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Connexion

Bears
GP: 15 | W: 9 | L: 5 | OTL: 1 | P: 19
GF: 62 | GA: 51 | PP%: 15.09% | PK%: 56.52%
DG: Jean-Manuel Estrada | Morale : 44 | Moyenne d’équipe : 65
Prochains matchs #212 vs Crunch

Centre de jeu
Bears
9-5-1, 19pts
5
2 Condors
5-9-1, 11pts
Team Stats
OTW1SéquenceL2
4-3-1Fiche domicile3-4-1
5-2-0Fiche domicile2-5-0
6-4-0Derniers 10 matchs3-6-1
4.13Buts par match 3.47
3.40Buts contre par match 4.20
15.09%Pourcentage en avantage numérique13.33%
56.52%Pourcentage en désavantage numérique78.72%
Moose
6-5-5, 17pts
4
5 Bears
9-5-1, 19pts
Team Stats
OTL1SéquenceOTW1
2-2-3Fiche domicile4-3-1
4-3-2Fiche domicile5-2-0
3-3-4Derniers 10 matchs6-4-0
3.56Buts par match 4.13
4.13Buts contre par match 3.40
17.24%Pourcentage en avantage numérique15.09%
79.31%Pourcentage en désavantage numérique56.52%
Bears
9-5-1, 19pts
Jour 35
Crunch
6-7-2, 14pts
Statistiques d’équipe
OTW1SéquenceW2
4-3-1Fiche domicile3-5-0
5-2-0Fiche visiteur3-2-2
6-4-010 derniers matchs5-4-1
4.13Buts par match 4.27
3.40Buts contre par match 4.27
15.09%Pourcentage en avantage numérique17.86%
56.52%Pourcentage en désavantage numérique77.78%
Thunderbirds
8-7-1, 17pts
Jour 36
Bears
9-5-1, 19pts
Statistiques d’équipe
L2SéquenceOTW1
4-3-0Fiche domicile4-3-1
4-4-1Fiche visiteur5-2-0
6-4-010 derniers matchs6-4-0
4.00Buts par match 4.13
4.00Buts contre par match 4.13
23.26%Pourcentage en avantage numérique15.09%
78.43%Pourcentage en désavantage numérique56.52%
Little Stars
6-6-3, 15pts
Jour 39
Bears
9-5-1, 19pts
Statistiques d’équipe
L1SéquenceOTW1
3-4-1Fiche domicile4-3-1
3-2-2Fiche visiteur5-2-0
4-4-210 derniers matchs6-4-0
3.53Buts par match 4.13
4.13Buts contre par match 4.13
26.42%Pourcentage en avantage numérique15.09%
78.26%Pourcentage en désavantage numérique56.52%
Meneurs d'équipe
Buts
Tanner Laczynski
11
Passes
Tanner Laczynski
18
Points
Tanner Laczynski
29
Plus/Moins
Cole Smith
9
Victoires
Garret Sparks
7
Pourcentage d’arrêts
Artyom Zagidulin
0.925

Statistiques d’équipe
Buts pour
62
4.13 GFG
Tirs pour
496
33.07 Avg
Pourcentage en avantage numérique
15.1%
8 GF
Début de zone offensive
37.3%
Buts contre
51
3.40 GAA
Tirs contre
496
33.07 Avg
Pourcentage en désavantage numérique
56.5%%
10 GA
Début de la zone défensive
34.5%
Informations de l'équipe

Directeur généralJean-Manuel Estrada
EntraîneurRon Wilson
DivisionJohn-Ahearne
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,775
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure19
Limite contact 48 / 250
Espoirs0


