Panthers
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Career Team Stat
Web Lines Editor

Game Center
	Wolf Pack 43-28-11, 97pts	2	FINAL	3	Checkers 8-68-6, 22pts

Team Stats
OTL1	Streak	L1
23-11-7	Home Record	5-33-3
20-17-4	Away Record	3-35-3
5-1-4	Last 10 Games	1-9-0
3.73	Goals Per Game	3.18
3.33	Goals Against Per Game	6.24
22.63%	Power Play Percentage	19.08%
81.18%	Penalty Kill Percentage	63.29%

Griffins
15-66-1, 31pts

FINAL

Checkers
8-68-6, 22pts

Team Stats
W1	Streak	L1
10-30-1	Home Record	5-33-3
5-36-0	Away Record	3-35-3
2-8-0	Last 10 Games	1-9-0
3.12	Goals Per Game	3.18
6.29	Goals Against Per Game	6.24
15.27%	Power Play Percentage	19.08%
67.42%	Penalty Kill Percentage	63.29%

Team Leaders

Team Stats
Goals For 261 3.18 GFG	Shots For 3311 40.38 Avg	Power Play Percentage 19.1% 33 GF	Offensive Zone Start 36.7%
Goals Against 512 6.24 GAA	Shots Against 4686 57.15 Avg	Penalty Kill Percentage 63.3% 76 GA	Defensive Zone Start 44.9%

Team Info
	General Manager	Félix Fortier
	Coach	Joel Bouchard
	Division	North Division
	Conference	Eastern Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	2,954
	Season Tickets	300
Roster Info
	Pro Team	24
	Farm Team	20
	Contract Limit	44 / 80
	Prospects	42
Team History
	This Season	8-68-6 (22PTS)
	History	46-101-12 (0.289%)
	Playoff Appearances	0
	Playoff Record (W-L)	-
	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	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 Average
1	Thomas Bordeleau (R)	0	X				100.00	59	37	78	68	66	87	83	66	74	64	63	62	71	64	65	0	75	64	0	23	1	950,000$
2	Jake Lucchini	0	X				100.00	61	38	84	63	70	81	87	62	68	60	61	64	62	70	72	0	75	63	0	30	2	950,000$
3	Jesse Ylonen	0			X		100.00	68	38	92	63	79	78	83	62	65	60	58	64	59	66	68	0	75	63	0	26	2	900,000$
4	Nate Danielson (R)	0	X				100.00	68	39	85	66	77	81	73	64	69	62	57	61	59	62	64	0	75	63	0	21	3	950,000$
5	Ryan Suzuki (R)	0	X	X			100.00	67	38	89	65	77	78	83	62	74	63	58	62	61	64	66	0	75	63	0	24	2	800,000$
6	Noah Ostlund (R)	0	X				100.00	57	38	90	65	67	85	69	64	67	59	60	63	66	61	62	0	75	62	0	21	3	950,000$
7	Stefan Matteau	0		X			100.00	73	51	67	58	82	79	64	57	67	60	56	59	57	71	76	0	75	61	0	31	2	950,000$
8	Tyler Madden (R)	0	X				100.00	63	36	93	62	63	81	86	58	68	61	57	54	56	66	68	0	75	61	0	25	1	900,000$
9	Bokondji Imama	0		X			100.00	77	85	54	59	82	67	78	57	53	59	58	56	55	69	70	0	75	61	0	29	2	850,000$
10	Gabriel Szturc (R)	0	X				100.00	62	37	91	59	71	69	70	58	63	57	56	55	54	62	64	0	75	59	0	22	3	950,000$
11	Cale Fleury (R)	0				X	100.00	73	38	92	65	78	81	82	62	30	64	58	66	51	67	69	0	75	64	0	26	2	1,000,000$
12	Ryan Johnson (R)	0				X	100.00	64	37	87	65	76	81	86	64	30	66	58	62	50	64	66	0	75	64	0	24	2	950,000$
13	Wyatt Aamodt	77				X	100.00	74	39	76	62	75	83	84	59	30	56	60	58	55	68	70	0	75	62	0	27	3	950,000$
14	Calen Addison	0				X	100.00	58	40	71	65	67	73	85	63	30	66	54	56	48	65	67	0	75	61	0	25	2	1,405,000$
15	Chase Priskie	0				X	100.00	62	38	84	60	71	74	84	59	30	62	57	58	49	69	71	0	75	61	0	29	1	850,000$
16	Zach Metsa	0				X	100.00	56	36	92	61	66	77	83	60	30	65	55	56	49	67	69	0	75	61	0	26	3	950,000$
17	Cavan Fitzgerald	0				X	100.00	66	39	85	59	75	70	83	56	30	58	57	59	47	69	71	0	75	61	0	29	1	850,000$
18	Ryan Mast (R)	0				X	100.00	85	42	85	52	94	64	67	51	30	53	50	59	45	62	64	0	75	59	0	22	3	950,000$
Scratches
1	Samuel Laberge	0		X			100.00	72	44	59	56	82	67	78	57	54	53	55	58	56	68	70	0	75	59	0	28	1	900,000$
2	Jack Rathbone	0				X	100.00	57	38	82	59	66	84	85	56	30	58	55	54	47	66	68	0	75	59	0	26	2	900,000$
3	Jack Matier (R)	0				X	100.00	84	41	90	53	93	64	70	52	30	54	51	59	45	62	64	0	75	59	0	22	2	950,000$
4	Noah Warren (R)	0				X	100.00	82	42	80	54	91	61	70	53	30	52	50	58	45	61	63	0	75	58	0	21	3	950,000$

