Thunder

GM : Jean-François Moquin Morale : 73 Team Overall : 45
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
1Ronalds KeninsX100.00593583696957365150505263483533081550
2Brett RitchieX100.00644381667758365045455461483532082540
3Nicklas JensenXX100.00493586667156344635424959543936081520
4Tommy SestitoX100.00644325618248354635573558484844078520
5Derek GrantXX100.00593591677152363956433564483734081500
6Brody Sutter (R)XX100.00543595657253353570353564453532080490
7Kasperi KapanenXX100.00463588695457353535353566483532081480
8Petr StrakaXX100.00453594685846333535363359473532081460
9Samuel Henley (R)XX100.00454545457545454545454545453230077460
10Ryan Martindale (R)X100.00434343435843434343434343433230058440
11John PerssonX100.00328535457333503335333354473532082420
12Luca CaputiX100.00399228427033433335333344474036041400
13Brett Lernout (R)X100.00573595657142353135303261483532081500
14Thomas Vannelli (R)X100.00454545454945454545454545453230081450
15James Melindy (R)X100.00434343436043434343434343433230081440
16Simon Bertilsson (R)X100.00434343436343434343434343433230081440
17Michael Brodzinski (R)X100.00373737376037373737373737373230081400
Scratches
1Carter AshtonX100.00564385667549353749403354474036042480
2Adam Gilmour (R)XX100.00404040406640404040404040403230019420
3Thomas Di Pauli (R)X100.00404040405940404040404040403230019410
4Spencer MachacekX100.00358931416933413335333342474036032400
5Nicolas DeschampsX100.00328535355233433335333335473532019370
6Jamie ArnielXX100.00329327325633403335333333473532019360
7Rinat ValievX100.00503595677049353135303272483532028520
8Calle Andersson (R)X100.00404040406940404040404040403230020420
9Adam Polasek (R)X100.00373737376237373737373737373230019390
10Mikael Wikstrand (R)X100.00373737375737373737373737373230020390
TEAM AVERAGE100.0045485651654439394139395045353205745
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
1Linus Ullmark100.0047458981494850514565703532076530
Scratches
1Calvin Pickard100.0069458174726874746289703532065650
2Jake Paterson (R)100.0043434363434343434343433230020440
3Zachary Nagelvoort (R)100.0040404069404040404040403230020420
4Janne Juvonen (R)100.0037373766373737373737373230020400
5Timo Pielmeier100.0036383862373636383633333532020390
TEAM AVERAGE100.004541556946454747445149343103747
Coaches Name PH DF OF PD EX LD PO CNT Age Contract Salary
Dean Evason53807749787068CAN522500,000$


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
1Ronalds KeninsThunder (Tam)LW81527312547340861563750013.87%32160619.841322359934501121646450.00%11200121.564170008129
2Brett RitchieThunder (Tam)RW825355108566820911373020017.55%34140017.0799185117311261783651.60%28100021.541131121376
3Derek GrantThunder (Tam)C/LW8221436410160341941720012.21%23128715.70101121453211011322055.86%152700000.9901000343
4Nicklas JensenThunder (Tam)LW/RW82323163102610251242560012.50%16131716.0661218723220111546241.76%9100000.9625002123
5Tommy SestitoThunder (Tam)LW8219395817163252591401650011.52%18133016.22110112923710181462238.61%10100000.8727014542
6Samuel HenleyThunder (Tam)C/LW821228403610030881201020011.76%6114713.990115920001911047.40%140300000.7000222014
