Connexion

Bears
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Karp | Morale : 40 | Moyenne d’équipe : 56
Prochain matchs #5 vs Bruins
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Bruins
0-0-0, 0pts
2022-09-14
Bears
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%
Bears
0-0-0, 0pts
2022-09-15
Marlies
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%
Rocket
0-0-0, 0pts
2022-09-17
Bears
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 généralKarp
EntraîneurDean Evason
DivisionMetropolitan Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Information formation

Équipe Pro26
Équipe Mineure18
Limite contact 44 / 90
Espoirs44


Historique d'équipe

Saison actuelle0-0-0 (0PTS)
Historique56-94-20 (0.329%)
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
1Parker Kelly0XX100.00994776638166626046626366625366040610231700,000$
2Maxim Mamin0XXX100.008047836286755859466665636352630406102711,000,000$
3Henrik Borgstrom0X100.005645825985766155606059656051610405802511,250,000$
4Austin Poganski0X100.00795076568360525740645961605465040570262875,000$
5Jake Lucchini0X100.00504175597960506140666262615363040570272750,000$
6Martin Kaut0X100.00704376588260456040636458625665040570231800,000$
7Mikey Eyssimont0X100.00504575607960366140666362625464040570262825,000$
8Cole Bardreau0X100.00504475568160235860636262616069040560292750,000$
9Tyler Madden (R)0XXX100.00504075597860266040656362625262040560222925,000$
10Rhett Gardner0X100.00755375518760545256615762595363040560261750,000$
11Aidan Dudas0XXX100.00503675607360395540625962605363040550222800,000$
12Mason Mannek (R)0XXX100.00505375577560505240605762595564040550222750,000$
13Chris Wideman0X100.005945806878766767207463696257660406403222,000,000$
14Robin Salo (R)0X100.00534380588362526820676067605262040590232850,000$
15Justin Barron (R)0X100.00594477568360447020656367625161040590202925,000$
16Nate Clurman (R)0X100.00504575518460396420605768595563040570241925,000$
17Niclas Almari0X100.00504075558060106420615868595161040550241925,000$
18Michael Karow (R)0X100.00504775518660106820646068605161040550232925,000$
Rayé
1Anatolii Golyshev (R)0X100.00504275567860105740616362625060040540272750,000$
2Carson Focht (R)0XXX100.00503975577860225260615662585161040530222895,000$
3Devante Smith-Pelly0X100.00505175488860105540615962605464040530302750,000$
4Zach Solow (R)0XXX100.00504075567760165240605762595664040530231925,000$
5Pierrick Dube (R)0X100.00503875577660105040605562585060040520213750,000$
6Brandon Scanlin (R)0X100.00504975478960106320605568585060040540232925,000$
MOYENNE D’ÉQUIPE100.0058447657816236593863606460536304056
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
1Mareks Mitens (R)100.0047625984515249525148507068040560
2Lukas Parik (R)100.0048625987525349535349516566040560
Rayé
MOYENNE D’ÉQUIPE100.004862598652534953524951686704056
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dean Evason75757575757575CAN588500,000$


