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

Game Center
	San Diego Gulls 32-34-6, 70pts	4	FINAL	3	Manitoba Moose 36-26-10, 82pts

Team Stats
W2	Streak	L1
17-15-4	Home Record	22-9-5
15-19-2	Away Record	14-17-5
4-4-2	Last 10 Games	3-6-1
2.81	Goals Per Game	3.10
2.93	Goals Against Per Game	2.76
15.72%	Power Play Percentage	19.58%
81.21%	Penalty Kill Percentage	81.94%

Rochester Americans
39-29-4, 82pts

FINAL

San Diego Gulls
32-34-6, 70pts

Team Stats
L1	Streak	W2
23-11-2	Home Record	17-15-4
16-18-2	Away Record	15-19-2
5-5-0	Last 10 Games	4-4-2
3.18	Goals Per Game	2.81
3.10	Goals Against Per Game	2.93
21.38%	Power Play Percentage	15.72%
83.33%	Penalty Kill Percentage	81.21%

Team Leaders
	Goals Peyton Krebs 25	Assists Peyton Krebs 38

	Points Peyton Krebs 63	Plus/Minus Joachim Blichfeld 12

	Wins Lukas Dostal 25	Save Percentage Ben Bishop 0.911

Team Stats
Goals For 202 2.81 GFG	Shots For 2190 30.42 Avg	Power Play Percentage 15.7% 50 GF	Offensive Zone Start 40.2%
Goals Against 211 2.93 GAA	Shots Against 2157 29.96 Avg	Penalty Kill Percentage 81.2% 53 GA	Defensive Zone Start 40.1%

Team Info
	General Manager	Thomas Larsson
	Coach	Neil Graham
	Division	Pacific
	Conference	Western Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	2,836
	Season Tickets	300
Roster Info
	Pro Team	22
	Farm Team	20
	Contract Limit	42 / 60
	Prospects	29
Team History
	This Season	32-34-6 (70PTS)
	History	62-66-10 (0.449%)
	Playoff Appearances	1
	Playoff Record (W-L)	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	Nate Thompson	0	X	X			100.00	80	65	74	69	76	62	64	59	88	56	56	84	25	79	83	0	60	64	0	38	1	950,000$
2	Peyton Krebs (R)	0	X	X			100.00	63	41	88	80	66	68	69	74	48	71	62	63	25	51	51	0	60	64	0	22	1	894,167$
3	Sam Carrick	0	X				100.00	84	99	64	70	78	59	79	60	72	61	70	72	25	57	57	0	63	63	0	31	2	850,000$
4	Max Jones	0		X	X		100.00	77	46	78	73	80	62	50	63	44	54	63	66	25	59	59	0	60	61	0	25	2	1,295,000$
5	Thomas Novak	0	X				100.00	57	40	97	67	66	61	57	74	61	67	56	63	25	46	46	0	60	60	0	25	1	750,000$
6	Benoit-Olivier Groulx (R)	0	X				100.00	76	44	96	67	73	59	76	58	60	60	57	77	25	45	45	0	60	60	0	23	1	822,500$
7	Jacob Perreault (R)	0	X		X		100.00	69	69	69	70	69	66	67	62	78	60	61	61	58	44	44	0	60	60	0	20	1	925,000$
8	Joachim Blichfeld	86		X	X		100.00	75	69	90	66	69	63	63	63	50	58	65	64	62	44	44	0	60	60	0	24	3	950,000$
9	Brayden Tracey (R)	0	X	X			100.00	69	65	79	70	65	57	57	61	50	59	58	61	55	44	44	0	57	58	0	21	2	863,333$
10	Valtteri Puustinen	0		X	X		100.00	73	64	93	65	64	62	63	61	50	56	62	63	59	44	44	0	60	58	0	23	1	842,500$
11	Josh Lopina (R)	0	X				100.00	76	72	86	61	72	38	35	51	64	51	46	62	44	44	44	0	57	52	0	22	3	878,333$
12	Derrick Pouliot	0				X	100.00	73	43	87	77	71	67	64	63	25	64	47	71	25	63	63	0	60	65	0	29	2	1,750,000$
13	Ryan Merkley (R)	0				X	100.00	61	41	92	76	64	67	76	69	25	50	48	66	25	47	47	0	60	60	0	22	1	863,333$
14	Hunter Drew	0			X	X	100.00	65	75	43	66	75	71	75	59	25	47	57	58	54	44	44	0	50	58	0	24	1	793,333$
15	Andreas Borgman	0				X	100.00	75	73	80	67	73	45	44	54	25	37	53	65	50	55	55	0	57	56	0	27	1	900,000$
16	Tarmo Reunanen	51				X	100.00	73	65	90	68	65	56	57	52	25	48	41	61	39	44	44	0	60	56	0	25	1	809,167$
17	Mitchell Vande Sompel	0				X	100.00	75	70	88	62	70	56	58	50	25	46	40	61	38	44	44	0	60	55	0	26	2	750,000$
18	Axel Andersson (R)	0				X	100.00	72	65	87	64	65	49	50	48	25	37	43	59	41	44	44	0	41	52	0	23	1	772,500$
Scratches
1	Maxim Golod (R)	0		X			100.00	69	61	89	68	61	45	44	49	50	47	46	58	44	44	44	0	19	51	0	22	1	793,333$

	TEAM AVERAGE						100.00	72	61	83	69	70	59	60	59	47	54	54	65	39	50	50	0	56	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	Lukas Dostal (R)	100.00	59	52	65	67	63	62	55	63	62	61	30	44	44	0	31	58	0	22	1	822,500$
2	Dylan Ferguson (R)	100.00	52	40	50	72	57	56	51	57	58	57	30	44	44	0	40	54	0	24	3	850,000$
Scratches
1	Ben Bishop	100.00	44	40	50	88	45	44	45	49	45	45	45	44	44	0	15	49	0	36	1	4,916,666$

