Nashville Predators
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance

Game Center
	Milwaukee Admirals 3-1-0, 6pts	8	FINAL	4	Providence Bruins 1-2-1, 3pts

Team Stats
L1	Streak	L2
1-1-0	Home Record	0-1-1
2-0-0	Away Record	1-1-0
3-1-0	Last 10 Games	1-2-1
5.50	Goals Per Game	3.00
4.25	Goals Against Per Game	4.25
10.00%	Power Play Percentage	42.86%
85.71%	Penalty Kill Percentage	77.78%

Lehigh Valley Phantoms
2-2-0, 4pts

FINAL

Milwaukee Admirals
3-1-0, 6pts

Team Stats
W2	Streak	L1
1-1-0	Home Record	1-1-0
1-1-0	Away Record	2-0-0
2-2-0	Last 10 Games	3-1-0
5.00	Goals Per Game	5.50
4.25	Goals Against Per Game	4.25
16.67%	Power Play Percentage	10.00%
66.67%	Penalty Kill Percentage	85.71%

Milwaukee Admirals
3-1-0, 6pts

2023-09-20

Toronto Marlies
1-3-0, 2pts

Team Stats
L1	Streak	L1
1-1-0	Home Record	1-1-0
2-0-0	Away Record	0-2-0
3-1-0	Last 10 Games	1-3-0
5.50	Goals Per Game	3.00
4.25	Goals Against Per Game	3.00
10.00%	Power Play Percentage	12.50%
85.71%	Penalty Kill Percentage	85.71%

Cleveland Monsters
2-1-1, 5pts

2023-09-21

Milwaukee Admirals
3-1-0, 6pts

Team Stats
OTL1	Streak	L1
2-0-0	Home Record	1-1-0
0-1-1	Away Record	2-0-0
2-1-1	Last 10 Games	3-1-0
2.75	Goals Per Game	5.50
2.50	Goals Against Per Game	5.50
12.50%	Power Play Percentage	10.00%
87.50%	Penalty Kill Percentage	85.71%

Milwaukee Admirals
3-1-0, 6pts

2023-09-22

Bridgeport Islanders
1-3-0, 2pts

Team Stats
L1	Streak	L3
1-1-0	Home Record	1-1-0
2-0-0	Away Record	0-2-0
3-1-0	Last 10 Games	1-3-0
5.50	Goals Per Game	2.50
4.25	Goals Against Per Game	2.50
10.00%	Power Play Percentage	0.00%
85.71%	Penalty Kill Percentage	75.00%

Team Leaders
	Goals Joshua Ho-Sang 3	Assists Jack Finley 4

	Points Joshua Ho-Sang 6	Plus/Minus Jack Finley 7

	Wins Michael McNiven 3	Save Percentage Michael McNiven 0.894

Team Stats
Goals For 22 5.50 GFG	Shots For 221 55.25 Avg	Power Play Percentage 10.0% 1 GF	Offensive Zone Start 49.4%
Goals Against 17 4.25 GAA	Shots Against 152 38.00 Avg	Penalty Kill Percentage 85.7%% 1 GA	Defensive Zone Start 31.6%

Team Info
	General Manager	Matt Sullivan
	Coach	Greg Johnson
	Division	Central
	Conference	Western Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	8,000
	Attendance	0
	Season Tickets	0
Roster Info
	Pro Team	16
	Farm Team	21
	Contract Limit	37 / 45
	Prospects	2

