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Bears
GP: 29 | W: 12 | L: 15 | OTL: 2 | P: 26
GF: 77 | GA: 93 | PP%: 15.85% | PK%: 81.16%
DG: Jeremy Pilon | Morale : 45 | Moyenne d’équipe : 63
Prochains matchs #475 vs BruinsF

Centre de jeu
Marlies
16-9-3, 35pts
1
3 Bears
12-15-2, 26pts
Team Stats
L2SéquenceL1
9-3-3Fiche domicile8-6-0
7-6-0Fiche domicile4-9-2
3-6-1Derniers 10 matchs4-5-1
3.04Buts par match 2.66
2.89Buts contre par match 3.21
25.93%Pourcentage en avantage numérique15.85%
80.23%Pourcentage en désavantage numérique81.16%
Bears
12-15-2, 26pts
1
3 Crunch
13-13-1, 27pts
Team Stats
L1SéquenceW1
8-6-0Fiche domicile9-6-0
4-9-2Fiche domicile4-7-1
4-5-1Derniers 10 matchs4-5-1
2.66Buts par match 3.67
3.21Buts contre par match 3.41
15.85%Pourcentage en avantage numérique26.92%
81.16%Pourcentage en désavantage numérique83.33%
BruinsF
17-11-1, 35pts
2025-10-30
Bears
12-15-2, 26pts
Statistiques d’équipe
W1SéquenceL1
11-3-0Fiche domicile8-6-0
6-8-1Fiche visiteur4-9-2
8-2-010 derniers matchs4-5-1
3.28Buts par match 2.66
3.03Buts contre par match 2.66
23.19%Pourcentage en avantage numérique15.85%
77.78%Pourcentage en désavantage numérique81.16%
Bears
12-15-2, 26pts
2025-11-01
Wranglers
17-12-1, 35pts
Statistiques d’équipe
L1SéquenceL1
8-6-0Fiche domicile8-7-0
4-9-2Fiche visiteur9-5-1
4-5-110 derniers matchs5-5-0
2.66Buts par match 3.37
3.21Buts contre par match 3.37
15.85%Pourcentage en avantage numérique23.91%
81.16%Pourcentage en désavantage numérique77.39%
Bears
12-15-2, 26pts
2025-11-03
Checkers
18-7-3, 39pts
Statistiques d’équipe
L1SéquenceW2
8-6-0Fiche domicile10-3-1
4-9-2Fiche visiteur8-4-2
4-5-110 derniers matchs7-2-1
2.66Buts par match 3.71
3.21Buts contre par match 3.71
15.85%Pourcentage en avantage numérique20.51%
81.16%Pourcentage en désavantage numérique90.54%
Meneurs d'équipe
Buts
Walker Duehr
8
Passes
Joshua Jacobs
16
Points
Joshua Jacobs
19
Plus/Moins
Greg Meireles
2
Victoires
Jakub Skarek
11
Pourcentage d’arrêts
Remi Poirier
0.957

Statistiques d’équipe
Buts pour
77
2.66 GFG
Tirs pour
837
28.86 Avg
Pourcentage en avantage numérique
15.9%
13 GF
Début de zone offensive
41.2%
Buts contre
93
3.21 GAA
Tirs contre
849
29.28 Avg
Pourcentage en désavantage numérique
81.2%%
13 GA
Début de la zone défensive
39.7%
Informations de l'équipe

Directeur généralJeremy Pilon
EntraîneurKevin Constantine
DivisionDivision Sud-Est
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison300


