Blue Jackets
Home
Roster
Players Stats
Players Info
Lines
Team Stats
Schedule
Finance

Game Center
	Stars 56-16-14, 126pts	1	Box score	2	Monsters 30-37-19, 79pts

Team Stats
SOL1	Streak	SOL1
27-9-7	Home Record	12-20-11
29-7-7	Home Record	18-17-8
7-0-3	Last 10 Games	6-2-2
3.19	Goals Per Game	1.79
2.31	Goals Against Per Game	2.41
26.74%	Power Play Percentage	23.98%
73.43%	Penalty Kill Percentage	72.68%

Monsters
30-37-19, 79pts

Box score

Comets
48-29-9, 105pts

Team Stats
SOL1	Streak	W1
12-20-11	Home Record	23-16-4
18-17-8	Home Record	25-13-5
6-2-2	Last 10 Games	9-1-0
1.79	Goals Per Game	2.19
2.41	Goals Against Per Game	2.33
23.98%	Power Play Percentage	33.14%
72.68%	Penalty Kill Percentage	68.27%

Team Leaders
	Goals Cole Guttman 36	Assists Cole Guttman 41

	Points Cole Guttman 77	Plus/Minus Kyle Jackson 2

	Wins Jacob Ingham 28	Save Percentage Jacob Ingham 0.871

Team Stats
Goals For 154 1.79 GFG	Shots For 1276 14.84 Avg	Power Play Percentage 24.0% 41 GF	Offensive Zone Start 34.0%
Goals Against 207 2.41 GAA	Shots Against 1496 17.40 Avg	Penalty Kill Percentage 72.7%% 53 GA	Defensive Zone Start 40.5%

Team Info
	General Manager	Trent Zeigler
	Coach	Jim Montgomery
	Division	Division 2
	Conference	Conference 1
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	2,111
	Season Tickets	1,500
Roster Info
	Pro Team	22
	Farm Team	19
	Contract Limit	41 / 100
	Prospects	61

Show or Hide Columns

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	Age	Contract	Salary
1	Cole Guttman	X	X	X		100.00	71	65	85	70	65	81	86	68	81	66	69	61	60	47	47	63	66	65	0	27	1	950,000$
2	Brian Halonen (R)		X			100.00	76	74	78	71	74	77	81	64	50	55	72	62	65	47	47	63	51	63	0	27	1	996,000$
3	Egor Sokolov (R)		X			100.00	84	80	92	68	80	81	87	60	50	56	60	66	58	47	46	63	65	63	0	26	3	1,495,000$
4	Tristan Broz (R)	X				100.00	76	74	86	68	76	53	52	59	76	54	62	62	60	47	46	60	50	59	0	23	3	1,350,000$
5	Givani Smith			X		100.00	79	99	64	75	81	45	46	59	25	49	53	65	25	64	64	57	47	58	0	28	2	1,136,000$
6	Jacob Perreault			X		100.00	72	71	75	66	73	61	64	50	50	51	44	57	44	47	46	51	43	54	0	24	3	1,106,000$
7	Adam Raska		X	X		100.00	65	66	61	66	68	67	72	49	50	46	47	53	45	46	46	51	28	53	0	24	3	1,315,000$
8	Tucker Robertson	X				100.00	72	67	90	65	69	56	58	48	63	45	46	58	46	47	46	51	43	53	0	22	3	1,256,000$
9	Connor Clattenburg (R)	X				100.00	82	76	99	81	77	32	30	43	55	37	43	63	42	45	45	50	25	52	0	21	3	1,265,000$
10	Kyle Jackson (R)	X	X	X		100.00	58	72	25	80	72	33	31	44	55	38	44	51	42	44	44	46	29	49	0	23	3	1,467,000$
11	Valtteri Pulli				X	100.00	85	80	99	81	81	35	31	56	25	56	41	68	37	46	46	52	20	59	0	25	2	800,000$
12	Max Szuber				X	100.00	77	76	80	68	78	53	54	54	25	49	46	62	41	46	46	53	60	58	0	23	1	1,000,000$
13	Billy Sweezey				X	100.00	73	74	71	63	74	73	81	46	25	36	39	57	37	46	46	49	24	57	0	30	1	1,000,000$
14	Ben Zloty				X	100.00	72	68	86	82	70	35	32	49	25	42	40	58	37	46	46	49	30	55	0	24	1	1,000,000$
15	Ethan Frisch				X	100.00	74	69	89	63	69	51	53	47	25	38	41	58	39	46	46	48	34	54	0	25	2	800,000$
16	Tyson Feist				X	100.00	68	69	69	81	70	35	33	45	25	36	39	54	37	47	46	46	49	53	0	25	2	800,000$
17	Braden Hache (R)				X	100.00	65	79	36	65	81	43	42	48	25	39	40	53	39	46	46	45	38	52	0	23	1	1,000,000$
18	Leon Muggli (R)				X	100.00	74	65	99	82	67	32	30	40	25	27	38	57	37	46	46	46	24	52	0	19	3	1,261,000$
Scratches
1	Martin Chromiak			X		85.46	77	70	96	69	72	56	55	60	50	56	62	63	59	46	46	62	29	59	0	23	1	820,000$