	TEAM AVERAGE					100.00	68	41	82	61	76	76	79	59	48	60	57	59	54	66	68	0	75	61

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 Average
1	Oscar Dansk	100.00	72	83	78	84	71	70	72	71	70	72	71	72	85	0	75	65	0	31	1	950,000$
2	Vadim Zherenko	100.00	73	83	79	76	72	71	73	72	71	73	72	64	71	0	75	64	0	24	1	975,000$
Scratches

	TEAM AVERAGE	100.00	73	83	79	80	72	71	73	72	71	73	72	68	78	0	75	65

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Joel Bouchard	66	73	68	70	79	74	74	CAN	51	2	900,000$

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	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	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

#	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	Contract	Type	Current Salary	Salary Average	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Link
Bokondji Imama	Checkers (FLA)	LW	29	1996-08-03	No	221 Lbs	6 ft1	No	No	No	2	Pro & Farm	850,000$	850,000$	0$	0$	No	850,000$		Link / NHL Link
Cale Fleury	Checkers (FLA)	D	26	1998-11-19	Yes	204 Lbs	6 ft1	No	No	No	2	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No	1,000,000$		Link / NHL Link
Calen Addison (1 Way Contract)	Checkers (FLA)	D	25	2000-04-11	No	173 Lbs	5 ft11	No	No	No	2	Pro & Farm	1,405,000$	1,405,000$	1,405,000$	0$	No	1,405,000$		Link / NHL Link
Cavan Fitzgerald	Checkers (FLA)	D	29	1996-08-23	No	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	850,000$	850,000$	0$	0$	No			Link / NHL Link
Chase Priskie	Checkers (FLA)	D	29	1996-03-19	No	185 Lbs	6 ft0	No	No	No	1	Pro & Farm	850,000$	850,000$	0$	0$	No			Link / NHL Link
Gabriel Szturc	Checkers (FLA)	C	22	2003-09-24	Yes	194 Lbs	5 ft11	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Jack Matier	Checkers (FLA)	D	22	2003-04-08	Yes	205 Lbs	6 ft6	No	No	No	2	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$		Link / NHL Link
Jack Rathbone	Checkers (FLA)	D	26	1999-05-20	No	177 Lbs	5 ft10	No	No	No	2	Pro & Farm	900,000$	900,000$	0$	0$	No	900,000$		Link / NHL Link
Jake Lucchini	Checkers (FLA)	C	30	1995-05-09	No	180 Lbs	6 ft0	No	No	No	2	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$		Link / NHL Link
Jesse Ylonen	Checkers (FLA)	RW	26	1999-10-03	No	200 Lbs	6 ft1	No	No	No	2	Pro & Farm	900,000$	900,000$	0$	0$	No	900,000$		Link / NHL Link
Nate Danielson	Checkers (FLA)	C	21	2004-09-27	Yes	185 Lbs	6 ft2	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Noah Ostlund	Checkers (FLA)	C	21	2004-03-11	Yes	175 Lbs	5 ft11	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Noah Warren	Checkers (FLA)	D	21	2004-07-15	Yes	224 Lbs	6 ft4	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Oscar Dansk	Checkers (FLA)	G	31	1994-02-28	No	204 Lbs	6 ft3	No	No	No	1	Pro & Farm	950,000$	950,000$	0$	0$	No			Link / NHL Link
Ryan Johnson	Checkers (FLA)	D	24	2001-07-24	Yes	195 Lbs	6 ft1	No	No	No	2	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$		Link / NHL Link
Ryan Mast	Checkers (FLA)	D	22	2003-01-14	Yes	221 Lbs	6 ft5	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Ryan Suzuki	Checkers (FLA)	C/LW	24	2001-05-28	Yes	196 Lbs	6 ft1	No	No	No	2	Pro & Farm	800,000$	800,000$	0$	0$	No	800,000$		Link / NHL Link
Samuel Laberge	Checkers (FLA)	LW	28	1997-04-10	No	206 Lbs	6 ft2	No	No	No	1	Pro & Farm	900,000$	900,000$	0$	0$	No			Link / NHL Link
Stefan Matteau	Checkers (FLA)	LW	31	1994-02-23	No	208 Lbs	6 ft2	No	No	No	2	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$		Link / NHL Link
Thomas Bordeleau	Checkers (FLA)	C	23	2002-01-03	Yes	180 Lbs	5 ft10	No	No	No	1	Pro & Farm	950,000$	950,000$	0$	0$	No			Link / NHL Link
Tyler Madden	Checkers (FLA)	C	25	1999-11-09	Yes	152 Lbs	5 ft11	No	No	No	1	Pro & Farm	900,000$	900,000$	0$	0$	No			Link / NHL Link
Vadim Zherenko	Checkers (FLA)	G	24	2001-03-15	No	176 Lbs	6 ft2	No	No	No	1	Pro & Farm	975,000$	975,000$	0$	0$	No			Link / NHL Link
Wyatt Aamodt	Checkers (FLA)	D	27	1997-11-22	No	201 Lbs	6 ft0	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Zach Metsa	Checkers (FLA)	D	26	1998-10-19	No	181 Lbs	5 ft9	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
24	25.50	193 Lbs	6 ft1	2.00	945,000$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

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

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

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

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

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

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense

Extra Forwards
Normal	PowerPlay	Penalty Kill
, ,	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