Informations de la formation

Équipe Pro26
Équipe Mineure20
Limite Contrat46 / 56
Espoirs30


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
1Denis Gurianov0XX96.00624993787382926864707062717758584967X02911,200,000$
2Ryan Spooner0XXX100.0059459969707578686168666763736226526503421,200,000$
3Jake Virtanen0XX100.0065459372767383716068686966736046526503031,200,000$
4Walker Duehr0X100.0067469380727181716269667360564754526502821,500,000$
5Greg Meireles0X100.006445957469667374757069716054476252640272900,000$
6Vladislav Kamenev0X100.0064458272697875697770686664575050426403031,000,000$
7Josh Leivo0XX100.0056459769727076696769666766705542536403311,200,000$
8Joni Ikonen0X100.006545877267707666756868636055495852630272800,000$
9Ivan Muranov0XX100.007345797373707072626665745848476252630271750,000$
10Joakim Nygard0XX100.006145937069677368626468676364463034620332900,000$
11Maxim Tsyplakov (R)0X100.007145927372698166506565695960454048620281900,000$
12Nikita Rtishchev (R)0XX100.006847886870505060576159635650516022580263750,000$
13Shakir Mukhamadullin0X100.006645907572797673457267776748466652670242900,000$
14Joshua Jacobs54X100.0062459371777471714568657263614742526503031,200,000$
15Andrei Mironov0X100.0066459070757375714569667264675238526503221,000,000$
16Michael Downing0X100.0066508569737468694565616854736150526403111,200,000$
17Artyom Minulin0X100.006744857271727563456563715654465452630281700,000$
18Linus Arnesson0X100.005945877172736068455748735553514629610321800,000$
Rayé
1Ville Koivunen (R)0X87.866345907368747768507166716350457042630233900,000$
2Cameron Hillis (R)0X100.006248727066707065706664686151536025610263750,000$
3Ronald Brickey0X100.007251837272736459455664705746465826610271500,000$
4Ryan O'rourke (R)0X100.006748857270505066456666736345457040610243750,000$
5Case Mccarthy (R)0X100.006647886870505061456371677145457021590253750,000$
MOYENNE D’ÉQUIPE99.26654689727170716856666569625850534463
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 SPÂgeContratSalaire
1Jakub Skarek099.00807676788178757776748047476649620261750,000$
2Ian Scott0100.00766867807675767676767346495460610272600,000$
Rayé
1Remi Poirier0100.00605858806062626262625845516638520252750,000$
MOYENNE D’ÉQUIPE99.6772676779727271727171704649624958
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Kevin Constantine62776267999915USA672100,000$


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
1Joshua JacobsBears (Was)D2931619-68029284220257.14%3263822.021341969000054100%000000.5900000102
2Walker DuehrBears (Was)LW298917010030338122619.88%655519.1523513680001541044.59%7400000.6100000110
3Greg MeirelesBears (Was)C2961117240134858123510.34%646215.960003210002484050.89%56000000.7300000312
4Michael DowningBears (Was)D292141612003617287217.14%2862421.551341368000050000%000000.5100000020
5Jake VirtanenBears (Was)LW/RW298715-580352472274611.11%251917.90011450000074144.44%6300000.5800000111
6Shakir MukhamadullinBears (Was)D295914-8100232948183610.42%4763621.960222168000252010%000000.4400000100
7Ryan SpoonerBears (Was)C/LW/RW29581322019345410379.26%452017.950116540000170046.00%51300000.5002000100
8Vladislav KamenevBears (Was)C297613-4100274158235012.07%148216.643141365000000149.83%59000000.5400000100
9Andrei MironovBears (Was)D294812-210021284916218.16%3862621.591122667000252000%000000.3800000000
10Maxim TsyplakovBears (Was)RW275712-310021204283211.90%639914.79000000001261044.83%2900000.6000000000
11Ryan LombergCapitalsLW/RW1946100141034204311339.30%530816.23022545000070142.50%4000000.6522011021
12Denis GurianovBears (Was)LW/RW22639-840232451113911.76%242819.47303947000000043.48%2300000.4202000021
13Artyom MinulinBears (Was)D29279-91003328174811.76%2548416.7011214000011010%000000.3700000000
14Ville KoivunenBears (Was)RW2144822012133462011.76%127212.9600000000000023.08%1300000.5900000012
15Josh LeivoBears (Was)LW/RW28178-400816357302.86%337213.310446550000150043.33%3000000.4300000000
16Ryan O'rourkeBears (Was)D15246-31351281461214.29%1124716.481011100000000%000000.4900001000
17Joni IkonenBears (Was)C29134-1340926295253.45%52809.67011150001420053.31%31700000.2900000000
18Ivan MuranovBears (Was)LW/RW29224-710023183811225.26%22699.30000020000140030.00%2000000.3000000010
19Filip HallanderCapitalsC/LW/RW8123-3209925764.00%213516.8800049000010044.19%12900000.4400000001
20Linus ArnessonBears (Was)D9022-220353000%615417.2100002000011000%000000.2600000000
21Ronald BrickeyBears (Was)D5011-460502130%107715.550000000001000%000000.2600000000
22Joakim NygardBears (Was)LW/RW10000100014010%1292.970000000000000%00000000000000
23Cameron HillisBears (Was)C4000-400304110%0379.4600000000000033.33%30000000000000
24Nikita RtishchevBears (Was)LW/RW6000-500326130%0488.1100000000000033.33%30000000000000
Statistiques d’équipe totales ou en moyenne52276136212-82159154314728372345679.08%243861316.50132336145709000947011548.44%240700000.492601291110
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
1Jakub SkarekBears (Was)24111120.8923.10137501716580000.6676244220
2Remi PoirierBears (Was)11000.9571.0060001230000010000
3Ian ScottBears (Was)60400.8813.81315002016800000425000
Statistiques d’équipe totales ou en moyenne31121520.8923.151751019284900062929220


