	1,400,000$/4yrs
Josiah Didier	0	D	100.00	61	44	66	62	68	71	70	58	40	51	51	67	57	68	60	1	50	62	33	975,000$/2yrs
Steven Santini	0	D	100.00	63	41	72	63	67	70	68	59	40	54	53	67	58	65	59	1	50	62	31	3,000,000$/1yrs
Noah Warren	0	D	100.00	66	42	69	62	72	62	59	60	40	54	52	64	58	50	50	1	50	60	21	865,000$/1yrs
Jackson van de Leest	0	D	100.00	68	43	69	57	76	62	59	54	40	51	51	65	54	53	50	1	50	59	25	1,000,000$/1yrs
Djibril Touré	0	D	100.00	63	44	60	62	67	60	58	57	40	54	55	63	58	50	50	1	50	59	23	1,000,000$/1yrs
Wyatte Wylie	0	D	100.00	59	41	68	65	63	64	62	56	40	52	52	62	58	54	50	1	50	59	26	1,350,000$/4yrs
Filip Král	0	D	100.00	53	42	63	60	60	61	60	59	40	57	54	56	57	52	50	1	50	57	26	1,000,000$/1yrs
Joe Arntsen	0	D	100.00	61	51	60	60	69	62	60	57	40	51	52	57	56	51	50	1	50	57	23	1,000,000$/1yrs
Scratches
Chase Wouters	0	C	100.00	55	49	61	65	62	69	67	63	60	60	56	53	61	54	50	1	50	59	26
Max McCormick	0	LW	100.00	52	41	63	57	55	61	60	54	41	52	53	52	54	70	63	1	50	55	34	975,000$/2yrs
Ondrej Pavel	0	C	100.00	58	43	56	56	60	60	58	55	41	52	52	54	54	52	50	1	50	54	25	975,000$/2yrs
Jordan Martel	0	RW	100.00	53	40	63	56	55	57	55	52	40	50	51	52	52	55	50	1	50	53	28	1,000,000$/1yrs
Connor Kurth	0	RW	100.00	57	40	58	54	59	52	52	51	40	50	50	52	51	50	50	1	50	52	22	1,250,000$/4yrs
Josh Prokop	0	RW	100.00	53	40	58	56	55	55	53	51	40	50	50	52	52	53	50	1	50	52	26	1,000,000$/1yrs
Riley Hughes	0	C/LW/RW	100.00	54	40	64	54	57	57	55	52	40	50	51	51	52	53	50	1	50	52	26	1,100,000$/4yrs
Seth Helgeson	0	D	100.00	54	41	59	53	62	61	60	52	40	50	50	55	52	70	58	1	50	55	35	975,000$/2yrs
Grant Gabriele	0	D	100.00	55	40	64	57	58	59	56	51	40	50	50	56	52	58	50	1	50	55	29	1,000,000$/1yrs
Grant Hutton	0	D	100.00	54	41	61	54	61	61	59	53	40	51	50	55	52	60	51	1	50	55	30	1,000,000$/1yrs
Ryan Jones	0	D	100.00	55	41	63	54	61	62	59	52	40	51	50	56	52	60	50	1	50	55	30	975,000$/2yrs
Jeremie Bucheler	0	D	100.00	57	40	64	55	62	56	54	52	40	50	50	56	52	53	50	1	50	54	26	1,000,000$/1yrs
Jeremie Biakabutuka	0	D	100.00	56	40	63	55	61	54	52	51	40	50	50	54	52	51	50	1	50	54	24	1,000,000$/1yrs
Dyllan Gill	0	D	100.00	54	40	64	58	56	54	52	52	40	50	51	54	52	50	50	1	50	53	22	1,000,000$/1yrs