	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	1	0	0	3	8	-5	1	0	1	0	0	0	0	0	2	6	-4	1	0	0	0	0	1	0	0	1	2	-1	1	0.250	3	6	9	0	0	101	91	67	2	80	1110	1050	1130	24	76	33	6	46	2	0	0.00%	4	0	100.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
2	Americans	4	0	3	0	0	1	0	0	12	28	-16	2	0	1	0	0	1	0	0	9	16	-7	2	0	2	0	0	0	0	0	3	12	-9	1	0.125	12	23	35	0	0	101	91	67	2	134	1110	1050	1130	24	217	66	18	91	6	1	16.67%	8	3	62.50%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
3	Barracuda	2	0	2	0	0	0	0	0	7	18	-11	1	0	1	0	0	0	0	0	3	10	-7	1	0	1	0	0	0	0	0	4	8	-4	0	0.000	7	14	21	0	0	101	91	67	2	90	1110	1050	1130	24	127	39	16	50	4	1	25.00%	7	4	42.86%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
4	Bears	3	0	3	0	0	0	0	0	11	19	-8	2	0	2	0	0	0	0	0	8	13	-5	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	11	22	33	1	0	101	91	67	2	93	1110	1050	1130	24	153	34	22	86	3	1	33.33%	11	3	72.73%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
5	Bruins	3	0	3	0	0	0	0	0	6	15	-9	2	0	2	0	0	0	0	0	4	11	-7	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	6	11	17	0	0	101	91	67	2	102	1110	1050	1130	24	181	63	30	67	9	3	33.33%	15	3	80.00%	1	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
6	Comets	2	0	2	0	0	0	0	0	4	16	-12	1	0	1	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	2	10	-8	0	0.000	4	8	12	0	0	101	91	67	2	66	1110	1050	1130	24	138	30	10	58	4	1	25.00%	5	0	100.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
7	Condors	2	0	2	0	0	0	0	0	8	15	-7	1	0	1	0	0	0	0	0	5	7	-2	1	0	1	0	0	0	0	0	3	8	-5	0	0.000	8	14	22	0	0	101	91	67	2	84	1110	1050	1130	24	90	20	10	58	7	1	14.29%	4	2	50.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
8	Crunch	4	1	3	0	0	0	0	0	12	27	-15	2	1	1	0	0	0	0	0	8	7	1	2	0	2	0	0	0	0	0	4	20	-16	2	0.250	12	23	35	0	0	101	91	67	2	133	1110	1050	1130	24	226	66	12	105	13	3	23.08%	6	4	33.33%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
9	Devils	3	0	3	0	0	0	0	0	12	23	-11	1	0	1	0	0	0	0	0	6	8	-2	2	0	2	0	0	0	0	0	6	15	-9	0	0.000	12	24	36	0	0	101	91	67	2	151	1110	1050	1130	24	161	36	15	93	7	1	14.29%	5	3	40.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
10	Eagles	2	0	1	0	0	1	0	0	9	11	-2	1	0	1	0	0	0	0	0	5	6	-1	1	0	0	0	0	1	0	0	4	5	-1	1	0.250	9	17	26	0	0	101	91	67	2	85	1110	1050	1130	24	82	30	8	75	5	1	20.00%	4	1	75.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
11	Firebirds	2	0	2	0	0	0	0	0	6	10	-4	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	4	6	-2	0	0.000	6	12	18	0	0	101	91	67	2	73	1110	1050	1130	24	88	31	6	37	3	0	0.00%	3	1	66.67%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
12	Griffins	4	0	3	0	1	0	0	0	19	25	-6	2	0	2	0	0	0	0	0	7	13	-6	2	0	1	0	1	0	0	0	12	12	0	2	0.250	19	37	56	0	0	101	91	67	2	251	1110	1050	1130	24	287	91	28	139	6	2	33.33%	14	2	85.71%	1	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
