Thunder

GP: 82 | W: 46 | L: 28 | OTL: 8 | P: 100
GF: 302 | GA: 259 | PP%: 20.16% | PK%: 78.90%
DG: Jean-François Moquin | Morale : 50 | Moyenne d'Équipe : 46
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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
1Jacob JosefsonX100.00543589716761475081505076555347050580
2Matt MoulsonXX100.00493591667061455635526058456354050570
3Kasperi KapanenXX100.00613592766057425235426259454137050550
4Samuel Blais (R)X100.00543582655652365235525255483230050520
5Tage Thompson (R)XX100.00533587637253424935485054483532050520
6Ronalds KeninsX100.00533581676949324649454763463533050510
7Samuel Henley (R)XX100.00513594677442333735334065473532050480
8Nicklas JensenXX100.00573594687546333335333356474138050470
9Brody SutterX100.00483593637246313268323264433532050460
10Petr StrakaXX100.00413592665840293235323159453532050440
11Ryan Martindale (R)X100.00394343435837373943393943413230050420
12Brendan Guhle (R)X100.00523582696462374235523268483734050550
13Brett Lernout (R)X100.00573586607161363535373270483936050540
14Anthony BitettoX100.00625076606963434635454755484136050530
15Rinat Valiev (R)X100.00503573637148353135303264483734050500
16Jacob LarssonX100.00453582646250333035293161473532050490
17Thomas Vannelli (R)X100.00414545454939394145414145433230050430
18James Melindy (R)X100.00394343436037373943393943413230050420
Rayé
1Brett RitchieX100.00745081637560685738506352484536050570
2Tommy SestitoX100.00625030638245344135483354475046050490
3Carter AshtonXX100.00504383647543313349363154454036050460
4Grayson Downing (R)X100.00454545456645454545454545453230050460
5Adam Gilmour (R)XX100.00364040406635353640363640383230050400
6Thomas Di Pauli (R)XX100.00364040405935353640363640383230050390
7Avery Peterson (R)X100.00353737377535353537353537363230050390
8Spencer MachacekX100.00328931416929353135313142454036050380
9Jamie ArnielXX100.00309327325629353135313133453532050350
10Ryan Pulock (R)X100.00663589757065555835595769484236050620
11Simon Bertilsson (R)X100.00394343436337373943393943413230050420
12Michael Prapavessis (R)X100.00404040405840404040404040403230050420
13Calle Andersson (R)X100.00364040406935353640363640383230050410
14Adam Polasek (R)X100.00333737376233333337333337353230050380
15Michael Brodzinski (R)X100.00333737376033333337333337353230050380
16Mikael Wikstrand (R)X100.00333737375733333337333337353230050380
MOYENNE D'ÉQUIPE100.0047426455664538404040405244373405047
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
1Jonas Gunnarsson (R)100.0045454573454545454545453230050460
2Jake Paterson (R)100.0041434163403939393939383230050420
Rayé
1Linus Ullmark (R)100.0050457085494850484565454036050530
2Zachary Nagelvoort (R)100.0038403869373636363636353230050400
3Janne Juvonen (R)100.0035373566343333333333333230050380
MOYENNE D'ÉQUIPE100.004242467141404140404439343105044
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Matt MoulsonThunder (Tam)LW/RW684253953922060702769619115.22%12128818.9471623502390000115242.70%8900021.48050008611
2Lee StempniakTampa BayRW5742438542260681152417318417.43%1394816.640885450003514146.30%5400021.79050006104
3Jacob JosefsonThunder (Tam)C4824426646160431521983511412.12%1988718.4802242711271541366.93%114600001.4912000664
4Samuel BlaisThunder (Tam)LW82313566-324099942246915113.84%13118614.47101828612590003353030.77%7800001.11020002211
5Brendan GuhleThunder (Tam)D6810546412540878310828709.26%69151522.289182769255000088300.00%000000.8400000322
6Anthony BitettoThunder (Tam)D68839471469151284710333637.77%55142420.9551419582391011168000.00%000000.6622012122
7Kasperi KapanenThunder (Tam)LW/RW692221431020088731976314911.17%686712.5871219592680007923133.90%5900010.9912000361
8Rinat ValievThunder (Tam)D6813274015360544789346614.61%81134919.8410818462220000132200.00%000000.5900000041
9Sergey KalininTampa BayC/LW/RW4315213671155197148419310.14%1077117.947815381530002483065.48%59100010.9314001512
10Brett LernoutThunder (Tam)D821223351346010352103406911.65%92178121.729615572660000102220.00%000000.3900000112