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Andrei MironovBears (Was)D321994-07-29RUSNo211 Lbs6 ft2NoNoFree AgentNoNo22026-07-06FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien
Artyom MinulinBears (Was)D281998-01-10RUSNo196 Lbs6 ft3NoNoN/ANoNo12026-04-29FalseFalsePro & Farm700,000$0$0$No---------------------------Lien
Cameron HillisBears (Was)C262000-06-24CANYes174 Lbs5 ft9NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Case MccarthyBears (Was)D252001-09-01USAYes198 Lbs6 ft1NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Denis GurianovBears (Was)LW/RW291997-06-07RUSNo195 Lbs6 ft2NoYesN/ANoNo12026-04-29FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Greg MeirelesBears (Was)C271999-01-01CANNo180 Lbs5 ft10NoNoN/ANoNo22026-04-29FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Ian ScottBears (Was)G271999-01-11CANNo178 Lbs6 ft3NoNoN/ANoNo22026-04-29FalseFalsePro & Farm600,000$0$0$No600,000$--------600,000$--------No--------Lien
Ivan MuranovBears (Was)LW/RW271999-10-06RUSNo209 Lbs6 ft4NoNoProspectNoNo12024-06-18FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Jake VirtanenBears (Was)LW/RW301996-08-17CANNo227 Lbs6 ft1NoNoFree AgentNoNo32026-07-13FalseFalsePro & Farm1,200,000$0$0$No1,200,000$1,200,000$-------1,200,000$1,200,000$-------NoNo-------Lien
Jakub SkarekBears (Was)G261999-11-10CZENo206 Lbs6 ft4NoNoTrade2026-09-30NoNo12024-06-19FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Joakim NygardBears (Was)LW/RW331993-01-08SWENo190 Lbs5 ft11NoNoFree AgentNoNo22025-07-23FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Joni IkonenBears (Was)C271999-04-14FINNo172 Lbs5 ft11NoNoN/ANoNo22026-04-29FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien
Josh LeivoBears (Was)LW/RW331993-05-26CANNo192 Lbs6 ft2NoNoFree AgentNoNo12024-07-22FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Joshua JacobsBears (Was)D301996-02-15USANo227 Lbs6 ft2NoNoFree AgentNoNo32026-07-08FalseFalsePro & Farm1,200,000$0$0$No1,200,000$1,200,000$-------1,200,000$1,200,000$-------NoNo-------Lien
Linus ArnessonBears (Was)D321994-09-21SWENo188 Lbs6 ft1NoNoN/ANoNo12024-04-29FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Maxim TsyplakovBears (Was)RW281998-09-19RUSYes203 Lbs6 ft3NoNoTrade2026-05-11NoNo12026-05-11FalseFalsePro & Farm900,000$0$0$No---------900,000$900,000$----------------Lien
Michael DowningBears (Was)D311995-05-19USANo204 Lbs6 ft3NoNoN/ANoNo12024-04-29FalseFalsePro & Farm1,200,000$0$0$No---------------------------Lien
Nikita RtishchevBears (Was)LW/RW262000-05-23RUSYes196 Lbs6 ft2NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Remi PoirierBears (Was)G252001-10-06CANNo210 Lbs6 ft2NoNoFree AgentNoNo22025-08-14FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Ronald BrickeyBears (Was)D271999-05-27USANo207 Lbs6 ft3NoNoN/ANoNo12026-04-29FalseFalsePro & Farm500,000$0$0$No---------------------------Lien