7Brett LernoutThunder (Tam)D82629351500985078007.69%72164720.09369372860001134210.00%000000.4201000011
8Petr StrakaThunder (Tam)LW/RW82171835875171141490011.41%2188910.844812411920004912143.02%8600000.7900000014
9Kasperi KapanenThunder (Tam)LW/RW82141933-108022116169008.28%2386410.55000410000071339.62%5300000.7600000212
10Thomas VannelliThunder (Tam)D8272330301111514138510013.73%77152918.66347212410111212300.00%000000.3900111221
11Brody SutterThunder (Tam)C/RW4261521-6160199571008.45%1064015.2639122217100001081160.17%69300000.6600000112
12John PerssonThunder (Tam)LW8211920969355849680016.18%2091111.12213157721392180044.59%14800000.4400502002
13James MelindyThunder (Tam)D8221618368751153026007.69%51126015.37022101190111171000.00%000000.2900001201
14Ryan MartindaleThunder (Tam)C414131752204126370010.81%22887.0300000000001042.86%35700001.1800000100
15Simon BertilssonThunder (Tam)D8221315289751432231006.45%75145817.78101122290000208000.00%000000.2100010003
16Carter AshtonThunder (Tam)LW426410-732103744480012.50%645910.951125190003761443.24%3700000.4300011010
17Rinat ValievThunder (Tam)D20549020318450011.11%2742421.234263488000082200.00%000000.4200000010
18Luca CaputiThunder (Tam)LW41358-35556316200015.00%343810.6900002000010044.44%2700000.3600001100
19Michael BrodzinskiThunder (Tam)D8226822640784130015.38%39128915.7211242240000229000.00%000000.1200000000
20Spencer MachacekThunder (Tam)RW33011235151832000.00%11665.04000013000000047.06%1700000.1200201000
21Adam GilmourThunder (Tam)C/RW3000-100101000.00%062.240000000000000.00%100000.0000000000
22Adam PolasekThunder (Tam)D1000000000000.00%01111.300000000000000.00%000000.0000000000
23Calle AnderssonThunder (Tam)D2000120301000.00%13115.780000800005000.00%000000.0000000000
24Jamie ArnielThunder (Tam)C/RW4000100300000.00%0287.2300000000000030.43%2300000.0000000000
25Nicolas DeschampsThunder (Tam)LW1000000000000.00%033.600000000003000.00%200000.0000000000
26Thomas Di PauliThunder (Tam)C1000000100000.00%011.820000100000000.00%100000.0000000000
Team Total or Average137827444471829210641801444149621820012.56%5572044114.83619916050631815611382222332451.07%496000140.7094411717393843
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
1Calvin PickardThunder (Tam)57391320.9132.43328217213315250100.906325224523
2Linus UllmarkThunder (Tam)33141040.8684.321721201249390200.818333058100
Team Total or Average90532360.8963.08500319225724640300.862658282623


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 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
Adam GilmourThunder (Tam)C/RW211994-01-29Yes193 Lbs6 ft2NoNo4ELCPro & Farm650,000$650,000$650,000$650,000$Link
Adam PolasekThunder (Tam)D241991-07-12Yes190 Lbs6 ft3NoNo4RFAPro & Farm525,000$525,000$525,000$525,000$Link
Brett LernoutThunder (Tam)D201995-09-24Yes213 Lbs6 ft4NoNo4ELCPro & Farm667,000$667,000$667,000$667,000$Link
Brett RitchieThunder (Tam)RW221993-07-01No220 Lbs6 ft3NoNo3RFAPro & Farm818,000$818,000$818,000$Link
Brody SutterThunder (Tam)C/RW241991-09-26Yes203 Lbs6 ft5NoNo3RFAPro & Farm585,000$585,000$585,000$Link
Calle AnderssonThunder (Tam)D211994-05-16Yes211 Lbs6 ft2NoNo4ELCPro & Farm660,000$660,000$660,000$660,000$Link
