LSMH - LIGUE SIMULE DES MORDUS DE HOCKEY

Predators
Roster
Scoring
Informations
Lines
Stats
Schedule
Finance
Records
Web Lines Editor

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
1	Rodrigo Abols	X				100.00	76	43	89	65	88	78	81	63	79	62	61	64	60	71	72	39	75	66	0
2	Dominik Shine			X		100.00	64	51	70	66	68	82	84	65	67	64	63	60	62	73	78	26	75	65	0
3	Seth Griffith	X				100.00	58	39	77	66	67	75	86	65	78	69	61	60	63	73	78	34	75	65	0
4	Brian Pinho	X				100.00	66	37	94	64	75	90	86	63	65	61	62	64	63	71	73	38	75	64	0
5	Garrett Wilson		X	X		100.00	78	72	55	58	87	73	82	57	54	56	55	59	53	75	77	31	75	62	0
6	Jujhar Khaira		X			100.00	80	78	69	58	89	73	74	55	59	57	56	60	54	72	74	41	75	62	0
7	Hayden Hodgson			X		100.00	77	65	52	58	86	70	79	56	55	54	55	57	53	70	72	35	75	60	0
8	Luke Prokop				X	100.00	88	51	89	56	97	66	73	54	30	55	53	61	46	64	66	63	75	62	0
9	Ethan Edwards				X	100.00	57	40	72	56	66	67	74	54	30	58	53	55	46	64	66	57	75	57	0
10	Thomas Miller				X	100.00	68	39	87	55	77	64	76	54	30	53	52	56	45	67	69	37	75	57	0
Scratches
1	Patrick Brown	X				100.00	83	39	82	64	81	88	87	62	66	63	58	69	61	74	79	23	75	67	0
2	Austin Poganski			X		100.00	68	38	91	65	77	78	87	63	67	64	61	62	66	70	75	48	75	65	0
3	Jack D. Hughes (R)	X				100.00	57	37	86	56	66	67	82	55	58	57	54	53	56	63	65	71	75	56	0
4	Nick DeSimone				X	100.00	69	38	94	65	79	83	73	62	30	69	57	56	50	72	74	27	75	64	0
5	Christopher Merisier-Ortiz				X	100.00	58	36	94	56	67	62	68	54	30	55	50	53	45	65	67	42	75	55	0

	TEAM AVERAGE					100.00	70	47	80	61	78	74	79	59	53	60	57	59	55	70	72	41	75	62

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
Scratches

	TEAM AVERAGE	0.00	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0

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	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

Show or Hide Column

Filter Tips

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

#	Goalie Name	Team Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA	ST	BG	S1	S2	S3

Show or Hide Column

Filter Tips

Priority	Type	Description
1	`\|` or `OR`	Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2	`&&` or `AND`	Logical "and". Filter the column for content that matches text from either side of the operator.
3	`/\d/`	Add any regex to the query to use in the query ("mig" flags can be included `/\w/mig`)
4	`< <= >= >`	Find alphabetical or numerical values less than or greater than or equal to the filtered query
5	`!` or `!=`	Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (`=`), single (`'`) or double quote (`"`) to exactly not match a filter.
6	`"` or `=`	To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7	`-` or `to`	Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8	`?`	Wildcard for a single, non-space character.
8	`*`	Wildcard for zero or more non-space characters.
9	`~`	Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10	text	Any text entered in the filter will match text found within the column