Ryan O'rourkeBears (Was)D242002-05-16CANYes192 Lbs6 ft1NoNoProspectNoNo32026-05-15FalseFalsePro & Farm750,000$0$0$No750,000$750,000$-------750,000$750,000$-------NoNo-------Lien
Ryan SpoonerBears (Was)C/LW/RW341992-01-30CANNo198 Lbs5 ft11NoNoFree AgentNoNo22025-07-11FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Shakir MukhamadullinBears (Was)D242002-01-10RUSNo200 Lbs6 ft4NoNoProspectNoNo22025-05-07FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Ville Koivunen (sur la masse salariale)Bears (Was)RW232003-06-13FINYes184 Lbs6 ft0NoNoProspectNoNo32026-05-07FalseFalsePro & Farm900,000$0$0$Yes900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Vladislav KamenevBears (Was)C301996-08-12RUSNo185 Lbs6 ft2NoNoN/ANoNo32026-04-29FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------Lien
Walker DuehrBears (Was)LW281997-11-23USANo210 Lbs6 ft2NoNoFree AgentNoNo22025-05-28FalseFalsePro & Farm1,500,000$0$0$No1,500,000$--------1,500,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2628.15197 Lbs6 ft21.96917,308$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Denis GurianovVladislav KamenevJake Virtanen30122
2Walker DuehrRyan SpoonerJosh Leivo25122
3Ivan MuranovGreg MeirelesMaxim Tsyplakov25122
4Denis GurianovJoni IkonenRyan Spooner20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Shakir MukhamadullinAndrei Mironov35122
2Joshua JacobsMichael Downing35122
3Artyom MinulinLinus Arnesson30122
4Shakir MukhamadullinAndrei Mironov0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Denis GurianovRyan SpoonerJake Virtanen50122
2Walker DuehrVladislav KamenevJosh Leivo50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Shakir MukhamadullinAndrei Mironov50122
2Joshua JacobsMichael Downing50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Greg MeirelesJosh Leivo50122
2Walker DuehrIvan Muranov50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Shakir MukhamadullinAndrei Mironov50122
2Joshua JacobsMichael Downing50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Denis Gurianov50122Shakir MukhamadullinAndrei Mironov50122
2Jake Virtanen50122Joshua JacobsMichael Downing50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Vladislav KamenevJake Virtanen50122
2Greg MeirelesWalker Duehr50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Shakir MukhamadullinAndrei Mironov50122
2Joshua JacobsMichael Downing50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Denis GurianovRyan SpoonerJake VirtanenShakir MukhamadullinAndrei Mironov
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Denis GurianovRyan SpoonerJake VirtanenShakir MukhamadullinAndrei Mironov
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Greg Meireles, Ivan Muranov, Joni IkonenGreg Meireles, Ivan MuranovJoni Ikonen
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Artyom Minulin, Linus Arnesson, Joshua JacobsArtyom MinulinLinus Arnesson, Joshua Jacobs
Tirs de pénalité
Denis Gurianov, Jake Virtanen, Walker Duehr, Ryan Spooner, Vladislav Kamenev
Gardien
#1 : Jakub Skarek, #2 : Ian Scott