	TEAM AVERAGE					99.23	74	73	78	72	74	53	54	52	42	46	49	59	45	47	47	53	40	56

Show or Hide Columns

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	Age	Contract	Salary
1	Jacob Ingham	100.00	44	40	50	86	45	94	50	54	95	81	45	46	46	57	82	63	0	25	3	1,250,000$
2	Mitch Gibson	100.00	40	40	50	69	45	90	45	49	91	81	45	44	44	60	40	59	0	26	1	1,000,000$
Scratches
1	Connor Hughes	100.00	52	40	50	93	55	53	56	59	58	58	30	44	44	54	60	57	0	29	1	1,000,000$

	TEAM AVERAGE	100.00	45	40	50	83	48	79	50	54	81	73	40	45	45	57	61	60

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Jim Montgomery	80	80	80	80	80	80	80	CAN	51	1	1,600,000$

Show or Hide Columns

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	Cole Guttman	Monsters (CBJ)	C/LW/RW	86	36	41	77	-9	51	15	100	153	232	72	140	15.52%	32	1989	23.13	13	18	31	44	143	1	1	2	9	106	5	2	59.69%	960	45	34	0	2	0.77	2	9	1	0	2	10	1	9
2	Brian Halonen	Monsters (CBJ)	LW	86	21	34	55	-15	78	40	140	160	149	41	83	14.09%	24	1872	21.77	7	13	20	46	140	1	0	1	10	88	4	1	48.28%	582	39	26	0	0	0.59	3	6	2	4	2	4	7	4
3	Mattias Samuelsson	Blue Jackets	D	75	6	38	44	-7	61	15	132	137	162	69	66	3.70%	108	2032	27.10	2	12	14	17	180	0	4	4	5	222	0	1	0%	0	43	64	0	0	0.43	0	0	0	1	2	0	1	1
4	Egor Sokolov	Monsters (CBJ)	LW	86	7	21	28	-8	77	55	97	174	86	36	76	8.14%	29	1778	20.68	1	2	3	11	107	1	0	1	5	65	0	0	47.15%	789	25	23	0	0	0.31	3	8	6	1	4	0	2	5
5	Martin Chromiak	Monsters (CBJ)	RW	80	9	13	22	-6	22	10	54	55	70	20	41	12.86%	14	840	10.50	5	8	13	12	68	0	0	0	0	0	2	0	42.11%	38	18	9	0	0	0.52	2	6	0	2	0	4	2	3
6	Glenn Gawdin	Blue Jackets	C	40	6	14	20	-3	40	10	64	65	52	25	51	11.54%	23	904	22.62	2	1	3	8	47	1	0	1	4	73	1	0	58.18%	55	17	14	0	0	0.44	1	3	1	1	0	1	1	2
7	Tristan Broz	Monsters (CBJ)	C	86	6	12	18	-12	14	10	72	87	73	15	48	8.22%	14	1297	15.08	0	3	3	6	69	0	1	1	3	24	2	0	50.40%	248	19	16	0	0	0.28	1	3	1	0	1	0	2	1
8	Max Szuber	Monsters (CBJ)	D	55	6	11	17	-6	31	5	76	76	56	25	18	10.71%	47	1342	24.41	4	1	5	10	88	0	1	1	1	71	2	0	100.00%	1	10	32	0	0	0.25	0	0	1	0	0	1	3	0
9	Valtteri Pulli	Monsters (CBJ)	D	63	0	14	14	0	49	35	44	121	65	25	21	0%	59	1425	22.63	0	1	1	6	74	0	0	0	1	91	0	0	0%	0	20	29	0	0	0.20	0	0	4	2	1	0	2	0
