Spiders

GM : Simon Bouchard Morale : 77 Team Overall : 47
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# 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
1Ryan CarterXXX100.00675075697058605148465671486153079590
2James SheppardXX100.00675081697458695181505159445546080580
3Maxim LapierreXX100.00684381677555764784464764546758080580
4Andreas Martinsen (R)XX100.00825075667752464935485059483532082540
5Nikolay Goldobin (R)XX100.00463595765552355135465668483532071540
6Matt EllisXX100.00473591677249434262394466475649079530
7Steven PinizzottoX100.00713557667148354835465163474037079530
8Ryan Hamilton (C)X100.00503585677655344335404665444239072520
9John Quenneville (R)XX100.00505050505650505050505050503230080490
10Brett Pollock (R)X100.00454545455745454545454545453230079450
11Connor Hurley (R)X100.00454545455345454545454545453230033450
12John Hayden (R)X100.00434343437343434343434343433230027440
13Matt BartkowskiX100.00754380716465684735464769484744080610
14John Draeger (R)X100.00434343435943434343434343433230079440
15Keaton Thompson (R)X100.00434343435943434343434343433230080440
16Matt DelaheyX100.00404040406940404040404040403230032420
17Jamie DoornboschX100.00329327326533313335333333473532080370
18Kevin QuickX100.00329624345333353335333330473532082360
Scratches
1Colton OrrX100.00635055607845353339333356476254019470
2Justin ShuggXX100.00453578725743333335333360473532020450
3Arkhip Nekolenko (R)XX100.00454545454545454545454545453230020440
4Jimmy Vesey (R)X100.00434343436643434343434343433230036440
5Kyle Platzer (R)XX100.00404040405740404040404040403230028410
6Zachary Stepan (R)X100.00404040404740404040404040403230020410
7Anton Zlobin (R)XX100.00373737376637373737373737373230020390
8Michael CarusoX100.00328733336233383335333333473532020370
9Shane SimsX100.00329327326333313335333333473532020360
TEAM AVERAGE100.0049505552644544424441435045393605547
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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
1Anton Khudobin100.0057457875575959575887634844062600
2Mackenzie Skapski100.0052455570515151505162603532080520
Scratches
1Jon Gillies (R)100.0043434383434343434343433230062460
2Brent Moran (R)100.0040404068404040404040403230020420
3Stephon Williams (R)100.0040404071404040404040403230019420
TEAM AVERAGE100.004643517346474746465449363304948
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Phil Housley60767162657067USA524500,000$


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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
1Maxim LapierreSpiders (Har)C/RW723969108483601032012140018.22%38137719.131326396628302271758368.67%159900021.5714000697
2James SheppardSpiders (Har)C/LW78376610346400641772480014.92%25126716.25131730742910002373370.06%144600111.63020001116
3Ryan CarterSpiders (Har)C/LW/RW6840621025481251121292910013.75%23118817.48101929642491126794250.33%46100001.7203031476
4Matt BartkowskiSpiders (Har)D752065852412801911151900010.53%117176023.471118291072842136281320.00%000000.9700000364
5Matt EllisSpiders (Har)C/LW8222517331004831820012.09%31100712.2961723542450001123257.37%25100001.4501000403
6Nikolay GoldobinSpiders (Har)LW/RW4131386934001871640018.90%2069917.07111021451750000144242.86%4900011.9701000643
7Steven PinizzottoSpiders (Har)RW82333467457001491031900017.37%32112713.75202625044143327141.90%10500011.1900000644
8Andreas MartinsenSpiders (Har)LW/RW762141624411715142841930010.88%1899013.04077201080001184146.88%6400011.2500102313
9John QuennevilleSpiders (Har)C/LW8217284515451571901120015.18%1795711.6822476101141423248.66%70700000.9401012003
10Ryan HamiltonSpiders (Har)LW6823204313100211201450015.86%4694513.91213732202133143142.97%64000010.9100000111
