hellpepitosKingspatriots

 

 


Werewolves

GP: 37 | W: 28 | L: 8 | OTL: 1 | P: 57
GF: 166 | GA: 82 | PP%: 28.77% | PK%: 79.22%
DG: Jean-Nicolas Bleau | Morale : 50 | Moyenne d'Équipe : 69
Prochain matchs #280 vs Chevalier
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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
1James Neal0XX100.00573063318274567541808258857874050740
2Colton Sissons (A)0X100.00763263386776757082798180605859050730
3Mark Jankowski0X100.00442567377959907584798270724044050720
4Evan Rodrigues0X100.00422666344472737473818172704445050720
5Nolan Patrick (A)0X100.00583064346269707381818262783954050720
6Jimmy Vesey0XX100.00602770347073797337798269784347050720
7Sven Baertschi0X100.0045766295572477633818458775836050710
8Jesper Fast0X100.0078963406173656839808275576043050710
9Mattias Janmark0X100.00391064376273676943808171705638050710
10Vinnie Hinostroza0X100.00572670323969777647828365754645050710
11Jason Dickinson0X100.00783063436760756869798072655155050700
12Anthony Duclair0X100.00482767315459777633798456805151050700
13Jordan Greenway0X100.00551564398663876842778056663935050690
14Jordan Oesterle0X100.00561675445269798229837664654536050710
15Matt Grzelcyk0X100.00541458443965718329837650654742050700
16Jamie Oleksiak0X100.00873949479755768127817653625455050700
17Stephen Johns0X100.00853264458764508229797667644951050700
18Gustav Forsling0X100.00551659455164688231827663654637050690
19Ben Gleason0X100.00362083585055836731727055683737050630
Rayé
1Brendan Leipsic0X100.00573163354863747158818156715558050700
2Adam Erne0X100.00853752437848756954788152655160050680
3Warren Foegele0X100.00792364396458876952768156663940050680
4Anders Bjork0XX100.00472073415456676364777951663639050650
5Denis Gurianov0X100.00562883546149815935687655673843050620
6Kailer Yamamoto0X100.00472277561862765931687665673638050610
7Kevin Stenlund (R)0X100.00332174667550835631647066683942050600
8Chase De Leo (R)0X100.00282690674157835631647070685345050590
9Gavin Bayreuther0X100.00422468486166817430747361673943050680
10Christian Djoos0X100.00481174464148718029837637655434050670
11Jonas Siegenthaler (R)0X100.00661264567053817430787454674533050660
MOYENNE D'ÉQUIPE100.0057236743616274724478786169484505069
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 Delia100.0083928481838987878856603955050790
Rayé
MOYENNE D'ÉQUIPE100.008692868486918988896770546305081
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe70707070707070CAN453450,000$


