LHSDB - Ligue de hockey simulee des debiles barbus

Florida Panthers
Roster
Scoring
Informations
Lines
Stats
Schedule
Finance
Records

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	Evgeny Svechnikov		X	X		100.00	70	36	84	67	85	78	84	68	57	66	63	56	70	68	67	79	50	65	0
2	Alex Nylander		X	X		100.00	60	37	94	66	76	87	95	65	62	61	63	58	67	64	66	85	50	64	0
3	Nathan Smith (R)	X				100.00	79	34	82	64	70	84	67	63	78	64	65	56	62	63	64	61	50	63	0
4	Taro Hirose		X			100.00	61	35	94	66	63	86	83	67	71	66	58	56	64	67	68	42	50	63	0
5	Gage Goncalves (R)	X				100.00	62	38	82	58	71	75	85	55	63	56	59	55	58	61	63	68	50	59	0
6	Curtis Hall	X				100.00	64	38	91	52	83	72	74	53	58	54	55	51	53	62	64	66	50	57	0
7	Daniil Miromanov				X	100.00	73	39	82	68	87	79	85	67	30	66	58	63	52	65	67	54	50	67	0
8	Chris Wideman				X	100.00	63	36	77	72	66	85	79	68	30	76	63	58	53	72	75	38	50	66	0
9	Brian Lashoff				X	100.00	77	42	83	57	86	65	88	56	30	55	54	58	46	72	77	27	50	63	0
10	Ben Gleason				X	100.00	64	38	77	62	73	76	94	61	30	65	56	55	48	64	66	52	50	62	0
11	Tyler Wotherspoon				X	100.00	73	35	84	56	82	69	80	55	30	60	52	59	46	69	71	56	50	62	0
12	Dillon Simpson				X	100.00	72	38	93	57	81	69	89	56	30	57	56	58	48	69	74	51	50	62	0
13	Donovan Sebrango				X	100.00	66	38	87	55	74	63	84	54	30	53	52	51	45	60	62	69	50	57	0
Scratches

	TEAM AVERAGE					100.00	68	37	85	62	77	76	84	61	46	61	58	56	55	66	68	58	50	62

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	Hunter Shepard	100.00	76	66	67	79	75	74	76	75	74	76	75	67	77	37	50	72	0
2	Joey Daccord	100.00	74	82	79	80	73	72	74	73	72	74	73	66	75	56	50	72	0
Scratches
1	Nico Daws (R)	100.00	73	81	80	87	72	71	73	72	71	73	72	62	67	65	50	72	0
2	Alex Stalock	100.00	73	70	72	69	72	71	73	72	71	73	72	76	89	45	50	71	0
3	John Lethemon	100.00	73	65	66	83	72	71	73	72	71	73	72	66	75	42	50	70	0
4	Philippe Desrosiers	100.00	70	74	75	76	69	68	70	69	68	70	69	67	77	60	50	69	0

	TEAM AVERAGE	100.00	73	73	73	79	72	71	73	72	71	73	72	67	77	51	50	71

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Chris Taylor	61	61	64	69	75	70	76	CAN	50	4	100,000$

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	PKM	GW	GT	FO%	FOT	P/20	PSG	PSS	FL	FT	S1	S2	S3
1	Taro Hirose	Thunderbirds (Flo)	LW	72	20	13	33	-6	36	10	81	75	161	48	123	12.42%	26	642	8.92	0	0	0	0	0	0	0	0	60.53%	38	1.03	1	3	1	1	10	3	4
2	Joel Teasdale	Florida Panthers	LW/RW	57	13	19	32	23	23	5	41	71	155	37	117	8.39%	9	826	14.49	3	3	6	21	108	22	1	2	60.94%	64	0.77	0	0	0	1	0	1	3
3	Dakota Joshua	Florida Panthers	C	69	10	0	10	-10	20	0	32	38	91	23	85	10.99%	14	224	3.25	0	0	0	0	0	0	1	0	59.31%	290	0.89	1	2	0	0	3	6	3
4	Chris Wideman	Thunderbirds (Flo)	D	72	0	10	10	-8	29	5	38	27	12	10	13	0.00%	25	231	3.22	0	0	0	0	0	0	0	0	0.00%	0	0.86	0	1	1	0	0	4	7
Team Total or Average				270	43	42	85	-1	108	20	192	211	419	118	338	10.26%	74	1924	7.13	3	3	6	21	108	22	2	2	59.69%	392	0.88	2	6	2	2	13	14	17

