LHSDB - Ligue de hockey simulee des debiles barbus

Tampa Lightning
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	Mason McTavish (R)	X				100.00	72	35	80	66	76	83	75	69	70	65	68	67	71	60	62	93	50	66	0
2	Byron Froese	X				100.00	70	39	87	60	78	87	77	63	78	61	62	68	64	71	76	51	50	65	0
3	Karson Kuhlman	X		X		100.00	74	34	86	67	68	79	77	65	71	63	64	65	62	67	68	39	50	64	0
4	Brendan Perlini	X	X			100.00	75	42	86	64	86	71	70	64	53	62	68	55	64	66	68	81	50	63	0
5	Dmitrij Jaskin			X		100.00	86	36	89	63	84	85	68	64	59	62	55	61	66	71	69	65	50	63	0
6	Lane Pederson	X				100.00	68	36	81	62	74	82	79	60	76	62	61	59	63	66	67	54	50	62	0
7	Max Willman	X				100.00	65	39	79	63	71	84	87	60	68	57	61	59	61	67	69	50	50	62	0
8	Christopher Wilkie			X		100.00	63	38	82	59	72	78	69	58	52	60	57	56	59	66	68	45	50	59	0
9	Chad Yetman			X		100.00	59	36	91	58	68	69	63	56	51	57	54	53	56	62	64	52	50	57	0
10	Wyatt Newpower				X	100.00	73	34	75	56	82	65	81	55	30	56	54	63	45	65	67	52	50	62	0
11	Nikolas Brouillard				X	100.00	57	43	63	61	64	74	86	59	30	62	57	56	50	67	69	37	50	60	0
12	Blake Hillman				X	100.00	67	38	92	58	76	66	63	56	30	59	50	57	45	66	68	57	50	59	0
Scratches

	TEAM AVERAGE					100.00	69	38	83	61	75	77	75	61	56	61	59	60	59	66	68	56	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	Louis Domingue	100.00	73	75	77	85	72	71	73	72	71	73	72	72	84	53	50	73	0
2	Trevin Kozlowski	100.00	67	68	65	90	66	65	67	66	65	67	66	65	73	42	50	67	0
Scratches
1	Kaden Fulcher	100.00	64	66	67	84	63	62	64	63	62	64	63	64	71	43	50	65	0

	TEAM AVERAGE	100.00	68	70	70	86	67	66	68	67	66	68	67	67	76	46	50	68

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Mike Van Ryn	65	70	73	68	64	59	83	CAN	43	2	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	PKP	PKS	PKM	GW	GT	FO%	FOT	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3
1	Karson Kuhlman	Crunch (Tam)	C/RW	72	57	53	110	37	47	5	123	170	439	122	351	12.98%	35	1157	16.08	12	9	21	95	242	0	0	0	0	9	2	73.97%	73	4	1.90	1	2	0	0	1	6	10	7
2	Lane Pederson	Crunch (Tam)	C	70	51	57	108	39	50	20	87	169	368	127	300	13.86%	33	1122	16.04	8	12	20	78	236	0	0	0	0	5	4	61.75%	1396	4	1.92	0	6	0	0	4	11	4	8
3	Byron Froese	Crunch (Tam)	C	72	76	25	101	-1	106	30	226	274	565	146	395	13.45%	75	1541	21.41	24	10	34	159	301	0	0	1	23	8	4	61.23%	1749	9	1.31	1	8	1	1	4	14	6	3
4	Wyatt Newpower	Crunch (Tam)	D	72	10	62	72	-7	160	0	211	137	204	75	163	4.90%	104	1480	20.57	6	17	23	130	216	1	1	3	114	0	2	0.00%	0	0	0.97	0	1	0	0	0	0	3	6
5	Brendan Perlini	Crunch (Tam)	C/LW	71	35	13	48	10	40	0	146	93	216	72	197	16.20%	38	713	10.04	0	0	0	0	0	0	0	1	6	5	1	50.00%	84	2	1.35	0	2	0	0	0	4	4	9
6	Christopher Wilkie	Crunch (Tam)	RW	72	12	6	18	-9	31	15	83	45	107	31	72	11.21%	36	379	5.27	0	0	0	0	0	0	0	0	0	0	0	52.17%	23	0	0.95	0	1	0	1	2	0	3	0
Team Total or Average				429	241	216	457	69	434	70	876	888	1899	573	1478	12.69%	321	6396	14.91	50	48	98	462	997	1	1	5	143	27	13	61.38%	3325	19	1.43	2	20	1	2	11	35	30	33

