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Bears
GP: 11 | W: 7 | L: 4 | OTL: 0 | P: 14
GF: 41 | GA: 41 | PP%: 30.61% | PK%: 75.61%
DG: Sebastien Cossette | Morale : 70 | Moyenne d’équipe : 66
Prochains matchs #192 vs Wolf Pack

Centre de jeu
Bears
7-4-0, 14pts
5
3 Thunderbirds
7-5-0, 14pts
Team Stats
W2SéquenceW1
5-1-0Fiche domicile4-2-0
2-3-0Fiche domicile3-3-0
6-4-0Derniers 10 matchs6-4-0
3.73Buts par match 3.17
3.73Buts contre par match 3.08
30.61%Pourcentage en avantage numérique18.00%
75.61%Pourcentage en désavantage numérique87.50%
Phantoms
3-8-1, 7pts
1
2 Bears
7-4-0, 14pts
Team Stats
L4SéquenceW2
2-3-0Fiche domicile5-1-0
1-5-1Fiche domicile2-3-0
3-6-1Derniers 10 matchs6-4-0
3.08Buts par match 3.73
3.58Buts contre par match 3.73
24.53%Pourcentage en avantage numérique30.61%
76.27%Pourcentage en désavantage numérique75.61%
Bears
7-4-0, 14pts
Jour 28
Wolf Pack
6-4-2, 14pts
Statistiques d’équipe
W2SéquenceL1
5-1-0Fiche domicile4-1-0
2-3-0Fiche visiteur2-3-2
6-4-010 derniers matchs5-3-2
3.73Buts par match 3.33
3.73Buts contre par match 3.33
30.61%Pourcentage en avantage numérique23.19%
75.61%Pourcentage en désavantage numérique78.72%
Bears
7-4-0, 14pts
Jour 29
Wolves
5-7-0, 10pts
Statistiques d’équipe
W2SéquenceW1
5-1-0Fiche domicile4-2-0
2-3-0Fiche visiteur1-5-0
6-4-010 derniers matchs4-6-0
3.73Buts par match 3.00
3.73Buts contre par match 3.00
30.61%Pourcentage en avantage numérique14.81%
75.61%Pourcentage en désavantage numérique80.49%
Penguins
10-2-0, 20pts
Jour 32
Bears
7-4-0, 14pts
Statistiques d’équipe
W5SéquenceW2
6-0-0Fiche domicile5-1-0
4-2-0Fiche visiteur2-3-0
8-2-010 derniers matchs6-4-0
3.08Buts par match 3.73
2.08Buts contre par match 3.73
18.03%Pourcentage en avantage numérique30.61%
85.11%Pourcentage en désavantage numérique75.61%
Meneurs d'équipe
Buts
Rory Kerins
6
Passes
Ryan Johnson
9
Points
Anton Frondell
13
Plus/Moins
Andy Welinski
3
Victoires
Devin Cooley
7
Pourcentage d’arrêts
Devin Cooley
0.865

Statistiques d’équipe
Buts pour
41
3.73 GFG
Tirs pour
328
29.82 Avg
Pourcentage en avantage numérique
30.6%
15 GF
Début de zone offensive
40.9%
Buts contre
41
3.73 GAA
Tirs contre
295
26.82 Avg
Pourcentage en désavantage numérique
75.6%%
10 GA
Début de la zone défensive
37.8%
Informations de l'équipe

Directeur généralSebastien Cossette
EntraîneurDerek Lalonde
DivisionAtlantic
ConférenceConference Est
Capitaine
Assistant #1
Assistant #2Philippe Maillet


