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

Game Center
	Condors 15-1-2, 32pts	5	FINAL	4	Moose 12-5-1, 25pts

Team Stats
SOW1	Streak	W1
7-1-1	Home Record	7-1-1
8-0-1	Away Record	5-4-0
9-0-1	Last 10 Games	5-4-1
5.72	Goals Per Game	3.78
1.89	Goals Against Per Game	2.17
21.74%	Power Play Percentage	16.00%
85.71%	Penalty Kill Percentage	85.58%

Barracuda
6-12-0, 12pts

FINAL

Moose
12-5-1, 25pts

Team Stats
L2	Streak	W1
5-4-0	Home Record	7-1-1
1-8-0	Away Record	5-4-0
5-5-0	Last 10 Games	5-4-1
3.28	Goals Per Game	3.78
4.11	Goals Against Per Game	2.17
22.22%	Power Play Percentage	16.00%
78.18%	Penalty Kill Percentage	85.58%

Team Leaders
	Goals Beck Malenstyn 15	Assists Fredrik Karlstrom 14

	Points Fredrik Karlstrom 24	Plus/Minus Tyler Kleven 21

	Wins Joel Blomqvist 7	Save Percentage Joel Blomqvist 0.899

Team Stats
Goals For 68 3.78 GFG	Shots For 458 25.44 Avg	Power Play Percentage 16.0% 12 GF	Offensive Zone Start 41.7%
Goals Against 39 2.17 GAA	Shots Against 279 15.50 Avg	Penalty Kill Percentage 85.6%% 15 GA	Defensive Zone Start 35.8%

Team Info
	General Manager	Mika
	Coach	Todd Richards
	Division	Central Division
	Conference	Western Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	0
	Season Tickets	0
Roster Info
	Pro Team	22
	Farm Team	22
	Contract Limit	44 / 50
	Prospects	36
Team History
	This Season	12-5-1 (25PTS)
	History	0-0-0


	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
1	Beck Malenstyn	X	X			100.00	95	57	90	73	76	67	82	66	41	65	58	89	25	55	55	70	50	68	0	26	1	775,000$
2	Jansen Harkins		X			100.00	81	56	86	69	68	51	79	66	25	59	55	70	75	64	65	63	50	63	0	27	1	850,000$
3	Roby Jarventie (R)		X			100.00	77	79	72	68	79	57	55	66	50	62	66	66	63	44	44	66	50	62	0	22	1	894,167$
4	Mikael Pyyhtia	X				100.00	65	41	99	63	63	64	74	64	32	61	55	77	25	45	45	64	50	61	0	22	3	925,000$
5	Fredrik Karlstrom	X				100.00	79	73	94	61	73	74	78	61	76	57	60	66	57	44	44	64	50	61	0	26	1	750,000$
6	Samu Tuomaala (R)			X		100.00	72	62	94	65	62	69	72	61	50	60	58	62	55	44	44	63	50	60	0	21	3	863,333$
7	Clark Bishop	X	X			100.00	70	72	66	66	72	71	76	57	71	50	56	64	53	58	58	60	50	60	0	28	2	775,000$
8	Rasmus Kupari	X	X	X		100.00	79	70	80	77	70	64	70	45	58	56	53	59	42	60	61	54	50	59	0	24	2	1,000,000$
9	Judd Caulfield (R)			X		100.00	81	77	89	61	77	64	67	56	50	52	56	66	53	44	44	61	50	59	0	23	3	837,500$
10	Joona Koppanen	X	X			100.00	79	75	88	63	75	75	81	52	65	53	47	64	45	44	44	57	50	58	0	26	2	775,000$
11	Tucker Robertson (R)	X				100.00	74	68	87	61	68	57	59	50	63	45	51	61	48	44	44	55	50	54	0	21	3	950,000$
12	Gustav Lindstrom				X	100.00	79	44	84	75	72	67	62	63	25	51	49	77	25	61	61	62	50	66	0	25	1	950,000$
13	Santeri Hatakka (R)				X	100.00	77	43	89	76	64	65	66	59	25	52	47	79	25	45	45	61	50	64	0	23	1	925,000$
14	Tyler Kleven (R)				X	100.00	76	77	75	68	77	63	67	51	25	46	42	62	40	44	44	55	50	59	0	22	3	1,125,000$
15	Simon Johansson				X	100.00	70	66	80	65	66	76	83	49	25	37	46	58	44	44	44	54	50	58	0	25	3	925,000$
16	Markus Niemelainen (R)				X	100.00	79	76	85	65	76	58	62	45	25	35	40	62	38	46	46	51	50	57	0	26	1	925,000$
17	Lian Bichsel (R)				X	100.00	72	83	46	63	83	52	52	52	25	49	41	60	39	44	44	51	50	56	0	20	3	1,418,333$
Scratches
1	Matt Filipe	X	X			100.00	77	75	82	67	75	60	63	49	61	45	47	62	45	44	44	55	50	55	0	26	1	925,000$

