Maple Leafs
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance

Game Center
	Marlies 3-7-0, 6pts	10	FINAL	6	Griffins 4-6-1, 9pts

Team Stats
W2	Streak	L4
1-4-0	Home Record	2-2-0
2-3-0	Home Record	2-4-1
3-7-0	Last 10 Games	4-6-0
5.40	Goals Per Game	6.64
6.50	Goals Against Per Game	7.82
45.71%	Power Play Percentage	45.45%
56.10%	Penalty Kill Percentage	35.85%

Reign
3-5-1, 7pts

FINAL

Marlies
3-7-0, 6pts

Team Stats
L1	Streak	W2
3-2-0	Home Record	1-4-0
0-3-1	Home Record	2-3-0
3-5-1	Last 10 Games	3-7-0
4.33	Goals Per Game	5.40
4.89	Goals Against Per Game	6.50
33.33%	Power Play Percentage	45.71%
63.89%	Penalty Kill Percentage	56.10%

Marlies
3-7-0, 6pts

Day 14

Roadrunners
4-4-0, 8pts

Team Stats
W2	Streak	L1
1-4-0	Home Record	2-3-0
2-3-0	Away Record	2-1-0
3-7-0	Last 10 Games	4-4-0
5.40	Goals Per Game	6.88
6.50	Goals Against Per Game	6.88
45.71%	Power Play Percentage	54.55%
56.10%	Penalty Kill Percentage	52.63%

Roadrunners
4-4-0, 8pts

Day 15

Marlies
3-7-0, 6pts

Team Stats
L1	Streak	W2
2-3-0	Home Record	1-4-0
2-1-0	Away Record	2-3-0
4-4-0	Last 10 Games	3-7-0
6.88	Goals Per Game	5.40
7.88	Goals Against Per Game	5.40
54.55%	Power Play Percentage	45.71%
52.63%	Penalty Kill Percentage	56.10%

Thunderbirds
7-2-0, 14pts

Day 17

Marlies
3-7-0, 6pts

Team Stats
W4	Streak	W2
4-1-0	Home Record	1-4-0
3-1-0	Away Record	2-3-0
7-2-0	Last 10 Games	3-7-0
6.56	Goals Per Game	5.40
4.67	Goals Against Per Game	5.40
34.15%	Power Play Percentage	45.71%
65.85%	Penalty Kill Percentage	56.10%

Team Leaders
	Goals Noel Hoefenmayer 5	Assists Noel Hoefenmayer 14

	Points Noel Hoefenmayer 19	Plus/Minus Noel Hoefenmayer 2

Team Stats
Goals For 54 5.40 GFG	Shots For 362 36.20 Avg	Power Play Percentage 45.7% 16 GF	Offensive Zone Start 32.8%
Goals Against 65 6.50 GAA	Shots Against 314 31.40 Avg	Penalty Kill Percentage 56.1%% 18 GA	Defensive Zone Start 26.9%

Team Info
	General Manager	Phil VendorMolen
	Coach	Benoit Grouix
	Division	Division 5
	Conference	Conference 2
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	0
	Season Tickets	1,500
Roster Info
	Pro Team	24
	Farm Team	18
	Contract Limit	42 / 100
	Prospects	149