	TEAM AVERAGE	100.00	52	44	55	76	55	54	50	56	55	54	35	44	44	0	29	54

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Neil Graham	64	63	69	72	55	52	90	CAN	36	3	700,000$

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	EG	HT	P/20	PSG	PSS	FW	FL	S1	S2	S3
1	Peyton Krebs	San Diego Gulls (ANA)	C/LW	72	25	38	63	-7	4	0	13	200	250	82	177	10.00%	13	1630	22.64	8	16	24	56	316	2	3	5	13	259	1	0	22.64	605	1	0	0.77	1	5	0	0	4	3	1
2	Nate Thompson	San Diego Gulls (ANA)	C/LW	72	24	33	57	9	44	0	166	149	253	46	184	9.49%	33	1425	19.80	9	10	19	58	280	2	0	2	6	199	3	5	19.80	424	1	1	0.80	0	5	0	0	5	6	3
3	Joachim Blichfeld	San Diego Gulls (ANA)	LW/RW	72	22	30	52	12	10	0	52	71	206	53	136	10.68%	12	1401	19.47	8	8	16	53	254	0	0	0	4	108	4	0	19.47	195	0	0	0.74	0	1	0	0	1	2	4
4	Sam Carrick	San Diego Gulls (ANA)	C	72	19	31	50	-7	102	10	230	201	232	60	188	8.19%	22	1400	19.45	5	11	16	62	246	2	0	2	8	126	4	1	19.45	1763	0	0	0.71	2	4	1	0	5	1	3
5	Max Jones	San Diego Gulls (ANA)	LW/RW	72	18	23	41	9	24	0	63	54	142	36	111	12.68%	12	818	11.37	2	6	8	32	228	0	0	0	5	109	6	2	11.37	59	0	0	1.00	2	3	0	0	4	2	3
6	Ryan Merkley	San Diego Gulls (ANA)	D	72	10	31	41	-14	24	0	57	76	109	37	68	9.17%	80	1702	23.64	6	12	18	66	284	0	0	0	0	213	2	0	0.00%	0	0	0	0.48	0	0	0	0	0	2	0
7	Derrick Pouliot	San Diego Gulls (ANA)	D	72	8	32	40	-11	64	0	194	94	121	36	90	6.61%	111	1709	23.74	4	14	18	77	282	0	1	1	0	212	0	0	0.00%	0	0	0	0.47	0	0	0	0	3	3	1
8	Benoit-Olivier Groulx	San Diego Gulls (ANA)	C	72	14	19	33	11	18	0	44	117	146	29	86	9.59%	15	948	13.18	0	0	0	0	0	0	0	0	0	0	2	2	13.18	1067	0	0	0.70	0	0	0	0	2	4	1
9	Thomas Novak	San Diego Gulls (ANA)	C	72	9	22	31	-14	2	0	16	169	147	39	112	6.12%	19	1087	15.11	0	0	0	6	40	0	0	0	3	112	2	0	15.11	1063	0	0	0.57	0	0	0	0	1	0	0
10	Jacob Perreault	San Diego Gulls (ANA)	C/RW	72	15	13	28	-8	26	0	76	85	137	44	106	10.95%	11	1315	18.27	4	2	6	21	212	0	1	1	0	17	2	0	18.27	148	1	0	0.43	0	1	0	0	0	1	1
11	Brayden Tracey	San Diego Gulls (ANA)	C/LW	72	10	13	23	-14	27	5	78	87	144	21	86	6.94%	10	1015	14.10	2	4	6	15	97	0	0	0	0	13	2	0	14.10	76	0	0	0.45	0	0	0	1	1	1	0
12	Valtteri Puustinen	San Diego Gulls (ANA)	LW/RW	72	10	11	21	-18	30	0	59	80	113	34	101	8.85%	8	897	12.46	0	0	0	5	15	0	0	0	0	2	1	1	12.46	57	0	0	0.47	1	1	0	0	0	1	2
13	Mitchell Vande Sompel	San Diego Gulls (ANA)	D	72	1	18	19	-1	60	0	120	31	22	8	33	4.55%	69	1216	16.89	1	6	7	7	145	0	1	1	0	64	0	0	0.00%	0	0	0	0.31	0	0	0	0	0	1	0
14	Hunter Drew	San Diego Gulls (ANA)	RW/D	72	4	11	15	5	90	10	171	24	35	15	36	11.43%	47	1194	16.59	0	1	1	2	13	0	0	0	0	102	0	2	16.59	15	0	0	0.25	0	0	0	2	0	0	2
15	Tarmo Reunanen	San Diego Gulls (ANA)	D	72	4	10	14	3	34	0	92	33	44	15	29	9.09%	80	1356	18.84	1	0	1	22	178	0	0	0	1	164	0	1	0.00%	0	0	0	0.21	0	0	0	0	0	0	2
16	Andreas Borgman	San Diego Gulls (ANA)	D	69	2	10	12	4	50	10	109	26	46	20	37	4.35%	72	1215	17.62	0	2	2	18	177	0	2	2	1	147	0	0	0.00%	0	0	0	0.20	0	0	1	1	0	0	1
17	Josh Lopina	San Diego Gulls (ANA)	C	68	4	5	9	6	2	0	17	38	25	6	20	16.00%	2	346	5.09	0	0	0	0	0	0	0	0	0	1	0	0	5.09	370	0	0	0.52	0	0	0	0	0	3	0
18	Wyatt Kalynuk	San Diego Gulls (ANA)	D	10	0	2	2	3	8	0	17	3	4	4	4	0.00%	7	170	17.03	0	0	0	2	4	0	0	0	0	3	0	0	0.00%	0	0	0	0.23	0	0	0	0	0	0	1
19	Ryan Murray	Anaheim Ducks	D	12	0	1	1	-4	2	0	7	8	10	3	5	0.00%	7	99	8.31	0	0	0	7	16	0	0	0	0	18	0	0	0.00%	0	0	0	0.20	0	0	0	0	0	0	0
20	Axel Andersson	San Diego Gulls (ANA)	D	53	0	1	1	-1	2	0	17	3	4	1	1	0.00%	11	179	3.39	0	1	1	2	23	0	0	0	0	29	0	0	0.00%	0	0	0	0.11	0	0	0	0	0	0	0
21	Maxim Golod	San Diego Gulls (ANA)	LW	4	0	0	0	-5	2	0	4	3	0	0	1	0.00%	0	46	11.56	0	0	0	0	0	0	0	0	0	0	0	0	11.56	3	0	0	0.00%	0	0	0	0	0	0	0
Team Total or Average				1296	199	354	553	-42	625	35	1602	1552	2190	589	1611	9.09%	641	21177	16.34	50	93	143	511	2820	6	8	14	41	1909	29	14	48.64%	5845	3	1	0.52	6	20	2	4	26	30	25