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
Alex Nylander	LW/RW	25	1998-03-02	No	192 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Alex Stalock	G	35	1987-07-28	No	170 Lbs	5 ft11	No	No	No	3	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Ben Gleason	D	24	1998-03-25	No	180 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Brian Lashoff	D	32	1990-07-16	No	213 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Chris Wideman	D	33	1990-01-07	No	180 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Curtis Hall	C	22	2000-04-26	No	197 Lbs	6 ft3	No	No	No	2	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Daniil Miromanov	D	25	1997-07-11	No	202 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Dillon Simpson	D	30	1993-02-10	No	204 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Donovan Sebrango	D	21	2002-01-12	No	189 Lbs	6 ft1	No	No	No	4	ELC	Pro & Farm	500,000$	0$	0$	No	Link
Evgeny Svechnikov	LW/RW	26	1996-10-31	No	208 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Gage Goncalves	C	22	2001-01-16	Yes	181 Lbs	6 ft0	No	No	No	4	ELC	Pro & Farm	500,000$	0$	0$	No
Hunter Shepard	G	27	1995-11-07	No	209 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	750,000$	0$	0$	No	Link
Joey Daccord	G	26	1996-08-19	No	197 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
John Lethemon	G	26	1996-08-15	No	196 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Nathan Smith	C	24	1998-10-19	Yes	177 Lbs	6 ft0	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No
Nico Daws	G	22	2000-12-22	Yes	205 Lbs	6 ft4	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No
Philippe Desrosiers	G	27	1995-08-16	No	195 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Taro Hirose	LW	26	1996-06-30	No	162 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Tyler Wotherspoon	D	29	1993-03-12	No	207 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
19	26.42	193 Lbs	6 ft1	2.05	431,579$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	1	3
2				30	1	1	3
3			Taro Hirose	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	Chris Wideman		10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				60	0	1	4
2				40	0	1	4

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	0	2	3
2			40	0	2	3

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	3	1
2			40	1	3	1

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	3	1
2			40	1	3	1

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	0	5	0			60	0	5	0
2		40	0	5	0			40	0	5	0

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
, , Chris Wideman		, Chris Wideman

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
72	27	L2	144	274	418	1926	3461	975	664	1245	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
72	10	57	1	1	1	2	144	362

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	6	29	0	0	0	1	75	180

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	4	28	1	1	1	1	69	182

Last 10 Games
W	L	OTW	OTL	SOW	SOL
0	8	0	1	0	1

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
248	17	6.85%	273	61	77.66%	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
680	618	610	29	78	32	32	3

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
612	1806	33.89%	752	2560	29.38%	340	1087	31.28%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1128	775	2462	513	747	296