10	Adam Raska	Monsters (CBJ)	LW/RW	74	7	6	13	-18	41	5	102	69	37	15	19	18.92%	14	1158	15.65	0	0	0	2	23	1	0	1	3	52	2	0	50.00%	18	20	14	0	0	0.22	0	0	0	0	1	0	1	2
11	Givani Smith	Monsters (CBJ)	RW	86	3	8	11	-1	70	20	57	29	36	10	24	8.33%	4	503	5.85	1	2	3	3	8	0	0	0	0	8	0	0	18.18%	11	8	5	1	0	0.44	0	0	1	1	2	0	1	1
12	Billy Sweezey	Monsters (CBJ)	D	79	1	8	9	-21	92	40	87	114	31	20	16	3.23%	56	1728	21.88	0	3	3	4	89	0	0	0	0	91	0	0	0%	0	9	35	0	0	0.10	1	1	4	4	0	0	0	1
13	Ben Zloty	Monsters (CBJ)	D	80	3	6	9	-8	50	20	58	120	51	20	27	5.88%	51	1694	21.18	1	0	1	3	87	0	1	1	1	91	1	1	0%	0	24	26	0	0	0.11	0	0	0	2	2	1	0	0
14	Tyson Feist	Monsters (CBJ)	D	86	1	6	7	-18	39	15	53	86	21	11	6	4.76%	34	1529	17.78	1	1	2	4	96	0	1	1	4	134	0	0	0%	0	5	23	0	0	0.09	0	0	2	0	1	0	0	0
15	Jacob Perreault	Monsters (CBJ)	RW	86	3	2	5	-10	18	0	101	59	30	7	27	10.00%	3	1014	11.79	0	0	0	0	20	0	0	0	0	0	0	1	44.44%	9	11	9	0	0	0.10	0	0	0	0	0	0	0	0
16	Ethan Frisch	Monsters (CBJ)	D	64	0	5	5	-19	20	10	32	67	15	10	9	0%	22	1107	17.30	0	0	0	2	36	0	0	0	0	58	0	0	0%	0	7	17	0	0	0.09	0	0	0	1	1	0	0	0
17	Kyle Jackson	Monsters (CBJ)	C/LW/RW	11	3	2	5	2	17	5	31	12	21	2	8	14.29%	5	191	17.39	0	0	0	0	0	0	0	0	0	0	1	0	37.50%	8	6	1	0	0	0.52	0	0	1	0	0	1	0	1
18	Tucker Robertson	Monsters (CBJ)	C	86	3	0	3	-7	10	10	35	43	15	8	9	20.00%	6	692	8.05	0	0	0	0	5	0	0	0	0	1	0	0	47.31%	167	4	8	0	0	0.09	0	2	1	1	0	0	1	0
19	Leon Muggli	Monsters (CBJ)	D	61	0	3	3	2	5	5	16	71	14	4	7	0%	17	811	13.30	0	2	2	5	54	0	0	0	0	30	0	0	0%	0	1	11	0	0	0.07	0	0	0	1	0	0	0	0
20	Braden Hache	Monsters (CBJ)	D	79	0	2	2	-1	27	5	33	21	4	1	3	0%	4	661	8.37	0	0	0	0	3	0	0	0	0	17	0	0	0%	0	1	8	0	0	0.06	0	0	0	1	0	0	0	0
21	Connor Clattenburg	Monsters (CBJ)	C	46	1	1	2	2	0	0	15	12	2	4	1	50.00%	2	238	5.18	0	0	0	0	0	0	0	0	0	0	0	0	40.43%	47	1	2	0	0	0.17	0	0	0	0	0	1	0	0
22	Curtis McKenzie	Blue Jackets	LW	1	0	1	1	1	0	0	2	0	1	0	1	0%	0	17	17.78	0	0	0	0	0	0	0	0	0	1	0	0	100.00%	1	0	0	0	0	1.12	0	0	0	0	0	0	0	0
Team Total or Average				1496	122	248	370	-162	812	330	1401	1731	1223	440	701	9.98%	568	24829	16.60	37	67	104	183	1346	5	9	14	46	1231	20	6	51.70%	2934	333	406	1	2	0.30	13	38	25	22	19	23	24	30

