Utah Mammoth
Home
Roster
Players Stats
Players Info
Lines
Team Stats
Schedule
Career Team Stats

Game Center
	Tucson Roadrunners 13-16-2, 28pts	4	Box score	3	Rhode Island Red Army 17-12-1, 35pts

Team Stats
L1	Streak	L2
7-7-1	Home Record	6-8-1
6-9-1	Home Record	11-4-0
3-6-1	Last 10 Games	3-6-1
3.71	Goals Per Game	4.20
4.19	Goals Against Per Game	4.33
23.02%	Power Play Percentage	14.05%
80.42%	Penalty Kill Percentage	83.21%

Syracuse Crunch
15-14-1, 31pts

Box score

Tucson Roadrunners
13-16-2, 28pts

Team Stats
L1	Streak	L1
8-8-0	Home Record	7-7-1
7-6-1	Home Record	6-9-1
6-4-0	Last 10 Games	3-6-1
4.27	Goals Per Game	3.71
4.37	Goals Against Per Game	4.19
16.91%	Power Play Percentage	23.02%
85.00%	Penalty Kill Percentage	80.42%

Tucson Roadrunners
13-16-2, 28pts

Day 69

Kimberley Dynamiters
15-12-3, 33pts

Team Stats
L1	Streak	W6
7-7-1	Home Record	8-4-3
6-9-1	Away Record	7-8-0
3-6-1	Last 10 Games	7-2-1
3.71	Goals Per Game	3.87
4.19	Goals Against Per Game	3.87
23.02%	Power Play Percentage	17.14%
80.42%	Penalty Kill Percentage	78.46%

Grand Rapids Griffins
17-12-4, 38pts

Day 70

Tucson Roadrunners
13-16-2, 28pts

Team Stats
L2	Streak	L1
7-5-3	Home Record	7-7-1
10-7-1	Away Record	6-9-1
4-5-1	Last 10 Games	3-6-1
3.52	Goals Per Game	3.71
3.79	Goals Against Per Game	3.71
14.18%	Power Play Percentage	23.02%
84.28%	Penalty Kill Percentage	80.42%

Tucson Roadrunners
13-16-2, 28pts

Day 74

Syracuse Crunch
15-14-1, 31pts

Team Stats
L1	Streak	L1
7-7-1	Home Record	8-8-0
6-9-1	Away Record	7-6-1
3-6-1	Last 10 Games	6-4-0
3.71	Goals Per Game	4.27
4.19	Goals Against Per Game	4.27
23.02%	Power Play Percentage	16.91%
80.42%	Penalty Kill Percentage	85.00%

Team Leaders
	Goals Ryan Winterton 15	Assists Yan Kuznetsov 21

	Points Yan Kuznetsov 27	Plus/Minus Ryan Winterton -5

Team Stats
Goals For 115 3.71 GFG	Shots For 1210 39.03 Avg	Power Play Percentage 23.0% 29 GF	Offensive Zone Start 39.5%
Goals Against 130 4.19 GAA	Shots Against 1328 42.84 Avg	Penalty Kill Percentage 80.4%% 28 GA	Defensive Zone Start 42.6%

Team Info
	General Manager	Adam D-S
	Division	Pacific Division
	Conference	Western Conference
	Captain
	Assistant #1
	Assistant #2
Arena Info
	Capacity	3,000
	Attendance	0
	Season Tickets	300
Roster Info
	Pro Team	17
	Farm Team	20
	Contract Limit	37 / 60
	Prospects	20
Team History
	This Season	13-16-2 (28PTS)
	History	75-97-19 (0.393%)
	Playoff Appearances	0
	Playoff Record (W-L)	0 - 0
	Stanley Cup	0