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	A	EG	PS %	PSA	ST	BG	S1	S2	S3
1	Lukas Dostal	San Diego Gulls (ANA)	50	25	20	3	0.903	2.76	2866	6	4	132	1362	1	1	0.706	17	49	7	5	0	3
2	Dylan Ferguson	San Diego Gulls (ANA)	27	7	14	3	0.905	3.05	1399	2	1	71	748	1	1	1.000	3	23	49	4	4	0
3	Ben Bishop	San Diego Gulls (ANA)	3	0	0	0	0.911	3.04	79	2	0	4	45	0	0	0.00%	0	0	16	0	0	0
Team Total or Average			80	32	34	6	0.904	2.86	4345	10	5	207	2155	2	2		20	72	72	9	4	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

Player Name	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Link
Andreas Borgman	San Diego Gulls (ANA)	D	27	1995-06-18	No	200 Lbs	6 ft0	No	No	No	1	Pro & Farm	900,000$	0$	0$	No			Link / NHL Link
Axel Andersson	San Diego Gulls (ANA)	D	23	2000-02-10	Yes	179 Lbs	6 ft0	No	No	No	1	Pro & Farm	772,500$	0$	0$	No			Link / NHL Link
Ben Bishop (1 Way Contract)	San Diego Gulls (ANA)	G	36	1986-11-21	No	209 Lbs	6 ft7	No	No	Yes	1	Pro & Farm	4,916,666$	3,916,666$	359,910$	No			Link / NHL Link
Benoit-Olivier Groulx	San Diego Gulls (ANA)	C	23	2000-02-05	Yes	195 Lbs	6 ft2	No	No	No	1	Pro & Farm	822,500$	0$	0$	No			Link / NHL Link
Brayden Tracey	San Diego Gulls (ANA)	C/LW	21	2001-05-28	Yes	176 Lbs	6 ft0	No	No	No	2	Pro & Farm	863,333$	0$	0$	No	863,333$		Link / NHL Link
Derrick Pouliot (1 Way Contract)	San Diego Gulls (ANA)	D	29	1994-01-16	No	196 Lbs	6 ft0	No	No	Yes	2	Pro & Farm	1,750,000$	750,000$	68,919$	No	1,750,000$		Link / NHL Link
Dylan Ferguson	San Diego Gulls (ANA)	G	24	1998-09-19	Yes	183 Lbs	6 ft2	No	No	No	3	Pro & Farm	850,000$	0$	0$	No	850,000$	850,000$	Link / NHL Link
Hunter Drew	San Diego Gulls (ANA)	RW/D	24	1998-10-21	No	192 Lbs	6 ft2	No	No	No	1	Pro & Farm	793,333$	0$	0$	No			Link / NHL Link
Jacob Perreault	San Diego Gulls (ANA)	C/RW	20	2002-04-15	Yes	192 Lbs	5 ft11	No	No	No	1	Pro & Farm	925,000$	0$	0$	No			Link / NHL Link
Joachim Blichfeld	San Diego Gulls (ANA)	LW/RW	24	1998-07-17	No	180 Lbs	6 ft2	No	No	No	3	Pro & Farm	950,000$	0$	0$	No	950,000$	950,000$	Link / NHL Link
Josh Lopina	San Diego Gulls (ANA)	C	22	2001-02-16	Yes	194 Lbs	6 ft2	No	No	No	3	Pro & Farm	878,333$	0$	0$	No	878,333$	878,333$	Link / NHL Link
Lukas Dostal	San Diego Gulls (ANA)	G	22	2000-06-22	Yes	174 Lbs	6 ft2	No	No	No	1	Pro & Farm	822,500$	0$	0$	No			Link / NHL Link
Max Jones (1 Way Contract)	San Diego Gulls (ANA)	LW/RW	25	1998-02-17	No	216 Lbs	6 ft3	No	No	Yes	2	Pro & Farm	1,295,000$	295,000$	27,108$	No	1,295,000$		Link / NHL Link
Maxim Golod	San Diego Gulls (ANA)	LW	22	2000-08-18	Yes	168 Lbs	5 ft11	No	No	No	1	Pro & Farm	793,333$	0$	0$	No			Link / NHL Link
Mitchell Vande Sompel	San Diego Gulls (ANA)	D	26	1997-02-11	No	198 Lbs	5 ft11	No	No	No	2	Pro & Farm	750,000$	0$	0$	No	750,000$		Link / NHL Link
Nate Thompson	San Diego Gulls (ANA)	C/LW	38	1984-10-05	No	205 Lbs	6 ft1	No	No	No	1	Pro & Farm	950,000$	0$	0$	No			Link / NHL Link
Peyton Krebs	San Diego Gulls (ANA)	C/LW	22	2001-01-26	Yes	180 Lbs	5 ft11	No	No	No	1	Pro & Farm	894,167$	0$	0$	No			Link / NHL Link
Ryan Merkley	San Diego Gulls (ANA)	D	22	2000-08-14	Yes	176 Lbs	5 ft11	No	No	No	1	Pro & Farm	863,333$	0$	0$	No			Link / NHL Link
Sam Carrick (1 Way Contract)	San Diego Gulls (ANA)	C	31	1992-02-04	No	205 Lbs	6 ft0	No	No	Yes	2	Pro & Farm	850,000$	0$	0$	No	850,000$		Link / NHL Link
Tarmo Reunanen	San Diego Gulls (ANA)	D	25	1998-03-01	No	179 Lbs	6 ft0	No	No	No	1	Pro & Farm	809,167$	0$	0$	No			Link / NHL Link
Thomas Novak	San Diego Gulls (ANA)	C	25	1997-04-28	No	179 Lbs	6 ft1	No	No	No	1	Pro & Farm	750,000$	0$	0$	No			Link / NHL Link
Valtteri Puustinen	San Diego Gulls (ANA)	LW/RW	23	1999-06-04	No	183 Lbs	5 ft9	No	No	No	1	Pro & Farm	842,500$	0$	0$	No			Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
22	25.18	189 Lbs	6 ft1	1.50	1,092,803$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Peyton Krebs	Sam Carrick	Jacob Perreault	40	1	1	3
2	Nate Thompson	Benoit-Olivier Groulx	Joachim Blichfeld	30	1	1	3
3	Brayden Tracey	Thomas Novak	Valtteri Puustinen	20	2	1	2
4	Max Jones	Josh Lopina	Hunter Drew	10	4	1	0

