LHS - Ligue de Hockey Simule

Red Wings
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	Jack Finley (R)	0	X				100.00	82	51	82	61	96	77	78	63	69	60	58	64	59	63	65	0	75	64	0
2	Olle Lycksell (R)	0	X	X	X		100.00	62	35	91	66	63	86	82	65	68	67	64	63	65	66	68	0	75	64	0
3	Angus Crookshank (R)	0		X			100.00	66	38	76	64	69	87	85	62	65	61	63	60	64	66	68	0	75	63	0
4	Carson Meyer	0			X		100.00	71	39	73	64	70	84	78	63	56	62	61	60	63	68	70	0	75	63	0
5	Aku Raty	0		X	X		100.00	67	37	84	63	68	79	83	62	58	64	55	57	59	65	66	0	75	62	0
6	Brendan Furry	0		X			100.00	68	39	80	59	77	80	82	58	55	56	57	58	56	67	69	0	75	61	0
7	Matthew Strome (R)	0		X			100.00	79	42	80	59	88	75	80	58	54	57	56	55	58	66	68	0	75	61	0
8	Donovan Houle-Villeneuve	0	X				100.00	65	41	72	59	74	79	72	58	64	57	55	56	58	66	68	0	75	60	0
9	Mathias Laferriere (R)	0			X		100.00	69	39	89	59	78	74	83	58	55	57	54	56	58	65	67	0	75	60	0
10	Filip Mesar (R)	0			X		100.00	56	36	87	63	65	74	67	61	65	62	54	53	64	61	63	0	75	59	0
11	Anthony Romano (R)	0	X				100.00	59	36	95	56	69	68	69	55	60	54	53	52	56	65	67	0	75	58	0
12	Olen Zellweger (R)	0				X	100.00	63	36	91	74	68	90	85	72	30	73	65	66	55	62	64	0	75	67	0
13	Matthew Kessel (R)	0				X	100.00	70	39	85	65	81	83	85	61	30	64	58	63	49	65	67	0	75	64	0
14	Robbie Russo	0				X	100.00	64	39	81	61	73	71	86	57	30	63	53	56	47	72	74	0	75	61	0
15	Brandon Hickey	0				X	100.00	72	38	91	56	81	66	71	55	30	53	54	57	45	69	71	0	75	60	0
16	Joseph Cecconi	52				X	100.00	73	42	74	58	82	66	85	57	30	56	52	55	45	68	70	0	75	60	0
17	Lleyton Moore	0				X	100.00	55	36	94	56	64	63	68	53	30	55	54	51	46	63	65	0	75	57	0
18	Joe Fleming	0				X	100.00	71	46	50	53	80	64	66	51	30	52	50	55	45	62	64	0	75	56	0
Scratches

	TEAM AVERAGE					100.00	67	39	82	61	75	76	78	59	49	60	56	58	55	66	67	0	75	61

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	Filip Larsson (R)	100.00	74	76	72	79	73	72	74	73	72	74	73	67	77	0	75	65	0
2	Collin Delia	100.00	72	82	77	82	71	70	72	71	70	72	71	71	85	0	75	65	0
Scratches
1	Malcolm Subban	100.00	72	82	77	83	71	70	72	71	70	72	71	72	86	0	75	65	0

	TEAM AVERAGE	100.00	73	80	75	81	72	71	73	72	71	73	72	70	83	0	75	65

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
John MacLean	68	69	67	73	91	85	54	CAN	61	2	750,000$

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

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	A	EG	PS %	PSA	ST	BG	S1	S2	S3

