Pittsburgh
Home
Roster
Scoring
Players Info
Lines
Team Stats
Schedule
Finance
Web Lines Editor

Game Center
	Baby Hawks 50-23-9, 109pts	1	FINAL	3	Manchots 43-32-7, 93pts

Team Stats
W1	Streak	L1
27-9-5	Home Record	23-14-4
23-14-4	Away Record	20-18-3
7-3-0	Last 10 Games	6-4-0
3.61	Goals Per Game	3.10
2.88	Goals Against Per Game	2.98
22.11%	Power Play Percentage	19.29%
86.05%	Penalty Kill Percentage	82.53%

Manchots
43-32-7, 93pts

FINAL

Monsters
49-24-9, 107pts

Team Stats
L1	Streak	W1
23-14-4	Home Record	24-13-4
20-18-3	Away Record	25-11-5
6-4-0	Last 10 Games	4-2-4
3.10	Goals Per Game	3.50
2.98	Goals Against Per Game	3.15
19.29%	Power Play Percentage	19.75%
82.53%	Penalty Kill Percentage	80.38%

Team Leaders
	Goals C.J. Suess 33	Assists Shane Pinto 40

	Points Shane Pinto 67	Plus/Minus Shane Pinto 12

	Wins Nico Daws 33	Save Percentage Daniel Vladar 0.923

Team Stats
Goals For 254 3.10 GFG	Shots For 2788 34.00 Avg	Power Play Percentage 19.3% 49 GF	Offensive Zone Start 41.4%
Goals Against 244 2.98 GAA	Shots Against 2743 33.45 Avg	Penalty Kill Percentage 82.5%% 40 GA	Defensive Zone Start 38.5%

Team Info
	General Manager	Raphael Belanger
	Division	Est
	Conference	Est
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	1,883
	Season Tickets	300
Roster Info
	Pro Team	23
	Farm Team	20
	Contract Limit	43 / 50
	Prospects	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

#	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 Average
1	Shane Pinto	X				100.00	69	43	76	77	72	58	46	61	72	74	54	78	24	45	45	0	50	61	0	20	2	925,000$
2	Mackenzie MacEachern		X	X		100.00	79	44	90	71	72	50	67	59	25	62	55	71	25	58	58	0	50	60	0	27	2	560,000$
3	Paul Carey		X			100.00	74	74	87	79	74	58	59	58	49	57	53	65	52	47	48	0	50	59	0	33	2	875,000$
4	C.J. Suess		X			100.00	75	69	89	66	69	65	66	61	50	56	61	64	58	44	44	0	50	59	0	27	2	700,000$
5	Simon Holmstrom (R)		X	X		100.00	81	75	95	63	75	63	64	61	50	61	57	67	54	44	44	0	50	59	0	20	2	894,167$
6	Vitaly Abramov (R)		X	X		100.00	68	65	86	67	65	58	58	60	49	58	57	62	56	44	44	0	50	57	0	23	2	600,000$
7	Ivan Chekhovich		X			100.00	76	74	95	60	67	58	53	58	54	58	51	66	47	44	44	0	50	56	0	22	2	776,667$
8	Joel Kellman	X				100.00	71	69	77	77	69	46	45	54	68	56	47	61	45	46	46	0	50	55	0	27	2	800,000$
9	Mikhail Vorobyev	X				100.00	53	41	88	69	72	48	67	49	83	53	50	65	24	47	47	0	50	55	0	24	1	650,000$
10	Tyler Steenbergen	X	X	X		100.00	70	66	93	67	66	63	67	53	69	41	58	61	58	44	44	0	50	55	0	23	1	650,000$
11	Blade Jenkins (R)	X	X			100.00	78	71	93	63	71	53	54	52	65	46	53	63	50	44	44	0	50	54	0	21	3	600,000$
12	Pavel Gogolev (R)		X			100.00	77	72	89	61	72	47	47	50	50	47	47	62	45	44	44	0	50	52	0	21	4	834,167$
13	Joel Hanley				X	100.00	79	44	96	72	69	58	65	57	25	48	48	75	25	60	60	0	50	63	0	30	2	1,020,000$
14	Ian Mitchell				X	100.00	61	40	99	76	63	58	80	56	25	50	47	73	25	48	48	0	50	61	0	22	2	925,000$
15	Dan Renouf				X	100.00	77	78	76	62	78	66	71	48	25	37	41	65	39	56	56	0	50	59	0	27	1	700,000$
16	Steven Santini				X	100.00	80	76	88	63	76	56	58	50	25	42	40	66	38	54	54	0	50	58	0	26	2	1,000,000$
17	Seth Barton (R)				X	100.00	80	74	93	67	74	41	40	50	25	43	41	64	39	44	44	0	50	55	0	22	1	925,000$
18	Clayton Phillips (R)				X	100.00	46	44	77	63	64	44	58	35	25	33	30	46	33	54	54	0	50	48	0	22	2	575,000$
Scratches
1	Tyler Weiss (R)		X			100.00	48	42	62	68	56	50	61	44	50	43	35	45	39	50	50	0	50	47	0	21	3	650,000$