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Derrick Pouliot	Ryan Merkley	40	1	2	2
2	Andreas Borgman	Tarmo Reunanen	30	1	2	2
3	Mitchell Vande Sompel	Hunter Drew	20	1	2	2
4	Derrick Pouliot	Ryan Merkley	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Nate Thompson	Peyton Krebs	Max Jones	60	0	1	4
2	Peyton Krebs	Sam Carrick	Joachim Blichfeld	40	1	1	3

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Derrick Pouliot	Ryan Merkley	60	0	0	5
2	Andreas Borgman	Mitchell Vande Sompel	40	1	1	3

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Peyton Krebs	Nate Thompson	50	1	4	0
2	Sam Carrick	Peyton Krebs	50	2	3	0

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Derrick Pouliot	Ryan Merkley	60	2	2	1
2	Andreas Borgman	Hunter Drew	40	1	3	1

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Peyton Krebs	60	0	5	0	Derrick Pouliot	Ryan Merkley	60	1	2	2
2	Sam Carrick	40	1	4	0	Andreas Borgman	Hunter Drew	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Peyton Krebs	Nate Thompson	60	1	1	3
2	Sam Carrick	Peyton Krebs	40	2	1	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Derrick Pouliot	Ryan Merkley	60	1	2	2
2	Andreas Borgman	Mitchell Vande Sompel	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Nate Thompson	Peyton Krebs	Max Jones	Derrick Pouliot	Ryan Merkley

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Nate Thompson	Peyton Krebs	Max Jones	Derrick Pouliot	Ryan Merkley

Extra Forwards
Normal	PowerPlay	Penalty Kill
Joachim Blichfeld, Jacob Perreault, Thomas Novak	Joachim Blichfeld, Jacob Perreault	Joachim Blichfeld

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Ryan Merkley, Mitchell Vande Sompel, Derrick Pouliot	Derrick Pouliot	Derrick Pouliot, Mitchell Vande Sompel

Penalty Shots
Nate Thompson, Peyton Krebs, Sam Carrick, Max Jones, Joachim Blichfeld

Goalie
#1 : Lukas Dostal, #2 : Dylan Ferguson

Custom OT Lines Forwards
Nate Thompson, Peyton Krebs, Sam Carrick, Max Jones, Joachim Blichfeld, Jacob Perreault, Jacob Perreault, Thomas Novak, Benoit-Olivier Groulx, Hunter Drew, Valtteri Puustinen

Custom OT Lines Defensemen
Derrick Pouliot, Ryan Merkley, Andreas Borgman, Tarmo Reunanen, Mitchell Vande Sompel

