Thunder

DG: Jean-François Moquin Morale : 73 Moyenne d'Équipe : 45
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Astuces sur les Filtres (Anglais seulement)
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
# Nom du Joueur 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
Rayé
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
MOYENNE D'ÉQUIPE100.0045485651654439394139395045353205745
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Linus Ullmark100.0047458981494850514565703532076530
Rayé
1Calvin Pickard100.0069458174726874746289703532065650
2Jake Paterson (R)100.0043434363434343434343433230020440
3Zachary Nagelvoort (R)100.0040404069404040404040403230020420
4Janne Juvonen (R)100.0037373766373737373737373230020400
5Timo Pielmeier100.0036383862373636383633333532020390
MOYENNE D'ÉQUIPE100.004541556946454747445149343103747
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dean Evason53807749787068CAN522500,000$


Astuces sur les Filtres (Anglais seulement)
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
# Nom du Joueur Nom de l'ÉquipePOS 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
Stats d'équipe Total ou en Moyenne137827444471829210641801444149621820012.56%5572044114.83619916050631815611382222332451.07%496000140.7094411717393843
Astuces sur les Filtres (Anglais seulement)
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
# Nom du Gardien Nom de l'ÉquipeGP 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
Stats d'équipe Total ou en Moyenne90532360.8963.08500319225724640300.862658282623


