LHSDB - Ligue de hockey simulee des debiles barbus

Boston Bruins
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1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
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8	`?`	Wildcard for a single, non-space character.
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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
1	Justin Richards	X				100.00	67	35	94	69	72	77	81	67	71	66	61	68	64	65	62	53	50	65	0
2	Alex Limoges	X	X	X		100.00	58	43	83	65	78	80	82	66	73	64	67	63	68	67	64	53	50	64	0
3	Joel Kellman	X				100.00	68	35	92	64	71	68	72	65	77	66	64	69	63	73	68	37	50	64	0
4	Nathan Gerbe	X	X	X		100.00	79	36	80	67	61	79	80	66	69	67	63	59	65	84	78	30	50	64	0
5	Parker Kelly	X	X	X		100.00	79	35	91	64	66	74	78	63	68	62	71	69	67	63	62	54	50	64	0
6	Dylan Gambrell	X				100.00	77	35	91	65	71	70	75	66	79	68	62	68	66	69	66	65	50	64	0
7	Carter Camper	X				100.00	56	39	85	59	66	82	84	61	77	66	58	57	62	81	73	26	50	62	0
8	Cameron Hughes	X				100.00	64	35	92	63	66	77	73	62	76	61	59	68	62	69	66	48	50	62	0
9	Jack Kopacka		X			100.00	71	35	93	57	80	69	74	57	58	57	56	59	62	65	63	61	50	59	0
10	Alexander Yelesin				X	100.00	82	35	95	61	73	85	78	60	30	59	56	64	53	69	71	52	50	65	0
11	William Borgen				X	100.00	83	39	87	58	84	87	80	57	30	58	54	64	47	69	65	60	50	65	0
12	Jimmy Schuldt				X	100.00	69	46	80	59	78	84	89	56	30	58	56	57	48	71	66	42	50	62	0
13	Jalen Chatfield				X	100.00	57	46	79	58	75	79	77	56	30	58	53	57	47	69	65	42	50	60	0
Scratches
1	Patrick Marleau	X	X	X		100.00	65	35	94	70	83	81	90	65	74	67	66	61	68	92	84	33	50	67	0
2	Joakim Nordstrom	X	X	X		100.00	85	35	92	65	76	74	85	64	72	63	62	79	61	77	69	51	50	67	0
3	Joakim Nygard		X			100.00	58	35	91	68	70	81	84	66	59	65	62	56	64	75	68	36	50	63	0
4	Curtis McKenzie		X			100.00	72	55	71	61	82	79	85	58	64	62	59	61	62	78	73	39	50	63	0
5	Zac Rinaldo	X	X	X		100.00	95	84	56	61	70	73	78	63	67	65	62	58	63	79	72	38	50	63	0
6	Zach Senyshyn			X		100.00	64	35	95	66	79	69	71	65	61	63	62	59	65	67	64	82	50	62	0
7	Yannick Veilleux		X			100.00	71	76	63	64	79	66	71	62	57	61	65	63	67	75	71	51	50	62	0
8	Liam O'Brien		X			100.00	82	63	54	62	80	70	74	60	63	64	60	61	61	73	67	37	50	62	0
9	Luke Philp	X				100.00	60	37	88	61	69	80	85	61	71	58	63	57	62	71	66	42	50	61	0
10	Michael Carcone		X			100.00	63	39	75	61	63	85	90	59	60	58	64	56	62	69	65	52	50	61	0
11	Patrick Khodorenko	X				100.00	65	35	93	58	74	79	73	57	69	61	56	54	57	65	63	45	50	59	0
12	Sam Miletic		X			100.00	65	35	92	57	74	78	83	56	54	59	55	57	58	67	64	53	50	59	0
13	Spencer Smallman			X		100.00	68	43	83	57	77	79	84	58	60	56	53	57	54	69	64	56	50	59	0
14	Cole Reinhardt (R)		X			100.00	64	37	89	56	74	78	83	57	55	56	58	54	59	61	62	52	50	58	0
15	Felix Robert	X				100.00	61	46	79	58	61	73	78	56	70	58	59	53	59	63	62	45	50	58	0
16	Giovanni Fiore		X	X		100.00	66	36	90	55	75	60	65	55	50	52	60	55	58	69	65	42	50	57	0
17	Giorgio Estephan (R)			X		100.00	65	35	93	56	74	65	70	56	60	58	55	56	60	67	64	48	50	57	0
18	Nate Prosser				X	100.00	54	36	95	61	82	83	77	62	30	64	63	66	53	85	75	23	50	65	0
19	Joe Morrow				X	100.00	65	56	69	57	74	78	73	58	30	56	53	54	46	77	69	66	50	60	0
20	Luke Green				X	100.00	66	38	88	51	75	60	65	51	30	50	54	53	45	65	63	64	50	55	0

