LHS - Ligue de Hockey Simule

Maple Leafs
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	Reid Schaefer (R)	0		X			100.00	86	54	74	60	95	80	75	61	59	62	60	64	61	63	64	0	75	64	0
2	Matt Savoie (R)	0	X				100.00	60	37	86	66	67	82	74	65	73	64	59	60	62	61	63	0	75	62	0
3	Viktor Neuchev (R)	0		X			100.00	64	37	95	60	73	86	77	59	64	61	57	58	62	63	64	0	75	61	0
4	Luke Tuch (R)	0		X			100.00	76	41	73	58	85	75	68	56	52	55	54	59	56	63	65	0	75	60	0
5	Luke Philp	0	X		X		100.00	58	37	90	58	67	74	73	56	66	59	57	54	58	70	72	0	75	60	0
6	Roni Hirvonen (R)	0	X				100.00	57	37	89	61	66	78	77	59	62	58	58	56	60	63	65	0	75	60	0
7	Anthony Vincent	0			X		100.00	63	42	66	58	72	80	76	57	59	55	56	54	58	67	70	0	75	59	0
8	Corey Andonovski	0			X		100.00	67	42	67	57	76	71	81	54	59	55	56	58	54	66	68	0	75	59	0
9	Marc Johnstone	98			X		100.00	68	38	77	58	71	74	78	56	59	53	55	54	58	69	71	0	75	59	0
10	Jacob Doty	0	X				100.00	74	45	65	55	83	64	80	52	60	53	54	56	52	72	74	0	75	59	0
11	Jordan Martel	0			X		100.00	67	37	94	57	76	81	61	55	52	50	56	53	58	67	69	0	75	59	0
12	Tate Singleton	0			X		100.00	58	43	59	56	65	76	63	55	62	54	51	53	57	67	69	0	75	56	0
13	Michael Callahan	0				X	100.00	68	40	85	62	81	80	85	58	30	60	57	61	49	66	68	0	75	62	0
14	Ethan Prow	6				X	100.00	60	37	94	59	69	68	74	57	30	58	53	54	46	73	75	0	75	60	0
15	Chris Harpur	0				X	100.00	75	39	81	55	84	64	65	54	30	57	50	56	45	69	71	0	75	59	0
16	Colin Felix	0				X	100.00	79	57	59	55	78	63	70	52	30	53	51	54	45	66	68	0	75	58	0
Scratches
1	Chris Wagner	0	X	X	X		100.00	75	43	74	63	73	79	80	62	65	60	64	63	62	76	77	0	75	64	0
2	Andre Lee	0		X			100.00	79	42	79	62	91	75	79	60	55	59	58	61	57	65	66	0	75	63	0
3	Vasily Ponomarev (R)	0	X				100.00	59	37	82	67	69	78	80	65	73	63	60	62	67	63	64	0	75	63	0
4	Travis Howe	0			X		100.00	77	69	52	54	86	60	75	53	51	52	50	56	50	71	73	0	75	58	0
5	Alexander Petrovic	0				X	100.00	82	71	74	60	92	80	85	58	30	59	57	62	45	74	75	0	75	63	0
6	Matthew Robertson (R)	0				X	100.00	76	42	74	61	89	85	84	59	30	60	56	62	49	64	66	0	75	62	0
7	Ty Nelson (R)	0				X	100.00	55	39	79	64	68	78	73	63	30	61	54	56	47	61	63	0	75	60	0
8	Will Zmolek	0				X	100.00	75	38	95	57	84	63	64	56	30	55	52	58	45	66	68	0	75	60	0

	TEAM AVERAGE					100.00	69	44	78	59	78	75	75	58	50	57	56	58	54	67	69	0	75	60

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	Magnus Hellberg	100.00	76	84	78	96	75	74	76	75	74	76	75	74	88	0	75	68	0
2	Jack Campbell	100.00	74	81	76	83	73	72	74	73	72	74	73	75	87	0	75	66	0
Scratches