Calvin PickardThunder (Tam)G231992-04-15No200 Lbs6 ft1NoNo3RFAPro & Farm810,000$810,000$810,000$Link
Carter AshtonThunder (Tam)LW241991-04-01No215 Lbs6 ft3NoNo3RFAPro & Farm1,100,000$1,100,000$1,100,000$Link
Derek GrantThunder (Tam)C/LW251990-04-20No202 Lbs6 ft3NoNo1RFAPro & Farm580,000$Link
Jake PatersonThunder (Tam)G211994-05-03Yes176 Lbs6 ft0NoNo4ELCPro & Farm667,000$667,000$667,000$667,000$Link
James MelindyThunder (Tam)D211993-12-11Yes187 Lbs6 ft2NoNo4ELCPro & Farm675,000$675,000$675,000$675,000$Link
Jamie ArnielThunder (Tam)C/RW251989-11-16No183 Lbs5 ft11NoNo3RFAPro & Farm800,000$800,000$800,000$Link
Janne JuvonenThunder (Tam)G211994-10-03Yes183 Lbs6 ft1NoNo4ELCPro & Farm525,000$525,000$525,000$525,000$Link
John PerssonThunder (Tam)LW231992-05-18No209 Lbs6 ft2NoNo2RFAPro & Farm610,000$610,000$Link
Kasperi KapanenThunder (Tam)LW/RW191996-07-23No178 Lbs6 ft0NoNo4ELCPro & Farm925,000$925,000$925,000$925,000$Link
Linus UllmarkThunder (Tam)G221993-07-31No212 Lbs6 ft4NoNo4RFAPro & Farm792,000$792,000$792,000$792,000$Link
Luca CaputiThunder (Tam)LW271988-10-01No200 Lbs6 ft3NoNo1RFAPro & Farm630,000$Link
Michael BrodzinskiThunder (Tam)D201995-05-28Yes190 Lbs5 ft11NoNo4ELCPro & Farm525,000$525,000$525,000$525,000$Link
Mikael WikstrandThunder (Tam)D211993-11-05Yes183 Lbs6 ft1NoNo4ELCPro & Farm830,000$830,000$830,000$830,000$Link
Nicklas JensenThunder (Tam)LW/RW221993-03-06No202 Lbs6 ft3NoNo1RFAPro & Farm925,000$Link
Nicolas DeschampsThunder (Tam)LW251990-01-06No173 Lbs6 ft0NoNo2RFAPro & Farm726,000$726,000$Link
Petr StrakaThunder (Tam)LW/RW231992-06-15No185 Lbs6 ft1NoNo3RFAPro & Farm925,000$925,000$925,000$Link
Rinat ValievThunder (Tam)D201995-05-11No214 Lbs6 ft2NoNo4ELCPro & Farm743,000$743,000$743,000$743,000$Link
Ronalds KeninsThunder (Tam)LW241991-02-28No201 Lbs6 ft0NoNo3RFAPro & Farm718,000$718,000$718,000$Link
Ryan MartindaleThunder (Tam)C231991-10-27Yes183 Lbs6 ft3NoNo4RFAPro & Farm700,000$700,000$700,000$700,000$Link
Samuel HenleyThunder (Tam)C/LW221993-07-25Yes220 Lbs6 ft0NoNo4RFAPro & Farm590,000$590,000$590,000$590,000$Link
Simon BertilssonThunder (Tam)D241991-04-19Yes196 Lbs6 ft0NoNo4RFAPro & Farm700,000$700,000$700,000$700,000$Link
Spencer MachacekThunder (Tam)RW261988-10-14No200 Lbs6 ft1NoNo1RFAPro & Farm750,000$Link
Thomas Di PauliThunder (Tam)C211994-04-29Yes188 Lbs5 ft11NoNo4ELCPro & Farm650,000$650,000$650,000$650,000$Link
Thomas VannelliThunder (Tam)D201995-01-26Yes165 Lbs6 ft2NoNo4ELCPro & Farm667,000$667,000$667,000$667,000$Link
Timo PielmeierThunder (Tam)G261989-07-07No175 Lbs5 ft11NoNo2RFAPro & Farm725,000$725,000$Link
Tommy SestitoThunder (Tam)LW281987-09-28No228 Lbs6 ft5NoNo6RFAPro & Farm750,000$750,000$750,000$750,000$750,000$750,000$Link
Zachary NagelvoortThunder (Tam)G211994-01-30Yes190 Lbs6 ft2NoNo4ELCPro & Farm650,000$650,000$650,000$650,000$Link
Total PlayersAverage AgeAverage WeightAverage HeightAverage ContractAverage Year 1 Salary
3322.70196 Lbs6 ft23.30714,939$



5 vs 5 Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ronalds KeninsSamuel HenleyBrett Ritchie40122
2Tommy SestitoDerek GrantNicklas Jensen30122
3Luca CaputiKasperi Kapanen20122
4John PerssonRyan MartindalePetr Straka10122
5 vs 5 Defense
Line #DefenseDefenseTime %PHYDFOF