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
1	Colin White	11	X				100.00	72	40	89	65	75	62	75	61	68	72	63	70	54	63	67	0	60	67	0	26	1	1,200,000$
2	Zack Kassian	19		X			100.00	73	69	82	61	81	59	76	58	53	68	60	67	56	75	60	0	60	65	0	32	2	3,200,000$
3	Rocco Grimaldi	25	X		X		100.00	55	61	66	64	56	66	65	65	55	61	65	61	57	69	61	0	60	63	0	30	1	750,000$
4	Matthew Phillips	24	X				100.00	54	59	67	64	54	67	64	65	55	61	66	64	59	60	56	0	60	63	0	25	1	750,000$
5	Kevin Rooney	15	X	X			100.00	63	53	77	61	70	64	71	57	69	61	58	66	54	65	59	0	60	62	0	30	2	1,300,000$
6	Joshua Ho-Sang	23			X		100.00	53	39	89	64	69	72	71	63	59	60	56	58	63	67	64	0	60	62	0	27	3	750,000$
7	Chris Wagner	64	X		X		100.00	56	56	64	63	64	66	65	59	70	56	60	60	54	72	63	0	60	61	0	32	1	1,350,000$
8	Jasper Weatherby	70	X	X			100.00	59	51	70	62	76	66	66	58	62	60	58	62	54	60	57	0	60	61	0	25	1	750,000$
9	Cedric Paquette	14	X				100.00	71	38	79	54	77	53	67	51	46	63	52	67	51	65	56	0	60	59	0	30	1	750,000$
10	Jack Finley	63	X				100.00	55	55	61	57	67	63	62	56	65	55	58	59	54	54	53	0	60	58	0	21	1	750,000$
11	Ryan Greene (R)	75	X				100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	19	4	750,000$
12	Alexander Suzdalev (R)	76		X			100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	19	4	750,000$
13	Colton White	71				X	100.00	64	41	86	58	70	68	65	56	40	69	56	81	54	56	58	0	60	65	0	26	2	762,500$
14	Benjamin Roger (R)	80				X	100.00	45	45	45	45	45	45	45	45	45	45	45	45	45	45	45	0	60	45	0	20	4	750,000$
Scratches

	TEAM AVERAGE						100.00	58	50	69	58	64	60	63	56	56	59	56	61	53	60	56	0	60	59

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	Evan Fitzpatrick	33	100.00	54	54	54	69	64	54	66	54	58	55	65	60	55	0	60	58	0	25	1	750,000$
Scratches
1	Michael McNiven	1	94.00	53	54	54	58	59	54	60	54	58	56	63	59	53	0	60	56	0	26	1	750,000$

	TEAM AVERAGE		97.00	54	54	54	64	62	54	63	54	58	56	64	60	54	0	60	57

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Greg Johnson	75	75	75	75	75	75	75	CAN	52	5	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	Team Name	POS	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKS	PKM	GW	FO%	FOT	P/20	S1	S2	S3
1	Joshua Ho-Sang	Milwaukee Admirals (NSH)	RW	4	3	3	6	-3	0	1	6	17	6	12	17.65%	0	72	18.12	1	0	1	6	9	0	0	0	71.43%	7	1.66	1	0	1
2	Kevin Rooney	Milwaukee Admirals (NSH)	C/LW	4	2	3	5	-3	2	7	18	24	5	5	8.33%	2	77	19.39	0	1	1	3	9	0	5	0	66.67%	132	1.29	0	0	1
3	Jack Finley	Milwaukee Admirals (NSH)	C	4	1	4	5	7	2	4	5	10	3	12	10.00%	4	33	8.38	0	0	0	0	0	0	0	0	63.41%	41	2.98	0	2	0
4	Chris Wagner	Milwaukee Admirals (NSH)	C/RW	4	2	2	4	1	0	6	18	20	4	18	10.00%	0	70	17.55	0	0	0	2	7	0	0	0	100.00%	3	1.14	0	0	1
5	Cedric Paquette	Milwaukee Admirals (NSH)	C	4	2	2	4	2	2	7	8	24	7	14	8.33%	6	73	18.30	0	0	0	3	7	2	3	1	48.94%	94	1.09	1	0	0
6	Jasper Weatherby	Milwaukee Admirals (NSH)	C/LW	4	1	3	4	-3	0	8	8	23	3	16	4.35%	2	78	19.69	0	0	0	6	9	0	6	0	80.00%	10	1.02	0	1	0
7	Rocco Grimaldi	Milwaukee Admirals (NSH)	C/RW	4	0	2	2	-1	2	6	9	17	6	11	0.00%	1	54	13.64	0	0	0	0	0	0	4	0	33.33%	6	0.73	0	0	0
8	Matthew Phillips	Milwaukee Admirals (NSH)	C	4	1	0	1	-1	2	6	10	20	7	15	5.00%	1	50	12.70	0	0	0	0	0	0	0	1	51.85%	81	0.39	0	0	0
9	Benjamin Roger	Milwaukee Admirals (NSH)	D	4	0	0	0	-3	0	6	0	2	1	1	0.00%	4	52	13.20	0	0	0	0	0	0	0	0	0.00%	0	0.00%	0	0	0
10	Ryan Greene	Milwaukee Admirals (NSH)	C	4	0	0	0	0	0	0	0	0	0	0	0.00%	0	1	0.28	0	0	0	0	0	0	0	0	25.00%	4	0.00%	0	0	0
11	Alexander Suzdalev	Milwaukee Admirals (NSH)	LW	4	0	0	0	-1	2	6	0	0	1	3	0.00%	0	52	13.02	0	0	0	0	0	0	1	0	25.00%	4	0.00%	0	0	0
Team Total or Average				44	12	19	31	-5	12	57	82	157	43	107	7.64%	20	617	14.02	1	1	2	20	44	2	21	2	58.12%	382	1.00	2	3	3