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	#	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	AGE	CONTRACT
Matt Villalta	0	100.00	74	66	72	64	71	72	75	70	73	72	59	54	50	1	50	65	27	975,000$/2yrs
Matthew Villalta	0	98.00	74	67	73	64	70	70	73	68	71	72	62	55	50	1	50	64	27	2,600,000$/3yrs
Scratches
Felix Sandström	0	100.00	73	66	65	66	68	67	68	66	67	69	61	57	51	1	50	62	29	975,000$/2yrs
Jaxon Castor	0	100.00	62	59	57	63	60	57	57	54	58	59	57	55	51	1	50	54	29	975,000$/2yrs
Jordan Papirny	0	100.00	68	60	55	59	60	57	57	52	58	61	59	59	52	1	50	54	30	1,000,000$/1yrs

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Joe Sacco	82	76	72	72	86	63	1	USA	57	1	1,000,000$

General Manager

Player Stats

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	SHT	OSB	OSM	SHT%	SB	MP	PPG	PPA	PPP	PKM	GW	GT	FO%	EG	HT	P/GP	PSG	PSS	GSAVG
1	Phil Di Giuseppe	Phantoms (PHI)	LW	15	6	10	16	-2	12	10	31	47	17	34	12.77%	8	23.66	1	3	4	31	1	0	44.88%	0	0	1.07	0	1	0.90
2	Kyle MacLean	Phantoms (PHI)	C/LW	15	5	10	15	-6	9	5	20	57	14	32	8.77%	11	23.18	3	2	5	28	0	0	50.45%	0	0	1.00	1	1	0.81
3	Cole Reinhardt	Phantoms (PHI)	LW	15	4	4	8	-4	0	0	21	44	9	26	9.09%	6	20.14	0	0	0	12	0	0	52.54%	0	0	0.53	0	0	0.57
4	Max Crozier	Phantoms (PHI)	D	15	1	5	6	-9	34	10	20	23	17	14	4.35%	22	25.48	0	2	2	27	0	0	0.00%	0	0	0.40	0	0	-0.11
5	Joe Fleming	Phantoms (PHI)	RW	15	3	2	5	-1	46	20	20	14	3	10	21.43%	5	18.49	1	0	1	0	0	0	20.00%	0	0	0.33	0	0	-0.22
6	Juha Jaaska	Phantoms (PHI)	LW	15	5	0	5	-4	7	5	21	26	7	21	19.23%	2	17.36	0	0	0	13	1	1	30.00%	0	0	0.33	0	0	0.26
7	Steven Santini	Phantoms (PHI)	D	15	1	4	5	-7	6	0	20	20	5	2	5.00%	18	25.82	0	1	1	30	1	0	0.00%	0	0	0.33	0	0	0.15
8	Lukas Rousek	Phantoms (PHI)	RW	15	2	2	4	-2	6	0	20	16	5	8	12.50%	4	16.05	0	0	0	0	0	0	50.00%	0	0	0.27	0	0	0.18
9	Jordan Martel	Phantoms (PHI)	RW	6	0	3	3	0	0	0	4	6	0	6	0.00%	1	11.15	0	0	0	0	0	0	0.00%	0	0	0.50	0	0	0.44
10	Jackson van de Leest	Phantoms (PHI)	D	15	0	2	2	1	2	0	15	7	2	1	0.00%	6	14.69	0	0	0	2	0	0	0.00%	0	0	0.13	0	0	0.14