	TEAM AVERAGE					100.00	69	42	85	61	74	76	78	60	58	61	60	60	59	71	67	48	50	62

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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
1	Christopher Gibson	100.00	77	89	88	84	76	75	77	76	75	77	76	77	83	58	50	76	0
2	Anton Forsberg	100.00	76	80	78	76	75	74	76	75	74	76	75	78	83	54	50	74	0
Scratches
1	Callum Booth	100.00	77	75	79	83	76	75	77	76	75	77	76	67	71	61	50	74	0
2	Alexei Melnichuk	100.00	75	82	80	78	74	73	75	74	73	75	74	65	70	63	50	72	0
3	Artyom Zagidulin	100.00	72	83	81	76	71	70	72	71	70	72	71	73	76	45	50	71	0

	TEAM AVERAGE	100.00	75	82	81	79	74	73	75	74	73	75	74	72	77	56	50	73

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Bob Hartley	72	70	75	73	87	81	59	CAN	60	4	6,300,000$

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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	Parker Kelly	Bruins (Bos)	C/LW/RW	82	28	38	66	33	52	0	151	86	291	70	219	9.62%	10	1585	19.34	9	13	22	81	363	2	0	2	6	92	7	4	51.30%	115	0	1	0.83	0	3	0	0	0	10	5	2
2	Justin Richards	Bruins (Bos)	C	81	26	40	66	31	28	0	55	209	237	61	193	10.97%	17	1670	20.62	7	9	16	43	266	1	0	1	11	268	4	1	59.98%	1869	0	1	0.79	1	7	0	0	0	8	5	4
3	Alex Limoges	Bruins (Bos)	C/LW/RW	82	27	37	64	26	20	0	35	107	251	74	174	10.76%	8	1409	17.19	5	13	18	50	270	0	0	0	0	19	6	1	57.65%	85	0	2	0.91	0	1	0	0	0	3	6	8
4	Jarred Tinordi	Boston Bruins	D	78	13	43	56	30	206	40	193	75	156	51	97	8.33%	75	1802	23.10	9	20	29	108	352	1	2	3	3	256	2	2	0.00%	0	0	0	0.62	0	0	3	1	4	1	4	1
5	Joel Kellman	Bruins (Bos)	C	82	23	31	54	26	22	0	83	108	232	40	150	9.91%	15	1142	13.93	0	1	1	2	17	0	0	0	0	30	5	2	62.04%	714	0	0	0.95	1	1	0	0	0	5	4	2
6	Nathan Gerbe	Bruins (Bos)	C/LW/RW	82	22	27	49	15	83	5	172	103	199	60	153	11.06%	5	1508	18.40	9	9	18	45	352	0	0	0	0	31	2	1	57.55%	106	0	0	0.65	0	2	0	0	0	3	2	3
7	Dylan Gambrell	Bruins (Bos)	C	64	17	25	42	16	32	0	67	107	154	39	105	11.04%	10	989	15.46	5	6	11	41	201	0	2	2	2	78	2	1	62.48%	1018	0	0	0.85	0	3	0	0	0	3	4	2