Player Name	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
Austin Poganski	RW	30	1996-02-16	No	198 Lbs	6 ft1	No	No	No	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Brian Pinho	C	31	1995-05-11	No	190 Lbs	6 ft1	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Christopher Merisier-Ortiz	D	25	2001-01-17	No	171 Lbs	5 ft11	No	No	No	0	ELC	Pro & Farm		0$	0$	No	Link / NHL Link
Dominik Shine	RW	33	1993-04-18	No	177 Lbs	5 ft11	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Ethan Edwards	D	24	2002-06-06	No	176 Lbs	5 ft10	No	No	No	2	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Garrett Wilson	LW/RW	35	1991-03-16	No	218 Lbs	6 ft3	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Hayden Hodgson	RW	30	1996-03-02	No	226 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Jack D. Hughes	C	22	2003-11-02	Yes	170 Lbs	5 ft11	No	No	No	3	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Jujhar Khaira	LW	31	1994-08-13	No	212 Lbs	6 ft4	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Luke Prokop	D	24	2002-06-05	No	224 Lbs	6 ft6	No	No	No	2	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Nick DeSimone	D	31	1994-11-21	No	194 Lbs	6 ft2	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Patrick Brown	C	34	1992-05-29	No	218 Lbs	6 ft1	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Rodrigo Abols	C	30	1996-01-05	No	206 Lbs	6 ft4	No	No	No	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Seth Griffith	C	33	1993-01-04	No	190 Lbs	5 ft9	No	No	Yes	2	UFA	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Thomas Miller	D	27	1999-03-06	No	181 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	800,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
15	29.33	197 Lbs	6 ft1	1.80	833,333$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jujhar Khaira	Rodrigo Abols	Dominik Shine	35	1	2	2
2		Brian Pinho		30	1	2	2
3	Garrett Wilson	Seth Griffith		20	1	2	2
4	Rodrigo Abols	Brian Pinho	Hayden Hodgson	15	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Ethan Edwards		35	1	2	2
2	Luke Prokop		30	1	2	2
3	Thomas Miller		20	1	2	2
4	Luke Prokop		15	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1	Jujhar Khaira	Rodrigo Abols	Dominik Shine	60	1	2	2
2		Seth Griffith		40	1	2	2

Power Play Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Thomas Miller		60	1	2	2
2	Luke Prokop		40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Rodrigo Abols	Brian Pinho	60	1	2	2
2	Seth Griffith	Dominik Shine	40	1	2	2

Penalty Kill 4 Players Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Thomas Miller		60	1	2	2
2	Luke Prokop		40	1	2	2

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1	Rodrigo Abols	60	1	2	2	Ethan Edwards		60	1	2	2
2	Dominik Shine	40	1	2	2	Luke Prokop		40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1	Rodrigo Abols	Brian Pinho	60	1	2	2
2	Seth Griffith	Dominik Shine	40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1	Thomas Miller		60	1	2	2
2	Luke Prokop		40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense
Jujhar Khaira	Rodrigo Abols	Dominik Shine	Luke Prokop

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense
Jujhar Khaira	Rodrigo Abols	Dominik Shine	Luke Prokop

Extra Forwards
Normal	PowerPlay	Penalty Kill
, Brian Pinho,	, Brian Pinho

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Thomas Miller, , Luke Prokop	Thomas Miller	, Luke Prokop

Penalty Shots
Rodrigo Abols, Jujhar Khaira, Seth Griffith, Dominik Shine, Brian Pinho

Goalie
#1 : , #2 :

Custom OT Lines Forwards
Rodrigo Abols, Garrett Wilson, Seth Griffith, Dominik Shine, Brian Pinho, Jujhar Khaira, Jujhar Khaira, , , ,

Custom OT Lines Defensemen
, , Luke Prokop, , Thomas Miller

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

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
0	0	N/A	0	0	0	0	0	0	0	0	0	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
0	0	0	0	0	0	0	0	0

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

Last 10 Games
W	L	OTW	OTL	SOW	SOL
0	0	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
0	0	0.00%	0	0	0.00%	0

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
0	0	0	0	0	0	0	0

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
0	0	0.00%	0	0	0.00%	0	0	0.00%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
0	0	0	0	0	0

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	RI	Link

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	0.00%	0.00%
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
41	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	625,000$	625,000$	0$