	TEAM AVERAGE					100.00	71	61	87	68	70	55	59	53	47	51	49	64	41	48	48	0	50	56

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 Average
1	Nico Daws (R)	100.00	63	47	47	83	69	56	69	63	65	62	78	46	46	0	50	61	0	20	4	850,833$
2	Trent Miner (R)	100.00	44	42	53	70	45	44	45	49	45	45	45	44	44	0	50	48	0	20	3	560,000$
Scratches
1	Hunter Shepard (R)	100.00	44	41	51	73	45	44	45	49	45	45	45	44	44	0	50	48	0	25	2	950,000$
2	Tomas Vomacka (R)	100.00	44	71	64	64	43	38	39	41	36	39	38	54	50	0	50	47	0	22	2	525,000$

	TEAM AVERAGE	100.00	49	50	54	73	51	46	50	51	48	48	52	47	46	0	50	51

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

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	FT	S1	S2	S3
1	Shane Pinto	Manchots (Pit)	C	67	27	40	67	12	22	0	85	204	256	79	178	10.55%	24	1526	22.78	0	13	13	41	164	0	1	1	3	154	3	3	55.82%	1709	0	0	0.88	2	10	0	0	0	6	4	1
2	C.J. Suess	Manchots (Pit)	LW	82	33	31	64	-4	24	0	145	103	298	80	218	11.07%	25	1599	19.51	6	6	12	46	191	1	2	3	6	106	2	2	44.19%	172	0	0	0.80	2	4	0	0	0	6	3	3
3	Mackenzie MacEachern	Manchots (Pit)	LW/RW	82	25	34	59	8	18	0	101	100	224	61	159	11.16%	16	1530	18.67	4	5	9	36	204	0	0	0	3	196	6	3	40.15%	137	0	0	0.77	2	10	0	0	0	3	1	3
4	Jamie Drysdale	Pittsburgh	D	71	13	39	52	3	14	0	67	145	128	37	72	10.16%	98	1764	24.85	9	7	16	71	200	0	1	1	3	175	4	0	0.00%	0	0	1	0.59	0	0	0	0	0	3	2	3
5	Simon Holmstrom	Manchots (Pit)	LW/RW	81	18	32	50	10	56	20	118	83	172	36	110	10.47%	14	1399	17.28	4	8	12	30	210	2	0	2	5	114	5	0	41.77%	158	0	0	0.71	0	5	1	1	2	2	7	4
6	Vitaly Abramov	Manchots (Pit)	LW/RW	82	25	24	49	-5	22	0	87	110	259	62	163	9.65%	16	1489	18.17	7	8	15	43	211	0	0	0	0	0	3	1	39.29%	84	0	0	0.66	1	1	0	0	0	3	2	3
7	Paul Carey	Manchots (Pit)	LW	82	14	34	48	-1	33	5	134	149	270	70	186	5.19%	18	1321	16.12	1	4	5	11	51	0	0	0	1	15	4	0	37.40%	123	0	0	0.73	1	2	0	1	0	1	4	1
8	Ian Mitchell	Manchots (Pit)	D	82	12	36	48	-8	12	0	48	97	146	47	113	8.22%	114	1701	20.74	6	10	16	67	199	0	0	0	2	175	2	0	0.00%	0	0	0	0.56	0	0	0	0	0	3	0	2
9	Joel Hanley	Manchots (Pit)	D	82	7	27	34	-6	47	5	176	82	107	34	80	6.54%	121	1747	21.31	4	4	8	39	214	0	1	1	3	176	1	0	0.00%	0	1	0	0.39	0	0	0	0	0	0	1	3
10	Joel Kellman	Manchots (Pit)	C	82	14	20	34	0	44	0	123	190	135	33	109	10.37%	10	1372	16.74	2	5	7	8	108	0	0	0	0	7	2	1	51.97%	1601	0	0	0.50	0	0	0	0	0	1	5	3
11	Mikhail Vorobyev	Manchots (Pit)	C	82	10	24	34	-5	12	0	19	144	156	56	127	6.41%	5	1318	16.08	0	6	6	10	84	0	1	1	2	41	0	0	58.05%	1497	0	0	0.52	0	0	0	0	0	0	1	2
12	Tyler Steenbergen	Manchots (Pit)	C/LW/RW	82	14	15	29	-5	16	0	60	63	173	53	121	8.09%	8	1247	15.22	0	0	0	1	11	0	0	0	0	0	1	0	63.41%	82	0	0	0.46	1	1	0	0	0	1	1	3
13	Steven Santini	Manchots (Pit)	D	82	3	22	25	10	60	10	136	39	55	16	56	5.45%	87	1291	15.76	1	0	1	7	29	0	1	1	0	50	2	0	0.00%	0	0	0	0.39	0	0	0	1	1	0	1	1
14	Ivan Chekhovich	Manchots (Pit)	LW	82	5	12	17	-3	20	10	47	38	83	30	64	6.02%	12	630	7.68	0	4	4	3	10	0	0	0	3	79	0	0	47.66%	107	0	0	0.54	0	0	2	0	0	0	0	1
15	Dan Renouf	Manchots (Pit)	D	82	7	9	16	-4	79	15	160	29	56	17	36	12.50%	79	1461	17.83	1	1	2	11	111	0	0	0	0	72	1	1	0.00%	0	0	0	0.22	0	0	0	1	2	0	0	1
16	Seth Barton	Manchots (Pit)	D	82	2	8	10	11	37	5	83	24	29	11	17	6.90%	62	879	10.73	0	0	0	2	5	0	0	0	0	56	0	0	0.00%	0	0	0	0.23	0	0	0	0	0	0	0	0
17	Blade Jenkins	Manchots (Pit)	C/LW	78	4	5	9	-1	8	0	44	61	42	12	41	9.52%	4	518	6.65	0	0	0	0	1	0	0	0	0	48	0	0	52.68%	541	0	0	0.35	0	0	0	0	0	0	0	2
18	Pavel Gogolev	Manchots (Pit)	LW	40	1	4	5	0	2	0	5	1	11	3	7	9.09%	0	101	2.53	0	1	1	3	20	0	0	0	0	0	0	0	45.83%	48	0	0	0.99	0	0	0	0	0	0	0	0
19	Clayton Phillips	Manchots (Pit)	D	5	0	0	0	2	0	0	2	0	0	0	0	0.00%	3	89	17.98	0	0	0	0	0	0	0	0	0	2	0	0	0.00%	0	0	0	0.00%	0	0	0	0	0	0	0	0
Team Total or Average				1408	234	416	650	14	526	70	1640	1662	2600	737	1857	9.00%	716	22992	16.33	45	82	127	429	2032	3	7	10	31	1472	36	11	53.38%	6259	1	1	0.57	9	33	3	4	5	29	32	36