8	Alexander Yelesin	Bruins (Bos)	D	82	7	33	40	29	95	5	135	46	102	35	56	6.86%	94	1808	22.06	3	13	16	60	356	0	0	0	1	305	2	0	100.00%	2	0	0	0.44	0	0	0	0	1	0	2	0
9	Mason Marchment	Boston Bruins	C/LW/RW	30	18	21	39	23	35	5	75	52	103	26	71	17.48%	5	618	20.62	3	8	11	24	120	0	0	0	1	63	2	3	62.96%	621	0	2	1.26	1	1	0	1	0	6	3	1
10	Jimmy Schuldt	Bruins (Bos)	D	82	7	27	34	37	85	5	107	21	46	16	19	15.22%	64	1400	17.08	2	2	4	22	155	0	0	0	2	140	0	1	0.00%	0	0	0	0.49	0	0	0	1	0	2	1	2
11	Cameron Hughes	Bruins (Bos)	C	81	13	16	29	18	22	0	32	67	94	26	69	13.83%	7	699	8.64	1	1	2	7	25	0	0	0	0	9	4	1	64.46%	121	0	0	0.83	0	0	0	0	0	1	3	1
12	William Borgen	Bruins (Bos)	D	82	6	23	29	22	65	5	100	40	71	26	53	8.45%	66	1833	22.36	2	9	11	40	333	0	1	1	0	277	2	0	0.00%	0	1	0	0.32	0	0	0	1	0	1	1	4
13	Jay Beagle	Boston Bruins	C/RW	37	16	8	24	13	63	15	70	111	109	48	81	14.68%	26	787	21.30	2	1	3	26	110	1	2	3	6	160	3	1	66.20%	1003	0	0	0.61	1	3	1	1	1	4	2	1
14	Jalen Chatfield	Bruins (Bos)	D	82	2	14	16	33	51	15	44	21	32	8	21	6.25%	38	1154	14.09	0	1	1	6	34	0	0	0	0	121	0	1	0.00%	0	0	0	0.28	0	0	0	1	2	0	1	0
15	Carter Camper	Bruins (Bos)	C	80	1	13	14	8	15	5	25	21	17	7	15	5.88%	19	547	6.85	0	2	2	1	19	0	0	0	0	59	1	0	51.09%	92	0	0	0.51	0	0	0	0	1	0	0	1
16	Jack Kopacka	Bruins (Bos)	LW	82	7	7	14	16	35	5	52	36	69	16	47	10.14%	3	755	9.21	0	1	1	0	9	0	0	0	1	71	2	0	47.62%	84	0	0	0.37	0	0	0	0	0	1	1	2
17	Sam Miletic	Bruins (Bos)	LW	12	2	4	6	3	6	0	9	5	11	7	9	18.18%	0	149	12.45	0	0	0	0	0	0	0	0	0	14	1	0	61.54%	13	0	0	0.80	0	0	0	0	0	0	0	1
18	Zach Senyshyn	Bruins (Bos)	RW	1	1	0	1	-2	0	0	0	4	4	2	1	25.00%	0	17	17.72	1	0	1	1	2	0	0	0	0	0	0	0	0.00%	0	0	0	1.13	0	0	0	0	0	0	0	0
Team Total or Average				1202	236	407	643	377	915	105	1405	1219	2178	612	1533	10.84%	462	19883	16.54	58	109	167	557	2993	5	7	12	33	2000	45	19	61.60%	5843	1	6	0.65	4	21	4	6	9	48	44	35