Show or Hide Columns

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	Age	Contract	Salary
1	Oliver Wahlstrom			X		100.00	76	44	91	80	78	58	55	70	37	61	57	65	61	62	63	64	56	63	0	24	1	1,177,000$
2	James Malatesta (R)		X			100.00	99	97	86	66	65	56	69	68	25	64	71	64	25	45	45	71	52	62	0	21	3	841,667$
3	Elmer Soderblom (R)	X	X			100.00	94	93	95	60	93	66	68	58	73	53	58	73	55	45	45	64	50	61	0	23	2	925,000$
4	Jonathan Gruden		X			100.00	92	92	88	63	65	52	75	63	38	50	58	78	25	45	45	64	60	60	0	24	3	1,092,000$
5	Olle Lycksell			X		99.00	59	40	89	65	60	55	74	67	37	68	58	57	25	46	46	61	59	59	0	25	2	875,000$
6	Scott Reedy	X				100.00	83	76	99	64	76	55	55	59	74	47	67	67	64	44	44	65	54	59	0	25	3	1,253,000$
7	Ben King (R)	X		X		100.00	78	73	90	62	73	65	67	59	74	53	61	65	58	44	44	63	54	59	0	22	3	790,000$
8	Andre Lee	X	X			100.00	79	79	80	66	79	61	63	55	69	46	60	64	57	44	44	61	53	58	0	24	1	864,515$
9	Judd Caulfield (R)			X		100.00	81	77	89	61	77	64	67	56	50	52	56	66	53	44	44	61	52	58	0	23	1	750,000$
10	Aidan McDonough		X			100.00	81	75	95	63	75	62	65	54	50	47	57	65	54	44	44	61	52	57	0	24	1	750,000$
11	Maxim Cajkovic (R)			X		100.00	73	67	87	59	67	51	50	59	50	56	58	62	55	44	44	60	55	56	0	23	1	750,000$
12	Isaac Ratcliffe		X			100.00	82	86	74	64	86	66	71	47	50	41	48	64	46	44	44	55	54	56	0	25	3	1,088,000$
13	Travis Barron		X			100.00	73	75	68	62	75	70	75	52	50	47	53	61	50	44	44	57	51	56	0	26	3	973,000$
14	Philip Kemp				X	100.00	76	76	76	62	76	76	84	48	25	40	40	61	38	44	44	53	57	59	0	25	3	1,135,000$
15	Santtu Kinnunen				X	100.00	68	60	88	65	60	77	84	50	25	43	41	58	39	44	44	54	52	58	0	25	2	925,000$
16	Noel Hoefenmayer				X	100.00	68	70	62	65	70	68	72	55	25	44	52	58	47	44	44	55	54	58	0	25	2	750,000$
17	Dawson Barteaux				X	100.00	74	65	96	67	65	59	61	52	25	45	45	61	43	44	44	55	57	57	0	24	1	750,000$
18	Cole Krygier				X	100.00	76	73	84	60	73	61	65	46	25	38	39	61	37	44	44	51	51	56	0	24	1	750,000$
Scratches
1	Ben McCartney		X			100.00	66	67	64	64	67	60	62	55	50	58	48	58	46	44	44	56	42	55	0	23	1	880,643$
2	Blade Jenkins		X			100.00	78	72	93	64	72	46	45	54	50	45	58	64	55	44	44	59	42	55	0	24	3	971,000$
3	Mitchell Hoelscher	X				100.00	72	65	89	63	65	56	57	52	65	55	44	60	42	44	44	54	38	54	0	24	2	750,000$
4	Robert Mastrosimone (R)	X	X			100.00	64	59	74	60	59	59	61	52	65	53	47	56	45	44	44	53	47	53	0	23	1	750,000$

	TEAM AVERAGE					99.95	77	72	84	64	72	61	66	56	47	50	53	63	46	45	45	59	52	58

Show or Hide Columns

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	Age	Contract	Salary
1	Kevin Mandolese	100.00	50	45	56	85	51	52	50	55	53	52	30	44	44	51	59	54	0	24	3	942,000$
2	Keith Petruzzelli	100.00	45	47	59	83	42	43	50	52	45	46	30	44	44	47	59	50	0	25	1	802,110$
Scratches

	TEAM AVERAGE	100.00	48	46	58	84	47	48	50	54	49	49	30	44	44	49	59	52

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Benoit Grouix	60	47	73	37	56	47	53	CAN	55	1	750,000$

Show or Hide Columns

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	PKA	PKP	PKM	GT	FO%	FOT	GA	TA	P/20	FL	FT	S1	S2	S3
1	Noel Hoefenmayer	Marlies (TOR)	D	10	5	14	19	2	54	10	12	14	73	29	48	6.85%	11	197	19.74	4	6	10	13	26	1	1	16	0	0%	0	7	5	1.92	1	1	2	3	0
2	Olle Lycksell	Marlies (TOR)	RW	10	5	13	18	-2	15	15	8	5	57	26	35	8.77%	3	197	19.74	0	2	2	1	1	0	0	0	1	30.00%	10	11	4	1.82	1	2	2	0	2
Team Total or Average				20	10	27	37	0	69	25	20	19	130	55	83	7.69%	14	394	19.74	4	8	12	14	27	1	1	16	1	30.00%	10	18	9	1.87	2	3	4	3	2

