Connexion

Wolf Pack
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: NewStarRising | Morale : 40 | Moyenne d’équipe : 58
Prochain matchs #3 vs Crunch
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Crunch
0-0-0, 0pts
2022-09-13
Wolf Pack
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Wolf Pack
0-0-0, 0pts
2022-09-15
Wild
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Wolf Pack
0-0-0, 0pts
2022-09-16
Moose
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
0
0.00 GFG
Tirs pour
0
0.00 Avg
Pourcentage en avantage numérique
0.0%
0 GF
Début de zone offensive
0.0%
Buts contre
0
0.00 GAA
Tirs contre
0
0.00 Avg
Pourcentage en désavantage numérique
0.0%
0 GA
Début de la zone défensive
0.0%
Information d’équipe

Directeur généralNewStarRising
EntraîneurRoy Sommer
DivisionMetropolitan Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Information formation

Équipe Pro25
Équipe Mineure18
Limite contact 43 / 90
Espoirs23


Historique d'équipe

Saison actuelle0-0-0 (0PTS)
Historique54-84-22 (0.338%)
Apparitions séries éliminatoires 0
Historique séries éliminatoires (W-L)-
Stanley Cup0


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
1Taylor Raddysh0X100.007845916485797561536664656351620406202432,000,000$
2Bobby Brink (R)0X100.00803790747486506265755559585061040610213925,000$
3Dylan Sikura0XX100.005038766676605269607068616456650406102721,500,000$
4Garrett Pilon0XX100.00704375598160506156666362625665040590242900,000$
5Riley Barber0X100.006145755983604665406768596464710405902811,000,000$
6Alexander Nylander0X100.005043755782604560406463626255650405702411,500,000$
7Lukas Vejdemo0X100.00744577568360395654636063605363040570262750,000$
8Fredrik Karlstrom (R)0X100.00504475558460535760636162615161040560241850,000$
9Linus Weissbach (R)0X100.00503975597760455840646162615161040560241850,000$
10Brayden Tracey (R)0XX100.00504475597860475840656062605161040560212925,000$
11Daniel Walcott0X100.00504475577860415240605762596068040550281850,000$
12Spencer Watson0XXX100.00504075567860485240605862595666040550261850,000$
13Michal Kempny0X100.008043775782634266206359696061700406103221,000,000$
14Derrick Pouliot0X100.00674477578260466920685767595969040600282950,000$
15Darren Raddysh0X100.007045765484605269206462676157660406002611,000,000$
16Declan Chisholm (R)0X100.00564175588160477120666367625262040590222825,000$
17Ian McCoshen0X100.00505475498860386520625768595464040570271850,000$
18Peter DiLiberatore (R)0X100.00504175568060316820645968605161040570222900,000$
Rayé
1Grant Mismash (R)0X100.00504175558060355240605762595161040540232850,000$
2Kale Howarth (R)0XXX100.00505575528660105340605962605060040530251850,000$
3Kasper Bjorkqvist (R)0X100.00504575528360325240595862595262040530251850,000$
4Ty Pelton-Byce (R)0XXX100.00504475528360105160605662585161040520252750,000$
5Jake Massie0X100.00505575518460136420595868595161040550251750,000$
MOYENNE D’ÉQUIPE100.0058447757816241603964606460546404057
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
1Michael DiPietro100.0062686583666664666663656867040650
2Antoine Bibeau100.0050585587545453545451537671040580
Rayé
MOYENNE D’ÉQUIPE100.005663608560605960605759726904062
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Roy Sommer75757575757575USA658500,000$