11Brett PollockSpiders (Har)LW8213253814601087521030012.62%996111.72134107710111330148.54%10300010.7900002013
12Connor HurleySpiders (Har)C28681413601327260023.08%32629.3800000000001047.51%30100001.0700000211
13John DraegerSpiders (Har)D8201111575401142725000.00%71162819.8602282650002321000.00%000000.1400000001
14Jamie DoornboschSpiders (Har)D8217852835122870014.29%50139517.020110520000270010.00%000000.1100001000
15Kevin QuickSpiders (Har)D82055541382011362000.00%32134616.4300001010000173000.00%000000.0700211000
16Jimmy VeseySpiders (Har)LW26145560271090011.11%139715.28101366000040047.06%3400000.2501000000
17Keaton ThompsonSpiders (Har)D82145215010461324004.17%49164520.07011142530000344000.00%000000.0600011000
18Colton OrrSpiders (Har)RW6213-18010350040.00%0579.540000000000100.00%200001.0500000010
19Kyle PlatzerSpiders (Har)C/RW35033-6120302410000.00%23128.9300000000000039.27%24700000.1900000000
20Matt DelaheySpiders (Har)D24033111602512000.00%1047119.64011068000041000.00%000000.1300000000
21John HaydenSpiders (Har)C19022-40092610000.00%21889.910001250001190049.36%15600000.2100000000
22Michael CarusoSpiders (Har)D4000460710000.00%56817.1800007000010000.00%000000.0000000000
Team Total or Average12763075478545749661001461138721520014.27%6012005815.727212519748626766915582728442158.13%616500180.851133610463645
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
1Mackenzie SkapskiSpiders (Har)45281070.8943.0726980313813080100.600104431311
2Jon GilliesSpiders (Har)1813400.8853.46105720615300501.00041846000
3Anton KhudobinSpiders (Har)139310.9032.6878420353590000.5004134001
4Stephon WilliamsSpiders (Har)77000.9112.7142021192140100.000071000
Team Total or Average83571780.8953.0649606425324110700.667188282312


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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 Force Waivers Contract StatusType Current Salary Salary RemainingSalary 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
Andreas MartinsenSpiders (Har)LW/RW251990-06-13Yes220 Lbs6 ft3NoNo4RFAPro & Farm743,000$743,000$743,000$743,000$Link
Anton KhudobinSpiders (Har)G291986-05-07No203 Lbs5 ft11NoNo2RFAPro & Farm1,600,000$1,600,000$Link
Anton ZlobinSpiders (Har)LW/RW221993-02-22Yes195 Lbs5 ft11NoNo4RFAPro & Farm625,000$625,000$625,000$625,000$Link
Arkhip NekolenkoSpiders (Har)LW/RW181996-11-03Yes159 Lbs6 ft1NoNo4ELCPro & Farm825,000$825,000$825,000$825,000$Link
Brent MoranSpiders (Har)G191996-07-05Yes186 Lbs6 ft3NoNo4ELCPro & Farm650,000$650,000$650,000$650,000$Link
Brett PollockSpiders (Har)LW191996-05-17Yes182 Lbs6 ft2NoNo4ELCPro & Farm925,000$925,000$925,000$925,000$Link
Colton OrrSpiders (Har)RW331982-03-03No222 Lbs6 ft3NoNo2UFAPro & Farm910,000$910,000$Link
Connor HurleySpiders (Har)C201995-09-15Yes174 Lbs6 ft1NoNo4ELCPro & Farm825,000$825,000$825,000$825,000$Link
James SheppardSpiders (Har)C/LW271988-04-25No215 Lbs6 ft1NoNo4RFAPro & Farm900,000$900,000$900,000$900,000$Link
Jamie DoornboschSpiders (Har)D251990-02-01No198 Lbs6 ft2NoNo3RFAPro & Farm700,000$700,000$700,000$Link
Jimmy VeseySpiders (Har)LW221993-05-26Yes194 Lbs6 ft1NoNo4RFAPro & Farm700,000$700,000$700,000$700,000$Link
John DraegerSpiders (Har)D211993-12-02Yes186 Lbs6 ft1NoNo4ELCPro & Farm700,000$700,000$700,000$700,000$Link
John HaydenSpiders (Har)C201995-02-14Yes210 Lbs6 ft2NoNo4ELCPro & Farm700,000$700,000$700,000$700,000$Link
John QuennevilleSpiders (Har)C/LW191996-04-16Yes182 Lbs6 ft0NoNo4ELCPro & Farm843,000$843,000$843,000$843,000$Link
Jon GilliesSpiders (Har)G211994-01-22Yes216 Lbs6 ft4NoNo4ELCPro & Farm925,000$925,000$925,000$925,000$Link
Justin ShuggSpiders (Har)LW/RW231991-12-24No185 Lbs5 ft11NoNo3RFAPro & Farm600,000$600,000$600,000$Link