13	Gulls	2	0	1	0	0	0	0	1	7	9	-2	1	0	0	0	0	0	0	1	4	5	-1	1	0	1	0	0	0	0	0	3	4	-1	1	0.250	7	13	20	0	0	101	91	67	2	66	1110	1050	1130	24	129	36	8	44	3	0	0.00%	4	0	100.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
14	IceHogs	2	0	2	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	1	4	-3	1	0	1	0	0	0	0	0	3	4	-1	0	0.000	4	8	12	0	0	101	91	67	2	69	1110	1050	1130	24	124	33	10	44	4	1	25.00%	5	2	60.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
15	Marlies	4	1	3	0	0	0	0	0	10	23	-13	2	1	1	0	0	0	0	0	7	9	-2	2	0	2	0	0	0	0	0	3	14	-11	2	0.250	10	20	30	0	0	101	91	67	2	164	1110	1050	1130	24	217	66	18	112	11	2	18.18%	9	3	66.67%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
16	Monsters	3	0	3	0	0	0	0	0	7	19	-12	2	0	2	0	0	0	0	0	4	13	-9	1	0	1	0	0	0	0	0	3	6	-3	0	0.000	7	13	20	0	0	101	91	67	2	92	1110	1050	1130	24	150	54	12	73	4	1	25.00%	7	3	57.14%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
17	Moose	2	0	2	0	0	0	0	0	7	15	-8	1	0	1	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	4	8	-4	0	0.000	7	14	21	0	0	101	91	67	2	77	1110	1050	1130	24	122	41	13	59	5	2	40.00%	4	3	25.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
18	Penguins	3	0	3	0	0	0	0	0	10	21	-11	1	0	1	0	0	0	0	0	2	5	-3	2	0	2	0	0	0	0	0	8	16	-8	0	0.000	10	20	30	0	0	101	91	67	2	120	1110	1050	1130	24	160	60	16	59	10	2	20.00%	8	4	50.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
19	Phantoms	3	0	3	0	0	0	0	0	10	20	-10	2	0	2	0	0	0	0	0	7	15	-8	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	10	19	29	0	0	101	91	67	2	121	1110	1050	1130	24	163	60	18	87	4	1	25.00%	8	7	12.50%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
20	Reign	2	1	1	0	0	0	0	0	6	8	-2	1	0	1	0	0	0	0	0	1	4	-3	1	1	0	0	0	0	0	0	5	4	1	2	0.500	6	11	17	0	0	101	91	67	2	62	1110	1050	1130	24	100	35	16	52	5	0	0.00%	8	3	62.50%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
21	Roadrunners	2	0	2	0	0	0	0	0	6	14	-8	1	0	1	0	0	0	0	0	2	5	-3	1	0	1	0	0	0	0	0	4	9	-5	0	0.000	6	12	18	0	0	101	91	67	2	74	1110	1050	1130	24	124	43	23	54	4	3	75.00%	9	3	66.67%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
22	Rocket	3	0	1	0	1	1	0	0	15	17	-2	1	0	0	0	1	0	0	0	7	6	1	2	0	1	0	0	1	0	0	8	11	-3	3	0.500	15	28	43	0	0	101	91	67	2	210	1110	1050	1130	24	207	61	12	98	5	1	20.00%	6	3	50.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
23	Senators	4	0	4	0	0	0	0	0	6	31	-25	2	0	2	0	0	0	0	0	5	15	-10	2	0	2	0	0	0	0	0	1	16	-15	0	0.000	6	12	18	0	0	101	91	67	2	124	1110	1050	1130	24	217	72	24	92	11	1	9.09%	7	3	57.14%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
24	Silver Knights	2	1	1	0	0	0	0	0	11	10	1	1	0	1	0	0	0	0	0	5	6	-1	1	1	0	0	0	0	0	0	6	4	2	2	0.500	11	21	32	0	0	101	91	67	2	141	1110	1050	1130	24	121	38	8	67	5	1	20.00%	3	0	100.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