Show or Hide Columns

Filter Tips

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

#	Player Name	C	L	R	D	CON	CK	FG	DI	SK	ST	EN	DU	PH	FO	PA	SC	DF	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Matej Blumel	X				100.00	56	63	70	72	67	70	68	72	57	66	72	68	59	61	56	0	50	68	0	25	1	900,000$
2	Fedor Svechkov	X				100.00	72	42	89	77	71	59	69	65	62	67	69	67	56	56	58	0	50	68	0	22	2	975,000$
3	David Gustafsson	X				100.00	75	68	95	70	76	49	70	60	80	64	62	79	56	58	58	0	50	66	0	25	1	900,000$
4	Samuel Fagemo		X			100.00	57	66	69	69	69	70	68	66	57	61	68	65	59	61	56	0	50	65	0	25	1	930,000$
5	Ryan Winterton	X				100.00	61	56	76	67	69	67	66	64	58	63	63	69	57	56	55	0	50	65	0	21	2	875,000$
6	Filip Bystedt	X				100.00	57	60	70	62	70	67	65	63	57	62	61	66	56	54	52	0	50	63	0	21	2	975,000$
7	Jack Williams (R)			X		100.00	59	42	79	69	69	70	57	56	52	61	55	65	56	54	58	0	50	61	0	23	2	625,000$
8	Otto Stenberg (R)	X				100.00	56	59	72	59	67	64	63	60	57	60	58	65	56	52	51	0	50	60	0	20	3	975,000$
9	Julian Lutz (R)	X				100.00	56	56	71	58	71	66	64	59	57	59	57	64	56	54	52	0	50	60	0	21	3	925,000$
10	Gabriel Landeskog	X	X	X		100.00	57	56	72	56	73	56	56	56	57	56	56	61	56	75	64	0	50	58	0	32	1	900,000$
11	Helge Grans				X	100.00	58	60	70	64	80	72	69	61	43	63	60	68	57	58	55	0	50	64	0	23	1	925,000$
12	Yan Kuznetsov				X	100.00	57	57	69	62	80	72	69	61	42	61	58	70	56	57	54	0	50	64	0	23	1	750,000$
13	Ryan O'Rourke				X	100.00	57	56	68	59	67	69	67	59	42	59	57	65	56	61	56	0	50	61	0	23	1	925,000$
14	Calle Odelius (R)				X	100.00	56	56	70	59	69	69	67	59	42	60	56	62	56	54	52	0	50	60	0	21	3	925,000$
15	Ryan Chesley (R)				X	100.00	56	56	72	56	69	57	57	57	42	57	56	61	56	54	52	0	50	58	0	21	3	925,000$
Scratches

	TEAM AVERAGE					100.00	59	57	74	64	71	65	65	61	54	61	61	66	57	58	55	0	50	63

Show or Hide Columns

Filter Tips

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

#	Goalie Name	CON	SK	DU	EN	SZ	AG	RB	SC	HS	RT	PH	PS	EX	LD	PO	MO	OV	SP	Age	Contract	Salary
1	Drew Commesso	100.00	73	76	76	64	72	72	71	76	65	73	76	61	55	0	50	71	0	22	1	925,000$
2	Calle Clang	100.00	67	73	73	65	70	60	69	71	64	72	64	61	55	0	50	67	0	23	1	875,000$
Scratches

	TEAM AVERAGE	100.00	70	75	75	65	71	66	70	74	65	73	70	61	55	0	50	69

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

Show or Hide Columns

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	PPP	PPS	PPM	PKS	PKM	GW	FO%	FOT	P/20	PSG	PSS	FW	FL	S1	S2	S3
1	Yan Kuznetsov	Tucson Roadrunners (UTA)	D	31	6	21	27	-6	48	0	85	71	48	20	40	12.50%	53	609	19.67	2	2	12	12	1	14	0	25.00%	4	0.89	0	4	0	0	3	8	4
2	Ryan Winterton	Tucson Roadrunners (UTA)	C	31	15	11	26	-5	20	0	53	118	132	38	109	11.36%	5	537	17.33	0	0	0	0	0	3	1	55.02%	687	0.97	1	3	0	0	7	2	5
3	Helge Grans	Tucson Roadrunners (UTA)	D	31	8	15	23	-16	56	10	71	86	104	30	69	7.69%	25	680	21.95	0	0	0	0	0	0	0	29.41%	34	0.68	3	4	1	1	2	6	7
Team Total or Average				93	29	47	76	-27	124	10	209	275	284	88	218	10.21%	83	1827	19.65	2	2	12	12	1	17	1	53.66%	725	0.83	4	11	1	1	12	16	16