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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	PS %	PSA	ST	BG	S1	S2	S3
1	Christopher Gibson	Bruins (Bos)	73	52	15	6	0.919	1.64	4419	8	14	121	1492	0.724	29	73	8	4	5	8
2	Anton Forsberg	Bruins (Bos)	12	9	2	1	0.903	2.07	726	0	2	25	259	0.800	5	12	26	1	0	0
Team Total or Average			85	61	17	7	0.917	1.70	5145	8	16	146	1751	0.735	34	85	34	5	5	8

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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	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Link
Alex Limoges	C/LW/RW	24	1997-09-16	No	201 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Alexander Yelesin	D	26	1996-02-07	No	195 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Alexei Melnichuk	G	23	1998-06-29	No	190 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Anton Forsberg	G	29	1992-11-27	No	176 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	750,000$	0$	0$	No	Link / NHL Link
Artyom Zagidulin	G	26	1995-08-08	No	180 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Callum Booth	G	24	1997-05-21	No	184 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Cameron Hughes	C	25	1996-10-09	No	160 Lbs	5 ft11	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Carter Camper	C	33	1988-07-06	No	176 Lbs	5 ft9	No	No	No	1	UFA	Pro & Farm	311,002$	0$	0$	No	Link / NHL Link
Christopher Gibson	G	29	1992-12-27	No	217 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Cole Reinhardt	LW	22	2000-02-01	Yes	200 Lbs	6 ft0	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No
Curtis McKenzie	LW	31	1991-02-22	No	205 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Dylan Gambrell	C	25	1996-08-26	No	185 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Felix Robert	C	22	1999-07-24	No	165 Lbs	5 ft8	No	No	No	2	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Giorgio Estephan	RW	25	1997-02-03	Yes	196 Lbs	6 ft0	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No
Giovanni Fiore	LW/RW	25	1996-08-13	No	188 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jack Kopacka	LW	24	1998-03-05	No	197 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jalen Chatfield	D	25	1996-05-15	No	188 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jimmy Schuldt	D	26	1995-05-11	No	203 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Joakim Nordstrom	C/LW/RW	30	1992-02-25	No	194 Lbs	6 ft1	No	No	No	4	UFA	Pro & Farm	990,000$	0$	0$	No	Link / NHL Link
Joakim Nygard	LW	29	1993-01-08	No	179 Lbs	6 ft0	No	No	No	3	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Joe Morrow	D	29	1992-12-09	No	196 Lbs	6 ft0	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Joel Kellman	C	27	1994-05-25	No	192 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Justin Richards	C	24	1998-03-17	No	190 Lbs	5 ft11	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link
Liam O'Brien	LW	27	1994-07-29	No	213 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Luke Green	D	24	1998-01-12	No	188 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Luke Philp	C	26	1995-11-06	No	181 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Michael Carcone	LW	25	1996-05-19	No	170 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nate Prosser	D	35	1986-05-07	No	201 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Nathan Gerbe	C/LW/RW	34	1987-07-24	No	176 Lbs	5 ft4	No	No	No	1	UFA	Pro & Farm	400,000$	0$	0$	No	Link / NHL Link
Parker Kelly	C/LW/RW	22	1999-05-14	No	168 Lbs	5 ft11	No	No	No	2	ELC	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Patrick Khodorenko	C	23	1998-10-13	No	200 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link
Patrick Marleau	C/LW/RW	42	1979-09-15	No	215 Lbs	6 ft2	No	No	No	3	UFA	Pro & Farm	700,000$	0$	0$	No	Link / NHL Link
Sam Miletic	LW	24	1997-05-04	No	197 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Spencer Smallman	RW	25	1996-09-09	No	198 Lbs	6 ft1	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
William Borgen	D	25	1996-12-19	No	205 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Yannick Veilleux	LW	29	1993-02-22	No	195 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Zac Rinaldo	C/LW/RW	31	1990-06-15	No	192 Lbs	5 ft10	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Zach Senyshyn	RW	24	1997-03-30	No	207 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
38	26.82	191 Lbs	6 ft0	2.21	417,132$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Parker Kelly	Justin Richards	Nathan Gerbe	40	1	2	2
2	Alex Limoges	Dylan Gambrell	Cameron Hughes	30	1	2	2
3	Jack Kopacka	Joel Kellman	Carter Camper	20	1	2	2
4	Justin Richards	Cameron Hughes	Dylan Gambrell	10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	William Borgen	Alexander Yelesin	40	1	2	2
2	Jimmy Schuldt	Jalen Chatfield	30	1	2	2
3			20	1	2	2
4	William Borgen	Alexander Yelesin	10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Parker Kelly	Justin Richards	Nathan Gerbe	60	1	2	2
2	Alex Limoges	Dylan Gambrell	Cameron Hughes	40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	William Borgen	Alexander Yelesin	60	1	2	2
2	Jimmy Schuldt	Jalen Chatfield	40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Justin Richards	Dylan Gambrell	60	1	2	2
2	Parker Kelly	Nathan Gerbe	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	William Borgen	Alexander Yelesin	60	1	2	2
2	Jimmy Schuldt	Jalen Chatfield	40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Justin Richards	60	1	2	2	William Borgen	Alexander Yelesin	60	1	2	2
2	Dylan Gambrell	40	1	2	2	Jimmy Schuldt	Jalen Chatfield	40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Justin Richards	Dylan Gambrell	60	1	2	2
2	Parker Kelly	Nathan Gerbe	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	William Borgen	Alexander Yelesin	60	1	2	2
2	Jimmy Schuldt	Jalen Chatfield	40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Parker Kelly	Justin Richards	Nathan Gerbe	William Borgen	Alexander Yelesin

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Parker Kelly	Justin Richards	Nathan Gerbe	William Borgen	Alexander Yelesin

Extra Forwards
Normal	PowerPlay	Penalty Kill
Joel Kellman, Carter Camper, Jack Kopacka	Joel Kellman, Carter Camper	Jack Kopacka

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Jimmy Schuldt, Jalen Chatfield, William Borgen	Jimmy Schuldt	Jalen Chatfield, William Borgen

Penalty Shots
Justin Richards, Dylan Gambrell, Parker Kelly, Nathan Gerbe, Joel Kellman