1Brett Lernout40122
2Thomas VannelliSimon Bertilsson30122
3James MelindyMichael Brodzinski20122
4James MelindyBrett Lernout10122
Power Play Forward
Line #Left WingCenterRight WingTime %PHYDFOF
1Ronalds KeninsPetr Straka60122
2Tommy SestitoDerek GrantNicklas Jensen40122
Power Play Defense
Line #DefenseDefenseTime %PHYDFOF
1Michael BrodzinskiBrett Lernout60122
2Thomas VannelliSimon Bertilsson40122
Penalty Kill 4 Players Forward
Line #CenterWingTime %PHYDFOF
1John Persson60122
2Brett RitchieTommy Sestito40122
Penalty Kill 4 Players Defense
Line #DefenseDefenseTime %PHYDFOF
1Michael Brodzinski60122
2Thomas VannelliSimon Bertilsson40122
Penalty Kill 3 Players
Line #WingTime %PHYDFOFDefenseDefenseTime %PHYDFOF
1Derek Grant60122Brett Lernout60122
2Kasperi Kapanen40122Thomas VannelliSimon Bertilsson40122
4 vs 4 Forward
Line #CenterWingTime %PHYDFOF
1Ryan MartindaleRonalds Kenins60122
2Samuel HenleyTommy Sestito40122
4 vs 4 Defense
Line #DefenseDefenseTime %PHYDFOF
1Brett Lernout60122
2Thomas VannelliSimon Bertilsson40122
Last Minutes Offensive
Left WingCenterRight WingDefenseDefense
Ronalds KeninsBrett RitchieMichael BrodzinskiSimon Bertilsson
Last Minutes Defensive
Left WingCenterRight WingDefenseDefense
Ronalds KeninsSamuel HenleyBrett RitchieBrett Lernout
Extra Forwards
Normal PowerPlayPenalty Kill
John Persson, , Brett RitchieJohn Persson, Nicklas JensenPetr Straka
Extra Defensemen
Normal PowerPlayPenalty Kill
James Melindy, Michael Brodzinski, Thomas VannelliJames MelindyMichael Brodzinski, Thomas Vannelli
Penalty Shots
, Ronalds Kenins, Brett Ritchie, Tommy Sestito, Nicklas Jensen
Goalie
#1 : , #2 : Linus Ullmark


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
Admirals20200000711-41010000046-21010000035-200.0007132000109111811854779796810118842728469111.11%14471.43%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Falcons321000008532110000034-11100000051440.66781422001091118118967797968101186817316321314.29%12283.33%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Bruins52200100181622020000057-232000100139450.50018314900109111811813077979681011814534599214214.29%26773.08%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Crunch4210001014122210000107522110000077060.750141832011091118118125779796810118943156902328.70%22672.73%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Heat21000001871110000006421000000123-130.75081523001091118118537797968101186911434010330.00%17382.35%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Phantoms3120000048-4110000003032020000018-720.3334711011091118118697797968101188023495013215.38%16381.25%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Baby Hawks20000011880100000105411000000134-130.75081321001091118118547797968101187820264210220.00%12466.67%11245248550.10%1412275051.35%703137950.98%1956131319526571097539
