Thunder

GP: 82 | W: 21 | L: 52 | OTL: 9 | P: 51
GF: 182 | GA: 305 | PP%: 19.28% | PK%: 78.61%
DG: Jean-François Moquin | Morale : 50 | Moyenne d'Équipe : 52
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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 SPÂgeContratSalaire Moyen
1Tage ThompsonXX100.00796887787963636343586265625252050620212925,000$
2Anthony PelusoX100.00838474638656585050464571446464050560301875,000$
3Thomas Di PauliXX100.00726782656757575771515861554444050560252715,000$
4Jamie McGinnX100.006243846571575255355060505464550505403141,463,333$
5Tanner FritzX100.00463587706357364750464759473734050500284825,000$
6Shane PrinceXX100.00454380616451344762474752464136050480261560,000$
7Samuel Henley (R)XX100.00463592657436293335313665453532050440262690,000$
8Nicklas JensenXX100.00513592667540293135313156454138050430261750,000$
9Grayson Downing (R)X100.00414545456639394145414145433230050420272650,000$
10Adam Gilmour (R)XX100.00324040406631313240323240363230050360252715,000$
11Avery Peterson (R)X100.00323737377531313237323237343230050360241525,000$
12Kevan MillerX100.007061736169676145354939884752440506103143,566,667$
13Rasmus SandinX100.00774388806764636425594862254646050610193894,167$
14Dylan Samberg (R)X100.00605881638056684725553155335454050550204925,000$
15Nikita NesterovX100.00593578716151404335434363454037050520261560,000$
16Brady AustinX100.00463574577943292835272973453532050490263850,000$
Rayé
1Brett RitchieX100.00956477778156646233595757256566050600264850,000$
2Joel Kiviranta (R)XX100.00804388805957716325505954254545050570234925,000$
3Freddie HamiltonXXX100.00633587626746334046374259464541050470272750,000$
4Austin Carroll (R)X100.00323737377531313237323237343230050360251525,000$
5Brett LernoutX100.00817482648065734625323967375555050590243750,000$
6Urho VaakanainenX100.00756989786959634725374260404444050570203925,000$
7Michael PrapavessisX100.00787097657050524325314061384444050540232650,000$
MOYENNE D'ÉQUIPE100.0061507663715148463842435841454305051
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
1Louis Domingue100.0057586083575152606057875959050590
2Jonas Gunnarsson (R)100.0042454473424141414141393230050440
Rayé
1Jeremy Swayman (R)100.0062746970596358615961615858050610
2Calvin Pickard100.0053587177545660575755305757050580
MOYENNE D'ÉQUIPE100.005459617653535355545454525105056
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'ÉquipePOSGP 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
1Rasmus SandinThunder (Tam)D8284957-61660146138170541124.71%135188122.9411718751911012113010.00%000000.6100000120
2Joel KivirantaThunder (Tam)LW/RW60272653-172201561132698020510.04%9116219.3841014511460000194031.91%9400010.9106000605
3Kevan MillerThunder (Tam)D82153752-308220230153176581228.52%211182422.259716821920113118010.00%000100.5701220322
4Tanner FritzThunder (Tam)C82202545-3960502101995414010.05%19151118.44671337174000013245.54%182700000.6001000115
5Thomas Di PauliThunder (Tam)C/LW82212142-144068941873814411.23%1387510.688917572030001552157.88%85700000.9629000322
6Jamie McGinnThunder (Tam)LW82202040-4218017093277831827.22%9155118.926612441740001222140.18%11200000.5214000422
7Anthony PelusoThunder (Tam)RW701623397792511197182471338.79%2397313.911124460112683247.62%14700000.8002203141
8Shane PrinceThunder (Tam)LW/RW8291726-4260537414541846.21%11156419.08055151720002580244.34%10600000.3301000002
9Dylan SambergThunder (Tam)D8232326-2224089846833584.41%71161319.683912361740002114000.00%000000.3200000001
10Samuel HenleyThunder (Tam)C/LW82111425-212013139105266610.48%33117014.2702221701101180036.49%142500000.4300000002
11Nikita NesterovThunder (Tam)D8242024-313201521029932644.04%119139216.980221970000059100.00%000000.3400000002
12Brett LernoutThunder (Tam)D5441721-3868201447110340543.88%120120622.3324641116000067210.00%000000.3500211100
13Tage ThompsonThunder (Tam)LW/RW229918-11120336690338710.00%1150222.831129410000381038.00%15000000.7224000201
14Sammy BlaisTampa BayLW12771408047318919557.87%526722.272021531000070023.53%1700001.0512000231
15Nicklas JensenThunder (Tam)LW/RW8231013-192048415813285.17%20118014.400110700021320136.28%11300000.2200000000
16Brady AustinThunder (Tam)D824812-4612058808119514.94%143144717.65011417000076100.00%000000.1700000003