Show or Hide Columns

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	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Jacob Ingham	Monsters (CBJ)	76	28	30	16	0.871	2.17	4420	11	160	1239	569	3	1	0.550	40	76	0	3	2	8
2	Mitch Gibson	Monsters (CBJ)	10	2	4	2	0.858	2.34	488	1	19	134	59	0	0	0	0	10	6	0	1	0
3	Connor Hughes	Monsters (CBJ)	10	0	3	1	0.828	4.00	315	0	21	122	70	0	0	0	0	0	80	0	0	0
Team Total or Average			96	30	37	19	0.866	2.30	5224	12	200	1495	698	3	1		40	86	86	3	3	8

Show or Hide Columns

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	Age	Birthday	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Salary Cap Year 2	Salary Cap Year 3	Salary Cap Year 4	Salary Cap Year 5	Salary Cap Year 6	Salary Cap Year 7	Salary Cap Year 8	Salary Cap Year 9	Salary Cap Year 10	No Trade Year 2	No Trade Year 3	No Trade Year 4	No Trade Year 5	No Trade Year 6	No Trade Year 7	No Trade Year 8	No Trade Year 9	No Trade Year 10	Link
Adam Raska	Monsters (CBJ)	LW/RW	24	2001-09-25	CZE	No	185 Lbs	5 ft10	No	No	N/A	No	No	3	2025-10-22	False	False	Pro & Farm	1,315,000$	0$	0$	No	1,315,000$	1,315,000$	-	-	-	-	-	-	-	1,315,000$	1,315,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Ben Zloty	Monsters (CBJ)	D	24	2002-02-24	AB	No	187 Lbs	6 ft0	No	No	Assign Manually	No	No	1	2025-12-08	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Billy Sweezey	Monsters (CBJ)	D	30	1996-02-06	USA	No	204 Lbs	6 ft1	No	No	Assign Manually	No	No	1	2025-12-08	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Braden Hache	Monsters (CBJ)	D	23	2003-05-21	USA	Yes	210 Lbs	6 ft3	No	No	Assign Manually	No	No	1	2026-01-02	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Brian Halonen	Monsters (CBJ)	LW	27	1999-01-11	USA	Yes	207 Lbs	6 ft0	No	No	N/A	No	No	1		False	False	Pro & Farm	996,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Cole Guttman	Monsters (CBJ)	C/LW/RW	27	1999-04-06	USA	No	181 Lbs	5 ft10	No	No	N/A	No	No	1		False	False	Pro & Farm	950,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Connor Clattenburg	Monsters (CBJ)	C	21	2005-05-02	ON	Yes	205 Lbs	6 ft2	No	No	Draft	No	No	3	2025-10-22	False	False	Pro & Farm	1,265,000$	0$	0$	No	1,265,000$	1,265,000$	-	-	-	-	-	-	-	1,265,000$	1,265,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Connor Hughes	Monsters (CBJ)	G	29	1996-09-10	SWI	No	231 Lbs	6 ft4	No	No	Assign Manually	No	No	1	2025-12-08	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Egor Sokolov	Monsters (CBJ)	LW	26	2000-06-07	RUS	Yes	217 Lbs	6 ft3	No	No	Draft	No	No	3	2025-10-22	False	False	Pro & Farm	1,495,000$	0$	0$	No	1,495,000$	1,495,000$	-	-	-	-	-	-	-	1,495,000$	1,495,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Ethan Frisch	Monsters (CBJ)	D	25	2000-10-29	USA	No	192 Lbs	5 ft11	No	No	Free Agent	No	No	2	2024-10-16	False	False	Pro & Farm	800,000$	0$	0$	No	800,000$	-	-	-	-	-	-	-	-	800,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Givani Smith	Monsters (CBJ)	RW	28	1998-02-27	CAN	No	214 Lbs	6 ft2	No	No	N/A	No	No	2		False	False	Pro & Farm	1,136,000$	0$	0$	No	1,136,000$	-	-	-	-	-	-	-	-	1,136,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link / NHL Link