11Tage ThompsonThunder (Tam)C/RW68171734-122005690191531118.90%14118817.483111437285000177142.18%29400000.5700000103
12Jacob LarssonThunder (Tam)D829223114280635083305410.84%123146417.8612331880002211100.00%000000.4200000140
13Nicklas JensenThunder (Tam)LW/RW82915241260746210137648.91%8108913.2800094301121881037.10%6200000.4400000012
14Tommy SestitoThunder (Tam)LW61121224-17138301676684215214.29%1091515.0106691210000374052.58%9700000.5211321004
15Ronalds KeninsThunder (Tam)LW68714218100355510235856.86%156719.8802252900031002060.81%7400000.6300000111
16Samuel HenleyThunder (Tam)C/LW6871320-580339511629716.03%1178811.59000120004921047.29%86700000.5100000110
17Brody SutterThunder (Tam)C8221618130020997314602.74%77509.15101838000040063.72%84900000.4800000010
18Ryan PulockThunder (Tam)D1649135120282031131412.90%1535121.972021222000150010.00%000000.7400000000
19James MelindyThunder (Tam)D791891197151189163176.25%37133416.891123550000173000.00%000000.1300102000
20John MitchellTampa BayC/LW122684201624259288.00%423419.55000030000411069.18%27900000.6812000001
21Petr StrakaThunder (Tam)LW/RW13167-600015192135.26%216112.41011180001100038.46%1300000.8700000000
22Adam GilmourThunder (Tam)C/RW13123-420141012678.33%215311.79112536000010045.66%17300000.3900000001
23Calle AnderssonThunder (Tam)D13123-64021442425.00%423017.71101334000013100.00%000000.2600000000
24Thomas Di PauliThunder (Tam)C/LW13123-44013814297.14%116112.44022635000050041.18%3400000.3700000000
25Adam PolasekThunder (Tam)D13022-7401031320.00%422917.67000033000017000.00%000000.1700000000
26Brett RitchieThunder (Tam)RW11011201031133.33%01616.0210114000000066.67%300001.2500000000
27Spencer MachacekThunder (Tam)RW13011-22011411320.00%21168.9800000000000054.55%1100000.1700000000
28Ryan MartindaleThunder (Tam)C13101-32051283412.50%217613.60000020000230044.44%17100000.1100000000
Stats d'équipe Total ou en Moyenne136329550580018668565146614562581778174811.43%6312205316.18751362115782825224371866441157.24%494400060.73725436394852
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
1Linus UllmarkThunder (Tam)56371440.8922.7832412715013860210.53813560530
2Jonas GunnarssonThunder (Tam)3191330.8713.72158241987570100.733152668100
3Jake PatersonThunder (Tam)10000.9441.5838001180000.0000013000
Stats d'équipe Total ou en Moyenne88462770.8853.0748626824921610310.643288281630


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 Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Adam GilmourThunder (Tam)C/RW231994-01-29Yes193 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Adam PolasekThunder (Tam)D261991-07-12Yes190 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Anthony BitettoThunder (Tam)D271990-07-15No210 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm605,000$60,500$0$NoLien
Avery PetersonThunder (Tam)C221995-06-20Yes215 Lbs6 ft3NoNoNo3Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Brendan GuhleThunder (Tam)D201997-07-29Yes196 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm667,000$66,700$0$NoLien
Brett LernoutThunder (Tam)D221995-09-24Yes214 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Brett RitchieThunder (Tam)RW241993-07-01No217 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm818,000$81,800$0$NoLien
Brody SutterThunder (Tam)C261991-09-26No203 Lbs6 ft5NoNoNo1Avec RestrictionPro & Farm585,000$58,500$0$NoLien
Calle AnderssonThunder (Tam)D231994-05-16Yes211 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm660,000$66,000$0$NoLien
Carter AshtonThunder (Tam)LW/RW261991-04-01No215 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm1,100,000$110,000$0$NoLien
Grayson DowningThunder (Tam)C251992-04-18Yes195 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Jacob JosefsonThunder (Tam)C261991-03-02No196 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm1,100,000$110,000$0$NoLien
Jacob LarssonThunder (Tam)D201997-04-29No191 Lbs6 ft2NoNoNo3Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Jake PatersonThunder (Tam)G231994-05-03Yes176 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
James MelindyThunder (Tam)D231993-12-11Yes187 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm675,000$67,500$0$NoLien
