NHLS - National Hockey League Simulated

Blue Jackets
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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
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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	Zachary L'Heureux		X			100.00	80	61	69	67	72	82	83	66	61	65	67	68	62	63	65	80	75	65	0
2	Mackenzie MacEachern		X			100.00	72	41	70	62	79	81	72	61	59	67	63	61	63	72	74	39	75	63	0
3	Brendan Hoffman (R)			X		100.00	80	39	95	56	89	81	68	57	62	59	58	63	56	65	67	42	75	62	0
4	Garrett Pilon	X		X		100.00	64	39	82	62	73	76	83	58	69	65	57	59	63	68	73	53	75	62	0
5	Artem Shlaine (R)	X				100.00	61	36	95	59	70	78	85	58	60	57	56	55	59	64	66	56	75	60	0
6	Kaleb Lawrence	X				100.00	90	69	58	56	99	68	69	54	59	53	55	62	56	63	65	49	75	60	0
7	Oscar Fisker Molgaard (R)	X				100.00	61	36	94	62	68	76	83	59	61	60	58	57	59	61	63	72	75	60	0
8	Chase Wouters	X				100.00	62	39	72	58	71	81	87	56	62	59	57	55	58	66	71	42	75	60	0
9	David Silye (R)	X				100.00	61	39	82	57	70	68	81	56	63	55	54	58	53	67	69	37	75	59	0
10	Ethan Keppen		X			100.00	74	42	70	56	83	75	73	55	53	54	57	58	56	65	67	56	75	59	0
11	Maros Jedlicka	X				100.00	70	40	81	58	79	64	71	55	59	54	56	57	53	64	66	48	75	59	0
12	Shane Bowers	X		X		100.00	71	40	80	58	78	72	77	56	66	55	52	57	54	67	69	68	75	59	0
13	Samuel Johannesson				X	100.00	59	37	95	61	68	70	77	58	30	62	54	56	47	66	68	47	75	60	0
14	Nikita Novikov				X	100.00	74	42	75	56	83	64	85	55	30	57	54	58	46	63	65	49	75	59	0
15	Scott Harrington				X	100.00	72	39	87	54	81	63	82	52	30	55	53	56	46	73	75	42	75	59	0
16	Ole Bjorgvik-Holm (R)				X	100.00	69	40	75	55	78	64	74	54	30	53	52	56	45	64	66	54	75	58	0
17	Carter Berger (R)				X	100.00	66	37	91	56	74	65	63	53	30	54	50	55	46	67	69	51	75	57	0
18	Noah Beck (R)				X	100.00	74	40	73	53	83	66	64	51	30	52	50	56	45	65	67	47	75	57	0
Scratches
1	Chris Douglas (R)			X		100.00	70	41	74	55	79	67	63	53	50	52	54	56	51	66	68	42	75	58	0
2	Arnaud Durandeau		X			100.00	62	38	87	54	71	73	62	52	56	55	50	53	51	67	69	42	75	57	0
3	Djibril Toure				X	100.00	90	56	53	55	99	64	73	54	30	53	53	61	45	63	65	44	75	59	0
4	Philip Kemp				X	100.00	75	42	76	56	84	65	83	54	30	53	55	57	46	67	72	42	75	59	0

	TEAM AVERAGE					100.00	71	42	79	58	79	71	75	56	49	57	55	58	53	66	68	50	75	60

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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	Matt Tomkins	100.00	76	84	79	85	75	74	76	75	74	76	75	72	86	30	75	65	0
2	Isaiah Saville	100.00	72	73	68	76	71	70	72	71	70	72	71	66	75	54	75	63	0
Scratches
1	Luke Cavallin	100.00	69	73	69	80	68	67	69	68	67	69	68	66	73	42	75	61	0
2	Connor D. Murphy	100.00	66	73	68	87	65	64	66	65	64	66	65	68	81	36	75	59	0

	TEAM AVERAGE	100.00	71	76	71	82	70	69	71	70	69	71	70	68	79	41	75	62

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Jason King	65	71	70	69	66	61	82	CAN	44	1	500,000$