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
TotalDomicile Visiteur
# 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 RI
1Americans21100000330110000002111010000012-120.500369002723244452892442921848104294125.00%2150.00%047298248.07%46794849.26%22745549.89%696481676213380189
2Barracuda11000000321000000000001100000032121.00036900272324424289244292183711618200.00%3166.67%047298248.07%46794849.26%22745549.89%696481676213380189
3BruinsF1010000036-3000000000001010000036-300.00035800272324426289244292183476133133.33%30100.00%047298248.07%46794849.26%22745549.89%696481676213380189
4Checkers3210000011110220000008531010000036-340.6671121320027232447828924429218101201845600.00%9188.89%047298248.07%46794849.26%22745549.89%696481676213380189
5Crunch2020000027-5000000000002020000027-500.000246002723244532892442921855201226500.00%6266.67%047298248.07%46794849.26%22745549.89%696481676213380189
6Eagles1010000013-21010000013-20000000000000.00012300272324427289244292182496164125.00%3166.67%047298248.07%46794849.26%22745549.89%696481676213380189
7Firebirds1010000023-11010000023-10000000000000.0002350027232442928924429218169025100.00%000%047298248.07%46794849.26%22745549.89%696481676213380189
8Islanders513010001417-33110100011922020000038-540.400142539002723244131289244292181564035641218.33%15380.00%047298248.07%46794849.26%22745549.89%696481676213380189
9Marlies21001000743110000003121000100043141.000711180027232446328924429218461082610110.00%40100.00%047298248.07%46794849.26%22745549.89%696481676213380189
10Monsters1010000013-21010000013-20000000000000.00011200272324434289244292182710418400.00%20100.00%047298248.07%46794849.26%22745549.89%696481676213380189
11Moose11000000431110000004310000000000021.00048120027232442628924429218291271522100.00%10100.00%047298248.07%46794849.26%22745549.89%696481676213380189
12Phantoms1000000134-1000000000001000000134-110.50035800272324436289244292182174125120.00%2150.00%047298248.07%46794849.26%22745549.89%696481676213380189
13Rocket21100000743211000007430000000000020.500712190127232447628924429218641713358112.50%4175.00%047298248.07%46794849.26%22745549.89%696481676213380189
14SenatorsF1010000036-31010000036-30000000000000.000369002723244392892442921834102193133.33%10100.00%047298248.07%46794849.26%22745549.89%696481676213380189
15StarsF1010000025-3000000000001010000025-300.000235002723244182892442921841612143133.33%5180.00%047298248.07%46794849.26%22745549.89%696481676213380189
16Wolf Pack2010010058-3000000000002010010058-310.250510150027232447028924429218672612287228.57%5180.00%047298248.07%46794849.26%22745549.89%696481676213380189
17Wolves21000010642000000000002100001064241.0006814002723244622892442921849191028300.00%40100.00%047298248.07%46794849.26%22745549.89%696481676213380189
Total29915021117793-16147601000423841529011113555-20260.4487713621301272324483728924429218849243159431821315.85%691381.16%047298248.07%46794849.26%22745549.89%696481676213380189
_Since Last GM Reset29915021117793-16147601000423841529011113555-20260.4487713621301272324483728924429218849243159431821315.85%691381.16%047298248.07%46794849.26%22745549.89%696481676213380189
_Vs Conference25812021117080-10127401000403281318011113048-18240.4807012419401272324473428924429218720207131365691115.94%561082.14%047298248.07%46794849.26%22745549.89%696481676213380189