Monsters21100000770110000004221010000035-220.50071219001091118118557797968101185316284618422.22%9188.89%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Jayhawks22000000954110000003121100000064241.0009152400109111811844779796810118752023477114.29%90100.00%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Cougars523000001819-1312000001112-12110000077040.400182947001091118118118779796810118148451469529724.14%43979.07%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Oil Kings20200000610-41010000046-21010000024-200.0006101600109111811865779796810118551522401400.00%11372.73%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Sound Tigers32100000972110000003212110000065140.667915240010911181181007797968101189633445617529.41%11190.91%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Monarchs2110000078-11010000024-21100000054120.5007111800109111811839779796810118661947319222.22%14285.71%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Minnesota200000118801000000134-11000001054130.75081220001091118118717797968101185619224013323.08%10460.00%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Spiders31100010111012010001068-21100000052340.667111627001091118118857797968101189629406417317.65%20385.00%11245248550.10%1412275051.35%703137950.98%1956131319526571097539
Senators4110101015123200010108622110000076160.75015243900109111811812877979681011811831469219210.53%16381.25%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Manchots31200000910-11010000012-12110000088020.33391524001091118118927797968101188217436015213.33%14285.71%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Wolf Pack3200001015114100000106512200000096361.00015254000109111811813477979681011811626325618316.67%15566.67%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Sharks2010000158-31010000024-21000000134-110.250581300109111811853779796810118511924368112.50%11372.73%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Chiefs20100010660100000104311010000023-120.500691500109111811842779796810118602193371218.33%17476.47%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Marlies44000000217142200000012392200000094581.00021345500109111811812477979681011891185210914428.57%21290.48%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Comets220000001046110000005231100000052341.000101626001091118118697797968101184812203310220.00%10190.00%11245248550.10%1412275051.35%703137950.98%1956131319526571097539
Cabaret Lady Mary Ann430000102314922000000126621000010118381.00023426500109111811816377979681011813945289324416.67%12375.00%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
IceCaps220000001073110000004311100000064241.0001017270010911181184377979681011849112736900.00%10280.00%11245248550.10%1412275051.35%703137950.98%1956131319526571097539
Chill21000010972110000003211000001065141.000912210010911181186777979681011882162441700.00%12375.00%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Rocket4210001016124210000108532110000087160.75016284400109111811812077979681011813638698121419.05%26484.62%11245248550.10%1412275051.35%703137950.98%1956131319526571097539
Bears330000001156220000007251100000043161.00011203100109111811885779796810118561826511100.00%13192.31%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Caroline32000010151142100001010821100000053261.0001524390010911181188977979681011811825815917423.53%20385.00%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Las Vegas20000011770100000103211000000145-130.7507111800109111811873779796810118551626511616.25%7185.71%01245248550.10%1412275051.35%703137950.98%1956131319526571097539