	TEAM AVERAGE					100.00	77	66	83	67	72	64	69	56	44	52	52	67	44	49	49	59	50	60

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	Joel Blomqvist (R)	100.00	62	47	59	72	65	62	69	71	68	68	30	44	44	64	50	62	0	22	3	925,000$
2	Jeremy Helvig	100.00	61	52	65	79	65	62	58	65	62	61	30	44	44	61	50	61	0	27	1	750,000$
Scratches
1	Dylan Wells	100.00	50	45	56	72	51	52	50	55	53	52	30	44	44	51	50	53	0	26	1	750,000$
2	Jean-Francois Berube	100.00	47	47	59	66	46	48	50	53	50	50	30	47	47	49	50	51	0	33	1	775,000$

	TEAM AVERAGE	100.00	55	48	60	72	57	56	57	61	58	58	30	45	45	56	50	57

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Todd Richards	67	74	71	63	81	76	67	USA	55	2	925,000$

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	HT	P/20	PSG	PSS	FW	S1	S2	S3
1	Fredrik Karlstrom	Moose (WPG)	C	18	10	14	24	18	11	5	13	28	52	15	45	19.23%	0	322	17.89	0	3	3	6	55	0	0	0	0	18	3	0	68.93%	280	0	1.49	0	1	1	3	1	3
2	Beck Malenstyn	Moose (WPG)	C/LW	18	15	7	22	7	24	0	53	31	60	19	51	25.00%	8	407	22.65	4	3	7	8	59	1	0	1	2	83	2	1	53.40%	427	1	1.08	0	1	0	3	0	0
3	Santeri Hatakka	Moose (WPG)	D	18	2	14	16	4	12	0	23	16	29	4	15	6.90%	8	402	22.39	2	6	8	19	58	0	1	1	3	74	0	0	0.00%	0	0	0.79	0	0	0	0	2	2
4	Samu Tuomaala	Moose (WPG)	RW	18	5	10	15	11	2	0	10	21	47	7	26	10.64%	1	295	16.42	0	2	2	10	62	0	0	0	0	0	2	0	52.63%	19	0	1.02	0	0	0	1	2	0
5	Rasmus Kupari	Moose (WPG)	C/LW/RW	18	3	12	15	17	20	0	20	11	34	10	31	8.82%	1	303	16.85	0	0	0	6	54	0	0	0	0	2	0	0	47.83%	23	0	0.99	0	0	0	0	0	0
6	Clark Bishop	Moose (WPG)	C/LW	18	4	10	14	7	20	0	20	14	40	10	27	10.00%	1	284	15.78	0	0	0	0	8	0	0	0	0	11	0	0	65.63%	32	0	0.99	0	0	0	0	1	1
7	Mikael Pyyhtia	Moose (WPG)	C	18	9	3	12	5	6	0	6	33	54	11	32	16.67%	3	267	14.86	2	1	3	2	7	0	0	0	0	13	1	0	54.41%	204	1	0.90	0	0	0	1	1	0
8	Jansen Harkins	Moose (WPG)	LW	18	4	8	12	13	8	0	15	22	33	13	28	12.12%	5	342	19.02	0	0	0	8	52	1	0	1	3	50	0	0	45.45%	33	0	0.70	0	1	0	1	1	2
9	Roby Jarventie	Moose (WPG)	LW	14	2	9	11	6	22	0	30	18	25	17	24	8.00%	0	217	15.53	0	0	0	2	13	0	1	1	1	25	0	0	63.16%	19	0	1.01	1	1	0	1	0	0
10	Gustav Lindstrom	Moose (WPG)	D	18	3	6	9	3	10	0	34	25	22	9	14	13.64%	11	405	22.55	2	2	4	10	59	0	0	0	0	80	2	0	0.00%	0	0	0.44	0	0	0	2	1	0
11	Tyler Kleven	Moose (WPG)	D	18	3	4	7	21	18	0	41	9	12	5	7	25.00%	6	374	20.83	1	0	1	7	54	0	0	0	0	78	2	0	0.00%	0	0	0.37	0	0	0	1	0	1
12	Lian Bichsel	Moose (WPG)	D	18	1	5	6	9	34	0	42	7	6	1	0	16.67%	7	284	15.79	1	0	1	1	3	0	1	1	0	27	0	0	0.00%	0	0	0.42	0	0	0	0	0	0
13	Judd Caulfield	Moose (WPG)	RW	7	2	4	6	4	2	0	12	4	10	3	12	20.00%	0	101	14.55	0	0	0	0	0	0	0	0	0	0	0	0	66.67%	3	0	1.18	0	0	0	0	1	0
14	Joona Koppanen	Moose (WPG)	C/LW	18	2	1	3	2	10	0	10	14	10	2	11	20.00%	1	154	8.57	0	0	0	1	2	0	0	0	2	48	0	0	54.84%	62	0	0.39	0	0	0	0	0	0
15	Simon Johansson	Moose (WPG)	D	18	1	2	3	21	10	0	31	8	12	4	9	8.33%	8	388	21.59	0	0	0	6	60	0	0	0	0	82	0	0	0.00%	0	0	0.15	0	0	0	0	0	2
16	Matt Filipe	Moose (WPG)	C/LW	15	2	1	3	1	0	0	4	1	6	1	3	33.33%	0	51	3.46	0	0	0	3	9	0	0	0	0	11	0	0	70.59%	17	0	1.16	0	0	0	0	1	0
17	Markus Niemelainen	Moose (WPG)	D	18	0	3	3	7	10	0	15	5	5	3	4	0.00%	12	285	15.86	0	0	0	0	10	0	0	0	0	19	0	0	0.00%	0	0	0.21	0	0	0	0	0	0
18	Tucker Robertson	Moose (WPG)	C	7	0	2	2	1	0	0	0	0	1	0	1	0.00%	0	24	3.46	0	1	1	1	5	0	0	0	0	5	0	0	55.56%	9	0	1.65	0	0	0	0	0	0
Team Total or Average				295	68	115	183	157	219	5	379	267	458	134	340	14.85%	72	4914	16.66	12	18	30	90	580	2	3	5	11	633	12	1	57.98%	1128	2	0.74	1	4	1	13	11	11