Astuces sur les Filtres (Anglais seulement)
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
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Ballotage Forcé Contrat StatusType Salaire Actuel Salaire RestantSalaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Adam GilmourThunder (Tam)C/RW211994-01-29Yes193 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm650,000$650,000$650,000$650,000$Lien
Adam PolasekThunder (Tam)D241991-07-12Yes190 Lbs6 ft3NoNo4Avec RestrictionPro & Farm525,000$525,000$525,000$525,000$Lien
Brett LernoutThunder (Tam)D201995-09-24Yes213 Lbs6 ft4NoNo4Contrat d'EntréePro & Farm667,000$667,000$667,000$667,000$Lien
Brett RitchieThunder (Tam)RW221993-07-01No220 Lbs6 ft3NoNo3Avec RestrictionPro & Farm818,000$818,000$818,000$Lien
Brody SutterThunder (Tam)C/RW241991-09-26Yes203 Lbs6 ft5NoNo3Avec RestrictionPro & Farm585,000$585,000$585,000$Lien
Calle AnderssonThunder (Tam)D211994-05-16Yes211 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm660,000$660,000$660,000$660,000$Lien
Calvin PickardThunder (Tam)G231992-04-15No200 Lbs6 ft1NoNo3Avec RestrictionPro & Farm810,000$810,000$810,000$Lien
Carter AshtonThunder (Tam)LW241991-04-01No215 Lbs6 ft3NoNo3Avec RestrictionPro & Farm1,100,000$1,100,000$1,100,000$Lien
Derek GrantThunder (Tam)C/LW251990-04-20No202 Lbs6 ft3NoNo1Avec RestrictionPro & Farm580,000$Lien
Jake PatersonThunder (Tam)G211994-05-03Yes176 Lbs6 ft0NoNo4Contrat d'EntréePro & Farm667,000$667,000$667,000$667,000$Lien
James MelindyThunder (Tam)D211993-12-11Yes187 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm675,000$675,000$675,000$675,000$Lien
Jamie ArnielThunder (Tam)C/RW251989-11-16No183 Lbs5 ft11NoNo3Avec RestrictionPro & Farm800,000$800,000$800,000$Lien
Janne JuvonenThunder (Tam)G211994-10-03Yes183 Lbs6 ft1NoNo4Contrat d'EntréePro & Farm525,000$525,000$525,000$525,000$Lien
John PerssonThunder (Tam)LW231992-05-18No209 Lbs6 ft2NoNo2Avec RestrictionPro & Farm610,000$610,000$Lien
Kasperi KapanenThunder (Tam)LW/RW191996-07-23No178 Lbs6 ft0NoNo4Contrat d'EntréePro & Farm925,000$925,000$925,000$925,000$Lien
Linus UllmarkThunder (Tam)G221993-07-31No212 Lbs6 ft4NoNo4Avec RestrictionPro & Farm792,000$792,000$792,000$792,000$Lien
Luca CaputiThunder (Tam)LW271988-10-01No200 Lbs6 ft3NoNo1Avec RestrictionPro & Farm630,000$Lien
Michael BrodzinskiThunder (Tam)D201995-05-28Yes190 Lbs5 ft11NoNo4Contrat d'EntréePro & Farm525,000$525,000$525,000$525,000$Lien
Mikael WikstrandThunder (Tam)D211993-11-05Yes183 Lbs6 ft1NoNo4Contrat d'EntréePro & Farm830,000$830,000$830,000$830,000$Lien
Nicklas JensenThunder (Tam)LW/RW221993-03-06No202 Lbs6 ft3NoNo1Avec RestrictionPro & Farm925,000$Lien
Nicolas DeschampsThunder (Tam)LW251990-01-06No173 Lbs6 ft0NoNo2Avec RestrictionPro & Farm726,000$726,000$Lien
Petr StrakaThunder (Tam)LW/RW231992-06-15No185 Lbs6 ft1NoNo3Avec RestrictionPro & Farm925,000$925,000$925,000$Lien
Rinat ValievThunder (Tam)D201995-05-11No214 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm743,000$743,000$743,000$743,000$Lien
Ronalds KeninsThunder (Tam)LW241991-02-28No201 Lbs6 ft0NoNo3Avec RestrictionPro & Farm718,000$718,000$718,000$Lien
Ryan MartindaleThunder (Tam)C231991-10-27Yes183 Lbs6 ft3NoNo4Avec RestrictionPro & Farm700,000$700,000$700,000$700,000$Lien
Samuel HenleyThunder (Tam)C/LW221993-07-25Yes220 Lbs6 ft0NoNo4Avec RestrictionPro & Farm590,000$590,000$590,000$590,000$Lien
Simon BertilssonThunder (Tam)D241991-04-19Yes196 Lbs6 ft0NoNo4Avec RestrictionPro & Farm700,000$700,000$700,000$700,000$Lien
Spencer MachacekThunder (Tam)RW261988-10-14No200 Lbs6 ft1NoNo1Avec RestrictionPro & Farm750,000$Lien
Thomas Di PauliThunder (Tam)C211994-04-29Yes188 Lbs5 ft11NoNo4Contrat d'EntréePro & Farm650,000$650,000$650,000$650,000$Lien
Thomas VannelliThunder (Tam)D201995-01-26Yes165 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm667,000$667,000$667,000$667,000$Lien
Timo PielmeierThunder (Tam)G261989-07-07No175 Lbs5 ft11NoNo2Avec RestrictionPro & Farm725,000$725,000$Lien
Tommy SestitoThunder (Tam)LW281987-09-28No228 Lbs6 ft5NoNo6Avec RestrictionPro & Farm750,000$750,000$750,000$750,000$750,000$750,000$Lien
Zachary NagelvoortThunder (Tam)G211994-01-30Yes190 Lbs6 ft2NoNo4Contrat d'EntréePro & Farm650,000$650,000$650,000$650,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3322.70196 Lbs6 ft23.30714,939$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ronalds KeninsSamuel HenleyBrett Ritchie40122
2Tommy SestitoDerek GrantNicklas Jensen30122
3Luca CaputiKasperi Kapanen20122
4John PerssonRyan MartindalePetr Straka10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett Lernout40122
2Thomas VannelliSimon Bertilsson30122
3James MelindyMichael Brodzinski20122
4James MelindyBrett Lernout10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Ronalds KeninsPetr Straka60122
2Tommy SestitoDerek GrantNicklas Jensen40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael BrodzinskiBrett Lernout60122
2Thomas VannelliSimon Bertilsson40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1John Persson60122
2Brett RitchieTommy Sestito40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Michael Brodzinski60122
2Thomas VannelliSimon Bertilsson40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Derek Grant60122Brett Lernout60122
2Kasperi Kapanen40122Thomas VannelliSimon Bertilsson40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Ryan MartindaleRonalds Kenins60122
2Samuel HenleyTommy Sestito40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brett Lernout60122
2Thomas VannelliSimon Bertilsson40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ronalds KeninsBrett RitchieMichael BrodzinskiSimon Bertilsson
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Ronalds KeninsSamuel HenleyBrett RitchieBrett Lernout
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
John Persson, , Brett RitchieJohn Persson, Nicklas JensenPetr Straka
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
James Melindy, Michael Brodzinski, Thomas VannelliJames MelindyMichael Brodzinski, Thomas Vannelli
Tirs de Pénalité
, Ronalds Kenins, Brett Ritchie, Tommy Sestito, Nicklas Jensen
Gardien
#1 : , #2 : Linus Ullmark