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 restantSalaire moyenSalaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Alexander NylanderWolf Pack (NYR)RW243/2/1998No192 Lbs6 ft1NoNoNo1Pro & Farm1,500,000$1,484,127$1,500,000$1,484,127$0$0$NoLien
Antoine Bibeau (contrat à 1 volet)Wolf Pack (NYR)G287/1/1994No205 Lbs6 ft3NoNoNo1Pro & Farm1,500,000$1,484,127$1,500,000$1,484,127$375,000$371,032$NoLien
Bobby BrinkWolf Pack (NYR)RW217/8/2001Yes166 Lbs5 ft8NoNoNo3Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$925,000$Lien
Brayden TraceyWolf Pack (NYR)LW/RW215/28/2001Yes177 Lbs6 ft0NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Daniel WalcottWolf Pack (NYR)LW282/19/1994No175 Lbs6 ft1NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Darren RaddyshWolf Pack (NYR)D262/28/1996No200 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Declan ChisholmWolf Pack (NYR)D221/12/2000Yes185 Lbs6 ft1NoNoNo2Pro & Farm825,000$816,270$825,000$816,270$0$0$No825,000$Lien
Derrick PouliotWolf Pack (NYR)D281/16/1994No196 Lbs6 ft0NoNoNo2Pro & Farm950,000$939,947$950,000$939,947$0$0$No950,000$Lien
Dylan Sikura (contrat à 1 volet)Wolf Pack (NYR)C/RW276/1/1995No170 Lbs5 ft11NoNoNo2Pro & Farm1,500,000$1,484,127$1,500,000$1,484,127$375,000$371,032$No1,500,000$Lien
Fredrik KarlstromWolf Pack (NYR)C241/12/1998Yes195 Lbs6 ft3NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Garrett PilonWolf Pack (NYR)C/RW244/13/1998No191 Lbs6 ft0NoNoNo2Pro & Farm900,000$890,476$900,000$890,476$0$0$No900,000$Lien
Grant MismashWolf Pack (NYR)LW232/19/1999Yes184 Lbs6 ft1NoNoNo2Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$Lien
Ian McCoshenWolf Pack (NYR)D278/5/1995No215 Lbs6 ft3NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Jake MassieWolf Pack (NYR)D251/21/1997No200 Lbs6 ft1NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Kale HowarthWolf Pack (NYR)C/LW/RW256/10/1997Yes201 Lbs6 ft5NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Kasper BjorkqvistWolf Pack (NYR)RW257/18/1997Yes198 Lbs6 ft1NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Linus WeissbachWolf Pack (NYR)LW244/19/1998Yes177 Lbs5 ft9NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Lukas VejdemoWolf Pack (NYR)C261/25/1996No198 Lbs6 ft1NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Michael DiPietroWolf Pack (NYR)G236/9/1999No201 Lbs6 ft0NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Michal Kempny (contrat à 1 volet)Wolf Pack (NYR)D329/8/1990No192 Lbs6 ft1NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Peter DiLiberatoreWolf Pack (NYR)D223/31/2000Yes184 Lbs6 ft0NoNoNo2Pro & Farm900,000$890,476$900,000$890,476$0$0$No900,000$Lien