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
1Tanner Laczynski (R)X100.0067358179717970747278736479565246487102311,200,000$
2Eric KarlssonX100.008133757374737366707277636159543248700261800,000$
3Kevin RooneyX100.006745757367757369797276667660582948700271750,000$
4Cole SmithX100.007847886471656479727570666754553748700251800,000$
5Vladimir TkachevX100.006544807567766967586979667459573648690251700,000$
6Vincent DunnX100.006838776973627774727368656849513448680251700,000$
7Nicholas Caamano (R)X100.006543757267676970687367677447465148670222500,000$
8Nathan Bastian (R)X100.005545776266776772867267556445473648660232500,000$
9Blake Speers (R)X100.006539685973635867577178465845454048630232900,000$
10Isaac Ratcliffe (R)X100.007032805469726962616377536445445548630213500,000$
11Tim Gettinger (R)X100.006333705971656165556569407044444141600221600,000$
12Kirill Maksimov (R)X100.006327775776566664665971475543434948600213500,000$
13Tommy VannelliX100.006531897274737775588263786176513648730251900,000$
14Jesper PetterssonX100.006546766668716365666872606456512648660251675,000$
15Ryan GravesX100.006234777068697265467254715252522848660251675,000$
16Will Reilly (R)X100.004938807866506470277961564947463648640233600,000$
17David Farrance (R)X100.006036736162676362396960715143434844630213550,000$
18Mario Ferraro (R)X100.005836826163696762326846714444454238630223500,000$
Rayé
1Cole UllyX97.256737857369777374778274596954533433710251900,000$
2Oliver Tarnstrom (R)X100.005139624656535159484662524740406628520182500,000$
3Jeremy Michel (R)X100.005520635236523365554456447041415428510191500,000$
4Michael Prapavessis (R)X77.146833877470707170537660766061523830710242500,000$
5Emil Johansson (R)X67.786348807067716864617267705357513532670242750,000$
6Mackenze Stewart (R)X100.006049726563686462676870555548472928630242500,000$
7Zack Hayes (R)X100.006634616072675553275951584143435028590214500,000$
8Jakob Stenqvist (R)X100.005930776646496365417248554144443828580222500,000$
9Arvid Henrikson (R)X100.005430636765604653336156603444444128580222500,000$
MOYENNE D’ÉQUIPE97.86633776666667656657696661595048404165
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
1Garret Sparks99.00797683697276806069857169603152730271900,000$
2Artyom Zagidulin100.00726669787065626363636847504852650252900,000$
Rayé
MOYENNE D’ÉQUIPE99.5076717674717171626674705855405269
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ron Wilson83816466557149USA613650,000$


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
1Tanner LaczynskiBears (Was)C15111829-100272871184015.49%833822.592574490000111049.89%447142001.7102000241
2Nicholas CaamanoBears (Was)RW1561016-180261846101713.04%632121.42134648000091036.00%2553001.0000000110
3Tommy VannelliBears (Was)D151121320014363613142.78%2540927.32000552000018000%0917000.6300000000
4Cole SmithBears (Was)LW155712900262246172510.87%725717.17011133000071138.89%1854000.9301000110
5Eric KarlssonBears (Was)LW154711-280351135122611.43%627318.24123331000050058.82%1765000.8002000002
6Nathan BastianBears (Was)RW15561170010121771329.41%523715.85011025000000155.56%941000.9300000010
7Cole UllyBears (Was)LW646104401391710923.53%012621.10022116000042053.85%1383001.5811000101
8Kevin RooneyBears (Was)C15551082029185115259.80%026517.73101539000090056.59%182115000.7522000110
9Vincent DunnBears (Was)C1527930020132913166.90%418112.0800000000030044.57%9276000.9900000000
10Vladimir TkachevBears (Was)LW152680008154612214.35%219012.67011524000020033.33%374000.8411000001
11Emil JohanssonBears (Was)D825722082492322.22%1418523.2100012300005000%036000.7500000001
12Jesper PetterssonBears (Was)D1525721402319134815.38%1632121.422022370000300100.00%139000.4400000100
13Blake SpeersBears (Was)C1542622015220131720.00%11348.9500001000150050.00%4632000.8900000001
14Ryan GravesBears (Was)D15213920928138415.38%2129419.64101228000014100%0115000.2000000000
15Kirill MaksimovBears (Was)RW152133008883425.00%317611.7800001000000120.00%514000.3400000001
16David FarranceBears (Was)D110220205127340%414913.5900000000010000%026000.2700000000
17Will ReillyBears (Was)D1502232031110750%625517.0500002800006000%024000.1600000000
18Mackenze StewartBears (Was)D110110030100100.00%01010.030000000000100%000001.9900000000
19Michael PrapavessisBears (Was)D41015005642125.00%69824.5700001100001000%024000.2000000000
20Isaac RatcliffeBears (Was)LW1501110011310320%61288.540000200002000%111000.1600000000
21Tim GettingerBears (Was)LW121010003160116.67%2665.580000000000000%024000.3000000000
22Oliver TarnstromBears (Was)C1000000000000%000.150000000000000%00000000000000
23Zack HayesBears (Was)D1000000000000%055.450000000000000%00000000000000
24Mario FerraroBears (Was)D7000-200141120%88412.040000000000000%00400000000000
Statistiques d’équipe totales ou en moyenne276601031635546030230049617325712.10%150451316.35815233545600011237350.17%85996109000.7249000788
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
1Garret SparksBears (Was)137510.8933.407580043402210110.7789132110
2Artyom ZagidulinBears (Was)42000.9252.7315400793570000213000
Statistiques d’équipe totales ou en moyenne179510.8993.2991200504952671191515110