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
1	Michael McNiven	Milwaukee Admirals (NSH)	4	3	1	0	0.894	4.02	239	0	0	16	151	0	0	1	0.00%	0	4	4	0	0	0
Team Total or Average			4	3	1	0	0.894	4.02	239	0	0	16	151	0	0	1		0	4	4	0	0	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	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	Link
Alexander Suzdalev	Milwaukee Admirals (NSH)	LW	19	3/5/2004 4:59:38 AM	Yes	176 Lbs	6 ft2	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Benjamin Roger	Milwaukee Admirals (NSH)	D	20	11/3/2002 2:43:22 AM	Yes	201 Lbs	6 ft3	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Cedric Paquette	Milwaukee Admirals (NSH)	C	30	8/13/1993	No	205 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Chris Wagner	Milwaukee Admirals (NSH)	C/RW	32	5/27/1991	No	192 Lbs	6 ft0	No	No	No	No	1	Pro & Farm	1,350,000$	0$	0$	No				Link
Colin White	Milwaukee Admirals (NSH)	C	26	1/30/1997	No	194 Lbs	6 ft1	No	No	No	No	1	Pro & Farm	1,200,000$	0$	0$	No				Link
Colton White	Milwaukee Admirals (NSH)	D	26	5/3/1997	No	187 Lbs	6 ft1	No	No	No	No	2	Pro & Farm	762,500$	0$	0$	No	762,500$			Link
Evan Fitzpatrick	Milwaukee Admirals (NSH)	G	25	1/28/1998	No	205 Lbs	6 ft3	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Jack Finley	Milwaukee Admirals (NSH)	C	21	9/2/2002	No	223 Lbs	6 ft6	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Jasper Weatherby	Milwaukee Admirals (NSH)	C/LW	25	1/22/1998	No	223 Lbs	6 ft4	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Joshua Ho-Sang	Milwaukee Admirals (NSH)	RW	27	1/22/1996	No	173 Lbs	6 ft0	No	No	No	No	3	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$		Link
Kevin Rooney	Milwaukee Admirals (NSH)	C/LW	30	5/21/1993	No	190 Lbs	6 ft2	No	No	No	No	2	Pro & Farm	1,300,000$	0$	0$	No	1,300,000$			Link
Matthew Phillips	Milwaukee Admirals (NSH)	C	25	4/6/1998	No	140 Lbs	5 ft7	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Michael McNiven (Out of Payroll)	Milwaukee Admirals (NSH)	G	26	7/9/1997	No	198 Lbs	6 ft1	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Rocco Grimaldi	Milwaukee Admirals (NSH)	C/RW	30	2/8/1993	No	179 Lbs	5 ft6	No	No	No	No	1	Pro & Farm	750,000$	0$	0$	No				Link
Ryan Greene	Milwaukee Admirals (NSH)	C	19	10/21/2003 8:13:16 AM	Yes	174 Lbs	6 ft1	No	No	No	No	4	Pro & Farm	750,000$	0$	0$	No	750,000$	750,000$	750,000$
Zack Kassian (1 Way Contract)	Milwaukee Admirals (NSH)	LW	32	1/24/1991	No	211 Lbs	6 ft3	No	No	No	No	2	Pro & Farm	3,200,000$	3,200,000$	3,200,000$	No	3,200,000$			Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
16	25.81	192 Lbs	6 ft1	1.88	1,003,906$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jasper Weatherby	Kevin Rooney	Joshua Ho-Sang	30	1	2	2
2		Cedric Paquette	Chris Wagner	30	1	2	2
3	Alexander Suzdalev	Matthew Phillips	Rocco Grimaldi	25	1	2	2
4		Jack Finley		15	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			30	1	2	2
2			30	1	2	2
3	Benjamin Roger		25	1	2	2
4			15	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jasper Weatherby	Kevin Rooney	Joshua Ho-Sang	60	1	2	2
2		Cedric Paquette	Chris Wagner	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	Kevin Rooney	Jasper Weatherby	60	1	2	2
2		Cedric Paquette	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	Kevin Rooney	60	1	2	2			60	1	2	2
2	Jasper Weatherby	40	1	2	2			40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Kevin Rooney	Jasper Weatherby	60	1	2	2
2		Cedric Paquette	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
Jasper Weatherby	Kevin Rooney	Joshua Ho-Sang