Riley BarberWolf Pack (NYR)RW282/7/1994No199 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Spencer WatsonWolf Pack (NYR)C/LW/RW264/25/1996No180 Lbs5 ft11NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Taylor Raddysh (contrat à 1 volet)Wolf Pack (NYR)RW242/18/1998No198 Lbs6 ft3NoNoNo3Pro & Farm2,000,000$1,978,836$2,000,000$1,978,836$875,000$865,741$No2,000,000$2,000,000$Lien
Ty Pelton-ByceWolf Pack (NYR)C/LW/RW254/14/1997Yes194 Lbs6 ft2NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2525.12191 Lbs6 ft11.56996,000$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Taylor RaddyshRiley BarberDylan Sikura40122
2Garrett PilonBobby BrinkLukas Vejdemo30122
3Alexander NylanderRiley BarberBrayden Tracey20122
4Fredrik KarlstromLinus WeissbachDaniel Walcott10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Michal KempnyDarren Raddysh40122
2Derrick PouliotDeclan Chisholm30122
3Darren RaddyshPeter DiLiberatore20122
4Peter DiLiberatoreDarren Raddysh10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Dylan SikuraTaylor RaddyshRiley Barber60122
2Garrett PilonBobby BrinkLukas Vejdemo40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Peter DiLiberatoreDarren Raddysh60122
2Michal KempnyDeclan Chisholm40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Riley BarberTaylor Raddysh60122
2Dylan SikuraAlexander Nylander40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Peter DiLiberatoreDarren Raddysh60122
2Michal KempnyDerrick Pouliot40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Riley Barber60122Michal KempnyDarren Raddysh60122
2Brayden Tracey40122Peter DiLiberatoreDeclan Chisholm40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Riley BarberDylan Sikura60122
2Taylor RaddyshFredrik Karlstrom40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Peter DiLiberatoreDarren Raddysh60122
2Derrick PouliotMichal Kempny40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dylan SikuraTaylor RaddyshRiley BarberMichal KempnyDarren Raddysh
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dylan SikuraTaylor RaddyshRiley BarberMichal KempnyDarren Raddysh
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Riley Barber, Linus Weissbach, Daniel WalcottTaylor Raddysh, Bobby BrinkRiley Barber
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Darren Raddysh, Ian McCoshen, Peter DiLiberatoreDarren RaddyshDarren Raddysh, Peter DiLiberatore
Tirs de pénalité
Riley Barber, Linus Weissbach, Daniel Walcott, Taylor Raddysh, Bobby Brink
Gardien
#1 : Michael DiPietro, #2 : Antoine Bibeau
Lignes d’attaque personnalisées en prolongation
Linus Weissbach, Riley Barber, Daniel Walcott, Taylor Raddysh, Bobby Brink, Dylan Sikura, Dylan Sikura, Garrett Pilon, Alexander Nylander, Lukas Vejdemo, Brayden Tracey
Lignes de défense personnalisées en prolongation
Peter DiLiberatore, Darren Raddysh, Michal Kempny, Derrick Pouliot, Declan Chisholm