11	Noah Warren	Phantoms (PHI)	D	15	0	2	2	-1	22	10	15	6	4	3	0.00%	6	19.96	0	0	0	21	0	0	0.00%	0	0	0.13	0	0	-0.14
12	Riley Hughes	Phantoms (PHI)	C/LW/RW	6	2	0	2	2	0	0	7	7	0	0	28.57%	0	10.14	0	0	0	0	1	0	28.57%	0	0	0.33	0	0	0.45
13	Curtis Douglas	Phantoms (PHI)	C/LW/RW	10	0	2	2	-5	30	20	24	11	4	4	0.00%	3	16.01	0	0	0	3	0	0	27.27%	0	0	0.20	0	0	-0.44
14	Max McCormick	Phantoms (PHI)	LW	6	0	2	2	3	0	0	4	6	1	9	0.00%	1	10.36	0	0	0	0	0	0	75.00%	0	0	0.33	0	0	0.52
15	Ondrej Pavel	Phantoms (PHI)	C	5	1	0	1	2	4	0	7	10	2	6	10.00%	1	14.09	0	0	0	0	0	0	46.43%	0	0	0.20	0	0	0.35
16	Connor Kurth	Phantoms (PHI)	RW	6	0	1	1	1	0	0	11	4	3	7	0.00%	0	9.41	0	0	0	5	0	0	60.00%	0	0	0.17	0	0	0.29
17	Keaton Mastrodonato	Phantoms (PHI)	C/LW/RW	15	0	0	0	-5	8	0	18	5	4	7	0.00%	5	16.21	0	0	0	11	0	0	45.54%	0	0	0.00	0	0	-0.16
18	Sam Bitten	Phantoms (PHI)	LW	9	0	0	0	-3	2	0	8	3	2	2	0.00%	0	10.84	0	0	0	6	0	0	66.67%	0	0	0.00	0	0	-0.10
19	Djibril Touré	Phantoms (PHI)	D	9	0	0	0	0	0	0	2	1	0	0	0.00%	1	3.68	0	0	0	0	0	0	0.00%	0	0	0.00	0	0	0.01
20	Filip Král	Phantoms (PHI)	D	9	0	0	0	0	0	0	1	0	0	0	0.00%	0	1.71	0	0	0	0	0	0	0.00%	0	0	0.00	0	0	0.00
21	Joe Arntsen	Phantoms (PHI)	D	9	0	0	0	0	0	0	1	0	0	0	0.00%	0	0.36	0	0	0	0	0	0	0.00%	0	0	0.00	0	0	0.00
22	Josiah Didier	Phantoms (PHI)	D	15	0	0	0	-3	4	0	11	11	3	4	0.00%	9	20.44	0	0	0	21	0	0	0.00%	0	0	0.00	0	0	-0.04
23	Wyatte Wylie	Phantoms (PHI)	D	15	0	0	0	3	2	0	6	7	1	1	0.00%	7	14.03	0	0	0	10	0	0	0.00%	0	0	0.00	0	0	0.10
Team Total or Average			270	30	49	79	-40	194	80	307	331	103	197	9.06%	116	16.52	5	8	13	251	227	4	1	46.68%	737	73	89	0	0	0.35	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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Matt Villalta	Phantoms (PHI)	7	3	4	0	0.880	3.36	357	0	0	20	166	88	0	0.000	0	6	9	0	0	0
2	Matthew Villalta	Phantoms (PHI)	9	1	5	2	0.894	2.81	512	0	2	24	227	128	0	0.000	3	9	0	1	1	0
3	Felix Sandström	Phantoms (PHI)	1	0	0	0	1.000	0.00	34	0	0	0	11	6	0	0.000	0	0	6	0	0	0
Team Total or Average		17	4	9	2	0.891	2.92	903	0	2	44	404	222	0	0.000	3	15	15	1	1	0