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	SO	GA	SA	A	PS %	PSA	ST	BG
1	Joel Blomqvist	Moose (WPG)	10	7	1	1	0.899	1.38	523	1	12	119	1	0.500	4	8	10
2	Jeremy Helvig	Moose (WPG)	10	5	4	0	0.838	2.78	561	1	26	160	0	0.00%	0	10	8
Team Total or Average			20	12	5	1	0.864	2.10	1085	2	38	279	1		4	18	18

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 Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Link
Beck Malenstyn	Moose (WPG)	C/LW	26	1998-02-04	No	200 Lbs	6 ft3	No	No	No	1	Pro & Farm	775,000$	775,000$	0$	0$	No			Link / NHL Link
Clark Bishop	Moose (WPG)	C/LW	28	1996-03-28	No	199 Lbs	6 ft1	No	No	No	2	Pro & Farm	775,000$	775,000$	0$	0$	No	775,000$		Link / NHL Link
Dylan Wells	Moose (WPG)	G	26	1998-01-03	No	183 Lbs	6 ft2	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Link / NHL Link
Fredrik Karlstrom	Moose (WPG)	C	26	1998-01-12	No	190 Lbs	6 ft3	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Link
Gustav Lindstrom	Moose (WPG)	D	25	1998-10-20	No	194 Lbs	6 ft2	No	No	No	1	Pro & Farm	950,000$	950,000$	0$	0$	No			Link / NHL Link
Jansen Harkins	Moose (WPG)	LW	27	1997-05-23	No	183 Lbs	6 ft1	No	No	No	1	Pro & Farm	850,000$	850,000$	0$	0$	No			Link / NHL Link
Jean-Francois Berube	Moose (WPG)	G	33	1991-07-13	No	177 Lbs	6 ft1	No	No	No	1	Pro & Farm	775,000$	775,000$	0$	0$	No			Link
Jeremy Helvig	Moose (WPG)	G	27	1997-05-24	No	188 Lbs	6 ft4	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Link / NHL Link
Joel Blomqvist	Moose (WPG)	G	22	2002-01-10	Yes	183 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Joona Koppanen	Moose (WPG)	C/LW	26	1998-02-25	No	194 Lbs	6 ft5	No	No	No	2	Pro & Farm	775,000$	775,000$	0$	0$	No	775,000$		Link / NHL Link
Judd Caulfield	Moose (WPG)	RW	23	2001-03-19	Yes	207 Lbs	6 ft3	No	No	No	3	Pro & Farm	837,500$	837,500$	0$	0$	No	837,500$	837,500$	Link
Lian Bichsel	Moose (WPG)	D	20	2004-05-18	Yes	216 Lbs	6 ft6	No	No	No	3	Pro & Farm	1,418,333$	1,418,333$	0$	0$	No	1,418,333$	1,418,333$	Link
Markus Niemelainen	Moose (WPG)	D	26	1998-06-07	Yes	190 Lbs	6 ft6	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Link
Matt Filipe	Moose (WPG)	C/LW	26	1997-12-31	No	203 Lbs	6 ft2	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Link
Mikael Pyyhtia	Moose (WPG)	C	22	2001-12-17	No	174 Lbs	5 ft11	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Rasmus Kupari	Moose (WPG)	C/LW/RW	24	2000-03-15	No	189 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,000,000$	1,000,000$	0$	0$	No	1,000,000$		Link / NHL Link
Roby Jarventie	Moose (WPG)	LW	22	2002-08-08	Yes	213 Lbs	6 ft3	No	No	No	1	Pro & Farm	894,167$	894,167$	0$	0$	No			Link
Samu Tuomaala	Moose (WPG)	RW	21	2003-01-08	Yes	174 Lbs	5 ft10	No	No	No	3	Pro & Farm	863,333$	863,333$	0$	0$	No	863,333$	863,333$	Link
Santeri Hatakka	Moose (WPG)	D	23	2001-01-15	Yes	174 Lbs	6 ft0	No	No	No	1	Pro & Farm	925,000$	925,000$	0$	0$	No			Link
Simon Johansson	Moose (WPG)	D	25	1999-06-14	No	170 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Tucker Robertson	Moose (WPG)	C	21	2003-06-22	Yes	190 Lbs	5 ft10	No	No	No	3	Pro & Farm	950,000$	950,000$	0$	0$	No	950,000$	950,000$	Link
Tyler Kleven	Moose (WPG)	D	22	2002-01-10	Yes	200 Lbs	6 ft4	No	No	No	3	Pro & Farm	1,125,000$	1,125,000$	0$	0$	No	1,125,000$	1,125,000$	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
22	24.59	191 Lbs	6 ft2	1.86	899,470$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jansen Harkins	Beck Malenstyn	Samu Tuomaala	40	1	2	2
2	Roby Jarventie	Fredrik Karlstrom	Rasmus Kupari	30	1	2	2
3	Clark Bishop	Mikael Pyyhtia	Judd Caulfield	20	1	2	2
4	Beck Malenstyn	Joona Koppanen	Jansen Harkins	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Gustav Lindstrom	Santeri Hatakka	40	1	2	2
2	Tyler Kleven	Simon Johansson	30	1	2	2
3	Markus Niemelainen	Lian Bichsel	20	1	2	2
4	Gustav Lindstrom	Santeri Hatakka	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jansen Harkins	Beck Malenstyn	Samu Tuomaala	60	1	2	2
2	Roby Jarventie	Fredrik Karlstrom	Rasmus Kupari	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Gustav Lindstrom	Santeri Hatakka	60	1	2	2
2	Tyler Kleven	Simon Johansson	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Beck Malenstyn	Jansen Harkins	60	1	2	2
2	Roby Jarventie	Fredrik Karlstrom	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Gustav Lindstrom	Santeri Hatakka	60	1	2	2
2	Tyler Kleven	Simon Johansson	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Beck Malenstyn	60	1	2	2	Gustav Lindstrom	Santeri Hatakka	60	1	2	2
2	Jansen Harkins	40	1	2	2	Tyler Kleven	Simon Johansson	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Beck Malenstyn	Jansen Harkins	60	1	2	2
2	Roby Jarventie	Fredrik Karlstrom	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Gustav Lindstrom	Santeri Hatakka	60	1	2	2
2	Tyler Kleven	Simon Johansson	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Jansen Harkins	Beck Malenstyn	Samu Tuomaala	Gustav Lindstrom	Santeri Hatakka

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jansen Harkins	Beck Malenstyn	Samu Tuomaala	Gustav Lindstrom	Santeri Hatakka

Extra Forwards
Normal	PowerPlay	Penalty Kill
Tucker Robertson, Mikael Pyyhtia, Clark Bishop	Tucker Robertson, Mikael Pyyhtia	Clark Bishop

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Markus Niemelainen, Lian Bichsel, Tyler Kleven	Markus Niemelainen	Lian Bichsel, Tyler Kleven

Penalty Shots
Beck Malenstyn, Jansen Harkins, Roby Jarventie, Fredrik Karlstrom, Mikael Pyyhtia

Goalie
#1 : Jeremy Helvig, #2 : Joel Blomqvist

Custom OT Lines Forwards
Beck Malenstyn, Jansen Harkins, Roby Jarventie, Fredrik Karlstrom, Mikael Pyyhtia, Clark Bishop, Clark Bishop, Samu Tuomaala, Rasmus Kupari, Judd Caulfield, Joona Koppanen

Custom OT Lines Defensemen
Gustav Lindstrom, Santeri Hatakka, Tyler Kleven, Simon Johansson, Markus Niemelainen

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	Americans	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	30	18	20	1	16	163	144	151	4	16	4	8	23	9	1	11.11%	4	1	75.00%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
2	Barracuda	2	2	0	0	0	0	0	0	9	2	7	1	1	0	0	0	0	0	0	4	2	2	1	1	0	0	0	0	0	0	5	0	5	4	1.000	9	16	25	0	1	30	18	20	1	48	163	144	151	4	21	7	16	40	8	1	12.50%	8	1	87.50%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
3	Bears	1	1	0	0	0	0	0	0	3	1	2	1	1	0	0	0	0	0	0	3	1	2	0	0	0	0	0	0	0	0	0	0	0	2	1.000	3	5	8	0	0	30	18	20	1	36	163	144	151	4	9	3	14	27	4	0	0.00%	7	1	85.71%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
4	Condors	2	0	1	0	0	0	0	1	7	10	-3	1	0	0	0	0	0	0	1	4	5	-1	1	0	1	0	0	0	0	0	3	5	-2	1	0.250	7	10	17	0	0	30	18	20	1	43	163	144	151	4	35	12	28	43	12	2	16.67%	13	3	76.92%	1	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
5	Eagles	2	1	1	0	0	0	0	0	4	6	-2	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	4	7	11	0	0	30	18	20	1	26	163	144	151	4	43	6	39	48	10	2	20.00%	16	2	87.50%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
6	Gulls	2	2	0	0	0	0	0	0	10	3	7	1	1	0	0	0	0	0	0	6	1	5	1	1	0	0	0	0	0	0	4	2	2	4	1.000	10	18	28	0	0	30	18	20	1	85	163	144	151	4	28	6	16	39	3	1	33.33%	8	0	100.00%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
7	Reign	2	0	2	0	0	0	0	0	0	7	-7	1	0	1	0	0	0	0	0	0	4	-4	1	0	1	0	0	0	0	0	0	3	-3	0	0.000	0	0	0	0	0	30	18	20	1	32	163	144	151	4	50	15	28	47	9	0	0.00%	14	6	57.14%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
8	Roadrunners	2	2	0	0	0	0	0	0	15	1	14	1	1	0	0	0	0	0	0	7	0	7	1	1	0	0	0	0	0	0	8	1	7	4	1.000	15	26	41	0	1	30	18	20	1	60	163	144	151	4	20	7	20	44	3	3	100.00%	10	0	100.00%	1	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
9	Thunderbirds	1	1	0	0	0	0	0	0	4	1	3	1	1	0	0	0	0	0	0	4	1	3	0	0	0	0	0	0	0	0	0	0	0	2	1.000	4	7	11	0	0	30	18	20	1	34	163	144	151	4	10	0	12	28	1	0	0.00%	6	0	100.00%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
10	Wild	1	1	0	0	0	0	0	0	9	1	8	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	9	1	8	2	1.000	9	15	24	0	0	30	18	20	1	29	163	144	151	4	18	5	18	11	2	1	50.00%	8	0	100.00%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
11	Wranglers	2	1	1	0	0	0	0	0	4	6	-2	1	1	0	0	0	0	0	0	3	2	1	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	4	7	11	0	0	30	18	20	1	49	163	144	151	4	29	7	20	29	14	1	7.14%	10	1	90.00%	0	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
	Total	18	12	5	0	0	0	0	1	68	39	29	9	7	1	0	0	0	0	1	34	18	16	9	5	4	0	0	0	0	0	34	21	13	25	0.694	68	117	185	0	2	30	18	20	1	458	163	144	151	4	279	72	219	379	75	12	16.00%	104	15	85.58%	2	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
	_Since Last GM Reset	18	12	5	0	0	0	0	1	68	39	29	9	7	1	0	0	0	0	1	34	18	16	9	5	4	0	0	0	0	0	34	21	13	25	0.694	68	117	185	0	2	30	18	20	1	458	163	144	151	4	279	72	219	379	75	12	16.00%	104	15	85.58%	2	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
	_Vs Conference	17	11	5	0	0	0	0	1	65	38	27	8	6	1	0	0	0	0	1	31	17	14	9	5	4	0	0	0	0	0	34	21	13	23	0.676	65	112	177	0	2	30	18	20	1	422	163	144	151	4	270	69	205	352	71	12	16.90%	97	14	85.57%	2	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119
	_Vs Division	6	3	0	0	0	0	0	0	32	9	23	3	1	0	0	0	0	0	0	14	3	11	3	2	0	0	0	0	0	0	18	6	12	6	0.500	32	55	87	0	1	30	18	20	1	149	163	144	151	4	91	18	89	131	16	6	37.50%	40	2	95.00%	1	297	475	62.53%	211	408	51.72%	152	256	59.38%	540	398	332	112	211	119

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
18	25	W1	68	117	185	458	279	72	219	379	0	2

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
18	12	5	0	0	0	1	68	39

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	7	1	0	0	0	1	34	18

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	5	4	0	0	0	0	34	21

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

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
75	12	16.00%	104	15	85.58%	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
163	144	151	4	30	18	20	1

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
297	475	62.53%	211	408	51.72%	152	256	59.38%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
540	398	332	112	211	119

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 - 2024-09-23	2	Thunderbirds	1	Moose	4	BW			BoxScore
3 - 2024-09-25	32	Moose	4	Gulls	2	AW			BoxScore
4 - 2024-09-26	45	Moose	8	Roadrunners	1	AW			BoxScore
5 - 2024-09-27	51	Wranglers	2	Moose	3	BW			BoxScore
6 - 2024-09-28	61	Moose	1	Wranglers	4	AL			BoxScore
7 - 2024-09-29	82	Bears	1	Moose	3	BW			BoxScore
9 - 2024-10-01	98	Moose	5	Barracuda	0	AW			BoxScore
10 - 2024-10-02	117	Moose	3	Americans	1	AW			BoxScore
11 - 2024-10-03	125	Eagles	2	Moose	3	BW			BoxScore
13 - 2024-10-05	150	Reign	4	Moose	0	BL			BoxScore
14 - 2024-10-06	163	Moose	0	Reign	3	AL			BoxScore
15 - 2024-10-07	178	Gulls	1	Moose	6	BW			BoxScore
16 - 2024-10-08	195	Moose	9	Wild	1	AW			BoxScore
17 - 2024-10-09	207	Moose	1	Eagles	4	AL			BoxScore
18 - 2024-10-10	219	Roadrunners	0	Moose	7	BW			BoxScore
19 - 2024-10-11	232	Moose	3	Condors	5	AL			BoxScore
21 - 2024-10-13	251	Condors	5	Moose	4	BL	X	X	BoxScore
24 - 2024-10-16	275	Barracuda	2	Moose	4	BW			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	33	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
0	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,978,833$	1,978,833$	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$	1	0$	0$

Moose 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

Moose 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

Moose 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

Moose 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

Moose 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

	Moose
	GP: 18 \| W: 12 \| L: 5 \| OTL: 1 \| P: 25 GF: 68 \| GA: 39 \| PP%: 16.00% \| PK%: 85.58% GM : Mika \| Morale : 50 \| Team Overall : 59