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
3 - 2022-09-30	15	Senators	7	Thunderbirds	1	L			BoxScore
5 - 2022-10-02	35	Americans	10	Thunderbirds	0	L			BoxScore
8 - 2022-10-05	52	Thunderbirds	1	Eagles	2	L			BoxScore
10 - 2022-10-07	70	Sound Tigers	4	Thunderbirds	1	L			BoxScore
13 - 2022-10-10	87	Thunderbirds	2	Bruins	3	L	X	X	BoxScore
15 - 2022-10-12	101	Thunderbirds	3	Penguins	7	L			BoxScore
16 - 2022-10-13	111	Thunderbirds	1	Moose	7	L			BoxScore
17 - 2022-10-14	122	Condors	4	Thunderbirds	3	L			BoxScore
19 - 2022-10-16	138	Thunderbirds	2	Griffins	7	L			BoxScore
21 - 2022-10-18	155	Senators	3	Thunderbirds	1	L			BoxScore
24 - 2022-10-21	174	IceHogs	4	Thunderbirds	3	L			BoxScore
27 - 2022-10-24	197	Barracuda	5	Thunderbirds	1	L			BoxScore
29 - 2022-10-26	217	Thunderbirds	4	Admirals	2	W			BoxScore
31 - 2022-10-28	227	Thunderbirds	1	Penguins	7	L			BoxScore
33 - 2022-10-30	236	Marlies	1	Thunderbirds	8	W			BoxScore
35 - 2022-11-01	257	Wolves	7	Thunderbirds	1	L			BoxScore
38 - 2022-11-04	277	Thunderbirds	2	Devils	9	L			BoxScore
41 - 2022-11-07	294	Firebirds	4	Thunderbirds	6	W			BoxScore
43 - 2022-11-09	312	Thunderbirds	1	Wild	6	L			BoxScore
45 - 2022-11-11	324	Thunderbirds	0	Crunch	5	L			BoxScore
46 - 2022-11-12	334	Rampage	6	Thunderbirds	0	L			BoxScore
49 - 2022-11-15	353	Stars	5	Thunderbirds	1	L			BoxScore
51 - 2022-11-17	371	Thunderbirds	2	Phantoms	4	L			BoxScore
54 - 2022-11-20	389	Eagles	6	Thunderbirds	1	L			BoxScore
56 - 2022-11-22	403	Thunderbirds	2	Wolf Pack	3	L			BoxScore
58 - 2022-11-24	421	Thunderbirds	1	Wolves	7	L			BoxScore
60 - 2022-11-26	430	Bruins	2	Thunderbirds	1	L			BoxScore
62 - 2022-11-28	449	Thunderbirds	0	Wranglers	2	L			BoxScore
64 - 2022-11-30	462	Americans	6	Thunderbirds	1	L			BoxScore
67 - 2022-12-03	486	Crunch	7	Thunderbirds	0	L			BoxScore
69 - 2022-12-05	498	Thunderbirds	1	Americans	6	L			BoxScore
71 - 2022-12-07	516	Thunderbirds	3	Bears	2	W	X	X	BoxScore
72 - 2022-12-08	527	Griffins	7	Thunderbirds	0	L			BoxScore
75 - 2022-12-11	548	Thunderbirds	5	Roadrunners	4	W	X		BoxScore
77 - 2022-12-13	555	Monsters	6	Thunderbirds	1	L			BoxScore
79 - 2022-12-15	572	Thunderbirds	0	Barracuda	7	L			BoxScore
81 - 2022-12-17	586	Reign	3	Thunderbirds	8	W			BoxScore
83 - 2022-12-19	604	Thunderbirds	1	Rampage	4	L			BoxScore
85 - 2022-12-21	619	Condors	5	Thunderbirds	3	L			BoxScore
87 - 2022-12-23	632	Thunderbirds	4	Reign	3	W			BoxScore
89 - 2022-12-25	649	Roadrunners	2	Thunderbirds	4	W			BoxScore
92 - 2022-12-28	677	Checkers	4	Thunderbirds	2	L			BoxScore
94 - 2022-12-30	689	Thunderbirds	2	Bruins	4	L			BoxScore
96 - 2023-01-01	706	Bears	4	Thunderbirds	6	W			BoxScore
98 - 2023-01-03	723	Thunderbirds	1	Senators	6	L			BoxScore
100 - 2023-01-05	734	Thunderbirds	3	Sound Tigers	9	L			BoxScore
102 - 2023-01-07	748	Sound Tigers	5	Thunderbirds	0	L			BoxScore
105 - 2023-01-10	769	Thunderbirds	5	Firebirds	3	W			BoxScore
106 - 2023-01-11	781	Devils	6	Thunderbirds	1	L			BoxScore
109 - 2023-01-14	795	Thunderbirds	3	IceHogs	4	L			BoxScore
111 - 2023-01-16	812	Wranglers	8	Thunderbirds	1	L			BoxScore
115 - 2023-01-20	837	Thunderbirds	0	Comets	4	L			BoxScore
116 - 2023-01-21	845	Wolf Pack	5	Thunderbirds	1	L			BoxScore
119 - 2023-01-24	871	Wild	5	Thunderbirds	4	L			BoxScore
121 - 2023-01-26	883	Thunderbirds	1	Griffins	5	L			BoxScore
123 - 2023-01-28	903	Rocket	9	Thunderbirds	1	L			BoxScore
125 - 2023-01-30	918	Thunderbirds	0	Checkers	8	L			BoxScore
127 - 2023-02-01	933	Thunderbirds	1	Stars	6	L			BoxScore
129 - 2023-02-03	940	Penguins	6	Thunderbirds	1	L			BoxScore