Salary

Player Name	POS	Age	Cap Hit	2017-18	2018-19	2019-20	2020-21	2021-22
Chase Wouters	C	26	0$	RFA
Cole Reinhardt	LW	26	1,500,000$	1,500,000$	1,500,000$	UFA
Connor Kurth	RW	22	1,250,000$	1,250,000$	1,250,000$	1,250,000$	1,250,000$	RFA
Curtis Douglas	C/LW/RW	26	1,400,000$	1,400,000$	1,400,000$	1,400,000$	UFA
Djibril Touré	D	23	1,000,000$	1,000,000$	RFA
Dyllan Gill	D	22	1,000,000$	1,000,000$	RFA
Felix Sandström	G	29	975,000$	975,000$	975,000$	UFA
Filip Král	D	26	1,000,000$	1,000,000$	UFA
Grant Gabriele	D	29	1,000,000$	1,000,000$	UFA
Grant Hutton	D	30	1,000,000$	1,000,000$	UFA
Jackson van de Leest	D	25	1,000,000$	1,000,000$	RFA
Jaxon Castor	G	29	975,000$	975,000$	975,000$	UFA
Jeremie Biakabutuka	D	24	1,000,000$	1,000,000$	RFA
Jeremie Bucheler	D	26	1,000,000$	1,000,000$	RFA
Joe Arntsen	D	23	1,000,000$	1,000,000$	RFA
Joe Fleming	RW	23	1,000,000$	1,000,000$	RFA
Jordan Martel	RW	28	1,000,000$	1,000,000$	UFA
Jordan Papirny	G	30	1,000,000$	1,000,000$	UFA
Josh Prokop	RW	26	1,000,000$	1,000,000$	RFA
Josiah Didier	D	33	975,000$	975,000$	975,000$	UFA
Juha Jaaska	LW	28	1,000,000$	1,000,000$	UFA
Keaton Mastrodonato	C/LW/RW	25	1,000,000$	1,000,000$	RFA
Kyle MacLean	C/LW	27	2,000,000$	2,000,000$	2,000,000$	2,000,000$	2,000,000$	UFA
Lukas Rousek	RW	27	975,000$	975,000$	975,000$	UFA
Matt Villalta	G	27	975,000$	975,000$	975,000$	UFA
Matthew Villalta	G	27	2,600,000$	2,600,000$	2,600,000$	2,600,000$	UFA
Max Crozier	D	26	1,400,000$	1,400,000$	1,400,000$	1,400,000$	1,400,000$	UFA
Max McCormick	LW	34	975,000$	975,000$	975,000$	UFA
Noah Warren	D	21	865,000$	975,000$	RFA
Ondrej Pavel	C	25	975,000$	975,000$	975,000$	UFA
Phil Di Giuseppe	LW	32	2,400,000$	2,400,000$	UFA
Riley Hughes	C/LW/RW	26	1,100,000$	1,100,000$	1,100,000$	1,100,000$	1,100,000$	UFA
Ryan Jones	D	30	975,000$	975,000$	975,000$	UFA
Sam Bitten	LW	26	975,000$	975,000$	975,000$	975,000$	UFA
Seth Helgeson	D	35	975,000$	975,000$	975,000$	UFA
Steven Santini	D	31	3,000,000$	3,000,000$	UFA
Wyatte Wylie	D	26	1,350,000$	1,350,000$	1,350,000$	1,350,000$	1,350,000$	UFA

Lines

Forward Lines
# - Phil Di Giuseppe	# - Kyle MacLean	# - Joe Fleming
# - Cole Reinhardt	# - Phil Di Giuseppe	# - Lukas Rousek
# - Juha Jaaska	# - Keaton Mastrodonato	# - Kyle MacLean
# - Curtis Douglas	# - Cole Reinhardt	# - Juha Jaaska

Defensive Pairings
# - Max Crozier	# - Steven Santini
# - Josiah Didier	# - Noah Warren
# - Jackson van de Leest	# - Wyatte Wylie

1st Power Play Unit
# - Phil Di Giuseppe		# - Kyle MacLean		# - Joe Fleming
# - Max Crozier			# - Steven Santini

2nd Power Play Unit
# - Cole Reinhardt		# - Phil Di Giuseppe		# - Lukas Rousek
# - Josiah Didier			# - Noah Warren