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	Nico Daws	Manchots (Pit)	58	33	17	6	0.921	2.64	3368	6	2	148	1880	3	1	0.703	37	58	0	7	9	2
2	Trent Miner	Manchots (Pit)	29	10	14	1	0.894	3.40	1449	2	1	82	777	1	0	0.00%	0	24	58	3	1	1
3	Daniel Vladar	Pittsburgh	4	2	2	0	0.923	3.01	239	0	0	12	155	0	0	0.00%	0	4	13	0	0	1
4	Hunter Shepard	Manchots (Pit)	5	0	1	0	0.906	3.08	156	0	0	8	85	0	0	0.00%	0	0	24	0	0	0
Team Total or Average			96	45	34	7	0.914	2.88	5214	8	3	250	2897	4	1		37	86	95	10	10	4

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	Salary Year 4	Link
Blade Jenkins	Manchots (Pit)	C/LW	21	2000-08-11	Yes	194 Lbs	6 ft1	Yes	No	No	3	Pro & Farm	600,000$	0$	0$	No	600,000$	600,000$		Link
C.J. Suess (1 Way Contract)	Manchots (Pit)	LW	27	1994-03-16	No	190 Lbs	5 ft11	No	No	Yes	2	Pro & Farm	700,000$	0$	0$	No	700,000$			Link
Clayton Phillips	Manchots (Pit)	D	22	1999-09-09	Yes	182 Lbs	5 ft10	No	No	No	2	Pro & Farm	575,000$	0$	0$	No	575,000$			Link
Dan Renouf (1 Way Contract)	Manchots (Pit)	D	27	1994-06-01	No	198 Lbs	6 ft3	No	No	Yes	1	Pro & Farm	700,000$	0$	0$	No				Link
Hunter Shepard	Manchots (Pit)	G	25	1995-11-07	Yes	201 Lbs	6 ft0	No	No	Yes	2	Pro & Farm	950,000$	0$	0$	No	950,000$			Link
Ian Mitchell	Manchots (Pit)	D	22	1999-01-18	No	173 Lbs	5 ft11	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Link
Ivan Chekhovich	Manchots (Pit)	LW	22	1999-01-04	No	187 Lbs	5 ft11	No	No	No	2	Pro & Farm	776,667$	0$	0$	No	776,667$			Link
Joel Hanley (1 Way Contract)	Manchots (Pit)	D	30	1991-06-08	No	190 Lbs	5 ft11	No	No	Yes	2	Pro & Farm	1,020,000$	120,000$	0$	No	1,020,000$			Link
Joel Kellman (1 Way Contract)	Manchots (Pit)	C	27	1994-05-25	No	192 Lbs	5 ft11	No	No	Yes	2	Pro & Farm	800,000$	0$	0$	No	800,000$			Link
Mackenzie MacEachern (1 Way Contract)	Manchots (Pit)	LW/RW	27	1994-03-08	No	190 Lbs	6 ft2	No	No	Yes	2	Pro & Farm	560,000$	0$	0$	No	560,000$			Link
Mikhail Vorobyev	Manchots (Pit)	C	24	1997-01-04	No	194 Lbs	6 ft2	No	No	Yes	1	Pro & Farm	650,000$	0$	0$	No				Link
Nico Daws	Manchots (Pit)	G	20	2000-12-22	Yes	203 Lbs	6 ft4	No	No	No	4	Pro & Farm	850,833$	0$	0$	No	850,833$	850,833$	850,833$	Link
Paul Carey (1 Way Contract)	Manchots (Pit)	LW	33	1988-09-24	No	200 Lbs	6 ft1	No	No	Yes	2	Pro & Farm	875,000$	0$	0$	No	875,000$			Link
Pavel Gogolev	Manchots (Pit)	LW	21	2000-02-19	Yes	198 Lbs	6 ft1	No	No	No	4	Pro & Farm	834,167$	0$	0$	No	834,167$	834,167$	834,167$	Link
Seth Barton	Manchots (Pit)	D	22	1999-08-18	Yes	196 Lbs	6 ft3	Yes	No	No	1	Pro & Farm	925,000$	0$	0$	No				Link
Shane Pinto	Manchots (Pit)	C	20	2000-11-12	No	192 Lbs	6 ft2	No	No	No	2	Pro & Farm	925,000$	0$	0$	No	925,000$			Link
Simon Holmstrom	Manchots (Pit)	LW/RW	20	2001-05-24	Yes	202 Lbs	6 ft2	No	No	No	2	Pro & Farm	894,167$	0$	0$	No	894,167$			Link