	TEAM AVERAGE	100.00	75	83	77	90	74	73	75	74	73	75	74	75	88	0	75	67

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Bob Woods	63	65	68	69	86	80	61	CAN	57	1	850,000$

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	PKS	PKM	GW	GT	FO%	FOT	EG	P/20	PSS	FW	FT	S1	S2	S3
1	Michael Callahan	Marlies (TOR)	D	28	11	25	36	11	24	0	51	50	64	22	27	17.19%	60	701	25.07	4	4	8	26	68	0	65	3	0	0.00%	0	0	1.03	0	0	0	0	3	2
2	Matt Savoie	Marlies (TOR)	C	28	14	19	33	8	4	0	4	120	145	34	114	9.66%	6	677	24.19	5	3	8	20	67	3	77	1	0	57.54%	789	0	0.97	1	0	0	3	1	1
3	Reid Schaefer	Marlies (TOR)	LW	28	12	19	31	10	28	0	127	84	146	31	114	8.22%	18	687	24.56	1	6	7	20	66	1	75	2	0	49.43%	352	0	0.90	1	0	0	2	3	3
4	Roni Hirvonen	Marlies (TOR)	C	28	12	15	27	4	10	0	25	80	104	33	68	11.54%	5	525	18.75	2	2	4	19	55	0	1	2	0	48.05%	693	0	1.03	0	0	0	2	1	1
5	Viktor Neuchev	Marlies (TOR)	LW	22	10	13	23	-1	6	0	37	41	99	24	76	10.10%	4	465	21.18	1	5	6	11	44	1	42	2	1	51.16%	86	0	0.99	1	0	0	3	2	1
6	Luke Tuch	Marlies (TOR)	LW	28	7	15	22	13	4	0	46	46	72	25	46	9.72%	3	419	14.97	0	0	0	0	0	1	41	0	0	47.62%	42	0	1.05	1	0	0	1	3	1
7	Marc Johnstone	Marlies (TOR)	RW	28	9	11	20	11	8	0	16	36	60	17	50	15.00%	1	380	13.58	0	0	0	0	1	0	0	0	0	50.00%	26	0	1.05	0	0	0	0	2	0
8	Luke Philp	Marlies (TOR)	C/RW	28	6	14	20	12	0	0	4	32	73	18	47	8.22%	6	531	18.99	0	4	4	10	66	1	11	0	0	59.65%	57	0	0.75	0	0	0	0	0	1
9	Jacob Doty	Marlies (TOR)	C	28	7	12	19	8	9	5	42	48	54	16	48	12.96%	8	400	14.32	1	0	1	0	1	1	20	1	1	53.00%	500	0	0.95	0	0	1	1	0	0
10	Matthew Robertson	Marlies (TOR)	D	19	3	12	15	7	16	0	50	32	47	13	18	6.38%	33	450	23.69	0	0	0	18	49	1	39	2	0	0.00%	0	1	0.67	0	0	0	1	2	1
11	Jordan Martel	Marlies (TOR)	RW	28	7	7	14	1	2	0	51	28	69	17	43	10.14%	6	532	19.00	2	1	3	13	61	0	0	0	0	41.46%	41	0	0.53	0	0	0	0	1	0
12	Ethan Prow	Marlies (TOR)	D	28	2	11	13	10	10	0	57	26	31	12	26	6.45%	41	579	20.68	2	2	4	13	58	1	60	0	0	0.00%	0	0	0.45	0	0	0	0	0	1
13	Ty Nelson	Marlies (TOR)	D	18	3	9	12	11	0	0	32	21	31	9	16	9.68%	33	366	20.36	0	2	2	13	42	0	34	0	0	0.00%	0	0	0.65	0	0	0	0	0	0
14	Chris Harpur	Marlies (TOR)	D	25	2	8	10	0	12	0	18	20	17	4	10	11.76%	27	364	14.56	0	1	1	1	4	0	5	1	0	0.00%	0	0	0.55	0	0	0	0	1	0
15	Colin Felix	Marlies (TOR)	D	25	1	6	7	5	38	0	72	13	10	8	11	10.00%	18	362	14.48	0	0	0	0	1	1	18	1	0	0.00%	0	0	0.39	0	0	0	0	0	1
16	Andre Lee	Marlies (TOR)	LW	5	2	1	3	3	4	0	13	7	20	8	17	10.00%	4	92	18.41	0	0	0	0	11	0	7	0	0	50.00%	4	0	0.65	0	0	0	1	0	0
17	Anthony Vincent	Marlies (TOR)	RW	25	0	1	1	-1	0	0	4	7	5	1	2	0.00%	1	57	2.30	0	0	0	1	5	0	1	0	0	40.91%	22	0	0.35	0	0	0	0	0	0
18	Corey Andonovski	Marlies (TOR)	RW	25	1	0	1	0	0	0	1	5	13	4	8	7.69%	1	78	3.14	0	0	0	0	0	0	0	0	0	100.00%	6	0	0.25	0	0	0	0	0	0
19	Chris Wagner	Marlies (TOR)	C/LW/RW	1	0	0	0	0	0	0	3	2	4	1	3	0.00%	0	14	14.07	0	0	0	1	3	0	2	0	0	59.26%	27	0	0.00	0	0	0	0	0	0
20	Tate Singleton	Marlies (TOR)	RW	24	0	0	0	0	5	5	0	0	0	1	0	0.00%	0	10	0.44	0	0	0	0	2	0	0	0	0	100.00%	2	0	0.00	0	1	0	0	0	0
Team Total or Average				469	109	198	307	112	180	10	653	698	1064	298	744	10.24%	275	7696	16.41	18	30	48	166	612	11	506	15	2	52.47%	2647	1	0.80	4	1	1	14	19	13