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
Aidan DudasBears (WSH)C/LW/RW226/15/2000No164 Lbs5 ft7NoNoNo2Pro & Farm800,000$791,534$800,000$791,534$0$0$No800,000$Lien
Anatolii GolyshevBears (WSH)LW272/14/1995Yes187 Lbs5 ft8NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Austin PoganskiBears (WSH)RW262/16/1996No198 Lbs6 ft1NoNoNo2Pro & Farm875,000$865,741$875,000$865,741$0$0$No875,000$Lien
Brandon ScanlinBears (WSH)D236/2/1999Yes216 Lbs6 ft4NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Carson FochtBears (WSH)C/LW/RW222/4/2000Yes175 Lbs6 ft0NoNoNo2Pro & Farm895,000$885,529$895,000$885,529$0$0$No895,000$Lien
Chris Wideman (contrat à 1 volet)Bears (WSH)D321/7/1990No180 Lbs5 ft10NoNoNo2Pro & Farm2,000,000$1,978,836$2,000,000$1,978,836$875,000$865,741$No2,000,000$Lien
Cole BardreauBears (WSH)C297/22/1993No194 Lbs5 ft10NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Devante Smith-PellyBears (WSH)RW306/14/1992No223 Lbs6 ft0NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Henrik Borgstrom (contrat à 1 volet)Bears (WSH)C258/6/1997No199 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$1,236,772$1,250,000$1,236,772$125,000$123,677$NoLien
Jake LucchiniBears (WSH)LW275/9/1995No183 Lbs5 ft11NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Justin BarronBears (WSH)D2011/15/2001Yes195 Lbs6 ft2NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Lukas ParikBears (WSH)G213/15/2001Yes185 Lbs6 ft4NoNoNo3Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$750,000$Lien
Mareks MitensBears (WSH)G247/1/1998Yes185 Lbs6 ft1NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Martin KautBears (WSH)RW2310/2/1999No190 Lbs6 ft2NoNoNo1Pro & Farm800,000$791,534$800,000$791,534$0$0$NoLien
Mason MannekBears (WSH)C/LW/RW224/10/2000Yes173 Lbs5 ft8NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Maxim MaminBears (WSH)C/LW/RW271/13/1995No206 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Michael KarowBears (WSH)D2312/18/1998Yes209 Lbs6 ft2NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Mikey EyssimontBears (WSH)LW269/9/1996No180 Lbs6 ft0NoNoNo2Pro & Farm825,000$816,270$825,000$816,270$0$0$No825,000$Lien
Nate ClurmanBears (WSH)D245/8/1998Yes200 Lbs6 ft2NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Niclas AlmariBears (WSH)D245/11/1998No181 Lbs6 ft1NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Parker KellyBears (WSH)LW/RW235/14/1999No188 Lbs6 ft0NoNoNo1Pro & Farm700,000$692,593$700,000$692,593$0$0$NoLien
Pierrick DubeBears (WSH)RW211/7/2001Yes172 Lbs5 ft9NoNoNo3Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$750,000$Lien
Rhett Gardner (contrat à 1 volet)Bears (WSH)C262/28/1996No210 Lbs6 ft3NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Robin SaloBears (WSH)D2310/13/1998Yes192 Lbs6 ft2NoNoNo2Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$Lien
Tyler MaddenBears (WSH)C/LW/RW2211/9/1999Yes180 Lbs5 ft11NoNoNo2Pro & Farm925,000$915,212$925,000$915,212$0$0$No925,000$Lien
Zach SolowBears (WSH)C/LW/RW2311/6/1998Yes178 Lbs5 ft9NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2624.42190 Lbs6 ft01.73893,077$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Parker KellyMaxim MaminJake Lucchini40122
2Aidan DudasHenrik BorgstromAustin Poganski30122
3Parker KellyMikey EyssimontMartin Kaut20122
4Tyler MaddenParker KellyRhett Gardner10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Chris WidemanRobin Salo40122
2Nate ClurmanJustin Barron30122
3Justin BarronNate Clurman20122
4Niclas AlmariMichael Karow10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Maxim MaminParker KellyJake Lucchini60122
2Aidan DudasHenrik BorgstromMartin Kaut40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nate ClurmanRobin Salo60122
2Chris WidemanJustin Barron40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Parker KellyMaxim Mamin60122
2Jake LucchiniAidan Dudas40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nate ClurmanChris Wideman60122
2Robin SaloJustin Barron40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Parker Kelly60122Nate ClurmanRobin Salo60122
2Aidan Dudas40122Niclas AlmariJustin Barron40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Parker KellyJake Lucchini60122
2Aidan DudasMaxim Mamin40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Chris WidemanNate Clurman60122
2Michael KarowJustin Barron40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Parker KellyMaxim MaminJake LucchiniChris WidemanRobin Salo
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Parker KellyMaxim MaminJake LucchiniChris WidemanRobin Salo
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Parker Kelly, Mikey Eyssimont, Aidan DudasAidan Dudas, Parker KellyParker Kelly
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Justin Barron, Nate Clurman, Chris WidemanJustin BarronNate Clurman, Justin Barron
Tirs de pénalité
Mikey Eyssimont, Aidan Dudas, Austin Poganski, Parker Kelly, Tyler Madden
Gardien
#1 : Lukas Parik, #2 : Mareks Mitens
Lignes d’attaque personnalisées en prolongation
Mikey Eyssimont, Austin Poganski, Rhett Gardner, Tyler Madden, Maxim Mamin, Parker Kelly, Parker Kelly, Aidan Dudas, Jake Lucchini, Henrik Borgstrom, Martin Kaut
Lignes de défense personnalisées en prolongation
Chris Wideman, Nate Clurman, Robin Salo, Justin Barron, Michael Karow