Steven Santini (1 Way Contract)	Manchots (Pit)	D	26	1995-03-07	No	205 Lbs	6 ft2	No	No	Yes	2	Pro & Farm	1,000,000$	100,000$	0$	No	1,000,000$			Link
Tomas Vomacka	Manchots (Pit)	G	22	1999-05-02	Yes	165 Lbs	6 ft3	No	No	No	2	Pro & Farm	525,000$	0$	0$	No	525,000$			Link
Trent Miner	Manchots (Pit)	G	20	2001-02-05	Yes	185 Lbs	6 ft1	No	No	No	3	Pro & Farm	560,000$	0$	0$	No	560,000$	560,000$		Link
Tyler Steenbergen	Manchots (Pit)	C/LW/RW	23	1998-01-07	No	188 Lbs	5 ft10	No	No	No	1	Pro & Farm	650,000$	0$	0$	No				Link
Tyler Weiss	Manchots (Pit)	LW	21	2000-01-03	Yes	151 Lbs	5 ft11	No	No	No	3	Pro & Farm	650,000$	0$	0$	No	650,000$	650,000$		Link
Vitaly Abramov	Manchots (Pit)	LW/RW	23	1998-05-08	Yes	181 Lbs	5 ft10	Yes	No	No	2	Pro & Farm	600,000$	0$	0$	No	600,000$			Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
23	23.70	189 Lbs	6 ft1	2.13	762,862$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Mackenzie MacEachern	Shane Pinto	Simon Holmstrom	40	1	2	2
2	Paul Carey	Joel Kellman	Vitaly Abramov	30	1	2	2
3	C.J. Suess	Tyler Steenbergen	Ivan Chekhovich	20	1	2	2
4	Ivan Chekhovich	Mikhail Vorobyev	Shane Pinto	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Joel Hanley	Ian Mitchell	40	1	2	2
2	Dan Renouf	Steven Santini	30	1	2	2
3	Seth Barton	Clayton Phillips	20	1	2	2
4	Joel Hanley	Ian Mitchell	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Mackenzie MacEachern	Shane Pinto	Simon Holmstrom	60	1	2	2
2	Paul Carey	Joel Kellman	Vitaly Abramov	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Joel Hanley	Ian Mitchell	60	1	2	2
2	Dan Renouf	Steven Santini	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Shane Pinto	Mackenzie MacEachern	60	1	2	2
2	Simon Holmstrom	Paul Carey	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Joel Hanley	Ian Mitchell	60	1	2	2
2	Dan Renouf	Steven Santini	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Shane Pinto	60	1	2	2	Joel Hanley	Ian Mitchell	60	1	2	2
2	Mackenzie MacEachern	40	1	2	2	Dan Renouf	Steven Santini	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Shane Pinto	Mackenzie MacEachern	60	1	2	2
2	Simon Holmstrom	Paul Carey	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Joel Hanley	Ian Mitchell	60	1	2	2
2	Dan Renouf	Steven Santini	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Mackenzie MacEachern	Shane Pinto	Simon Holmstrom	Joel Hanley	Ian Mitchell

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Mackenzie MacEachern	Shane Pinto	Simon Holmstrom	Joel Hanley	Ian Mitchell

Extra Forwards
Normal	PowerPlay	Penalty Kill
Blade Jenkins, Pavel Gogolev, C.J. Suess	Blade Jenkins, Pavel Gogolev	C.J. Suess

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Seth Barton, Clayton Phillips, Dan Renouf	Seth Barton	Clayton Phillips, Dan Renouf

Penalty Shots
Shane Pinto, Mackenzie MacEachern, Simon Holmstrom, Paul Carey, C.J. Suess