Jamie ArnielThunder (Tam)C/RW271989-11-16No183 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm800,000$80,000$0$NoLien
Janne JuvonenThunder (Tam)G231994-10-03Yes183 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Jonas GunnarssonThunder (Tam)G251992-03-31Yes198 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm825,000$82,500$0$NoLien
Kasperi KapanenThunder (Tam)LW/RW211996-07-23No187 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Linus UllmarkThunder (Tam)G241993-07-31Yes221 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm792,000$79,200$0$NoLien
Matt MoulsonThunder (Tam)LW/RW331983-11-01No203 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm2,074,000$207,400$0$NoLien
Michael BrodzinskiThunder (Tam)D221995-05-28Yes190 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm525,000$52,500$0$NoLien
Michael PrapavessisThunder (Tam)D211996-01-07Yes185 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm650,000$65,000$0$NoLien
Mikael WikstrandThunder (Tam)D231993-11-05Yes183 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm830,000$83,000$0$NoLien
Nicklas JensenThunder (Tam)LW/RW241993-03-06No216 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm950,000$95,000$0$NoLien
Petr StrakaThunder (Tam)LW/RW251992-06-15No185 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Rinat ValievThunder (Tam)D221995-05-11Yes215 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm743,000$74,300$0$NoLien
Ronalds KeninsThunder (Tam)LW261991-02-28No201 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm718,000$71,800$0$NoLien
Ryan MartindaleThunder (Tam)C251991-10-27Yes183 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Ryan PulockThunder (Tam)D221994-10-06Yes214 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm925,000$92,500$0$NoLien
Samuel BlaisThunder (Tam)LW211996-06-17Yes181 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm525,000$52,500$0$NoLien
Samuel HenleyThunder (Tam)C/LW241993-07-25Yes210 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm590,000$59,000$0$NoLien
Simon BertilssonThunder (Tam)D261991-04-19Yes196 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm700,000$70,000$0$NoLien
Spencer MachacekThunder (Tam)RW281988-10-14No200 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm775,000$77,500$0$NoLien
Tage ThompsonThunder (Tam)C/RW191997-10-30Yes205 Lbs6 ft5NoNoNo4Contrat d'EntréePro & Farm925,000$92,500$0$NoLien
Thomas Di PauliThunder (Tam)C/LW231994-04-29Yes188 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Thomas VannelliThunder (Tam)D221995-01-26Yes165 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm667,000$66,700$0$NoLien
Tommy SestitoThunder (Tam)LW301987-09-28No228 Lbs6 ft5NoNoNo4Sans RestrictionPro & Farm750,000$75,000$0$NoLien
Zachary NagelvoortThunder (Tam)G231994-01-30Yes190 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm650,000$65,000$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3923.97198 Lbs6 ft22.18768,154$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt Moulson40122
2Tage Thompson30122
3Samuel BlaisSamuel HenleyNicklas Jensen20122
4Ronalds KeninsBrody SutterKasperi Kapanen10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brendan GuhleBrett Lernout40122
2Anthony BitettoRinat Valiev30122
3Jacob LarssonJames Melindy20122
4Brendan GuhleBrett Lernout10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Matt MoulsonTage ThompsonKasperi Kapanen60122
2Samuel BlaisTage Thompson40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Brendan GuhleBrett Lernout60122
2Anthony BitettoRinat Valiev40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Nicklas Jensen60122
2Samuel HenleyKasperi Kapanen40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jacob LarssonJames Melindy60122
2Anthony BitettoRinat Valiev40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Brendan GuhleJames Melindy60122
240122Anthony BitettoRinat Valiev40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Brody Sutter60122