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	A	PS %	PSA	ST	BG	S1	S2	S3
1	Jack Campbell	Marlies (TOR)	16	11	4	1	0.912	3.73	966	2	0	60	678	1	0.000	0	16	11	2	0	0
2	Magnus Hellberg	Marlies (TOR)	11	4	6	1	0.932	2.27	662	0	2	25	367	1	0.750	4	11	16	1	1	2
Team Total or Average			27	15	10	2	0.919	3.13	1629	2	2	85	1045	2	0.750	4	27	27	3	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
Alexander Petrovic	D	33	1992-03-03	No	211 Lbs	6 ft5	No	No	No	3	UFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Andre Lee	LW	25	2000-07-26	No	206 Lbs	6 ft5	No	No	No	1	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Anthony Vincent	RW	28	1997-08-12	No	190 Lbs	6 ft0	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Chris Harpur	D	29	1996-09-13	No	201 Lbs	6 ft3	No	No	No	2	UFA	Pro & Farm	775,000$	0$	0$	No	Link / NHL Link
Chris Wagner (1 Way Contract)	C/LW/RW	34	1991-05-27	No	192 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	800,000$	800,000$	541,667$	No	Link / NHL Link
Colin Felix	D	26	1999-01-07	No	203 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	775,000$	0$	0$	No	Link / NHL Link
Corey Andonovski	RW	26	1999-03-26	No	195 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Ethan Prow	D	32	1992-11-17	No	182 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Jack Campbell (1 Way Contract)	G	33	1992-01-09	No	200 Lbs	6 ft3	No	No	No	3	UFA	Pro & Farm	999,999$	999,999$	677,083$	No	Link / NHL Link
Jacob Doty	C	32	1993-06-19	No	212 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Jordan Martel	RW	27	1998-02-24	No	194 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Luke Philp (1 Way Contract)	C/RW	29	1995-11-06	No	181 Lbs	5 ft10	No	No	No	3	UFA	Pro & Farm	800,000$	800,000$	541,667$	No	Link / NHL Link
Luke Tuch	LW	23	2002-03-07	Yes	209 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Magnus Hellberg	G	34	1991-04-04	No	220 Lbs	6 ft6	No	No	No	3	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Marc Johnstone	RW	29	1996-06-19	No	181 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Matt Savoie	C	21	2004-01-01	Yes	179 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Matthew Robertson	D	24	2001-09-01	Yes	211 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Michael Callahan	D	26	1999-09-23	No	199 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Reid Schaefer	LW	22	2003-09-21	Yes	226 Lbs	6 ft5	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Roni Hirvonen	C	23	2002-01-10	Yes	178 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Tate Singleton	RW	27	1998-09-05	No	176 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Travis Howe	RW	31	1994-02-10	No	198 Lbs	6 ft4	No	No	No	3	UFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Ty Nelson	D	21	2004-03-30	Yes	195 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Vasily Ponomarev	C	23	2002-03-13	Yes	180 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link
Viktor Neuchev	LW	21	2003-10-25	Yes	165 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Will Zmolek	D	26	1999-04-17	No	205 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
26	27.12	196 Lbs	6 ft1	2.42	850,000$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Reid Schaefer	Matt Savoie	Luke Philp	40	1	2	2
2	Viktor Neuchev	Roni Hirvonen	Jordan Martel	30	1	2	2
3	Luke Tuch	Jacob Doty	Marc Johnstone	20	1	2	2
4	Matt Savoie	Reid Schaefer	Corey Andonovski	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Michael Callahan		40	1	2	2
2	Ethan Prow		30	1	2	2
3	Chris Harpur	Colin Felix	20	1	2	2
4	Michael Callahan		10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Reid Schaefer	Matt Savoie	Luke Philp	60	1	2	2
2	Viktor Neuchev	Roni Hirvonen	Jordan Martel	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Michael Callahan		60	1	2	2
2	Ethan Prow		40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Reid Schaefer	Matt Savoie	60	1	2	2
2	Viktor Neuchev	Luke Tuch	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Michael Callahan		60	1	2	2
2	Ethan Prow		40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Reid Schaefer	60	1	2	2	Michael Callahan		60	1	2	2
2	Matt Savoie	40	1	2	2	Ethan Prow		40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Reid Schaefer	Matt Savoie	60	1	2	2
2	Viktor Neuchev	Luke Tuch	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Michael Callahan		60	1	2	2
2	Ethan Prow		40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Reid Schaefer	Matt Savoie	Luke Philp	Michael Callahan

