Wolves

GP: 4 | W: 0 | L: 4 | OTL: 0 | P: 0
GF: 4 | GA: 21 | PP%: 9.09% | PK%: 91.67%
DG: Jean-François Misson | Morale : 47 | Moyenne d'Équipe : N/A
Prochain matchs #87 vs Griffins
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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
1Zach Aston-Reese (R)X100.0090558576747169735064686655625014800
2Beau BennettX100.0083557882777078655060606055777615100
3Daniel O'ReganX100.0067556572636075675060606355737515100
4Derek GrantX100.0079558774868072779170747755767815100
5Jujhar KhairaX100.0060556673797554777567727955605915100
6Corey TroppX100.0056555555565757555055555555737015100
7Tommy WingelsX100.0084557578747882767565707655767414800
8Ryan BourqueX100.0060556660625969555055555955505015100
9Teemu PulkkinenX100.0056555555555555555055555555555514800
10Tim SchallerX100.0091556575787776737166728155606015100
11Pontus AbergX100.0069556682686367746072616955707015100
12Scott LaughtonX100.0091557375817285778866707755737414800
13Ashton SautnerX100.0065556464757359612561606355535315100
14Brandon ManningX100.0086557482838283842570698155827114800
15Stephen JohnsX100.0097558181928282812564698955787514800
16Ryan CulkinX100.0055555560555557552555555555535315100
Rayé
1Andrej NestrasilX100.0055555555555555555055555555727214600
2Jimmy LodgeX100.0060556766646169555055555855505014600
3Tom KostopoulosX100.0056555555555555555055555555727214600
4Michael Spacek (R)X100.0056555555555555555055555555505014300
5Clark Bishop (R)X100.0056556661776766555055555555747314600
6Michael LattaX100.0057555771756969575056575555575814600
7Sam CarrickX100.0059555965686469595058595955505014600
MOYENNE D'ÉQUIPE100.006955666870676865536162655565641490
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
1Carter Hutton100.008888888589898788868555807814800
2Philipp Grubauer100.008487878989908789868955807814800
Rayé
1Curtis McElhinney100.008569719090908178807655807914300
MOYENNE D'ÉQUIPE100.00868182888990858584835580781460
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dave Cameron46656367754852CAN5922,555,500$


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
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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Andrej NestrasilWolves (VGK)C251991-02-21No200 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Ashton SautnerWolves (VGK)D221994-05-27No194 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Beau BennettWolves (VGK)RW251991-11-26No195 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Brandon ManningWolves (VGK)D261990-06-03No195 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Carter HuttonWolves (VGK)G311985-12-19No195 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm2,500,000$0$0$No2,500,000$
Clark BishopWolves (VGK)C201996-03-28Yes194 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Corey TroppWolves (VGK)RW271989-07-25No185 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Curtis McElhinneyWolves (VGK)G331983-05-23No205 Lbs6 ft3NoNoNo1Sans RestrictionPro & Farm2,500,000$0$0$No
Daniel O'ReganWolves (VGK)C221994-01-30No175 Lbs5 ft9NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Derek GrantWolves (VGK)C261990-04-20No206 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jimmy LodgeWolves (VGK)C211995-03-05No166 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm805,000$0$0$No
Jujhar KhairaWolves (VGK)C221994-08-13No214 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Michael LattaWolves (VGK)C251991-05-24No209 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Michael SpacekWolves (VGK)C191997-04-09Yes187 Lbs5 ft11NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Philipp GrubauerWolves (VGK)G251991-11-24No184 Lbs6 ft1NoNoNo2Avec RestrictionPro & Farm3,000,000$0$0$No3,000,000$
Pontus AbergWolves (VGK)LW231993-09-22No189 Lbs5 ft11NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Ryan BourqueWolves (VGK)LW261991-01-02No170 Lbs5 ft9NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$300,000$
Ryan CulkinWolves (VGK)D231993-12-14No201 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Sam CarrickWolves (VGK)C241992-02-03No188 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Scott LaughtonWolves (VGK)C221994-05-29No177 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm900,000$0$0$No
Stephen JohnsWolves (VGK)D241992-04-17No229 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm1,000,000$0$0$No
Teemu PulkkinenWolves (VGK)LW251992-01-01No183 Lbs5 ft11NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Tim SchallerWolves (VGK)LW261990-11-15No206 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Tom KostopoulosWolves (VGK)RW371979-01-23No197 Lbs6 ft0NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Tommy WingelsWolves (VGK)RW281988-04-11No200 Lbs6 ft0NoNoNo4Sans RestrictionPro & Farm1,000,000$0$0$No1,000,000$1,000,000$1,000,000$
Zach Aston-ReeseWolves (VGK)C221994-08-10Yes205 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2624.96194 Lbs6 ft12.00700,192$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
Gardien
#1 : , #2 :


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
1Admirals1010000026-41010000026-40000000000000.0002460020201926302503117812900.00%4175.00%0199120.88%4214728.57%125920.34%4528153304014
2Eagles20200000011-110000000000020200000011-1100.00000000202029263025093301921800.00%60100.00%0199120.88%4214728.57%125920.34%4528153304014
3Griffins1010000024-21010000024-20000000000000.0002460020203326302506513495240.00%20100.00%0199120.88%4214728.57%125920.34%4528153304014
Total40400000421-1720200000410-620200000011-1100.00048120020208126302501896031422229.09%12191.67%0199120.88%4214728.57%125920.34%4528153304014
_Since Last GM Reset40400000421-1720200000410-620200000011-1100.00048120020208126302501896031422229.09%12191.67%0199120.88%4214728.57%125920.34%4528153304014
_Vs Conference40400000421-1720200000410-620200000011-1100.00048120020208126302501896031422229.09%12191.67%0199120.88%4214728.57%125920.34%4528153304014