Goalie
#1 : Nico Daws, #2 : Trent Miner

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	Admirals	2	1	1	0	0	0	0	0	3	3	0	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	0	2	-2	2	0.500	3	6	9	0	0	96	85	65	12	60	930	930	889	72	57	13	14	32	5	1	20.00%	7	1	85.71%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
2	Baby Hawks	2	1	1	0	0	0	0	0	7	7	0	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	4	6	-2	2	0.500	7	12	19	0	0	96	85	65	12	65	930	930	889	72	73	17	18	58	5	0	0.00%	6	3	50.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
3	Bears	3	0	2	0	0	0	0	1	8	11	-3	1	0	1	0	0	0	0	0	1	2	-1	2	0	1	0	0	0	0	1	7	9	-2	1	0.167	8	16	24	0	0	96	85	65	12	117	930	930	889	72	89	17	14	48	16	3	18.75%	7	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
4	Bruins	3	1	2	0	0	0	0	0	9	13	-4	2	1	1	0	0	0	0	0	8	8	0	1	0	1	0	0	0	0	0	1	5	-4	2	0.333	9	16	25	0	0	96	85	65	12	89	930	930	889	72	103	20	31	62	7	3	42.86%	13	3	76.92%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
5	Cabaret Lady Mary Ann	3	3	0	0	0	0	0	0	15	6	9	1	1	0	0	0	0	0	0	6	4	2	2	2	0	0	0	0	0	0	9	2	7	6	1.000	15	27	42	0	0	96	85	65	12	167	930	930	889	72	114	20	23	91	4	1	25.00%	9	1	88.89%	1	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
6	Caroline	4	2	2	0	0	0	0	0	11	9	2	2	1	1	0	0	0	0	0	5	5	0	2	1	1	0	0	0	0	0	6	4	2	4	0.500	11	19	30	0	0	96	85	65	12	132	930	930	889	72	141	39	26	64	9	2	22.22%	13	1	92.31%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
7	Chiefs	2	1	1	0	0	0	0	0	10	9	1	1	1	0	0	0	0	0	0	5	3	2	1	0	1	0	0	0	0	0	5	6	-1	2	0.500	10	16	26	0	0	96	85	65	12	70	930	930	889	72	59	16	6	41	8	2	25.00%	3	2	33.33%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
8	Chill	2	0	0	0	1	0	1	0	10	8	2	1	0	0	0	0	0	1	0	4	3	1	1	0	0	0	1	0	0	0	6	5	1	4	1.000	10	16	26	0	0	96	85	65	12	72	930	930	889	72	84	27	14	66	7	0	0.00%	6	2	66.67%	1	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
9	Comets	2	0	1	0	0	1	0	0	4	6	-2	1	0	1	0	0	0	0	0	3	4	-1	1	0	0	0	0	1	0	0	1	2	-1	1	0.250	4	7	11	0	0	96	85	65	12	57	930	930	889	72	69	19	10	34	8	1	12.50%	4	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
10	Cougars	3	2	0	0	0	0	0	1	12	9	3	1	0	0	0	0	0	0	1	5	6	-1	2	2	0	0	0	0	0	0	7	3	4	5	0.833	12	21	33	0	0	96	85	65	12	115	930	930	889	72	93	17	16	53	12	2	16.67%	8	1	87.50%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
11	Crunch	3	2	0	0	0	0	0	1	11	8	3	1	0	0	0	0	0	0	1	2	3	-1	2	2	0	0	0	0	0	0	9	5	4	5	0.833	11	21	32	0	0	96	85	65	12	112	930	930	889	72	80	26	22	61	9	4	44.44%	11	2	81.82%	1	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
12	Heat	2	1	1	0	0	0	0	0	5	5	0	1	0	1	0	0	0	0	0	1	2	-1	1	1	0	0	0	0	0	0	4	3	1	2	0.500	5	10	15	0	0	96	85	65	12	65	930	930	889	72	73	19	14	50	4	2	50.00%	7	1	85.71%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
13	Jayhawks	2	1	1	0	0	0	0	0	4	6	-2	1	0	1	0	0	0	0	0	2	5	-3	1	1	0	0	0	0	0	0	2	1	1	2	0.500	4	8	12	0	0	96	85	65	12	70	930	930	889	72	60	24	8	45	8	3	37.50%	4	1	75.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
14	Las Vegas	2	0	1	0	0	1	0	0	6	9	-3	1	0	1	0	0	0	0	0	4	6	-2	1	0	0	0	0	1	0	0	2	3	-1	1	0.250	6	12	18	0	0	96	85	65	12	64	930	930	889	72	63	16	16	49	6	1	16.67%	7	3	57.14%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
15	Marlies	3	1	2	0	0	0	0	0	6	13	-7	2	0	2	0	0	0	0	0	3	12	-9	1	1	0	0	0	0	0	0	3	1	2	2	0.333	6	11	17	0	0	96	85	65	12	120	930	930	889	72	80	18	38	77	10	2	20.00%	6	1	83.33%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
16	Minnesota	2	0	1	0	0	0	1	0	6	6	0	1	0	0	0	0	0	1	0	2	1	1	1	0	1	0	0	0	0	0	4	5	-1	2	0.500	6	9	15	0	0	96	85	65	12	67	930	930	889	72	70	22	10	39	3	0	0.00%	5	1	80.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
17	Monarchs	2	2	0	0	0	0	0	0	12	6	6	1	1	0	0	0	0	0	0	8	3	5	1	1	0	0	0	0	0	0	4	3	1	4	1.000	12	22	34	0	0	96	85	65	12	123	930	930	889	72	67	22	2	63	5	2	40.00%	1	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