Show or Hide Columns

Filter Tips

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

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

Show or Hide Columns

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	Age	Birthday	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Salary Cap Year 2	Salary Cap Year 3	Salary Cap Year 4	Salary Cap Year 5	Salary Cap Year 6	Salary Cap Year 7	Salary Cap Year 8	Salary Cap Year 9	Salary Cap Year 10	No Trade Year 2	No Trade Year 3	No Trade Year 4	No Trade Year 5	No Trade Year 6	No Trade Year 7	No Trade Year 8	No Trade Year 9	No Trade Year 10	Link
Aidan McDonough	Marlies (TOR)	LW	24	1999-11-06	USA	No	201 Lbs	6 ft2	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Andre Lee	Marlies (TOR)	C/LW	24	2000-07-26	SWE	No	205 Lbs	6 ft5	No	No	N/A	No	No	1		False	False	Pro & Farm	864,515$	864,515$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Ben King	Marlies (TOR)	C/RW	22	2002-05-15	BC	Yes	198 Lbs	6 ft2	No	No	Prospect	No	No	3	2024-09-17	False	False	Pro & Farm	790,000$	790,000$	0$	0$	No	790,000$	790,000$	-	-	-	-	-	-	-	790,000$	790,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Ben McCartney	Marlies (TOR)	LW	23	2001-07-13	MAN	No	182 Lbs	6 ft0	No	No	N/A	No	No	1		False	False	Pro & Farm	880,643$	880,643$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Blade Jenkins	Marlies (TOR)	LW	24	2000-08-11	USA	No	195 Lbs	6 ft1	No	No	N/A	No	No	3		False	False	Pro & Farm	971,000$	971,000$	0$	0$	No	971,000$	971,000$	-	-	-	-	-	-	-	971,000$	971,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Cole Krygier	Marlies (TOR)	D	24	2000-05-05	USA	No	192 Lbs	6 ft3	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Dawson Barteaux	Marlies (TOR)	D	24	2000-01-12	MAN	No	170 Lbs	6 ft1	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Elmer Soderblom	Marlies (TOR)	C/LW	23	2001-05-07	SWE	Yes	246 Lbs	6 ft8	No	No	N/A	No	No	2		False	False	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	-	-	-	-	-	-	-	-	925,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Isaac Ratcliffe	Marlies (TOR)	LW	25	1999-02-15	ONT	No	225 Lbs	6 ft6	No	No	N/A	No	No	3		False	False	Pro & Farm	1,088,000$	1,088,000$	0$	0$	No	1,088,000$	1,088,000$	-	-	-	-	-	-	-	1,088,000$	1,088,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
James Malatesta	Marlies (TOR)	LW	21	2003-05-31	QUE	Yes	178 Lbs	5 ft9	No	No	N/A	No	No	3		False	False	Pro & Farm	841,667$	841,667$	0$	0$	No	841,667$	841,667$	-	-	-	-	-	-	-	841,667$	841,667$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-
Jonathan Gruden	Marlies (TOR)	LW	24	2000-05-04	USA	No	169 Lbs	6 ft0	No	No	N/A	No	No	3		False	False	Pro & Farm	1,092,000$	1,092,000$	0$	0$	No	1,092,000$	1,092,000$	-	-	-	-	-	-	-	1,092,000$	1,092,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Judd Caulfield	Marlies (TOR)	RW	23	2001-03-19	USA	Yes	207 Lbs	6 ft3	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Keith Petruzzelli	Marlies (TOR)	G	25	1999-02-09	USA	No	190 Lbs	6 ft6	No	No	N/A	No	No	1		False	False	Pro & Farm	802,110$	802,110$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Kevin Mandolese	Marlies (TOR)	G	24	2000-08-22	QUE	No	200 Lbs	6 ft5	No	No	N/A	No	No	3		