NHLS - National Hockey League Simulated

IceHogs

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
GM : Mathieu et remy | Morale : 75 | Team Overall : 61
Next Games #13 vs Crunch

Blackhawks
Roster
Scoring
Informations
Lines
Stats
Schedule
Finance
Records

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	TA	SP
Scratches
1	Ryan Leonard (R)			X		100.00	75	42	80	77	79	84	88	74	61	72	73	64	76	60	63	87	75	69		0
2	Cole Reinhardt		X			100.00	73	42	80	68	79	82	83	63	65	61	62	60	63	66	68	47	75	64		0
3	Landon Slaggert		X			100.00	69	39	86	67	70	78	85	63	57	60	59	68	62	64	65	63	75	63		0
4	Antonio Stranges	X				100.00	57	37	90	64	66	89	83	63	65	62	61	60	64	65	67	58	75	62		0
5	Carter Mazur			X		100.00	64	38	85	65	74	85	67	63	55	60	64	62	65	63	66	67	75	62		0
6	Danila Klimovich			X		100.00	72	42	73	61	81	95	84	59	60	57	63	61	62	64	65	74	75	62		0
7	Filip Mesar			X		100.00	56	37	88	58	65	74	81	57	62	59	56	53	58	62	64	80	75	59		0
8	Tyler Boucher			X		100.00	69	56	70	59	78	79	77	57	54	56	58	55	59	63	65	85	75	59		0
9	Justin Janicke (R)		X			100.00	60	36	90	58	69	83	63	57	68	62	50	54	56	63	65	49	75	58		0
10	Alec Regula				X	100.00	75	44	67	63	89	82	68	59	30	63	56	64	48	66	68	63	75	62		0
11	Isaak Phillips				X	100.00	73	41	73	61	84	76	86	58	30	55	65	59	52	65	67	54	75	62		0
12	Hunter Brzustewicz				X	100.00	62	36	94	63	72	83	86	59	30	64	57	58	49	62	64	66	75	61		0
13	Corson Ceulemans				X	100.00	71	38	76	58	80	82	78	57	30	56	55	59	46	63	65	81	75	60		0
14	Jakub Dvorak (R)				X	100.00	81	43	76	55	90	62	77	54	30	53	52	58	45	61	63	71	75	59		0
15	Noah Warren				X	100.00	82	42	83	53	91	62	83	52	30	54	51	59	45	62	64	74	75	59		0
16	Leo Loof				X	100.00	67	41	73	56	76	63	80	53	30	55	52	57	45	64	66	62	75	58		0

	TEAM AVERAGE					100.00	69	41	80	62	78	79	79	59	47	59	58	59	56	63	65	68	75	61

Show or Hide Column

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	TA	SP
Scratches
1	Kirill Gerasimyuk (R)	100.00	71	78	74	76	70	69	71	70	69	71	70	63	69	49	75	62		0
2	Isak Posch (R)	100.00	64	82	78	85	63	62	64	63	62	64	63	64	71	43	75	58		0

	TEAM AVERAGE	100.00	68	80	76	81	67	66	68	67	66	68	67	64	70	46	75	60

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Michael Peca	64	66	65	67	78	72	73	CAN	52	2	500,000$

Show or Hide Column

Filter Tips

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

#	Player Name	Team Name	POS	GP	G	A	P	+/-	PIM	PIM5	HIT	HTT	SHT	OSB	OSM	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PPM	PKG	PKA	PKP	PKS	PKM	GW	GT	FO%	FOT	GA	TA	EG	HT	P/20	PSG	PSS	FW	FL	FT	S1	S2	S3