Show or Hide Columns

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 Columns

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	Country	Rookie	Weight	Height	No Trade	Available For Trade	Acquired By	Last Trade Date	Force Waivers	Waiver Possible	Contract	Contract Signature Date	Force UFA	Emergency Recall	Type	Current Salary	Salary Remaining	Salary Cap	Salary Cap Remaining	Exclude from Salary Cap	Salary Year 2	Salary Year 3	Salary Year 4	Salary Year 5	Salary Year 6	Salary Year 7	Salary Year 8	Salary Year 9	Salary Year 10	Salary Cap Year 2	Salary Cap Year 3	Salary Cap Year 4	Salary Cap Year 5	Salary Cap Year 6	Salary Cap Year 7	Salary Cap Year 8	Salary Cap Year 9	Salary Cap Year 10	No Trade Year 2	No Trade Year 3	No Trade Year 4	No Trade Year 5	No Trade Year 6	No Trade Year 7	No Trade Year 8	No Trade Year 9	No Trade Year 10	Link
Calle Clang	Tucson Roadrunners (UTA)	G	23	2002-05-20	SWE	No	194 Lbs	6 ft2	No	No	N/A		No	No	1		False	False	Pro & Farm	875,000$	558,511$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Calle Odelius	Tucson Roadrunners (UTA)	D	21	2004-05-30	SWE	Yes	192 Lbs	6 ft0	No	No	Trade	2025-10-10	No	No	3	2025-07-27	False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	925,000$	925,000$	-	-	-	-	-	-	-	925,000$	925,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
David Gustafsson	Tucson Roadrunners (UTA)	C	25	2000-04-11	SWE	No	195 Lbs	6 ft2	No	No	N/A		No	No	1	2025-08-27	False	False	Pro & Farm	900,000$	574,468$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Drew Commesso	Tucson Roadrunners (UTA)	G	22	2002-07-19	USA	No	180 Lbs	6 ft2	No	No	Assign Manually		No	No	1	2024-11-23	False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Fedor Svechkov	Tucson Roadrunners (UTA)	C	22	2003-04-05	RUS	No	187 Lbs	6 ft0	No	No	Assign Manually		No	No	2	2025-09-28	False	False	Pro & Farm	975,000$	622,340$	0$	0$	No	975,000$	-	-	-	-	-	-	-	-	925,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Filip Bystedt	Tucson Roadrunners (UTA)	C	21	2004-02-04	SWE	No	187 Lbs	6 ft2	No	No	Prospect		No	No	2	2024-07-20	False	False	Pro & Farm	975,000$	622,340$	0$	0$	No	975,000$	-	-	-	-	-	-	-	-	975,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Gabriel Landeskog	Tucson Roadrunners (UTA)	C/LW/RW	32	1992-11-23	SWE	No	216 Lbs	6 ft0	No	No	N/A		No	No	1	2025-04-02	False	False	Pro & Farm	900,000$	574,468$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Helge Grans	Tucson Roadrunners (UTA)	D	23	2002-05-10	SWE	No	204 Lbs	6 ft3	No	No	N/A		No	No	1		False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Jack Williams	Tucson Roadrunners (UTA)	RW	23	2002-03-02	USA	Yes	184 Lbs	5 ft10	No	No	Draft		No	No	2	2025-07-05	False	False	Pro & Farm	625,000$	398,936$	0$	0$	No	625,000$	-	-	-	-	-	-	-	-	625,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Julian Lutz	Tucson Roadrunners (UTA)	C	21	2004-02-29	GER	Yes	194 Lbs	6 ft2	No	No	Prospect		No	No	3	2025-07-05	False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	925,000$	925,000$	-	-	-	-	-	-	-	925,000$	925,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Matej Blumel	Tucson Roadrunners (UTA)	C	25	2000-05-31	CZE	No	195 Lbs	5 ft11	No	No	N/A		No	No	1	2025-08-27	False	False	Pro & Farm	900,000$	574,468$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Otto Stenberg	Tucson Roadrunners (UTA)	C	20	2005-05-29	SWE	Yes	187 Lbs	6 ft0	No	No	Prospect		No	No	3	2025-07-05	False	False	Pro & Farm	975,000$	622,340$	0$	0$	No	975,000$	975,000$	-	-	-	-	-	-	-	975,000$	975,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Ryan Chesley	Tucson Roadrunners (UTA)	D	21	2004-02-27	USA	Yes	194 Lbs	6 ft0	No	No	Prospect		No	No	3	2025-07-05	False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	925,000$	925,000$	-	-	-	-	-	-	-	925,000$	925,000$	-	-	-	-	-	-	-	No	No	-	-	-	-	-	-	-	Link
Ryan O'Rourke	Tucson Roadrunners (UTA)	D	23	2002-05-16	CAN	No	192 Lbs	6 ft1	No	No	Prospect		No	No	1	2024-07-20	False	False	Pro & Farm	925,000$	590,426$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Ryan Winterton	Tucson Roadrunners (UTA)	C	21	2003-09-04	CAN	No	173 Lbs	6 ft2	No	No	Prospect		No	No	2	2024-07-20	False	False	Pro & Farm	875,000$	558,511$	0$	0$	No	875,000$	-	-	-	-	-	-	-	-	875,000$	-	-	-	-	-	-	-	-	No	-	-	-	-	-	-	-	-	Link
Samuel Fagemo	Tucson Roadrunners (UTA)	LW	25	2000-03-14	SWE	No	201 Lbs	5 ft11	No	No	N/A		No	No	1	2024-08-11	False	False	Pro & Farm	930,000$	593,617$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link
Yan Kuznetsov	Tucson Roadrunners (UTA)	D	23	2002-03-09	RUS	No	220 Lbs	6 ft5	No	No	N/A		No	No	1	2024-08-11	False	False	Pro & Farm	750,000$	478,723$	0$	0$	No	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	-	Link