2Samuel HenleySamuel Blais40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1James MelindyJacob Larsson60122
2Anthony BitettoRinat Valiev40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt MoulsonBrendan GuhleBrett Lernout
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Matt MoulsonBrendan GuhleBrett Lernout
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Samuel Blais, Ronalds Kenins, Samuel BlaisRonalds Kenins
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jacob Larsson, James Melindy, Anthony BitettoJacob LarssonJames Melindy, Anthony Bitetto
Tirs de Pénalité
, , Matt Moulson, Kasperi Kapanen,
Gardien
#1 : , #2 : Jonas Gunnarsson


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
1Admirals21001000532110000002111000100032141.00059140013997611072971873774546519165010330.00%80100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
2Baby Hawks20200000510-51010000035-21010000025-300.000591400139976110509718737745459131838700.00%9366.67%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
3Bears3120000012120211000008711010000045-120.3331221330013997611097971873774548028326118422.22%11554.55%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
4Bruins412001001215-3210001007612020000059-430.37512203200139976110115971873774548437189218633.33%9366.67%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
5Cabaret Lady Mary Ann42101000211472200000013672010100088060.750213758001399761101879718737745412827269629620.69%13653.85%11358259452.35%1225232152.78%773140255.14%2058141218096231103568
6Caroline32100000121022110000079-21100000051440.66712233500139976110108971873774547622224515426.67%10190.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
7Chiefs2110000045-11010000025-31100000020220.5004812011399761103197187377454461510271218.33%5260.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
8Chill22000000954110000004221100000053241.000916250013997611048971873774543512163210440.00%8275.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
9Comets220000001037110000002021100000083541.000101727011399761107697187377454511116308112.50%8187.50%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
10Cougars412000011317-420100001710-32110000067-130.375132538001399761101099718737745412840306920420.00%14471.43%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
11Crunch430000012213922000000116521000001117470.87522406200139976110185971873774549220317521523.81%13469.23%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
12Heat22000000835110000004311100000040441.000815230113997611077971873774543712273612216.67%11190.91%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
13Jayhawks2010001067-1100000104311010000024-220.5006915101399761106297187377454631910431119.09%5260.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
14Las Vegas201010009901010000034-11000100065120.50091625001399761107597187377454521214436233.33%70100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
15Manchots321000001147110000003032110000084440.6671116270213997611070971873774545520395211436.36%17194.12%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
16Marlies42200000911-2220000006332020000038-540.500917260013997611089971873774541203636931417.14%15286.67%11358259452.35%1225232152.78%773140255.14%2058141218096231103568
17Minnesota2020000047-31010000024-21010000023-100.0004812001399761106497187377454501921379111.11%7271.43%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
18Monarchs201000011013-31010000057-21000000156-110.2501017270013997611059971873774546115263010330.00%13469.23%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
19Monsters3110010089-1211000007701000010012-130.50081523001399761107597187377454802232498225.00%16287.50%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
20Monsters21000001862110000006331000000123-130.7508132100139976110609718737745452181241700.00%60100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
21Oceanics20200000710-31010000035-21010000045-100.000711180013997611056971873774547219243812433.33%7357.14%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
22Oil Kings22000000835110000004131100000042241.0008142200139976110739718737745426984515213.33%40100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
23Phantoms321000001266110000007072110000056-140.6671221330113997611098971873774545816334016212.50%90100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
24Rocket43000010161152200000010732100001064281.00016254100139976110127971873774549833486712216.67%22481.82%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
25Senators42100001121202110000023-121000001109150.62512213300139976110115971873774541052722751815.56%11463.64%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
26Sharks22000000972110000005411100000043141.000915240013997611010197187377454842126397228.57%90100.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
27Sound Tigers33000000133101100000030322000000103761.00013243702139976110103971873774545924295910220.00%12191.67%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
28Spiders30300000716-920200000511-61010000025-300.000713200013997611083971873774541012722521200.00%10370.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
29Stars211000006511010000023-11100000042220.50061218001399761105297187377454351425316350.00%5180.00%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
Total8241280322630225943412414001111521262641171403115150133171000.61030252983118139976110263997187377454219463972615563777620.16%3086578.90%21358259452.35%1225232152.78%773140255.14%2058141218096231103568
31Wolf Pack3200000114104110000005142100000199050.833142236001399761101229718737745414232377113430.77%14471.43%01358259452.35%1225232152.78%773140255.14%2058141218096231103568
_Since Last GM Reset8241280322630225943412414001111521262641171403115150133171000.61030252983118139976110263997187377454219463972615563777620.16%3086578.90%21358259452.35%1225232152.78%773140255.14%2058141218096231103568
_Vs Conference432116012031501361421137001007257152289011037879-1490.5701502584080513997611013039718737745412013554088331874222.46%1693479.88%11358259452.35%1225232152.78%773140255.14%2058141218096231103568

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82100L230252983126392194639726155618
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8241283226302259
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4124140111152126
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4117143115150133
Derniers 10 Matchs
WLOTWOTL SOWSOL
630001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3777620.16%3086578.90%2
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
97187377454139976110
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
1358259452.35%1225232152.78%773140255.14%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2058141218096231103568


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
4 - 2018-10-0621Cabaret Lady Mary Ann2Thunder7WSommaire du Match
9 - 2018-10-1153Comets0Thunder2WSommaire du Match
11 - 2018-10-1363Monsters5Thunder4LSommaire du Match
14 - 2018-10-1682Caroline5Thunder2LSommaire du Match
16 - 2018-10-1893Cougars4Thunder3LXXSommaire du Match
18 - 2018-10-20110Thunder2Minnesota3LSommaire du Match
19 - 2018-10-21115Thunder2Baby Hawks5LSommaire du Match
22 - 2018-10-24132Thunder2Monsters3LXXSommaire du Match
24 - 2018-10-26144Thunder6Las Vegas5WXSommaire du Match
25 - 2018-10-27157Thunder2Jayhawks4LSommaire du Match
28 - 2018-10-30172Spiders4Thunder2LSommaire du Match
30 - 2018-11-01185Chill2Thunder4WSommaire du Match
32 - 2018-11-03196Thunder3Rocket2WXXSommaire du Match
33 - 2018-11-04207Thunder5Senators3WSommaire du Match
35 - 2018-11-06220Oil Kings1Thunder4WSommaire du Match
37 - 2018-11-08232Sound Tigers0Thunder3WSommaire du Match
39 - 2018-11-10247Senators1Thunder2WSommaire du Match
42 - 2018-11-13264Thunder8Crunch3WSommaire du Match
44 - 2018-11-15279Thunder5Manchots0WSommaire du Match
46 - 2018-11-17293Thunder4Phantoms2WSommaire du Match
48 - 2018-11-19314Thunder5Chill3WSommaire du Match
50 - 2018-11-21325Cabaret Lady Mary Ann4Thunder6WSommaire du Match
52 - 2018-11-23341Baby Hawks5Thunder3LSommaire du Match
54 - 2018-11-25359Spiders7Thunder3LSommaire du Match