False	False	Pro & Farm	942,000$	942,000$	0$	0$	No	942,000$	942,000$	-	-	-	-	-	-	-	942,000$	942,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Maxim Cajkovic	Marlies (TOR)	RW	23	2001-01-03	SLO	Yes	185 Lbs	5 ft11	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Mitchell Hoelscher	Marlies (TOR)	C	24	2000-01-27	ONT	No	176 Lbs	6 ft0	No	No	N/A	No	No	2		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	-	-	-	-	-	-	-	-	750,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Noel Hoefenmayer	Marlies (TOR)	D	25	1999-01-06	ONT	No	192 Lbs	6 ft0	No	No	N/A	No	No	2		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	750,000$	-	-	-	-	-	-	-	-	750,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Oliver Wahlstrom	Marlies (TOR)	RW	24	2000-06-13	USA	No	211 Lbs	6 ft2	No	No	N/A	No	No	1		False	False	Pro & Farm	1,177,000$	1,177,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Olle Lycksell	Marlies (TOR)	RW	25	1999-08-24	SWE	No	165 Lbs	5 ft10	No	No	N/A	No	No	2		False	False	Pro & Farm	875,000$	875,000$	0$	0$	No	875,000$	-	-	-	-	-	-	-	-	875,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Philip Kemp	Marlies (TOR)	D	25	1999-02-12	USA	No	200 Lbs	6 ft3	No	No	N/A	No	No	3		False	False	Pro & Farm	1,135,000$	1,135,000$	0$	0$	No	1,135,000$	1,135,000$	-	-	-	-	-	-	-	1,135,000$	1,135,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Robert Mastrosimone	Marlies (TOR)	C/LW	23	2001-01-24	USA	Yes	163 Lbs	5 ft10	No	No	N/A	No	No	1		False	False	Pro & Farm	750,000$	750,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-
Santtu Kinnunen	Marlies (TOR)	D	25	1999-03-25	FIN	No	154 Lbs	6 ft2	No	No	N/A	No	No	2		False	False	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	-	-	-	-	-	-	-	-	925,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Scott Reedy	Marlies (TOR)	C	25	1999-04-04	USA	No	205 Lbs	6 ft2	No	No	N/A	No	No	3		False	False	Pro & Farm	1,253,000$	1,253,000$	0$	0$	No	1,253,000$	1,253,000$	-	-	-	-	-	-	-	1,253,000$	1,253,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Travis Barron	Marlies (TOR)	LW	26	1998-08-17	ONT	No	205 Lbs	6 ft1	No	No	N/A	No	No	3		False	False	Pro & Farm	973,000$	973,000$	0$	0$	No	973,000$	973,000$	-	-	-	-	-	-	-	973,000$	973,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
24	23.96	192 Lbs	6 ft2	1.96	897,289$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				30	1	2	2
2	Olle Lycksell			30	1	2	2
3			Olle Lycksell	20	1	2	2
4				20	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			35	1	2	2
2		Noel Hoefenmayer	35	1	2	2
3			30	1	2	2
4			0	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				60	1	2	2
2	Olle Lycksell			40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Noel Hoefenmayer		60	1	2	2
2			40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2		Olle Lycksell	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Noel Hoefenmayer		60	1	2	2
2			40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	1	2	2	Noel Hoefenmayer		60	1	2	2
2		40	1	2	2			40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2		Olle Lycksell	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2	Noel Hoefenmayer		40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense

Extra Forwards
Normal	PowerPlay	Penalty Kill
Olle Lycksell, ,	Olle Lycksell,	Olle Lycksell

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Noel Hoefenmayer, ,	Noel Hoefenmayer	Noel Hoefenmayer,

Penalty Shots
, , , , Olle Lycksell

Goalie
#1 : , #2 :

Custom OT Lines Forwards
, , , , , , , Olle Lycksell, , ,

Custom OT Lines Defensemen
, , , , Noel Hoefenmayer

Show or Hide Columns

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

	Overall												Home											Visitor
#	VS Team	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	PCT	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
1	Bears	2	1	1	0	0	0	0	0	8	10	-2	1	0	1	0	0	0	0	0	3	6	-3	1	1	0	0	0	0	0	0	5	4	1	2	0.500	8	16	24	0	0	11	22	21	0	83	116	132	114	0	52	17	18	32	4	1	25.00%	9	6	33.33%	1	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
2	Griffins	2	1	1	0	0	0	0	0	17	15	2	1	0	1	0	0	0	0	0	7	9	-2	1	1	0	0	0	0	0	0	10	6	4	2	0.500	17	33	50	0	0	11	22	21	0	75	116	132	114	0	64	29	26	31	14	8	57.14%	8	4	50.00%	0	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
3	Islanders	1	0	1	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	3	7	-4	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	11	22	21	0	31	116	132	114	0	38	13	12	16	1	0	0.00%	6	2	66.67%	0	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
4	Phantoms	2	0	2	0	0	0	0	0	7	14	-7	1	0	1	0	0	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	3	9	-6	0	0.000	7	14	21	0	0	11	22	21	0	56	116	132	114	0	67	24	14	20	4	3	75.00%	7	1	85.71%	1	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
5	Reign	2	1	1	0	0	0	0	0	11	9	2	1	1	0	0	0	0	0	0	9	6	3	1	0	1	0	0	0	0	0	2	3	-1	2	0.500	11	21	32	0	0	11	22	21	0	78	116	132	114	0	51	18	37	24	6	2	33.33%	6	1	83.33%	0	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
6	Thunderbirds	1	0	1	0	0	0	0	0	8	10	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	8	10	-2	0	0.000	8	16	24	0	0	11	22	21	0	39	116	132	114	0	42	13	20	14	6	2	33.33%	5	4	20.00%	0	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
	Total	10	3	7	0	0	0	0	0	54	65	-11	5	1	4	0	0	0	0	0	26	33	-7	5	2	3	0	0	0	0	0	28	32	-4	6	0.300	54	106	160	0	0	11	22	21	0	362	116	132	114	0	314	114	127	137	35	16	45.71%	41	18	56.10%	2	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
	_Since Last GM Reset	10	3	7	0	0	0	0	0	54	65	-11	5	1	4	0	0	0	0	0	26	33	-7	5	2	3	0	0	0	0	0	28	32	-4	6	0.300	54	106	160	0	0	11	22	21	0	362	116	132	114	0	314	114	127	137	35	16	45.71%	41	18	56.10%	2	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
	_Vs Conference	10	3	7	0	0	0	0	0	54	65	-11	5	1	4	0	0	0	0	0	26	33	-7	5	2	3	0	0	0	0	0	28	32	-4	6	0.300	54	106	160	0	0	11	22	21	0	362	116	132	114	0	314	114	127	137	35	16	45.71%	41	18	56.10%	2	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79
	_Vs Division	2	3	7	0	0	0	0	0	17	15	2	1	1	4	0	0	0	0	0	7	9	-2	1	2	3	0	0	0	0	0	10	6	4	6	1.500	17	33	50	0	0	11	22	21	0	75	116	132	114	0	64	29	26	31	14	8	57.14%	8	4	50.00%	0	80	195	41.03%	59	160	36.88%	87	240	36.25%	216	133	206	96	176	79

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
10	6	W2	54	106	160	362	314	114	127	137	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	3	7	0	0	0	0	54	65

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	1	4	0	0	0	0	26	33

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
5	2	3	0	0	0	0	28	32

Last 10 Games
W	L	OTW	OTL	SOW	SOL
3	7	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
35	16	45.71%	41	18	56.10%	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
116	132	114	0	11	22	21	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
80	195	41.03%	59	160	36.88%	87	240	36.25%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
216	133	206	96	176	79

Last Played Games Show or Hide Columns

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	Link
1	1	Phantoms	5	Marlies	4	L	BoxScore
3	34	Islanders	7	Marlies	3	L	BoxScore
4	46	Marlies	2	Reign	3	L	BoxScore
5	66	Griffins	9	Marlies	7	L	BoxScore
7	83	Marlies	3	Phantoms	9	L	BoxScore
8	96	Bears	6	Marlies	3	L	BoxScore
9	111	Marlies	5	Bears	4	W	BoxScore
10	113	Marlies	8	Thunderbirds	10	L	BoxScore
11	127	Marlies	10	Griffins	6	W	BoxScore
12	141	Reign	6	Marlies	9	W	BoxScore
14	163	Marlies	-	Roadrunners	-
15	174	Roadrunners	-	Marlies	-
17	198	Thunderbirds	-	Marlies	-
18	210	Marlies	-	Islanders	-

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

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
2	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
0$	2,153,493$	2,110,793$	750,000$0$

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

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	8	0$	0$

Marlies Players Stat Leaders (Regular Season)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Marlies Goalies Stat Leaders (Regular Season)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Marlies Career Team Stats

Show or Hide Columns

	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

Marlies Players Stat Leaders (Play-Off)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Marlies Goalies Stat Leaders (Play-Off)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Marlies
	GP: 10 \| W: 3 \| L: 7 \| OTL: 0 \| P: 6 GF: 54 \| GA: 65 \| PP%: 45.71% \| PK%: 56.10% GM : Phil VendorMolen \| Morale : 48 \| Team Overall : 57 Next Games #163 vs Roadrunners