Goalies
# - Matthew Villalta		# - Matt Villalta

Team Stats

Show or Hide Column

Filter Tips

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

#	VS Team	GP	W	L	OTW	OTL	SOL	GF	GA	Diff	P	PCT	G	A	TP	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT	GF%	SH%	SV%	PDO	PDOBRK
1	Gulls	2	1	0	0	0	1	2	2	0	3	0.750	2	4	6	0	11	8	10	2	36	87	137	104	5	19	7	13	49	6	0	0.00%	4	1	75.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	66.7%	5.6%	89.5%	95.0	Unlucky
2	Moose	1	0	0	1	0	0	1	0	1	2	1.000	1	2	3	1	11	8	10	2	13	87	137	104	5	14	2	14	17	0	0	0.00%	2	0	100.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	100.0%	7.7%	100.0%	107.7	DULL
3	Bruins	3	1	2	0	0	0	12	15	-3	2	0.333	12	20	32	0	11	8	10	2	71	87	137	104	5	107	31	44	46	7	4	57.14%	7	2	71.43%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	38.1%	16.9%	86.0%	102.9	FUN
4	Americans	1	0	0	0	1	0	1	2	-1	1	0.500	1	1	2	0	11	8	10	2	12	87	137	104	5	22	7	4	21	1	0	0.00%	2	0	100.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	33.3%	8.3%	90.9%	99.2	Unlucky
5	Monsters	1	0	1	0	0	0	2	3	-1	0	0.000	2	2	4	0	11	8	10	2	15	87	137	104	5	34	12	4	22	0	0	0.00%	2	1	50.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	50.0%	13.3%	91.2%	104.5	LUCKY
6	Stars	1	1	0	0	0	0	3	2	1	2	1.000	3	4	7	0	11	8	10	2	40	87	137	104	5	14	10	6	27	4	0	0.00%	3	1	66.67%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	75.0%	7.5%	85.7%	93.2	Unlucky
7	Islanders	2	0	2	0	0	0	4	6	-2	0	0.000	4	6	10	0	11	8	10	2	64	87	137	104	5	72	21	28	44	4	0	0.00%	9	3	66.67%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	57.1%	6.3%	91.7%	97.9	DULL
8	Marlies	1	0	1	0	0	0	0	4	-4	0	0.000	0	0	0	0	11	8	10	2	11	87	137	104	5	39	10	21	17	0	0	0.00%	3	1	66.67%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	0.0%	0.0%	89.7%	89.7	Unlucky
9	Hershey Bears	3	0	3	0	0	0	5	11	-6	0	0.000	5	10	15	0	11	8	10	2	69	87	137	104	5	83	16	60	64	7	1	14.29%	5	2	60.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	30.8%	7.2%	86.7%	94.0	Unlucky
	_Vs Division	5	1	7	0	0	0	13	21	-8	2	0.200	13	21	34	0	11	8	10	2	94	87	137	104	5	168	48	69	84	8	4	50.00%	12	3	75.00%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	33.3%	13.8%	87.5%	101.3	FUN
	_Vs Conference	11	1	9	0	1	0	24	41	-17	3	0.136	24	39	63	0	11	8	10	2	242	87	137	104	5	357	97	161	214	19	5	26.32%	28	9	67.86%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	37.3%	9.9%	88.5%	98.4	FUN
	_Since Last GM Reset	15	3	9	1	1	1	30	45	-15	10	0.333	30	49	79	1	11	8	10	2	331	87	137	104	5	404	116	194	307	29	5	17.24%	37	11	70.27%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	42.4%	9.1%	88.9%	97.9	FUN
	Total	15	3	9	1	1	1	30	45	-15	10	0.333	30	49	79	1	11	8	10	2	331	87	137	104	5	404	116	194	307	29	5	17.24%	37	11	70.27%	125	268	46.64%	132	288	45.83%	87	178	48.88%	273	123	307	153	324	164	42.4%	9.1%	88.9%	97.9	FUN

	Puck Time
Offensive Zone	18
Neutral Zone	21
Defensive Zone	20

	Puck Time
Offensive Zone Start	268
Neutral Zone Start	178
Defensive Zone Start	288

	Puck Time
With Puck	29
Without Puck	30

	Faceoffs
Faceoffs Won	344
Faceoffs Lost	390

	Team Average Shots after	League Average Shots after
1st Period	5.8	9.57
2nd Period	14.9	20.31
3rd Period	21.9	30.68
Overtime	22.2	31.4

Goals in	Team Average Goals after	League Average Goals after
1st Period	0.7	0.64
2nd Period	1.3	1.65
3rd Period	1.9	2.67
Overtime	2.1	2.83