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 Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantPlafond 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
Artyom ZagidulinBears (Was)G251995-01-01RUSNo181 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm900,000$729,586$0$0$No900,000$--------900,000$--------No--------Lien
Arvid HenriksonBears (Was)D221998-01-01SWEYes212 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------Lien
Blake SpeersBears (Was)C231997-01-01CANYes185 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm900,000$729,586$0$0$No900,000$--------900,000$--------No--------Lien
Cole SmithBears (Was)LW251995-01-01CANNo195 Lbs6 ft3NoNoFree AgentNoNo12024-09-17FalseFalsePro & Farm800,000$648,521$0$0$No---------------------------Lien
Cole UllyBears (Was)LW251995-01-01CANNo185 Lbs5 ft11NoNoTrade2025-10-27NoNo12025-08-30FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
David FarranceBears (Was)D211999-01-01USAYes191 Lbs6 ft0NoNoFree AgentNoNo32024-09-17FalseFalsePro & Farm550,000$445,858$0$0$No550,000$550,000$-------550,000$550,000$-------NoNo-------Lien
Emil Johansson (sur la masse salariale)Bears (Was)D241996-01-01SWEYes189 Lbs5 ft11NoNoFree AgentNoNo22024-09-17FalseFalsePro & Farm750,000$607,988$0$0$Yes750,000$--------750,000$--------No--------Lien
Eric KarlssonBears (Was)LW261994-01-01SWENo161 Lbs5 ft11NoNoFree Agent2025-03-20NoNo12025-09-02FalseFalsePro & Farm800,000$648,521$0$0$No---------------------------Lien
Garret SparksBears (Was)G271993-01-01USANo207 Lbs6 ft2NoNoFree AgentNoNo12024-10-17FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
Isaac RatcliffeBears (Was)LW211999-01-01CANYes200 Lbs6 ft6NoNoFree AgentNoNo32024-09-17FalseFalsePro & Farm500,000$405,325$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
Jakob StenqvistBears (Was)D221998-01-01SWEYes179 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------Lien
Jeremy MichelBears (Was)LW192001-01-01CANYes176 Lbs6 ft1NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$405,325$0$0$No---------------------------Lien
Jesper PetterssonBears (Was)D251995-01-01SWENo189 Lbs5 ft9NoNoFree AgentNoNo12024-09-17FalseFalsePro & Farm675,000$547,189$0$0$No---------------------------Lien
Kevin RooneyBears (Was)C271993-01-01USANo190 Lbs6 ft2NoNoFree AgentNoNo12025-08-28FalseFalsePro & Farm750,000$607,988$0$0$No---------------------------Lien
Kirill MaksimovBears (Was)RW211999-01-01RUSYes207 Lbs6 ft2NoNoFree AgentNoNo32024-09-17FalseFalsePro & Farm500,000$405,325$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
Mackenze StewartBears (Was)D241996-01-01CANYes230 Lbs6 ft4NoNoFree AgentNoNo22024-09-17FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------Lien
Mario FerraroBears (Was)D221998-01-01CANYes209 Lbs6 ft0NoNoFree AgentNoNo32024-09-17FalseFalsePro & Farm500,000$405,325$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien
Michael Prapavessis (sur la masse salariale)Bears (Was)D241996-01-01CANYes185 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$405,325$0$0$Yes500,000$--------500,000$--------No--------Lien
Nathan BastianBears (Was)RW231997-01-01CANYes205 Lbs6 ft4NoNoTrade2025-10-27NoNo22025-10-01FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------Lien
Nicholas CaamanoBears (Was)RW221998-01-01CANYes201 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------Lien
Oliver TarnstromBears (Was)C182002-01-01SWEYes185 Lbs6 ft1NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$405,325$0$0$No500,000$--------500,000$--------No--------
Ryan GravesBears (Was)D251995-01-01CANNo225 Lbs6 ft4NoNoFree AgentNoNo12024-09-17FalseFalsePro & Farm675,000$547,189$0$0$No---------------------------Lien
Tanner LaczynskiBears (Was)C231997-01-01USAYes205 Lbs6 ft1NoNoTrade2024-10-17NoNo1FalseFalsePro & Farm1,200,000$972,781$0$0$No---------------------------Lien
Tim GettingerBears (Was)LW221998-01-01USAYes220 Lbs6 ft6NoNoFree AgentNoNo12024-10-19FalseFalsePro & Farm600,000$486,391$0$0$No---------------------------Lien
Tommy VannelliBears (Was)D251995-01-01USANo185 Lbs6 ft2NoNoFree AgentNoNo12024-09-17FalseFalsePro & Farm900,000$729,586$0$0$No---------------------------Lien
Vincent DunnBears (Was)C251995-01-01CANNo185 Lbs5 ft11NoNoFree AgentNoNo12025-08-28FalseFalsePro & Farm700,000$567,456$0$0$No---------------------------Lien
Vladimir TkachevBears (Was)LW251995-01-01RUSNo165 Lbs5 ft10NoNoTrade2025-08-28NoNo12024-09-18FalseFalsePro & Farm700,000$567,456$0$0$No---------------------------Lien
Will ReillyBears (Was)D231997-01-01CANYes196 Lbs6 ft2NoNoFree AgentNoNo32024-09-17FalseFalsePro & Farm600,000$486,391$0$0$No600,000$600,000$-------600,000$600,000$-------NoNo-------Lien
Zack HayesBears (Was)D211999-01-01CANYes222 Lbs6 ft3NoNoFree AgentNoNo42025-08-28FalseFalsePro & Farm500,000$405,325$0$0$No500,000$600,000$600,000$------500,000$600,000$600,000$------NoNoNo------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2923.28195 Lbs6 ft21.79665,517$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Eric KarlssonTanner LaczynskiNicholas Caamano40014
2Cole SmithKevin RooneyNathan Bastian30014
3Vladimir TkachevVincent DunnKirill Maksimov20014
4Isaac RatcliffeBlake SpeersTim Gettinger10023
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tommy VannelliJesper Pettersson40032
2Ryan GravesWill Reilly30032
3Mario FerraroDavid Farrance20032
4Tommy VannelliJesper Pettersson10032
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Eric KarlssonTanner LaczynskiNicholas Caamano60005
2Cole SmithKevin RooneyVladimir Tkachev40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tommy VannelliJesper Pettersson60023
2Ryan GravesWill Reilly40023
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Kevin RooneyNicholas Caamano60041
2Vincent DunnCole Smith40041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tommy VannelliJesper Pettersson60041
2Ryan GravesWill Reilly40041
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Kevin Rooney60050Tommy VannelliJesper Pettersson60050
2Vincent Dunn40050Ryan GravesWill Reilly40050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Tanner LaczynskiEric Karlsson60014
2Kevin RooneyCole Smith40014
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Tommy VannelliJesper Pettersson60032
2Ryan GravesWill Reilly40032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Eric KarlssonTanner LaczynskiNicholas CaamanoTommy VannelliJesper Pettersson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Eric KarlssonTanner LaczynskiNicholas CaamanoTommy VannelliJesper Pettersson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Tanner Laczynski, Kevin Rooney, Eric KarlssonTanner Laczynski, Eric KarlssonKevin Rooney
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Tommy Vannelli, Jesper Pettersson, Ryan GravesTommy VannelliTommy Vannelli, Jesper Pettersson
Tirs de pénalité
Tanner Laczynski, Eric Karlsson, Kevin Rooney, Cole Smith, Vladimir Tkachev
Gardien
#1 : Garret Sparks, #2 : Artyom Zagidulin
Lignes d’attaque personnalisées en prolongation
Tanner Laczynski, Eric Karlsson, Kevin Rooney, Cole Smith, Vladimir Tkachev, Vincent Dunn, Nicholas Caamano, Nathan Bastian, Blake Speers, Isaac Ratcliffe
Lignes de défense personnalisées en prolongation
Tommy Vannelli, Jesper Pettersson, Ryan Graves, Will Reilly, David Farrance