Goalie
#1 : Christopher Gibson, #2 : Anton Forsberg

Custom OT Lines Forwards
, , , , , , , , , ,

Custom OT Lines Defensemen
, , , ,

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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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
82	119	L2	266	478	744	2575	1700	526	988	1528	0	17

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
82	48	19	5	2	3	5	266	147

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	24	8	3	2	2	2	133	71

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
41	24	11	2	0	1	3	133	76

Last 10 Games
W	L	OTW	OTL	SOW	SOL
4	3	2	1	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
449	71	15.81%	403	41	89.83%	8

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
831	891	821	65	101	75	82	11

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
1684	2693	62.53%	1313	2242	58.56%	736	1171	62.85%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
2261	1648	1748	554	961	506

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 - 2021-10-02	13	Bruins	4	Wolves	5	L			BoxScore
3 - 2021-10-03	26	Americans	0	Bruins	1	W			BoxScore
5 - 2021-10-05	38	Rocket	2	Bruins	0	L			BoxScore
7 - 2021-10-07	60	Bruins	6	Palm Springs	0	W			BoxScore
8 - 2021-10-08	69	Rocket	0	Bruins	3	W			BoxScore
10 - 2021-10-10	84	Bruins	5	Condors	3	W			BoxScore
13 - 2021-10-13	105	Comets	2	Bruins	7	W			BoxScore
15 - 2021-10-15	115	Bruins	2	Stars	1	W	X		BoxScore
17 - 2021-10-17	136	IceHogs	2	Bruins	7	W			BoxScore
18 - 2021-10-18	146	Bruins	1	Checkers	2	L			BoxScore
20 - 2021-10-20	166	Bruins	1	Admirals	2	L			BoxScore
21 - 2021-10-21	177	Bruins	3	IceHogs	0	W			BoxScore
23 - 2021-10-23	189	Eagles	1	Bruins	7	W			BoxScore
26 - 2021-10-26	211	Rampage	1	Bruins	2	W			BoxScore
28 - 2021-10-28	227	Bruins	3	Wild	2	W			BoxScore
31 - 2021-10-31	248	Griffins	3	Bruins	4	W	X		BoxScore
32 - 2021-11-01	255	Bruins	3	Rocket	1	W			BoxScore
34 - 2021-11-03	276	Crunch	2	Bruins	3	W			BoxScore
37 - 2021-11-06	294	Bruins	2	Wolves	0	W			BoxScore
38 - 2021-11-07	305	Roadrunners	1	Bruins	5	W			BoxScore
40 - 2021-11-09	324	Bruins	5	Reign	0	W			BoxScore
43 - 2021-11-12	338	Bruins	4	Wolf Pack	3	W			BoxScore
44 - 2021-11-13	348	Gulls	2	Bruins	1	L			BoxScore
46 - 2021-11-15	364	Bruins	1	Rampage	4	L			BoxScore
47 - 2021-11-16	379	Thunderbirds	3	Bruins	2	L	X	X	BoxScore
49 - 2021-11-18	398	Bruins	1	Gulls	3	L			BoxScore
51 - 2021-11-20	410	Rampage	0	Bruins	3	W			BoxScore
53 - 2021-11-22	423	Bruins	1	Wild	2	L	X	X	BoxScore
55 - 2021-11-24	440	Bruins	1	Devils	3	L			BoxScore
56 - 2021-11-25	447	Penguins	0	Bruins	1	W	X	X	BoxScore
58 - 2021-11-27	468	Bruins	4	Bears	3	W			BoxScore
59 - 2021-11-28	479	Checkers	4	Bruins	0	L			BoxScore
62 - 2021-12-01	503	Bruins	4	Rocket	1	W			BoxScore
63 - 2021-12-02	512	Wolves	1	Bruins	3	W			BoxScore
66 - 2021-12-05	537	Bruins	9	IceHogs	2	W			BoxScore
67 - 2021-12-06	543	Heat	6	Bruins	5	L			BoxScore