Even Strenght Goal	25
PP Goal	5
PK Goal	0
Empty Net Goal	0

	Home	Away
Win	2	2
Lost	4	5
Overtime Lost	2	0


PP Attempt	29
PP Goal	5
PK Attempt	37
PK Goal Against	11

	Home
Shots For	22.1
Shots Against	26.9
Goals For	2.0
Goals Against	3.0
Hits	20.5
Shots Blocked	7.7
Pim	12.9

Schedule

Date	Matchup			Result	Detail
Sun, Oct 11	PHI	@	WAS	PHI2,WAS4	RECAP
Tue, Oct 13	DAL	@	PHI	DAL2,PHI3	RECAP
Thu, Oct 15	PHI	@	ANA	PHI2,ANA1	RECAP
Fri, Oct 16	NYI	@	PHI	NYI3,PHI2	RECAP
Sun, Oct 18	PHI	@	NYI	PHI2,NYI3	RECAP
Tue, Oct 20	BOS	@	PHI	BOS4,PHI5	RECAP
Thu, Oct 22	WAS	@	PHI	WAS4,PHI1	RECAP
Sat, Oct 24	PHI	@	WAS	PHI2,WAS3	RECAP
Mon, Oct 26	BOS	@	PHI	BOS7,PHI5	RECAP
Wed, Oct 28	PHI	@	CLB	PHI2,CLB3	RECAP
Fri, Oct 30	PHI	@	BOS	PHI2,BOS4	RECAP
Sun, Nov 1	BUF	@	PHI	BUF2,PHI1 (OT)	RECAP
Tue, Nov 3	ANA	@	PHI	ANA1,PHI0 (SO)	RECAP
Thu, Nov 5	PHI	@	WPG	PHI1,WPG0 (OT)	RECAP
Sat, Nov 7	TOR	@	PHI	TOR4,PHI0	RECAP
Mon, Nov 9	PHI	@	NJD
Wed, Nov 11	PHI	@	EDM
Fri, Nov 13	VAN	@	PHI
Sun, Nov 15	PHI	@	VAN
Tue, Nov 17	CHI	@	PHI
Thu, Nov 19	PHI	@	TOR
Sat, Nov 21	EDM	@	PHI
Mon, Nov 23	NYR	@	PHI
Wed, Nov 25	PHI	@	LOS
Fri, Nov 27	PHI	@	OTT
Sun, Nov 29	FLO	@	PHI
Mon, Nov 30	PHI	@	CHI
Wed, Dec 2	PHI	@	MIN
Thu, Dec 3	PHO	@	PHI
Sun, Dec 6	PIT	@	PHI
Mon, Dec 7	PHI	@	FLO
Wed, Dec 9	PHI	@	MTL
Fri, Dec 11	TAM	@	PHI
Sun, Dec 13	CAL	@	PHI
Tue, Dec 15	PHI	@	CAR
Thu, Dec 17	PHI	@	TAM
Fri, Dec 18	NYI	@	PHI
Mon, Dec 21	DAL	@	PHI
Wed, Dec 23	PHI	@	FLO
Thu, Dec 24	PHI	@	NYI
Sat, Dec 26	MIN	@	PHI
Mon, Dec 28	NJD	@	PHI
Wed, Dec 30	PHI	@	WAS
Thu, Dec 31	CLB	@	PHI
Sat, Jan 2	PHI	@	STL
Mon, Jan 4	PHI	@	BUF
Tue, Jan 5	S J	@	PHI
Thu, Jan 7	PHI	@	CAL
Sat, Jan 9	WPG	@	PHI
Sun, Jan 10	PHI	@	BOS
Tue, Jan 12	STL	@	PHI
Thu, Jan 14	PHI	@	DET
Fri, Jan 15	DET	@	PHI
Sun, Jan 17	PHI	@	DET
Tue, Jan 19	FLO	@	PHI
Thu, Jan 21	PHI	@	CHI
Fri, Jan 22	CHI	@	PHI
Sun, Jan 24	PHI	@	DAL
Tue, Jan 26	MTL	@	PHI
Wed, Jan 27	PHI	@	S J
Fri, Jan 29	PHI	@	FLO
Sat, Jan 30	NAS	@	PHI
Mon, Feb 1	PHI	@	NYR
Wed, Feb 3	NYR	@	PHI
Fri, Feb 5	PHI	@	CAR
Sat, Feb 6	OTT	@	PHI
Mon, Feb 8	PHI	@	ANA
Tue, Feb 9	PHI	@	NYR
Thu, Feb 11	COL	@	PHI
Sun, Feb 14	WAS	@	PHI
Tue, Feb 16	PHI	@	PIT
Wed, Feb 17	SEA	@	PHI
Fri, Feb 19	PHI	@	SEA
Sat, Feb 20	PHI	@	PHO
Mon, Feb 22	LOS	@	PHI
Wed, Feb 24	PHI	@	PIT
Thu, Feb 25	SEA	@	PHI
Sun, Feb 28	PHI	@	COL
Mon, Mar 1	PIT	@	PHI
Thu, Mar 4	PHI	@	NAS
Sat, Mar 6	DAL	@	PHI
Thu, Mar 11	CAR	@	PHI
Mon, Mar 15	DAL	@	PHI
Trade Deadline --- Trades can�t be done after this day is simulated!
Thu, Mar 18	CAR	@	PHI