Keaton ThompsonSpiders (Har)D201995-09-14Yes187 Lbs6 ft0NoNo4ELCPro & Farm700,000$700,000$700,000$700,000$Link
Kevin QuickSpiders (Har)D271988-03-29No175 Lbs6 ft0NoNo1RFAPro & Farm700,000$Link
Kyle PlatzerSpiders (Har)C/RW201995-03-04Yes185 Lbs5 ft11NoNo4ELCPro & Farm710,000$710,000$710,000$710,000$Link
Mackenzie SkapskiSpiders (Har)G211994-06-15No191 Lbs6 ft3NoNo3ELCPro & Farm630,000$630,000$630,000$Link
Matt BartkowskiSpiders (Har)D271988-06-04No196 Lbs6 ft1NoNo1RFAPro & Farm985,000$Link
Matt DelaheySpiders (Har)D261989-09-25No210 Lbs6 ft1NoNo4RFAPro & Farm650,000$650,000$650,000$650,000$Link
Matt EllisSpiders (Har)C/LW341981-08-31No208 Lbs6 ft0NoNo2UFAPro & Farm700,000$700,000$Link
Maxim LapierreSpiders (Har)C/RW301985-03-29No215 Lbs6 ft2NoNo4UFAPro & Farm1,000,000$1,000,000$1,000,000$1,000,000$Link
Michael CarusoSpiders (Har)D271988-07-05No191 Lbs6 ft2NoNo1RFAPro & Farm600,000$Link
Nikolay GoldobinSpiders (Har)LW/RW191995-10-07Yes180 Lbs5 ft11NoNo4ELCPro & Farm925,000$925,000$925,000$925,000$Link
Ryan CarterSpiders (Har)C/LW/RW321983-08-03No202 Lbs6 ft1YesNo5UFAPro & Farm500,000$500,000$500,000$500,000$500,000$Link
Ryan HamiltonSpiders (Har)LW301985-04-15No219 Lbs6 ft2NoNo3UFAPro & Farm600,000$600,000$600,000$Link
Shane SimsSpiders (Har)D271988-04-30No195 Lbs6 ft1NoNo1RFAPro & Farm725,000$Link
Stephon WilliamsSpiders (Har)G221993-04-28Yes194 Lbs6 ft1NoNo4RFAPro & Farm925,000$925,000$925,000$925,000$Link
Steven PinizzottoSpiders (Har)RW311984-04-26No205 Lbs6 ft1NoNo2UFAPro & Farm650,000$650,000$Link
Zachary StepanSpiders (Har)C211994-01-06Yes165 Lbs5 ft11NoNo4ELCPro & Farm650,000$650,000$650,000$650,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3224.28195 Lbs6 ft13.28775,656$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ryan HamiltonJames SheppardMaxim Lapierre36113
2Nikolay GoldobinRyan CarterAndreas Martinsen34113
3John QuennevilleMatt EllisSteven Pinizzotto20122
4Brett PollockConnor HurleyJohn Hayden10311
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Matt BartkowskiKeaton Thompson33122
2John DraegerMatt Delahey32122
3Jamie DoornboschKevin Quick25122
4Matt BartkowskiMatt Delahey10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Nikolay GoldobinJames SheppardMaxim Lapierre60014
2John QuennevilleRyan CarterAndreas Martinsen40104
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Matt BartkowskiMatt Delahey60014
2John DraegerKeaton Thompson40113
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1Maxim LapierreSteven Pinizzotto60122
2Ryan CarterNikolay Goldobin40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Matt BartkowskiKeaton Thompson60122
2John DraegerJamie Doornbosch40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Maxim Lapierre60122Matt BartkowskiKeaton Thompson60122
2Ryan Carter40122John DraegerKevin Quick40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Maxim LapierreNikolay Goldobin60122
2James SheppardRyan Carter40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Matt BartkowskiKeaton Thompson60122
2Matt DelaheyJamie Doornbosch40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
James SheppardMaxim LapierreRyan CarterMatt BartkowskiJohn Draeger
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Matt EllisMaxim LapierreRyan CarterMatt BartkowskiJohn Draeger
Extra Forwards
Normal PowerPlayPenalty Kill
Brett Pollock, James Sheppard, Andreas MartinsenBrett Pollock, Andreas MartinsenSteven Pinizzotto
Extra Defensemen
Normal PowerPlayPenalty Kill
Matt Delahey, Kevin Quick, John DraegerMatt BartkowskiKevin Quick, John Draeger
Penalty Shots
John Quenneville, Ryan Carter, Maxim Lapierre, Nikolay Goldobin, Matt Ellis
Goalie
#1 : Anton Khudobin, #2 : Mackenzie Skapski