18	Monsters	4	2	2	0	0	0	0	0	13	14	-1	2	2	0	0	0	0	0	0	10	3	7	2	0	2	0	0	0	0	0	3	11	-8	4	0.500	13	23	36	0	0	96	85	65	12	128	930	930	889	72	116	50	8	78	17	1	5.88%	4	1	75.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
19	Monsters	2	0	2	0	0	0	0	0	4	8	-4	1	0	1	0	0	0	0	0	3	4	-1	1	0	1	0	0	0	0	0	1	4	-3	0	0.000	4	7	11	0	0	96	85	65	12	57	930	930	889	72	77	19	22	44	8	0	0.00%	10	1	90.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
20	Oceanics	2	1	0	0	0	0	1	0	10	5	5	1	0	0	0	0	0	1	0	2	1	1	1	1	0	0	0	0	0	0	8	4	4	4	1.000	10	16	26	0	0	96	85	65	12	72	930	930	889	72	63	21	20	39	9	3	33.33%	3	1	66.67%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
21	Oil Kings	2	0	2	0	0	0	0	0	6	10	-4	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	6	11	17	0	0	96	85	65	12	72	930	930	889	72	76	15	12	41	6	0	0.00%	6	2	66.67%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
22	Phantoms	3	2	0	0	1	0	0	0	11	4	7	2	2	0	0	0	0	0	0	7	1	6	1	0	0	0	1	0	0	0	4	3	1	6	1.000	11	22	33	0	1	96	85	65	12	107	930	930	889	72	85	29	23	47	14	3	21.43%	8	1	87.50%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
23	Rocket	3	1	1	0	0	0	0	1	8	10	-2	1	0	0	0	0	0	0	1	4	5	-1	2	1	1	0	0	0	0	0	4	5	-1	3	0.500	8	16	24	0	0	96	85	65	12	85	930	930	889	72	96	37	20	67	9	2	22.22%	9	1	88.89%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
24	Seattle	2	1	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	1	0	1	1	0	1	0	0	0	0	0	2	5	-3	2	0.500	3	6	9	0	1	96	85	65	12	68	930	930	889	72	71	10	8	49	6	1	16.67%	4	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
25	Senators	3	1	2	0	0	0	0	0	6	6	0	2	1	1	0	0	0	0	0	4	3	1	1	0	1	0	0	0	0	0	2	3	-1	2	0.333	6	12	18	0	0	96	85	65	12	90	930	930	889	72	92	31	26	55	11	1	9.09%	8	2	75.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
26	Sharks	2	0	1	0	0	0	1	0	7	7	0	1	0	0	0	0	0	1	0	4	3	1	1	0	1	0	0	0	0	0	3	4	-1	2	0.500	7	11	18	0	0	96	85	65	12	64	930	930	889	72	80	25	14	38	1	0	0.00%	7	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
27	Sound Tigers	4	1	2	0	0	0	0	1	8	12	-4	2	0	1	0	0	0	0	1	3	6	-3	2	1	1	0	0	0	0	0	5	6	-1	3	0.375	8	15	23	0	0	96	85	65	12	117	930	930	889	72	139	56	10	76	10	1	10.00%	5	0	100.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
28	Spiders	4	2	1	0	0	0	1	0	12	9	3	2	2	0	0	0	0	0	0	6	3	3	2	0	1	0	0	0	1	0	6	6	0	6	0.750	12	20	32	0	0	96	85	65	12	127	930	930	889	72	134	32	32	81	12	3	25.00%	16	4	75.00%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
29	Stars	2	1	1	0	0	0	0	0	6	7	-1	1	0	1	0	0	0	0	0	3	5	-2	1	1	0	0	0	0	0	0	3	2	1	2	0.500	6	9	15	1	0	96	85	65	12	46	930	930	889	72	81	23	25	45	3	1	33.33%	7	1	85.71%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
30	Thunder	3	3	0	0	0	0	0	0	10	4	6	2	2	0	0	0	0	0	0	6	2	4	1	1	0	0	0	0	0	0	4	2	2	6	1.000	10	15	25	0	0	96	85	65	12	77	930	930	889	72	103	30	36	63	12	3	25.00%	13	1	92.31%	0	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
31	Wolf Pack	4	2	1	0	1	0	0	0	11	9	2	2	1	0	0	1	0	0	0	7	5	2	2	1	1	0	0	0	0	0	4	4	0	6	0.750	11	22	33	0	1	96	85	65	12	113	930	930	889	72	155	49	24	92	10	1	10.00%	12	2	83.33%	1	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
	Total	82	35	32	0	3	2	5	5	254	244	10	41	18	14	0	1	0	4	4	128	115	13	41	17	18	0	2	2	1	1	126	129	-3	93	0.567	254	454	708	1	3	96	85	65	12	2788	930	930	889	72	2743	779	562	1748	254	49	19.29%	229	40	82.53%	4	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
	_Since Last GM Reset	82	35	32	0	3	2	5	5	254	244	10	41	18	14	0	1	0	4	4	128	115	13	41	17	18	0	2	2	1	1	126	129	-3	93	0.567	254	454	708	1	3	96	85	65	12	2788	930	930	889	72	2743	779	562	1748	254	49	19.29%	229	40	82.53%	4	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566
	_Vs Conference	44	19	16	0	3	0	4	2	136	124	12	24	13	6	0	1	0	3	1	76	56	20	20	6	10	0	2	0	1	1	60	68	-8	54	0.614	136	243	379	0	2	96	85	65	12	1476	930	930	889	72	1447	440	306	917	146	27	18.49%	116	19	83.62%	2	1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%	2096	1452	1794	590	1093	566