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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	HT	P/20	FT	S1	S2	S3
1	Zachary L'Heureux	Monsters (CBJ)	LW	10	9	4	13	3	17	5	33	36	53	18	30	16.98%	5	240	24.07	1	3	4	8	28	1	33	2	1	50.62%	81	1	1	1.08	1	3	0	0
2	Mackenzie MacEachern	Monsters (CBJ)	LW	10	7	2	9	-1	6	0	15	26	36	10	29	19.44%	2	224	22.44	0	1	1	3	27	1	34	1	0	33.33%	18	0	0	0.80	0	1	2	1
3	Garrett Pilon	Monsters (CBJ)	C/RW	10	3	4	7	3	0	0	8	24	34	15	13	8.82%	3	216	21.67	2	0	2	11	30	1	17	0	0	47.84%	255	0	0	0.65	0	0	2	0
4	Nikita Novikov	Monsters (CBJ)	D	10	0	7	7	-1	6	0	29	9	13	2	7	0.00%	11	221	22.20	0	1	1	6	28	0	26	0	0	0.00%	0	0	0	0.63	0	1	0	0
5	Chase Wouters	Monsters (CBJ)	C	10	0	7	7	-2	0	0	13	14	15	8	17	0.00%	1	175	17.55	0	1	1	4	22	0	0	0	0	48.80%	166	0	0	0.80	0	0	0	0
6	Brendan Hoffman	Monsters (CBJ)	RW	10	0	6	6	4	4	0	15	14	25	9	15	0.00%	3	215	21.56	0	3	3	4	30	0	16	0	0	75.00%	20	0	0	0.56	0	0	0	0
7	Shane Bowers	Monsters (CBJ)	C/RW	10	3	3	6	-1	2	0	9	9	24	2	9	12.50%	1	174	17.48	0	1	1	1	27	0	0	0	0	40.00%	10	0	0	0.69	0	0	0	0
8	Scott Harrington	Monsters (CBJ)	D	10	1	5	6	2	10	0	24	6	8	4	3	12.50%	10	223	22.38	1	2	3	4	29	0	27	1	0	0.00%	0	0	0	0.54	0	0	0	1
9	Ole Bjorgvik-Holm	Monsters (CBJ)	D	10	0	5	5	5	12	0	13	9	7	4	7	0.00%	9	202	20.22	0	0	0	5	25	0	24	0	0	0.00%	0	0	0	0.49	0	0	0	1
10	Ethan Keppen	Monsters (CBJ)	LW	10	0	4	4	1	2	0	16	13	20	8	13	0.00%	5	153	15.38	0	0	0	0	0	0	5	0	0	41.67%	12	0	0	0.52	0	0	0	0
11	Carter Berger	Monsters (CBJ)	D	8	1	3	4	0	2	0	3	6	1	1	1	100.00%	6	141	17.70	0	0	0	0	0	0	9	0	0	0.00%	0	0	0	0.57	0	0	0	1
12	Kaleb Lawrence	Monsters (CBJ)	C	10	2	2	4	0	9	5	33	11	17	9	16	11.76%	0	147	14.76	0	0	0	0	4	0	0	0	0	48.57%	70	0	0	0.54	1	0	0	0
13	Noah Beck	Monsters (CBJ)	D	9	2	2	4	2	14	0	25	4	7	3	3	28.57%	11	140	15.57	1	0	1	1	0	0	6	0	0	0.00%	0	0	0	0.57	0	0	1	0
14	Oscar Fisker Molgaard	Monsters (CBJ)	C	10	1	3	4	0	0	0	1	18	30	8	16	3.33%	2	144	14.46	0	0	0	0	0	0	0	0	0	42.20%	173	0	0	0.55	0	0	0	1
15	Samuel Johannesson	Monsters (CBJ)	D	6	2	1	3	0	0	0	4	10	10	2	6	20.00%	8	139	23.25	1	0	1	5	20	1	16	0	0	0.00%	0	0	0	0.43	0	1	0	0
16	David Silye	Monsters (CBJ)	C	10	0	2	2	2	0	0	0	3	1	0	1	0.00%	2	22	2.24	0	0	0	0	0	0	11	0	0	50.00%	26	0	0	1.78	0	0	0	0
17	Artem Shlaine	Monsters (CBJ)	C	10	1	0	1	1	0	0	0	0	2	1	2	50.00%	0	23	2.35	0	0	0	0	1	0	6	1	0	46.15%	13	0	0	0.85	0	0	0	0
18	Djibril Toure	Monsters (CBJ)	D	5	0	1	1	1	17	5	22	1	2	1	4	0.00%	5	90	18.08	0	0	0	2	7	0	7	0	0	0.00%	0	0	0	0.22	0	0	0	0
19	Maros Jedlicka	Monsters (CBJ)	C	10	0	0	0	2	0	0	2	1	3	1	0	0.00%	1	7	0.72	0	0	0	1	0	0	0	0	0	75.00%	4	0	0	0.00	0	0	0	0
20	Philip Kemp	Monsters (CBJ)	D	2	0	0	0	-1	0	0	7	2	1	0	0	0.00%	3	32	16.22	0	0	0	0	0	0	1	0	0	0.00%	0	0	0	0.00	0	0	0	0
Team Total or Average				180	32	61	93	20	101	15	272	216	309	106	192	10.36%	88	2938	16.33	6	12	18	55	286	4	246	5	1	47.52%	848	1	1	0.63	2	6	5	5

