LHSDB - Ligue de hockey simulee des debiles barbus

Toronto 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	Chase DeLeo	0	X	X			100.00	73	36	89	66	66	89	74	65	69	64	63	60	66	69	68	51	50	64	0
2	Brett Seney	0	X	X			100.00	68	37	70	65	61	90	84	66	67	63	64	61	65	68	67	42	50	64	0
3	Charles Hudon	0	X	X	X		100.00	69	37	78	65	68	89	85	66	67	60	64	59	67	69	71	47	50	64	0
4	Joseph Cramarossa	0	X				100.00	71	46	62	65	75	76	73	63	65	62	64	60	65	71	73	52	50	63	0
5	Sean Malone	0	X				100.00	65	40	79	62	74	82	77	63	69	61	63	59	62	68	70	41	50	63	0
6	Danny O'Regan	0	X	X			100.00	57	35	91	64	66	84	83	62	70	65	58	61	60	69	71	46	50	63	0
7	Dylan Sikura	0	X	X	X		100.00	57	35	93	63	66	89	85	62	63	64	58	61	60	68	70	41	50	63	0
8	Clark Bishop	0	X	X			100.00	68	40	73	60	77	74	80	58	72	59	55	57	61	67	69	49	50	60	0
9	Pierre-Cedric Labrie	0		X			100.00	80	67	68	53	89	68	74	52	54	53	52	58	52	77	79	20	50	59	0
10	Tyrell Goulbourne	0		X			100.00	64	41	72	53	73	68	66	52	55	53	54	52	55	69	71	53	50	56	0
11	Seth Helgeson	0				X	100.00	81	46	64	54	90	63	86	52	30	53	52	58	45	73	78	35	50	62	0
12	Mitch Reinke	0				X	100.00	60	36	95	59	69	70	81	58	30	65	52	56	47	67	69	37	50	60	0
13	Ashton Sautner	0				X	100.00	67	40	77	54	76	70	80	53	30	55	53	54	45	69	71	36	50	59	0
14	Keaton Thompson	0				X	100.00	62	38	82	56	71	65	72	53	30	55	54	52	46	68	70	53	50	57	0
Scratches
1	Anthony Bitetto	0				X	100.00	70	43	68	55	79	69	83	54	30	55	54	56	46	73	75	29	50	61	0

	TEAM AVERAGE					100.00	67	41	77	60	73	76	79	59	53	59	57	58	56	70	71	42	50	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	Malcolm Subban	100.00	74	65	67	83	73	72	74	73	72	74	73	71	84	65	50	72	0
2	Troy Grosenick	100.00	71	58	59	74	70	69	71	70	69	71	70	74	88	23	50	69	0
Scratches

	TEAM AVERAGE	100.00	73	62	63	79	72	71	73	72	71	73	72	73	86	44	50	71

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Greg Cronin	69	70	70	66	91	85	58	USA	59	9	1,000,000$

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
1	Luke Glendening	Toronto Leafs	C	23	10	24	34	21	6	0	34	88	114	33	98	8.77%	13	512	22.27	3	7	10	22	70	1	1	2	9	125	2	0	79.35%	707	0	0	0	0	1.33	0	2	0	0	0	1	6	2
Team Total or Average				23	10	24	34	21	6	0	34	88	114	33	98	8.77%	13	512	22.27	3	7	10	22	70	1	1	2	9	125	2	0	79.35%	707	0	0	0	0	1.33	0	2	0	0	0	1	6	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	A	EG	PS %	PSA	ST	BG	S1	S2	S3
Team Total or Average							0.000	0.00	0								0.000

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	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
Anthony Bitetto	D	33	1990-07-15	No	210 Lbs	6 ft1	No	No	No	3	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Ashton Sautner	D	29	1994-05-27	No	195 Lbs	6 ft1	No	No	No	4	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Brett Seney	C/LW	28	1996-02-28	No	156 Lbs	5 ft9	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Charles Hudon	C/LW/RW	29	1994-06-23	No	190 Lbs	5 ft10	No	No	No	3	UFA	Pro & Farm	785,662$	0$	0$	No	Link / NHL Link
Chase DeLeo	C/LW	28	1995-10-25	No	185 Lbs	5 ft9	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Clark Bishop	C/LW	28	1996-03-29	No	197 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Danny O'Regan	C/LW	30	1994-01-30	No	180 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Dylan Sikura	C/LW/RW	28	1995-06-01	No	170 Lbs	5 ft11	No	No	No	4	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Joseph Cramarossa	C	31	1992-10-26	No	190 Lbs	6 ft1	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Keaton Thompson	D	28	1995-09-14	No	182 Lbs	6 ft0	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Malcolm Subban	G	30	1993-12-21	No	215 Lbs	6 ft2	No	No	No	4	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Mitch Reinke	D	28	1996-02-04	No	181 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Pierre-Cedric Labrie	LW	37	1986-12-06	No	226 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Sean Malone	C	28	1995-04-30	No	197 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Seth Helgeson	D	33	1990-10-08	No	219 Lbs	6 ft4	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Troy Grosenick	G	34	1989-08-27	No	185 Lbs	6 ft1	No	No	No	4	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Tyrell Goulbourne	LW	30	1994-01-26	No	203 Lbs	5 ft11	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
17	30.12	193 Lbs	6 ft0	2.29	457,980$