56 - 2018-11-27370Admirals1Thunder2WSommaire du Match
58 - 2018-11-29385Crunch3Thunder5WSommaire du Match
60 - 2018-12-01400Thunder5Cabaret Lady Mary Ann4WXSommaire du Match
62 - 2018-12-03413Thunder2Spiders5LSommaire du Match
63 - 2018-12-04422Thunder4Cougars3WSommaire du Match
65 - 2018-12-06434Bruins3Thunder2LXSommaire du Match
67 - 2018-12-08449Monsters3Thunder6WSommaire du Match
69 - 2018-12-10463Wolf Pack1Thunder5WSommaire du Match
72 - 2018-12-13482Marlies1Thunder2WSommaire du Match
75 - 2018-12-16510Thunder4Oceanics5LSommaire du Match
77 - 2018-12-18526Thunder8Comets3WSommaire du Match
79 - 2018-12-20537Thunder4Heat0WSommaire du Match
81 - 2018-12-22558Thunder4Oil Kings2WSommaire du Match
86 - 2018-12-27571Phantoms0Thunder7WSommaire du Match
88 - 2018-12-29590Rocket4Thunder6WSommaire du Match
90 - 2018-12-31611Thunder3Admirals2WXSommaire du Match
93 - 2019-01-03628Thunder5Monarchs6LXXSommaire du Match
95 - 2019-01-05644Thunder4Sharks3WSommaire du Match
98 - 2019-01-08663Monsters2Thunder3WSommaire du Match
100 - 2019-01-10676Caroline4Thunder5WSommaire du Match
102 - 2019-01-12689Thunder3Crunch4LXXSommaire du Match
103 - 2019-01-13703Thunder5Sound Tigers3WSommaire du Match
105 - 2019-01-15719Thunder4Stars2WSommaire du Match
107 - 2019-01-17729Marlies2Thunder4WSommaire du Match
109 - 2019-01-19746Sharks4Thunder5WSommaire du Match
120 - 2019-01-30776Thunder3Manchots4LSommaire du Match
122 - 2019-02-01783Thunder5Sound Tigers0WSommaire du Match
123 - 2019-02-02796Thunder3Wolf Pack2WSommaire du Match
126 - 2019-02-05816Las Vegas4Thunder3LSommaire du Match
128 - 2019-02-07831Chiefs5Thunder2LSommaire du Match
130 - 2019-02-09848Manchots0Thunder3WSommaire du Match
131 - 2019-02-10858Thunder3Cabaret Lady Mary Ann4LSommaire du Match
133 - 2019-02-12868Heat3Thunder4WSommaire du Match
135 - 2019-02-14880Stars3Thunder2LSommaire du Match
137 - 2019-02-16897Rocket3Thunder4WSommaire du Match
139 - 2019-02-18911Thunder1Monsters2LXSommaire du Match
140 - 2019-02-19918Thunder1Phantoms4LSommaire du Match
142 - 2019-02-21935Crunch3Thunder6WSommaire du Match
146 - 2019-02-25964Monarchs7Thunder5LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
148 - 2019-02-27981Thunder6Wolf Pack7LXXSommaire du Match
149 - 2019-02-28984Thunder3Bruins5LSommaire du Match
151 - 2019-03-021004Senators2Thunder0LSommaire du Match
154 - 2019-03-051023Oceanics5Thunder3LSommaire du Match
156 - 2019-03-071037Minnesota4Thunder2LSommaire du Match
158 - 2019-03-091052Cougars6Thunder4LSommaire du Match
160 - 2019-03-111065Thunder2Marlies3LSommaire du Match
163 - 2019-03-141087Thunder2Cougars4LSommaire du Match
165 - 2019-03-161106Bears4Thunder3LSommaire du Match
167 - 2019-03-181118Jayhawks3Thunder4WXXSommaire du Match
169 - 2019-03-201133Thunder4Bears5LSommaire du Match
170 - 2019-03-211138Thunder5Caroline1WSommaire du Match
172 - 2019-03-231159Thunder2Chiefs0WSommaire du Match
174 - 2019-03-251172Bruins3Thunder5WSommaire du Match
179 - 2019-03-301207Bears3Thunder5WSommaire du Match
181 - 2019-04-011224Thunder5Senators6LXXSommaire du Match
182 - 2019-04-021232Thunder3Rocket2WSommaire du Match
184 - 2019-04-041243Thunder1Marlies5LSommaire du Match
186 - 2019-04-061257Thunder2Bruins4LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance62,27430,472
Assistance PCT75.94%74.32%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2262 - 75.40% 64,309$2,636,670$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,452,546$ 2,995,800$ 2,995,800$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
16,020$ 3,452,546$ 39 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 16,020$ 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
201882412803226302259434124140011115212626411714031151501331710030252983118139976110263997187377454219463972615563777620.16%3086578.90%21358259452.35%1225232152.78%773140255.14%2058141218096231103568
Total Saison Régulière82412803226302259434124140011115212626411714031151501331710030252983118139976110263997187377454219463972615563777620.16%3086578.90%21358259452.35%1225232152.78%773140255.14%2058141218096231103568