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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
1	Matt Tomkins	Monsters (CBJ)	10	5	5	0	0.886	3.10	601	0	0	31	272	0	0	0	0.000	0	10	0	0	0	0
Team Total or Average			10	5	5	0	0.886	3.10	601	0	0	31	272	0	0	0	0.000	0	10	0	0	0	0

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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
Arnaud Durandeau	LW	28	1999-01-14	No	185 Lbs	6 ft0	No	No	Yes	3	UFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Artem Shlaine	C	25	2002-03-07	Yes	165 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Brendan Hoffman	RW	26	2001-10-09	Yes	230 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Carter Berger	D	28	1999-09-17	Yes	200 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Chase Wouters	C	27	2000-02-08	No	182 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Chris Douglas	RW	27	2000-07-06	Yes	194 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Connor D. Murphy	G	29	1998-09-01	No	201 Lbs	6 ft4	No	No	Yes	3	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
David Silye	C	28	1999-03-02	Yes	187 Lbs	5 ft11	No	No	No	3	UFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Djibril Toure	D	24	2003-06-05	No	217 Lbs	6 ft7	No	No	No	2	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Ethan Keppen	LW	26	2001-03-20	No	212 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Garrett Pilon	C/RW	29	1998-04-13	No	191 Lbs	6 ft0	No	No	Yes	3	UFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Isaiah Saville	G	27	2000-09-21	No	193 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Kaleb Lawrence	C	24	2003-01-10	No	230 Lbs	6 ft7	No	No	No	2	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Luke Cavallin	G	26	2001-04-29	No	196 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Mackenzie MacEachern	LW	33	1994-03-09	No	193 Lbs	6 ft2	No	No	Yes	2	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Maros Jedlicka	C	25	2002-10-23	No	194 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Matt Tomkins	G	33	1994-06-19	No	191 Lbs	6 ft4	No	No	Yes	1	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Nikita Novikov	D	24	2003-07-25	No	196 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Noah Beck	D	26	2001-03-25	Yes	184 Lbs	6 ft4	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Ole Bjorgvik-Holm	D	25	2002-05-23	Yes	190 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Oscar Fisker Molgaard	C	22	2005-02-18	Yes	168 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Philip Kemp	D	28	1999-02-12	No	202 Lbs	6 ft3	No	No	Yes	1	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Samuel Johannesson	D	27	2000-12-27	No	176 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Scott Harrington	D	34	1993-03-10	No	204 Lbs	6 ft2	No	No	Yes	1	UFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Shane Bowers	C/RW	28	1999-07-30	No	186 Lbs	6 ft2	No	No	Yes	1	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Zachary L'Heureux	LW	24	2003-05-15	No	197 Lbs	5 ft11	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
26	27.04	195 Lbs	6 ft2	2.23	924,038$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Zachary L'Heureux	Garrett Pilon	Brendan Hoffman	40	1	0	4
2	Mackenzie MacEachern	Chase Wouters	Shane Bowers	30	1	0	4
3	Ethan Keppen	Oscar Fisker Molgaard	Kaleb Lawrence	20	1	2	2
4	Zachary L'Heureux	Kaleb Lawrence	Mackenzie MacEachern	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Samuel Johannesson	Scott Harrington	40	1	2	2
2	Nikita Novikov	Ole Bjorgvik-Holm	30	1	2	2
3	Noah Beck	Carter Berger	20	1	2	2
4	Samuel Johannesson	Scott Harrington	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Zachary L'Heureux	Garrett Pilon	Brendan Hoffman	60	1	2	2
2	Mackenzie MacEachern	Chase Wouters	Shane Bowers	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Samuel Johannesson	Scott Harrington	60	1	2	2
2	Nikita Novikov	Ole Bjorgvik-Holm	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Zachary L'Heureux	Mackenzie MacEachern	60	1	2	2
2	Brendan Hoffman	Garrett Pilon	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Samuel Johannesson	Scott Harrington	60	1	2	2
2	Nikita Novikov	Ole Bjorgvik-Holm	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Zachary L'Heureux	60	1	2	2	Samuel Johannesson	Scott Harrington	60	1	2	2
2	Mackenzie MacEachern	40	1	2	2	Nikita Novikov	Ole Bjorgvik-Holm	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Zachary L'Heureux	Mackenzie MacEachern	60	1	2	2
2	Brendan Hoffman	Garrett Pilon	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Samuel Johannesson	Scott Harrington	60	1	2	2
2	Nikita Novikov	Ole Bjorgvik-Holm	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Zachary L'Heureux	Garrett Pilon	Brendan Hoffman	Samuel Johannesson	Scott Harrington