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
Admirals2110000059-4110000003211010000027-520.50051015001571339395690995485641712526411119.09%13469.23%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Falcons43001000209112200000011472100100095481.000203353001571339391259099548564111234409424729.17%20195.00%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Bruins3200001018991100000063321000010126661.00018294700157133939118909954856417919426313215.38%21385.71%11575271458.03%1453260755.73%834143158.28%2004135318916321068533
Crunch3210000015132211000009901100000064240.667152843001571339391269099548564110123386224833.33%19478.95%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Heat21100000752110000004131010000034-120.500713200015713393961909954856416014184517423.53%9277.78%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Phantoms531001002519632000100181262110000077070.7002545700015713393917090995485641161506810026623.08%34682.35%11575271458.03%1453260755.73%834143158.28%2004135318916321068533
Baby Hawks211000001073110000007251010000035-220.500101727001571339396090995485641571629391119.09%14378.57%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Monsters2010010047-31000010034-11010000013-210.2504711001571339394690995485641642140317228.57%14471.43%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Jayhawks2110000089-11010000035-21100000054120.50081523001571339395090995485641583045324375.00%19573.68%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Cougars3110100016124110000008352010100089-140.66716284400157133939103909954856417428416015320.00%18288.89%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Oil Kings220000001129110000006241100000050541.0001120310115713393965909954856415119274217317.65%10190.00%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Sound Tigers42100001141402110000078-12100000176150.625142236001571339391189099548564111729607816318.75%22290.91%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Monarchs210000016511000000112-11100000053230.750611170015713393961909954856417114324010110.00%16193.75%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Minnesota220000001358110000006331100000072541.0001324370015713393995909954856415516315914428.57%13284.62%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Senators3200000112842200000010551000000123-150.833122032001571339399290995485641832337511516.67%15473.33%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Manchots54001000265212200000014113320010001248101.000264470011571339391829099548564110123588322522.73%22290.91%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Wolf Pack4310000025121321100000136722000000126660.7502541660015713393920490995485641120313011125520.00%15473.33%11575271458.03%1453260755.73%834143158.28%2004135318916321068533
Sharks2110000068-2110000005411010000014-320.50061016001571339397290995485641532220361218.33%10460.00%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Chiefs20200000610-41010000014-31010000056-100.000611170015713393952909954856416216423611218.18%11645.45%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Thunder311000011011-11010000025-32100000186230.5001017270015713393996909954856418525345820315.00%17382.35%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Marlies33000000217142200000015691100000061561.00021375800157133939112909954856415918375015320.00%16568.75%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Comets220000001367110000007251100000064241.000132538001571339395790995485641571828449222.22%13376.92%11575271458.03%1453260755.73%834143158.28%2004135318916321068533
Cabaret Lady Mary Ann320010001587110000006152100100097261.0001528430015713393999909954856411184238699111.11%18477.78%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