70 - 2021-12-09	567	Bruins	1	Sound Tigers	0	W			BoxScore
71 - 2021-12-10	575	Griffins	1	Bruins	3	W			BoxScore
73 - 2021-12-12	599	Sound Tigers	1	Bruins	2	W			BoxScore
75 - 2021-12-14	618	Bruins	6	Crunch	2	W			BoxScore
77 - 2021-12-16	633	Bears	2	Bruins	5	W			BoxScore
79 - 2021-12-18	649	Bruins	3	Stars	0	W			BoxScore
81 - 2021-12-20	664	Phantoms	1	Bruins	2	W			BoxScore
83 - 2021-12-22	679	Bruins	5	Moose	0	W			BoxScore
85 - 2021-12-24	698	Stars	0	Bruins	3	W			BoxScore
86 - 2021-12-25	708	Bruins	8	Heat	2	W			BoxScore
89 - 2021-12-28	727	Bruins	4	Barracuda	1	W			BoxScore
90 - 2021-12-29	735	Eagles	2	Bruins	1	L	X		BoxScore
93 - 2022-01-01	759	Bruins	3	Thunderbirds	1	W			BoxScore
94 - 2022-01-02	767	Devils	1	Bruins	0	L			BoxScore
96 - 2022-01-04	789	Wild	3	Bruins	5	W			BoxScore
99 - 2022-01-07	807	Bruins	4	Monsters	1	W			BoxScore
100 - 2022-01-08	824	IceHogs	0	Bruins	9	W			BoxScore
102 - 2022-01-10	841	Bruins	3	Checkers	5	L			BoxScore
103 - 2022-01-11	848	Bruins	2	Phantoms	0	W			BoxScore
105 - 2022-01-13	862	Bears	2	Bruins	3	W	X		BoxScore
107 - 2022-01-15	876	Bruins	1	Thunderbirds	3	L			BoxScore
109 - 2022-01-17	893	Senators	5	Bruins	4	L	X	X	BoxScore
111 - 2022-01-19	913	Bruins	3	Marlies	1	W			BoxScore
113 - 2022-01-21	925	Palm Springs	1	Bruins	2	W	X	X	BoxScore
115 - 2022-01-23	950	Condors	2	Bruins	7	W			BoxScore
117 - 2022-01-25	959	Bruins	1	Griffins	2	L	X	X	BoxScore
119 - 2022-01-27	981	Americans	2	Bruins	3	W			BoxScore
120 - 2022-01-28	988	Bruins	6	Condors	1	W			BoxScore
122 - 2022-01-30	1009	Bruins	4	Senators	0	W			BoxScore
123 - 2022-01-31	1021	Americans	1	Bruins	6	W			BoxScore
126 - 2022-02-03	1045	Checkers	3	Bruins	2	L			BoxScore
127 - 2022-02-04	1055	Bruins	2	Eagles	3	L	X	X	BoxScore
130 - 2022-02-07	1079	Wolf Pack	3	Bruins	2	L			BoxScore
131 - 2022-02-08	1086	Bruins	5	Palm Springs	4	W	X	X	BoxScore
134 - 2022-02-11	1101	Bruins	4	Americans	0	W			BoxScore
136 - 2022-02-13	1113	Bruins	2	Griffins	4	L			BoxScore
137 - 2022-02-14	1121	Monsters	2	Bruins	3	W	X		BoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
141 - 2022-02-18	1147	Heat	2	Bruins	4	W			BoxScore
144 - 2022-02-21	1171	Rocket	1	Bruins	2	W			BoxScore
148 - 2022-02-25	1201	Comets	3	Bruins	2	L	X		BoxScore
150 - 2022-02-27	1220	Bruins	2	Admirals	3	L			BoxScore
152 - 2022-03-01	1234	Bruins	3	Comets	2	W	X		BoxScore
153 - 2022-03-02	1242	Marlies	0	Bruins	6	W			BoxScore
157 - 2022-03-06	1269	Marlies	1	Bruins	2	W			BoxScore
161 - 2022-03-10	1292	Admirals	2	Bruins	1	L			BoxScore
162 - 2022-03-11	1299	Bruins	1	Penguins	4	L			BoxScore

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	75,958	38,648
Attendance PCT	92.63%	94.26%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
0	2795 - 93.18%	69,504$	2,849,660$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
6,461,177$	158,510$	6,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	161,154$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	39,142$	0$