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Zachary L'Heureux	Garrett Pilon	Brendan Hoffman	Samuel Johannesson	Scott Harrington

Extra Forwards
Normal	PowerPlay	Penalty Kill
Artem Shlaine, Maros Jedlicka, David Silye	Artem Shlaine, Maros Jedlicka	David Silye

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Noah Beck, Carter Berger, Nikita Novikov	Noah Beck	Carter Berger, Nikita Novikov

Penalty Shots
Zachary L'Heureux, Mackenzie MacEachern, Brendan Hoffman, Garrett Pilon, Chase Wouters

Goalie
#1 : Matt Tomkins, #2 : Isaiah Saville

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

Custom OT Lines Defensemen
, , , ,

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			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
10	10	L2	32	61	93	309	272	88	101	272	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
10	3	5	2	0	0	0	32	31

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
7	2	3	2	0	0	0	22	21

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
3	1	2	0	0	0	0	10	10

Last 10 Games
W	L	OTW	OTL	SOW	SOL
5	5	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
32	6	18.75%	37	10	72.97%	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
85	115	105	4	9	10	11	2

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
165	346	47.69%	157	319	49.22%	81	178	45.51%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
230	157	245	74	127	62

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Day	Game	Visitor Team	Score	Home Team	Score	ST	OT	Link
3 - 2026-10-01	9	Americans	4	Monsters	5	W	X	BoxScore
5 - 2026-10-03	24	Roadrunners	2	Monsters	0	L		BoxScore
11 - 2026-10-09	66	Penguins	1	Monsters	3	W		BoxScore
12 - 2026-10-10	77	Monsters	2	Thunderbirds	4	L		BoxScore
15 - 2026-10-13	91	Checkers	5	Monsters	3	L		BoxScore
19 - 2026-10-17	127	Wolf Pack	2	Monsters	4	W		BoxScore
20 - 2026-10-18	135	Monsters	7	Wild	2	W		BoxScore
22 - 2026-10-20	143	Marlies	3	Monsters	4	W	X	BoxScore
26 - 2026-10-24	173	Silver Knights	4	Monsters	3	L		BoxScore
29 - 2026-10-27	188	Monsters	1	Phantoms	4	L		BoxScore
31 - 2026-10-29	203	Monsters	-	Wolves	-
33 - 2026-10-31	225	Monsters	-	Stars	-
36 - 2026-11-03	236	Eagles	-	Monsters	-
38 - 2026-11-05	254	Stars	-	Monsters	-
39 - 2026-11-06	262	Monsters	-	Americans	-
43 - 2026-11-10	287	Checkers	-	Monsters	-
45 - 2026-11-12	302	Crunch	-	Monsters	-
47 - 2026-11-14	316	Phantoms	-	Monsters	-
50 - 2026-11-17	335	Monsters	-	Hammers	-
52 - 2026-11-19	354	Monsters	-	IceHogs	-
54 - 2026-11-21	364	Monsters	-	Marlies	-
56 - 2026-11-23	378	Monsters	-	Comets	-
58 - 2026-11-25	390	Comets	-	Monsters	-
60 - 2026-11-27	404	Griffins	-	Monsters	-
63 - 2026-11-30	432	Monsters	-	Penguins	-
66 - 2026-12-03	448	Monsters	-	Wolves	-
68 - 2026-12-05	466	Monsters	-	Admirals	-
70 - 2026-12-07	483	Monsters	-	Crunch	-
73 - 2026-12-10	503	Wild	-	Monsters	-