17Grayson DowningThunder (Tam)C821910-621801261298221581.22%19146817.90000000000580041.08%133400000.1400000002
18Adam GilmourThunder (Tam)C/RW82224-58807625245148.33%1135016.4700001000000039.22%10200000.0600000001
19Avery PetersonThunder (Tam)C82011-112011392240.00%25716.970000340000520031.77%51300000.0400000000
Stats d'équipe Total ou en Moyenne1366184338522-5574716517811779240669816617.65%9742351417.2143821254911814134151184191242.56%679700110.44630634241632
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
1Louis DomingueThunder (Tam)82215290.9123.64468510228432410130.771358201364
2Jonas GunnarssonThunder (Tam)80000.9412.5428400122040000.0000082000
Stats d'équipe Total ou en Moyenne90215290.9143.57496910229634450130.7713582821364


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 Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam GilmourThunder (Tam)C/RW251994-01-29Yes193 Lbs6 ft2NoNoNo2Pro & Farm715,000$71,500$0$No715,000$Lien
Anthony PelusoThunder (Tam)RW301989-04-17No235 Lbs6 ft3NoNoNo1Pro & Farm875,000$87,500$0$NoLien
Austin CarrollThunder (Tam)RW251994-03-26Yes214 Lbs6 ft3NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Avery PetersonThunder (Tam)C241995-06-20Yes215 Lbs6 ft3NoNoNo1Pro & Farm525,000$52,500$0$NoLien
Brady AustinThunder (Tam)D261993-06-16No230 Lbs6 ft4NoNoNo3Pro & Farm850,000$85,000$0$No850,000$850,000$Lien
Brett LernoutThunder (Tam)D241995-09-23No213 Lbs6 ft4NoNoNo3Pro & Farm750,000$75,000$0$No750,000$750,000$Lien
Brett RitchieThunder (Tam)RW261993-07-01No217 Lbs6 ft3NoNoNo4Pro & Farm850,000$85,000$0$No850,000$850,000$850,000$Lien
Calvin PickardThunder (Tam)G271992-04-14No207 Lbs6 ft1NoNoNo3Pro & Farm915,000$91,500$0$No915,000$915,000$Lien
Dylan SambergThunder (Tam)D201999-01-24Yes216 Lbs6 ft4NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Freddie HamiltonThunder (Tam)C/LW/RW271992-01-01No195 Lbs6 ft1NoNoNo2Pro & Farm750,000$75,000$0$No750,000$Lien
Grayson DowningThunder (Tam)C271992-04-18Yes195 Lbs6 ft0NoNoNo2Pro & Farm650,000$65,000$0$No650,000$Lien
Jamie McGinnThunder (Tam)LW311988-08-05No205 Lbs6 ft1NoNoNo4Pro & Farm1,360,000$146,333$0$No1,360,000$1,360,000$1,320,000$Lien
Jeremy SwaymanThunder (Tam)G201998-11-24Yes187 Lbs6 ft3NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Joel KivirantaThunder (Tam)LW/RW231996-03-23Yes163 Lbs5 ft10NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Jonas GunnarssonThunder (Tam)G271992-03-31Yes198 Lbs6 ft1NoNoNo2Pro & Farm825,000$82,500$0$No825,000$Lien
Kevan MillerThunder (Tam)D311987-11-15No210 Lbs6 ft2NoNoNo4Pro & Farm3,600,000$356,667$0$No3,600,000$3,600,000$3,000,000$Lien
Louis DomingueThunder (Tam)G271992-03-05No210 Lbs6 ft3NoNoNo1Pro & Farm1,700,000$170,000$0$NoLien
Michael PrapavessisThunder (Tam)D231996-01-07No185 Lbs6 ft2NoNoNo2Pro & Farm650,000$65,000$0$No650,000$Lien
Nicklas JensenThunder (Tam)LW/RW261993-03-06No216 Lbs6 ft3NoNoNo1Pro & Farm750,000$75,000$0$NoLien
Nikita NesterovThunder (Tam)D261993-03-28No191 Lbs5 ft11NoNoNo1Pro & Farm560,000$56,000$0$NoLien
Rasmus SandinThunder (Tam)D192000-03-07No187 Lbs5 ft11NoNoNo3Pro & Farm894,167$89,417$0$No894,167$894,167$Lien
Samuel HenleyThunder (Tam)C/LW261993-07-25Yes210 Lbs6 ft4NoNoNo2Pro & Farm690,000$69,000$0$No690,000$Lien
Shane PrinceThunder (Tam)LW/RW261992-11-16No193 Lbs5 ft11NoNoNo1Pro & Farm560,000$56,000$0$NoLien
Tage ThompsonThunder (Tam)LW/RW211997-10-30No205 Lbs6 ft5NoNoNo2Pro & Farm925,000$92,500$0$No925,000$Lien
Tanner FritzThunder (Tam)C281991-08-20No192 Lbs5 ft11NoNoNo4Pro & Farm750,000$82,500$0$No750,000$560,000$560,000$Lien
Thomas Di PauliThunder (Tam)C/LW251994-04-29No187 Lbs5 ft11NoNoNo2Pro & Farm715,000$71,500$0$No715,000$Lien
Urho VaakanainenThunder (Tam)D201999-01-01No187 Lbs6 ft1NoNoNo3Pro & Farm925,000$92,500$0$No925,000$925,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2725.19202 Lbs6 ft22.44929,043$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonAvery PetersonAnthony Peluso40122
2Jamie McGinnTanner FritzShane Prince30122
3Nicklas JensenSamuel HenleyAdam Gilmour20122
4Tage ThompsonGrayson DowningThomas Di Pauli10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus SandinKevan Miller40122