25	Sound Tigers	3	0	3	0	0	0	0	0	9	23	-14	1	0	1	0	0	0	0	0	2	9	-7	2	0	2	0	0	0	0	0	7	14	-7	0	0.000	9	18	27	0	0	101	91	67	2	99	1110	1050	1130	24	197	50	20	91	4	1	25.00%	10	4	60.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
26	Stars	2	0	1	0	0	1	0	0	8	10	-2	1	0	0	0	0	1	0	0	6	7	-1	1	0	1	0	0	0	0	0	2	3	-1	1	0.250	8	16	24	0	0	101	91	67	2	93	1110	1050	1130	24	64	27	10	59	5	0	0.00%	4	1	75.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
27	Thunderbirds	2	1	1	0	0	0	0	0	11	11	0	1	1	0	0	0	0	0	0	6	5	1	1	0	1	0	0	0	0	0	5	6	-1	2	0.500	11	21	32	0	0	101	91	67	2	103	1110	1050	1130	24	117	32	8	63	6	0	0.00%	3	1	66.67%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
28	Wild	2	0	2	0	0	0	0	0	4	16	-12	1	0	1	0	0	0	0	0	3	6	-3	1	0	1	0	0	0	0	0	1	10	-9	0	0.000	4	7	11	0	0	101	91	67	2	56	1110	1050	1130	24	146	37	8	56	3	0	0.00%	4	2	50.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
29	Wolf Pack	3	1	2	0	0	0	0	0	9	12	-3	2	1	1	0	0	0	0	0	6	6	0	1	0	1	0	0	0	0	0	3	6	-3	2	0.333	9	18	27	0	0	101	91	67	2	91	1110	1050	1130	24	195	58	14	75	4	0	0.00%	8	2	75.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
30	Wolves	3	0	3	0	0	0	0	0	6	18	-12	1	0	1	0	0	0	0	0	0	7	-7	2	0	2	0	0	0	0	0	6	11	-5	0	0.000	6	12	18	0	0	101	91	67	2	110	1110	1050	1130	24	193	43	16	62	9	2	22.22%	9	5	44.44%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
31	Wranglers	2	0	2	0	0	0	0	0	6	12	-6	1	0	1	0	0	0	0	0	0	4	-4	1	0	1	0	0	0	0	0	6	8	-2	0	0.000	6	11	17	0	0	101	91	67	2	97	1110	1050	1130	24	114	31	15	54	2	0	0.00%	5	1	80.00%	0	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
	Total	82	6	68	0	2	5	0	1	261	512	-251	41	4	33	0	1	2	0	1	132	245	-113	41	2	35	0	1	3	0	0	129	267	-138	22	0.134	261	505	766	1	0	101	91	67	2	3311	1110	1050	1130	24	4686	1416	450	2206	173	33	19.08%	207	76	63.29%	2	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
	_Since Last GM Reset	82	6	68	0	2	5	0	1	261	512	-251	41	4	33	0	1	2	0	1	132	245	-113	41	2	35	0	1	3	0	0	129	267	-138	22	0.134	261	505	766	1	0	101	91	67	2	3311	1110	1050	1130	24	4686	1416	450	2206	173	33	19.08%	207	76	63.29%	2	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
	_Vs Conference	50	3	43	0	2	2	0	0	154	321	-167	25	3	20	0	1	1	0	0	82	153	-71	25	0	23	0	1	1	0	0	72	168	-96	12	0.120	154	300	454	1	0	101	91	67	2	1995	1110	1050	1130	24	2924	880	275	1330	106	22	20.75%	131	52	60.31%	2	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
	_Vs Division	26	2	20	0	2	2	0	0	80	166	-86	13	2	9	0	1	1	0	0	47	77	-30	13	0	11	0	1	1	0	0	33	89	-56	10	0.192	80	154	234	0	0	101	91	67	2	1118	1110	1050	1130	24	1552	485	142	704	61	13	21.31%	65	21	67.69%	2	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
82	22	L1	261	505	766	3311	4686	1416	450	2206	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	6	68	2	5	0	1	261	512