Show or Hide Column

Filter Tips

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

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

Show or Hide Column

Filter Tips

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

Player Name	Team Name	POS	Age	Birthday	Rookie	Weight	Height	No Trade	Available For Trade	Force Waivers	Contract	Status	Type	Current Salary	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Link
Alec Regula		D	27	2000-08-06	No	211 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Antonio Stranges		C	25	2002-02-05	No	168 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Carter Mazur		RW	25	2002-03-28	No	200 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Cole Reinhardt		LW	27	2000-02-01	No	207 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Corson Ceulemans		D	24	2003-05-05	No	198 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	850,000$	0$	0$	No	Link / NHL Link
Danila Klimovich		RW	24	2003-01-09	No	202 Lbs	6 ft2	No	No	No	2	RFA	Pro & Farm	999,999$	0$	0$	No	Link / NHL Link
Filip Mesar		RW	23	2004-01-03	No	176 Lbs	5 ft9	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Hunter Brzustewicz		D	23	2004-11-29	No	190 Lbs	6 ft0	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Isaak Phillips		D	26	2001-09-28	No	205 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	856,400$	0$	0$	No	Link / NHL Link
Isak Posch		G	25	2002-01-31	Yes	209 Lbs	6 ft3	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Jakub Dvorak		D	22	2005-05-25	Yes	203 Lbs	6 ft5	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Justin Janicke		LW	24	2003-06-30	Yes	185 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Kirill Gerasimyuk		G	24	2003-08-22	Yes	178 Lbs	6 ft2	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Landon Slaggert		LW	25	2002-06-25	No	180 Lbs	6 ft0	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Leo Loof		D	25	2002-04-25	No	176 Lbs	6 ft2	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Noah Warren		D	23	2004-07-15	No	224 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Ryan Leonard		RW	22	2005-01-21	Yes	205 Lbs	6 ft1	No	No	No	3	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link
Tyler Boucher		RW	24	2003-01-16	No	205 Lbs	6 ft1	No	No	No	1	RFA	Pro & Farm	925,000$	0$	0$	No	Link / NHL Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
18	24.33	196 Lbs	6 ft1	1.89	908,689$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense		Time %	PHY	DF	OF
1				40	1	2	2
2				30	1	2	2
3				20	1	2	2
4				10	1	2	2

Power Play Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				60	1	2	2
2				40	1	2	2

Power Play Defense
Line #	Defense	Defense		Time %	PHY	DF	OF
1				60	1	2	2
2				40	1	2	2

Penalty Kill 4 Players Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

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

Penalty Kill 3 Players
Line #	Wing	Time %	PHY	DF	OF	Defense	Defense	Time %	PHY	DF	OF
1		60	1	2	2			60	1	2	2
2		40	1	2	2			40	1	2	2

4 vs 4 Forward
Line #	Center	Wing	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

4 vs 4 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			60	1	2	2
2			40	1	2	2

Last Minutes Offensive
Left Wing	Center	Right Wing	Defense	Defense

Last Minutes Defensive
Left Wing	Center	Right Wing	Defense	Defense

Extra Forwards
Normal	PowerPlay	Penalty Kill
, ,	,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
, ,		,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