Jacob Ingham	Monsters (CBJ)	G	25	2000-06-10	ONT	No	205 Lbs	6 ft5	No	No	N/A	No	No	3	2025-12-08	False	False	Pro & Farm	1,250,000$	0$	0$	No	1,250,000$	1,250,000$	-	-	-	-	-	-	-	1,250,000$	1,250,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Jacob Perreault	Monsters (CBJ)	RW	24	2002-04-15	CAN	No	196 Lbs	6 ft0	No	No	N/A	No	No	3	2025-10-17	False	False	Pro & Farm	1,106,000$	0$	0$	No	1,106,000$	1,106,000$	-	-	-	-	-	-	-	1,106,000$	1,106,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Kyle Jackson	Monsters (CBJ)	C/LW/RW	23	2002-10-17	CAN	Yes	192 Lbs	6 ft2	No	No	Prospect	No	No	3	2025-10-22	False	False	Pro & Farm	1,467,000$	0$	0$	No	1,467,000$	1,467,000$	-	-	-	-	-	-	-	1,467,000$	1,467,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Leon Muggli	Monsters (CBJ)	D	19	2006-07-09	SWI	Yes	173 Lbs	6 ft1	No	No	Draft	No	No	3	2025-10-22	False	False	Pro & Farm	1,261,000$	0$	0$	No	1,261,000$	1,261,000$	-	-	-	-	-	-	-	1,261,000$	1,261,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Martin Chromiak (Out of Payroll)	Monsters (CBJ)	RW	23	2002-08-20	SVK	No	190 Lbs	6 ft0	No	No	N/A	No	No	1		False	False	Pro & Farm	820,000$	0$	0$	Yes	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Max Szuber	Monsters (CBJ)	D	23	2002-08-25	GER	No	201 Lbs	6 ft3	No	No	Assign Manually	No	No	1	2026-02-24	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Mitch Gibson	Monsters (CBJ)	G	26	1999-06-25	USA	No	187 Lbs	6 ft0	No	No	Assign Manually	No	No	1	2026-03-10	False	False	Pro & Farm	1,000,000$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Tristan Broz	Monsters (CBJ)	C	23	2002-10-10	USA	Yes	205 Lbs	6 ft0	No	No	Prospect	No	No	3	2025-10-22	False	False	Pro & Farm	1,350,000$	0$	0$	No	1,350,000$	1,350,000$	-	-	-	-	-	-	-	1,350,000$	1,350,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Tucker Robertson	Monsters (CBJ)	C	22	2003-06-22	CAN	No	189 Lbs	5 ft11	No	No	N/A	No	No	3	2025-10-22	False	False	Pro & Farm	1,256,000$	0$	0$	No	1,256,000$	1,256,000$	-	-	-	-	-	-	-	1,256,000$	1,256,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Tyson Feist	Monsters (CBJ)	D	25	2001-01-14	BC	No	181 Lbs	6 ft2	No	No	Free Agent	No	No	2	2024-10-16	False	False	Pro & Farm	800,000$	0$	0$	No	800,000$	-	-	-	-	-	-	-	-	800,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Valtteri Pulli	Monsters (CBJ)	D	25	2001-03-13	FIN	No	209 Lbs	6 ft6	No	No	Free Agent	No	No	2	2024-10-16	False	False	Pro & Farm	800,000$	0$	0$	No	800,000$	-	-	-	-	-	-	-	-	800,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
22	24.64	198 Lbs	6 ft1	2.00	1,093,955$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Brian Halonen	Cole Guttman	Givani Smith	40	1	2	2
2	Egor Sokolov	Tristan Broz	Kyle Jackson	30	1	2	2
3	Adam Raska	Tucker Robertson	Givani Smith	20	1	2	2
4	Kyle Jackson	Connor Clattenburg	Jacob Perreault	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Valtteri Pulli	Max Szuber	40	1	2	2
2	Billy Sweezey	Ethan Frisch	30	1	2	2
3	Tyson Feist	Braden Hache	20	1	2	2
4	Leon Muggli	Max Szuber	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Brian Halonen	Cole Guttman	Givani Smith	60	1	2	2
2	Egor Sokolov	Tristan Broz	Jacob Perreault	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Tyson Feist	Max Szuber	60	1	2	2
2	Billy Sweezey	Ethan Frisch	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Cole Guttman	Brian Halonen	60	1	2	2
2	Tristan Broz	Egor Sokolov	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Valtteri Pulli	Max Szuber	60	1	2	2
2	Billy Sweezey	Ethan Frisch	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Cole Guttman	60	1	2	2	Braden Hache	Max Szuber	60	1	2	2
2	Tristan Broz	40	1	2	2	Billy Sweezey	Ethan Frisch	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Cole Guttman	Brian Halonen	60	1	2	2
2	Tristan Broz	Egor Sokolov	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Tyson Feist	Max Szuber	60	1	2	2
2	Billy Sweezey	Ethan Frisch	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Brian Halonen	Cole Guttman	Jacob Perreault	Valtteri Pulli	Max Szuber