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	Louis Domingue	Crunch (Tam)	25	16	7	2	0.935	2.03	1451	2	2	49	756	5	0.850	20	25	35	3	4	4
2	Logan Thompson	Tampa Lightning	10	6	1	3	0.919	2.46	610	0	1	25	308	0	0.500	6	10	0	2	0	1
Team Total or Average			35	22	8	5	0.930	2.15	2061	2	3	74	1064	5	0.769	26	35	35	5	4	5

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
Blake Hillman	D	27	1996-01-26	No	193 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Brendan Perlini	C/LW	26	1996-04-27	No	211 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Byron Froese	C	31	1991-03-12	No	202 Lbs	6 ft1	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Chad Yetman	RW	23	2000-02-18	No	179 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Christopher Wilkie	RW	26	1996-07-10	No	190 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Dmitrij Jaskin	RW	29	1993-03-23	No	216 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link
Kaden Fulcher	G	24	1998-09-23	No	201 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Karson Kuhlman	C/RW	27	1995-09-26	No	190 Lbs	5 ft10	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Lane Pederson	C	25	1997-08-04	No	192 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Louis Domingue	G	30	1992-03-06	No	208 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Mason McTavish	C	20	2003-01-30	Yes	213 Lbs	6 ft0	No	No	No	1	ELC	Pro & Farm		0$	0$	No
Max Willman	C	28	1995-02-13	No	184 Lbs	6 ft0	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link
Nikolas Brouillard	D	28	1995-02-07	No	168 Lbs	5 ft10	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link
Trevin Kozlowski	G	25	1997-03-27	No	220 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Wyatt Newpower	D	25	1997-12-09	No	194 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
15	26.27	197 Lbs	6 ft1	1.60	336,667$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1		Byron Froese		40	1	2	2
2			Karson Kuhlman	30	1	2	2
3				20	1	2	2
4			Christopher Wilkie	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1		Wyatt Newpower	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		Byron Froese		60	1	2	2
2			Karson Kuhlman	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1		Wyatt Newpower	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	Byron Froese		40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1		Wyatt Newpower	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		Wyatt Newpower	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	Byron Froese		40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1		Wyatt Newpower	60	1	2	2
2			40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
	Byron Froese			Wyatt Newpower

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
	Byron Froese			Wyatt Newpower

Extra Forwards
Normal	PowerPlay	Penalty Kill
, ,	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , Byron Froese, ,

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	81	L3	290	441	731	2632	2387	712	703	1280	1	3

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
72	33	28	2	1	2	6	290	264

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	18	12	0	0	2	4	152	131

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	15	16	2	1	0	2	138	133

Last 10 Games
W	L	OTW	OTL	SOW	SOL
3	7	0	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
347	60	17.29%	294	65	77.89%	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
851	832	927	52	123	79	84	6

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1186	2280	52.02%	946	2193	43.14%	608	1188	51.18%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1686	1259	1905	470	774	367