Vs Conference4019140114113812513197801030575522112600111817011500.625138228366011091118118117577979681011811893205207741872613.90%2044179.90%21245248550.10%1412275051.35%703137950.98%1956131319526571097539
Since Last GM Reset82402301112531426252411911010911541223241211200134160140201120.68331451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539
Total82402301112531426252411911010911541223241211200134160140201120.68331451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539

Total For Players
Games PlayedPointsStreakGoalsAssistsPointsShots ForShots AgainstShots BlockedPenalty MinutesHitsEmpty Net GoalsShutouts
82112SOW1314516830244024646721255167702
All Games
GPWLOTWOTL SOWSOLGFGA
82402311125314262
Home Games
GPWLOTWOTL SOWSOLGFGA
4119111091154122
Visitor Games
GPWLOTWOTL SOWSOLGFGA
4121120134160140
Last 10 Games
WLOTWOTL SOWSOL
420130
Power Play AttempsPower Play GoalsPower Play %Penalty Kill AttempsPenalty Kill Goals AgainstPenalty Kill %Penalty Kill Goals For
4256816.00%4508980.22%5
Shots 1 PeriodShots 2 PeriodShots 3 PeriodShots 4+ PeriodGoals 1 PeriodGoals 2 PeriodGoals 3 PeriodGoals 4+ Period
7797968101181091118118
Face Offs
Won Offensive ZoneTotal OffensiveWon Offensive %Won Defensif ZoneTotal DefensiveWon Defensive %Won Neutral ZoneTotal NeutralWon Neutral %
1245248550.10%1412275051.35%703137950.98%
Puck Time
In Offensive ZoneControl In Offensive ZoneIn Defensive ZoneControl In Defensive ZoneIn Neutral ZoneControl In Neutral Zone
1956131319526571097539


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
2 - 2016-10-135Cougars1Thunder4WBoxScore
4 - 2016-10-1520Spiders5Thunder2LBoxScore
7 - 2016-10-1843Cabaret Lady Mary Ann1Thunder5WBoxScore
9 - 2016-10-2055Monsters2Thunder4WBoxScore
11 - 2016-10-2275Thunder4Senators2WBoxScore
14 - 2016-10-2587Thunder5Marlies3WBoxScore
16 - 2016-10-27102Thunder5Rocket3WBoxScore
18 - 2016-10-29114Thunder5Spiders2WBoxScore
19 - 2016-10-30127Thunder4Wolf Pack3WBoxScore
21 - 2016-11-01139Thunder2Sound Tigers3LBoxScore
23 - 2016-11-03154Bruins4Thunder3LBoxScore
25 - 2016-11-05166Spiders3Thunder4WXXBoxScore
27 - 2016-11-07182Thunder4Cabaret Lady Mary Ann3WXXBoxScore
30 - 2016-11-10198Sound Tigers2Thunder3WBoxScore
32 - 2016-11-12217Sharks4Thunder2LBoxScore
34 - 2016-11-14229Thunder4Sound Tigers2WBoxScore
35 - 2016-11-15230Thunder1Cougars6LBoxScore
37 - 2016-11-17253Thunder3Crunch2WBoxScore
39 - 2016-11-19265Thunder1Phantoms4LBoxScore
41 - 2016-11-21279Thunder4Las Vegas5LXXBoxScore
43 - 2016-11-23294Phantoms0Thunder3WBoxScore
45 - 2016-11-25305Falcons2Thunder3WBoxScore
47 - 2016-11-27325Thunder5Bruins1WBoxScore
49 - 2016-11-29332Thunder5Falcons1WBoxScore
51 - 2016-12-01351Thunder2Chiefs3LBoxScore
53 - 2016-12-03359Bears1Thunder4WBoxScore
54 - 2016-12-04371Thunder5Caroline3WBoxScore
58 - 2016-12-08399Comets2Thunder5WBoxScore
60 - 2016-12-10411Manchots2Thunder1LBoxScore
64 - 2016-12-14443Thunder2Heat3LXXBoxScore
66 - 2016-12-16458Thunder5Comets2WBoxScore
67 - 2016-12-17469Thunder2Oil Kings4LBoxScore
70 - 2016-12-20486Cougars4Thunder2LBoxScore
72 - 2016-12-22500Chiefs3Thunder4WXXBoxScore
73 - 2016-12-23512Thunder4Bears3WBoxScore