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	Abbotsford Canucks	3	2	1	0	0	0	0	0	12	8	4	1	1	0	0	0	0	0	0	6	3	3	2	1	1	0	0	0	0	0	6	5	1	4	0.667	12	20	32	0	0	70	58	68	9	104	693	730	742	45	79	21	16	63	11	0	0.00%	8	1	87.50%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
2	Bakersfield Condors	3	0	3	0	0	0	0	0	7	14	-7	1	0	1	0	0	0	0	0	2	7	-5	2	0	2	0	0	0	0	0	5	7	-2	0	0.000	7	12	19	0	0	70	58	68	9	98	693	730	742	45	91	31	30	59	20	3	15.00%	14	3	78.57%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
3	Belleville Senators	2	1	1	0	0	0	0	0	2	2	0	1	0	1	0	0	0	0	0	1	2	-1	1	1	0	0	0	0	0	0	1	0	1	2	0.500	2	4	6	0	1	70	58	68	9	50	693	730	742	45	54	15	20	40	9	1	11.11%	10	0	100.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
4	Bridgeport Islanders	2	0	0	0	1	1	0	0	9	9	0	1	0	0	0	0	1	0	0	5	6	-1	1	0	0	0	1	0	0	0	4	3	1	3	0.750	9	14	23	0	0	70	58	68	9	53	693	730	742	45	54	14	12	43	10	2	20.00%	6	1	83.33%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
5	Calgary Wranglers	3	3	0	0	0	0	0	0	16	2	14	1	1	0	0	0	0	0	0	6	0	6	2	2	0	0	0	0	0	0	10	2	8	6	1.000	16	29	45	0	2	70	58	68	9	128	693	730	742	45	66	21	26	85	25	5	20.00%	12	2	83.33%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
6	Charlotte Checkers	2	0	1	0	0	1	0	0	5	7	-2	1	0	1	0	0	0	0	0	2	3	-1	1	0	0	0	0	1	0	0	3	4	-1	1	0.250	5	10	15	0	0	70	58	68	9	60	693	730	742	45	60	18	18	45	10	0	0.00%	8	1	87.50%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
7	Chicago Wolves	2	1	1	0	0	0	0	0	5	5	0	1	0	1	0	0	0	0	0	2	3	-1	1	1	0	0	0	0	0	0	3	2	1	2	0.500	5	10	15	0	0	70	58	68	9	66	693	730	742	45	64	10	12	42	11	3	27.27%	6	1	83.33%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
8	Cleveland Monsters	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	4	7	11	0	0	70	58	68	9	55	693	730	742	45	85	19	11	46	9	0	0.00%	3	1	66.67%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
9	Coachella Valley Firebirds	2	0	2	0	0	0	0	0	6	9	-3	1	0	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	6	10	16	1	0	70	58	68	9	64	693	730	742	45	75	21	14	46	10	2	20.00%	6	3	50.00%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
10	Colorado Eagles	2	1	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	1	4	-3	1	1	0	0	0	0	0	0	2	1	1	2	0.500	3	4	7	0	0	70	58	68	9	58	693	730	742	45	45	14	19	43	9	1	11.11%	8	0	100.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
11	Grand Rapids Griffins	2	2	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	3	2	1	1	1	0	0	0	0	0	0	3	0	3	4	1.000	6	12	18	0	1	70	58	68	9	57	693	730	742	45	46	13	25	55	10	3	30.00%	9	1	88.89%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
12	Hartford Wolf Pack	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	4	8	12	0	0	70	58	68	9	54	693	730	742	45	45	7	10	34	11	2	18.18%	5	1	80.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
13	Henderson Silver Knights	3	1	2	0	0	0	0	0	8	9	-1	1	0	1	0	0	0	0	0	2	4	-2	2	1	1	0	0	0	0	0	6	5	1	2	0.333	8	15	23	0	0	70	58	68	9	68	693	730	742	45	99	32	32	64	10	3	30.00%	15	3	80.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
14	Hershey Bears	2	1	1	0	0	0	0	0	4	3	1	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	1	2	-1	2	0.500	4	7	11	0	0	70	58	68	9	65	693	730	742	45	52	17	10	39	10	1	10.00%	5	0	100.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
15	Iowa Wild	2	1	1	0	0	0	0	0	8	7	1	1	1	0	0	0	0	0	0	5	2	3	1	0	1	0	0	0	0	0	3	5	-2	2	0.500	8	14	22	0	0	70	58	68	9	65	693	730	742	45	91	26	18	44	9	2	22.22%	9	3	66.67%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
16	Laval Rocket	2	0	1	0	0	0	0	1	3	8	-5	1	0	0	0	0	0	0	1	3	4	-1	1	0	1	0	0	0	0	0	0	4	-4	1	0.250	3	6	9	0	0	70	58	68	9	69	693	730	742	45	53	15	16	45	9	0	0.00%	7	4	42.86%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
17	Lehigh Valley Phantoms	2	0	2	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	3	6	9	0	0	70	58	68	9	46	693	730	742	45	51	24	16	43	8	1	12.50%	8	1	87.50%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
18	Manitoba Moose	2	0	1	0	0	0	1	0	5	7	-2	1	0	1	0	0	0	0	0	1	4	-3	1	0	0	0	0	0	1	0	4	3	1	2	0.500	5	6	11	0	0	70	58	68	9	64	693	730	742	45	43	14	24	44	2	0	0.00%	11	3	72.73%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
19	Milwaukee Admirals	2	0	1	0	0	0	0	1	3	5	-2	1	0	0	0	0	0	0	1	2	3	-1	1	0	1	0	0	0	0	0	1	2	-1	1	0.250	3	6	9	0	0	70	58	68	9	66	693	730	742	45	63	17	13	40	9	2	22.22%	4	1	75.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
20	Ontario Reign	3	1	2	0	0	0	0	0	9	13	-4	2	1	1	0	0	0	0	0	6	8	-2	1	0	1	0	0	0	0	0	3	5	-2	2	0.333	9	18	27	1	0	70	58	68	9	78	693	730	742	45	97	36	42	70	10	2	20.00%	21	3	85.71%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
21	Providence Bruins	2	0	1	0	0	1	0	0	5	8	-3	1	0	0	0	0	1	0	0	3	4	-1	1	0	1	0	0	0	0	0	2	4	-2	1	0.250	5	9	14	0	0	70	58	68	9	56	693	730	742	45	62	17	16	43	6	0	0.00%	8	1	87.50%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
22	Rochester Americans	2	1	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	2	1	1	1	0	1	0	0	0	0	0	1	4	-3	2	0.500	3	6	9	0	0	70	58	68	9	44	693	730	742	45	60	20	18	43	9	0	0.00%	9	2	77.78%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
23	Rockford IceHogs	2	0	2	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	2	3	-1	1	0	1	0	0	0	0	0	2	4	-2	0	0.000	4	6	10	0	0	70	58	68	9	60	693	730	742	45	57	20	23	39	6	0	0.00%	4	1	75.00%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
24	San Jose Barracuda	3	3	0	0	0	0	0	0	9	4	5	2	2	0	0	0	0	0	0	7	3	4	1	1	0	0	0	0	0	0	2	1	1	6	1.000	9	15	24	0	0	70	58	68	9	83	693	730	742	45	90	28	28	75	8	0	0.00%	14	1	92.86%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
25	Springfield Thunderbirds	3	3	0	0	0	0	0	0	8	2	6	1	1	0	0	0	0	0	0	3	1	2	2	2	0	0	0	0	0	0	5	1	4	6	1.000	8	14	22	0	1	70	58	68	9	86	693	730	742	45	90	38	30	61	11	3	27.27%	14	2	85.71%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
26	Syracuse Crunch	2	1	1	0	0	0	0	0	4	7	-3	1	0	1	0	0	0	0	0	0	5	-5	1	1	0	0	0	0	0	0	4	2	2	2	0.500	4	7	11	0	0	70	58	68	9	66	693	730	742	45	58	20	12	39	10	3	30.00%	4	0	100.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
27	Texas Stars	2	0	1	0	0	0	1	0	5	6	-1	1	0	0	0	0	0	1	0	3	2	1	1	0	1	0	0	0	0	0	2	4	-2	2	0.500	5	7	12	0	0	70	58	68	9	57	693	730	742	45	74	29	14	48	7	1	14.29%	7	0	100.00%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
28	Toronto Marlies	2	0	0	0	0	1	1	0	5	5	0	1	0	0	0	0	0	1	0	3	2	1	1	0	0	0	0	1	0	0	2	3	-1	3	0.750	5	7	12	0	0	70	58	68	9	51	693	730	742	45	84	14	28	53	7	1	14.29%	14	3	78.57%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
29	Tucson Roadrunners	3	2	0	0	1	0	0	0	18	10	8	2	1	0	0	1	0	0	0	11	8	3	1	1	0	0	0	0	0	0	7	2	5	6	1.000	18	31	49	0	0	70	58	68	9	114	693	730	742	45	99	23	20	62	15	4	26.67%	10	6	40.00%	1	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
30	Utica Comets	2	0	2	0	0	0	0	0	4	9	-5	1	0	1	0	0	0	0	0	2	6	-4	1	0	1	0	0	0	0	0	2	3	-1	0	0.000	4	8	12	0	0	70	58	68	9	68	693	730	742	45	65	23	25	53	5	0	0.00%	9	1	88.89%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
31	Wilkes-Barre/Scranton Penguins	4	2	1	0	1	0	0	0	15	12	3	3	2	0	0	1	0	0	0	14	9	5	1	0	1	0	0	0	0	0	1	3	-2	6	0.750	15	26	41	0	0	70	58	68	9	137	693	730	742	45	105	24	37	96	22	5	22.73%	14	3	78.57%	0	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
	Total	72	26	34	0	3	4	3	2	202	211	-9	36	13	15	0	2	2	2	2	109	114	-5	36	13	19	0	1	2	1	0	93	97	-4	70	0.486	202	354	556	2	5	70	58	68	9	2190	693	730	742	45	2157	641	635	1602	318	50	15.72%	282	53	81.21%	6	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
	_Since Last GM Reset	72	26	34	0	3	4	3	2	202	211	-9	36	13	15	0	2	2	2	2	109	114	-5	36	13	19	0	1	2	1	0	93	97	-4	70	0.486	202	354	556	2	5	70	58	68	9	2190	693	730	742	45	2157	641	635	1602	318	50	15.72%	282	53	81.21%	6	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
	_Vs Conference	37	16	17	0	1	0	2	1	121	108	13	18	8	7	0	1	0	1	1	62	58	4	19	8	10	0	0	0	1	0	59	50	9	39	0.527	121	211	332	2	3	70	58	68	9	1172	693	730	742	45	1134	342	337	836	163	30	18.40%	150	32	78.67%	6	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
	_Vs Division	20	12	8	0	1	0	0	0	67	59	8	9	6	3	0	1	0	0	0	33	31	2	11	6	5	0	0	0	0	0	34	28	6	26	0.650	67	119	186	2	2	70	58	68	9	623	693	730	742	45	597	190	188	462	94	15	15.96%	90	16	82.22%	2	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
72	70	W2	202	354	556	2190	2157	641	635	1602	2	5

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
72	26	34	3	4	3	2	202	211

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	13	15	2	2	2	2	109	114

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
36	13	19	1	2	1	0	93	97

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

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
318	50	15.72%	282	53	81.21%	6

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
693	730	742	45	70	58	68	9

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
1722	1163	1692	555	940	474

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
2 - 2022-10-12	13	Wilkes-Barre/Scranton Penguins	4	San Diego Gulls	7	BW			BoxScore
4 - 2022-10-14	28	San Diego Gulls	3	Henderson Silver Knights	4	AL			BoxScore
6 - 2022-10-16	44	Charlotte Checkers	3	San Diego Gulls	2	BL			BoxScore
9 - 2022-10-19	67	San Diego Gulls	2	Bakersfield Condors	3	AL			BoxScore
11 - 2022-10-21	78	Tucson Roadrunners	5	San Diego Gulls	6	BW	X		BoxScore
14 - 2022-10-24	100	San Jose Barracuda	1	San Diego Gulls	3	BW			BoxScore
16 - 2022-10-26	116	San Diego Gulls	4	Calgary Wranglers	2	AW			BoxScore
17 - 2022-10-27	128	San Diego Gulls	2	Abbotsford Canucks	4	AL			BoxScore
19 - 2022-10-29	143	Wilkes-Barre/Scranton Penguins	2	San Diego Gulls	3	BW			BoxScore
21 - 2022-10-31	162	Ontario Reign	3	San Diego Gulls	4	BW			BoxScore
23 - 2022-11-02	177	San Diego Gulls	1	Lehigh Valley Phantoms	4	AL			BoxScore
25 - 2022-11-04	194	San Diego Gulls	4	Abbotsford Canucks	1	AW			BoxScore
26 - 2022-11-05	205	Toronto Marlies	2	San Diego Gulls	3	BW	X	X	BoxScore
27 - 2022-11-06	212	San Diego Gulls	2	Springfield Thunderbirds	0	AW			BoxScore
31 - 2022-11-10	238	Utica Comets	6	San Diego Gulls	2	BL			BoxScore
33 - 2022-11-12	257	Chicago Wolves	3	San Diego Gulls	2	BL			BoxScore
35 - 2022-11-14	276	San Diego Gulls	3	Charlotte Checkers	4	AL	X		BoxScore
37 - 2022-11-16	289	San Diego Gulls	3	Chicago Wolves	2	AW			BoxScore
38 - 2022-11-17	301	Hershey Bears	1	San Diego Gulls	3	BW			BoxScore
41 - 2022-11-20	322	San Diego Gulls	3	Bakersfield Condors	4	AL			BoxScore
42 - 2022-11-21	334	Coachella Valley Firebirds	6	San Diego Gulls	4	BL			BoxScore
45 - 2022-11-24	357	Texas Stars	2	San Diego Gulls	3	BW	X	X	BoxScore
47 - 2022-11-26	372	San Diego Gulls	2	Rockford IceHogs	4	AL			BoxScore
49 - 2022-11-28	386	Springfield Thunderbirds	1	San Diego Gulls	3	BW			BoxScore
51 - 2022-11-30	403	San Diego Gulls	1	Milwaukee Admirals	2	AL			BoxScore
53 - 2022-12-02	421	Syracuse Crunch	5	San Diego Gulls	0	BL			BoxScore
55 - 2022-12-04	436	San Diego Gulls	1	Belleville Senators	0	AW			BoxScore
58 - 2022-12-07	453	San Diego Gulls	2	San Jose Barracuda	1	AW			BoxScore
60 - 2022-12-09	465	Lehigh Valley Phantoms	3	San Diego Gulls	2	BL			BoxScore
62 - 2022-12-11	485	Rockford IceHogs	3	San Diego Gulls	2	BL			BoxScore
66 - 2022-12-15	513	San Jose Barracuda	2	San Diego Gulls	4	BW			BoxScore
69 - 2022-12-18	537	San Diego Gulls	6	Calgary Wranglers	0	AW			BoxScore
70 - 2022-12-19	548	Grand Rapids Griffins	2	San Diego Gulls	3	BW			BoxScore
73 - 2022-12-22	576	Bridgeport Islanders	6	San Diego Gulls	5	BL	X		BoxScore
75 - 2022-12-24	588	San Diego Gulls	1	Rochester Americans	4	AL			BoxScore
76 - 2022-12-25	600	San Diego Gulls	1	Wilkes-Barre/Scranton Penguins	3	AL			BoxScore
77 - 2022-12-26	612	Cleveland Monsters	2	San Diego Gulls	1	BL			BoxScore
81 - 2022-12-30	638	San Diego Gulls	1	Hershey Bears	2	AL			BoxScore
82 - 2022-12-31	644	Bakersfield Condors	7	San Diego Gulls	2	BL			BoxScore
84 - 2023-01-02	669	San Diego Gulls	2	Providence Bruins	4	AL			BoxScore
85 - 2023-01-03	677	Colorado Eagles	4	San Diego Gulls	1	BL			BoxScore
89 - 2023-01-07	699	San Diego Gulls	2	Colorado Eagles	1	AW			BoxScore
90 - 2023-01-08	708	Hartford Wolf Pack	3	San Diego Gulls	2	BL			BoxScore
93 - 2023-01-11	730	San Diego Gulls	2	Utica Comets	3	AL			BoxScore
94 - 2023-01-12	740	Belleville Senators	2	San Diego Gulls	1	BL			BoxScore
97 - 2023-01-15	764	San Diego Gulls	2	Toronto Marlies	3	AL	X		BoxScore
98 - 2023-01-16	773	Abbotsford Canucks	3	San Diego Gulls	6	BW			BoxScore
100 - 2023-01-18	793	San Diego Gulls	3	Springfield Thunderbirds	1	AW			BoxScore
101 - 2023-01-19	802	Ontario Reign	5	San Diego Gulls	2	BL			BoxScore
103 - 2023-01-21	816	San Diego Gulls	3	Ontario Reign	5	AL			BoxScore
105 - 2023-01-23	834	San Diego Gulls	3	Cleveland Monsters	5	AL			BoxScore
106 - 2023-01-24	841	Henderson Silver Knights	4	San Diego Gulls	2	BL			BoxScore
109 - 2023-01-27	866	San Diego Gulls	3	Iowa Wild	5	AL			BoxScore
110 - 2023-01-28	872	Wilkes-Barre/Scranton Penguins	3	San Diego Gulls	4	BW	X		BoxScore
113 - 2023-01-31	898	Laval Rocket	4	San Diego Gulls	3	BL	X	X	BoxScore
114 - 2023-02-01	906	San Diego Gulls	3	Henderson Silver Knights	1	AW			BoxScore
117 - 2023-02-04	931	Calgary Wranglers	0	San Diego Gulls	6	BW			BoxScore
119 - 2023-02-06	949	San Diego Gulls	4	Syracuse Crunch	2	AW			BoxScore
121 - 2023-02-08	962	Tucson Roadrunners	3	San Diego Gulls	5	BW			BoxScore
123 - 2023-02-10	981	San Diego Gulls	3	Grand Rapids Griffins	0	AW			BoxScore
125 - 2023-02-12	994	San Diego Gulls	2	Coachella Valley Firebirds	3	AL			BoxScore
126 - 2023-02-13	1003	Iowa Wild	2	San Diego Gulls	5	BW			BoxScore
128 - 2023-02-15	1013	San Diego Gulls	2	Hartford Wolf Pack	4	AL			BoxScore
130 - 2023-02-17	1026	San Diego Gulls	0	Laval Rocket	4	AL			BoxScore
131 - 2023-02-18	1039	Milwaukee Admirals	3	San Diego Gulls	2	BL	X	X	BoxScore
132 - 2023-02-19	1046	San Diego Gulls	2	Texas Stars	4	AL			BoxScore
135 - 2023-02-22	1067	Manitoba Moose	4	San Diego Gulls	1	BL			BoxScore
136 - 2023-02-23	1082	San Diego Gulls	7	Tucson Roadrunners	2	AW			BoxScore
138 - 2023-02-25	1095	San Diego Gulls	4	Bridgeport Islanders	3	AW	X		BoxScore
139 - 2023-02-26	1104	Providence Bruins	4	San Diego Gulls	3	BL	X		BoxScore
140 - 2023-02-27	1115	San Diego Gulls	4	Manitoba Moose	3	AW	X	X	BoxScore
146 - 2023-03-05	1150	Rochester Americans	1	San Diego Gulls	2	BW			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	68,159	33,930
Attendance PCT	94.67%	94.25%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
0	2836 - 94.53%	80,403$	2,894,515$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
2,282,521$	1,615,499$	1,615,499$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	1,582,528$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	15,752$	0$

San Diego Gulls Stat Leaders (Regular Season)

Show or Hide Column

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Sam Carrick	119	34	52	86	-17	196	403	324	369	9.21%	33	2320	19.50	8	19	27	103	2	0	2	9	5	2	51.85	0	0.74	2	5
2	Nate Thompson	98	32	44	76	15	62	184	208	305	10.49%	43	1882	19.21	9	12	21	63	2	0	2	11	3	5	54.89	1	0.81	0	7
3	Jacob Perreault	144	30	42	72	-5	82	166	170	240	12.50%	20	2414	16.77	12	11	23	47	0	2	2	2	5	2	53.62	0	0.60	0	1
4	Benoit-Olivier Groulx	139	24	43	67	10	85	139	287	295	8.14%	26	2140	15.40	4	6	10	41	1	2	3	6	3	3	49.05	0	0.63	0	1
5	Peyton Krebs	72	25	38	63	-7	4	13	200	250	10.00%	13	1630	22.64	8	16	24	56	2	3	5	13	1	0	39.17	0	0.77	1	5

San Diego Gulls Goalies Stat Leaders (Regular Season)

Show or Hide Column

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	A	EG	PS %	PSA
1	Lukas Dostal	114	52	44	13	0.898	2.82	6594	16	6	310	3025	1	1	0.742	31
2	Dylan Ferguson	27	7	14	3	0.905	3.05	1399	2	1	71	748	1	1	1.000	3
3	Olle Eriksson Ek	12	3	8	0	0.888	3.87	574	0	0	37	329	1	0	0.00%	0
4	Ryan Miller	3	0	0	0	0.906	2.77	65	0	0	3	32	0	0	0.00%	0
5	Ben Bishop	3	0	0	0	0.911	3.04	79	2	0	4	45	0	0	0.00%	0

San Diego Gulls Career Team Stats

Show or Hide Column

	Overall											Home											Visitor
Year	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
Regular Season
2021	72	25	32	0	3	8	2	2	191	220	-29	36	15	10	0	2	5	2	2	94	94	0	36	10	22	0	1	3	0	0	97	126	-29	70	191	334	525	0	2	65	66	55	6	1827	592	615	587	46	2024	560	1128	1430	433	52	12.01%	489	79	83.84%	6	1061	2223	47.73%	1204	2470	48.74%	535	1065	50.23%	1652	1089	1799	581	917	446
2022	72	26	34	0	3	4	3	2	202	211	-9	36	13	15	0	2	2	2	2	109	114	-5	36	13	19	0	1	2	1	0	93	97	-4	70	202	354	556	2	5	70	58	68	9	2190	693	730	742	45	2157	641	635	1602	318	50	15.72%	282	53	81.21%	6	1156	2331	49.59%	1119	2325	48.13%	568	1139	49.87%	1722	1163	1692	555	940	474
Total Regular Season	144	51	66	0	6	12	5	4	393	431	-38	72	28	25	0	4	7	4	4	203	208	-5	72	23	41	0	2	5	1	0	190	223	-33	140	393	688	1081	2	7	135	124	123	15	4017	1285	1345	1329	91	4181	1201	1763	3032	751	102	13.58%	771	132	82.88%	12	2217	4554	48.68%	2323	4795	48.45%	1103	2204	50.05%	3375	2252	3492	1136	1857	921
Playoff
Total Playoff	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0.00%	0	0	0.00%	0	0	0	0.00%	0	0	0.00%	0	0	0.00%	0	0	0	0	0	0

San Diego Gulls 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

San Diego Gulls 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

	San Diego Gulls
	GP: 72 \| W: 32 \| L: 34 \| OTL: 6 \| P: 70 GF: 202 \| GA: 211 \| PP%: 15.72% \| PK%: 81.21% GM : Thomas Larsson \| Morale : 42 \| Team Overall : 58