Penguins
Home
Roster
Players Stats
Players Info
Lines
Team Stats
Schedule

Game Center
	Marlies 18-18-4, 40pts	2	Box score	5	Penguins 19-16-5, 43pts

Team Stats
L2	Streak	W2
9-9-2	Home Record	11-7-2
9-9-2	Home Record	8-9-3
3-6-1	Last 10 Games	5-4-1
2.03	Goals Per Game	1.78
1.95	Goals Against Per Game	1.88
26.90%	Power Play Percentage	19.32%
75.00%	Penalty Kill Percentage	75.54%

Bears
21-17-2, 44pts

Box score

Penguins
19-16-5, 43pts

Team Stats
L1	Streak	W2
9-9-2	Home Record	11-7-2
12-8-0	Home Record	8-9-3
3-6-1	Last 10 Games	5-4-1
1.83	Goals Per Game	1.78
1.88	Goals Against Per Game	1.88
24.62%	Power Play Percentage	19.32%
73.62%	Penalty Kill Percentage	75.54%

Team Leaders

Team Stats
Goals For 71 1.78 GFG	Shots For 654 16.35 Avg	Power Play Percentage 19.3% 34 GF	Offensive Zone Start 33.9%
Goals Against 75 1.88 GAA	Shots Against 679 16.98 Avg	Penalty Kill Percentage 75.5%% 45 GA	Defensive Zone Start 34.4%

Team Info
	General Manager	Maxime Dube Gagne
	Division	Atlantique
	Conference	Conference Est
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	8,000
	Attendance	0
	Season Tickets	1,600
Roster Info
	Pro Team	1
	Farm Team	23
	Contract Limit	24 / 250
	Prospects	51

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	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
Scratches
1	Josh Dunne (R)	0	X	100.00	82	83	80	68	83	80	86	57	71	55	54	67	51	45	45	62	20	70	0	25	2	775,000$

	TEAM AVERAGE			100.00	82	83	80	68	83	80	86	57	71	55	54	67	51	45	45	62	20	70

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
Scratches

	TEAM AVERAGE	0.00	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary

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

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	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

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	Last Trade Date	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Remaining	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
Josh Dunne	Penguins (PIT)	C	25	1998-12-08	USA	Yes	211 Lbs	6 ft4	No	No	N/A		No	Yes	2		False	False	Pro & Farm	775,000$		0$	0$	No	775,000$	-	-	-	-	-	-	-	-	775,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
1	25.00	211 Lbs	6 ft4	2.00	775,000$