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	4	33	1	2	0	1	132	245

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	2	35	1	3	0	0	129	267

Last 10 Games
W	L	OTW	OTL	SOW	SOL
1	9	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
173	33	19.08%	207	76	63.29%	2

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
1110	1050	1130	24	101	91	67	2

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1380	923	2589	618	971	408

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
1 - 2025-10-07	1	IceHogs	4	Checkers	1	BL			BoxScore
3 - 2025-10-09	12	Phantoms	10	Checkers	4	BL			BoxScore
5 - 2025-10-11	27	Senators	8	Checkers	2	BL			BoxScore
7 - 2025-10-13	44	Checkers	3	Phantoms	5	AL			BoxScore
9 - 2025-10-15	58	Checkers	6	Griffins	7	AL			BoxScore
10 - 2025-10-16	64	Checkers	4	Devils	6	AL			BoxScore
12 - 2025-10-18	76	Checkers	1	Americans	6	AL			BoxScore
15 - 2025-10-21	103	Checkers	2	Bruins	4	AL			BoxScore
17 - 2025-10-23	114	Penguins	5	Checkers	2	BL			BoxScore
19 - 2025-10-25	130	Silver Knights	6	Checkers	5	BL			BoxScore
22 - 2025-10-28	154	Gulls	5	Checkers	4	BL	X	X	BoxScore
26 - 2025-11-01	185	Stars	7	Checkers	6	BL	X		BoxScore
29 - 2025-11-04	211	Checkers	3	Gulls	4	AL			BoxScore
31 - 2025-11-06	226	Checkers	5	Reign	4	AW			BoxScore
33 - 2025-11-08	243	Checkers	4	Barracuda	8	AL			BoxScore
35 - 2025-11-10	255	Checkers	6	Silver Knights	4	AW			BoxScore
38 - 2025-11-13	273	Bears	6	Checkers	4	BL			BoxScore
40 - 2025-11-15	283	Crunch	4	Checkers	2	BL			BoxScore
42 - 2025-11-17	303	Comets	6	Checkers	2	BL			BoxScore
45 - 2025-11-20	322	Devils	8	Checkers	6	BL			BoxScore
47 - 2025-11-22	338	Condors	7	Checkers	5	BL			BoxScore
49 - 2025-11-24	357	Checkers	1	Admirals	2	AL	X		BoxScore
51 - 2025-11-26	363	Phantoms	5	Checkers	3	BL			BoxScore
53 - 2025-11-28	380	Wranglers	4	Checkers	0	BL			BoxScore
57 - 2025-12-02	415	Marlies	5	Checkers	2	BL			BoxScore
59 - 2025-12-04	429	Admirals	6	Checkers	2	BL			BoxScore
61 - 2025-12-06	442	Monsters	6	Checkers	2	BL			BoxScore
62 - 2025-12-07	454	Sound Tigers	9	Checkers	2	BL			BoxScore
65 - 2025-12-10	478	Checkers	4	Roadrunners	9	AL			BoxScore
66 - 2025-12-11	490	Checkers	4	Eagles	5	AL	X		BoxScore
68 - 2025-12-13	505	Checkers	2	Stars	3	AL			BoxScore
70 - 2025-12-15	514	Checkers	4	Crunch	12	AL			BoxScore
72 - 2025-12-17	529	Reign	4	Checkers	1	BL			BoxScore
74 - 2025-12-19	544	Wolves	7	Checkers	0	BL			BoxScore
75 - 2025-12-20	554	Thunderbirds	5	Checkers	6	BW			BoxScore
78 - 2025-12-23	581	Checkers	4	Wolves	7	AL			BoxScore
82 - 2025-12-27	591	Crunch	3	Checkers	6	BW			BoxScore
84 - 2025-12-29	607	Bears	7	Checkers	4	BL			BoxScore
85 - 2025-12-30	618	Rocket	6	Checkers	7	BW	X		BoxScore
88 - 2026-01-02	641	Wolf Pack	4	Checkers	3	BL			BoxScore
90 - 2026-01-04	659	Eagles	6	Checkers	5	BL			BoxScore