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jasper Weatherby	Kevin Rooney	Joshua Ho-Sang

Extra Forwards
Normal	PowerPlay	Penalty Kill
Ryan Greene, Matthew Phillips, Rocco Grimaldi	Ryan Greene, Matthew Phillips	Rocco Grimaldi

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Benjamin Roger, ,	Benjamin Roger	,

Penalty Shots
Kevin Rooney, Jasper Weatherby, , Cedric Paquette, Joshua Ho-Sang

Goalie
#1 : , #2 :

Custom OT Lines Forwards
Kevin Rooney, Jasper Weatherby, , Cedric Paquette, Joshua Ho-Sang, Matthew Phillips, Matthew Phillips, Chris Wagner, Rocco Grimaldi, Alexander Suzdalev, Jack Finley

Custom OT Lines Defensemen
, , , , Benjamin Roger

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	Belleville Senators	2	2	0	0	0	0	0	0	9	6	3	1	1	0	0	0	0	0	0	5	4	1	1	1	0	0	0	0	0	0	4	2	2	4	1.000	9	17	26	0	0	10	7	5	0	102	69	78	74	0	67	26	6	54	4	0	0.00%	3	1	66.67%	0	110	195	56.41%	75	125	60.00%	44	75	58.67%	104	75	85	26	50	25
2	Lehigh Valley Phantoms	1	0	1	0	0	0	0	0	5	7	-2	1	0	1	0	0	0	0	0	5	7	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	5	9	14	1	0	10	7	5	0	47	69	78	74	0	52	12	6	21	1	0	0.00%	3	0	100.00%	1	110	195	56.41%	75	125	60.00%	44	75	58.67%	104	75	85	26	50	25
3	Providence Bruins	1	1	0	0	0	0	0	0	8	4	4	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	8	4	4	2	1.000	8	14	22	0	0	10	7	5	0	72	69	78	74	0	33	13	2	16	5	1	20.00%	1	0	100.00%	0	110	195	56.41%	75	125	60.00%	44	75	58.67%	104	75	85	26	50	25
	Total	4	3	1	0	0	0	0	0	22	17	5	2	1	1	0	0	0	0	0	10	11	-1	2	2	0	0	0	0	0	0	12	6	6	6	0.750	22	40	62	1	0	10	7	5	0	221	69	78	74	0	152	51	14	91	10	1	10.00%	7	1	85.71%	1	110	195	56.41%	75	125	60.00%	44	75	58.67%	104	75	85	26	50	25
	_Since Last GM Reset	4	3	1	0	0	0	0	0	22	17	5	2	1	1	0	0	0	0	0	10	11	-1	2	2	0	0	0	0	0	0	12	6	6	6	0.750	22	40	62	1	0	10	7	5	0	221	69	78	74	0	152	51	14	91	10	1	10.00%	7	1	85.71%	1	110	195	56.41%	75	125	60.00%	44	75	58.67%	104	75	85	26	50	25

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
4	6	L1	22	40	62	221	152	51	14	91	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
4	3	1	0	0	0	0	22	17