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 - 2022-09-29	12	Crunch	5	Eagles	4	W			BoxScore
4 - 2022-10-01	25	Crunch	1	Griffins	2	L	X		BoxScore
5 - 2022-10-02	31	Admirals	3	Crunch	4	W			BoxScore
7 - 2022-10-04	44	Crunch	1	Moose	2	L			BoxScore
8 - 2022-10-05	59	Firebirds	1	Crunch	7	W			BoxScore
12 - 2022-10-09	81	Rocket	3	Crunch	5	W			BoxScore
16 - 2022-10-13	109	Devils	6	Crunch	5	L	X	X	BoxScore
18 - 2022-10-15	126	Crunch	3	Devils	0	W			BoxScore
20 - 2022-10-17	146	Rocket	4	Crunch	3	L	X	X	BoxScore
21 - 2022-10-18	151	Crunch	3	Bruins	2	W			BoxScore
23 - 2022-10-20	170	Crunch	3	Eagles	4	L			BoxScore
25 - 2022-10-22	185	Devils	2	Crunch	4	W			BoxScore
28 - 2022-10-25	205	Eagles	3	Crunch	4	W	X	X	BoxScore
30 - 2022-10-27	221	Crunch	4	Monsters	2	W			BoxScore
33 - 2022-10-30	237	Penguins	1	Crunch	4	W			BoxScore
35 - 2022-11-01	255	Crunch	3	Griffins	1	W			BoxScore
37 - 2022-11-03	264	Bruins	1	Crunch	2	W	X	X	BoxScore
40 - 2022-11-06	291	Comets	5	Crunch	4	L	X	X	BoxScore
43 - 2022-11-09	307	Crunch	1	Rocket	2	L			BoxScore
45 - 2022-11-11	324	Thunderbirds	0	Crunch	5	W			BoxScore
47 - 2022-11-13	343	Crunch	11	Marlies	2	W			BoxScore
49 - 2022-11-15	357	Monsters	2	Crunch	3	W			BoxScore
51 - 2022-11-17	369	Crunch	0	Sound Tigers	2	L			BoxScore
53 - 2022-11-19	387	Americans	6	Crunch	2	L			BoxScore
55 - 2022-11-21	397	Crunch	2	Wolves	8	L			BoxScore
57 - 2022-11-23	413	Crunch	3	Wild	1	W			BoxScore
59 - 2022-11-25	428	Bears	1	Crunch	8	W			BoxScore
61 - 2022-11-27	439	Crunch	2	Wolf Pack	1	W	X		BoxScore
63 - 2022-11-29	457	Sound Tigers	3	Crunch	1	L			BoxScore
65 - 2022-12-01	467	Crunch	3	Eagles	4	L			BoxScore
67 - 2022-12-03	486	Crunch	7	Thunderbirds	0	W			BoxScore
69 - 2022-12-05	495	Crunch	7	Roadrunners	1	W			BoxScore
70 - 2022-12-06	509	Reign	1	Crunch	9	W			BoxScore
73 - 2022-12-09	532	Crunch	10	IceHogs	1	W			BoxScore
74 - 2022-12-10	539	Wolf Pack	3	Crunch	2	L	X	X	BoxScore
78 - 2022-12-14	562	Admirals	3	Crunch	6	W			BoxScore
80 - 2022-12-16	576	Crunch	5	Admirals	4	W	X		BoxScore
82 - 2022-12-18	595	Gulls	2	Crunch	3	W			BoxScore
84 - 2022-12-20	610	Crunch	2	Barracuda	4	L			BoxScore
86 - 2022-12-22	626	Marlies	4	Crunch	5	W			BoxScore
88 - 2022-12-24	641	Crunch	3	Moose	6	L			BoxScore
90 - 2022-12-26	659	Checkers	6	Crunch	2	L			BoxScore
93 - 2022-12-29	681	Crunch	4	Senators	5	L	X	X	BoxScore
95 - 2022-12-31	693	Condors	2	Crunch	7	W			BoxScore
97 - 2023-01-02	714	Senators	6	Crunch	2	L			BoxScore
99 - 2023-01-04	731	Crunch	2	Penguins	7	L			BoxScore