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
1Admirals42000110171072000011055022000000125770.875172845001625185131183152153171264488714214.29%4175.00%015631749.21%15029351.19%12524052.08%318179321139275138
2Checkers10000010321000000000001000001032121.0003250016251853218315215317299620300.00%3166.67%015631749.21%15029351.19%12524052.08%318179321139275138
3Condors422000002016421100000107321100000109140.500203656001625185131183152153171384416748337.50%8450.00%015631749.21%15029351.19%12524052.08%318179321139275138
4Moose10001000541100010005410000000000021.0005101500162518540183152153173872216233.33%110.00%015631749.21%15029351.19%12524052.08%318179321139275138
5Thunderbirds413000001316-320200000411-72110000095420.250132235101625185127183152153171343714841715.88%7357.14%015631749.21%15029351.19%12524052.08%318179321139275138
6Wolfpack11000000431110000004310000000000021.0004590016251853518315215317319016500.00%000%015631749.21%15029351.19%12524052.08%318179321139275138
Total156501120625111823011102830-274200010342113190.63362103165101625185496183152153174961504630253815.09%231056.52%015631749.21%15029351.19%12524052.08%318179321139275138
_Since Last GM Reset156501120625111823011102830-274200010342113190.63362103165101625185496183152153174961504630253815.09%231056.52%015631749.21%15029351.19%12524052.08%318179321139275138
_Vs Conference13550111055469713011102427-364200000311912150.5775596151101625185429183152153174361324026645817.78%20955.00%015631749.21%15029351.19%12524052.08%318179321139275138
_Vs Division12550011050428613001101923-464200000311912130.5425086136101625185389183152153173981253824539615.38%19857.89%015631749.21%15029351.19%12524052.08%318179321139275138