Show or Hide Column

Filter Tips

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

			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
1 - 2026-09-19	13	Crunch	-	IceHogs	-
2 - 2026-09-20	20	IceHogs	-	Penguins	-
4 - 2026-09-22	35	IceHogs	-	Rocket	-
5 - 2026-09-23	64	Moose	-	IceHogs	-
7 - 2026-09-25	67	IceHogs	-	Checkers	-
8 - 2026-09-26	85	IceHogs	-	Silver Knights	-
10 - 2026-09-28	99	IceHogs	-	Monsters	-
11 - 2026-09-29	122	Comets	-	IceHogs	-
13 - 2026-10-01	135	Reign	-	IceHogs	-
14 - 2026-10-02	150	Wild	-	IceHogs	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	3000	2000
Ticket Price	50	30
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
5	0 - 0.00%	0$	0$	5000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
0$	1,635,640$	1,635,640$	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$	14	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
2020	56	29	19	0	2	1	4	1	215	191	24	28	17	7	0	0	1	2	1	115	86	29	28	12	12	0	2	0	2	0	100	105	-5	72	215	391	606	0	0	0	80	67	62	2044	0	664	692	658	1890	536	315	1262	196	50	25.51%	131	31	76.34%	1	1128	2139	52.73%	1082	2018	53.62%	491	942	52.12%	1344	929	1312	415	735	370
2021	82	36	28	0	8	6	1	3	307	288	19	41	19	11	0	6	3	0	2	163	142	21	41	17	17	0	2	3	1	1	144	146	-2	99	307	547	854	1	2	0	118	103	77	2804	0	966	927	874	2687	786	553	1870	241	53	21.99%	237	55	76.79%	4	1525	2964	51.45%	1439	2820	51.03%	673	1383	48.66%	1952	1345	1944	599	1071	535
2022	82	46	25	0	2	5	1	3	327	262	65	41	28	9	0	1	3	0	0	174	130	44	41	18	16	0	1	2	1	3	153	132	21	106	327	593	920	4	0	0	125	96	103	3038	0	1050	972	997	2519	749	588	1764	315	64	20.32%	257	62	75.88%	2	1636	3139	52.12%	1417	2831	50.05%	716	1393	51.40%	2019	1404	1869	608	1067	541
2023	83	42	25	0	4	3	4	5	303	236	67	41	21	13	0	3	3	1	0	147	115	32	42	21	12	0	1	0	3	5	156	121	35	108	303	536	839	0	0	0	89	102	104	2846	0	889	962	958	2695	818	674	1984	301	54	17.94%	289	57	80.28%	1	1516	3000	50.53%	1512	2984	50.67%	678	1355	50.04%	1988	1379	1982	616	1067	531
2024	82	34	34	0	1	3	6	4	202	218	-16	41	20	13	0	1	3	2	2	106	96	10	41	14	21	0	0	0	4	2	96	122	-26	89	202	357	559	3	8	0	67	59	69	2232	0	681	783	743	2289	682	625	1886	247	48	19.43%	270	40	85.19%	1	1324	2555	51.82%	1384	2736	50.58%	596	1189	50.13%	1935	1329	1985	621	1059	523
2025	82	49	25	0	4	3	1	0	242	197	45	41	28	9	0	2	2	0	0	125	92	33	41	21	16	0	2	1	1	0	117	105	12	111	242	430	672	2	10	0	80	85	72	2415	0	788	867	750	2240	653	580	1941	262	48	18.32%	255	43	83.14%	1	1363	2723	50.06%	1296	2604	49.77%	619	1252	49.44%	1993	1388	1894	596	1051	525
Total Regular Season	467	236	156	0	21	21	17	16	1596	1392	204	233	133	62	0	13	15	5	5	830	661	169	234	103	94	0	8	6	12	11	766	731	35	585	1596	2854	4450	10	20	0	559	512	487	15379	0	5038	5203	4980	14320	4224	3335	10707	1562	317	20.29%	1439	288	79.99%	10	8492	16520	51.40%	8130	15993	50.83%	3773	7514	50.21%	11233	7777	10988	3458	6052	3026
Playoff
2020	12	7	5	0	0	0	0	0	43	32	11	7	3	4	0	0	0	0	0	21	19	2	5	4	1	0	0	0	0	0	22	13	9	14	43	85	128	0	3	0	15	17	10	445	0	139	135	167	372	103	57	273	43	8	18.60%	26	5	80.77%	0	261	474	55.06%	194	409	47.43%	106	194	54.64%	314	223	258	85	152	77
2021	18	10	8	0	0	0	0	0	68	66	2	9	7	2	0	0	0	0	0	37	26	11	9	3	6	0	0	0	0	0	31	40	-9	20	68	130	198	0	0	0	24	22	20	611	0	190	208	195	584	201	145	415	70	14	20.00%	60	14	76.67%	1	336	678	49.56%	337	662	50.91%	152	309	49.19%	437	301	436	137	237	115
2022	18	8	10	0	0	0	0	0	68	70	-2	10	6	4	0	0	0	0	0	36	27	9	8	2	6	0	0	0	0	0	32	43	-11	16	68	124	192	0	0	0	17	24	26	617	0	182	206	213	672	191	186	383	62	18	29.03%	79	19	75.95%	1	342	669	51.12%	321	693	46.32%	147	318	46.23%	421	285	446	135	235	113
2023	9	4	5	0	0	0	0	0	28	32	-4	5	2	3	0	0	0	0	0	13	15	-2	4	2	2	0	0	0	0	0	15	17	-2	8	28	53	81	0	0	0	12	10	6	304	0	103	103	98	311	102	97	212	32	5	15.63%	42	7	83.33%	0	149	319	46.71%	150	329	45.59%	72	150	48.00%	198	132	227	69	114	55
2025	5	1	4	0	0	0	0	0	15	20	-5	3	1	2	0	0	0	0	0	8	10	-2	2	0	2	0	0	0	0	0	7	10	-3	2	15	25	40	1	0	0	4	6	5	143	0	41	44	53	133	44	34	131	19	3	15.79%	14	3	78.57%	1	70	164	42.68%	72	145	49.66%	37	84	44.05%	125	87	117	38	67	33
Total Playoff	62	30	32	0	0	0	0	0	222	220	2	34	19	15	0	0	0	0	0	115	97	18	28	11	17	0	0	0	0	0	107	123	-16	60	222	417	639	1	3	0	72	79	67	2120	0	655	696	726	2072	641	519	1414	226	48	21.24%	221	48	78.28%	3	1158	2304	50.26%	1074	2238	47.99%	514	1055	48.72%	1496	1029	1485	467	807	394

Back to the Top