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Reid Schaefer	Matt Savoie	Luke Philp	Michael Callahan

Extra Forwards
Normal	PowerPlay	Penalty Kill
Anthony Vincent, Tate Singleton, Jacob Doty	Anthony Vincent, Tate Singleton	Jacob Doty

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Chris Harpur, Colin Felix, Ethan Prow	Chris Harpur	Colin Felix, Ethan Prow

Penalty Shots
Reid Schaefer, Matt Savoie, Viktor Neuchev, Luke Tuch, Luke Philp

Goalie
#1 : Jack Campbell, #2 : Magnus Hellberg

Custom OT Lines Forwards
Reid Schaefer, Matt Savoie, Viktor Neuchev, Luke Tuch, Luke Philp, Roni Hirvonen, Roni Hirvonen, Jordan Martel, Jacob Doty, Marc Johnstone, Corey Andonovski

Custom OT Lines Defensemen
Michael Callahan, , Ethan Prow, , Chris Harpur

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
28	34	W1	110	200	310	1071	1066	293	186	678	0	2

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
28	13	10	3	1	0	1	110	87

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	10	4	1	1	0	0	73	48

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
12	3	6	2	0	0	1	37	39

Last 10 Games
W	L	OTW	OTL	SOW	SOL
4	5	0	0	0	1

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
81	18	22.22%	81	17	79.01%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
358	366	333	18	51	30	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 %
562	1065	52.77%	608	1115	54.53%	223	452	49.34%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
666	464	668	209	357	178