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Brian Halonen	Cole Guttman	Egor Sokolov	Valtteri Pulli	Max Szuber

Extra Forwards
Normal	PowerPlay	Penalty Kill
Givani Smith, Tristan Broz, Jacob Perreault	Givani Smith, Tristan Broz	Givani Smith

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Tyson Feist, Braden Hache, Leon Muggli	Tyson Feist	Tyson Feist, Braden Hache

Penalty Shots
Cole Guttman, Brian Halonen, Egor Sokolov, Tristan Broz, Givani Smith

Goalie
#1 : Jacob Ingham, #2 : Mitch Gibson

Custom OT Lines Forwards
Brian Halonen, Egor Sokolov, Cole Guttman, Kyle Jackson, Jacob Perreault, Tristan Broz, Givani Smith, Adam Raska, Tucker Robertson, Connor Clattenburg

Custom OT Lines Defensemen
Ethan Frisch, Max Szuber, Braden Hache, Billy Sweezey, Tyson Feist

Show or Hide Columns

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

	Overall												Home											Visitor
#	VS Team	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	PCT	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
1	Admirals	2	0	1	0	0	0	0	1	1	3	-2	1	0	1	0	0	0	0	0	0	1	-1	1	0	0	0	0	0	0	1	1	2	-1	1	0.250	1	2	3	0	0	25	56	61	23	16	272	418	547	80	22	11	32	42	2	1	50.00%	6	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
2	Americans	3	1	2	0	0	0	0	0	7	13	-6	1	0	1	0	0	0	0	0	5	9	-4	2	1	1	0	0	0	0	0	2	4	-2	2	0.333	7	12	19	0	1	25	56	61	23	50	272	418	547	80	73	17	45	68	9	4	44.44%	5	1	80.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
3	Barracuda	5	0	3	0	0	1	1	0	5	9	-4	2	0	2	0	0	0	0	0	0	3	-3	3	0	1	0	0	1	1	0	5	6	-1	3	0.300	5	6	11	0	0	25	56	61	23	54	272	418	547	80	73	23	41	85	12	2	16.67%	8	2	75.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
4	Bears	3	0	3	0	0	0	0	0	3	11	-8	2	0	2	0	0	0	0	0	3	9	-6	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	3	6	9	0	0	25	56	61	23	57	272	418	547	80	69	15	10	40	4	0	0.00%	5	3	40.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
5	Bruins	2	0	2	0	0	0	0	0	0	3	-3	1	0	1	0	0	0	0	0	0	1	-1	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	0	0	0	0	0	25	56	61	23	19	272	418	547	80	23	5	4	26	0	0	0%	2	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
6	Canucks	2	0	1	0	0	1	0	0	3	6	-3	1	0	0	0	0	1	0	0	1	2	-1	1	0	1	0	0	0	0	0	2	4	-2	1	0.250	3	4	7	0	0	25	56	61	23	23	272	418	547	80	26	9	45	32	2	0	0.00%	5	2	60.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
7	Checkers	2	1	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	1	0	1	1	0	1	0	0	0	0	0	1	3	-2	2	0.500	2	4	6	0	1	25	56	61	23	20	272	418	547	80	18	7	4	38	2	0	0.00%	2	2	0.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
8	Comets	5	2	1	0	0	1	0	1	10	9	1	2	0	1	0	0	1	0	0	3	5	-2	3	2	0	0	0	0	0	1	7	4	3	6	0.600	10	12	22	0	1	25	56	61	23	73	272	418	547	80	102	28	47	80	9	3	33.33%	16	3	81.25%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
9	Condors	2	1	0	0	1	0	0	0	5	3	2	1	0	0	0	1	0	0	0	3	2	1	1	1	0	0	0	0	0	0	2	1	1	4	1.000	5	8	13	0	0	25	56	61	23	41	272	418	547	80	30	11	4	33	3	0	0.00%	2	1	50.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
10	Crunch	2	0	1	0	0	0	0	1	2	5	-3	1	0	0	0	0	0	0	1	0	1	-1	1	0	1	0	0	0	0	0	2	4	-2	1	0.250	2	1	3	0	0	25	56	61	23	18	272	418	547	80	43	10	2	34	3	1	33.33%	2	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
11	Eagles	2	1	1	0	0	0	0	0	4	6	-2	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	1	5	-4	2	0.500	4	7	11	0	0	25	56	61	23	73	272	418	547	80	44	14	42	50	5	0	0.00%	6	2	66.67%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
12	Griffins	3	0	0	0	1	1	0	1	5	6	-1	2	0	0	0	1	0	0	1	4	4	0	1	0	0	0	0	1	0	0	1	2	-1	4	0.667	5	9	14	0	1	25	56	61	23	24	272	418	547	80	25	10	2	50	6	0	0.00%	1	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
13	Gulls	2	0	1	0	0	0	0	1	1	4	-3	1	0	1	0	0	0	0	0	0	2	-2	1	0	0	0	0	0	0	1	1	2	-1	1	0.250	1	2	3	0	0	25	56	61	23	29	272	418	547	80	16	2	11	28	5	0	0.00%	3	1	66.67%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
14	Heat	2	1	1	0	0	0	0	0	3	3	0	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	0	2	-2	2	0.500	3	5	8	0	0	25	56	61	23	21	272	418	547	80	25	9	4	21	3	0	0.00%	2	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
15	IceHogs	5	3	0	0	0	1	1	0	20	10	10	3	1	0	0	0	1	1	0	10	7	3	2	2	0	0	0	0	0	0	10	3	7	9	0.900	20	29	49	0	2	25	56	61	23	120	272	418	547	80	73	20	88	115	15	7	46.67%	9	2	77.78%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