92 - 2026-01-06	672	Checkers	2	Marlies	7	AL			BoxScore
94 - 2026-01-08	683	Checkers	5	Rocket	6	AL	X		BoxScore
96 - 2026-01-10	704	Checkers	0	Senators	10	AL			BoxScore
98 - 2026-01-12	716	Checkers	2	Americans	6	AL			BoxScore
102 - 2026-01-16	750	Checkers	2	Wolves	4	AL			BoxScore
103 - 2026-01-17	761	Checkers	3	Bears	6	AL			BoxScore
105 - 2026-01-19	773	Barracuda	10	Checkers	3	BL			BoxScore
108 - 2026-01-22	799	Checkers	4	Moose	8	AL			BoxScore
110 - 2026-01-24	817	Checkers	1	Wild	10	AL			BoxScore
111 - 2026-01-25	823	Checkers	3	IceHogs	4	AL			BoxScore
113 - 2026-01-27	834	Roadrunners	5	Checkers	2	BL			BoxScore
115 - 2026-01-29	852	Checkers	5	Thunderbirds	6	AL			BoxScore
117 - 2026-01-31	862	Moose	7	Checkers	3	BL			BoxScore
119 - 2026-02-02	876	Americans	6	Checkers	5	BL	X		BoxScore
121 - 2026-02-04	893	Bruins	6	Checkers	2	BL			BoxScore
122 - 2026-02-05	908	Checkers	0	Crunch	8	AL			BoxScore
143 - 2026-02-26	921	Marlies	4	Checkers	5	BW			BoxScore
144 - 2026-02-27	930	Americans	10	Checkers	4	BL			BoxScore
146 - 2026-03-01	951	Checkers	2	Sound Tigers	7	AL			BoxScore
148 - 2026-03-03	961	Checkers	2	Devils	9	AL			BoxScore
150 - 2026-03-05	978	Checkers	3	Monsters	6	AL			BoxScore
151 - 2026-03-06	983	Checkers	6	Griffins	5	AW	X		BoxScore
155 - 2026-03-10	1016	Griffins	7	Checkers	5	BL			BoxScore
157 - 2026-03-12	1031	Monsters	7	Checkers	2	BL			BoxScore
160 - 2026-03-15	1062	Checkers	4	Firebirds	6	AL			BoxScore
162 - 2026-03-17	1074	Checkers	2	Comets	10	AL			BoxScore
164 - 2026-03-19	1089	Checkers	3	Condors	8	AL			BoxScore
165 - 2026-03-20	1097	Checkers	6	Wranglers	8	AL			BoxScore
169 - 2026-03-24	1123	Firebirds	4	Checkers	2	BL			BoxScore
171 - 2026-03-26	1140	Wild	6	Checkers	3	BL			BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
173 - 2026-03-28	1153	Checkers	5	Sound Tigers	7	AL			BoxScore
174 - 2026-03-29	1167	Checkers	3	Wolf Pack	6	AL			BoxScore
176 - 2026-03-31	1181	Senators	7	Checkers	3	BL			BoxScore
178 - 2026-04-02	1193	Bruins	5	Checkers	2	BL			BoxScore
180 - 2026-04-04	1211	Checkers	6	Penguins	9	AL			BoxScore
181 - 2026-04-05	1223	Checkers	2	Penguins	7	AL			BoxScore
183 - 2026-04-07	1233	Checkers	3	Rocket	5	AL			BoxScore
185 - 2026-04-09	1250	Checkers	1	Senators	6	AL			BoxScore
187 - 2026-04-11	1270	Checkers	1	Marlies	7	AL			BoxScore
189 - 2026-04-13	1283	Wolf Pack	2	Checkers	3	BW			BoxScore
191 - 2026-04-15	1303	Griffins	6	Checkers	2	BL			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	31	15
Attendance	80,251	40,851
Attendance PCT	97.87%	99.64%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
-31	2954 - 98.46%	94,529$	3,875,683$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
3,113,292$	2,127,500$	2,127,500$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	2,213,211$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
-2,930,394$	0	15,768$	0$