Total Players	Average Age	Average Weight	Average Height	Average Contract	Average Year 1 Salary
17	23.00	194 Lbs	6 ft1	1.71	895,882$

5 vs 5 Forward
Line #	Left Wing	Center	Right Wing	Time %	PHY	DF	OF
1				35	1	2	2
2				30	1	2	2
3				25	1	2	2
4				10	1	2	2

5 vs 5 Defense
Line #	Defense	Defense	Time %	PHY	DF	OF
1			35	1	2	2
2		Yan Kuznetsov	30	1	2	2
3	Helge Grans		25	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		Yan Kuznetsov	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		Yan Kuznetsov	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		Yan Kuznetsov	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		Yan Kuznetsov	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
Ryan Winterton, ,	Ryan Winterton,

Extra Defensemen
Normal	PowerPlay	Penalty Kill
Helge Grans, ,	Helge Grans	,

Penalty Shots
, , , ,

Goalie
#1 : , #2 :

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

Custom OT Lines Defensemen
, , , ,

Show or Hide Columns

Filter Tips

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

	Overall												Home											Visitor
#	VS Team	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	GP	W	L	T	OTW	OTL	SOW	SOL	GF	GA	Diff	P	PCT	G	A	TP	SO	EG	GP1	GP2	GP3	GP4	SHF	SH1	SP2	SP3	SP4	SHA	SHB	Pim	Hit	PPA	PPG	PP%	PKA	PK GA	PK%	PK GF	W OF FO	T OF FO	OF FO%	W DF FO	T DF FO	DF FO%	W NT FO	T NT FO	NT FO%	PZ DF	PZ OF	PZ NT	PC DF	PC OF	PC NT
1	Bobcaygeon Bullets	2	1	1	0	0	0	0	0	7	9	-2	1	1	0	0	0	0	0	0	3	1	2	1	0	1	0	0	0	0	0	4	8	-4	2	0.500	7	14	21	0	0	40	41	31	5	70	369	392	434	27	84	30	18	41	6	1	16.67%	6	2	66.67%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
2	Cairo Fighting Ice Camels	1	0	1	0	0	0	0	0	1	2	-1	1	0	1	0	0	0	0	0	1	2	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	1	2	3	0	0	40	41	31	5	31	369	392	434	27	25	12	14	18	4	0	0.00%	7	0	100.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
3	Charlotte Checkers	3	0	2	0	0	0	0	1	9	13	-4	1	0	0	0	0	0	0	1	2	3	-1	2	0	2	0	0	0	0	0	7	10	-3	1	0.167	9	18	27	0	0	40	41	31	5	124	369	392	434	27	115	28	24	92	16	1	6.25%	12	2	83.33%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
4	Grand Rapids Griffins	1	0	1	0	0	0	0	0	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	4	5	-1	0	0.000	4	8	12	0	0	40	41	31	5	52	369	392	434	27	44	9	6	26	7	1	14.29%	2	0	100.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
5	Hamilton Bulldogs	1	0	1	0	0	0	0	0	3	5	-2	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	4	7	1	0	40	41	31	5	37	369	392	434	27	46	13	23	34	1	0	0.00%	4	1	75.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
6	Kimberley Dynamiters	2	2	0	0	0	0	0	0	8	5	3	1	1	0	0	0	0	0	0	6	4	2	1	1	0	0	0	0	0	0	2	1	1	4	1.000	8	14	22	0	0	40	41	31	5	87	369	392	434	27	84	28	24	39	11	4	36.36%	12	2	83.33%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
7	Lehigh Valley Phantoms	1	1	0	0	0	0	0	0	2	1	1	1	1	0	0	0	0	0	0	2	1	1	0	0	0	0	0	0	0	0	0	0	0	2	1.000	2	4	6	0	0	40	41	31	5	42	369	392	434	27	28	5	4	18	8	0	0.00%	2	1	50.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
8	Manitoba Moose	1	0	0	0	0	0	1	0	7	6	1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	1	0	7	6	1	2	1.000	7	12	19	0	0	40	41	31	5	51	369	392	434	27	67	20	4	33	4	2	50.00%	2	0	100.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
9	Newfoundland Regiment	1	0	1	0	0	0	0	0	3	5	-2	0	0	0	0	0	0	0	0	0	0	0	1	0	1	0	0	0	0	0	3	5	-2	0	0.000	3	6	9	0	0	40	41	31	5	32	369	392	434	27	37	16	10	23	5	2	40.00%	5	1	80.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