Finance

Salary Cap
Players Total Salaries	Retained Salary	Total Cap Hit	Estimated Cap Space
4,372,500$	0$	0$	75,000,000$

Arena	About us
	Name
	City	Lehigh Valley
	Capacity	3000
	Season Ticket Holders	10%

Arena Capacity - Ticket Price Attendance - %

Arena Capacity	2000	1000
Ticket Price	35$	18$	$	$	$
Attendance	0	0
Attendance PCT	0.00%	0.00%	0.00%	0.00%	0.00%

Income

Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
34	0 - 0.00%	0$	0$	3000	100

Expenses
Players Total Salaries	Players Total Average Salaries	Coaches Salaries	Special Salary Cap Value
4,372,500$	4,372,500$	0$	0$

Year To Date Expenses	Salary Cap Per Days	Salary Cap To Date	Luxury Taxe Total
961,756$	0$	782,739$	0$

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	156	33,164$	4,410,812$

Team Total Estimate
Estimated Season Expenses	Estimated Season Salary Cap	Current Bank Account	Projected Bank Account
4,410,812$	0$	0$	0$

Sponsors
TV Rights	Primary Sponsor	Secondary Sponsor	Secondary Sponsor

Depth Chart

Rookie

Injured

Cold Streak

Hot Streak

Left Wing

Center

Right Wing

Defense #1

Defense #2

Goalie

Transactions

Injuries

No Injury or Suspension.

Game Center

Phantoms4-9-2, 10pts

10Final

Moose7-6-2, 16pts

Marlies13-1-1, 27pts

40Final

Phantoms4-9-2, 10pts

Marlies13-1-1, 27pts

Sun, Nov 08

Phantoms4-9-2, 10pts

Stars2-12-1, 5pts

Wed, Oct 14

Phantoms4-9-2, 10pts

Fri, Oct 16

Gulls4-7-4, 12pts

TRANSACTIONS

Team Info


	Head Coach	Joe Sacco
	Division	Atlantic Division
	City	Lehigh Valley
	Stadium Capacity	3,000

Phantoms Affiliation


	General Manager	Luc Gregoire
	Head Coach	Ray Bennett
	Stadium	Wachovia Center
	Capacity	20,523

Team Leaders

GOALS Phil Di Giuseppe Phantoms	6 GOALS
POINTS Phil Di Giuseppe Phantoms	16 POINTS
WINS Matt Villalta Phantoms	3 WINS
Expanded Player Leaderboard

Team Stats

Goals For 30 2.00 GFG	Goals Against 45 3.00 GAA
Power Play Percentage 17.2% 5 GF	Penalty Kill Percentage 70.3% 11 GA
Expanded Team Stats

Team Captain - Alternate Captains

Captain

Alternate Captain