75 - 2026-12-12	515	Rocket	-	Monsters	-
76 - 2026-12-13	528	Monsters	-	Wolf Pack	-
78 - 2026-12-15	538	Wolves	-	Monsters	-
80 - 2026-12-17	553	Firebirds	-	Monsters	-
82 - 2026-12-19	570	Reign	-	Monsters	-
84 - 2026-12-21	586	Monsters	-	Phantoms	-
85 - 2026-12-22	592	Rocket	-	Monsters	-
89 - 2026-12-26	605	Monsters	-	Bears	-
90 - 2026-12-27	613	Condors	-	Monsters	-
92 - 2026-12-29	627	Monsters	-	Rocket	-
94 - 2026-12-31	643	Bears	-	Monsters	-
96 - 2027-01-02	657	Bruins	-	Monsters	-
97 - 2027-01-03	670	Monsters	-	Wolf Pack	-
99 - 2027-01-05	682	Wolf Pack	-	Monsters	-
101 - 2027-01-07	696	Monsters	-	Comets	-
102 - 2027-01-08	704	Americans	-	Monsters	-
106 - 2027-01-12	732	Monsters	-	Wranglers	-
109 - 2027-01-15	756	Monsters	-	Condors	-
110 - 2027-01-16	770	Monsters	-	Canucks	-
112 - 2027-01-18	780	Monsters	-	Firebirds	-
115 - 2027-01-21	800	Wranglers	-	Monsters	-
117 - 2027-01-23	813	Monsters	-	Senators	-
118 - 2027-01-24	825	Gulls	-	Monsters	-
120 - 2027-01-26	834	Monsters	-	Bruins	-
122 - 2027-01-28	851	Moose	-	Monsters	-
124 - 2027-01-30	871	Griffins	-	Monsters	-
133 - 2027-02-08	895	Monsters	-	Marlies	-
134 - 2027-02-09	898	Monsters	-	Senators	-
136 - 2027-02-11	903	Senators	-	Monsters	-
138 - 2027-02-13	917	Monsters	-	Bruins	-
140 - 2027-02-15	931	Monsters	-	Eagles	-
142 - 2027-02-17	949	Monsters	-	Roadrunners	-
143 - 2027-02-18	960	Monsters	-	Silver Knights	-
145 - 2027-02-20	971	Admirals	-	Monsters	-
147 - 2027-02-22	987	Hammers	-	Monsters	-
151 - 2027-02-26	1012	Comets	-	Monsters	-
152 - 2027-02-27	1026	Hammers	-	Monsters	-
154 - 2027-03-01	1036	Wolves	-	Monsters	-
156 - 2027-03-03	1054	Monsters	-	Barracuda	-
158 - 2027-03-05	1070	Monsters	-	Reign	-
160 - 2027-03-07	1087	Monsters	-	Gulls	-
164 - 2027-03-11	1108	Canucks	-	Monsters	-
166 - 2027-03-13	1127	Barracuda	-	Monsters	-
169 - 2027-03-16	1147	Penguins	-	Monsters	-
171 - 2027-03-18	1162	Monsters	-	Griffins	-
173 - 2027-03-20	1179	Monsters	-	Moose	-
175 - 2027-03-22	1193	Monsters	-	Penguins	-
178 - 2027-03-25	1214	IceHogs	-	Monsters	-
180 - 2027-03-27	1233	Thunderbirds	-	Monsters	-
183 - 2027-03-30	1251	Monsters	-	Checkers	-
185 - 2027-04-01	1263	Monsters	-	Crunch	-
187 - 2027-04-03	1281	Monsters	-	Bears	-
190 - 2027-04-06	1302	Bears	-	Monsters	-
192 - 2027-04-08	1316	Phantoms	-	Monsters	-
194 - 2027-04-10	1332	Monsters	-	Hammers	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	3000	2000
Ticket Price	25	15
Attendance	20,991	14,000
Attendance PCT	99.96%	100.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
35	4999 - 99.97%	99,719$	698,036$	5000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
431,679$	2,402,500$	2,402,500$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	356,946$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
3,490,180$	165	14,961$	2,468,565$

