hellpepitosKingspatriots

 

 


Werewolves

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Jean-Nicolas Bleau | Morale : 50 | Moyenne d'Équipe : 69
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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
1Radek Faksa0XX100.00692858408276776988798178605949056740
2Evan Rodrigues0X100.00422666344472737473818172704445047720
3Nolan Patrick0X100.00583064346269707381818262783954047720
4Jimmy Vesey0XX100.00602770347073797337798269784347050720
5Sven Baertschi0X100.0045766295572477633818458775836050710
6Danton Heinen0X100.00531770345566797436828252744240047710
7Jesper Fast0X100.0078963406173656839808275576043050710
8Vinnie Hinostroza0X100.00572670323969777647828365754645050710
9Jason Dickinson0X100.00783063436760756869798072655155047700
10Anthony Duclair0X100.00482767315459777633798456805151050700
11Jordan Greenway0X100.00551564398663876842778056663935047690
12Rocco Grimaldi0XXX100.00602468373946767362778242665043050660
13Denis Gurianov0X100.00562883546149815935687655673843050620
14Kailer Yamamoto0X100.00472277561862765931687665673638047610
15Ben Hutton0X100.00522465447374728131827570694442011720
16Jordan Oesterle0X100.00561675445269798229837664654536050710
17Matt Grzelcyk0X100.00541458443965718329837650654742050700
18Jamie Oleksiak0X100.00873949479755768127817653625455050700
19Gustav Forsling0X100.00551659455164688231827663654637050690
20Jonas Siegenthaler (R)0X100.00661264567053817430787454674533050660
Rayé
1Warren Foegele0X100.00792364396458876952768156663940047680
2Anders Bjork0XX100.00472073415456676364777951663639047650
3Kevin Stenlund (R)0X100.00332174667550835631647066683942050600
4Chase De Leo (R)0X100.00282690674157835631647070685345050590
5Gavin Bayreuther0X100.00422468486166817430747361673943050680
6Ben Gleason0X100.00362083585055836731727055683737050630
MOYENNE D'ÉQUIPE100.0055226844586376714377786168454304868
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 Domingue100.0089928786889290899078806870050830
2Collin Delia100.0083928481838987878856603955047790
Rayé
MOYENNE D'ÉQUIPE100.008692868486918988896770546304981
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe70707070707070CAN465450,000$


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'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
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