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
70	18	L2	152	294	446	1875	3442	969	552	1322	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
70	8	61	1	0	0	0	152	416

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
34	6	28	0	0	0	0	74	189

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	2	33	1	0	0	0	78	227

Last 10 Games
W	L	OTW	OTL	SOW	SOL
1	9	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
278	34	12.23%	234	66	71.79%	1

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
609	618	647	1	56	45	50	1

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
585	1730	33.82%	727	2526	28.78%	317	1129	28.08%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1069	723	2389	507	741	293

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	Link
5 - 2023-08-14	14	Americans	8	Marlies	1	L		BoxScore
6 - 2023-08-15	28	Comets	5	Marlies	1	L		BoxScore
12 - 2023-08-21	44	Checkers	3	Marlies	5	W		BoxScore
13 - 2023-08-22	61	Checkers	5	Marlies	6	W		BoxScore
15 - 2023-08-24	64	Admirals	4	Marlies	6	W		BoxScore
18 - 2023-08-27	78	Marlies	2	Senators	9	L		BoxScore
19 - 2023-08-28	91	Marlies	1	Senators	6	L		BoxScore
25 - 2023-09-03	115	Marlies	1	Rocket	5	L		BoxScore
26 - 2023-09-04	130	Marlies	1	Rocket	7	L		BoxScore
30 - 2023-09-08	144	Marlies	0	Admirals	6	L		BoxScore
32 - 2023-09-10	154	Marlies	1	Griffins	8	L		BoxScore
33 - 2023-09-11	167	Marlies	0	Griffins	10	L		BoxScore
40 - 2023-09-18	205	Moose	4	Marlies	1	L		BoxScore
41 - 2023-09-19	219	Moose	8	Marlies	1	L		BoxScore
43 - 2023-09-21	224	Phantoms	3	Marlies	1	L		BoxScore
46 - 2023-09-24	240	Marlies	0	Monsters	3	L		BoxScore
48 - 2023-09-26	266	Monsters	6	Marlies	1	L		BoxScore
53 - 2023-10-01	278	Marlies	3	Crunch	5	L		BoxScore
54 - 2023-10-02	290	Crunch	3	Marlies	5	W		BoxScore
57 - 2023-10-05	309	Griffins	8	Marlies	0	L		BoxScore
62 - 2023-10-10	346	Griffins	7	Marlies	1	L		BoxScore
67 - 2023-10-15	363	Marlies	5	Bruins	10	L		BoxScore
69 - 2023-10-17	381	Marlies	0	Wolfpack	6	L		BoxScore
72 - 2023-10-20	390	Bruins	4	Marlies	1	L		BoxScore
74 - 2023-10-22	405	Marlies	1	Senators	8	L		BoxScore
78 - 2023-10-26	425	Senators	7	Marlies	2	L		BoxScore
79 - 2023-10-27	428	Marlies	3	Monsters	7	L		BoxScore
82 - 2023-10-30	451	Senators	5	Marlies	2	L		BoxScore
86 - 2023-11-03	471	Monsters	2	Marlies	3	W		BoxScore
89 - 2023-11-06	488	Crunch	4	Marlies	3	L		BoxScore
90 - 2023-11-07	508	Crunch	6	Marlies	5	L		BoxScore
95 - 2023-11-12	519	Senators	10	Marlies	3	L		BoxScore
97 - 2023-11-14	545	Marlies	2	Senators	9	L		BoxScore