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
6 - 2022-09-145Bruins-Bears-
7 - 2022-09-1515Bears-Marlies-
9 - 2022-09-1729Rocket-Bears-
11 - 2022-09-1943Canucks-Bears-
14 - 2022-09-2265Bears-Senators-
16 - 2022-09-2480Reign-Bears-
18 - 2022-09-2693Bears-Comets-
21 - 2022-09-29117Bears-Stars-
23 - 2022-10-01136Bears-Admirals-
25 - 2022-10-03145Bears-Wolves-
26 - 2022-10-04150Silver Knights-Bears-
28 - 2022-10-06164Bears-Griffins-
30 - 2022-10-08179Roadrunners-Bears-
32 - 2022-10-10195Condors-Bears-
34 - 2022-10-12208Penguins-Bears-
36 - 2022-10-14222Crunch-Bears-
38 - 2022-10-16242Bears-Crunch-
40 - 2022-10-18253Bears-Checkers-
42 - 2022-10-20269Bears-Thunderbirds-
44 - 2022-10-22279Eagles-Bears-
48 - 2022-10-26312Phantoms-Bears-
50 - 2022-10-28322Heat-Bears-
51 - 2022-10-29336Bears-Comets-
54 - 2022-11-01359Bears-Canucks-
56 - 2022-11-03374Bears-Firebirds-
58 - 2022-11-05390Bears-Heat-
60 - 2022-11-07400Bears-Condors-
62 - 2022-11-09413Bears-Phantoms-
64 - 2022-11-11427Firebirds-Bears-
66 - 2022-11-13446Bears-Moose-
68 - 2022-11-15463Bears-IceHogs-
70 - 2022-11-17471Stars-Bears-
72 - 2022-11-19491Marlies-Bears-
74 - 2022-11-21503Griffins-Bears-
77 - 2022-11-24528Bears-Senators-
78 - 2022-11-25537Moose-Bears-
82 - 2022-11-29549Bears-Wolf Pack-
84 - 2022-12-01566Senators-Bears-
86 - 2022-12-03581Rocket-Bears-
89 - 2022-12-06599Americans-Bears-
91 - 2022-12-08617Bears-Monsters-
92 - 2022-12-09622Admirals-Bears-
94 - 2022-12-11639Monsters-Bears-
97 - 2022-12-14659Bears-Phantoms-
100 - 2022-12-17681Phantoms-Bears-
102 - 2022-12-19702Bears-Islanders-
103 - 2022-12-20707Wild-Bears-
105 - 2022-12-22726Bears-Roadrunners-
107 - 2022-12-24745Bears-Silver Knights-
110 - 2022-12-27764Bears-Eagles-
112 - 2022-12-29773Penguins-Bears-
115 - 2023-01-01800Bears-Marlies-
117 - 2023-01-03804Bears-Monsters-
128 - 2023-01-14838Bears-Bruins-
129 - 2023-01-15847Barracuda-Bears-
131 - 2023-01-17855Wolves-Bears-
133 - 2023-01-19870Checkers-Bears-
135 - 2023-01-21889Bears-Wolves-
138 - 2023-01-24909Griffins-Bears-
140 - 2023-01-26920Gulls-Bears-
142 - 2023-01-28937Wolf Pack-Bears-
143 - 2023-01-29947Bears-Americans-
146 - 2023-02-01973Bears-Gulls-
149 - 2023-02-04992Bears-Barracuda-
151 - 2023-02-061011Bears-Reign-
154 - 2023-02-091029Comets-Bears-
156 - 2023-02-111048Bears-Islanders-
159 - 2023-02-141067Bears-Wolf Pack-
160 - 2023-02-151076Americans-Bears-
162 - 2023-02-171093Thunderbirds-Bears-
164 - 2023-02-191109Bears-Wild-
166 - 2023-02-211121Monsters-Bears-
168 - 2023-02-231135IceHogs-Bears-
170 - 2023-02-251162Bears-Penguins-
174 - 2023-03-011187Islanders-Bears-
175 - 2023-03-021194Bears-Crunch-
178 - 2023-03-051217Wolf Pack-Bears-
182 - 2023-03-091247Bears-Rocket-
184 - 2023-03-111262Checkers-Bears-
186 - 2023-03-131278Islanders-Bears-
187 - 2023-03-141290Bears-Bruins-
189 - 2023-03-161301Comets-Bears-



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
20,338$ 1,922,000$ 1,922,000$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,169$ 20,338$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 187 10,169$ 1,901,603$




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
11821447010740135208-7341924033206999-30415230742066109-4363135220355571954481818574547066714322947862041490842833.33%974058.76%1648131249.39%651139446.70%43689648.66%148164016318361851937
11821447010740135208-7341924033206999-30415230742066109-4363135220355571954481818574547066714322947862041490842833.33%974058.76%1648131249.39%651139446.70%43689648.66%148164016318361851937
Total Saison régulière16428940201480270416-14682184806640138198-60821046014840132218-861262704407101014381089636371490814121342864588157240829801685633.33%1948058.76%21296262449.39%1302278846.70%872179248.66%296312813263167237031874