Blue Jackets
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Career Team Stat

Game Center
	Wolves 11-4-0, 22pts	6	FINAL	4	Monsters 0-4-0, 0pts

Team Stats
OTL1	Streak	L4
6-2-0	Home Record	0-2-0
5-2-0	Away Record	0-2-0
6-3-1	Last 10 Games	0-4-0
4.47	Goals Per Game	1.75
2.27	Goals Against Per Game	8.00
23.33%	Power Play Percentage	0.00%
83.33%	Penalty Kill Percentage	57.14%

Wolves
11-4-0, 22pts

FINAL

Monsters
0-4-0, 0pts

Team Stats
OTL1	Streak	L4
6-2-0	Home Record	0-2-0
5-2-0	Away Record	0-2-0
6-3-1	Last 10 Games	0-4-0
4.47	Goals Per Game	1.75
2.27	Goals Against Per Game	8.00
23.33%	Power Play Percentage	0.00%
83.33%	Penalty Kill Percentage	57.14%

Team Leaders
	Goals Andre Lee 2	Assists Andre Lee 2

	Points Andre Lee 4	Plus/Minus Aliaksei Protas -1

Team Stats
Goals For 7 1.75 GFG	Shots For 83 20.75 Avg	Power Play Percentage 0.0% 0 GF	Offensive Zone Start 38.0%
Goals Against 32 8.00 GAA	Shots Against 189 47.25 Avg	Penalty Kill Percentage 57.1%% 6 GA	Defensive Zone Start 37.3%

Team Info
	General Manager	Rambo En-na
	Coach	Joel Bouchard
	Division	Division 2
	Conference	Conference 1
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	0
	Season Tickets	300
Roster Info
	Pro Team	15
	Farm Team	20
	Contract Limit	35 / 250
	Prospects	5
Team History
	This Season	0-4
	History	37-42-2 (0.457%)
	Playoff Appearances	1
	Playoff Record (W-L)	0-4
	Stanley Cup	0

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	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	Carl Hagelin		X		100.00	56	37	89	75	71	84	86	68	54	65	63	81	69	81	75	26	56	69	0	34	1	2,750,000$
2	Tyler Bozak	X			100.00	56	35	91	64	75	82	83	66	84	71	63	82	61	84	77	21	73	69	0	37	1	700,000$
3	Zach Aston-Reese	X			100.00	90	39	88	65	76	83	85	64	63	65	66	83	62	69	68	36	61	69	0	28	1	700,000$
4	Tyler Pitlick	X			100.00	82	36	89	67	79	83	78	64	71	63	62	80	58	73	71	59	72	68	0	31	1	700,000$
5	Quinton Byfield	X			100.00	76	37	82	68	93	84	81	66	79	64	67	65	72	61	64	93	72	67	0	20	2	894,167$
6	Aliaksei Protas	X			100.00	80	52	92	63	97	79	83	63	75	62	61	63	59	61	63	64	61	65	0	22	2	888,333$
7	Pat Maroon		X		100.00	77	82	64	62	91	79	88	63	57	67	64	56	61	79	74	26	58	65	0	35	2	1,000,000$
8	Chase De Leo	X			100.00	58	39	86	64	68	87	82	63	77	62	61	65	62	71	66	59	56	64	0	27	2	762,500$
9	Andre Lee		X		100.00	71	42	73	54	91	75	64	53	58	55	50	59	53	62	64	59	63	58	0	22	2	883,750$
10	Zach Werenski			X	100.00	57	38	89	78	83	95	86	76	30	82	73	76	59	68	67	84	40	73	0	25	6	9,583,333$
11	Philip Broberg			X	100.00	70	39	81	69	83	81	79	68	30	67	59	63	52	61	63	87	65	66	0	21	2	863,333$
12	Kale Clague			X	100.00	61	36	81	69	72	85	77	67	30	73	59	60	52	64	66	69	63	65	0	24	1	750,000$
13	Kaedan Korczak			X	100.00	67	33	82	59	84	79	71	58	30	57	55	65	50	61	63	74	58	63	0	22	2	789,167$
Scratches
1	Tanner Laczynski	X			100.00	69	37	94	61	75	87	66	59	74	60	58	63	61	65	67	47	39	62	0	25	2	762,500$

	TEAM AVERAGE				100.00	69	42	84	66	81	83	79	64	58	65	62	69	59	69	68	57	60	66

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	Age	Contract	Salary
1	Chris Driedger	100.00	89	87	82	88	88	87	89	88	87	89	88	68	81	54	63	84	0	29	2	3,500,000$
Scratches