103 - 2023-11-20	575	Marlies	6	Checkers	5	W	X	BoxScore
104 - 2023-11-21	589	Marlies	4	Checkers	5	L		BoxScore
107 - 2023-11-24	599	Marlies	3	Monsters	5	L		BoxScore
110 - 2023-11-27	629	Marlies	2	Phantoms	8	L		BoxScore
111 - 2023-11-28	640	Marlies	4	Bears	3	W		BoxScore
114 - 2023-12-01	648	Marlies	1	Penguins	6	L		BoxScore
116 - 2023-12-03	657	Marlies	1	Comets	3	L		BoxScore
117 - 2023-12-04	670	Marlies	2	Comets	7	L		BoxScore
123 - 2023-12-10	685	Rocket	4	Marlies	0	L		BoxScore
124 - 2023-12-11	697	Rocket	2	Marlies	1	L		BoxScore
128 - 2023-12-15	717	Penguins	7	Marlies	1	L		BoxScore
130 - 2023-12-17	726	Marlies	3	Senators	7	L		BoxScore
131 - 2023-12-18	735	Bears	4	Marlies	2	L		BoxScore
133 - 2023-12-20	755	Americans	5	Marlies	0	L		BoxScore
137 - 2023-12-24	772	Marlies	2	Rocket	8	L		BoxScore
138 - 2023-12-25	782	Marlies	1	Rocket	4	L		BoxScore
142 - 2023-12-29	808	Marlies	2	Monsters	7	L		BoxScore
144 - 2023-12-31	817	Marlies	4	Crunch	5	L		BoxScore
145 - 2024-01-01	831	Crunch	4	Marlies	5	W		BoxScore
149 - 2024-01-05	850	Senators	6	Marlies	3	L		BoxScore
151 - 2024-01-07	859	Marlies	2	Comets	6	L		BoxScore
152 - 2024-01-08	878	Marlies	1	Thunderbirds	7	L		BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
158 - 2024-01-14	910	Marlies	3	Americans	9	L		BoxScore
159 - 2024-01-15	915	Americans	9	Marlies	2	L		BoxScore
160 - 2024-01-16	931	Rocket	8	Marlies	2	L		BoxScore
165 - 2024-01-21	955	Marlies	1	Americans	7	L		BoxScore
166 - 2024-01-22	961	Wolfpack	8	Marlies	0	L		BoxScore
167 - 2024-01-23	978	Rocket	4	Marlies	1	L		BoxScore
170 - 2024-01-26	990	Marlies	4	Moose	6	L		BoxScore
172 - 2024-01-28	994	Marlies	3	Moose	4	L		BoxScore
177 - 2024-02-02	1027	Thunderbirds	5	Marlies	2	L		BoxScore
180 - 2024-02-05	1047	Comets	6	Marlies	3	L		BoxScore
181 - 2024-02-06	1064	Comets	8	Marlies	1	L		BoxScore
184 - 2024-02-09	1070	Senators	7	Marlies	3	L		BoxScore
186 - 2024-02-11	1078	Marlies	6	Crunch	4	W		BoxScore
187 - 2024-02-12	1093	Marlies	2	Crunch	4	L		BoxScore
191 - 2024-02-16	1112	Marlies	1	Americans	8	L		BoxScore
194 - 2024-02-19	1130	Monsters	-	Marlies	-
195 - 2024-02-20	1148	Monsters	-	Marlies	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	63,965	32,023
Attendance PCT	94.07%	94.19%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
2	2823 - 94.11%	70,377$	2,392,824$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,058,736$	77,857$	0$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	79,288$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
140,754$	4	5,527$	22,108$