IceCaps210001001091110000006421000010045-130.7501016260015713393956909954856417015304910330.00%15566.67%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Chill21100000743110000004041010000034-120.50071017011571339395090995485641652041558337.50%130100.00%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Rocket311010001293211000007521000100054140.66712223401157133939107909954856418937475313323.08%16287.50%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Bears430010002110112200000013492100100086281.000213455001571339391119099548564113055697916637.50%32778.13%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Caroline4210010023203220000001385201001001012-250.625233760001571339391239099548564113435669020315.00%21576.19%21575271458.03%1453260755.73%834143158.28%2004135318916321068533
Las Vegas220000001156110000006331100000052341.0001120310015713393974909954856415416334111436.36%13192.31%01575271458.03%1453260755.73%834143158.28%2004135318916321068533
Vs Division30113011011548965156200100894346155101001654619260.433154256410011571339391033909954856418752573916351493523.49%1662783.73%41575271458.03%1453260755.73%834143158.28%2004135318916321068533
Vs Conference452870321420513273221730010111360532311403113927220700.7782053425470215713393915119099548564113183855879382284720.61%2654682.64%31575271458.03%1453260755.73%834143158.28%2004135318916321068533
Since Last GM Reset8250170641439025713341317002012141189641191006213176139371220.7443906741064041571339392741909954856412411734114716914259321.88%4899580.57%61575271458.03%1453260755.73%834143158.28%2004135318916321068533
Total8250170641439025713341317002012141189641191006213176139371220.7443906741064041571339392741909954856412411734114716914259321.88%4899580.57%61575271458.03%1453260755.73%834143158.28%2004135318916321068533

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
82122L13906741064274124117341147169104
All Games
GPWLOTWOTL SOWSOLGFGA
8250176414390257
Home Games
GPWLOTWOTL SOWSOLGFGA
413170201214118
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4119106213176139
Last 10 Games
WLOTWOTL SOWSOL
720001
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4259321.88%4899580.57%6
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
90995485641157133939
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1575271458.03%1453260755.73%834143158.28%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
2004135318916321068533


Last Played Games
Filter Tips
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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)
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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
2 - 2016-10-136Spiders3Cabaret Lady Mary Ann2WBoxScore
4 - 2016-10-1520Spiders5Thunder2WBoxScore
7 - 2016-10-1838Admirals2Spiders3WBoxScore
9 - 2016-10-2051Spiders5Bruins4WXXBoxScore
11 - 2016-10-2266Minnesota3Spiders6WBoxScore
14 - 2016-10-2584Chill0Spiders4WBoxScore
17 - 2016-10-28107Baby Hawks2Spiders7WBoxScore
18 - 2016-10-29114Thunder5Spiders2LBoxScore
23 - 2016-11-03156Spiders6Cabaret Lady Mary Ann5WXBoxScore
25 - 2016-11-05166Spiders3Thunder4LXXBoxScore
26 - 2016-11-06176Spiders3Caroline4LBoxScore
28 - 2016-11-08183Caroline2Spiders6WBoxScore
31 - 2016-11-11206Spiders6Crunch4WBoxScore
32 - 2016-11-12219Crunch5Spiders3LBoxScore
35 - 2016-11-15236Spiders5Jayhawks4WBoxScore
37 - 2016-11-17251Spiders2Admirals7LBoxScore
39 - 2016-11-19266Spiders5Monarchs3WBoxScore
41 - 2016-11-21282Spiders1Sharks4LBoxScore
43 - 2016-11-23289Marlies3Spiders7WBoxScore
45 - 2016-11-25306Cougars3Spiders8WBoxScore
46 - 2016-11-26317Spiders3Manchots2WXBoxScore
49 - 2016-11-29335Spiders4IceCaps5LXBoxScore