10	Ontario Reign	1	0	1	0	0	0	0	0	4	5	-1	1	0	1	0	0	0	0	0	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	0	0.000	4	6	10	0	0	40	41	31	5	38	369	392	434	27	35	6	14	21	1	0	0.00%	6	3	50.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
11	Palm Springs Navigators	2	1	0	0	0	0	1	0	9	6	3	1	1	0	0	0	0	0	0	4	2	2	1	0	0	0	0	0	1	0	5	4	1	4	1.000	9	16	25	0	0	40	41	31	5	76	369	392	434	27	97	17	26	64	7	3	42.86%	12	1	91.67%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
12	Prince George Cougars	2	0	2	0	0	0	0	0	7	12	-5	0	0	0	0	0	0	0	0	0	0	0	2	0	2	0	0	0	0	0	7	12	-5	0	0.000	7	12	19	0	0	40	41	31	5	64	369	392	434	27	103	18	20	56	8	3	37.50%	10	2	80.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
13	Rhode Island Red Army	1	1	0	0	0	0	0	0	4	3	1	0	0	0	0	0	0	0	0	0	0	0	1	1	0	0	0	0	0	0	4	3	1	2	1.000	4	7	11	0	0	40	41	31	5	49	369	392	434	27	47	13	6	25	6	1	16.67%	3	0	100.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
14	San Diego Gulls	2	1	1	0	0	0	0	0	5	7	-2	0	0	0	0	0	0	0	0	0	0	0	2	1	1	0	0	0	0	0	5	7	-2	2	0.500	5	9	14	0	0	40	41	31	5	61	369	392	434	27	72	16	22	41	2	0	0.00%	11	3	72.73%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
15	Saskatchewan Snatchsniffers	1	0	1	0	0	0	0	0	3	7	-4	1	0	1	0	0	0	0	0	3	7	-4	0	0	0	0	0	0	0	0	0	0	0	0	0.000	3	6	9	0	0	40	41	31	5	40	369	392	434	27	43	19	4	19	2	1	50.00%	0	0	0%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
16	Stouffville Clippers	1	0	0	0	0	0	0	1	4	5	-1	0	0	0	0	0	0	0	0	0	0	0	1	0	0	0	0	0	0	1	4	5	-1	1	0.500	4	8	12	0	0	40	41	31	5	41	369	392	434	27	52	21	12	34	5	1	20.00%	6	1	83.33%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
17	Syracuse Crunch	4	2	1	0	1	0	0	0	17	15	2	4	2	1	0	1	0	0	0	17	15	2	0	0	0	0	0	0	0	0	0	0	0	6	0.750	17	32	49	1	0	40	41	31	5	175	369	392	434	27	194	57	54	106	15	4	26.67%	25	5	80.00%	1	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
18	Vancouver Millionaires	2	0	2	0	0	0	0	0	6	9	-3	1	0	1	0	0	0	0	0	2	4	-2	1	0	1	0	0	0	0	0	4	5	-1	0	0.000	6	12	18	0	0	40	41	31	5	68	369	392	434	27	71	11	16	45	8	1	12.50%	8	2	75.00%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
19	Victoria Grizzlies	2	1	1	0	0	0	0	0	12	10	2	1	0	1	0	0	0	0	0	5	6	-1	1	1	0	0	0	0	0	0	7	4	3	2	0.500	12	21	33	0	0	40	41	31	5	72	369	392	434	27	84	29	25	45	10	4	40.00%	10	2	80.00%	1	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
	Total	31	10	16	0	1	0	2	2	115	130	-15	15	6	7	0	1	0	0	1	52	55	-3	16	4	9	0	0	0	2	1	63	75	-12	28	0.452	115	211	326	2	0	40	41	31	5	1210	369	392	434	27	1328	368	326	780	126	29	23.02%	143	28	80.42%	2	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
	_Since Last GM Reset	31	10	16	0	1	0	2	2	115	130	-15	15	6	7	0	1	0	0	1	52	55	-3	16	4	9	0	0	0	2	1	63	75	-12	28	0.452	115	211	326	2	0	40	41	31	5	1210	369	392	434	27	1328	368	326	780	126	29	23.02%	143	28	80.42%	2	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
	_Vs Conference	15	5	8	0	0	0	2	0	61	67	-6	6	2	4	0	0	0	0	0	24	28	-4	9	3	4	0	0	0	2	0	37	39	-2	14	0.467	61	108	169	0	0	40	41	31	5	557	369	392	434	27	656	164	155	363	53	18	33.96%	71	15	78.87%	1	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
	_Vs Division	9	5	7	0	0	0	1	0	31	37	-6	4	2	3	0	0	0	0	0	13	18	-5	5	3	4	0	0	0	1	0	18	19	-1	12	0.667	31	56	87	0	0	40	41	31	5	332	369	392	434	27	365	82	88	215	26	6	23.08%	40	9	77.50%	0	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177

			Total For Players
Games Played	Points	Streak	Goals	Assists	Points	Shots For	Shots Against	Shots Blocked	Penalty Minutes	Hits	Empty Net Goals	Shutouts
31	28	L1	115	211	326	1210	1328	368	326	780	2	0

All Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
31	10	16	1	0	2	2	115	130

Home Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
15	6	7	1	0	0	1	52	55

Visitor Games
GP	W	L	OTW	OTL	SOW	SOL	GF	GA
16	4	9	0	0	2	1	63	75

Last 10 Games
W	L	OTW	OTL	SOW	SOL
3	6	0	0	0	1

Power Play Attemps	Power Play Goals	Power Play %	Penalty Kill Attemps	Penalty Kill Goals Against	Penalty Kill %	Penalty Kill Goals For
126	29	23.02%	143	28	80.42%	2

Shots 1 Period	Shots 2 Period	Shots 3 Period	Shots 4+ Period	Goals 1 Period	Goals 2 Period	Goals 3 Period	Goals 4+ Period
369	392	434	27	40	41	31	5

Face Offs
Won Offensive Zone	Total Offensive	Won Offensive %	Won Defensif Zone	Total Defensive	Won Defensive %	Won Neutral Zone	Total Neutral	Won Neutral %
563	1157	48.66%	610	1247	48.92%	261	525	49.71%

Puck Time
In Offensive Zone	Control In Offensive Zone	In Defensive Zone	Control In Defensive Zone	In Neutral Zone	Control In Neutral Zone
726	514	790	219	367	177

Last Played Games Show or Hide Columns

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
3	16	Syracuse Crunch	3	Tucson Roadrunners	4	W	X		Box score
5	34	Syracuse Crunch	3	Tucson Roadrunners	5	W			Box score
7	45	Tucson Roadrunners	5	Charlotte Checkers	7	L			Box score
10	67	Tucson Roadrunners	2	Kimberley Dynamiters	1	W			Box score
11	81	Palm Springs Navigators	2	Tucson Roadrunners	4	W			Box score
14	102	Syracuse Crunch	3	Tucson Roadrunners	4	W			Box score
16	111	Tucson Roadrunners	3	San Diego Gulls	1	W			Box score
18	130	Tucson Roadrunners	2	Charlotte Checkers	3	L			Box score
20	144	Ontario Reign	5	Tucson Roadrunners	4	L			Box score
22	161	Tucson Roadrunners	5	Prince George Cougars	7	L			Box score
23	169	Tucson Roadrunners	4	Vancouver Millionaires	5	L			Box score
25	185	Vancouver Millionaires	4	Tucson Roadrunners	2	L			Box score
27	201	Tucson Roadrunners	5	Palm Springs Navigators	4	W	X	X	Box score
30	217	Kimberley Dynamiters	4	Tucson Roadrunners	6	W			Box score
33	239	Victoria Grizzlies	6	Tucson Roadrunners	5	L			Box score
35	253	Tucson Roadrunners	7	Victoria Grizzlies	4	W			Box score
37	265	Hamilton Bulldogs	5	Tucson Roadrunners	3	L			Box score
40	288	Tucson Roadrunners	4	Stouffville Clippers	5	L	X	X	Box score
41	300	Bobcaygeon Bullets	1	Tucson Roadrunners	3	W			Box score
44	318	Tucson Roadrunners	4	Grand Rapids Griffins	5	L			Box score
46	332	Tucson Roadrunners	4	Bobcaygeon Bullets	8	L			Box score
48	345	Charlotte Checkers	3	Tucson Roadrunners	2	L	X	X	Box score
50	364	Saskatchewan Snatchsniffers	7	Tucson Roadrunners	3	L			Box score
53	386	Tucson Roadrunners	2	San Diego Gulls	6	L			Box score
55	396	Cairo Fighting Ice Camels	2	Tucson Roadrunners	1	L			Box score
57	410	Tucson Roadrunners	3	Newfoundland Regiment	5	L			Box score
59	429	Lehigh Valley Phantoms	1	Tucson Roadrunners	2	W			Box score
61	440	Tucson Roadrunners	7	Manitoba Moose	6	W	X	X	Box score
63	454	Tucson Roadrunners	2	Prince George Cougars	5	L			Box score
65	468	Tucson Roadrunners	4	Rhode Island Red Army	3	W			Box score
66	475	Syracuse Crunch	6	Tucson Roadrunners	4	L			Box score
69	495	Tucson Roadrunners	-	Kimberley Dynamiters	-
70	505	Grand Rapids Griffins	-	Tucson Roadrunners	-
74	529	Tucson Roadrunners	-	Syracuse Crunch	-
75	538	Palm Springs Navigators	-	Tucson Roadrunners	-
78	561	Tucson Roadrunners	-	Lehigh Valley Phantoms	-
79	568	Charlestown Chiefs	-	Tucson Roadrunners	-
82	596	Vancouver Millionaires	-	Tucson Roadrunners	-
84	606	Tucson Roadrunners	-	Hamilton Bulldogs	-
86	622	Tucson Roadrunners	-	Vancouver Millionaires	-
88	632	Prince George Cougars	-	Tucson Roadrunners	-
90	648	Tucson Roadrunners	-	Kitchener Rangers	-
92	663	Colorado Eagles	-	Tucson Roadrunners	-
94	678	Tucson Roadrunners	-	Henderson Silver Knights	-
96	694	Owen Sound Platers	-	Tucson Roadrunners	-
98	711	Tucson Roadrunners	-	Flint Michigan Tropics	-
100	722	Tucson Roadrunners	-	Cairo Fighting Ice Camels	-
102	734	Kitchener Rangers	-	Tucson Roadrunners	-
105	758	Ontario Reign	-	Tucson Roadrunners	-
107	777	Tucson Roadrunners	-	Syracuse Crunch	-
109	791	Iowa Wild	-	Tucson Roadrunners	-
112	807	Tucson Roadrunners	-	Owen Sound Platers	-
114	822	Kimberley Dynamiters	-	Tucson Roadrunners	-
116	841	Tucson Roadrunners	-	Texas Stars	-
118	856	Stouffville Clippers	-	Tucson Roadrunners	-
120	865	Tucson Roadrunners	-	Palm Springs Navigators	-
122	884	Prince George Cougars	-	Tucson Roadrunners	-
124	893	Tucson Roadrunners	-	Bridgeport Islanders	-
127	915	Tucson Roadrunners	-	Iowa Wild	-
128	925	Bridgeport Islanders	-	Tucson Roadrunners	-
131	950	Rhode Island Red Army	-	Tucson Roadrunners	-
133	962	Tucson Roadrunners	-	Colorado Eagles	-
135	978	Tucson Roadrunners	-	Cincinnati Cyclones	-
137	987	Manitoba Moose	-	Tucson Roadrunners	-
140	1009	Tucson Roadrunners	-	Victoria Grizzlies	-
142	1019	Hartford Wolf Pack	-	Tucson Roadrunners	-
145	1041	Tucson Roadrunners	-	Charlotte Checkers	-
147	1051	San Diego Gulls	-	Tucson Roadrunners	-
150	1076	Tucson Roadrunners	-	Ontario Reign	-
151	1082	Victoria Grizzlies	-	Tucson Roadrunners	-
154	1105	Tucson Roadrunners	-	Wilkes Scranton Penguins	-
156	1115	Texas Stars	-	Tucson Roadrunners	-
157	1123	Tucson Roadrunners	-	Hartford Wolf Pack	-
160	1147	Wilkes Scranton Penguins	-	Tucson Roadrunners	-
163	1167	Tucson Roadrunners	-	Ontario Reign	-
165	1178	Newfoundland Regiment	-	Tucson Roadrunners	-
Trade Deadline --- Trades can’t be done after this day is simulated!
169	1209	San Diego Gulls	-	Tucson Roadrunners	-
174	1237	Flint Michigan Tropics	-	Tucson Roadrunners	-
177	1262	Henderson Silver Knights	-	Tucson Roadrunners	-
179	1270	Tucson Roadrunners	-	Charlestown Chiefs	-
182	1290	Cincinnati Cyclones	-	Tucson Roadrunners	-
184	1301	Tucson Roadrunners	-	Saskatchewan Snatchsniffers	-

Arena Capacity - Ticket Price Attendance - %
	Level 1	Level 2
Capacity	2000	1000
Ticket Price	35	15
Attendance	0	0
Attendance PCT	0.00%	0.00%

Income
Home Games Left	Average Attendance - %	Average Income per Game	Year to Date Revenue	Capacity	Team Popularity
26	0 - 0.00%	0$	0$	3000	100

Expenses
Year To Date Expenses	Players Total Salaries	Players Total Salaries Cap	Coaches Salaries
574,159$	1,523,000$	1,523,000$	0$

Salary Cap Per Days	Salary Cap To Date	Players In Salary Cap	Players Out of Salary Cap
0$	574,159$	0	0

Estimate
Estimated Season Revenue	Remaining Season Days	Expenses Per Days	Estimated Season Expenses
0$	120	8,101$	972,120$

Tucson Roadrunners Players Stat Leaders (Regular Season)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS
1	Yan Kuznetsov	186	34	95	129	-36	216	386	272	399	8.52%	283	4029	21.66	23	26	49	218	0	1	1	4	1	0	22.22%	1	0.64	2	8
2	Luke Toporowski	154	50	72	122	-3	100	210	315	609	8.21%	28	2558	16.61	8	18	26	96	1	0	1	1	6	4	52.73%	1	0.95	0	5
3	Helge Grans	171	24	86	110	-13	210	340	239	275	8.73%	194	3071	17.96	6	6	12	47	0	0	0	1	2	2	29.41%	0	0.72	3	4
4	Kyle Capobianco	122	36	71	107	-50	183	283	245	362	9.94%	229	2850	23.37	27	25	52	227	0	0	0	2	1	1	0%	0	0.75	0	0
5	Alex Beaucage	116	35	56	91	2	74	190	221	295	11.86%	19	1886	16.26	12	27	39	90	0	0	0	2	5	1	50.79%	0	0.96	1	2

Tucson Roadrunners Goalies Stat Leaders (Regular Season)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA
1	Calle Clang	35	14	17	4	0.895	3.95	2111	2	0	139	1324	0	1	2	0.600	10
2	Lukas Parik	40	11	24	5	0.880	4.26	2393	2	0	170	1414	0	2	0	0.625	16

Tucson Roadrunners Career Team Stats

Show or Hide Columns

	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
2023	82	23	46	0	1	1	2	9	281	355	-74	41	11	24	0	0	0	2	4	147	182	-35	41	12	22	0	1	1	0	5	134	173	-39	62	281	518	799	3	0	107	110	61	7	2858	897	966	963	73	2959	804	896	1919	376	80	21.28%	386	99	74.35%	0	1533	2944	52.07%	1366	2870	47.60%	740	1448	51.10%	1989	1387	1959	594	1027	515
2024	82	29	35	0	1	6	6	5	295	300	-5	41	19	16	0	0	2	3	1	148	133	15	41	10	19	0	1	4	3	4	147	167	-20	83	295	528	823	3	4	120	97	71	13	3036	1001	989	1020	70	2894	839	913	1884	342	76	22.22%	386	90	76.68%	3	1679	3081	54.50%	1532	2919	52.48%	748	1393	53.70%	2094	1489	1886	569	1006	511
2025	31	10	16	0	1	0	2	2	115	130	-15	15	6	7	0	1	0	0	1	52	55	-3	16	4	9	0	0	0	2	1	63	75	-12	28	115	211	326	2	0	40	41	31	5	1210	369	392	434	27	1328	368	326	780	126	29	23.02%	143	28	80.42%	2	563	1157	48.66%	610	1247	48.92%	261	525	49.71%	726	514	790	219	367	177
Total Regular Season	195	62	97	0	3	7	10	16	691	785	-94	97	36	47	0	1	2	5	6	347	370	-23	98	26	50	0	2	5	5	10	344	415	-71	173	691	1257	1948	8	4	267	248	163	25	7104	2267	2347	2417	170	7181	2011	2135	4583	844	185	21.92%	915	217	76.28%	5	3775	7182	52.56%	3508	7036	49.86%	1749	3366	51.96%	4810	3391	4637	1383	2400	1204
Playoff
Total Playoff	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0	0%	0	0	0%	0	0	0	0%	0	0	0%	0	0	0%	0	0	0	0	0	0

Tucson Roadrunners Players Stat Leaders (Play-Off)

Show or Hide Columns

#	Player Name	GP	G	A	P	+/-	PIM	HIT	HTT	SHT	SHT%	SB	MP	AMG	PPG	PPA	PPP	PPS	PKG	PKA	PKP	PKS	GW	GT	FO%	HT	P/20	PSG	PSS

Tucson Roadrunners Goalies Stat Leaders (Play-Off)

Show or Hide Columns

#	Goalie Name	GP	W	L	OTL	PCT	GAA	MP	PIM	SO	GA	SA	SAR	A	EG	PS %	PSA

	Tucson Roadrunners
	GP: 31 \| W: 13 \| L: 16 \| OTL: 2 \| P: 28 GF: 115 \| GA: 130 \| PP%: 23.02% \| PK%: 80.42% GM : Adam D-S \| Morale : 50 \| Team Overall : 63 Next Games #495 vs Kimberley Dynamiters