Show or Hide Column

	Overall											Home											Visitor
Year	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Regular Season
12	82	9	68	0	2	2	0	1	170	454	-284	41	6	32	0	0	2	0	1	91	224	-133	41	3	36	0	2	0	0	0	79	230	-151	25	170	331	501	1	0	0	66	56	46	2056	0	706	670	665	3666	1018	775	1475	392	47	11.99%	321	102	68.22%	2	686	1998	34.33%	901	2849	31.63%	399	1355	29.45%	1241	824	2800	620	894	352
12	82	9	68	0	2	2	0	1	170	454	-284	41	6	32	0	0	2	0	1	91	224	-133	41	3	36	0	2	0	0	0	79	230	-151	25	170	331	501	1	0	0	66	56	46	2056	0	706	670	665	3666	1018	775	1475	392	47	11.99%	321	102	68.22%	2	686	1998	34.33%	901	2849	31.63%	399	1355	29.45%	1241	824	2800	620	894	352
13	76	4	68	0	1	3	0	0	118	417	-299	38	1	36	0	0	1	0	0	60	210	-150	38	3	32	0	1	2	0	0	58	207	-149	13	118	230	348	0	0	0	46	35	36	1763	0	580	601	579	3257	875	646	1275	323	30	9.29%	261	71	72.80%	1	527	1803	29.23%	702	2546	27.57%	326	1211	26.92%	1050	685	2692	580	827	303
13	76	4	68	0	1	3	0	0	118	417	-299	38	1	36	0	0	1	0	0	60	210	-150	38	3	32	0	1	2	0	0	58	207	-149	13	118	230	348	0	0	0	46	35	36	1763	0	580	601	579	3257	875	646	1275	323	30	9.29%	261	71	72.80%	1	527	1803	29.23%	702	2546	27.57%	326	1211	26.92%	1050	685	2692	580	827	303
14	76	4	69	0	0	2	1	0	123	440	-317	38	2	33	0	0	2	1	0	60	216	-156	38	2	36	0	0	0	0	0	63	224	-161	12	123	234	357	0	0	0	47	41	34	1643	0	544	519	576	3644	1020	713	1260	277	24	8.66%	303	74	75.58%	4	415	1718	24.16%	676	2732	24.74%	310	1205	25.73%	991	636	2786	561	791	289
14	76	4	69	0	0	2	1	0	123	440	-317	38	2	33	0	0	2	1	0	60	216	-156	38	2	36	0	0	0	0	0	63	224	-161	12	123	234	357	0	0	0	47	41	34	1643	0	544	519	576	3644	1020	713	1260	277	24	8.66%	303	74	75.58%	4	415	1718	24.16%	676	2732	24.74%	310	1205	25.73%	991	636	2786	561	791	289
15	82	32	31	0	6	6	2	5	200	180	20	41	16	14	0	4	3	2	2	110	93	17	41	16	17	0	2	3	0	3	90	87	3	91	200	344	544	3	10	0	79	61	52	2102	0	679	704	683	2258	656	1189	1618	386	62	16.06%	465	57	87.74%	2	1152	2444	47.14%	1147	2662	43.09%	553	1151	48.05%	2005	1416	2016	580	959	478
15	82	32	31	0	6	6	2	5	200	180	20	41	16	14	0	4	3	2	2	110	93	17	41	16	17	0	2	3	0	3	90	87	3	91	200	344	544	3	10	0	79	61	52	2102	0	679	704	683	2258	656	1189	1618	386	62	16.06%	465	57	87.74%	2	1152	2444	47.14%	1147	2662	43.09%	553	1151	48.05%	2005	1416	2016	580	959	478
16	82	21	48	0	2	4	4	3	164	253	-89	41	16	18	0	1	3	1	2	100	121	-21	41	5	30	0	1	1	3	1	64	132	-68	61	164	262	426	2	4	0	65	53	40	1858	0	601	621	614	2791	792	942	1665	362	64	17.68%	374	69	81.55%	0	659	2101	31.37%	889	2953	30.10%	357	1137	31.40%	1663	1155	2399	579	903	416
16	82	21	48	0	2	4	4	3	164	253	-89	41	16	18	0	1	3	1	2	100	121	-21	41	5	30	0	1	1	3	1	64	132	-68	61	164	262	426	2	4	0	65	53	40	1858	0	601	621	614	2791	792	942	1665	362	64	17.68%	374	69	81.55%	0	659	2101	31.37%	889	2953	30.10%	357	1137	31.40%	1663	1155	2399	579	903	416
17	72	7	62	0	2	0	0	1	141	423	-282	36	5	29	0	1	0	0	1	75	210	-135	36	2	33	0	1	0	0	0	66	213	-147	19	141	273	414	1	0	0	57	45	37	1880	0	682	558	630	3287	919	588	1326	255	34	13.33%	256	73	71.48%	1	574	1753	32.74%	743	2503	29.68%	360	1169	30.80%	1108	742	2454	518	768	307
17	72	7	62	0	2	0	0	1	141	423	-282	36	5	29	0	1	0	0	1	75	210	-135	36	2	33	0	1	0	0	0	66	213	-147	19	141	273	414	1	0	0	57	45	37	1880	0	682	558	630	3287	919	588	1326	255	34	13.33%	256	73	71.48%	1	574	1753	32.74%	743	2503	29.68%	360	1169	30.80%	1108	742	2454	518	768	307
18	70	8	61	0	1	0	0	0	152	416	-264	34	6	28	0	0	0	0	0	74	189	-115	36	2	33	0	1	0	0	0	78	227	-149	18	152	294	446	1	0	56	45	50	1	1875	609	618	647	1	3442	969	552	1322	278	34	12.23%	234	66	71.79%	1	585	1730	33.82%	727	2526	28.78%	317	1129	28.08%	1069	723	2389	507	741	293
Total Regular Season	1010	162	753	0	27	34	14	20	1984	4750	-2766	504	98	352	0	12	22	8	12	1066	2337	-1271	506	64	401	0	15	12	6	8	918	2413	-1495	460	1984	3642	5626	15	28	56	765	632	491	24479	609	8202	7993	7495	41248	11529	10258	18560	4268	556	13.03%	4194	958	77.16%	21	8611	25364	33.95%	10843	35016	30.97%	4927	15585	31.61%	17193	11648	32688	7387	11031	4592