2Dylan SambergNikita Nesterov30122
3Brady AustinGrayson Downing20122
4Rasmus SandinKevan Miller10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tage ThompsonThomas Di PauliAnthony Peluso60122
2Jamie McGinnTanner FritzShane Prince40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus SandinKevan Miller60122
2Dylan SambergNikita Nesterov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Tage ThompsonThomas Di Pauli60122
2Anthony PelusoJamie McGinn40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus SandinKevan Miller60122
2Dylan SambergNikita Nesterov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Tage Thompson60122Rasmus SandinKevan Miller60122
2Thomas Di Pauli40122Dylan SambergNikita Nesterov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Tage ThompsonThomas Di Pauli60122
2Anthony PelusoJamie McGinn40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Rasmus SandinKevan Miller60122
2Dylan SambergNikita Nesterov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonThomas Di PauliAnthony PelusoRasmus SandinKevan Miller
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tage ThompsonThomas Di PauliAnthony PelusoRasmus SandinKevan Miller
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Avery Peterson, Samuel Henley, Nicklas JensenAvery Peterson, Samuel HenleyNicklas Jensen
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brady Austin, Dylan Samberg, Nikita NesterovBrady AustinDylan Samberg, Nikita Nesterov
Tirs de Pénalité
Tage Thompson, Thomas Di Pauli, Anthony Peluso, Jamie McGinn, Tanner Fritz
Gardien
#1 : Louis Domingue, #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
1Admirals20200000413-91010000035-21010000018-700.0004711006655576547787777295991376443133.33%3166.67%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
2Baby Hawks2010000125-31000000123-11010000002-210.250235006655576497787777295975234569111.11%20100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
3Bears30200001712-51000000134-12020000048-410.1677142100665557682778777729591463886910330.00%30100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
4Bruins42200000813-52200000042220200000411-740.5008142201665557696778777729591624720729222.22%10370.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
5Cabaret Lady Mary Ann4120010016160210001009722020000079-230.3751631470066555762037787777295920274181083266.67%80100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
6Caroline31200000915-61010000039-62110000066020.33391524006655576647787777295912835196911436.36%7185.71%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
7Chiefs2010000148-41010000025-31000000123-110.25047110066555765077877772959782311507228.57%30100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
8Chill2110000046-2110000003211010000014-320.50047110066555765077877772959732585110110.00%40100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
9Comets2020000038-51010000014-31010000024-200.000347006655576517787777295973206427114.29%2150.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
10Cougars403000101019-92010001078-120200000311-820.25010162600665557691778777729591654223696233.33%9277.78%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
11Crunch40300100615-92020000039-62010010036-310.125612180066555761107787777295917439241028112.50%12650.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
12Heat21100000761110000004131010000035-220.500714210066555765977877772959822014266116.67%6183.33%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
13Jayhawks2010000135-21010000012-11000000123-110.250358006655576637787777295980101542500.00%40100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
14Las Vegas2020000029-71010000015-41010000014-300.0002460066555765677877772959921917335120.00%6350.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
15Manchots320000011091210000016601100000043150.833101828006655576100778777729591174029818112.50%7271.43%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
16Marlies40300100815-72020000057-22010010038-510.12581523006655576114778777729591393410671000.00%50100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
17Minnesota2010000158-31010000035-21000000123-110.250591410665557694778777729599022854300.00%40100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
18Monarchs2020000059-41010000024-21010000035-200.00059140066555765677877772959983610477114.29%5340.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
19Monsters3120000049-51010000005-52110000044020.333471100665557676778777729591223516597114.29%70100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
20Monsters2020000027-51010000024-21010000003-300.00023500665557659778777729597325636900.00%30100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
21Oceanics2020000038-51010000004-41010000034-100.0003690066555764377877772959931812454250.00%6183.33%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
22Oil Kings2020000059-41010000034-11010000025-300.0005101500665557662778777729591012714405120.00%7357.14%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
23Phantoms3120000048-4211000004401010000004-420.33346101066555767277877772959122371972700.00%70100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
24Rocket42200000812-42110000045-12110000047-340.500815230066555761077787777295916040288215533.33%13469.23%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
25Senators41300000818-1020200000111-102110000077020.250814221066555761187787777295918058168216212.50%60100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
26Sharks20200000311-81010000026-41010000015-400.0003690066555764077877772959942328374125.00%9277.78%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
27Sound Tigers30200010912-32020000059-41000001043120.3339142300665557674778777729591273614556350.00%7271.43%11109247344.84%1216301340.36%556131542.28%1818123020726191085524
28Spiders3120000039-6110000001012020000029-720.33336901665557664778777729591304011658112.50%20100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
29Stars22000000725110000004131100000031241.00071320006655576577787777295974228346233.33%30100.00%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
Total82175200346182305-1234111240012397147-50416280022385158-73510.311182323505326655576230977877772959344896942817422234319.28%1733778.61%11109247344.84%1216301340.36%556131542.28%1818123020726191085524
30Wolf Pack310000201394210000109631000001043161.0001319320066555769577877772959107246539111.11%3233.33%01109247344.84%1216301340.36%556131542.28%1818123020726191085524
_Since Last GM Reset82175200346182305-1234111240012397147-50416280022385158-73510.311182323505326655576230977877772959344896942817422234319.28%1733778.61%11109247344.84%1216301340.36%556131542.28%1818123020726191085524
_Vs Conference4310270013293161-6822712000124875-2721315001204586-41290.3379316225522665557611347787777295918015282138991182016.95%841680.95%11109247344.84%1216301340.36%556131542.28%1818123020726191085524

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
8251L318232350523093448969428174232
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8217520346182305
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
411124012397147
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41628022385158
Derniers 10 Matchs
WLOTWOTL SOWSOL
280000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2234319.28%1733778.61%1
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
778777729596655576
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
1109247344.84%1216301340.36%556131542.28%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
1818123020726191085524


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 - 2020-10-235Cabaret Lady Mary Ann3Thunder6WSommaire du Match
4 - 2020-10-2521Thunder4Cabaret Lady Mary Ann5LSommaire du Match
5 - 2020-10-2631Thunder4Caroline2WSommaire du Match
9 - 2020-10-3047Thunder2Marlies3LXSommaire du Match
11 - 2020-11-0162Thunder2Senators4LSommaire du Match
14 - 2020-11-0486Thunder3Rocket2WSommaire du Match
16 - 2020-11-0698Thunder3Bruins5LSommaire du Match
18 - 2020-11-08117Monsters4Thunder2LSommaire du Match
22 - 2020-11-12144Manchots4Thunder3LXXSommaire du Match
25 - 2020-11-15164Chill2Thunder3WSommaire du Match
28 - 2020-11-18181Thunder4Wolf Pack3WXXSommaire du Match
29 - 2020-11-19188Thunder1Spiders3LSommaire du Match
31 - 2020-11-21197Thunder4Sound Tigers3WXXSommaire du Match
38 - 2020-11-28248Thunder2Crunch4LSommaire du Match
39 - 2020-11-29253Crunch3Thunder1LSommaire du Match
44 - 2020-12-04287Wolf Pack3Thunder5WSommaire du Match
46 - 2020-12-06302Oceanics4Thunder0LSommaire du Match
49 - 2020-12-09324Thunder2Chiefs3LXXSommaire du Match
51 - 2020-12-11341Thunder0Baby Hawks2LSommaire du Match
53 - 2020-12-13355Admirals5Thunder3LSommaire du Match
55 - 2020-12-15365Crunch6Thunder2LSommaire du Match
57 - 2020-12-17380Chiefs5Thunder2LSommaire du Match
59 - 2020-12-19398Thunder2Bears3LSommaire du Match
60 - 2020-12-20408Caroline9Thunder3LSommaire du Match
63 - 2020-12-23430Thunder1Chill4LSommaire du Match
65 - 2020-12-25440Minnesota5Thunder3LSommaire du Match
67 - 2020-12-27457Sharks6Thunder2LSommaire du Match
69 - 2020-12-29468Sound Tigers2Thunder1LSommaire du Match
70 - 2020-12-30473Thunder3Cabaret Lady Mary Ann4LSommaire du Match
72 - 2021-01-01488Bruins0Thunder1WSommaire du Match
74 - 2021-01-03509Bears4Thunder3LXXSommaire du Match
77 - 2021-01-06526Senators5Thunder1LSommaire du Match
79 - 2021-01-08539Stars1Thunder4WSommaire du Match
81 - 2021-01-10559Thunder2Bears5LSommaire du Match
83 - 2021-01-12572Cabaret Lady Mary Ann4Thunder3LXSommaire du Match
88 - 2021-01-17595Rocket2Thunder3WSommaire du Match
89 - 2021-01-18607Cougars5Thunder3LSommaire du Match
91 - 2021-01-20617Thunder1Crunch2LXSommaire du Match
93 - 2021-01-22629Thunder1Rocket5LSommaire du Match
95 - 2021-01-24648Thunder5Senators3WSommaire du Match
96 - 2021-01-25655Thunder2Caroline4LSommaire du Match
98 - 2021-01-27663Comets4Thunder1LSommaire du Match
100 - 2021-01-29680Jayhawks2Thunder1LSommaire du Match
102 - 2021-01-31695Thunder0Phantoms4LSommaire du Match
103 - 2021-02-01708Thunder1Spiders6LSommaire du Match
105 - 2021-02-03716Monarchs4Thunder2LSommaire du Match
107 - 2021-02-05736Thunder2Minnesota3LXXSommaire du Match
108 - 2021-02-06742Thunder3Oceanics4LSommaire du Match
118 - 2021-02-16771Thunder3Stars1WSommaire du Match
120 - 2021-02-18779Thunder3Monarchs5LSommaire du Match
122 - 2021-02-20791Thunder1Admirals8LSommaire du Match
123 - 2021-02-21805Thunder1Sharks5LSommaire du Match
126 - 2021-02-24814Las Vegas5Thunder1LSommaire du Match
128 - 2021-02-26829Manchots2Thunder3WSommaire du Match
130 - 2021-02-28847Sound Tigers7Thunder4LSommaire du Match
132 - 2021-03-02863Thunder3Monsters1WSommaire du Match
133 - 2021-03-03870Thunder4Manchots3WSommaire du Match
135 - 2021-03-05882Oil Kings4Thunder3LSommaire du Match
137 - 2021-03-07897Phantoms3Thunder1LSommaire du Match
139 - 2021-03-09919Thunder0Monsters3LSommaire du Match
142 - 2021-03-12939Thunder1Las Vegas4LSommaire du Match
144 - 2021-03-14954Thunder2Jayhawks3LXXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17970Marlies3Thunder2LSommaire du Match
149 - 2021-03-19986Baby Hawks3Thunder2LXXSommaire du Match
151 - 2021-03-211001Heat1Thunder4WSommaire du Match
154 - 2021-03-241019Bruins2Thunder3WSommaire du Match
156 - 2021-03-261034Rocket3Thunder1LSommaire du Match
158 - 2021-03-281054Thunder1Bruins6LSommaire du Match
159 - 2021-03-291060Thunder2Cougars6LSommaire du Match
161 - 2021-03-311070Thunder1Marlies5LSommaire du Match
163 - 2021-04-021085Phantoms1Thunder3WSommaire du Match
165 - 2021-04-041100Cougars3Thunder4WXXSommaire du Match
166 - 2021-04-051114Spiders0Thunder1WSommaire du Match
169 - 2021-04-081134Thunder2Comets4LSommaire du Match
171 - 2021-04-101150Thunder2Oil Kings5LSommaire du Match
172 - 2021-04-111162Thunder3Heat5LSommaire du Match
176 - 2021-04-151185Marlies4Thunder3LSommaire du Match
178 - 2021-04-171199Monsters5Thunder0LSommaire du Match
179 - 2021-04-181211Wolf Pack3Thunder4WXXSommaire du Match
182 - 2021-04-211228Senators6Thunder0LSommaire du Match
184 - 2021-04-231249Thunder1Monsters3LSommaire du Match
186 - 2021-04-251264Thunder1Cougars5LSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance79,33539,291
Assistance PCT96.75%95.83%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 2893 - 96.44% 82,100$3,366,090$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,522,816$ 2,508,417$ 2,522,917$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
13,564$ 2,537,338$ 27 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 13,486$ 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