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	1	1	0	0	0	0	10	11

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
2	2	0	0	0	0	0	12	6

Last 10 Games
W	L	OTW	OTL	SOW	SOL
3	1	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
10	1	10.00%	7	1	85.71%	1

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
69	78	74	0	10	7	5	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
110	195	56.41%	75	125	60.00%	44	75	58.67%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
104	75	85	26	50	25

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 - 2023-09-15	14	Milwaukee Admirals	4	Belleville Senators	2	AW	BoxScore
2 - 2023-09-16	28	Belleville Senators	4	Milwaukee Admirals	5	BW	BoxScore
4 - 2023-09-18	37	Milwaukee Admirals	8	Providence Bruins	4	AW	BoxScore
5 - 2023-09-19	61	Lehigh Valley Phantoms	7	Milwaukee Admirals	5	BL	BoxScore
6 - 2023-09-20	68	Milwaukee Admirals	-	Toronto Marlies	-
7 - 2023-09-21	84	Cleveland Monsters	-	Milwaukee Admirals	-
8 - 2023-09-22	109	Milwaukee Admirals	-	Bridgeport Islanders	-
9 - 2023-09-23	123	Hershey Bears	-	Milwaukee Admirals	-
11 - 2023-09-25	132	Milwaukee Admirals	-	Cleveland Monsters	-
13 - 2023-09-27	148	Utica Comets	-	Milwaukee Admirals	-
15 - 2023-09-29	165	Milwaukee Admirals	-	Hershey Bears	-
17 - 2023-10-01	188	Syracuse Crunch	-	Milwaukee Admirals	-
19 - 2023-10-03	197	Toronto Marlies	-	Milwaukee Admirals	-
22 - 2023-10-06	221	Milwaukee Admirals	-	Springfield Thunderbirds	-
23 - 2023-10-07	231	Milwaukee Admirals	-	Laval Rocket	-
24 - 2023-10-08	244	Milwaukee Admirals	-	Abbotsford Canucks	-
25 - 2023-10-09	258	Providence Bruins	-	Milwaukee Admirals	-
26 - 2023-10-10	276	Wilkes-Barre/Scranton Penguins	-	Milwaukee Admirals	-
27 - 2023-10-11	298	Milwaukee Admirals	-	Utica Comets	-
28 - 2023-10-12	312	Rochester Americans	-	Milwaukee Admirals	-
30 - 2023-10-14	325	Milwaukee Admirals	-	Charlotte Checkers	-
31 - 2023-10-15	340	Bridgeport Islanders	-	Milwaukee Admirals	-
32 - 2023-10-16	355	Milwaukee Admirals	-	Rochester Americans	-
34 - 2023-10-18	369	Milwaukee Admirals	-	Syracuse Crunch	-
35 - 2023-10-19	383	Charlotte Checkers	-	Milwaukee Admirals	-
36 - 2023-10-20	404	Milwaukee Admirals	-	Wilkes-Barre/Scranton Penguins	-
Trade Deadline --- Trades can’t be done after this day is simulated!
37 - 2023-10-21	411	Springfield Thunderbirds	-	Milwaukee Admirals	-
38 - 2023-10-22	433	Milwaukee Admirals	-	Hartford Wolf Pack	-
39 - 2023-10-23	443	Abbotsford Canucks	-	Milwaukee Admirals	-
42 - 2023-10-26	475	Hartford Wolf Pack	-	Milwaukee Admirals	-
45 - 2023-10-29	497	Laval Rocket	-	Milwaukee Admirals	-
46 - 2023-10-30	507	Milwaukee Admirals	-	Lehigh Valley Phantoms	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	4500	3500
Ticket Price	35	0
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
14	0 - 0.00%	0$	0$	8000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,211,250$	911,250$	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$	42	0$	0$

Milwaukee Admirals 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	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Milwaukee Admirals 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

Milwaukee Admirals 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

Milwaukee Admirals Players 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

Milwaukee Admirals 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

	Milwaukee Admirals
	GP: 4 \| W: 3 \| L: 1 \| OTL: 0 \| P: 6 GF: 22 \| GA: 17 \| PP%: 10.00% \| PK%: 85.71% GM : Matt Sullivan \| Morale : 60 \| Team Overall : 58 Next Games #68 vs Toronto Marlies