78 - 2016-12-28529Rocket1Thunder3WBoxScore
79 - 2016-12-29535Marlies2Thunder5WBoxScore
81 - 2016-12-31555Caroline4Thunder5WXXBoxScore
84 - 2017-01-03569IceCaps3Thunder4WBoxScore
86 - 2017-01-05580Las Vegas2Thunder3WXXBoxScore
88 - 2017-01-07601Thunder0Phantoms4LBoxScore
89 - 2017-01-08603Thunder4Manchots3WBoxScore
93 - 2017-01-12626Crunch0Thunder1WBoxScore
94 - 2017-01-13635Falcons2Thunder0LBoxScore
97 - 2017-01-16659Thunder5Monarchs4WBoxScore
98 - 2017-01-17671Thunder3Admirals5LBoxScore
100 - 2017-01-19684Thunder3Sharks4LXXBoxScore
102 - 2017-01-21697Thunder6Chill5WXXBoxScore
105 - 2017-01-24722Thunder3Baby Hawks4LXXBoxScore
107 - 2017-01-26731Thunder7Cabaret Lady Mary Ann5WBoxScore
112 - 2017-01-31752Bruins3Thunder2LBoxScore
114 - 2017-02-02760Senators3Thunder4WXBoxScore
116 - 2017-02-04776Admirals6Thunder4LBoxScore
119 - 2017-02-07797Monarchs4Thunder2LBoxScore
122 - 2017-02-10813Thunder5Minnesota4WXXBoxScore
123 - 2017-02-11825Thunder6IceCaps4WBoxScore
130 - 2017-02-18864Thunder6Jayhawks4WBoxScore
131 - 2017-02-19873Thunder3Monsters5LBoxScore
133 - 2017-02-21887Oil Kings6Thunder4LBoxScore
135 - 2017-02-23896Heat4Thunder6WBoxScore
139 - 2017-02-27920Senators3Thunder4WXXBoxScore
141 - 2017-03-01934Caroline4Thunder5WBoxScore
Trade Deadline --- Trades can’t be done after this day is simulated!
143 - 2017-03-03948Thunder4Manchots5LBoxScore
144 - 2017-03-04953Thunder4Crunch5LBoxScore
146 - 2017-03-06971Wolf Pack5Thunder6WXXBoxScore
149 - 2017-03-09993Minnesota4Thunder3LXXBoxScore
151 - 2017-03-111005Cabaret Lady Mary Ann5Thunder7WBoxScore
153 - 2017-03-131017Thunder5Wolf Pack3WBoxScore
154 - 2017-03-141024Thunder3Senators4LBoxScore
156 - 2017-03-161045Marlies1Thunder7WBoxScore
158 - 2017-03-181057Bears1Thunder3WBoxScore
161 - 2017-03-211080Chill2Thunder3WBoxScore
163 - 2017-03-231089Thunder4Bruins3WBoxScore
164 - 2017-03-241102Thunder6Cougars1WBoxScore
167 - 2017-03-271126Baby Hawks4Thunder5WXXBoxScore
170 - 2017-03-301141Cougars7Thunder5LBoxScore
172 - 2017-04-011160Rocket4Thunder5WXXBoxScore
173 - 2017-04-021168Jayhawks1Thunder3WBoxScore
175 - 2017-04-041187Thunder4Bruins5LXBoxScore
177 - 2017-04-061201Thunder4Marlies1WBoxScore
178 - 2017-04-071206Thunder3Rocket4LBoxScore
180 - 2017-04-091230Crunch5Thunder6WXXBoxScore



Arena Capacity - Ticket Price Attendance - %
Level 1Level 2
Arena Capacity20001000
Ticket Price3515
Attendance6217131271
Attendance PCT75.82%76.27%

Income
Home Games LeftAverage Attendance - %Average Income per GameYear to Date RevenueArena CapacityTeam Popularity
0 2279 - 75.97% 64,513$2,645,050$3000100

Expenses
Players Total SalariesPlayers Total Average SalariesCoaches Salaries
2,359,300$ 2,359,300$ 0$
Year To Date ExpensesSalary Cap Per DaysSalary Cap To Date
3,015,134$ 13,035$ 2,512,381$

Estimate
Estimated Season RevenueRemaining Season DaysExpenses Per DaysEstimated Season Expenses
0$ 0 15,797$ 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
201682402301112531426252411911010911541223241211200134160140208031451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539
Total Regular Season82402301112531426252411911010911541223241211200134160140208031451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539