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
12	82	43	23	0	4	6	3	3	267	190	77	41	23	9	0	2	4	1	2	130	88	42	41	20	14	0	2	2	2	1	137	102	35	109	267	478	745	2	15	0	118	82	60	2382	0	855	786	721	1706	519	1302	1823	489	84	17.18%	544	77	85.85%	5	1617	2697	59.96%	1249	2159	57.85%	693	1159	59.79%	2278	1626	1708	560	988	530
13	76	48	17	0	2	4	3	2	246	143	103	38	25	8	0	2	1	2	0	123	67	56	38	23	9	0	0	3	1	2	123	76	47	112	246	435	681	0	11	0	98	88	55	2093	0	685	703	681	1751	501	934	1611	386	56	14.51%	402	50	87.56%	3	1278	2204	57.99%	1234	2236	55.19%	654	1073	60.95%	2051	1476	1650	518	903	480
14	76	44	22	0	2	5	3	0	215	135	80	38	25	9	0	1	2	1	0	110	69	41	38	19	13	0	1	3	2	0	105	66	39	103	215	380	595	0	11	0	92	69	49	2148	0	727	659	754	1621	437	712	1247	362	42	11.60%	281	36	87.19%	5	1491	2538	58.75%	1162	2173	53.47%	551	1047	52.63%	2028	1461	1640	530	921	484
15	82	40	33	0	2	2	4	1	240	186	54	41	23	13	0	2	1	2	0	129	77	52	41	17	20	0	0	1	2	1	111	109	2	95	240	433	673	1	8	0	88	82	64	2250	0	743	739	755	1852	588	1189	1549	431	77	17.87%	480	70	85.42%	3	1609	2612	61.60%	1339	2291	58.45%	682	1175	58.04%	2220	1594	1747	563	983	516
16	82	48	19	0	5	2	3	5	266	147	119	41	24	8	0	3	2	2	2	133	71	62	41	24	11	0	2	0	1	3	133	76	57	119	266	478	744	0	17	101	75	82	11	2575	831	891	821	65	1700	526	988	1528	449	71	15.81%	403	41	89.83%	8	1684	2693	62.53%	1313	2242	58.56%	736	1171	62.85%	2261	1648	1748	554	961	506
Total Regular Season	398	223	114	0	15	19	16	11	1234	801	433	199	120	47	0	10	10	8	4	625	372	253	199	103	67	0	5	9	8	7	609	429	180	538	1234	2204	3438	3	62	101	471	403	239	11448	831	3901	3708	2976	8630	2571	5125	7758	2117	330	15.59%	2110	274	87.01%	24	7679	12744	60.26%	6297	11101	56.72%	3316	5625	58.95%	10841	7808	8495	2727	4758	2518
Playoff
12	4	0	4	0	0	0	0	0	7	14	-7	2	0	2	0	0	0	0	0	4	8	-4	2	0	2	0	0	0	0	0	3	6	-3	0	7	14	21	0	0	0	2	2	3	76	0	32	20	24	100	46	93	81	33	3	9.09%	35	6	82.86%	0	56	123	45.53%	51	134	38.06%	28	72	38.89%	82	53	109	32	48	22
13	6	2	4	0	0	0	0	0	13	15	-2	3	1	2	0	0	0	0	0	7	7	0	3	1	2	0	0	0	0	0	6	8	-2	4	13	23	36	0	1	0	4	2	7	108	0	33	36	36	151	46	128	105	31	3	9.68%	51	9	82.35%	0	70	158	44.30%	103	215	47.91%	45	94	47.87%	139	92	156	48	79	35
14	4	0	4	0	0	0	0	0	4	9	-5	2	0	2	0	0	0	0	0	2	4	-2	2	0	2	0	0	0	0	0	2	5	-3	0	4	8	12	1	0	0	2	2	0	116	0	39	28	39	103	24	56	72	26	1	3.85%	22	3	86.36%	0	77	156	49.36%	73	142	51.41%	36	64	56.25%	103	71	104	32	53	25
15	4	0	4	0	0	0	0	0	5	11	-6	2	0	2	0	0	0	0	0	4	7	-3	2	0	2	0	0	0	0	0	1	4	-3	0	5	9	14	0	0	0	1	2	2	80	0	28	27	21	93	30	63	64	29	4	13.79%	28	3	89.29%	0	62	118	52.54%	62	117	52.99%	25	56	44.64%	88	57	111	34	51	24
Total Playoff	18	2	16	0	0	0	0	0	29	49	-20	9	1	8	0	0	0	0	0	17	26	-9	9	1	8	0	0	0	0	0	12	23	-11	4	29	54	83	1	1	0	9	8	12	380	0	132	111	120	447	146	340	322	119	11	9.24%	136	21	84.56%	0	265	555	47.75%	289	608	47.53%	134	286	46.85%	414	274	481	147	232	108