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
1Nolan PatrickWerewolves (GOB)C37184361242205458119307415.13%1376820.7851722311130001574358.61%604238001.5912000363
2Sven BaertschiWerewolves (GOB)LW37253459252001531117307921.37%569118.696172327115000006038.10%42196011.7100000435
3Colton SissonsWerewolves (GOB)C371129401726083104108357010.19%4288824.0219102610920261420164.64%4441324010.9012000210
4Jesper FastWerewolves (GOB)RW3610273710160718411733658.55%3367318.707111825115000003144.44%362117001.1001000233
5Vinnie HinostrozaWerewolves (GOB)LW371914332780273973234926.03%2343911.8900000000001270.00%10138011.5000000211
6Mark JankowskiWerewolves (GOB)C371116272040136679335113.92%2550213.57000000002492164.29%294137011.0800000002
7James NealWerewolves (GOB)LW/RW36718252280494010619766.60%1588224.5139122610501171393248.13%268169000.5702000210
8Gustav ForslingWerewolves (GOB)D37022223022020322512170.00%1750113.550000000001000.00%0612000.8800000000
9Jimmy VeseyWerewolves (GOB)LW/RW371012222120353286285411.63%839210.60651128112000000041.18%17115001.1200000000
10Evan RodriguesWerewolves (GOB)LW3761420178012327520458.00%1440210.8700000000001066.67%1589000.9900000000
11Jason DickinsonWerewolves (GOB)C371192017120293464232817.19%1240310.8900000000000268.07%23896000.9900000211
12Matt GrzelcykWerewolves (GOB)D371181911280462453212720.75%2792825.10527171300002136200.00%01510010.4100000001
13Jamie OleksiakWerewolves (GOB)D376101622440812340172015.00%2875620.442461198000380010.00%01811010.4200000001
14Jordan OesterleWerewolves (GOB)D3651116060206150302910.00%7094226.1924691300004149000.00%01724000.3401000000
15Anthony DuclairWerewolves (GOB)LW3769151920041331046.15%1611.67000020000120100.00%130014.8700000002
16Stephen JohnsWerewolves (GOB)D36691512435515352231811.54%3075120.875271798000482200.00%01314000.4000000021
17Mattias JanmarkWerewolves (GOB)LW37281010403161451014.29%41754.760002120000160060.00%2502001.1400000001
18Ben GleasonWerewolves (GOB)D36033182021612350.00%1653214.7900000000043000.00%018000.1100000000
19Jordan GreenwayWerewolves (GOB)LW37000000456410.00%51052.85000000005840048.98%4931000.0000000000
Stats d'équipe Total ou en Moyenne6981642964602833075615754120939272813.56%3881080015.474280122219114521334986261359.57%2043222181070.8528000171821
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 DomingueWerewolves (GOB)3627810.9252.26218101821099598200.83363601041
2Collin DeliaWerewolves (GOB)11001.0000.006001020000.0000137000
Stats d'équipe Total ou en Moyenne3728810.9262.20224102821101598200.833637371041