131 - 2023-02-05	960	Thunderbirds	3	Rocket	1	W			BoxScore
132 - 2023-02-06	972	Thunderbirds	0	Eagles	5	L			BoxScore
134 - 2023-02-08	982	Gulls	3	Thunderbirds	5	W			BoxScore
136 - 2023-02-10	997	Thunderbirds	1	Moose	9	L			BoxScore
137 - 2023-02-11	1011	Moose	6	Thunderbirds	0	L			BoxScore
141 - 2023-02-15	1035	Senators	3	Thunderbirds	1	L			BoxScore
143 - 2023-02-17	1050	Thunderbirds	5	Marlies	7	L			BoxScore
145 - 2023-02-19	1064	Thunderbirds	5	Gulls	6	L	X		BoxScore
147 - 2023-02-21	1076	Phantoms	2	Thunderbirds	0	L			BoxScore
148 - 2023-02-22	1077	Thunderbirds	3	Condors	5	L			BoxScore
151 - 2023-02-25	1107	Admirals	5	Thunderbirds	4	L	X	X	BoxScore
152 - 2023-02-26	1111	Thunderbirds	0	Monsters	3	L			BoxScore
157 - 2023-03-03	1138	Comets	5	Thunderbirds	3	L			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	67,472	33,518
Attendance PCT	93.71%	93.11%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	2805 - 93.51%	70,016$	2,520,576$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
192,223$	82,000$	0$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	92,242$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	1,130$	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
12	82	27	47	0	4	1	0	3	229	277	-48	41	10	27	0	3	0	0	1	103	146	-43	41	17	20	0	1	1	0	2	126	131	-5	66	229	421	650	2	7	0	89	87	49	2312	0	738	806	751	2896	824	938	1675	451	65	14.41%	387	57	85.27%	3	985	2317	42.51%	1140	2724	41.85%	493	1203	40.98%	1669	1152	2348	600	926	425
13	76	14	54	0	4	3	0	1	187	334	-147	38	9	23	0	2	3	0	1	107	157	-50	38	5	31	0	2	0	0	0	80	177	-97	40	187	319	506	1	1	0	71	71	41	2135	0	685	709	729	2656	769	750	1372	401	39	9.73%	323	87	73.07%	1	884	2198	40.22%	856	2298	37.25%	457	1153	39.64%	1408	970	2331	569	840	357
14	76	32	26	0	8	4	2	4	193	164	29	38	18	13	0	3	2	0	2	92	77	15	38	14	13	0	5	2	2	2	101	87	14	92	193	332	525	1	9	0	64	68	51	2027	0	687	681	633	1899	622	690	1163	344	48	13.95%	266	37	86.09%	2	1114	2318	48.06%	1089	2302	47.31%	528	1047	50.43%	1825	1309	1898	541	897	440
15	82	25	40	0	6	4	4	3	204	246	-42	41	15	15	0	5	2	2	2	117	109	8	41	10	25	0	1	2	2	1	87	137	-50	77	204	345	549	0	6	0	71	64	59	2201	0	716	725	731	2691	797	910	1487	386	69	17.88%	383	52	86.42%	3	1164	2410	48.30%	1226	2795	43.86%	551	1153	47.79%	1825	1292	2230	579	927	433
16	82	46	23	0	2	2	4	5	230	137	93	41	19	16	0	1	1	0	4	87	69	18	41	27	7	0	1	1	4	1	143	68	75	111	230	407	637	0	18	0	95	74	55	2083	0	693	673	691	1646	513	1425	1704	412	74	17.96%	610	65	89.34%	6	1646	2570	64.05%	1465	2425	60.41%	658	1067	61.67%	2328	1680	1670	563	975	519
17	72	10	57	0	1	1	1	2	144	362	-218	36	6	29	0	0	0	0	1	75	180	-105	36	4	28	0	1	1	1	1	69	182	-113	27	144	274	418	1	0	78	32	32	3	1926	680	618	610	29	3461	975	664	1245	248	17	6.85%	273	61	77.66%	2	612	1806	33.89%	752	2560	29.38%	340	1087	31.28%	1128	775	2462	513	747	296
Total Regular Season	470	154	247	0	25	15	11	18	1187	1520	-333	235	77	123	0	14	8	2	11	581	738	-157	235	77	124	0	11	7	9	7	606	782	-176	413	1187	2098	3285	5	41	78	422	396	258	12684	680	4137	4204	3564	15249	4500	5377	8646	2242	312	13.92%	2242	359	83.99%	17	6405	13619	47.03%	6528	15104	43.22%	3027	6710	45.11%	10185	7181	12941	3368	5314	2471
Playoff
16	6	2	4	0	0	0	0	0	7	9	-2	3	1	2	0	0	0	0	0	5	5	0	3	1	2	0	0	0	0	0	2	4	-2	4	7	14	21	1	1	0	2	1	4	87	0	26	27	34	131	47	120	128	24	2	8.33%	55	3	94.55%	0	81	153	52.94%	94	191	49.21%	38	78	48.72%	134	88	149	46	76	35
Total Playoff	6	2	4	0	0	0	0	0	7	9	-2	3	1	2	0	0	0	0	0	5	5	0	3	1	2	0	0	0	0	0	2	4	-2	4	7	14	21	1	1	0	2	1	4	87	0	26	27	34	131	47	120	128	24	2	8.33%	55	3	94.55%	0	81	153	52.94%	94	191	49.21%	38	78	48.72%	134	88	149	46	76	35