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 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	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	4	6	0	0	10	23	34	4	22	136	219	288	11	19	7	11	8	6	2	33.33%	3	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
2	Americans	1	1	0	0	0	0	0	0	3	0	3	1	1	0	0	0	0	0	0	3	0	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	6	9	0	1	10	23	34	4	16	136	219	288	11	13	6	29	7	7	2	28.57%	2	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
3	Barracuda	1	0	1	0	0	0	0	0	1	3	-2	1	0	1	0	0	0	0	0	1	3	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	10	23	34	4	13	136	219	288	11	21	9	64	6	6	1	16.67%	6	3	50.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
4	Bears	2	1	0	0	1	0	0	0	3	1	2	1	1	0	0	0	0	0	0	1	0	1	1	0	0	0	1	0	0	0	2	1	1	4	1.000	3	6	9	0	1	10	23	34	4	27	136	219	288	11	36	8	33	17	10	2	20.00%	9	1	88.89%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
5	Bruins	2	0	1	0	1	0	0	0	3	3	0	1	0	0	0	1	0	0	0	2	1	1	1	0	1	0	0	0	0	0	1	2	-1	2	0.500	3	6	9	0	0	10	23	34	4	40	136	219	288	11	33	10	36	18	9	1	11.11%	8	2	75.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
6	Checkers	2	1	0	0	0	1	0	0	3	3	0	1	1	0	0	0	0	0	0	2	1	1	1	0	0	0	0	1	0	0	1	2	-1	3	0.750	3	6	9	0	0	10	23	34	4	25	136	219	288	11	31	10	172	16	8	1	12.50%	11	2	81.82%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
7	Comets	1	0	0	0	0	1	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	1	0	0	3	4	-1	1	0.500	3	6	9	0	0	10	23	34	4	22	136	219	288	11	19	10	13	8	5	1	20.00%	4	1	75.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
8	Condors	2	0	2	0	0	0	0	0	0	3	-3	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	3	-3	0	0.000	0	0	0	0	0	10	23	34	4	9	136	219	288	11	35	11	57	21	4	0	0.00%	11	2	81.82%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
9	Crunch	1	0	1	0	0	0	0	0	0	1	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	1	-1	0	0.000	0	0	0	0	0	10	23	34	4	15	136	219	288	11	14	6	45	6	4	0	0.00%	5	1	80.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
10	Devils	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	2	4	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	10	23	34	4	14	136	219	288	11	14	3	17	9	6	2	33.33%	6	2	66.67%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
11	Eagles	1	0	1	0	0	0	0	0	0	4	-4	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	4	-4	0	0.000	0	0	0	0	0	10	23	34	4	15	136	219	288	11	12	7	76	16	4	0	0.00%	3	2	33.33%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
12	Griffins	2	0	0	0	0	2	0	0	2	4	-2	1	0	0	0	0	1	0	0	1	2	-1	1	0	0	0	0	1	0	0	1	2	-1	2	0.500	2	4	6	0	0	10	23	34	4	23	136	219	288	11	34	15	39	23	10	1	10.00%	7	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
13	Gulls	1	0	0	0	1	0	0	0	2	1	1	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	2	4	0	0	10	23	34	4	15	136	219	288	11	17	4	6	10	0	0	0%	3	1	66.67%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
14	Heat	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	1	2	2	1.000	3	6	9	0	0	10	23	34	4	18	136	219	288	11	14	4	16	12	2	1	50.00%	3	1	66.67%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
15	Hockey Club	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	6	9	0	0	10	23	34	4	19	136	219	288	11	15	3	17	13	4	2	50.00%	6	1	83.33%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
16	IceHogs	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	3	1	2	1.000	4	8	12	0	0	10	23	34	4	18	136	219	288	11	26	6	55	11	8	3	37.50%	5	3	40.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
17	Marlies	1	1	0	0	0	0	0	0	5	2	3	1	1	0	0	0	0	0	0	5	2	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	5	10	15	0	0	10	23	34	4	26	136	219	288	11	15	2	91	2	6	2	33.33%	8	2	75.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
18	Monsters	1	1	0	0	0	0	0	0	3	2	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	3	2	1	2	1.000	3	4	7	0	0	10	23	34	4	19	136	219	288	11	23	7	6	9	3	1	33.33%	3	1	66.67%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