16	Islanders	3	1	2	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	0	2	-2	2	1	1	0	0	0	0	0	4	4	0	2	0.333	4	6	10	0	0	25	56	61	23	35	272	418	547	80	64	28	10	49	6	1	16.67%	5	1	80.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
17	Marlies	2	1	0	0	1	0	0	0	6	3	3	1	1	0	0	0	0	0	0	3	1	2	1	0	0	0	1	0	0	0	3	2	1	4	1.000	6	9	15	0	0	25	56	61	23	32	272	418	547	80	25	8	10	41	6	2	33.33%	5	1	80.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
18	Moose	2	0	0	0	1	1	0	0	6	6	0	1	0	0	0	0	1	0	0	3	4	-1	1	0	0	0	1	0	0	0	3	2	1	3	0.750	6	11	17	0	0	25	56	61	23	36	272	418	547	80	31	10	31	27	4	4	100.00%	8	2	75.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
19	Penguins	2	0	0	0	0	2	0	0	0	2	-2	1	0	0	0	0	1	0	0	0	1	-1	1	0	0	0	0	1	0	0	0	1	-1	2	0.500	0	0	0	0	0	25	56	61	23	15	272	418	547	80	17	7	6	37	1	0	0.00%	3	0	100.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
20	Phantoms	2	0	2	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	1	5	-4	0	0.000	2	2	4	0	0	25	56	61	23	31	272	418	547	80	40	11	12	34	7	1	14.29%	6	3	50.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
21	Reign	2	1	1	0	0	0	0	0	6	5	1	1	0	1	0	0	0	0	0	2	4	-2	1	1	0	0	0	0	0	0	4	1	3	2	0.500	6	10	16	0	0	25	56	61	23	38	272	418	547	80	66	22	27	32	10	2	20.00%	11	1	90.91%	1	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
22	Roadrunners	2	1	1	0	0	0	0	0	7	11	-4	1	1	0	0	0	0	0	0	5	3	2	1	0	1	0	0	0	0	0	2	8	-6	2	0.500	7	12	19	0	0	25	56	61	23	31	272	418	547	80	75	22	30	35	7	3	42.86%	10	3	70.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
23	Rocket	6	0	2	0	1	2	1	0	6	9	-3	4	0	2	0	1	1	0	0	5	8	-3	2	0	0	0	0	1	1	0	1	1	0	6	0.500	6	7	13	0	2	25	56	61	23	66	272	418	547	80	64	18	20	87	3	1	33.33%	10	5	50.00%	2	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
24	Senators	5	2	2	0	1	0	0	0	13	13	0	2	1	1	0	0	0	0	0	5	5	0	3	1	1	0	1	0	0	0	8	8	0	6	0.600	13	22	35	1	1	25	56	61	23	68	272	418	547	80	92	30	35	79	9	2	22.22%	10	4	60.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
25	Silver Knights	2	0	0	0	0	2	0	0	6	8	-2	1	0	0	0	0	1	0	0	3	4	-1	1	0	0	0	0	1	0	0	3	4	-1	2	0.500	6	9	15	0	0	25	56	61	23	38	272	418	547	80	32	10	24	35	6	2	33.33%	2	2	0.00%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
26	Stars	3	0	1	0	2	0	0	0	8	10	-2	1	0	0	0	1	0	0	0	2	1	1	2	0	1	0	1	0	0	0	6	9	-3	4	0.667	8	13	21	0	0	25	56	61	23	58	272	418	547	80	61	23	41	56	5	1	20.00%	8	3	62.50%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
27	Thunderbirds	3	0	3	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	1	5	-4	0	0.000	5	6	11	0	0	25	56	61	23	52	272	418	547	80	99	39	87	44	14	3	21.43%	11	4	63.64%	1	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
28	Wild	2	0	2	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	4	8	12	0	0	25	56	61	23	51	272	418	547	80	72	29	12	29	2	1	50.00%	6	1	83.33%	1	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
29	Wolf Pack	3	1	1	0	1	0	0	0	6	3	3	1	0	1	0	0	0	0	0	0	1	-1	2	1	0	0	1	0	0	0	6	2	4	4	0.667	6	9	15	0	1	25	56	61	23	35	272	418	547	80	39	14	31	37	6	0	0.00%	8	1	87.50%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
30	Wolves	5	1	2	0	0	1	0	1	4	9	-5	3	0	1	0	0	1	0	1	3	6	-3	2	1	1	0	0	0	0	0	1	3	-2	4	0.400	4	6	10	0	1	25	56	61	23	52	272	418	547	80	57	28	59	89	5	0	0.00%	17	3	82.35%	0	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
	Total	86	18	37	0	9	13	3	6	154	207	-53	43	7	20	0	4	8	1	3	73	100	-27	43	11	17	0	5	5	2	3	81	107	-26	79	0.459	154	237	391	1	11	25	56	61	23	1276	272	418	547	80	1496	490	816	1453	171	41	23.98%	194	53	72.68%	5	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
	_Since Last GM Reset	86	18	37	0	9	13	3	6	154	207	-53	43	7	20	0	4	8	1	3	73	100	-27	43	11	17	0	5	5	2	3	81	107	-26	79	0.459	154	237	391	1	11	25	56	61	23	1276	272	418	547	80	1496	490	816	1453	171	41	23.98%	194	53	72.68%	5	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
	_Vs Conference	48	10	18	0	4	9	3	4	85	99	-14	24	2	11	0	2	6	1	2	34	49	-15	24	8	7	0	2	3	2	2	51	50	1	47	0.490	85	123	208	1	8	25	56	61	23	687	272	418	547	80	742	237	423	789	80	19	23.75%	100	27	73.00%	3	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096
	_Vs Division	21	8	10	0	2	6	3	2	55	67	-12	11	2	7	0	1	4	1	1	28	27	1	10	6	3	0	1	2	2	1	27	40	-13	34	0.810	55	88	143	0	2	25	56	61	23	437	272	418	547	80	477	168	363	398	54	20	37.04%	64	17	73.44%	2	574	1081	53.10%	646	1285	50.27%	446	810	55.06%	1427	485	1583	985	2223	1096