Checkers 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	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Austin Czarnik	82	35	43	78	1	6	71	230	287	12.20%	23	1742	21.25	5	10	15	51	0	0	0	1	6	1	55.89%	1	0.90	0	1
2	Bobby Brink	77	33	38	71	-9	4	44	158	332	9.94%	21	1434	18.62	2	13	15	60	1	0	1	2	3	2	49.13%	1	0.99	0	2
3	Ryan Johnson	81	16	45	61	1	40	89	128	151	10.60%	111	2003	24.73	4	8	12	81	0	0	0	0	4	0	0.00%	0	0.61	0	0
4	Thomas Bordeleau	76	27	31	58	-6	6	74	212	302	8.94%	19	1620	21.33	3	3	6	44	0	1	1	7	2	1	46.16%	0	0.72	1	1
5	Ivan Miroshnichenko	81	19	38	57	-1	20	130	119	202	9.41%	17	1351	16.69	0	1	1	13	0	0	0	1	4	1	40.31%	0	0.84	2	2

Checkers 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	Yaroslav Askarov	82	38	31	11	0.898	3.52	4836	8	2	284	2789	0	1	2	0.615	13
2	Oscar Dansk	4	0	2	0	0.906	2.88	125	0	0	6	64	0	0	0	0.000	0

Checkers 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
2024	82	31	33	0	6	8	1	3	283	295	-12	41	17	17	0	3	2	1	1	146	141	5	41	14	16	0	3	6	0	2	137	154	-17	87	283	511	794	2	2	98	93	85	9	2850	976	912	938	37	2855	788	432	1820	279	43	15.41%	183	37	79.78%	2	1514	2964	51.08%	1527	2978	51.28%	728	1406	51.78%	1930	1330	1965	608	1073	531
2025	82	6	68	0	2	5	0	1	261	512	-251	41	4	33	0	1	2	0	1	132	245	-113	41	2	35	0	1	3	0	0	129	267	-138	22	261	505	766	1	0	101	91	67	2	3311	1110	1050	1130	24	4686	1416	450	2206	173	33	19.08%	207	76	63.29%	2	1047	3005	34.84%	1241	3674	33.78%	462	1504	30.72%	1380	923	2589	618	971	408
Total Regular Season	164	37	101	0	8	13	1	4	544	807	-263	82	21	50	0	4	4	1	2	278	386	-108	82	16	51	0	4	9	0	2	266	421	-155	109	544	1016	1560	3	2	199	184	152	11	6161	2086	1962	2068	61	7541	2204	882	4026	452	76	16.81%	390	113	71.03%	4	2561	5969	42.91%	2768	6652	41.61%	1190	2910	40.89%	3310	2254	4555	1226	2045	939

Checkers Stat Leaders (Play-Off)

Show or Hide Column

#	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

Checkers 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

	Checkers
	GP: 82 \| W: 8 \| L: 68 \| OTL: 6 \| P: 22 GF: 261 \| GA: 512 \| PP%: 19.08% \| PK%: 63.29% GM : Félix Fortier \| Morale : 75 \| Team Overall : 62