19	Moose	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	10	23	34	4	14	136	219	288	11	21	7	35	7	6	1	16.67%	5	2	60.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
20	Phantoms	2	1	0	0	0	1	0	0	5	2	3	1	0	0	0	0	1	0	0	1	2	-1	1	1	0	0	0	0	0	0	4	0	4	3	0.750	5	9	14	0	1	10	23	34	4	40	136	219	288	11	36	7	51	18	9	1	11.11%	8	1	87.50%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
21	Rampage	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	3	4	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	10	23	34	4	21	136	219	288	11	33	8	13	14	7	2	28.57%	4	2	50.00%	1	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
22	Reign	1	0	0	0	1	0	0	0	2	1	1	1	0	0	0	1	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	4	6	0	0	10	23	34	4	17	136	219	288	11	18	3	22	14	3	1	33.33%	6	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
23	Rocket	1	1	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	1	0	1	2	1.000	1	2	3	0	1	10	23	34	4	18	136	219	288	11	10	1	12	7	3	0	0.00%	1	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
24	Sagnéens	1	1	0	0	0	0	0	0	2	0	2	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	2	0	2	2	1.000	2	4	6	0	1	10	23	34	4	22	136	219	288	11	8	2	6	11	7	0	0.00%	3	0	100.00%	1	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
25	Senators	1	0	1	0	0	0	0	0	0	4	-4	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	4	-4	0	0.000	0	0	0	0	0	10	23	34	4	14	136	219	288	11	13	3	21	6	3	0	0.00%	8	4	50.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
26	Sound Tigers	2	1	1	0	0	0	0	0	3	3	0	1	0	1	0	0	0	0	0	0	1	-1	1	1	0	0	0	0	0	0	3	2	1	2	0.500	3	5	8	0	0	10	23	34	4	23	136	219	288	11	30	7	32	19	6	1	16.67%	11	1	90.91%	2	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
27	Stars	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	3	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	2	4	6	0	0	10	23	34	4	19	136	219	288	11	20	5	9	9	5	1	20.00%	2	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
28	Thunderbirds	2	1	1	0	0	0	0	0	3	4	-1	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	0	2	-2	2	0.500	3	6	9	0	0	10	23	34	4	35	136	219	288	11	27	6	29	20	9	2	22.22%	12	4	66.67%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
29	Wild	1	0	1	0	0	0	0	0	0	1	-1	1	0	1	0	0	0	0	0	0	1	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	10	23	34	4	13	136	219	288	11	15	4	9	11	4	0	0.00%	2	0	100.00%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
30	Wolf Pack	2	1	1	0	0	0	0	0	7	7	0	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	4	5	-1	2	0.500	7	14	21	0	0	10	23	34	4	50	136	219	288	11	44	15	149	18	10	3	30.00%	12	4	66.67%	1	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
31	Wolves	1	0	1	0	0	0	0	0	0	2	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	2	-2	0	0.000	0	0	0	0	0	10	23	34	4	12	136	219	288	11	13	3	19	13	2	0	0.00%	7	2	71.43%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
	Total	40	15	16	0	4	5	0	0	71	75	-4	20	8	7	0	3	2	0	0	39	35	4	20	7	9	0	1	3	0	0	32	40	-8	43	0.538	71	136	207	0	5	10	23	34	4	654	136	219	288	11	679	199	1190	379	176	34	19.32%	184	45	75.54%	5	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
	_Since Last GM Reset	40	15	16	0	4	5	0	0	71	75	-4	20	8	7	0	3	2	0	0	39	35	4	20	7	9	0	1	3	0	0	32	40	-8	43	0.538	71	136	207	0	5	10	23	34	4	654	136	219	288	11	679	199	1190	379	176	34	19.32%	184	45	75.54%	5	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
	_Vs Conference	22	10	7	0	2	3	0	0	44	40	4	10	6	2	0	1	1	0	0	22	15	7	12	4	5	0	1	2	0	0	22	25	-3	27	0.614	44	84	128	0	4	10	23	34	4	384	136	219	288	11	358	101	736	180	98	19	19.39%	108	26	75.93%	3	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249
	_Vs Division	11	6	4	0	2	2	0	0	17	18	-1	5	4	1	0	1	1	0	0	14	7	7	6	2	3	0	1	1	0	0	3	11	-8	18	0.818	17	34	51	0	2	10	23	34	4	187	136	219	288	11	159	49	302	89	51	8	15.69%	51	13	74.51%	0	291	570	51.05%	297	579	51.30%	271	534	50.75%	1012	723	916	283	493	249