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1519OTW1621031654964961504630210
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
156511206251
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
82311102830
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
74200103421
Derniers 10 matchs
WLOTWOTL SOWSOL
441010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
53815.09%231056.52%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
183152153171625185
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
15631749.21%15029351.19%12524052.08%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
318179321139275138


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
29Admirals4Bears3LXSommaire du match
321Bears5Admirals1WSommaire du match
425Bears5Condors7LSommaire du match
531Bears6Thunderbirds1WSommaire du match
850Admirals1Bears2WXXSommaire du match
1066Condors3Bears7WSommaire du match
1387Thunderbirds4Bears2LSommaire du match
1598Bears3Thunderbirds4LSommaire du match
17104Bears7Admirals4WSommaire du match
20123Wolfpack3Bears4WSommaire du match
22139Bears3Checkers2WXXSommaire du match
24150Thunderbirds7Bears2LSommaire du match
26162Condors4Bears3LSommaire du match
28174Bears5Condors2WSommaire du match
30188Moose4Bears5WXSommaire du match
35212Bears-Crunch-
36219Thunderbirds-Bears-
39238Little Stars-Bears-
41251Bears-Marlies-
43262Bears-Icehogs-
44270Penguins-Bears-
47289Bears-Comets-
48295Canucks-Bears-
51311Bears-Canucks-
52321Crunch-Bears-
55339Bears-Firebirds-
57349Senators-Bears-
59366Bears-Griffins-
60374Wolfpack-Bears-
62385Bears-Roadrunners-
64399Moose-Bears-
66412Bears-Eagles-
68424Penguins-Bears-
70436Bears-Americans-
71441Bears-Penguins-
73456Condors-Bears-
75471Bears-Punishers-
78484Icehogs-Bears-
80500Bears-Condors-
81508Islander-Bears-
84525Bears-Condors-
85533Comets-Bears-
87542Bears-Gulls-
88556Bears-Checkers-
90567Bears-Roadrunners-
91571Griffins-Bears-
94592Rockets-Bears-
97612Canucks-Bears-
100630Bears-Rockets-
101636Bears-Islander-
103647Icehogs-Bears-
104662Bears-Little Stars-
106671Firebirds-Bears-
109690Bears-Punishers-
110698Punishers-Bears-
114718Eagles-Bears-
116734Wranglers-Bears-
118745Bears-Thunderbirds-
121762Bears-Wranglers-
122769Marlies-Bears-
125790Bears-Senators-
126797Gulls-Bears-
130816Barracuda-Bears-
133837Roadrunners-Bears-
135845Bears-Admirals-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
138863Checkers-Bears-
139875Bears-Wolfpack-
141891Americans-Bears-
142894Bears-Thunderbirds-
145909Bears-Moose-
147922Little Stars-Bears-
149936Bears-Islander-
150942Bears-Barracuda-
153956Firebirds-Bears-
155970Admirals-Bears-
159992Admirals-Bears-
160994Bears-Wolfpack-
1611004Bears-Senators-
1641019Americans-Bears-
1671038Bears-Admirals-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance14,9317,271
Assistance PCT93.32%90.89%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
32 2775 - 92.51% 175,352$1,402,812$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
469,590$ 1,805,000$ 1,805,000$ 650,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,680$ 338,520$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
5,611,248$ 137 14,527$ 1,990,199$




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