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
2 - 2025-10-08	4	Rocket	1	Marlies	3	W			BoxScore
5 - 2025-10-11	25	Marlies	2	Griffins	3	L			BoxScore
7 - 2025-10-13	43	Griffins	0	Marlies	9	W			BoxScore
8 - 2025-10-14	49	Admirals	0	Marlies	1	W			BoxScore
10 - 2025-10-16	61	Wolf Pack	2	Marlies	1	L			BoxScore
12 - 2025-10-18	79	Firebirds	4	Marlies	7	W			BoxScore
15 - 2025-10-21	98	Devils	2	Marlies	8	W			BoxScore
18 - 2025-10-24	125	Marlies	6	Americans	5	W	X		BoxScore
19 - 2025-10-25	132	Americans	4	Marlies	5	W	X		BoxScore
22 - 2025-10-28	151	Wranglers	1	Marlies	4	W			BoxScore
23 - 2025-10-29	166	Marlies	4	Monsters	3	W	X		BoxScore
26 - 2025-11-01	188	Marlies	4	Phantoms	2	W			BoxScore
28 - 2025-11-03	199	Penguins	5	Marlies	4	L	X		BoxScore
30 - 2025-11-05	213	Roadrunners	4	Marlies	5	W			BoxScore
33 - 2025-11-08	234	Bruins	5	Marlies	2	L			BoxScore
34 - 2025-11-09	246	Wolves	6	Marlies	4	L			BoxScore
36 - 2025-11-11	256	Marlies	3	Bruins	7	L			BoxScore
38 - 2025-11-13	269	Reign	2	Marlies	4	W			BoxScore
40 - 2025-11-15	291	Marlies	4	IceHogs	2	W			BoxScore
43 - 2025-11-18	307	Thunderbirds	4	Marlies	8	W			BoxScore
45 - 2025-11-20	319	Monsters	4	Marlies	3	L			BoxScore
47 - 2025-11-22	337	Marlies	4	Rocket	5	L			BoxScore
51 - 2025-11-26	369	Marlies	1	Monsters	2	L	X	X	BoxScore
53 - 2025-11-28	386	Marlies	2	Bears	3	L			BoxScore
54 - 2025-11-29	396	Marlies	1	Penguins	2	L			BoxScore
57 - 2025-12-02	415	Marlies	5	Checkers	2	W			BoxScore
59 - 2025-12-04	432	Marlies	1	Wolves	3	L			BoxScore
61 - 2025-12-06	444	Rocket	4	Marlies	5	W			BoxScore
63 - 2025-12-08	461	Crunch	-	Marlies	-
66 - 2025-12-11	480	Barracuda	-	Marlies	-
68 - 2025-12-13	499	Condors	-	Marlies	-
71 - 2025-12-16	520	IceHogs	-	Marlies	-
73 - 2025-12-18	538	Marlies	-	Bears	-
75 - 2025-12-20	558	Marlies	-	Admirals	-
76 - 2025-12-21	568	Marlies	-	Stars	-
78 - 2025-12-23	575	Penguins	-	Marlies	-
82 - 2025-12-27	590	Senators	-	Marlies	-
83 - 2025-12-28	603	Marlies	-	Griffins	-
85 - 2025-12-30	617	Devils	-	Marlies	-
87 - 2026-01-01	634	Moose	-	Marlies	-
89 - 2026-01-03	651	Marlies	-	Sound Tigers	-
92 - 2026-01-06	672	Checkers	-	Marlies	-
94 - 2026-01-08	686	Marlies	-	Phantoms	-
96 - 2026-01-10	702	Comets	-	Marlies	-
98 - 2026-01-12	723	Marlies	-	Eagles	-
99 - 2026-01-13	733	Marlies	-	Roadrunners	-
101 - 2026-01-15	748	Marlies	-	Silver Knights	-
103 - 2026-01-17	762	Marlies	-	Moose	-
105 - 2026-01-19	774	Wild	-	Marlies	-
107 - 2026-01-21	788	Griffins	-	Marlies	-
109 - 2026-01-23	802	Silver Knights	-	Marlies	-
111 - 2026-01-25	819	Eagles	-	Marlies	-
113 - 2026-01-27	831	Americans	-	Marlies	-
115 - 2026-01-29	857	Marlies	-	Firebirds	-
117 - 2026-01-31	869	Marlies	-	Comets	-
119 - 2026-02-02	885	Marlies	-	Wranglers	-
120 - 2026-02-03	891	Marlies	-	Condors	-
142 - 2026-02-25	912	Marlies	-	Crunch	-
143 - 2026-02-26	921	Marlies	-	Checkers	-
145 - 2026-02-28	940	Senators	-	Marlies	-
147 - 2026-03-02	954	Phantoms	-	Marlies	-
149 - 2026-03-04	971	Marlies	-	Devils	-
150 - 2026-03-05	975	Marlies	-	Wolf Pack	-
152 - 2026-03-07	994	Crunch	-	Marlies	-
155 - 2026-03-10	1014	Marlies	-	Rocket	-
157 - 2026-03-12	1029	Gulls	-	Marlies	-
159 - 2026-03-14	1047	Marlies	-	Americans	-
160 - 2026-03-15	1060	Marlies	-	Wild	-
162 - 2026-03-17	1068	Sound Tigers	-	Marlies	-
165 - 2026-03-20	1094	Wolves	-	Marlies	-
166 - 2026-03-21	1106	Marlies	-	Senators	-
169 - 2026-03-24	1120	Marlies	-	Bruins	-
170 - 2026-03-25	1136	Wolf Pack	-	Marlies	-
Trade Deadline --- Trades can’t be done after this day is simulated!
173 - 2026-03-28	1160	Marlies	-	Thunderbirds	-
175 - 2026-03-30	1176	Marlies	-	Gulls	-
178 - 2026-04-02	1202	Marlies	-	Barracuda	-
180 - 2026-04-04	1217	Marlies	-	Reign	-
184 - 2026-04-08	1245	Bears	-	Marlies	-
185 - 2026-04-09	1252	Marlies	-	Sound Tigers	-
187 - 2026-04-11	1270	Checkers	-	Marlies	-
189 - 2026-04-13	1285	Stars	-	Marlies	-
191 - 2026-04-15	1304	Marlies	-	Senators	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	40	25
Attendance	21,537	10,653
Attendance PCT	67.30%	66.58%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
-6	2012 - 67.06%	88,110$	1,409,758$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
902,482$	1,950,000$	1,950,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	626,344$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
-528,659$	130	14,583$	1,895,790$