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
82	93	L1	254	454	708	2788	2743	779	562	1748	1	3

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	35	32	3	2	5	5	254	244

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	18	14	1	0	4	4	128	115

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	17	18	2	2	1	1	126	129

Last 10 Games
W	L	OTW	OTL	SOW	SOL
6	4	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
254	49	19.29%	229	40	82.53%	4

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
930	930	889	72	96	85	65	12

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1528	2790	54.77%	1344	2589	51.91%	737	1353	54.47%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
2096	1452	1794	590	1093	566

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
7 - 2022-10-13	11	Jayhawks	5	Manchots	2	BL			BoxScore
9 - 2022-10-15	31	Thunder	1	Manchots	3	BW			BoxScore
11 - 2022-10-17	42	Manchots	2	Rocket	4	AL			BoxScore
14 - 2022-10-20	62	Monarchs	3	Manchots	8	BW			BoxScore
16 - 2022-10-22	82	Manchots	1	Monsters	4	AL			BoxScore
18 - 2022-10-24	94	Manchots	3	Oil Kings	5	AL			BoxScore
19 - 2022-10-25	104	Manchots	4	Heat	3	AW			BoxScore
22 - 2022-10-28	125	Manchots	1	Comets	2	AL	X		BoxScore
23 - 2022-10-29	137	Manchots	2	Seattle	5	AL			BoxScore
26 - 2022-11-01	147	Bruins	2	Manchots	4	BW			BoxScore
27 - 2022-11-02	160	Manchots	3	Crunch	2	AW			BoxScore
30 - 2022-11-05	184	Seattle	0	Manchots	1	BW			BoxScore
34 - 2022-11-09	208	Manchots	3	Bears	4	AL			BoxScore
36 - 2022-11-11	221	Manchots	3	Marlies	1	AW			BoxScore
37 - 2022-11-12	229	Manchots	2	Rocket	1	AW			BoxScore
40 - 2022-11-15	251	Marlies	5	Manchots	2	BL			BoxScore
42 - 2022-11-17	268	Manchots	4	Minnesota	5	AL			BoxScore
44 - 2022-11-19	276	Manchots	8	Oceanics	4	AW			BoxScore
45 - 2022-11-20	290	Manchots	4	Baby Hawks	6	AL			BoxScore
48 - 2022-11-23	306	Heat	2	Manchots	1	BL			BoxScore
50 - 2022-11-25	324	Manchots	4	Phantoms	3	AW	X		BoxScore
51 - 2022-11-26	335	Marlies	7	Manchots	1	BL			BoxScore
54 - 2022-11-29	352	Caroline	3	Manchots	2	BL			BoxScore
56 - 2022-12-01	368	Las Vegas	6	Manchots	4	BL			BoxScore
58 - 2022-12-03	384	Chiefs	3	Manchots	5	BW			BoxScore
61 - 2022-12-06	404	Monsters	2	Manchots	5	BW			BoxScore
64 - 2022-12-09	426	Manchots	6	Crunch	3	AW			BoxScore
65 - 2022-12-10	437	Crunch	3	Manchots	2	BL	X	X	BoxScore
67 - 2022-12-12	449	Stars	5	Manchots	3	BL			BoxScore
70 - 2022-12-15	474	Manchots	4	Cabaret Lady Mary Ann	1	AW			BoxScore
73 - 2022-12-18	498	Manchots	0	Caroline	2	AL			BoxScore
75 - 2022-12-20	511	Wolf Pack	2	Manchots	3	BW			BoxScore
77 - 2022-12-22	526	Caroline	2	Manchots	3	BW			BoxScore
82 - 2022-12-27	550	Manchots	4	Sound Tigers	3	AW			BoxScore
83 - 2022-12-28	560	Cougars	6	Manchots	5	BL	X	X	BoxScore
85 - 2022-12-30	576	Spiders	2	Manchots	4	BW			BoxScore
88 - 2023-01-02	595	Manchots	1	Bruins	5	AL			BoxScore
91 - 2023-01-05	620	Manchots	2	Las Vegas	3	AL	X		BoxScore
94 - 2023-01-08	640	Manchots	2	Jayhawks	1	AW			BoxScore
96 - 2023-01-10	652	Comets	4	Manchots	3	BL			BoxScore
99 - 2023-01-13	674	Oceanics	1	Manchots	2	BW	X	X	BoxScore
100 - 2023-01-14	682	Manchots	6	Caroline	2	AW			BoxScore
102 - 2023-01-16	700	Admirals	1	Manchots	3	BW			BoxScore
104 - 2023-01-18	712	Manchots	2	Senators	3	AL			BoxScore