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2926L17713621383784924315943101
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2991521117793
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
147610004238
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
152911113555
Derniers 10 matchs
WLOTWOTL SOWSOL
351100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
821315.85%691381.16%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
289244292182723244
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
47298248.07%46794849.26%22745549.89%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
696481676213380189


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
1 - 2025-08-282Islanders1Bears5WSommaire du match
4 - 2025-08-3129Bears3Wolves2WSommaire du match
6 - 2025-09-0248Bears1Americans2LSommaire du match
7 - 2025-09-0360Bears1Islanders5LSommaire du match
8 - 2025-09-0468Islanders5Bears6WXSommaire du match
10 - 2025-09-0687Americans1Bears2WSommaire du match
14 - 2025-09-10112Bears3Phantoms4LXXSommaire du match
16 - 2025-09-12126Checkers4Bears6WSommaire du match
18 - 2025-09-14145SenatorsF6Bears3LSommaire du match
20 - 2025-09-16159Bears2Islanders3LSommaire du match
23 - 2025-09-19180Moose3Bears4WSommaire du match
25 - 2025-09-21194Bears3Barracuda2WSommaire du match
27 - 2025-09-23209Bears1Crunch4LSommaire du match
29 - 2025-09-25221Firebirds3Bears2LSommaire du match
31 - 2025-09-27241Rocket4Bears3LSommaire du match
32 - 2025-09-28250Bears3Wolves2WXXSommaire du match
37 - 2025-10-03278Bears3Checkers6LSommaire du match
38 - 2025-10-04289Monsters3Bears1LSommaire du match
41 - 2025-10-07304Bears2Wolf Pack4LSommaire du match
43 - 2025-10-09317Rocket0Bears4WSommaire du match
45 - 2025-10-11336Bears3Wolf Pack4LXSommaire du match
47 - 2025-10-13346Bears4Marlies3WXSommaire du match
48 - 2025-10-14357Checkers1Bears2WSommaire du match
51 - 2025-10-17378Bears3BruinsF6LSommaire du match
52 - 2025-10-18387Eagles3Bears1LSommaire du match
55 - 2025-10-21411Islanders3Bears0LSommaire du match
58 - 2025-10-24430Bears2StarsF5LSommaire du match
60 - 2025-10-26444Marlies1Bears3WSommaire du match
62 - 2025-10-28463Bears1Crunch3LSommaire du match
64 - 2025-10-30475BruinsF-Bears-
66 - 2025-11-01491Bears-Wranglers-
68 - 2025-11-03504Bears-Checkers-
69 - 2025-11-04515Islanders-Bears-
72 - 2025-11-07539BruinsF-Bears-
74 - 2025-11-09552Bears-Wolves-
76 - 2025-11-11568Bears-Firebirds-
78 - 2025-11-13581PenguinsF-Bears-
81 - 2025-11-16603Wolves-Bears-
83 - 2025-11-18620Bears-Phantoms-
85 - 2025-11-20636Moose-Bears-
87 - 2025-11-22651Bears-Admirals-
90 - 2025-11-25668Bears-Comets-
91 - 2025-11-26676Wolf Pack-Bears-
93 - 2025-11-28695Bears-Reign-
95 - 2025-11-30708Crunch-Bears-
99 - 2025-12-04733Gulls-Bears-
102 - 2025-12-07758Bears-Marlies-
104 - 2025-12-09767Crunch-Bears-
107 - 2025-12-12793Comets-Bears-
109 - 2025-12-14804Bears-Iowa Wild-
111 - 2025-12-16822Bears-Firebirds-
112 - 2025-12-17830Thunderbirds-Bears-
116 - 2025-12-21858Canucks-Bears-
118 - 2025-12-23870Bears-BruinsF-
120 - 2025-12-25888Americans-Bears-
122 - 2025-12-27904Bears-Rocket-
124 - 2025-12-29919Roadrunners-Bears-
126 - 2025-12-31930Bears-Barracuda-
128 - 2026-01-02943Bears-Rocket-
130 - 2026-01-04959Wolf Pack-Bears-
132 - 2026-01-06981Comets-Bears-
134 - 2026-01-08993Bears-Comets-
136 - 2026-01-101007Bears-Moose-
138 - 2026-01-121022SenatorsF-Bears-
140 - 2026-01-141039Bears-Moose-
142 - 2026-01-161051Bears-SenatorsF-
144 - 2026-01-181060Bears-PenguinsF-
145 - 2026-01-191068Marlies-Bears-
147 - 2026-01-211086Bears-Americans-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
149 - 2026-01-231099PenguinsF-Bears-
152 - 2026-01-261123Icehogs-Bears-
154 - 2026-01-281138Bears-Silver Knights-
155 - 2026-01-291145Bears-Americans-
158 - 2026-02-011163Condors-Bears-
160 - 2026-02-031178Bears-SenatorsF-
162 - 2026-02-051193Monsters-Bears-
165 - 2026-02-081212Bears-Gulls-
167 - 2026-02-101225Canucks-Bears-
171 - 2026-02-141252Wolves-Bears-
175 - 2026-02-181280Phantoms-Bears-
176 - 2026-02-191288Bears-PenguinsF-
179 - 2026-02-221310Bears-Griffins-
181 - 2026-02-241323Phantoms-Bears-
183 - 2026-02-261339Firebirds-Bears-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4530
Assistance28,00014,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
28 3000 - 100.00% 178,800$2,503,200$3000125

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
863,967$ 2,295,000$ 2,295,000$ 100,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 829,728$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,006,400$ 121 13,016$ 1,574,936$




Bears Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Bears Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Bears Statistiques de l'Équipe de Carrière

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

Bears Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Bears Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA