WEB CLIENT LEAGUE FILES


Denver Spurs


GP: 53 | W: 24 | L: 20 | OTL: 9 | P: 57
GF: 149 | GA: 154 | PP%: 15.44% | PK%: 87.93%
GM : Patrick King | Team Overall : 67
Next Games at Milwaukee Admirals
Your browser screen resolution is too small for this page. Some information are hidden to keep the page readable.

Filter Tips
PriorityTypeDescription
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
10textAny 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
1Adam Erne (R)XX100.00825881777982857366706972726163050690
2Michael Haley (C)XX100.00779376717782817170706573627877050690
3Matt Puempel (R) (A)XX100.00694690747280827563657071647372050680
4Sergey Tolchinsky (R)XX100.00583094785879807558686770685855050660
5Taylor Leier (R)XX100.00683295767277786868646471656872050660
6Matthew Highmore (R)XX100.00723087807276757158656768695254050650
7Jean-Sebastien Dea (R)XX100.00673292766279786974676269746460050650
8Michael Dal Colle (R)XX100.00683385707378777164666670675050050650
9Jesse Gabrielle (R)X100.00815378757677746562616468615653050640
10Colin Smith (R)XX100.00713488776876766574635869616058050640
11Giovanni Fiore (R)XX100.00683685777674716760616568685050050640
12Gage Quinney (R)XX100.00723287737872686662636269645250050630
13Justin FalkX100.00794371718185836530644574337878050690
14Jordan Subban (R)X100.00693886796784827230696669626163050680
15Darren Dietz (R)X100.00764379747882806630635772516265050680
16Jan Kostalek (R)X100.00743087747581836330615673475860050670
17Victor Mete (R)X100.00613092796883806730645674566057050670
18Brennan Menell (R)X100.00673488737275706530635968495250050640
Scratches
1Greg Chase (R)X100.00763277747374646173595668534750050610
2Mitch Moroz (R)X100.00757367697674625755535467555050050590
3Clayton StonerX100.00755980698170656330613672408977050660
4Joey LaLeggia (R)X100.00663086786082806930666368576062050660
TEAM AVERAGE100.0071428475727876675264607059616005066
Filter Tips
PriorityTypeDescription
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
10textAny 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
1Joonas Korpisalo (R)100.0084848584858484838582896563050800
2Linus Ullmark (R)100.0082798185838382828381835652050780
Scratches
1Eric Comrie (R)100.0084807982868182798182835151050770
TEAM AVERAGE100.008381828485838381838285575505078
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
John Anderson70787771878080CAN613525,000$


Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
# Player Name Team NamePOS 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
1Dylan StromeColorado AvalancheC511525401116086149165451149.09%11101719.95279361350001913248.27%139000000.7916000223
2Jordan SubbanDenver Spurs (COL)D5343135108047767517435.33%76119222.50371033128011081000.00%000000.5900000302
3Brian GibbonsColorado AvalancheC/LW/RW46161935-28044111161561169.94%1290919.777411331220001904048.44%51200000.7700000222
4Adam ErneDenver Spurs (COL)LW/RW4312162821151297315145927.95%1082019.0825736991013782152.17%4600000.6812010411
5Michael HaleyDenver Spurs (COL)C/LW53121527-524012213112137849.92%1591017.18033271230003882052.05%119700000.5900000124
6Matt PuempelDenver Spurs (COL)LW/RW531115261605376134391028.21%690217.0333615930001222347.87%9400000.5800000121
7Matthew HighmoreDenver Spurs (COL)LW/RW53121325-680595212434869.68%485816.1931429121000001029.09%5500000.5823000022
8Sergey TolchinskyDenver Spurs (COL)LW/RW53111324300128013244968.33%1187216.461231687000043139.29%5600000.5504000111
9Victor MeteDenver Spurs (COL)D5232124-1710058694713346.38%62113521.8315622124000095000.00%000000.4200000030
10Jean-Sebastien DeaDenver Spurs (COL)C/RW5381018-7140328474215310.81%462311.7700018000000151.15%39300100.5816000000
11Colin SmithDenver Spurs (COL)C/RW5361117-2160398057243210.53%555310.45000000111100050.84%59600000.6100000200
12Justin FalkDenver Spurs (COL)D5361117104801564529151920.69%60107420.2700003000180200.00%000000.3200000121
13Gage QuinneyDenver Spurs (COL)C/LW5271017-180454369164610.14%353610.3200000000001037.50%6400000.6300000010
14Darren DietzDenver Spurs (COL)D48214160380116463410255.88%6188918.521121155000081000.00%000000.3600000021
15Joey LaLeggiaDenver Spurs (COL)D3431215-310068304118327.32%2170720.800332482000029000.00%000000.4200000003
16Brennan MenellDenver Spurs (COL)D5321214-56047375015294.00%3297018.3200026132000016000.00%000000.2900000100
17Michael Dal ColleDenver Spurs (COL)LW/RW536814-64043387923627.59%358511.0400000000000153.49%4300000.4800000000
18Giovanni FioreDenver Spurs (COL)LW/RW525510-166034437725526.49%358111.1800000000001047.22%3600000.3402000002
19Taylor LeierDenver Spurs (COL)LW/RW17527-2209192541820.00%120612.16000000002302038.10%2100000.6800000100
20Jan KostalekDenver Spurs (COL)D26044-15405628134200.00%2147718.3500002000032000.00%000000.1700000002
21Jesse GabrielleDenver Spurs (COL)LW22021005340150.00%02110.770000000000000.00%100001.8600000100
22Clayton StonerDenver Spurs (COL)D1000000000000.00%000.080000000000000.00%000000.0000000000
Team Total or Average954148267415-49247512601313166250511568.90%4211584616.6123416430913231231383323949.40%450400100.52523010202025
Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
# Goalie Name Team NameGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
1Linus UllmarkDenver Spurs (COL)2110920.9072.86126000606450011.00032117010
2Joonas KorpisaloDenver Spurs (COL)229740.9122.59124921546150200.42972016410
3Antoine BibeauColorado Avalanche53200.9122.0129921101130000.000053110
4Eric ComrieDenver Spurs (COL)72230.8743.3740920231830010.50014717000
Team Total or Average55242090.9062.7432186214715560220.542245353530


Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
Player Name Team NamePOS Age Birthday Rookie Weight Height No Trade Available For Trade Force Waivers Contract StatusType Current Salary 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 Link
Adam ErneDenver Spurs (COL)LW/RW234/20/1995 5:02:13 AMYes214 Lbs6 ft1NoNoNo2RFAPro & Farm800,000$800,000$Link / NHL Link
Brennan MenellDenver Spurs (COL)D215/24/1997 6:32:58 AMYes183 Lbs5 ft11NoNoNo5RFAPro & Farm1,500,000$1,300,000$1,250,000$1,250,000$1,500,000$Link / NHL Link
Clayton StonerDenver Spurs (COL)D337/12/1985 2:10:27 AMNo216 Lbs6 ft4NoNoNo1UFAPro & Farm625,000$Link / NHL Link
Colin SmithDenver Spurs (COL)C/RW256/20/1993 7:20:18 AMYes185 Lbs5 ft10NoNoNo1RFAPro & Farm600,000$Link / NHL Link
Darren DietzDenver Spurs (COL)D257/17/1993 7:36:04 AMYes201 Lbs6 ft1NoNoNo1RFAPro & Farm600,000$Link / NHL Link
Eric ComrieDenver Spurs (COL)C/LW237/6/1995 5:05:50 AMYes175 Lbs6 ft1NoNoNo2RFAPro & Farm750,000$750,000$Link / NHL Link
Gage QuinneyDenver Spurs (COL)C/LW237/29/1995 6:17:12 AMYes201 Lbs6 ft0NoNoNo2RFAPro & Farm770,000$770,000$Link / NHL Link
Giovanni FioreDenver Spurs (COL)LW/RW228/13/1996 6:19:21 AMYes194 Lbs6 ft1NoNoNo3RFAPro & Farm1,250,000$1,100,000$1,000,000$Link / NHL Link
Greg ChaseDenver Spurs (COL)C231/1/1995 10:40:06 AMYes190 Lbs6 ft0NoNoNo1RFAPro & Farm375,000$Link / NHL Link
Jan KostalekDenver Spurs (COL)D232/17/1995 5:03:21 AMYes181 Lbs6 ft1NoNoNo2RFAPro & Farm625,000$625,000$Link / NHL Link
Jean-Sebastien DeaDenver Spurs (COL)C/RW242/8/1994 9:33:07 AMYes175 Lbs5 ft11NoNoNo2RFAPro & Farm1,150,000$1,250,000$Link / NHL Link
Jesse GabrielleDenver Spurs (COL)LW216/17/1997 10:36:25 AMYes204 Lbs5 ft11NoNoNo1RFAPro & Farm550,000$Link / NHL Link
Joey LaLeggiaDenver Spurs (COL)D266/24/1992 10:41:32 AMYes185 Lbs5 ft10NoNoNo1RFAPro & Farm600,000$Link / NHL Link
Joonas KorpisaloDenver Spurs (COL)D244/28/1994 10:42:36 AMYes182 Lbs6 ft3NoNoNo1RFAPro & Farm750,000$Link / NHL Link
Jordan SubbanDenver Spurs (COL)D233/3/1995 10:16:47 AMYes175 Lbs5 ft9NoNoNo1RFAPro & Farm625,000$Link / NHL Link
Justin FalkDenver Spurs (COL)D307/11/1988 8:10:27 PMNo223 Lbs6 ft5NoNoNo1UFAPro & Farm900,000$Link / NHL Link
Linus UllmarkDenver Spurs (COL)C/RW257/31/1993 10:43:43 AMYes221 Lbs6 ft4NoNoNo1RFAPro & Farm500,000$Link / NHL Link
Matt PuempelDenver Spurs (COL)LW/RW251/24/1993 4:39:41 AMYes205 Lbs6 ft1NoNoNo3RFAPro & Farm950,000$950,000$950,000$Link / NHL Link
Matthew HighmoreDenver Spurs (COL)LW/RW222/27/1996 6:24:55 AMYes181 Lbs5 ft11NoNoNo5RFAPro & Farm1,500,000$1,500,000$1,350,000$1,350,000$1,350,000$Link / NHL Link
Michael Dal ColleDenver Spurs (COL)LW/RW226/20/1996 3:42:40 AMYes204 Lbs6 ft3NoNoNo2RFAPro & Farm950,000$950,000$Link / NHL Link
Michael HaleyDenver Spurs (COL)C/LW327/12/1986 8:10:27 AMNo205 Lbs5 ft11NoNoNo1UFAPro & Farm1,100,000$Link / NHL Link
Mitch MorozDenver Spurs (COL)LW245/3/1994 7:40:44 AMYes214 Lbs6 ft2NoNoNo1RFAPro & Farm700,000$Link / NHL Link
Sergey TolchinskyDenver Spurs (COL)LW/RW232/3/1995 7:39:14 AMYes170 Lbs5 ft8NoNoNo2RFAPro & Farm1,150,000$1,250,000$Link / NHL Link
Taylor LeierDenver Spurs (COL)LW/RW242/15/1994 7:23:05 AMYes180 Lbs5 ft11NoNoNo2RFAPro & Farm650,000$650,000$Link / NHL Link
Victor MeteDenver Spurs (COL)D206/7/1998 2:48:41 AMYes184 Lbs5 ft10NoNoNo3RFAPro & Farm700,000$700,000$700,000$Link / NHL Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
2524.24194 Lbs6 ft01.88826,800$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Adam ErneMichael HaleySergey Tolchinsky30023
2Matthew HighmoreJean-Sebastien DeaMatt Puempel27032
3Giovanni FioreGage QuinneyMichael Dal Colle22032
4Jesse GabrielleColin SmithTaylor Leier21032
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Justin FalkJordan Subban35023
2Victor MeteJan Kostalek30032
3Darren DietzBrennan Menell30032
4Victor MeteJan Kostalek5023
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Matt PuempelMichael HaleyAdam Erne60005
2Matthew HighmoreJean-Sebastien DeaSergey Tolchinsky40005
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Victor MeteJordan Subban50014
2Darren DietzBrennan Menell50014
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Michael HaleyTaylor Leier50050
2Colin SmithAdam Erne50050
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Justin FalkVictor Mete50140
2Jan KostalekDarren Dietz50050
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Michael Haley50050Justin FalkVictor Mete50140
2Adam Erne50050Jan KostalekDarren Dietz50140
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Michael HaleySergey Tolchinsky50023
2Jean-Sebastien DeaMatt Puempel50023
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Justin FalkJordan Subban50032
2Victor MeteJan Kostalek50032
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Matt PuempelMichael HaleyAdam ErneVictor MeteJordan Subban
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Adam ErneMichael HaleyTaylor LeierJustin FalkVictor Mete
Extra Forwards
Normal PowerPlayPenalty Kill
Matt Puempel, Michael Haley, Adam ErneGiovanni Fiore, Michael Dal ColleMatt Puempel
Extra Defensemen
Normal PowerPlayPenalty Kill
Justin Falk, Victor Mete, Darren DietzDarren DietzJordan Subban, Brennan Menell
Penalty Shots
Jean-Sebastien Dea, Michael Haley, Sergey Tolchinsky, Matthew Highmore, Giovanni Fiore
Goalie
#1 : Linus Ullmark, #2 : Joonas Korpisalo


Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
OverallHomeVisitor
# 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
1Adirondack Angels2020000026-41010000002-21010000024-200.000235005257377595525655284051181048300.00%50100.00%1929188949.18%888179249.55%40882349.57%12918951236386697353
2Binghamton Senators10000010651000000000001000001065121.0006915005257377325525655284045124193133.33%110.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
3Bridgeport Sound Tigers1000000123-1000000000001000000123-110.50023500525737729552565528403513433300.00%2150.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
4Carolina Panthers22000000642110000002111100000043141.00061117005257377515525655284060188476116.67%40100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
5Cleveland Monsters2020000027-51010000014-31010000013-200.0002460052573775455256552840681418424125.00%9277.78%0929188949.18%888179249.55%40882349.57%12918951236386697353
6Durham Pioneers320000011284210000017431100000054150.83312213300525737710955256552840962116689111.11%80100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
7Halifax Mooseheads1000010034-11000010034-10000000000010.500347005257377305525655284037111217100.00%6183.33%0929188949.18%888179249.55%40882349.57%12918951236386697353
8Hartford Wolfpack10001000321000000000001000100032121.0003580052573773455256552840257423300.00%20100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
9Hershey Bears1010000034-11010000034-10000000000000.000369005257377245525655284028106262150.00%30100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
10Iowa Wild22000000862110000003211100000054141.00081321005257377535525655284049134487114.29%2150.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
11Jacksonville Jokers210000018801000000145-11100000043130.7508152300525737778552565528405717452800.00%20100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
12Laval Rocket2000010157-22000010157-20000000000020.50059140052573775655256552840672216464125.00%7185.71%0929188949.18%888179249.55%40882349.57%12918951236386697353
13London Knights330000001477220000009451100000053261.000142539005257377114552565528408321147614535.71%7271.43%0929188949.18%888179249.55%40882349.57%12918951236386697353
14Long Island Ducks22000000936110000002111100000072541.00091827005257377855525655284054116497114.29%30100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
15Louisville Thunder21100000651110000003121010000034-120.50061218005257377585525655284063196516233.33%30100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
16Milwaukee Admirals31100001770110000005322010000124-230.500714210052573778755256552840801916759111.11%6183.33%0929188949.18%888179249.55%40882349.57%12918951236386697353
17Oakland Seals1010000035-21010000035-20000000000000.0003580052573772455256552840309028000.00%000.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
18Oakville Wolves11000000523000000000001100000052321.000510150052573773255256552840179426100.00%20100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
19Ontario Reign11000000422110000004220000000000021.0004711005257377295525655284026982111100.00%4175.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
20Pensacola Ice Flyers2010010036-31010000013-21000010023-110.250369005257377545525655284051126443133.33%3166.67%0929188949.18%888179249.55%40882349.57%12918951236386697353
21Philadelphia Phantoms1010000003-3000000000001010000003-300.0000000052573772055256552840305211300.00%10100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
22Rockford IceHogs41300000611-51010000023-13120000048-420.25061218115257377128552565528409524161011000.00%8187.50%0929188949.18%888179249.55%40882349.57%12918951236386697353
23Seattle Thunderbirds311010001192100010004312110000076140.66711182900525737794552565528409725147110110.00%50100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
24Syracuse Crunch2020000048-41010000035-21010000013-200.00047111052573777855256552840479114712216.67%20100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
25Texas Stars3110010037-42110000025-31000010012-130.5003580052573771035525655284098271662600.00%70100.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
26Toronto Marlies413000001012-22020000037-42110000075220.25010182800525737710855256552840140422810310220.00%14192.86%0929188949.18%888179249.55%40882349.57%12918951236386697353
Total53212002415149154-5261010012036975-62711100121280791570.538149267416215257377166255256552840155842125312601492315.44%1161487.93%1929188949.18%888179249.55%40882349.57%12918951236386697353
28Wilkes Barre-Scranton11000000431000000000001100000043121.00047110052573773955256552840294026400.00%000.00%0929188949.18%888179249.55%40882349.57%12918951236386697353
_Since Last GM Reset53212002415149154-5261010012036975-62711100121280791570.538149267416215257377166255256552840155842125312601492315.44%1161487.93%1929188949.18%888179249.55%40882349.57%12918951236386697353
_Vs Conference311213012038288-61666011024246-41567001014042-2310.5008214823011525737793555256552840926253162742771114.29%75889.33%0929188949.18%888179249.55%40882349.57%12918951236386697353

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
5357W114926741616621558421253126021
All Games
GPWLOTWOTL SOWSOLGFGA
5321202415149154
Home Games
GPWLOTWOTL SOWSOLGFGA
26101012036975
Visitor Games
GPWLOTWOTL SOWSOLGFGA
27111012128079
Last 10 Games
WLOTWOTL SOWSOL
360001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
1492315.44%1161487.93%1
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
552565528405257377
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
929188949.18%888179249.55%40882349.57%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
12918951236386697353


Last Played Games
Filter Tips
PriorityTypeDescription
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
10textAny text entered in the filter will match text found within the column
DayGame Visitor Team Score Home Team Score ST OT SO RI Link
1 - 2018-11-263Denver Spurs1Rockford IceHogs0WBoxScore
3 - 2018-11-2823Louisville Thunder1Denver Spurs3WBoxScore
4 - 2018-11-2937Denver Spurs2Milwaukee Admirals3LBoxScore
5 - 2018-11-3048Denver Spurs1Rockford IceHogs3LBoxScore
7 - 2018-12-0259Jacksonville Jokers5Denver Spurs4LXXBoxScore
8 - 2018-12-0371Denver Spurs5Oakville Wolves2WBoxScore
10 - 2018-12-0592Toronto Marlies4Denver Spurs1LBoxScore
11 - 2018-12-06107Denver Spurs3Toronto Marlies4LBoxScore
12 - 2018-12-07122Durham Pioneers3Denver Spurs2LXXBoxScore
15 - 2018-12-10142London Knights1Denver Spurs5WBoxScore
16 - 2018-12-11157Denver Spurs4Jacksonville Jokers3WBoxScore
17 - 2018-12-12165Denver Spurs5Iowa Wild4WBoxScore
19 - 2018-12-14185Laval Rocket3Denver Spurs2LXXBoxScore
21 - 2018-12-16201Denver Spurs5Seattle Thunderbirds3WBoxScore
22 - 2018-12-17214Texas Stars1Denver Spurs2WBoxScore
24 - 2018-12-19231Denver Spurs0Milwaukee Admirals1LXXBoxScore
26 - 2018-12-21245Milwaukee Admirals3Denver Spurs5WBoxScore
28 - 2018-12-23264Denver Spurs1Syracuse Crunch3LBoxScore
29 - 2018-12-24276Durham Pioneers1Denver Spurs5WBoxScore
31 - 2018-12-26296Texas Stars4Denver Spurs0LBoxScore
33 - 2018-12-28312Denver Spurs2Seattle Thunderbirds3LBoxScore
34 - 2018-12-29328Cleveland Monsters4Denver Spurs1LBoxScore
36 - 2018-12-31343Denver Spurs4Toronto Marlies1WBoxScore
38 - 2019-01-02359Denver Spurs4Wilkes Barre-Scranton3WBoxScore
39 - 2019-01-03368Halifax Mooseheads4Denver Spurs3LXBoxScore
41 - 2019-01-05389Denver Spurs2Rockford IceHogs5LBoxScore
42 - 2019-01-06399Hershey Bears4Denver Spurs3LBoxScore
44 - 2019-01-08418Adirondack Angels2Denver Spurs0LBoxScore
46 - 2019-01-10438Denver Spurs1Texas Stars2LXBoxScore
47 - 2019-01-11444Denver Spurs7Long Island Ducks2WBoxScore
49 - 2019-01-13462Toronto Marlies3Denver Spurs2LBoxScore
51 - 2019-01-15481Denver Spurs5London Knights3WBoxScore
52 - 2019-01-16495Rockford IceHogs3Denver Spurs2LBoxScore
54 - 2019-01-18509Denver Spurs5Durham Pioneers4WBoxScore
55 - 2019-01-19524Denver Spurs3Hartford Wolfpack2WXBoxScore
57 - 2019-01-21536Laval Rocket4Denver Spurs3LXBoxScore
58 - 2019-01-22550Denver Spurs2Pensacola Ice Flyers3LXBoxScore
60 - 2019-01-24568Long Island Ducks1Denver Spurs2WBoxScore
61 - 2019-01-25585Iowa Wild2Denver Spurs3WBoxScore
63 - 2019-01-27608London Knights3Denver Spurs4WBoxScore
64 - 2019-01-28619Denver Spurs6Binghamton Senators5WXXBoxScore
66 - 2019-01-30637Syracuse Crunch5Denver Spurs3LBoxScore
68 - 2019-02-01655Carolina Panthers1Denver Spurs2WBoxScore
70 - 2019-02-03670Denver Spurs4Carolina Panthers3WBoxScore
71 - 2019-02-04682Denver Spurs3Louisville Thunder4LBoxScore
73 - 2019-02-06702Pensacola Ice Flyers3Denver Spurs1LBoxScore
74 - 2019-02-07712Denver Spurs1Cleveland Monsters3LBoxScore
76 - 2019-02-09732Seattle Thunderbirds3Denver Spurs4WXBoxScore
78 - 2019-02-11746Denver Spurs0Philadelphia Phantoms3LBoxScore
79 - 2019-02-12754Denver Spurs2Bridgeport Sound Tigers3LXXBoxScore
82 - 2019-02-15775Oakland Seals5Denver Spurs3LBoxScore
84 - 2019-02-17793Denver Spurs2Adirondack Angels4LBoxScore
85 - 2019-02-18804Ontario Reign2Denver Spurs4WBoxScore
87 - 2019-02-20821Denver Spurs-Milwaukee Admirals-
88 - 2019-02-21835Butte Wolverines-Denver Spurs-
90 - 2019-02-23852Denver Spurs-Cleveland Monsters-
91 - 2019-02-24866Butte Wolverines-Denver Spurs-
93 - 2019-02-26884Denver Spurs-Halifax Mooseheads-
94 - 2019-02-27891Denver Spurs-Oakville Wolves-
95 - 2019-02-28899Binghamton Senators-Denver Spurs-
98 - 2019-03-03930Louisville Thunder-Denver Spurs-
99 - 2019-03-04946Denver Spurs-Hershey Bears-
100 - 2019-03-05959Ontario Reign-Denver Spurs-
103 - 2019-03-08982Richmond Renegades-Denver Spurs-
Trade Deadline --- Trades can’t be done after this day is simulated!
105 - 2019-03-101000Austin Aces-Denver Spurs-
106 - 2019-03-111015Denver Spurs-Iowa Wild-
107 - 2019-03-121029Hartford Wolfpack-Denver Spurs-
109 - 2019-03-141046Denver Spurs-Butte Wolverines-
111 - 2019-03-161063Bridgeport Sound Tigers-Denver Spurs-
112 - 2019-03-171073Denver Spurs-Laval Rocket-
114 - 2019-03-191091Wilkes Barre-Scranton-Denver Spurs-
115 - 2019-03-201104Denver Spurs-Ontario Reign-
118 - 2019-03-231124Jacksonville Jokers-Denver Spurs-
119 - 2019-03-241140Denver Spurs-Oakland Seals-
121 - 2019-03-261156Austin Aces-Denver Spurs-
122 - 2019-03-271164Denver Spurs-Richmond Renegades-
124 - 2019-03-291188Oakville Wolves-Denver Spurs-
125 - 2019-03-301198Denver Spurs-Richmond Renegades-
128 - 2019-04-021220Philadelphia Phantoms-Denver Spurs-
129 - 2019-04-031230Denver Spurs-Austin Aces-
131 - 2019-04-051246Oakville Wolves-Denver Spurs-
132 - 2019-04-061261Denver Spurs-Oakland Seals-



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance00
Attendance PCT0.00%0.00%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
15 0 - 0.00% 0$0$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
2,067,000$ 2,021,500$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
1,741,414$ 15,425$ 1,404,467$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 48 19,343$ 928,464$




OverallHomeVisitor
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
201853212002415149154-5261010012036975-6271110012128079157149267416215257377166255256552840155842125312601492315.44%1161487.93%1929188949.18%888179249.55%40882349.57%12918951236386697353
Total Regular Season53212002415149154-5261010012036975-6271110012128079157149267416215257377166255256552840155842125312601492315.44%1161487.93%1929188949.18%888179249.55%40882349.57%12918951236386697353