106 - 2023-01-20	730	Senators	1	Manchots	3	BW			BoxScore
108 - 2023-01-22	746	Manchots	3	Spiders	2	AW	X	X	BoxScore
110 - 2023-01-24	756	Cabaret Lady Mary Ann	4	Manchots	6	BW			BoxScore
112 - 2023-01-26	773	Manchots	4	Bears	5	AL	X	X	BoxScore
114 - 2023-01-28	793	Sharks	3	Manchots	4	BW	X	X	BoxScore
124 - 2023-02-07	813	Monsters	4	Manchots	3	BL			BoxScore
127 - 2023-02-10	831	Manchots	0	Admirals	2	AL			BoxScore
128 - 2023-02-11	845	Manchots	4	Monarchs	3	AW			BoxScore
131 - 2023-02-14	863	Manchots	3	Sharks	4	AL			BoxScore
134 - 2023-02-17	879	Manchots	1	Sound Tigers	3	AL			BoxScore
135 - 2023-02-18	886	Spiders	1	Manchots	2	BW			BoxScore
137 - 2023-02-20	906	Sound Tigers	3	Manchots	2	BL	X	X	BoxScore
140 - 2023-02-23	922	Oil Kings	5	Manchots	3	BL			BoxScore
142 - 2023-02-25	943	Manchots	5	Chiefs	6	AL			BoxScore
143 - 2023-02-26	951	Thunder	1	Manchots	3	BW			BoxScore
145 - 2023-02-28	963	Manchots	6	Chill	5	AW	X		BoxScore
147 - 2023-03-02	977	Manchots	4	Thunder	2	AW			BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
149 - 2023-03-04	993	Manchots	5	Cabaret Lady Mary Ann	1	AW			BoxScore
152 - 2023-03-07	1013	Monsters	1	Manchots	5	BW			BoxScore
154 - 2023-03-09	1027	Sound Tigers	3	Manchots	1	BL			BoxScore
156 - 2023-03-11	1039	Phantoms	0	Manchots	4	BW			BoxScore
157 - 2023-03-12	1054	Wolf Pack	3	Manchots	4	BW	X		BoxScore
159 - 2023-03-14	1064	Rocket	5	Manchots	4	BL	X	X	BoxScore
161 - 2023-03-16	1082	Manchots	2	Wolf Pack	0	AW			BoxScore
163 - 2023-03-18	1103	Manchots	2	Wolf Pack	4	AL			BoxScore
165 - 2023-03-20	1115	Senators	2	Manchots	1	BL			BoxScore
167 - 2023-03-22	1133	Manchots	1	Monsters	4	AL			BoxScore
168 - 2023-03-23	1143	Manchots	3	Stars	2	AW			BoxScore
170 - 2023-03-25	1162	Bears	2	Manchots	1	BL			BoxScore
173 - 2023-03-28	1180	Manchots	3	Cougars	2	AW			BoxScore
175 - 2023-03-30	1192	Chill	3	Manchots	4	BW	X	X	BoxScore
177 - 2023-04-01	1205	Bruins	6	Manchots	4	BL			BoxScore
178 - 2023-04-02	1221	Phantoms	1	Manchots	3	BW			BoxScore
180 - 2023-04-04	1233	Manchots	3	Spiders	4	AL			BoxScore
182 - 2023-04-06	1244	Minnesota	1	Manchots	2	BW	X	X	BoxScore
184 - 2023-04-08	1266	Manchots	4	Cougars	1	AW			BoxScore
187 - 2023-04-11	1286	Baby Hawks	1	Manchots	3	BW			BoxScore
189 - 2023-04-13	1303	Manchots	2	Monsters	7	AL			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	1750	1250
Ticket Price	50	20
Attendance	43,499	33,684
Attendance PCT	60.63%	65.72%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
0	1883 - 62.75%	69,479$	2,848,630$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
1,279,234$	1,189,084$	1,189,084$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
6,258$	1,279,234$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	6,258$	0$

Manchots 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

Manchots 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

Manchots 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

Manchots 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

Manchots 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

	Manchots
	GP: 82 \| W: 43 \| L: 32 \| OTL: 7 \| P: 93 GF: 254 \| GA: 244 \| PP%: 19.29% \| PK%: 82.53% GM : Raphael Belanger \| Morale : 50 \| Team Overall : 56