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
TotalDomicileVisiteur
# 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 pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
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 matchs 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
5 - 2022-09-133Crunch-Wolf Pack-
7 - 2022-09-1517Wolf Pack-Wild-
8 - 2022-09-1623Wolf Pack-Moose-
11 - 2022-09-1939Gulls-Wolf Pack-
14 - 2022-09-2264Barracuda-Wolf Pack-
17 - 2022-09-2589Monsters-Wolf Pack-
19 - 2022-09-2799Eagles-Wolf Pack-
20 - 2022-09-28108Wolf Pack-Islanders-
23 - 2022-10-01127Wolf Pack-Stars-
24 - 2022-10-02141Wolf Pack-Roadrunners-
26 - 2022-10-04149Phantoms-Wolf Pack-
28 - 2022-10-06161Bruins-Wolf Pack-
31 - 2022-10-09190Griffins-Wolf Pack-
33 - 2022-10-11198Islanders-Wolf Pack-
35 - 2022-10-13217Wolf Pack-Griffins-
37 - 2022-10-15232Wolf Pack-Admirals-
38 - 2022-10-16240Roadrunners-Wolf Pack-
42 - 2022-10-20271Wolf Pack-Firebirds-
44 - 2022-10-22288Wolf Pack-Barracuda-
47 - 2022-10-25302Wolf Pack-Reign-
48 - 2022-10-26314Wolf Pack-Gulls-
51 - 2022-10-29332Condors-Wolf Pack-
53 - 2022-10-31346Comets-Wolf Pack-
55 - 2022-11-02362Wolf Pack-Senators-
57 - 2022-11-04376Senators-Wolf Pack-
58 - 2022-11-05387IceHogs-Wolf Pack-
60 - 2022-11-07398Thunderbirds-Wolf Pack-
62 - 2022-11-09417Wolf Pack-Silver Knights-
64 - 2022-11-11430Wolf Pack-Eagles-
67 - 2022-11-14450Comets-Wolf Pack-
70 - 2022-11-17476Marlies-Wolf Pack-
72 - 2022-11-19489Wolf Pack-Phantoms-
73 - 2022-11-20499Wolf Pack-IceHogs-
75 - 2022-11-22511Wolf Pack-Penguins-
77 - 2022-11-24527Islanders-Wolf Pack-
82 - 2022-11-29549Bears-Wolf Pack-
84 - 2022-12-01565Wolf Pack-Crunch-
87 - 2022-12-04591Wolf Pack-Checkers-
89 - 2022-12-06600Wolves-Wolf Pack-
91 - 2022-12-08613Wolf Pack-Rocket-
93 - 2022-12-10628Wolf Pack-Comets-
96 - 2022-12-13649Wild-Wolf Pack-
98 - 2022-12-15663Stars-Wolf Pack-
101 - 2022-12-18691Rocket-Wolf Pack-
102 - 2022-12-19701Wolf Pack-Monsters-
105 - 2022-12-22718Bruins-Wolf Pack-
109 - 2022-12-26751Checkers-Wolf Pack-
111 - 2022-12-28767Wolf Pack-Marlies-
113 - 2022-12-30784Silver Knights-Wolf Pack-
123 - 2023-01-09809Heat-Wolf Pack-
125 - 2023-01-11819Canucks-Wolf Pack-
127 - 2023-01-13828Firebirds-Wolf Pack-
128 - 2023-01-14841Wolf Pack-Wolves-
132 - 2023-01-18869Wolf Pack-Canucks-
134 - 2023-01-20881Wolf Pack-Condors-
135 - 2023-01-21891Wolf Pack-Heat-
137 - 2023-01-23907Moose-Wolf Pack-
140 - 2023-01-26925Wolf Pack-Griffins-
142 - 2023-01-28937Wolf Pack-Bears-
143 - 2023-01-29950Reign-Wolf Pack-
146 - 2023-02-01968Wolf Pack-Phantoms-
147 - 2023-02-02976Senators-Wolf Pack-
149 - 2023-02-04991Wolf Pack-Bruins-
154 - 2023-02-091028Wolf Pack-Rocket-
156 - 2023-02-111040Wolf Pack-Americans-
157 - 2023-02-121054Wolf Pack-Penguins-
159 - 2023-02-141067Bears-Wolf Pack-
161 - 2023-02-161082Penguins-Wolf Pack-
163 - 2023-02-181103Penguins-Wolf Pack-
164 - 2023-02-191112Admirals-Wolf Pack-
166 - 2023-02-211120Wolves-Wolf Pack-
168 - 2023-02-231138Wolf Pack-Wolves-
170 - 2023-02-251156Wolf Pack-Checkers-
173 - 2023-02-281176Monsters-Wolf Pack-
175 - 2023-03-021191Wolf Pack-Comets-
176 - 2023-03-031200Wolf Pack-Americans-
178 - 2023-03-051217Wolf Pack-Bears-
181 - 2023-03-081241Crunch-Wolf Pack-
182 - 2023-03-091251Wolf Pack-Thunderbirds-
184 - 2023-03-111264Wolf Pack-Monsters-
186 - 2023-03-131276Americans-Wolf Pack-
189 - 2023-03-161304Marlies-Wolf Pack-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 0 - 0.00%0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
20,000$ 1,890,000$ 1,890,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,000$ 20,000$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 187 10,000$ 1,870,000$




TotalDomicileVisiteur
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
11821842081013165222-574110210521282108-26418210380183114-3167165273438582961661219154897036805422497482571734873034.48%1064260.38%2632130348.50%653132549.28%47294450.00%150666515848411869937
11821842081013165222-574110210521282108-26418210380183114-3167165273438582961661219154897036805422497482571734873034.48%1064260.38%2632130348.50%653132549.28%47294450.00%150666515848411869937
Total Saison régulière16436840162026330444-114822042010424164216-52821642061602166228-62134330546876101658122132243830978140613601084498149651434681746034.48%2128460.38%41264260648.50%1306265049.28%944188850.00%301213313168168237391874