	TEAM AVERAGE	100.00	89	87	82	88	88	87	89	88	87	89	88	68	81	54	63	84

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Joel Bouchard	71	68	69	65	74	69	78	CAN	48	1	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	PPS	PPM	PKM	FO%	FOT	P/20	FL
1	Andre Lee	Monsters (CLB)	LW	4	2	2	4	-10	2	0	20	4	13	1	8	15.38%	6	64	16.06	0	2	0	66.67%	3	1.25	0
2	Philip Broberg	Monsters (CLB)	D	4	0	2	2	-7	4	0	16	4	2	0	1	0.00%	8	60	15.19	1	2	1	0.00%	0	0.66	0
3	Kaedan Korczak	Monsters (CLB)	D	4	0	1	1	-1	4	0	5	2	5	0	3	0.00%	4	35	8.93	0	0	0	0.00%	0	0.56	0
4	Aliaksei Protas	Monsters (CLB)	C	4	0	0	0	-1	0	0	3	1	0	1	5	0.00%	1	12	3.19	0	3	0	50.00%	2	0.00%	0
5	Pat Maroon	Monsters (CLB)	LW	4	0	0	0	-5	13	5	23	6	16	6	16	0.00%	7	85	21.35	3	16	0	50.00%	8	0.00%	1
Team Total or Average				20	2	5	7	-24	23	5	67	17	36	8	33	5.56%	26	258	12.94	4	24	1	53.85%	13	0.54	1

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

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	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Waiver Possible	Contract	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	Link
Aliaksei Protas	Monsters (CLB)	C	22	2001-01-06	No	225 Lbs	6 ft6	No	No	No	No	2	Pro & Farm	888,333$	0$	0$	No	888,333$					Link
Andre Lee	Monsters (CLB)	LW	22	2000-07-26	No	206 Lbs	6 ft5	No	No	No	No	2	Pro & Farm	883,750$	0$	0$	No	883,750$					Link
Carl Hagelin	Monsters (CLB)	LW	34	1988-08-23	No	183 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	2,750,000$	0$	0$	No						Link
Chase De Leo	Monsters (CLB)	C	27	1995-10-25	No	186 Lbs	5 ft9	No	No	No	No	2	Pro & Farm	762,500$	0$	0$	No	762,500$					Link
Chris Driedger	Monsters (CLB)	G	29	1994-05-18	No	208 Lbs	6 ft4	No	No	No	No	2	Pro & Farm	3,500,000$	0$	0$	No	3,500,000$					Link
Kaedan Korczak	Monsters (CLB)	D	22	2001-01-29	No	202 Lbs	6 ft3	No	No	No	No	2	Pro & Farm	789,167$	0$	0$	No	789,167$					Link
Kale Clague	Monsters (CLB)	D	24	1998-06-05	No	190 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No						Link
Pat Maroon	Monsters (CLB)	LW	35	1988-04-23	No	238 Lbs	6 ft3	No	No	No	No	2	Pro & Farm	1,000,000$	0$	0$	No	700,000$					Link
Philip Broberg	Monsters (CLB)	D	21	2001-06-25	No	199 Lbs	6 ft3	No	No	No	No	2	Pro & Farm	863,333$	0$	0$	No	863,333$					Link
Quinton Byfield	Monsters (CLB)	C	20	2002-08-19	No	220 Lbs	6 ft5	No	No	No	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$					Link
Tanner Laczynski	Monsters (CLB)	C	25	1997-06-01	No	190 Lbs	6 ft1	No	No	No	No	2	Pro & Farm	762,500$	0$	0$	No	762,500$					Link
Tyler Bozak	Monsters (CLB)	C	37	1986-03-19	No	187 Lbs	6 ft1	No	No	No	No	1	Pro & Farm	700,000$	0$	0$	No						Link
Tyler Pitlick	Monsters (CLB)	C	31	1991-11-01	No	200 Lbs	6 ft2	No	No	No	No	1	Pro & Farm	700,000$	0$	0$	No						Link
Zach Aston-Reese	Monsters (CLB)	C	28	1994-08-10	No	204 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	700,000$	0$	0$	No						Link
Zach Werenski	Monsters (CLB)	D	25	1997-07-19	No	213 Lbs	6 ft2	No	No	No	No	6	Pro & Farm	9,583,333$	0$	0$	No	9,583,333$	9,583,333$	9,583,333$	9,583,333$	9,583,333$	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
15	26.80	203 Lbs	6 ft2	1.93	1,701,806$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Pat Maroon			40	1	2	2
2	Andre Lee			30	1	2	2
3				20	1	2	2
4	Pat Maroon		Aliaksei Protas	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			40	1	2	2
2		Philip Broberg	30	1	2	2
3	Kaedan Korczak		20	1	2	2
4			10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Pat Maroon			60	1	2	2
2	Andre Lee			40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2		Philip Broberg	40	1	2	2

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

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

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

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2		Philip Broberg	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Pat Maroon

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Pat Maroon

Extra Forwards
Normal	PowerPlay	Penalty Kill
Aliaksei Protas, Andre Lee, Pat Maroon	Aliaksei Protas, Andre Lee	Pat Maroon

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Kaedan Korczak, Philip Broberg,	Kaedan Korczak	Philip Broberg,