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
Aku Raty (1 Way Contract)	LW/RW	24	2001-07-05	No	170 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	1,110,000$	1,110,000$	79,286$	No	Link / NHL Link
Angus Crookshank	LW	26	1999-10-02	Yes	183 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Anthony Romano	C	24	2000-10-07	Yes	182 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Brandon Hickey	D	29	1996-04-13	No	201 Lbs	6 ft2	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Brendan Furry	LW	27	1998-07-08	No	198 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Carson Meyer	RW	28	1997-08-18	No	184 Lbs	5 ft11	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Collin Delia	G	31	1994-06-20	No	208 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Donovan Houle-Villeneuve	C	25	1999-11-04	No	196 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Filip Larsson	G	27	1998-08-17	Yes	194 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Filip Mesar	RW	21	2004-01-03	Yes	176 Lbs	5 ft9	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Jack Finley	C	23	2002-09-02	Yes	220 Lbs	6 ft6	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Joe Fleming	D	22	2003-06-19	No	215 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Joseph Cecconi	D	28	1997-05-23	No	210 Lbs	6 ft2	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Lleyton Moore	D	23	2002-02-27	No	178 Lbs	5 ft8	No	No	No	2	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Malcolm Subban	G	31	1993-12-21	No	215 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	775,000$	0$	0$	No	Link / NHL Link
Mathias Laferriere	RW	25	2000-06-27	Yes	188 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Matthew Kessel	D	25	2000-06-23	Yes	205 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Matthew Strome	LW	26	1999-01-06	Yes	206 Lbs	6 ft4	No	No	No	3	RFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Olen Zellweger	D	22	2003-09-10	Yes	187 Lbs	5 ft10	No	No	No	2	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Olle Lycksell	C/LW/RW	26	1999-08-24	Yes	163 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	950,000$	0$	0$	No	Link / NHL Link
Robbie Russo	D	32	1993-02-15	No	191 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
21	25.95	194 Lbs	6 ft1	2.43	856,429$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2			30	1	2	2
3			20	1	2	2
4			10	1	2	2

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

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

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

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			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
, ,	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
0	0	N/A	0	0	0	0	0	0	0	0	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Last 10 Games
W	L	OTW	OTL	SOW	SOL
0	0	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
0	0	0.00%	0	0	0.00%	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
0	0	0	0	0	0	0	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
0	0	0.00%	0	0	0.00%	0	0	0.00%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
0	0	0	0	0	0

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	RI	Link

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

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
10	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,687,500$	1,687,500$	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$	1	0$	0$

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	38	27	0	10	3	2	2	305	294	11	41	23	11	0	2	1	2	2	157	133	24	41	15	16	0	8	2	0	0	148	161	-13	105	305	543	848	0	1	108	92	93	13	2804	901	913	959	45	2893	818	585	1809	256	71	27.73%	247	50	79.76%	0	1452	2957	49.10%	1512	3005	50.32%	701	1405	49.89%	1888	1288	2005	617	1067	526
2025	82	12	66	0	2	1	1	0	256	516	-260	41	8	30	0	1	1	1	0	146	244	-98	41	4	36	0	1	0	0	0	110	272	-162	31	256	486	742	1	0	101	81	71	3	3281	1100	1076	1092	15	4797	1357	495	2136	203	31	15.27%	221	72	67.42%	1	1004	2959	33.93%	1318	3867	34.08%	514	1508	34.08%	1383	921	2579	612	967	409
Total Regular Season	164	50	93	0	12	4	3	2	561	810	-249	82	31	41	0	3	2	3	2	303	377	-74	82	19	52	0	9	2	0	0	258	433	-175	136	561	1029	1590	1	1	209	173	164	16	6085	2001	1989	2051	60	7690	2175	1080	3945	459	102	22.22%	468	122	73.93%	1	2456	5916	41.51%	2830	6872	41.18%	1215	2913	41.71%	3271	2210	4584	1229	2034	935
Playoff
2024	12	7	5	0	0	0	0	0	39	41	-2	7	4	3	0	0	0	0	0	26	23	3	5	3	2	0	0	0	0	0	13	18	-5	14	39	71	110	0	0	14	9	16	0	377	145	116	116	0	432	126	76	266	25	4	16.00%	35	7	80.00%	0	208	398	52.26%	214	406	52.71%	113	193	58.55%	255	173	312	88	152	73
Total Playoff	12	7	5	0	0	0	0	0	39	41	-2	7	4	3	0	0	0	0	0	26	23	3	5	3	2	0	0	0	0	0	13	18	-5	14	39	71	110	0	0	14	9	16	0	377	145	116	116	0	432	126	76	266	25	4	16.00%	35	7	80.00%	0	208	398	52.26%	214	406	52.71%	113	193	58.55%	255	173	312	88	152	73