101 - 2023-01-06	744	Roadrunners	2	Crunch	6	W			BoxScore
103 - 2023-01-08	756	Crunch	4	Phantoms	6	L			BoxScore
106 - 2023-01-11	780	Barracuda	4	Crunch	1	L			BoxScore
108 - 2023-01-13	793	Crunch	0	Rampage	9	L			BoxScore
110 - 2023-01-15	807	Crunch	7	Gulls	5	W			BoxScore
112 - 2023-01-17	817	Senators	5	Crunch	2	L			BoxScore
115 - 2023-01-20	839	Crunch	1	Stars	5	L			BoxScore
117 - 2023-01-22	852	Phantoms	6	Crunch	1	L			BoxScore
119 - 2023-01-24	869	Crunch	5	Comets	6	L	X	X	BoxScore
121 - 2023-01-26	884	IceHogs	3	Crunch	7	W			BoxScore
123 - 2023-01-28	906	Wranglers	10	Crunch	3	L			BoxScore
125 - 2023-01-30	917	Crunch	9	Reign	2	W			BoxScore
128 - 2023-02-02	938	Rampage	5	Crunch	2	L			BoxScore
130 - 2023-02-04	954	Crunch	5	Bears	3	W			BoxScore
132 - 2023-02-06	971	Wild	5	Crunch	7	W			BoxScore
133 - 2023-02-07	980	Crunch	10	Condors	5	W			BoxScore
136 - 2023-02-10	1000	Wolves	5	Crunch	8	W			BoxScore
138 - 2023-02-12	1014	Crunch	2	Americans	6	L			BoxScore
139 - 2023-02-13	1025	Crunch	7	Firebirds	4	W			BoxScore
142 - 2023-02-16	1041	Stars	6	Crunch	2	L			BoxScore
144 - 2023-02-18	1058	Crunch	1	Wranglers	5	L			BoxScore
146 - 2023-02-20	1067	Crunch	1	Checkers	5	L			BoxScore
148 - 2023-02-22	1080	Firebirds	2	Crunch	9	W			BoxScore
151 - 2023-02-25	1105	Griffins	4	Crunch	3	L			BoxScore
152 - 2023-02-26	1112	Crunch	1	Bruins	7	L			BoxScore
159 - 2023-03-05	1149	Moose	6	Crunch	4	L			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	67,282	33,642
Attendance PCT	93.45%	93.45%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	2803 - 93.45%	69,899$	2,516,363$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,060,778$	50,500$	0$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	60,685$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	6,525$	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	42	24	0	4	5	4	3	249	172	77	41	22	11	0	2	1	3	2	129	82	47	41	20	13	0	2	4	1	1	120	90	30	108	249	446	695	1	11	0	100	82	59	2209	0	713	722	749	1711	511	1392	1835	510	74	14.51%	576	72	87.50%	4	1584	2556	61.97%	1364	2335	58.42%	730	1182	61.76%	2253	1609	1733	575	989	519
13	76	38	25	0	4	5	2	2	219	172	47	38	16	15	0	2	3	1	1	110	87	23	38	22	10	0	2	2	1	1	109	85	24	95	219	386	605	1	12	0	74	79	60	1942	0	579	691	656	1716	532	1204	1628	442	63	14.25%	501	62	87.62%	7	1315	2300	57.17%	1227	2228	55.07%	613	1092	56.14%	1992	1405	1686	539	920	480