Penalty Shots
, , , , Pat Maroon

Goalie
#1 : , #2 :

Custom OT Lines Forwards
, , , , Pat Maroon, Aliaksei Protas, Aliaksei Protas, Andre Lee, , ,

Custom OT Lines Defensemen
, , , Philip Broberg, Kaedan Korczak

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

	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	Wolves	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	0.000	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17
	Total	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	0.000	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17
	_Since Last GM Reset	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	0.000	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17
	_Vs Conference	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	0.000	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17
	_Vs Division	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	0.000	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
4	0	L4	7	13	20	83	189	40	35	87	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	0	4	0	0	0	0	7	32

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	5	13

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	0	2	0	0	0	0	2	19

Last 10 Games
W	L	OTW	OTL	SOW	SOL
0	4	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
13	0	0.00%	14	6	57.14%	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
26	29	28	0	2	2	3	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
34	109	31.19%	28	107	26.17%	22	71	30.99%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
72	50	129	22	38	17

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	Link
1 - 2023-04-16	1	Monsters	1	Wolves	10	AL	BoxScore
3 - 2023-04-18	9	Monsters	1	Wolves	9	AL	BoxScore
5 - 2023-04-20	17	Wolves	6	Monsters	4	BL	BoxScore
7 - 2023-04-22	25	Wolves	7	Monsters	1	BL	BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
-2	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	2,552,708$	2,292,708$	0$

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

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	3	0$	0$

Monsters Players Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Pat Maroon	82	123	44	167	38	148	400	152	618	19.90%	104	1694	20.67	14	7	21	54	13	7	81.48	15	1.97	1	2
2	Andre Lee	82	74	32	106	10	98	331	111	576	12.85%	76	1397	17.04	9	8	17	54	12	3	72.09	3	1.52	1	1
3	Philip Broberg	82	24	66	90	15	110	254	87	105	22.86%	126	1274	15.54	2	1	3	4	1	1	0.00%	1	1.41	0	0
4	Kaedan Korczak	82	17	34	51	8	59	158	47	78	21.79%	81	808	9.86	0	0	0	0	0	1	0.00%	1	1.26	0	0
5	Aliaksei Protas	82	9	11	20	9	2	17	10	41	21.95%	7	154	1.89	3	0	3	8	0	0	69.23	0	2.59	0	1

Monsters Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA
1	Chris Driedger	3	1	1	1	0.919	3.26	184	0	0	10	124	0	0	0	0.333	3

Monsters Career Team Stats

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
1	82	35	42	0	1	2	1	1	349	399	-50	41	20	19	0	0	1	0	1	180	194	-14	41	15	23	0	1	1	1	0	169	205	-36	77	349	589	938	3	0	139	111	97	3	2986	1011	976	989	16	3044	841	631	1871	181	41	22.65%	250	71	71.60%	1	960	2231	43.03%	857	2121	40.41%	587	1452	40.43%	2121	1617	1928	470	883	444
Total Regular Season	82	35	42	0	1	2	1	1	349	399	-50	41	20	19	0	0	1	0	1	180	194	-14	41	15	23	0	1	1	1	0	169	205	-36	77	349	589	938	3	0	139	111	97	3	2986	1011	976	989	16	3044	841	631	1871	181	41	22.65%	250	71	71.60%	1	960	2231	43.03%	857	2121	40.41%	587	1452	40.43%	2121	1617	1928	470	883	444
Playoff
1	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17
Total Playoff	4	0	4	0	0	0	0	0	7	32	-25	2	0	2	0	0	0	0	0	5	13	-8	2	0	2	0	0	0	0	0	2	19	-17	0	7	13	20	0	0	2	2	3	0	83	26	29	28	0	189	40	35	87	13	0	0.00%	14	6	57.14%	0	34	109	31.19%	28	107	26.17%	22	71	30.99%	72	50	129	22	38	17

Monsters Players Stat Leaders (Play-Off)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPS	FO%	P/20
1	Andre Lee	4	2	2	4	-10	2	20	4	13	15.38%	6	64	16.06	0	66.67	1.25
2	Philip Broberg	4	0	2	2	-7	4	16	4	2	0.00%	8	60	15.19	1	0.00%	0.66
3	Kaedan Korczak	4	0	1	1	-1	4	5	2	5	0.00%	4	35	8.93	0	0.00%	0.56
4	Aliaksei Protas	4	0	0	0	-1	0	3	1	0	0.00%	1	12	3.19	0	50.00	0.00%
5	Pat Maroon	4	0	0	0	-5	13	23	6	16	0.00%	7	85	21.35	3	50.00	0.00%

Monsters Goalies Stat Leaders (Play-Off)

Show or Hide Column

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

	Monsters
	GP: 4 \| W: 0 \| L: 4 GF: 7 \| GA: 32 \| PP%: 0.00% \| PK%: 57.14% GM : Rambo En-na \| Morale : 20 \| Team Overall : 67