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
2020	56	24	24	0	3	2	1	2	205	201	4	28	14	12	0	0	1	1	0	107	97	10	28	10	12	0	3	1	0	2	98	104	-6	60	205	376	581	2	0	0	75	61	65	1945	0	643	598	685	2015	611	383	1374	179	40	22.35%	169	35	79.29%	1	1001	2127	47.06%	993	2064	48.11%	457	963	47.46%	1304	887	1344	422	737	361
2021	82	34	38	0	2	3	3	2	278	291	-13	41	18	18	0	1	1	2	1	144	144	0	41	16	20	0	1	2	1	1	134	147	-13	83	278	502	780	3	2	0	116	81	76	2852	0	940	970	919	2744	754	653	1969	264	63	23.86%	281	65	76.87%	2	1456	3035	47.97%	1517	3027	50.12%	681	1367	49.82%	1923	1315	1963	615	1067	527
2022	82	40	28	0	8	3	2	1	300	264	36	41	25	14	0	1	0	1	0	148	124	24	41	15	14	0	7	3	1	1	152	140	12	104	300	547	847	4	2	0	111	89	90	2823	0	917	919	958	2948	821	812	1918	326	57	17.48%	327	67	79.51%	3	1502	2998	50.10%	1561	3172	49.21%	673	1372	49.05%	1897	1290	1998	623	1060	520
2023	83	30	36	0	3	7	5	2	275	290	-15	41	18	17	0	3	1	1	1	132	126	6	42	12	19	0	0	6	4	1	143	164	-21	85	275	501	776	2	0	0	92	96	79	2757	0	911	874	922	2785	834	722	2083	301	56	18.60%	326	72	77.91%	3	1453	2951	49.24%	1455	3026	48.08%	682	1374	49.64%	1988	1369	1973	622	1075	537
2024	82	27	34	0	9	4	6	2	227	234	-7	41	17	11	0	6	3	2	2	125	108	17	41	10	23	0	3	1	4	0	102	126	-24	90	227	410	637	1	3	0	79	63	70	2145	0	716	699	699	2386	614	690	2044	251	45	17.93%	311	57	81.67%	1	1275	2538	50.24%	1318	2698	48.85%	581	1212	47.94%	1901	1288	2004	618	1079	534
2025	82	37	33	0	4	1	1	6	236	241	-5	41	23	13	0	1	1	0	3	124	114	10	41	14	20	0	3	0	1	3	112	127	-15	91	236	423	659	3	1	0	81	82	68	2333	0	788	748	773	2438	721	770	2157	259	46	17.76%	331	58	82.48%	5	1334	2694	49.52%	1378	2818	48.90%	647	1283	50.43%	1883	1275	2012	619	1067	525
2026	10	3	5	0	2	0	0	0	32	31	1	7	2	3	0	2	0	0	0	22	21	1	3	1	2	0	0	0	0	0	10	10	0	10	32	61	93	0	0	9	10	11	2	309	85	115	105	4	272	88	101	272	32	6	18.75%	37	10	72.97%	0	165	346	47.69%	157	319	49.22%	81	178	45.51%	230	157	245	74	127	62
Total Regular Season	477	195	198	0	31	20	18	15	1553	1552	1	240	117	88	0	14	7	7	7	802	734	68	237	78	110	0	17	13	11	8	751	818	-67	523	1553	2820	4373	15	8	9	564	483	450	15164	85	5030	4913	4960	15588	4443	4131	11817	1612	313	19.42%	1782	364	79.57%	15	8186	16689	49.05%	8379	17124	48.93%	3802	7749	49.06%	11129	7585	11542	3598	6215	3070
Playoff
2022	16	9	7	0	0	0	0	0	58	67	-9	8	4	4	0	0	0	0	0	28	35	-7	8	5	3	0	0	0	0	0	30	32	-2	18	58	102	160	0	0	0	21	19	15	538	0	176	178	172	652	194	165	444	66	14	21.21%	77	23	70.13%	1	293	595	49.24%	313	675	46.37%	136	284	47.89%	352	231	420	130	215	102
2024	5	1	4	0	0	0	0	0	9	19	-10	2	0	2	0	0	0	0	0	2	7	-5	3	1	2	0	0	0	0	0	7	12	-5	2	9	16	25	0	0	0	4	4	1	131	0	38	40	48	166	51	44	132	12	2	16.67%	17	4	76.47%	0	75	161	46.58%	90	176	51.14%	38	79	48.10%	110	71	135	41	67	31
Total Playoff	21	10	11	0	0	0	0	0	67	86	-19	10	4	6	0	0	0	0	0	30	42	-12	11	6	5	0	0	0	0	0	37	44	-7	20	67	118	185	0	0	0	25	23	16	669	0	214	218	220	818	245	209	576	78	16	20.51%	94	27	71.28%	1	368	756	48.68%	403	851	47.36%	174	363	47.93%	462	303	555	171	283	134