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
2024	82	23	42	0	7	1	4	5	264	310	-46	41	14	17	0	6	0	1	3	140	143	-3	41	9	25	0	1	1	3	2	124	167	-43	74	264	477	741	0	1	81	90	82	16	2683	848	950	836	79	2938	823	608	1944	260	48	18.46%	274	66	75.91%	4	1471	2850	51.61%	1630	3075	53.01%	684	1382	49.49%	1855	1253	2053	626	1072	522
2025	28	13	10	0	3	1	0	1	110	87	23	16	10	4	0	1	1	0	0	73	48	25	12	3	6	0	2	0	0	1	37	39	-2	34	110	200	310	0	2	51	30	26	3	1071	358	366	333	18	1066	293	186	678	81	18	22.22%	81	17	79.01%	0	562	1065	52.77%	608	1115	54.53%	223	452	49.34%	666	464	668	209	357	178
Total Regular Season	110	36	52	0	10	2	4	6	374	397	-23	57	24	21	0	7	1	1	3	213	191	22	53	12	31	0	3	1	3	3	161	206	-45	108	374	677	1051	0	3	132	120	108	19	3754	1206	1316	1169	97	4004	1116	794	2622	341	66	19.35%	355	83	76.62%	4	2033	3915	51.93%	2238	4190	53.41%	907	1834	49.45%	2521	1718	2722	835	1429	700