51 - 2016-12-01353Spiders3Baby Hawks5LBoxScore
53 - 2016-12-03369Spiders5Las Vegas2WBoxScore
56 - 2016-12-06390Comets2Spiders7WBoxScore
58 - 2016-12-08398Spiders5Rocket4WXBoxScore
59 - 2016-12-09407Chiefs4Spiders1LBoxScore
61 - 2016-12-11426Spiders5Wolf Pack2WBoxScore
65 - 2016-12-15449Spiders5Chiefs6LBoxScore
67 - 2016-12-17463Spiders2Senators3LXXBoxScore
68 - 2016-12-18472Spiders7Wolf Pack4WBoxScore
70 - 2016-12-20482Las Vegas3Spiders6WBoxScore
72 - 2016-12-22496Phantoms4Spiders6WBoxScore
73 - 2016-12-23511Spiders4Manchots1WBoxScore
77 - 2016-12-27517Manchots0Spiders8WBoxScore
79 - 2016-12-29533Spiders5Bears4WBoxScore
81 - 2016-12-31553Bears2Spiders8WBoxScore
83 - 2017-01-02563Bruins3Spiders6WBoxScore
84 - 2017-01-03567Spiders7Caroline8LXBoxScore
87 - 2017-01-06586Marlies3Spiders8WBoxScore
88 - 2017-01-07594Oil Kings2Spiders6WBoxScore
90 - 2017-01-09609Cabaret Lady Mary Ann1Spiders6WBoxScore
93 - 2017-01-12631Spiders5Oil Kings0WBoxScore
94 - 2017-01-13638Spiders3Heat4LBoxScore
96 - 2017-01-15653Spiders6Comets4WBoxScore
98 - 2017-01-17667Spiders7Minnesota2WBoxScore
101 - 2017-01-20688Rocket0Spiders4WBoxScore
102 - 2017-01-21695Spiders3Phantoms4LBoxScore
105 - 2017-01-24715Monarchs2Spiders1LXXBoxScore
107 - 2017-01-26739Bears2Spiders5WBoxScore
112 - 2017-01-31751Spiders6Cougars5WXBoxScore
115 - 2017-02-03770Heat1Spiders4WBoxScore
116 - 2017-02-04778Spiders6Falcons3WBoxScore
118 - 2017-02-06788Crunch4Spiders6WBoxScore
124 - 2017-02-12828Sharks4Spiders5WBoxScore
126 - 2017-02-14836Monsters4Spiders3LXBoxScore
128 - 2017-02-16847Senators2Spiders3WBoxScore
130 - 2017-02-18861Sound Tigers5Spiders3LBoxScore
131 - 2017-02-19870Spiders4Sound Tigers2WBoxScore
133 - 2017-02-21882Senators3Spiders7WBoxScore
137 - 2017-02-25906Wolf Pack4Spiders3LBoxScore
139 - 2017-02-27919Rocket5Spiders3LBoxScore
142 - 2017-03-02939Spiders3Bears2WXBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
144 - 2017-03-04952Spiders7Bruins2WBoxScore
145 - 2017-03-05963Falcons2Spiders5WBoxScore
147 - 2017-03-07974Spiders3Falcons2WXBoxScore
149 - 2017-03-09985Spiders1Monsters3LBoxScore
151 - 2017-03-111010Spiders3Chill4LBoxScore
154 - 2017-03-141029IceCaps4Spiders6WBoxScore
156 - 2017-03-161039Phantoms5Spiders4LXBoxScore
157 - 2017-03-171050Spiders5Manchots1WBoxScore
159 - 2017-03-191066Falcons2Spiders6WBoxScore
161 - 2017-03-211077Wolf Pack2Spiders10WBoxScore
163 - 2017-03-231091Spiders6Marlies1WBoxScore
165 - 2017-03-251109Caroline6Spiders7WBoxScore
166 - 2017-03-261118Jayhawks5Spiders3LBoxScore
171 - 2017-03-311151Spiders3Sound Tigers4LXXBoxScore
172 - 2017-04-011161Spiders4Phantoms3WBoxScore
175 - 2017-04-041188Phantoms3Spiders8WBoxScore
177 - 2017-04-061198Manchots1Spiders6WBoxScore
179 - 2017-04-081210Sound Tigers3Spiders4WBoxScore
180 - 2017-04-091229Spiders2Cougars4LBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3015
Attendance6174031448
Attendance PCT75.29%76.70%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2273 - 75.76% 56,681$2,323,920$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
2,482,100$ 2,482,100$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
2,968,750$ 13,713$ 2,465,975$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 16,476$ 0$




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
Regular Season
20168250170641439025713341317002012141189641191006213176139371003906741064041571339392741909954856412411734114716914259321.88%4899580.57%61575271458.03%1453260755.73%834143158.28%2004135318916321068533
Total Regular Season8250170641439025713341317002012141189641191006213176139371003906741064041571339392741909954856412411734114716914259321.88%4899580.57%61575271458.03%1453260755.73%834143158.28%2004135318916321068533