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
40L448128118960314200
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
4040000421
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2020000410
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2020000011
Derniers 10 Matchs
WLOTWOTL SOWSOL
040000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2229.09%12191.67%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
26302502020
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
199120.88%4214728.57%125920.34%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
4528153304014


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
3 - 2018-09-077Wolves0Eagles6LSommaire du Match
4 - 2018-09-0821Wolves0Eagles5LSommaire du Match
11 - 2018-09-1553Griffins4Wolves2LSommaire du Match
12 - 2018-09-1661Admirals6Wolves2LSommaire du Match
18 - 2018-09-2287Wolves-Griffins-
19 - 2018-09-2398Admirals-Wolves-
22 - 2018-09-26102Monsters-Wolves-
24 - 2018-09-28113Wolves-Stars-
26 - 2018-09-30133Wolves-Rampage-
31 - 2018-10-05148Wolves-Moose-
32 - 2018-10-06158Wolves-Moose-
36 - 2018-10-10174Wolves-Admirals-
39 - 2018-10-13200IceHogs-Wolves-
40 - 2018-10-14207Admirals-Wolves-
46 - 2018-10-20246Wild-Wolves-
47 - 2018-10-21251Moose-Wolves-
52 - 2018-10-26272Wolves-IceHogs-
53 - 2018-10-27286Griffins-Wolves-
54 - 2018-10-28294IceHogs-Wolves-
57 - 2018-10-31302Wolves-Griffins-
60 - 2018-11-03328Rampage-Wolves-
61 - 2018-11-04336Stars-Wolves-
64 - 2018-11-07346Wolves-Wild-
66 - 2018-11-09358Wolves-Wild-
67 - 2018-11-10367Wolves-IceHogs-
74 - 2018-11-17411Roadrunners-Wolves-
75 - 2018-11-18419Roadrunners-Wolves-
77 - 2018-11-20422Stars-Wolves-
80 - 2018-11-23443IceHogs-Wolves-
81 - 2018-11-24452Wolves-Admirals-
85 - 2018-11-28469Wolves-Admirals-
87 - 2018-11-30483Wolves-IceHogs-
88 - 2018-12-01495IceHogs-Wolves-
90 - 2018-12-03505Wolves-Wild-
92 - 2018-12-05514Wild-Wolves-
94 - 2018-12-07525Rampage-Wolves-
95 - 2018-12-08540Rampage-Wolves-
101 - 2018-12-14571Wolves-Roadrunners-
102 - 2018-12-15586Wolves-Roadrunners-
106 - 2018-12-19601Griffins-Wolves-
109 - 2018-12-22627IceHogs-Wolves-
110 - 2018-12-23635Admirals-Wolves-
114 - 2018-12-27653Wolves-Monsters-
116 - 2018-12-29675Wolves-Monsters-
122 - 2019-01-04691Wolves-IceHogs-
123 - 2019-01-05707Moose-Wolves-
130 - 2019-01-12734Wolves-Admirals-
131 - 2019-01-13754Wolves-Griffins-
134 - 2019-01-16766Wolves-Moose-
136 - 2019-01-18776Wolves-Moose-
138 - 2019-01-20798Wild-Wolves-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
142 - 2019-01-24814Stars-Wolves-
144 - 2019-01-26836Griffins-Wolves-
145 - 2019-01-27844Stars-Wolves-
147 - 2019-01-29847IceHogs-Wolves-
150 - 2019-02-01863Wolves-Stars-
151 - 2019-02-02877Wolves-Stars-
154 - 2019-02-05888Wolves-Rampage-
157 - 2019-02-08906Wolves-Admirals-
158 - 2019-02-09918Wild-Wolves-
159 - 2019-02-10928Admirals-Wolves-
164 - 2019-02-15950Monsters-Wolves-
165 - 2019-02-16964Rampage-Wolves-
169 - 2019-02-20981Wolves-IceHogs-
171 - 2019-02-22990Wolves-Stars-
172 - 2019-02-231003Wolves-Rampage-
175 - 2019-02-261016Wolves-Rampage-
178 - 2019-03-011030Wolves-Griffins-
179 - 2019-03-021049Admirals-Wolves-
180 - 2019-03-031056Wolves-IceHogs-
185 - 2019-03-081079Wolves-Admirals-
186 - 2019-03-091095Eagles-Wolves-
187 - 2019-03-101102Eagles-Wolves-
192 - 2019-03-151123Wolves-Wild-
193 - 2019-03-161137Moose-Wolves-
194 - 2019-03-171148Moose-Wolves-



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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
183,443$ 182,050$ 76,800$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 12,194$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 181 14,111$ 2,554,091$




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
1340400000421-1720200000410-620200000011-11048120020208126302501896031422229.09%12191.67%0199120.88%4214728.57%125920.34%4528153304014
Total Saison Régulière40400000421-1720200000410-620200000011-11048120020208126302501896031422229.09%12191.67%0199120.88%4214728.57%125920.34%4528153304014