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 ErneWerewolves (GOB)LW241995-04-20No214 Lbs185 CMNoNoNo2Pro & Farm800,000$466,257$0$0$No800,000$Lien
Anders BjorkWerewolves (GOB)LW/RW231996-08-05No190 Lbs183 CMNoNoNo1Pro & Farm1,066,667$621,677$0$0$NoLien
Anthony DuclairWerewolves (GOB)LW241995-08-26No191 Lbs180 CMNoNoNo2Pro & Farm650,000$378,834$0$0$No650,000$Lien / Lien NHL
Ben GleasonWerewolves (GOB)D211998-03-25No185 Lbs185 CMNoNoNo2Pro & Farm761,666$443,915$0$0$No761,666$Lien
Brendan LeipsicWerewolves (GOB)LW251994-05-19No182 Lbs178 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Chase De LeoWerewolves (GOB)LW231995-10-25Yes179 Lbs175 CMNoNoNo2Pro & Farm650,000$378,834$0$0$No650,000$Lien
Christian DjoosWerewolves (GOB)D251994-08-06No169 Lbs183 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien
Collin DeliaWerewolves (GOB)G251994-06-20No208 Lbs188 CMNoNoNo1Pro & Farm750,000$437,116$0$0$NoLien
Colton SissonsWerewolves (GOB)C251993-11-05No200 Lbs185 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien / Lien NHL
Denis GurianovWerewolves (GOB)RW221997-06-07No195 Lbs188 CMNoNoNo2Pro & Farm1,644,166$958,256$0$0$No1,644,166$Lien
Evan RodriguesWerewolves (GOB)LW261993-07-28No176 Lbs178 CMNoNoNo1Pro & Farm650,000$378,834$0$0$NoLien
Gavin BayreutherWerewolves (GOB)D251994-05-12No195 Lbs185 CMNoNoNo2Pro & Farm925,000$539,110$0$0$No925,000$Lien
Gustav ForslingWerewolves (GOB)D231996-06-12No186 Lbs183 CMNoNoNo2Pro & Farm925,000$539,110$0$0$No925,000$Lien / Lien NHL
James NealWerewolves (GOB)LW/RW321987-09-03No212 Lbs191 CMNoNoNo2Pro & Farm1,975,664$1,151,460$0$0$No1,975,664$Lien / Lien NHL
Jamie OleksiakWerewolves (GOB)D261992-12-21No255 Lbs201 CMNoNoNo3Pro & Farm2,137,500$1,245,782$0$0$No2,137,500$2,137,500$Lien / Lien NHL
Jason DickinsonWerewolves (GOB)C241995-07-04No200 Lbs188 CMNoNoNo1Pro & Farm925,000$539,110$0$0$NoLien
Jesper FastWerewolves (GOB)RW271991-12-02No192 Lbs185 CMNoNoNo2Pro & Farm1,850,000$1,078,220$0$0$No1,850,000$Lien / Lien NHL
Jimmy VeseyWerewolves (GOB)LW/RW261993-05-26No199 Lbs191 CMNoNoNo3Pro & Farm2,275,000$1,325,920$0$0$No2,275,000$2,275,000$Lien / Lien NHL
Jonas SiegenthalerWerewolves (GOB)D221997-05-06Yes206 Lbs191 CMNoNoNo2Pro & Farm888,333$517,740$0$0$No888,333$Lien
Jordan GreenwayWerewolves (GOB)LW221997-02-16No227 Lbs198 CMNoNoNo1Pro & Farm1,225,000$713,957$0$0$NoLien
Jordan OesterleWerewolves (GOB)D271992-06-25No182 Lbs183 CMNoNoNo2Pro & Farm650,000$378,834$0$0$No650,000$Lien / Lien NHL
Kailer YamamotoWerewolves (GOB)RW201998-09-29No153 Lbs173 CMNoNoNo1Pro & Farm1,155,000$673,159$0$0$NoLien
Kevin StenlundWerewolves (GOB)C231996-09-20Yes210 Lbs193 CMNoNoNo2Pro & Farm925,000$539,110$0$0$No925,000$Lien
Louis DomingueWerewolves (GOB)G271992-03-06No210 Lbs191 CMNoNoNo2Pro & Farm1,150,000$670,245$0$0$No1,150,000$Lien / Lien NHL
Mark JankowskiWerewolves (GOB)C251994-09-13No212 Lbs193 CMNoNoNo2Pro & Farm1,675,000$976,226$0$0$No1,675,000$Lien
Matt GrzelcykWerewolves (GOB)D251994-01-05No174 Lbs175 CMNoNoNo2Pro & Farm1,400,000$815,950$0$0$No1,400,000$Lien
Mattias JanmarkWerewolves (GOB)LW261992-12-08No195 Lbs185 CMNoNoNo1Pro & Farm700,000$407,975$0$0$NoLien / Lien NHL
Nolan PatrickWerewolves (GOB)C211998-09-19No198 Lbs188 CMNoNoNo1Pro & Farm3,575,000$2,083,588$0$0$NoLien