Astuces sur les Filtres (Anglais seulement)
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
LigueDomicileVisiteur
VS Équipe 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 Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82112SOW1314516830244024646721255167702
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
82402311125314262
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4119111091154122
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4121120134160140
Derniers 10 Matchs
WLOTWOTL SOWSOL
420130
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4256816.00%4508980.22%5
Tirs en 1e PériodeTirs en 2e PériodeTirs en 3e PériodeTirs en 4e PériodeButs en 1e PériodeButs en 2e PériodeButs en 3e PériodeButs en 4e Période
7797968101181091118118
Mises en Jeu
Gagnées en Zone OffensiveTotal en Zone Offensive% Gagnées en Zone Offensive Gagnées en Zone DéfensiveTotal en Zone Défensive% Gagnées en Zone DéfensiveGagnées en Zone NeutreTotal en Zone Neutre% Gagnées en Zone Neutre
1245248550.10%1412275051.35%703137950.98%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1956131319526571097539


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
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
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
2 - 2016-10-135Cougars1Thunder4WSommaire du Match
4 - 2016-10-1520Spiders5Thunder2LSommaire du Match
7 - 2016-10-1843Cabaret Lady Mary Ann1Thunder5WSommaire du Match
9 - 2016-10-2055Monsters2Thunder4WSommaire du Match
11 - 2016-10-2275Thunder4Senators2WSommaire du Match
14 - 2016-10-2587Thunder5Marlies3WSommaire du Match
16 - 2016-10-27102Thunder5Rocket3WSommaire du Match
18 - 2016-10-29114Thunder5Spiders2WSommaire du Match
19 - 2016-10-30127Thunder4Wolf Pack3WSommaire du Match
21 - 2016-11-01139Thunder2Sound Tigers3LSommaire du Match
23 - 2016-11-03154Bruins4Thunder3LSommaire du Match
25 - 2016-11-05166Spiders3Thunder4WXXSommaire du Match
27 - 2016-11-07182Thunder4Cabaret Lady Mary Ann3WXXSommaire du Match
30 - 2016-11-10198Sound Tigers2Thunder3WSommaire du Match
32 - 2016-11-12217Sharks4Thunder2LSommaire du Match
34 - 2016-11-14229Thunder4Sound Tigers2WSommaire du Match
35 - 2016-11-15230Thunder1Cougars6LSommaire du Match
37 - 2016-11-17253Thunder3Crunch2WSommaire du Match
39 - 2016-11-19265Thunder1Phantoms4LSommaire du Match
41 - 2016-11-21279Thunder4Las Vegas5LXXSommaire du Match
43 - 2016-11-23294Phantoms0Thunder3WSommaire du Match
45 - 2016-11-25305Falcons2Thunder3WSommaire du Match
47 - 2016-11-27325Thunder5Bruins1WSommaire du Match
49 - 2016-11-29332Thunder5Falcons1WSommaire du Match
51 - 2016-12-01351Thunder2Chiefs3LSommaire du Match
53 - 2016-12-03359Bears1Thunder4WSommaire du Match
54 - 2016-12-04371Thunder5Caroline3WSommaire du Match
58 - 2016-12-08399Comets2Thunder5WSommaire du Match
60 - 2016-12-10411Manchots2Thunder1LSommaire du Match
64 - 2016-12-14443Thunder2Heat3LXXSommaire du Match
66 - 2016-12-16458Thunder5Comets2WSommaire du Match
67 - 2016-12-17469Thunder2Oil Kings4LSommaire du Match
70 - 2016-12-20486Cougars4Thunder2LSommaire du Match
72 - 2016-12-22500Chiefs3Thunder4WXXSommaire du Match
73 - 2016-12-23512Thunder4Bears3WSommaire du Match
78 - 2016-12-28529Rocket1Thunder3WSommaire du Match
79 - 2016-12-29535Marlies2Thunder5WSommaire du Match
81 - 2016-12-31555Caroline4Thunder5WXXSommaire du Match
