LHSDB - Ligue de hockey simulee des debiles barbus

Utah Mammoth
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	Jiri Kulich	0	X				100.00	65	37	89	73	75	85	83	67	71	62	69	65	68	61	64	80	50	66	0
2	Phillip Di Giuseppe	0		X	X		100.00	75	40	83	67	73	85	77	63	58	62	60	69	64	74	72	46	50	65	0
3	Pat Maroon	0		X			100.00	74	84	66	64	90	80	82	66	55	68	59	61	56	85	78	22	50	65	0
4	Max Jones	0		X			100.00	81	53	75	63	87	80	82	62	58	63	62	60	65	68	69	71	50	64	0
5	Jujhar Khaira	0	X	X			100.00	80	78	75	61	89	78	70	58	64	62	57	63	59	71	73	52	50	63	0
6	Anders Bjork	0	X	X	X		100.00	63	37	92	64	72	74	73	63	59	60	57	62	58	69	71	45	50	62	0
7	Jared Davidson	0	X				100.00	63	39	76	61	70	84	80	59	66	58	62	57	61	64	65	57	50	61	0
8	Alexis Gendron	0			X		100.00	55	38	76	61	64	84	74	58	55	54	62	53	60	62	64	51	50	59	0
9	Pavel Mintyukov	0				X	100.00	72	35	90	71	77	89	85	67	30	76	62	68	54	63	65	86	50	69	0
10	Gustav Lindstrom	0				X	100.00	72	39	81	64	79	82	77	62	30	67	60	63	51	67	69	64	50	65	0
11	Maksymilian Szuber	0				X	100.00	72	40	77	60	81	82	86	58	30	62	55	59	48	63	65	49	50	63	0
12	Casey Fitzgerald	0				X	100.00	61	41	71	58	70	69	85	56	30	57	54	55	46	68	73	53	50	60	0
13	Gavin White	0				X	100.00	65	37	92	55	74	68	77	54	30	56	52	53	46	63	65	59	50	58	0
Scratches
1	Owen Beck	0	X				100.00	69	39	79	66	74	80	74	64	70	62	58	65	63	62	61	77	50	63	0
2	Jordan Dumais	0			X		100.00	60	35	94	62	64	71	63	61	65	60	59	57	64	61	63	65	50	59	0
3	Parker Bell	0		X			100.00	76	39	83	53	85	69	71	52	56	51	54	57	53	62	64	49	50	57	0
4	Ben Hemmerling	0			X		100.00	58	36	95	56	67	71	62	54	51	53	53	55	54	61	63	49	50	56	0
5	Arber Xhekaj	0				X	100.00	85	88	58	65	94	84	85	63	30	67	59	66	50	65	68	43	50	68	0
6	Nick DeSimone	0				X	100.00	69	38	95	65	79	82	74	64	30	67	60	61	52	71	73	34	50	65	0
7	Kirill Kudryavtsev	0				X	100.00	63	36	90	61	73	80	72	59	30	60	54	57	49	61	63	49	50	61	0
8	Elias Salomonsson	0				X	100.00	60	38	86	62	69	70	69	58	30	63	54	55	47	61	63	71	50	59	0
9	Jackson Edward	0				X	100.00	70	39	86	54	79	63	65	53	30	56	52	55	45	61	63	49	50	58	0
10	Jake Furlong	0				X	100.00	66	38	92	55	75	64	71	54	30	53	52	55	46	61	63	57	50	58	0

	TEAM AVERAGE					100.00	68	45	83	62	77	77	76	60	46	61	58	60	55	65	67	56	50	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	SP
1	Cayden Primeau	100.00	82	82	78	84	81	80	82	81	80	82	81	66	75	56	50	78	0
2	Matt Murray	100.00	74	76	71	93	73	72	74	73	72	74	73	75	85	53	50	74	0
Scratches
1	Dennis Hildeby	100.00	77	86	82	98	76	75	77	76	75	77	76	64	71	57	50	76	0
2	Vyacheslav Buteyets	100.00	57	70	66	88	56	55	57	56	55	57	56	63	69	49	50	61	0

	TEAM AVERAGE	100.00	73	79	74	91	72	71	73	72	71	73	72	67	75	54	50	72

Coaches Name	PH	DF	OF	PD	EX	LD	PO	CNT	Age	Contract	Salary
Bruce Boudreau	70	69	75	68	99	97	38	CAN	70	7	3,200,000$

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	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
Alexis Gendron	RW	22	2003-12-30	No	175 Lbs	5 ft9	No	No	No	3	ELC	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Anders Bjork	C/LW/RW	29	1996-08-05	No	190 Lbs	6 ft0	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Arber Xhekaj	D	25	2001-01-30	No	240 Lbs	6 ft4	No	No	No	2	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Ben Hemmerling	RW	21	2004-04-21	No	174 Lbs	5 ft11	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Casey Fitzgerald	D	29	1997-02-25	No	188 Lbs	5 ft11	No	No	No	2	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Cayden Primeau	G	26	1999-08-11	No	205 Lbs	6 ft3	No	No	No	2	RFA	Pro & Farm	1,000,000$	0$	0$	No	Link / NHL Link
Dennis Hildeby	G	24	2001-08-19	No	224 Lbs	6 ft7	No	No	No	3	RFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Elias Salomonsson	D	21	2004-08-31	No	172 Lbs	6 ft0	No	No	No	4	ELC	Pro & Farm	500,000$	0$	0$	No	Link
Gavin White	D	23	2002-11-12	No	196 Lbs	6 ft0	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Gustav Lindstrom	D	27	1998-10-20	No	194 Lbs	6 ft2	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Jackson Edward	D	22	2004-02-27	No	193 Lbs	6 ft2	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Jake Furlong	D	21	2004-03-04	No	189 Lbs	6 ft1	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Jared Davidson	C	23	2002-07-07	No	188 Lbs	5 ft11	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Jiri Kulich	C	21	2004-04-14	No	190 Lbs	6 ft1	No	No	No	3	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Jordan Dumais	RW	21	2004-04-15	No	173 Lbs	5 ft8	No	No	No	4	ELC	Pro & Farm	900,000$	0$	0$	No	Link
Jujhar Khaira	C/LW	31	1994-08-13	No	212 Lbs	6 ft4	No	No	No	3	UFA	Pro & Farm	949,750$	0$	0$	No	Link / NHL Link
Kirill Kudryavtsev	D	22	2004-02-05	No	200 Lbs	5 ft11	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Maksymilian Szuber	D	23	2002-08-25	No	190 Lbs	6 ft3	No	No	No	3	RFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Matt Murray	G	31	1994-05-25	No	220 Lbs	6 ft5	No	No	No	3	UFA	Pro & Farm	713,124$	0$	0$	No	Link / NHL Link
Max Jones	LW	28	1998-02-17	No	216 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Nick DeSimone	D	31	1994-11-21	No	194 Lbs	6 ft2	No	No	No	2	UFA	Pro & Farm	1,000,000$	0$	0$	No	Link / NHL Link
Owen Beck	C	22	2004-02-03	No	199 Lbs	6 ft0	No	No	No	4	ELC	Pro & Farm	900,000$	0$	0$	No	Link
Parker Bell	LW	22	2003-09-26	No	192 Lbs	6 ft4	No	No	No	4	ELC	Pro & Farm	300,000$	0$	0$	No	Link
Pat Maroon	LW	37	1988-04-23	No	234 Lbs	6 ft3	No	No	No	1	UFA	Pro & Farm	300,000$	0$	0$	No	Link / NHL Link
Pavel Mintyukov	D	22	2003-11-25	No	200 Lbs	6 ft1	No	No	No	3	ELC	Pro & Farm	900,000$	0$	0$	No	Link / NHL Link
Phillip Di Giuseppe	LW/RW	32	1993-10-09	No	193 Lbs	6 ft0	No	No	No	1	UFA	Pro & Farm	500,000$	0$	0$	No	Link / NHL Link
Vyacheslav Buteyets	G	23	2002-05-29	No	210 Lbs	6 ft4	No	No	No	4	RFA	Pro & Farm	300,000$	0$	0$	No	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
27	25.15	198 Lbs	6 ft1	2.81	517,143$

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
50	26	L5	151	290	441	1572	2369	733	405	992	1	1

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
50	10	37	3	0	0	0	151	276

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
24	7	16	1	0	0	0	72	122

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
26	3	21	2	0	0	0	79	154

Last 10 Games
W	L	OTW	OTL	SOW	SOL
1	7	2	0	0	0

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
179	30	16.76%	165	44	73.33%	1

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
510	474	576	12	59	37	52	3

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
507	1340	37.84%	644	1805	35.68%	297	855	34.74%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
854	585	1610	356	543	228

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	Link
8 - 2025-08-22	7	Roadrunners	2	Eagles	6	L		BoxScore
9 - 2025-08-23	22	Roadrunners	2	Eagles	6	L		BoxScore
16 - 2025-08-30	57	Stars	5	Roadrunners	1	L		BoxScore
17 - 2025-08-31	64	Stars	5	Roadrunners	1	L		BoxScore
22 - 2025-09-05	80	Condors	3	Roadrunners	5	W		BoxScore
23 - 2025-09-06	93	Condors	6	Roadrunners	4	L		BoxScore
26 - 2025-09-09	103	Roadrunners	1	Canucks	6	L		BoxScore
27 - 2025-09-10	110	Roadrunners	3	Canucks	6	L		BoxScore
37 - 2025-09-20	168	Gulls	6	Roadrunners	3	L		BoxScore
38 - 2025-09-21	177	Gulls	5	Roadrunners	0	L		BoxScore
41 - 2025-09-24	188	Roadrunners	4	Reign	7	L		BoxScore
43 - 2025-09-26	199	Roadrunners	2	Silver Knights	9	L		BoxScore
44 - 2025-09-27	214	Roadrunners	2	Silver Knights	5	L		BoxScore
50 - 2025-10-03	237	Wranglers	2	Roadrunners	5	W		BoxScore
51 - 2025-10-04	252	Wranglers	2	Roadrunners	3	W		BoxScore
54 - 2025-10-07	259	Firebirds	11	Roadrunners	1	L		BoxScore
55 - 2025-10-08	266	Firebirds	5	Roadrunners	0	L		BoxScore
58 - 2025-10-11	289	Roadrunners	1	Gulls	7	L		BoxScore
64 - 2025-10-17	316	Roadrunners	5	Wranglers	6	L		BoxScore
65 - 2025-10-18	328	Roadrunners	2	Wranglers	5	L		BoxScore
71 - 2025-10-24	359	Silver Knights	1	Roadrunners	5	W		BoxScore
72 - 2025-10-25	371	Silver Knights	7	Roadrunners	5	L		BoxScore
74 - 2025-10-27	382	Gulls	7	Roadrunners	0	L		BoxScore
76 - 2025-10-29	393	Gulls	7	Roadrunners	0	L		BoxScore
78 - 2025-10-31	405	Roadrunners	5	Canucks	7	L		BoxScore
79 - 2025-11-01	411	Roadrunners	7	Canucks	6	W		BoxScore
86 - 2025-11-08	450	Eagles	6	Roadrunners	4	L		BoxScore
87 - 2025-11-09	455	Eagles	5	Roadrunners	6	W		BoxScore
92 - 2025-11-14	477	Roadrunners	2	Stars	0	W		BoxScore
93 - 2025-11-15	490	Roadrunners	3	Stars	8	L		BoxScore
97 - 2025-11-19	508	Roadrunners	3	Firebirds	4	L		BoxScore
99 - 2025-11-21	520	Roadrunners	1	Gulls	8	L		BoxScore
100 - 2025-11-22	531	Roadrunners	0	Gulls	6	L		BoxScore
103 - 2025-11-25	543	Roadrunners	6	Wranglers	3	W		BoxScore
104 - 2025-11-26	553	Roadrunners	6	Wranglers	7	L		BoxScore
109 - 2025-12-01	590	Silver Knights	7	Roadrunners	1	L		BoxScore
111 - 2025-12-03	592	Silver Knights	8	Roadrunners	2	L		BoxScore
113 - 2025-12-05	609	Canucks	5	Roadrunners	6	W	X	BoxScore
114 - 2025-12-06	624	Canucks	7	Roadrunners	5	L		BoxScore
120 - 2025-12-12	657	Reign	3	Roadrunners	7	W		BoxScore
121 - 2025-12-13	673	Reign	1	Roadrunners	3	W		BoxScore
127 - 2025-12-19	689	Roadrunners	1	Barracuda	6	L		BoxScore
128 - 2025-12-20	692	Roadrunners	2	Barracuda	9	L		BoxScore
131 - 2025-12-23	710	Roadrunners	6	Condors	5	W	X	BoxScore
132 - 2025-12-24	718	Roadrunners	8	Reign	7	W	X	BoxScore
135 - 2025-12-27	739	Roadrunners	2	Silver Knights	7	L		BoxScore
136 - 2025-12-28	750	Roadrunners	1	Silver Knights	5	L		BoxScore
139 - 2025-12-31	766	Roadrunners	2	Firebirds	3	L		BoxScore
142 - 2026-01-03	789	Canucks	3	Roadrunners	2	L		BoxScore
143 - 2026-01-04	800	Canucks	5	Roadrunners	3	L		BoxScore
148 - 2026-01-09	821	IceHogs	-	Roadrunners	-
149 - 2026-01-10	838	IceHogs	-	Roadrunners	-
153 - 2026-01-14	857	Roadrunners	-	Reign	-
Trade Deadline --- Trades can’t be done after this day is simulated!
155 - 2026-01-16	866	Roadrunners	-	Condors	-
156 - 2026-01-17	881	Roadrunners	-	Condors	-
159 - 2026-01-20	890	Reign	-	Roadrunners	-
160 - 2026-01-21	898	Reign	-	Roadrunners	-
163 - 2026-01-24	923	Barracuda	-	Roadrunners	-
164 - 2026-01-25	932	Barracuda	-	Roadrunners	-
170 - 2026-01-31	969	Roadrunners	-	Eagles	-
171 - 2026-02-01	977	Roadrunners	-	Eagles	-
174 - 2026-02-04	989	Roadrunners	-	Reign	-
176 - 2026-02-06	999	Roadrunners	-	Gulls	-
177 - 2026-02-07	1016	Roadrunners	-	Condors	-
180 - 2026-02-10	1027	Wranglers	-	Roadrunners	-
181 - 2026-02-11	1035	Wranglers	-	Roadrunners	-
184 - 2026-02-14	1062	Condors	-	Roadrunners	-
185 - 2026-02-15	1069	Condors	-	Roadrunners	-
190 - 2026-02-20	1086	Roadrunners	-	IceHogs	-
191 - 2026-02-21	1101	Roadrunners	-	IceHogs	-
197 - 2026-02-27	1137	Eagles	-	Roadrunners	-
198 - 2026-02-28	1151	Eagles	-	Roadrunners	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Arena Capacity	2000	1000
Ticket Price	35	15
Attendance	45,833	22,674
Attendance PCT	95.49%	94.48%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Arena Capacity	Team Popularity
12	2854 - 95.15%	71,290$	1,710,955$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Average Salaries	Coaches Salaries
2,423,100$	144,629$	144,629$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	103,100$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
855,478$	55	16,723$	919,765$

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	35	29	0	3	6	4	5	294	257	37	41	18	12	0	1	4	2	4	173	131	42	41	17	17	0	2	2	2	1	121	126	-5	95	294	476	770	0	7	0	115	95	77	2444	0	797	796	824	2036	600	1033	1607	504	89	17.66%	417	83	80.10%	6	1298	2515	51.61%	1146	2215	51.74%	691	1282	53.90%	2219	1643	1823	555	937	481
13	68	23	37	0	1	4	2	1	174	216	-42	34	13	16	0	0	3	1	1	90	114	-24	34	10	21	0	1	1	1	0	84	102	-18	57	174	299	473	1	4	0	61	56	54	1665	0	528	530	591	1873	548	863	1253	411	54	13.14%	339	60	82.30%	3	1093	1948	56.11%	1063	1973	53.88%	559	988	56.58%	1603	1132	1711	493	794	386
14	68	38	16	0	2	4	3	5	239	167	72	34	17	12	0	1	2	1	1	110	81	29	34	21	4	0	1	2	2	4	129	86	43	95	239	429	668	0	5	0	94	84	56	2288	0	797	709	755	1630	429	795	1280	306	63	20.59%	274	43	84.31%	4	1365	2201	62.02%	1063	1781	59.69%	622	1015	61.28%	1996	1495	1350	421	783	428
14	68	38	16	0	2	4	3	5	239	167	72	34	17	12	0	1	2	1	1	110	81	29	34	21	4	0	1	2	2	4	129	86	43	95	239	429	668	0	5	0	94	84	56	2288	0	797	709	755	1630	429	795	1280	306	63	20.59%	274	43	84.31%	4	1365	2201	62.02%	1063	1781	59.69%	622	1015	61.28%	1996	1495	1350	421	783	428
14	68	38	16	0	2	4	3	5	239	167	72	34	17	12	0	1	2	1	1	110	81	29	34	21	4	0	1	2	2	4	129	86	43	95	239	429	668	0	5	0	94	84	56	2288	0	797	709	755	1630	429	795	1280	306	63	20.59%	274	43	84.31%	4	1365	2201	62.02%	1063	1781	59.69%	622	1015	61.28%	1996	1495	1350	421	783	428
15	82	34	29	0	5	5	1	8	235	195	40	41	19	13	0	2	1	1	5	118	94	24	41	15	16	0	3	4	0	3	117	101	16	93	235	407	642	1	5	0	80	68	81	2113	0	641	668	777	2125	653	1108	1649	427	85	19.91%	458	62	86.46%	2	1130	2410	46.89%	1075	2558	42.03%	540	1138	47.45%	2080	1484	1948	573	955	484
15	82	34	29	0	5	5	1	8	235	195	40	41	19	13	0	2	1	1	5	118	94	24	41	15	16	0	3	4	0	3	117	101	16	93	235	407	642	1	5	0	80	68	81	2113	0	641	668	777	2125	653	1108	1649	427	85	19.91%	458	62	86.46%	2	1130	2410	46.89%	1075	2558	42.03%	540	1138	47.45%	2080	1484	1948	573	955	484
16	82	19	56	0	4	1	0	2	223	364	-141	41	9	28	0	3	1	0	0	112	179	-67	41	10	28	0	1	0	0	2	111	185	-74	49	223	394	617	1	0	0	82	84	53	2298	0	755	832	700	3009	912	1013	1655	376	48	12.77%	434	116	73.27%	3	952	2315	41.12%	1107	2724	40.64%	526	1263	41.65%	1639	1149	2395	581	906	409
17	72	7	58	0	3	3	1	0	134	388	-254	36	3	30	0	2	1	0	0	69	189	-120	36	4	28	0	1	2	1	0	65	199	-134	25	134	259	393	0	0	0	54	35	41	1748	0	607	542	586	3632	1028	650	1237	242	14	5.79%	299	76	74.58%	0	493	1601	30.79%	794	2676	29.67%	323	1123	28.76%	999	652	2584	518	749	287
18	72	9	55	0	6	2	0	0	216	435	-219	36	8	22	0	4	2	0	0	117	192	-75	36	1	33	0	2	0	0	0	99	243	-144	32	216	420	636	1	0	0	82	67	61	2232	0	697	752	757	3561	993	681	1408	228	28	12.28%	272	76	72.06%	1	754	1764	42.74%	1002	2508	39.95%	487	1266	38.47%	1195	821	2369	500	771	322
19	70	19	46	0	3	1	0	1	213	355	-142	34	10	21	0	2	1	0	0	112	167	-55	36	9	25	0	1	0	0	1	101	188	-87	46	213	417	630	0	0	0	93	70	47	2343	0	759	812	765	3461	984	583	1558	242	33	13.64%	260	68	73.85%	2	868	1927	45.04%	1016	2529	40.17%	485	1202	40.35%	1254	864	2189	485	765	336
20	50	10	37	0	3	0	0	0	151	276	-125	24	7	16	0	1	0	0	0	72	122	-50	26	3	21	0	2	0	0	0	79	154	-75	26	151	290	441	1	1	59	37	52	3	1572	510	474	576	12	2369	733	405	992	179	30	16.76%	165	44	73.33%	1	507	1340	37.84%	644	1805	35.68%	297	855	34.74%	854	585	1610	356	543	228
Total Regular Season	864	304	424	0	39	39	18	40	2592	3182	-590	430	157	207	0	20	20	8	18	1311	1525	-214	434	147	217	0	19	19	10	22	1281	1657	-376	801	2592	4656	7248	6	37	59	966	847	666	25392	510	8290	8303	8054	29081	8391	9829	16848	3954	655	16.57%	3924	776	80.22%	32	12320	24833	49.61%	12111	26889	45.04%	6314	13300	47.47%	19917	14304	22632	5900	9731	4707
Playoff
11	7	3	4	0	0	0	0	0	13	18	-5	3	2	1	0	0	0	0	0	6	5	1	4	1	3	0	0	0	0	0	7	13	-6	6	13	22	35	0	1	0	4	3	6	156	0	41	63	52	186	55	94	129	62	11	17.74%	39	2	94.87%	0	95	213	44.60%	84	217	38.71%	37	89	41.57%	147	102	195	51	77	36
14	12	7	5	0	0	0	0	0	27	27	0	5	1	4	0	0	0	0	0	8	19	-11	7	6	1	0	0	0	0	0	19	8	11	14	27	45	72	0	3	0	9	7	8	270	0	82	84	80	297	77	176	216	67	11	16.42%	77	10	87.01%	0	189	400	47.25%	207	400	51.75%	86	176	48.86%	293	194	317	101	164	79
Total Playoff	19	10	9	0	0	0	0	0	40	45	-5	8	3	5	0	0	0	0	0	14	24	-10	11	7	4	0	0	0	0	0	26	21	5	20	40	67	107	0	4	0	13	10	14	426	0	123	147	132	483	132	270	345	129	22	17.05%	116	12	89.66%	0	284	613	46.33%	291	617	47.16%	123	265	46.42%	440	297	512	152	242	115