Stephen JohnsWerewolves (GOB)D271992-04-18No225 Lbs193 CMNoNoNo1Pro & Farm725,000$422,546$0$0$NoLien / Lien NHL
Sven BaertschiWerewolves (GOB)LW261992-10-05No190 Lbs180 CMNoNoNo2Pro & Farm1,955,692$1,139,820$0$0$No1,955,692$Lien / Lien NHL
Vinnie HinostrozaWerewolves (GOB)LW251994-04-03No173 Lbs175 CMNoNoNo2Pro & Farm1,500,000$874,233$0$0$No1,500,000$Lien / Lien NHL
Warren FoegeleWerewolves (GOB)LW231996-04-01No198 Lbs188 CMNoNoNo1Pro & Farm800,000$466,257$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3224.53196 Lbs185 CM1.661,195,615$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James NealColton SissonsJimmy Vesey40122
2Sven BaertschiNolan PatrickJesper Fast30122
3Vinnie HinostrozaMark JankowskiJames Neal20122
4Evan RodriguesJason DickinsonColton Sissons10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMatt Grzelcyk40122
2Stephen JohnsJamie Oleksiak30122
3Gustav ForslingBen Gleason20122
4Jordan OesterleMatt Grzelcyk10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1James NealColton SissonsJimmy Vesey60122
2Sven BaertschiNolan PatrickJesper Fast40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMatt Grzelcyk60122
2Stephen JohnsJamie Oleksiak40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1James NealColton Sissons60122
2Nolan PatrickMark Jankowski40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMatt Grzelcyk60122
2Stephen JohnsJamie Oleksiak40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1James Neal60122Jordan OesterleMatt Grzelcyk60122
2Colton Sissons40122Stephen JohnsJamie Oleksiak40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1James NealColton Sissons60122
2Nolan PatrickMark Jankowski40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMatt Grzelcyk60122
2Stephen JohnsJamie Oleksiak40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
James NealColton SissonsJimmy VeseyJordan OesterleMatt Grzelcyk
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
James NealColton SissonsJimmy VeseyJordan OesterleMatt Grzelcyk
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mattias Janmark, Anthony Duclair, Jordan GreenwayMattias Janmark, Anthony DuclairJordan Greenway
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Gustav Forsling, Ben Gleason, Stephen JohnsGustav ForslingBen Gleason, Stephen Johns
Tirs de Pénalité
James Neal, Colton Sissons, Nolan Patrick, Mark Jankowski, Jimmy Vesey
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
Total37248021201668284181420101010232701910601110645014570.77016629846402645147412094163873951711013883076151464228.77%1543279.22%246279258.33%45176758.80%30448562.68%876566792300573300
_Since Last GM Reset37248021201668284181420101010232701910601110645014570.77016629846402645147412094163873951711013883076151464228.77%1543279.22%246279258.33%45176758.80%30448562.68%876566792300573300
_Vs Conference141120100087246376001000648567520000023167240.857871592460164514744554163873951742014683230501530.00%42880.95%146279258.33%45176758.80%30448562.68%876566792300573300
_Vs Division80101000251114400010001441040100000117420.12525477200645147425041638739517245735015426934.62%26388.46%046279258.33%45176758.80%30448562.68%876566792300573300