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
40	43	W2	71	136	207	654	679	199	1190	379	0	5

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
40	15	16	4	5	0	0	71	75

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
20	8	7	3	2	0	0	39	35

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
20	7	9	1	3	0	0	32	40

Last 10 Games
W	L	OTW	OTL	SOW	SOL
5	4	0	1	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
176	34	19.32%	184	45	75.54%	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
136	219	288	11	10	23	34	4

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
291	570	51.05%	297	579	51.30%	271	534	50.75%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1012	723	916	283	493	249

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	Link
1 - 2025-10-05	5	Penguins	0	Condors	2	L		Box score
2 - 2025-10-06	29	Barracuda	3	Penguins	1	L		Box score
4 - 2025-10-08	38	Admirals	1	Penguins	2	W		Box score
5 - 2025-10-09	57	Penguins	3	Heat	1	W		Box score
6 - 2025-10-10	70	Penguins	4	Wolf Pack	5	L		Box score
7 - 2025-10-11	82	Penguins	1	Checkers	2	L	X	Box score
9 - 2025-10-13	97	Checkers	1	Penguins	2	W		Box score
11 - 2025-10-15	115	Rampage	4	Penguins	3	L		Box score
12 - 2025-10-16	139	Penguins	3	Comets	4	L	X	Box score
14 - 2025-10-18	153	Bruins	1	Penguins	2	W	X	Box score
16 - 2025-10-20	166	Reign	1	Penguins	2	W	X	Box score
17 - 2025-10-21	179	Penguins	1	Griffins	2	L	X	Box score
18 - 2025-10-22	201	Moose	2	Penguins	1	L		Box score
19 - 2025-10-23	221	Thunderbirds	2	Penguins	3	W		Box score
20 - 2025-10-24	236	Penguins	3	Monsters	2	W		Box score
21 - 2025-10-25	247	Penguins	4	IceHogs	3	W		Box score
23 - 2025-10-27	265	Penguins	4	Phantoms	0	W		Box score
25 - 2025-10-29	274	Penguins	0	Senators	4	L		Box score
26 - 2025-10-30	285	Hockey Club	2	Penguins	3	W		Box score
27 - 2025-10-31	303	Americans	0	Penguins	3	W		Box score
28 - 2025-11-01	321	Penguins	3	Sound Tigers	2	W		Box score
29 - 2025-11-02	341	Wild	1	Penguins	0	L		Box score
30 - 2025-11-03	355	Penguins	0	Wolves	2	L		Box score
32 - 2025-11-05	375	Stars	3	Penguins	2	L		Box score
33 - 2025-11-06	388	Penguins	2	Sagnéens	0	W		Box score
34 - 2025-11-07	405	Sound Tigers	1	Penguins	0	L		Box score
35 - 2025-11-08	410	Penguins	0	Thunderbirds	2	L		Box score
36 - 2025-11-09	431	Phantoms	2	Penguins	1	L	X	Box score
38 - 2025-11-11	457	Penguins	0	Condors	1	L		Box score
39 - 2025-11-12	469	Gulls	1	Penguins	2	W	X	Box score
40 - 2025-11-13	488	Wolf Pack	2	Penguins	3	W		Box score
41 - 2025-11-14	499	Penguins	0	Eagles	4	L		Box score
42 - 2025-11-15	508	Penguins	1	Bruins	2	L		Box score
43 - 2025-11-16	526	Penguins	1	Rocket	0	W		Box score
44 - 2025-11-17	542	Devils	4	Penguins	2	L		Box score
46 - 2025-11-19	562	Griffins	2	Penguins	1	L	X	Box score
49 - 2025-11-22	587	Penguins	2	Bears	1	W	X	Box score
50 - 2025-11-23	593	Penguins	0	Crunch	1	L		Box score
51 - 2025-11-24	607	Marlies	2	Penguins	5	W		Box score
54 - 2025-11-27	637	Bears	0	Penguins	1	W		Box score

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	5000	3000
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
0	0 - 0.00%	0$	0$	8000	110

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
775,005$	775,000$	775,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	775,005$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	14,091$	0$

Penguins 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

Penguins 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

Penguins 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

Penguins 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

Penguins 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

	Penguins
	GP: 40 \| W: 19 \| L: 16 \| OTL: 5 \| P: 43 GF: 71 \| GA: 75 \| PP%: 19.32% \| PK%: 75.54% GM : Maxime Dube Gagne \| Morale : 66 \| Team Overall : 70