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
Anders BjorkWerewolves (GOB)LW/RW231996-08-05No190 Lbs183 CMNoNoNo2Pro & Farm1,066,667$1,066,667$0$0$No1,066,667$Lien
Anthony DuclairWerewolves (GOB)LW241995-08-26No191 Lbs180 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien / Lien NHL
Ben GleasonWerewolves (GOB)D211998-03-25No185 Lbs185 CMNoNoNo1Pro & Farm761,666$761,666$0$0$NoLien
Ben HuttonWerewolves (GOB)D261993-04-20No206 Lbs188 CMNoNoNo1Pro & Farm999,000$999,000$0$0$NoLien / Lien NHL
Chase De LeoWerewolves (GOB)LW231995-10-25Yes179 Lbs175 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien
Collin DeliaWerewolves (GOB)G251994-06-20No208 Lbs188 CMNoNoNo1Pro & Farm1,000,000$1,000,000$0$0$NoLien
Danton HeinenWerewolves (GOB)C241995-07-05No188 Lbs185 CMNoNoNo1Pro & Farm995,833$995,833$0$0$NoLien
Denis GurianovWerewolves (GOB)RW221997-06-07No195 Lbs188 CMNoNoNo1Pro & Farm1,644,166$1,644,166$0$0$NoLien
Evan RodriguesWerewolves (GOB)LW261993-07-28No176 Lbs178 CMNoNoNo1Pro & Farm2,000,000$2,000,000$0$0$NoLien
Gavin BayreutherWerewolves (GOB)D251994-05-12No195 Lbs185 CMNoNoNo1Pro & Farm925,000$925,000$0$0$NoLien
Gustav ForslingWerewolves (GOB)D231996-06-12No186 Lbs183 CMNoNoNo1Pro & Farm925,000$925,000$0$0$NoLien / Lien NHL
Jamie OleksiakWerewolves (GOB)D261992-12-21No255 Lbs201 CMNoNoNo2Pro & Farm2,137,500$2,137,500$0$0$No2,137,500$Lien / Lien NHL
Jason DickinsonWerewolves (GOB)C241995-07-04No200 Lbs188 CMNoNoNo2Pro & Farm1,500,000$1,500,000$0$0$No1,500,000$Lien
Jesper FastWerewolves (GOB)RW271991-12-02No192 Lbs185 CMNoNoNo1Pro & Farm1,850,000$1,850,000$0$0$NoLien / Lien NHL
Jimmy VeseyWerewolves (GOB)LW/RW261993-05-26No199 Lbs191 CMNoNoNo2Pro & Farm2,275,000$2,275,000$0$0$No2,275,000$Lien / Lien NHL
Jonas SiegenthalerWerewolves (GOB)D221997-05-06Yes206 Lbs191 CMNoNoNo1Pro & Farm888,333$888,333$0$0$NoLien
Jordan GreenwayWerewolves (GOB)LW221997-02-16No227 Lbs198 CMNoNoNo2Pro & Farm1,225,000$1,225,000$0$0$No1,225,000$Lien
Jordan OesterleWerewolves (GOB)D271992-06-25No182 Lbs183 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien / Lien NHL
Kailer YamamotoWerewolves (GOB)RW201998-09-29No153 Lbs173 CMNoNoNo2Pro & Farm1,124,666$1,124,666$0$0$No1,124,666$Lien
Kevin StenlundWerewolves (GOB)C231996-09-20Yes210 Lbs193 CMNoNoNo1Pro & Farm925,000$925,000$0$0$NoLien
Louis DomingueWerewolves (GOB)G271992-03-06No210 Lbs191 CMNoNoNo1Pro & Farm1,150,000$1,150,000$0$0$NoLien / Lien NHL
Matt GrzelcykWerewolves (GOB)D251994-01-05No174 Lbs175 CMNoNoNo1Pro & Farm1,400,000$1,400,000$0$0$NoLien
Nolan PatrickWerewolves (GOB)C211998-09-19No198 Lbs188 CMNoNoNo1Pro & Farm3,575,000$3,575,000$0$0$NoLien
Radek FaksaWerewolves (GOB)C/LW251994-01-09No220 Lbs191 CMNoNoNo1Pro & Farm2,200,000$2,200,000$0$0$NoLien / Lien NHL
Rocco GrimaldiWerewolves (GOB)C/LW/RW261993-02-08No180 Lbs168 CMNoNoNo1Pro & Farm650,000$650,000$0$0$NoLien / Lien NHL
Sven BaertschiWerewolves (GOB)LW261992-10-05No190 Lbs180 CMNoNoNo1Pro & Farm1,955,692$1,955,692$0$0$NoLien / Lien NHL
Vinnie HinostrozaWerewolves (GOB)LW251994-04-03No173 Lbs175 CMNoNoNo1Pro & Farm1,500,000$1,500,000$0$0$NoLien / Lien NHL
Warren FoegeleWerewolves (GOB)LW231996-04-01No198 Lbs188 CMNoNoNo2Pro & Farm800,000$800,000$0$0$No800,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2824.18195 Lbs185 CM1.251,336,554$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anthony DuclairRadek FaksaDanton Heinen32122
2Vinnie HinostrozaNolan PatrickRocco Grimaldi30122
3Sven BaertschiRadek FaksaDenis Gurianov23122
4Jesper FastJason DickinsonJimmy Vesey15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ben HuttonJamie Oleksiak40122
2Jonas SiegenthalerMatt Grzelcyk30122
3Gustav ForslingJordan Oesterle20122
4Gustav ForslingJordan Oesterle10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Anthony DuclairNolan PatrickKailer Yamamoto60122
2Evan RodriguesRadek FaksaRocco Grimaldi40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ben HuttonJordan Oesterle60122
2Jamie OleksiakMatt Grzelcyk40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Radek FaksaKailer Yamamoto60122
2Jason DickinsonJimmy Vesey40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ben HuttonJordan Oesterle60122
2Jamie OleksiakMatt Grzelcyk40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Radek Faksa60122Ben HuttonJordan Oesterle60122
2Jimmy Vesey40122Jamie OleksiakMatt Grzelcyk40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Radek FaksaJordan Greenway60122
2Rocco GrimaldiSven Baertschi40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ben HuttonJordan Oesterle60122
2Jamie OleksiakMatt Grzelcyk40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Anthony DuclairNolan PatrickRocco GrimaldiMatt GrzelcykJamie Oleksiak
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Evan RodriguesRadek FaksaJesper FastBen HuttonJordan Oesterle
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Kailer Yamamoto, Sven Baertschi, Denis GurianovRocco Grimaldi, Nolan PatrickJason Dickinson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Gustav Forsling, Jonas Siegenthaler, Jamie OleksiakMatt GrzelcykJonas Siegenthaler, Jordan Oesterle
Tirs de Pénalité
Nolan Patrick, Anthony Duclair, Jimmy Vesey, Sven Baertschi, Jesper Fast
Gardien
#1 : Louis Domingue, #2 : Collin Delia


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%0
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
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


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



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
42 0 - 0.00%0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 3,742,353$ 3,102,853$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 0$ 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
20168459140413357218039242335020202678318442269021133059720811857210091581031771692198260886983089537232584590918323017926.25%2614881.61%13959164258.40%915162756.24%759132457.33%2066137217286601287670
2017844520083083651921734226905101198901084219110320716710265903656641029041251231099262689184284575234879079016802936923.55%3756582.67%11997164360.68%1016168260.40%678112460.32%2054133617496831294660
201882531706060496198298412850305026392171412512030102331061271064968901386031911521411332771223104997547264897687717612819132.38%4117681.51%131150193459.46%1206193562.33%752125959.73%2055136516706501239634
Total Saison Régulière250157510184911143357086312587190101717282654631257032083210705305400314143325633996010493444469308511298327212715159732126112576527387523927.31%104718981.95%373106521959.51%3137524459.82%2189370759.05%617640745148199338201965
Séries
2016211650000084444011920000055203510730000029245328414422802262828270120524024313597252166439761519.74%781185.90%126144159.18%25344057.50%17925769.65%534358445163309163
201762400000813-5321000005503030000038-54815230034011626347439160666014424312.50%30293.33%06412949.61%5912049.17%296445.31%143871395410049
2018148600000454238530000028217633000001721-416458513000211011354621215216022489169181295781823.08%871780.46%120636855.98%22135462.43%11218062.22%363236313118215111
Total Séries412615000001379938221660000088464219109000004953-45213724438102504239614094804394464412464874078781783620.22%1953084.62%253193856.61%53391458.32%32050163.87%1042682897335626324