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3757W31662984641209110138830761502
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
37248212016682
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
18142101010232
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1910611106450
Derniers 10 Matchs
WLOTWOTL SOWSOL
820000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1464228.77%1543279.22%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
416387395176451474
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
46279258.33%45176758.80%30448562.68%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
876566792300573300


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
1 - 2019-10-063Caribou0Werewolves44WSommaire du Match
3 - 2019-10-0811Werewolves4Hybrides1WSommaire du Match
5 - 2019-10-1018Werewolves2Hybrides3LSommaire du Match
6 - 2019-10-1123Hybrides1Werewolves5WSommaire du Match
8 - 2019-10-1330Werewolves4Leftovers5LSommaire du Match
10 - 2019-10-1539Werewolves3Leftovers0WSommaire du Match
12 - 2019-10-1745Casse-Tete2Werewolves3WXSommaire du Match
14 - 2019-10-1954Pirates2Werewolves0LSommaire du Match
17 - 2019-10-2266Diabotins1Werewolves3WSommaire du Match
19 - 2019-10-2473Werewolves3Caribou1WSommaire du Match
21 - 2019-10-2680Pirates1Werewolves4WSommaire du Match
23 - 2019-10-2890Werewolves5Benchwarmers3WSommaire du Match
24 - 2019-10-2996Caribou2Werewolves3WSommaire du Match
25 - 2019-10-3097Werewolves4Leftovers2WSommaire du Match
28 - 2019-11-02106Werewolves1Diabotins2LSommaire du Match
29 - 2019-11-03114Chevalier1Werewolves3WSommaire du Match
31 - 2019-11-05123Werewolves4Jardiniers5LXSommaire du Match
33 - 2019-11-07129Caribou1Werewolves4WSommaire du Match
34 - 2019-11-08137Werewolves6Vagabond4WSommaire du Match
36 - 2019-11-10144Vagabond4Werewolves2LSommaire du Match
38 - 2019-11-12153Werewolves4Hybrides1WSommaire du Match
40 - 2019-11-14159Werewolves5Benchwarmers4WXSommaire du Match
41 - 2019-11-15163Hybrides1Werewolves2WSommaire du Match
43 - 2019-11-17172Werewolves3Casse-Tete6LSommaire du Match
44 - 2019-11-18178Werewolves3Jardiniers1WSommaire du Match
46 - 2019-11-20185Leftovers3Werewolves4WSommaire du Match
48 - 2019-11-22193Diabotins1Werewolves4WSommaire du Match
51 - 2019-11-25204Werewolves1Benchwarmers3LSommaire du Match
52 - 2019-11-26209Pirates1Werewolves3WSommaire du Match
55 - 2019-11-29218Werewolves3Royaux1WSommaire du Match
56 - 2019-11-30224Jardiniers2Werewolves4WSommaire du Match
58 - 2019-12-02234Requins5Werewolves6WXXSommaire du Match
61 - 2019-12-05245Vagabond1Werewolves2WSommaire du Match
63 - 2019-12-07254Werewolves1Requins2LSommaire du Match
64 - 2019-12-08260Werewolves4Leftovers3WXXSommaire du Match
65 - 2019-12-09265Werewolves4Royaux3WSommaire du Match
67 - 2019-12-11271Pirates3Werewolves6WSommaire du Match
69 - 2019-12-13280Chevalier-Werewolves-
70 - 2019-12-14284Werewolves-Hooligans-
72 - 2019-12-16294Casse-Tete-Werewolves-
74 - 2019-12-18302Werewolves-Diabotins-
76 - 2019-12-20309Diabotins-Werewolves-
79 - 2019-12-23318Hooligans-Werewolves-
80 - 2019-12-24326Werewolves-Caribou-
83 - 2019-12-27333Werewolves-Chevalier-
85 - 2019-12-29340Casse-Tete-Werewolves-
86 - 2019-12-30348Caribou-Werewolves-
88 - 2020-01-01354Werewolves-Requins-
90 - 2020-01-03365Benchwarmers-Werewolves-
91 - 2020-01-04370Werewolves-Hooligans-
94 - 2020-01-07379Werewolves-Casse-Tete-
96 - 2020-01-09383Hybrides-Werewolves-
98 - 2020-01-11394Benchwarmers-Werewolves-
102 - 2020-01-15407Royaux-Werewolves-
103 - 2020-01-16411Werewolves-Caribou-
105 - 2020-01-18420Werewolves-Hybrides-
107 - 2020-01-20427Werewolves-Barracuda-
108 - 2020-01-21432Barracuda-Werewolves-
110 - 2020-01-23441Diabotins-Werewolves-
112 - 2020-01-25448Werewolves-Leftovers-
114 - 2020-01-27452Werewolves-Chevalier-
115 - 2020-01-28460Royaux-Werewolves-
118 - 2020-01-31470Werewolves-Pirates-
119 - 2020-02-01475Chevalier-Werewolves-
121 - 2020-02-03485Werewolves-Diabotins-
122 - 2020-02-04490Jardiniers-Werewolves-
125 - 2020-02-07500Pirates-Werewolves-
129 - 2020-02-11512Barracuda-Werewolves-
131 - 2020-02-13521Werewolves-Leftovers-
134 - 2020-02-16527Leftovers-Werewolves-
137 - 2020-02-19539Werewolves-Jardiniers-
138 - 2020-02-20544Hybrides-Werewolves-
140 - 2020-02-22553Werewolves-Pirates-
142 - 2020-02-24559Hooligans-Werewolves-
144 - 2020-02-26570Benchwarmers-Werewolves-
146 - 2020-02-28579Werewolves-Barracuda-
148 - 2020-03-01587Casse-Tete-Werewolves-
150 - 2020-03-03591Werewolves-Caribou-
151 - 2020-03-04596Werewolves-Benchwarmers-
154 - 2020-03-07605Barracuda-Werewolves-
156 - 2020-03-09612Werewolves-Vagabond-
158 - 2020-03-11616Requins-Werewolves-
159 - 2020-03-12619Werewolves-Barracuda-
160 - 2020-03-13623Werewolves-Royaux-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
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
24 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,596,096$ 3,825,969$ 2,716,552$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
23,472$ 1,596,096$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 95 23,472$ 2,229,840$




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
2019372480212016682841814201010102327019106011106450145716629846402645147412094163873951711013883076151464228.77%1543279.22%246279258.33%45176758.80%30448562.68%876566792300573300
Total Saison Régulière287181590205111115996529471431012101118183029753314480380943107693554143711599286144600125574955163497203399310831101768422299928835888102128127.52%120122181.60%393568601159.36%3588601159.69%2493419259.47%705246405940229343942266
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