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

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	0	0$	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
2	78	33	30	0	3	7	1	4	225	236	-11	39	18	12	0	1	5	1	2	118	108	10	39	15	18	0	2	2	0	2	107	128	-21	85	225	402	627	3	3	0	82	85	54	2291	0	701	803	758	2357	663	418	1592	158	29	18.35%	188	32	82.98%	5	1231	2504	49.16%	1296	2633	49.22%	622	1230	50.57%	1811	1225	1861	588	1055	524
2	78	24	35	0	7	4	3	5	208	233	-25	39	13	15	0	5	2	1	3	111	116	-5	39	11	20	0	2	2	2	2	97	117	-20	77	208	368	576	1	1	0	74	65	59	2122	0	683	672	733	2349	701	375	1476	161	25	15.53%	154	32	79.22%	2	1174	2327	50.45%	1260	2517	50.06%	618	1231	50.20%	1808	1230	1882	588	1051	526
3	82	34	36	0	4	5	1	2	294	284	10	41	16	20	0	2	2	1	0	148	151	-3	41	18	16	0	2	3	0	2	146	133	13	85	294	518	812	4	4	0	103	100	86	2762	0	905	931	904	2561	751	458	1792	199	46	23.12%	203	45	77.83%	3	1486	2862	51.92%	1434	2781	51.56%	767	1403	54.67%	2001	1396	1871	584	1077	540
4	82	39	29	0	6	3	3	2	253	214	39	41	21	13	0	2	2	2	1	132	111	21	41	18	16	0	4	1	1	1	121	103	18	101	253	455	708	0	3	0	78	80	86	2448	0	817	847	760	2411	685	407	1537	156	33	21.15%	180	43	76.11%	0	1471	2607	56.43%	1421	2646	53.70%	742	1282	57.88%	2051	1454	1856	571	1050	537
2020	82	30	36	0	7	5	2	2	269	282	-13	41	17	15	0	4	3	0	2	134	137	-3	41	13	21	0	3	2	2	0	135	145	-10	85	269	488	757	3	3	0	97	79	84	2614	0	864	830	892	2865	859	720	2022	258	56	21.71%	294	59	79.93%	2	1385	2835	48.85%	1480	3003	49.28%	688	1337	51.46%	1914	1297	1968	616	1075	534
2020	82	35	35	0	4	2	4	2	289	280	9	41	23	14	0	2	2	0	0	149	130	19	41	12	21	0	2	0	4	2	140	150	-10	90	289	519	808	0	1	0	102	95	84	2942	0	976	1001	935	2950	867	747	2086	242	50	20.66%	314	73	76.75%	3	1484	3049	48.67%	1508	3181	47.41%	676	1348	50.15%	1898	1296	2006	613	1053	519
2021	82	32	34	0	7	3	3	3	260	266	-6	41	13	17	0	6	2	1	2	129	143	-14	41	19	17	0	1	1	2	1	131	123	8	90	260	470	730	0	0	0	97	80	73	2600	0	889	838	838	2699	811	622	1856	249	44	17.67%	260	49	81.15%	3	1429	2800	51.04%	1460	2930	49.83%	697	1346	51.78%	1903	1293	1991	623	1083	533
2021	82	29	39	0	6	6	1	1	236	255	-19	41	15	19	0	3	4	0	0	111	120	-9	41	14	20	0	3	2	1	1	125	135	-10	79	236	423	659	1	3	0	80	78	71	2652	0	895	871	859	2722	833	693	2041	276	58	21.01%	284	60	78.87%	5	1446	2892	50.00%	1465	2976	49.23%	631	1276	49.45%	1894	1289	2002	612	1063	528
2022	82	25	40	0	5	6	1	5	242	288	-46	41	12	18	0	3	4	1	3	120	142	-22	41	13	22	0	2	2	0	2	122	146	-24	73	242	440	682	7	4	0	86	73	77	2622	0	879	851	871	2658	765	743	2024	238	36	15.13%	311	72	76.85%	2	1527	2875	53.11%	1528	2936	52.04%	705	1365	51.65%	1942	1319	1942	617	1080	538
2022	82	43	27	0	4	3	3	2	294	256	38	41	23	12	0	1	2	2	1	150	130	20	41	20	15	0	3	1	1	1	144	126	18	105	294	525	819	2	1	0	109	93	85	2794	0	926	952	888	2766	816	585	1922	255	52	20.39%	255	47	81.57%	6	1444	2908	49.66%	1456	2987	48.74%	662	1364	48.53%	1901	1300	1989	610	1069	525
2023	82	38	36	0	2	4	0	2	354	327	27	41	22	16	0	1	2	0	0	183	155	28	41	16	20	0	1	2	0	2	171	172	-1	86	354	631	985	1	3	0	161	110	81	3583	0	1244	1207	1120	3182	911	806	2128	294	69	23.47%	360	99	72.50%	11	1796	3221	55.76%	1757	3129	56.15%	813	1457	55.80%	2003	1401	1901	592	1032	518
2023	82	43	22	0	6	10	0	1	409	326	83	41	23	9	0	4	5	0	0	217	159	58	41	20	13	0	2	5	0	1	192	167	25	109	409	732	1141	0	4	0	153	146	104	3706	0	1214	1163	1297	3307	898	572	1953	299	76	25.42%	263	71	73.00%	8	1734	3298	52.58%	1550	3140	49.36%	786	1531	51.34%	1965	1388	1961	591	1035	512
2024	82	33	37	0	6	3	3	0	322	320	2	41	15	20	0	3	1	2	0	156	159	-3	41	18	17	0	3	2	1	0	166	161	5	87	322	580	902	1	1	0	126	97	90	3021	0	994	999	993	3307	946	744	2043	315	58	18.41%	328	83	74.70%	4	1652	3232	51.11%	1638	3286	49.85%	736	1411	52.16%	1890	1279	2016	614	1051	518
2025	82	41	31	0	7	2	0	1	310	284	26	41	20	18	0	3	0	0	0	147	140	7	41	21	13	0	4	2	0	1	163	144	19	99	310	555	865	1	1	0	102	116	85	3002	0	949	995	1039	2942	929	763	2027	317	72	22.71%	327	78	76.15%	4	1710	3172	53.91%	1658	3177	52.19%	745	1403	53.10%	1920	1310	1965	616	1058	523
Total Regular Season	1140	479	467	0	74	63	25	32	3965	3851	114	570	251	218	0	40	36	11	14	2005	1901	104	570	228	249	0	34	27	14	18	1960	1950	10	1251	3965	7106	11071	24	32	0	1450	1297	1119	39159	0	12936	12960	12887	39076	11435	8653	26499	3417	704	20.60%	3721	843	77.34%	58	20969	40582	51.67%	20911	41322	50.61%	9888	18984	52.09%	26907	18482	27216	8441	14840	7381
Playoff
4	7	3	4	0	0	0	0	0	17	20	-3	3	1	2	0	0	0	0	0	5	8	-3	4	2	2	0	0	0	0	0	12	12	0	6	17	31	48	2	0	0	8	5	4	199	0	63	75	61	201	71	44	129	19	4	21.05%	20	2	90.00%	0	137	243	56.38%	109	230	47.39%	43	99	43.43%	165	113	162	52	91	44
2020	4	0	4	0	0	0	0	0	10	19	-9	2	0	2	0	0	0	0	0	5	10	-5	2	0	2	0	0	0	0	0	5	9	-4	0	10	18	28	0	0	0	4	3	3	118	0	37	38	43	155	42	24	105	9	1	11.11%	10	1	90.00%	0	62	126	49.21%	66	157	42.04%	31	76	40.79%	90	61	98	29	51	25
2022	15	9	6	0	0	0	0	0	52	52	0	7	4	3	0	0	0	0	0	27	30	-3	8	5	3	0	0	0	0	0	25	22	3	18	52	95	147	0	0	0	16	13	19	513	0	148	152	165	634	171	113	376	42	9	21.43%	52	9	82.69%	0	243	538	45.17%	313	658	47.57%	105	256	41.02%	371	251	404	121	210	102
2023	4	0	4	0	0	0	0	0	14	35	-21	2	0	2	0	0	0	0	0	5	18	-13	2	0	2	0	0	0	0	0	9	17	-8	0	14	21	35	0	0	0	4	6	4	121	0	33	44	44	204	44	16	93	18	5	27.78%	8	3	62.50%	0	36	138	26.09%	38	124	30.65%	32	88	36.36%	79	52	108	28	52	23
2024	13	6	7	0	0	0	0	0	38	48	-10	6	1	5	0	0	0	0	0	16	28	-12	7	5	2	0	0	0	0	0	22	20	2	12	38	65	103	0	0	0	18	11	6	451	0	145	149	139	502	159	155	338	46	7	15.22%	60	15	75.00%	0	201	472	42.58%	297	567	52.38%	105	214	49.07%	274	182	354	106	175	80
2025	10	5	5	0	0	0	0	0	37	39	-2	4	2	2	0	0	0	0	0	14	18	-4	6	3	3	0	0	0	0	0	23	21	2	10	37	66	103	0	0	0	20	9	6	377	0	122	127	121	396	97	67	251	45	4	8.89%	27	9	66.67%	1	186	391	47.57%	211	413	51.09%	85	186	45.70%	234	161	241	78	134	65
Total Playoff	53	23	30	0	0	0	0	0	168	213	-45	24	8	16	0	0	0	0	0	72	112	-40	29	15	14	0	0	0	0	0	96	101	-5	46	168	296	464	2	0	0	70	47	42	1779	0	548	585	573	2092	584	419	1292	179	30	16.76%	177	39	77.97%	1	865	1908	45.34%	1034	2149	48.12%	401	919	43.63%	1215	821	1370	416	716	343