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

Game Center
	Thunderbirds 2-16-0, 4pts	0	FINAL	12	Monsters 7-10-1, 15pts

Team Stats
L6	Streak	L1
2-7-0	Home Record	4-5-0
0-9-0	Away Record	3-5-1
2-8-0	Last 10 Games	2-7-1
1.78	Goals Per Game	4.33
7.28	Goals Against Per Game	3.94
9.62%	Power Play Percentage	13.33%
76.00%	Penalty Kill Percentage	74.14%

Thunderbirds
2-16-0, 4pts

FINAL

Condors
15-1-2, 32pts

Team Stats
L6	Streak	SOW1
2-7-0	Home Record	7-1-1
0-9-0	Away Record	8-0-1
2-8-0	Last 10 Games	9-0-1
1.78	Goals Per Game	5.72
7.28	Goals Against Per Game	1.89
9.62%	Power Play Percentage	21.74%
76.00%	Penalty Kill Percentage	85.71%

Team Leaders

Team Stats
Goals For 32 1.78 GFG	Shots For 358 19.89 Avg	Power Play Percentage 9.6% 5 GF	Offensive Zone Start 27.5%
Goals Against 131 7.28 GAA	Shots Against 966 53.67 Avg	Penalty Kill Percentage 76.0%% 6 GA	Defensive Zone Start 45.6%

Team Info
	General Manager	Fred
	Coach	Martin St Louis
	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	24
	Farm Team	18
	Contract Limit	42 / 50
	Prospects	34
Team History
	This Season	2-16-0 (4PTS)
	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	Peyton Krebs	X	X			100.00	79	53	76	80	66	62	94	66	74	63	57	65	25	63	63	65	50	65	0	23	1	1,275,833$
2	Mavrik Bourque (R)	X				100.00	71	63	89	77	63	82	86	68	80	68	65	64	62	44	44	69	50	65	0	22	3	894,167$
3	Hendrix Lapierre (R)	X				100.00	65	41	97	77	65	59	83	68	60	72	70	64	25	50	50	70	50	65	0	22	3	1,105,833$
4	Samuel Blais		X	X		100.00	99	59	83	82	77	54	82	62	31	60	55	63	75	65	67	64	50	64	0	28	1	1,500,000$
5	Matthew Poitras (R)	X				100.00	65	41	93	77	64	65	57	67	72	75	68	65	25	47	47	69	50	63	0	20	3	950,000$
6	Georgi Merkulov		X			100.00	73	66	90	75	66	70	71	66	50	63	66	64	63	44	44	67	50	63	0	24	2	925,000$
7	Vasili Podkolzin (R)		X	X		100.00	76	71	89	65	71	61	61	64	50	56	64	69	61	59	59	65	50	62	0	23	1	1,775,000$
8	Logan Morrison (R)	X				100.00	76	67	98	64	67	68	70	62	78	59	60	65	57	44	44	64	50	61	0	22	3	870,000$
9	Mackenzie MacEachern			X		100.00	75	70	87	71	70	58	58	61	50	59	57	67	54	58	59	63	50	61	0	30	1	750,000$
10	Zack Ostapchuk (R)	X				100.00	78	77	80	74	77	70	74	56	70	47	61	64	58	44	44	62	50	60	0	21	3	825,000$
11	William Dufour (R)			X		100.00	76	73	83	60	73	74	78	58	50	49	63	64	60	44	44	63	50	60	0	22	3	925,000$
12	Nikita Alexandrov	X	X			100.00	78	44	94	71	68	52	65	60	54	59	55	62	25	49	49	61	50	59	0	24	3	880,000$
13	Justin Barron				X	100.00	78	44	89	77	75	76	88	69	25	50	58	74	25	56	56	66	50	68	0	22	2	1,158,333$
14	Adam Boqvist				X	100.00	61	41	99	82	64	75	60	77	25	60	48	67	25	63	63	62	50	65	0	24	2	1,500,000$
15	Cale Fleury				X	100.00	79	75	89	74	75	57	58	55	25	50	43	66	41	51	51	57	50	61	0	25	2	920,000$
16	Vincent Iorio (R)				X	100.00	79	77	85	65	77	74	82	47	25	37	41	62	39	44	44	54	50	60	0	21	3	863,333$
17	Jakub Zboril				X	100.00	76	73	82	65	73	54	55	51	25	46	39	65	37	58	58	53	50	59	0	27	3	990,000$
18	Jeremie Poirier (R)				X	100.00	73	72	74	65	72	61	62	57	25	52	48	62	46	44	44	58	50	59	0	22	2	833,333$
19	Robin Salo (R)				X	100.00	74	67	89	65	67	69	74	51	25	46	41	61	39	45	45	54	50	59	0	26	1	800,000$
Scratches
1	Henri Nikkanen (R)	X				100.00	81	77	90	65	77	71	77	50	63	44	51	64	48	44	44	58	50	57	0	23	3	925,000$
2	Mathias Laferriere	X				100.00	73	65	91	64	65	69	74	52	65	53	47	61	45	44	44	56	50	57	0	24	2	800,000$
3	Hunter Skinner (R)				X	100.00	63	69	48	65	69	54	56	47	25	37	41	54	39	44	44	49	50	53	0	23	3	925,000$

	TEAM AVERAGE					100.00	75	63	86	71	70	65	71	60	48	55	54	64	44	50	50	61	50	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
1	Alex Stalock	100.00	48	48	60	73	47	47	50	54	48	48	30	44	44	49	50	51	0	37	2	1,250,000$
2	Zach Sawchenko	100.00	46	52	65	70	45	47	45	51	45	45	45	44	44	47	50	50	0	26	1	775,000$
Scratches

	TEAM AVERAGE	100.00	47	50	63	72	46	47	48	53	47	47	38	44	44	48	50	51

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Martin St Louis	62	69	66	68	75	70	75	CAN	49	3	1,000,000$

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 Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Link
Adam Boqvist	Thunderbirds (STL)	D	24	2000-08-14	No	178 Lbs	5 ft11	No	No	No	2	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No	1,500,000$		Link / NHL Link
Alex Stalock	Thunderbirds (STL)	G	37	1987-07-28	No	200 Lbs	6 ft0	No	No	No	2	Pro & Farm	1,250,000$	1,250,000$	0$	0$	No	1,250,000$		Link / NHL Link
Cale Fleury	Thunderbirds (STL)	D	25	1998-11-18	No	205 Lbs	6 ft1	No	No	No	2	Pro & Farm	920,000$	920,000$	0$	0$	No	920,000$		Link / NHL Link
Georgi Merkulov	Thunderbirds (STL)	LW	24	2000-10-10	No	180 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$		Link
Hendrix Lapierre	Thunderbirds (STL)	C	22	2002-09-02	Yes	178 Lbs	6 ft0	No	No	No	3	Pro & Farm	1,105,833$	1,105,833$	0$	0$	No	1,105,833$	1,105,833$	Link
Henri Nikkanen	Thunderbirds (STL)	C	23	2001-04-28	Yes	200 Lbs	6 ft4	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Hunter Skinner	Thunderbirds (STL)	D	23	2001-04-29	Yes	182 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Jakub Zboril	Thunderbirds (STL)	D	27	1997-02-21	No	200 Lbs	6 ft0	No	No	No	3	Pro & Farm	990,000$	990,000$	0$	0$	No	990,000$	990,000$	Link / NHL Link
Jeremie Poirier	Thunderbirds (STL)	D	22	2002-02-06	Yes	196 Lbs	6 ft1	No	No	No	2	Pro & Farm	833,333$	833,333$	0$	0$	No	833,333$		Link
Justin Barron	Thunderbirds (STL)	D	22	2001-11-15	No	202 Lbs	6 ft2	No	No	No	2	Pro & Farm	1,158,333$	1,158,333$	0$	0$	No	1,158,333$		Link
Logan Morrison	Thunderbirds (STL)	C	22	2002-07-09	Yes	180 Lbs	6 ft0	No	No	No	3	Pro & Farm	870,000$	870,000$	0$	0$	No	870,000$	870,000$	Link
Mackenzie MacEachern	Thunderbirds (STL)	RW	30	1994-03-08	No	189 Lbs	6 ft2	No	No	No	1	Pro & Farm	750,000$	750,000$	0$	0$	No			Link / NHL Link
Mathias Laferriere	Thunderbirds (STL)	C	24	2000-06-27	No	174 Lbs	6 ft1	No	No	No	2	Pro & Farm	800,000$	800,000$	0$	0$	No	800,000$		Link
Matthew Poitras	Blues	C	20	2004-03-10	Yes	176 Lbs	5 ft11	No	No	No	3	Pro & Farm	950,000$	950,000$	950,000$	950,000$	No	950,000$	950,000$	Link
Mavrik Bourque	Blues	C	22	2002-08-01	Yes	178 Lbs	5 ft10	No	No	No	3	Pro & Farm	894,167$	894,167$	894,167$	894,167$	No	894,167$	894,167$	Link
Nikita Alexandrov	Thunderbirds (STL)	C/LW	24	2000-09-16	No	189 Lbs	6 ft0	No	No	No	3	Pro & Farm	880,000$	880,000$	0$	0$	No	880,000$	880,000$	Link
Peyton Krebs	Thunderbirds (STL)	C/LW	23	2001-01-26	No	180 Lbs	5 ft11	No	No	No	1	Pro & Farm	1,275,833$	1,275,833$	0$	0$	No			Link
Robin Salo	Thunderbirds (STL)	D	26	1998-10-13	Yes	181 Lbs	6 ft0	No	No	No	1	Pro & Farm	800,000$	800,000$	0$	0$	No			Link
Samuel Blais	Thunderbirds (STL)	LW/RW	28	1996-06-17	No	205 Lbs	6 ft2	No	No	No	1	Pro & Farm	1,500,000$	1,500,000$	0$	0$	No			Link
Vasili Podkolzin	Thunderbirds (STL)	LW/RW	23	2001-06-24	Yes	190 Lbs	6 ft1	No	No	No	1	Pro & Farm	1,775,000$	1,775,000$	0$	0$	No			Link
Vincent Iorio	Thunderbirds (STL)	D	21	2002-11-14	Yes	200 Lbs	6 ft4	No	No	No	3	Pro & Farm	863,333$	863,333$	0$	0$	No	863,333$	863,333$	Link
William Dufour	Thunderbirds (STL)	RW	22	2002-01-28	Yes	195 Lbs	6 ft2	No	No	No	3	Pro & Farm	925,000$	925,000$	0$	0$	No	925,000$	925,000$	Link
Zach Sawchenko	Thunderbirds (STL)	G	26	1997-12-30	No	185 Lbs	6 ft1	No	No	No	1	Pro & Farm	775,000$	775,000$	0$	0$	No			Link
Zack Ostapchuk	Thunderbirds (STL)	C	21	2003-05-29	Yes	202 Lbs	6 ft4	No	No	No	3	Pro & Farm	825,000$	825,000$	0$	0$	No	825,000$	825,000$	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
24	24.21	189 Lbs	6 ft1	2.21	1,017,326$

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	Americans	1	0	1	0	0	0	0	0	0	9	-9	1	0	1	0	0	0	0	0	0	9	-9	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	16	10	6	0	2	121	115	122	0	59	11	2	7	4	0	0.00%	1	0	100.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
2	Barracuda	2	1	1	0	0	0	0	0	8	9	-1	1	1	0	0	0	0	0	0	6	4	2	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	8	16	24	0	0	16	10	6	0	77	121	115	122	0	109	33	6	33	3	1	33.33%	3	1	66.67%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
3	Condors	2	0	2	0	0	0	0	0	2	18	-16	1	0	1	0	0	0	0	0	2	7	-5	1	0	1	0	0	0	0	0	0	11	-11	0	0.000	2	4	6	0	0	16	10	6	0	16	121	115	122	0	125	31	6	20	10	1	10.00%	2	0	100.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
4	Eagles	2	0	2	0	0	0	0	0	2	17	-15	1	0	1	0	0	0	0	0	1	11	-10	1	0	1	0	0	0	0	0	1	6	-5	0	0.000	2	4	6	0	0	16	10	6	0	15	121	115	122	0	116	27	6	13	2	0	0.00%	3	1	66.67%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
5	Griffins	1	0	1	0	0	0	0	0	0	10	-10	1	0	1	0	0	0	0	0	0	10	-10	0	0	0	0	0	0	0	0	0	0	0	0	0.000	0	0	0	0	0	16	10	6	0	14	121	115	122	0	57	18	2	5	1	0	0.00%	0	0	0.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
6	Gulls	2	0	2	0	0	0	0	0	6	14	-8	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	9	-6	0	0.000	6	12	18	0	0	16	10	6	0	67	121	115	122	0	138	38	4	53	3	0	0.00%	2	0	100.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
7	Monsters	1	0	1	0	0	0	0	0	0	12	-12	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	0	12	-12	0	0.000	0	0	0	0	0	16	10	6	0	18	121	115	122	0	71	26	4	17	2	0	0.00%	2	0	100.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
8	Moose	1	0	1	0	0	0	0	0	1	4	-3	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	1	1	2	0	0	16	10	6	0	10	121	115	122	0	34	10	2	5	6	0	0.00%	1	0	100.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
9	Reign	2	0	2	0	0	0	0	0	3	12	-9	1	0	1	0	0	0	0	0	1	8	-7	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	3	6	9	0	0	16	10	6	0	27	121	115	122	0	78	32	8	18	8	1	12.50%	4	1	75.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
10	Roadrunners	2	1	1	0	0	0	0	0	9	10	-1	1	1	0	0	0	0	0	0	5	4	1	1	0	1	0	0	0	0	0	4	6	-2	2	0.500	9	18	27	1	0	16	10	6	0	100	121	115	122	0	78	26	2	51	6	2	33.33%	1	1	0.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
11	Wranglers	2	0	2	0	0	0	0	0	1	16	-15	1	0	1	0	0	0	0	0	0	7	-7	1	0	1	0	0	0	0	0	1	9	-8	0	0.000	1	2	3	0	0	16	10	6	0	12	121	115	122	0	101	27	19	16	7	0	0.00%	6	2	66.67%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
	Total	18	2	16	0	0	0	0	0	32	131	-99	9	2	7	0	0	0	0	0	18	65	-47	9	0	9	0	0	0	0	0	14	66	-52	4	0.111	32	63	95	1	0	16	10	6	0	358	121	115	122	0	966	279	61	238	52	5	9.62%	25	6	76.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
	_Since Last GM Reset	18	2	16	0	0	0	0	0	32	131	-99	9	2	7	0	0	0	0	0	18	65	-47	9	0	9	0	0	0	0	0	14	66	-52	4	0.111	32	63	95	1	0	16	10	6	0	358	121	115	122	0	966	279	61	238	52	5	9.62%	25	6	76.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
	_Vs Conference	16	2	14	0	0	0	0	0	32	109	-77	8	2	6	0	0	0	0	0	18	55	-37	8	0	8	0	0	0	0	0	14	54	-40	4	0.125	32	63	95	1	0	16	10	6	0	326	121	115	122	0	838	235	55	216	49	5	10.20%	23	6	73.91%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67
	_Vs Division	5	0	2	0	0	0	0	0	12	31	-19	2	0	1	0	0	0	0	0	6	15	-9	3	0	1	0	0	0	0	0	6	16	-10	0	0.000	12	23	35	1	0	16	10	6	0	125	121	115	122	0	228	63	10	69	14	2	14.29%	5	2	60.00%	0	111	318	34.91%	162	527	30.74%	104	311	33.44%	208	130	680	131	190	67

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
18	4	L6	32	63	95	358	966	279	61	238	1	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
18	2	16	0	0	0	0	32	131

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	2	7	0	0	0	0	18	65

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
9	0	9	0	0	0	0	14	66

Last 10 Games
W	L	OTW	OTL	SOW	SOL
2	8	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
52	5	9.62%	25	6	76.00%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
121	115	122	0	16	10	6	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
111	318	34.91%	162	527	30.74%	104	311	33.44%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
208	130	680	131	190	67

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 - 2024-09-23	2	Thunderbirds	1	Moose	4	AL	BoxScore
2 - 2024-09-24	24	Thunderbirds	4	Roadrunners	6	AL	BoxScore
3 - 2024-09-25	31	Eagles	11	Thunderbirds	1	BL	BoxScore
5 - 2024-09-27	54	Americans	9	Thunderbirds	0	BL	BoxScore
6 - 2024-09-28	71	Thunderbirds	2	Barracuda	5	AL	BoxScore
7 - 2024-09-29	83	Griffins	10	Thunderbirds	0	BL	BoxScore
9 - 2024-10-01	99	Thunderbirds	1	Eagles	6	AL	BoxScore
10 - 2024-10-02	116	Thunderbirds	3	Gulls	9	AL	BoxScore
11 - 2024-10-03	127	Barracuda	4	Thunderbirds	6	BW	BoxScore
12 - 2024-10-04	147	Thunderbirds	1	Wranglers	9	AL	BoxScore
13 - 2024-10-05	159	Gulls	5	Thunderbirds	3	BL	BoxScore
15 - 2024-10-07	180	Roadrunners	4	Thunderbirds	5	BW	BoxScore
16 - 2024-10-08	199	Condors	7	Thunderbirds	2	BL	BoxScore
19 - 2024-10-11	225	Wranglers	7	Thunderbirds	0	BL	BoxScore
20 - 2024-10-12	242	Thunderbirds	2	Reign	4	AL	BoxScore
22 - 2024-10-14	260	Reign	8	Thunderbirds	1	BL	BoxScore
23 - 2024-10-15	266	Thunderbirds	0	Monsters	12	AL	BoxScore
24 - 2024-10-16	271	Thunderbirds	0	Condors	11	AL	BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	100	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$	2,257,165$	2,174,665$	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$

Thunderbirds 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

Thunderbirds 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

Thunderbirds 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

Thunderbirds 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

Thunderbirds 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

	Thunderbirds
	GP: 18 \| W: 2 \| L: 16 \| OTL: 0 \| P: 4 GF: 32 \| GA: 131 \| PP%: 9.62% \| PK%: 76.00% GM : Fred \| Morale : 50 \| Team Overall : 60