84 - 2017-01-03569IceCaps3Thunder4WSommaire du Match
86 - 2017-01-05580Las Vegas2Thunder3WXXSommaire du Match
88 - 2017-01-07601Thunder0Phantoms4LSommaire du Match
89 - 2017-01-08603Thunder4Manchots3WSommaire du Match
93 - 2017-01-12626Crunch0Thunder1WSommaire du Match
94 - 2017-01-13635Falcons2Thunder0LSommaire du Match
97 - 2017-01-16659Thunder5Monarchs4WSommaire du Match
98 - 2017-01-17671Thunder3Admirals5LSommaire du Match
100 - 2017-01-19684Thunder3Sharks4LXXSommaire du Match
102 - 2017-01-21697Thunder6Chill5WXXSommaire du Match
105 - 2017-01-24722Thunder3Baby Hawks4LXXSommaire du Match
107 - 2017-01-26731Thunder7Cabaret Lady Mary Ann5WSommaire du Match
112 - 2017-01-31752Bruins3Thunder2LSommaire du Match
114 - 2017-02-02760Senators3Thunder4WXSommaire du Match
116 - 2017-02-04776Admirals6Thunder4LSommaire du Match
119 - 2017-02-07797Monarchs4Thunder2LSommaire du Match
122 - 2017-02-10813Thunder5Minnesota4WXXSommaire du Match
123 - 2017-02-11825Thunder6IceCaps4WSommaire du Match
130 - 2017-02-18864Thunder6Jayhawks4WSommaire du Match
131 - 2017-02-19873Thunder3Monsters5LSommaire du Match
133 - 2017-02-21887Oil Kings6Thunder4LSommaire du Match
135 - 2017-02-23896Heat4Thunder6WSommaire du Match
139 - 2017-02-27920Senators3Thunder4WXXSommaire du Match
141 - 2017-03-01934Caroline4Thunder5WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2017-03-03948Thunder4Manchots5LSommaire du Match
144 - 2017-03-04953Thunder4Crunch5LSommaire du Match
146 - 2017-03-06971Wolf Pack5Thunder6WXXSommaire du Match
149 - 2017-03-09993Minnesota4Thunder3LXXSommaire du Match
151 - 2017-03-111005Cabaret Lady Mary Ann5Thunder7WSommaire du Match
153 - 2017-03-131017Thunder5Wolf Pack3WSommaire du Match
154 - 2017-03-141024Thunder3Senators4LSommaire du Match
156 - 2017-03-161045Marlies1Thunder7WSommaire du Match
158 - 2017-03-181057Bears1Thunder3WSommaire du Match
161 - 2017-03-211080Chill2Thunder3WSommaire du Match
163 - 2017-03-231089Thunder4Bruins3WSommaire du Match
164 - 2017-03-241102Thunder6Cougars1WSommaire du Match
167 - 2017-03-271126Baby Hawks4Thunder5WXXSommaire du Match
170 - 2017-03-301141Cougars7Thunder5LSommaire du Match
172 - 2017-04-011160Rocket4Thunder5WXXSommaire du Match
173 - 2017-04-021168Jayhawks1Thunder3WSommaire du Match
175 - 2017-04-041187Thunder4Bruins5LXSommaire du Match
177 - 2017-04-061201Thunder4Marlies1WSommaire du Match
178 - 2017-04-071206Thunder3Rocket4LSommaire du Match
180 - 2017-04-091230Crunch5Thunder6WXXSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance6217131271
Assistance PCT75.82%76.27%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2279 - 75.97% 64,513$2,645,050$3000100

Dépenses
Salaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,359,300$ 2,359,300$ 0$
Dépenses Annuelles à Ce JourCap Salarial Par JourCap salarial à ce jour
3,015,134$ 13,035$ 2,512,381$

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 15,797$ 0$




LigueDomicileVisiteur
Année 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
Saison Régulière
201682402301112531426252411911010911541223241211200134160140208031451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539
Total Saison Régulière82402301112531426252411911010911541223241211200134160140208031451683002109111811824407797968101182464672125516774256816.00%4508980.22%51245248550.10%1412275051.35%703137950.98%1956131319526571097539