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
86	79	SOL1	154	237	391	1276	1496	490	816	1453	1	11

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
86	18	37	9	13	3	6	154	207

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
43	7	20	4	8	1	3	73	100

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
43	11	17	5	5	2	3	81	107

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	2	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
171	41	23.98%	194	53	72.68%	5

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
272	418	547	80	25	56	61	23

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
574	1081	53.10%	646	1285	50.27%	446	810	55.06%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1427	485	1583	985	2223	1096

Last Played Games Show or Hide Columns

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
1	6	Rocket	2	Monsters	1	L	X		Box score
2	21	Monsters	1	Rocket	0	W	X	X	Box score
4	43	Wolves	3	Monsters	2	L	X	X	Box score
5	51	Monsters	4	Senators	7	L			Box score
7	70	Rocket	0	Monsters	1	W	X		Box score
9	97	IceHogs	0	Monsters	1	W	X	X	Box score
10	103	Monsters	3	Comets	2	W			Box score
11	126	Monsters	0	Wolves	3	L			Box score
12	136	Barracuda	1	Monsters	0	L			Box score
13	148	Monsters	1	Barracuda	2	L	X		Box score
15	170	Rocket	4	Monsters	2	L			Box score
16	184	Monsters	3	Stars	2	W	X		Box score
17	197	Monsters	2	Senators	0	W			Box score
18	213	Thunderbirds	4	Monsters	3	L			Box score
19	231	IceHogs	6	Monsters	5	L	X		Box score
20	245	Monsters	2	Islanders	3	L			Box score
22	258	Monsters	3	Comets	0	W			Box score
23	271	Canucks	2	Monsters	1	L	X		Box score
24	289	Moose	4	Monsters	3	L	X		Box score
26	305	Monsters	3	Silver Knights	4	L	X		Box score
27	320	Wild	2	Monsters	1	L			Box score
29	335	Monsters	2	Canucks	4	L			Box score
30	352	Heat	1	Monsters	3	W			Box score
31	375	Wolves	1	Monsters	0	L	X		Box score
32	384	Monsters	1	Griffins	2	L	X		Box score
33	398	Monsters	2	Condors	1	W			Box score
34	413	Reign	4	Monsters	2	L			Box score
35	433	Monsters	0	Bears	2	L			Box score
36	442	Monsters	2	Crunch	4	L			Box score
37	458	Rocket	2	Monsters	1	L			Box score
39	475	Senators	4	Monsters	2	L			Box score
40	494	Monsters	1	Checkers	3	L			Box score
41	507	Condors	2	Monsters	3	W	X		Box score
42	526	Monsters	2	Senators	1	W	X		Box score
43	537	Monsters	1	Thunderbirds	5	L			Box score
44	550	Admirals	1	Monsters	0	L			Box score
45	566	Wolf Pack	1	Monsters	0	L			Box score
46	584	Monsters	2	Islanders	1	W			Box score
47	598	Monsters	3	Moose	2	W	X		Box score
48	611	Penguins	1	Monsters	0	L	X		Box score
49	628	Bruins	1	Monsters	0	L			Box score
51	657	Islanders	2	Monsters	0	L			Box score
53	674	Monsters	0	Bruins	2	L			Box score
54	689	Silver Knights	4	Monsters	3	L	X		Box score
55	708	Monsters	3	Stars	7	L			Box score
56	719	Checkers	0	Monsters	1	W			Box score
57	735	Monsters	4	Reign	1	W			Box score
59	751	Americans	9	Monsters	5	L			Box score
60	769	Monsters	0	Penguins	1	L	X		Box score
61	780	Gulls	2	Monsters	0	L			Box score
63	803	Monsters	0	Heat	2	L			Box score
64	812	IceHogs	1	Monsters	4	W			Box score
65	824	Monsters	2	Barracuda	1	W	X	X	Box score
67	844	Comets	1	Monsters	0	L			Box score
68	856	Monsters	2	Americans	0	W			Box score
69	871	Monsters	3	Marlies	2	W	X		Box score
70	884	Crunch	1	Monsters	0	L	X	X	Box score
72	905	Barracuda	2	Monsters	0	L			Box score
73	915	Monsters	0	Rocket	1	L	X		Box score
74	927	Monsters	2	Barracuda	3	L			Box score
75	942	Marlies	1	Monsters	3	W			Box score
77	964	Griffins	4	Monsters	3	L	X	X	Box score
79	975	Monsters	1	Wolf Pack	0	W	X		Box score
80	997	Bears	3	Monsters	2	L			Box score
81	1003	Monsters	1	Phantoms	5	L			Box score
82	1021	Monsters	2	Roadrunners	8	L			Box score
83	1036	Bears	6	Monsters	1	L			Box score
85	1056	Griffins	0	Monsters	1	W	X		Box score
86	1065	Monsters	1	Gulls	2	L	X	X	Box score
88	1083	Monsters	1	Admirals	2	L	X	X	Box score
89	1098	Roadrunners	3	Monsters	5	W			Box score
90	1116	Monsters	1	Wolves	0	W			Box score
91	1126	Monsters	0	Americans	4	L			Box score
92	1139	Phantoms	2	Monsters	1	L			Box score
94	1158	Wolves	2	Monsters	1	L			Box score
96	1180	Monsters	1	Eagles	5	L			Box score
Trade Deadline --- Trades can’t be done after this day is simulated!
97	1194	Comets	4	Monsters	3	L	X		Box score
98	1201	Monsters	7	IceHogs	3	W			Box score
99	1220	Eagles	1	Monsters	3	W			Box score
100	1231	Monsters	3	Wild	6	L			Box score
101	1239	Monsters	3	IceHogs	0	W			Box score
102	1246	Monsters	5	Wolf Pack	2	W			Box score
104	1264	Thunderbirds	4	Monsters	1	L			Box score
106	1290	Senators	1	Monsters	3	W			Box score
108	1311	Stars	1	Monsters	2	W	X		Box score
110	1321	Monsters	1	Comets	2	L	X	X	Box score

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	58,046	32,712
Attendance PCT	67.50%	76.07%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
0	2111 - 70.36%	87,400$	3,758,211$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
4,243,192$	2,406,700$	2,406,700$	1,600,000$0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
20,756$	2,612,469$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	35,774$	0$

Monsters Players Stat Leaders (Regular Season)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Monsters Goalies Stat Leaders (Regular Season)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

Monsters Career Team Stats

Show or Hide Columns

	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

Monsters Players Stat Leaders (Play-Off)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Monsters Goalies Stat Leaders (Play-Off)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Monsters
	GP: 86 \| W: 30 \| L: 37 \| OTL: 19 \| P: 79 GF: 154 \| GA: 207 \| PP%: 23.98% \| PK%: 72.68% GM : Trent Zeigler \| Morale : 22 \| Team Overall : 57