14	76	40	24	0	3	2	4	3	233	140	93	38	22	10	0	0	1	4	1	125	65	60	38	18	14	0	3	1	0	2	108	75	33	99	233	426	659	2	10	0	90	75	61	2210	0	746	698	748	1718	528	959	1434	338	57	16.86%	378	42	88.89%	5	1375	2439	56.38%	1220	2283	53.44%	609	1087	56.03%	1992	1423	1706	527	906	471
15	82	43	25	0	3	6	3	2	256	187	69	41	22	9	0	3	4	2	1	134	79	55	41	21	16	0	0	2	1	1	122	108	14	106	256	469	725	1	8	0	96	79	75	2522	0	831	844	826	1834	508	1027	1382	458	63	13.76%	409	61	85.09%	7	1643	2755	59.64%	1282	2262	56.68%	716	1210	59.17%	2231	1616	1760	567	974	508
16	82	33	39	0	2	3	2	3	272	299	-27	41	17	19	0	0	2	1	2	145	149	-4	41	16	20	0	2	1	1	1	127	150	-23	80	272	441	713	1	5	0	112	71	85	2542	0	832	773	913	2435	734	905	1373	412	86	20.87%	386	73	81.09%	6	1317	2540	51.85%	1113	2371	46.94%	634	1303	48.66%	1956	1422	2079	553	920	450
17	72	33	28	0	2	1	2	6	290	264	26	36	18	12	0	0	0	2	4	152	131	21	36	15	16	0	2	1	0	2	138	133	5	81	290	441	731	1	3	123	79	84	6	2632	851	832	927	52	2387	712	703	1280	347	60	17.29%	294	65	77.89%	1	1186	2280	52.02%	946	2193	43.14%	608	1188	51.18%	1686	1259	1905	470	774	367
Total Regular Season	470	229	165	0	18	22	17	19	1519	1234	285	235	117	76	0	7	11	13	11	795	593	202	235	112	89	0	11	11	4	8	724	641	83	569	1519	2609	4128	7	49	123	551	470	346	14057	851	4533	4655	3944	11801	3525	6190	8932	2507	403	16.07%	2544	375	85.26%	30	8420	14870	56.62%	7152	13672	52.31%	3910	7062	55.37%	12112	8736	10870	3235	5485	2798
Playoff
11	5	1	4	0	0	0	0	0	6	16	-10	2	0	2	0	0	0	0	0	1	7	-6	3	1	2	0	0	0	0	0	5	9	-4	2	6	12	18	0	0	0	0	5	1	81	0	20	34	27	125	30	136	123	34	2	5.88%	57	9	84.21%	0	67	144	46.53%	98	176	55.68%	36	66	54.55%	105	66	132	40	62	29
12	5	1	4	0	0	0	0	0	5	15	-10	2	1	1	0	0	0	0	0	5	5	0	3	0	3	0	0	0	0	0	0	10	-10	2	5	10	15	0	1	0	1	1	3	81	0	26	26	28	145	35	89	130	16	2	12.50%	38	7	81.58%	0	75	132	56.82%	92	170	54.12%	35	65	53.85%	100	63	138	37	63	29
14	12	7	5	0	0	0	0	0	24	19	5	5	4	1	0	0	0	0	0	10	7	3	7	3	4	0	0	0	0	0	14	12	2	14	24	41	65	0	2	0	10	4	7	349	0	103	94	87	330	98	125	247	94	7	7.45%	54	5	90.74%	0	240	493	48.68%	215	475	45.26%	80	189	42.33%	347	239	372	112	183	90
15	5	1	4	0	0	0	0	0	13	19	-6	2	0	2	0	0	0	0	0	4	9	-5	3	1	2	0	0	0	0	0	9	10	-1	2	13	23	36	0	1	0	3	5	5	134	0	40	48	46	124	29	59	83	27	7	25.93%	26	7	73.08%	0	65	164	39.63%	51	123	41.46%	27	72	37.50%	113	78	124	37	62	30
Total Playoff	27	10	17	0	0	0	0	0	48	69	-21	11	5	6	0	0	0	0	0	20	28	-8	16	5	11	0	0	0	0	0	28	41	-13	20	48	86	134	0	4	0	14	15	16	645	0	189	202	188	724	192	409	583	171	18	10.53%	175	28	84.00%	0	447	933	47.91%	456	944	48.31%	178	392	45.41%	666	447	767	227	371	179