Informations de l’aréna

Capacité3,000
Assistance1,524
Billets de saison300


Informations de la formation

Équipe Pro30
Équipe Mineure20
Limite Contrat50 / 99
Espoirs47


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
1Nicolas Deslauriers0XX100.0099873762767199674368666660889231706903512,215,000$
2Hudson Fasching0X99.0063299657827480705670736571818060706803112,000,000$
3Rory Kerins0XX100.007567897073778370806373676766656870680241900,000$
4Carl Grundstrom0XX100.0080369662766471861268866050595957706802821,855,000$
5Philippe Maillet (A)0X100.0059556969705868738467728060777611706803411,135,000$
6Anton Frondell (R)0XX100.005735767166778172637666637464658270670193900,000$
7Pierrick Dube0X100.0064578769685870704771736968666367706602521,534,000$
8Emil Bemstrom0XX100.0052199964726981706268695868757649706602731,525,000$
9Sheldon Rempal0XX100.0056479570695969754273736259646444706603111,381,000$
10Brendan Warren0XX100.0047189965746071664366676162797946706402921,238,000$
11Nick Cousins0XXX100.0057329968705293656969585460848544706403311,384,000$
12Ryan Wagner0XX100.005830896171617758466159716280784270630301975,000$
13Jonathan Castagna (R)0XX100.005940685960677162587068606550598270620213895,000$
14Sean Walker0X100.00582399607683896930766670558681237069N03131,190,000$
15Nikolai Knyzhov0X100.0094546163777976683071646950757541706902811,855,000$
16Mason Lohrei0X100.0063338663808378693076727565706857706902532,153,000$
17Josh Brown0X100.0083756162937780593064527247737430706803211,705,000$
18Nate Clurman0X100.0089877963766775636566666865757443706702811,301,000$
19Ryan Johnson0X100.0056379368757982662572526757666566706602531,551,000$
20Andy Welinski0X100.0057219961775282653069626149898443706503311,313,333$
21Broten Sabo (R)0X100.006440706366677364457653695555587270630242900,000$
Rayé
1Ben McCartney0XX100.0087725766766274605461636263666152706202531,216,000$
2Gerald Mayhew0XXX100.002920996969547560615170686575751170620331975,000$
3Axel Jonsson Fjallby0X100.0063269965736473606062606063757542706202831,272,000$
4Timothy Gettinger0X100.007432965984717756535554605374764370610281615,000$
5Tyson Empey0XX100.008469596476577353735651655978734170600311975,000$
6Riley Sutter0X100.007231966279617155615551605471715470590261961,000$
MOYENNE D’ÉQUIPE99.96674383647467776650676465607372487065
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
1Devin Cooley0100.007685818575747675747675677753707502912,025,000$
2Clay Stevenson0100.007161658172747675747574697666707202731,699,000$
3Kyle Keyser0100.006879777774666867666968768041707002731,673,000$
Rayé
MOYENNE D’ÉQUIPE100.0072757481747173727173727178537072
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Derek Lalonde76817564787372USA5443,250,000$


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
1Anton FrondellBears (WAS)C/LW115813040111721131823.81%115914.50145315000071044.00%10000001.6300000020
2Philippe MailletBears (WAS)C1147110407254211459.52%220618.732469370000160263.11%24400001.0700000010
3Ryan JohnsonBears (WAS)D11099260592050%615514.140000200005000%000001.1600000002
4Mason LohreiBears (WAS)D11279-3602317269197.69%1826223.892462044000130100%000000.6800000100
5Rory KerinsBears (WAS)C/LW11628-440271935143117.14%220919.0441511400001151250.29%17500000.7611000110
6Carl GrundstromBears (WAS)LW/RW11448-760182236162411.11%023121.05123641000225104.76%2100000.6901000010
7Sheldon RempalBears (WAS)LW/RW11178120414225154.55%112411.3010155000020042.86%700001.2900000101
8Hudson FaschingBears (WAS)RW11167-30099256194.00%023121.041238420001240048.72%3900000.6001000000
9Sean WalkerBears (WAS)D11167-240111517635.88%1925923.611341242000035000%000000.5400000000
10Pierrick DubeBears (WAS)RW11415-14012112361117.39%012611.5200001000081057.14%2100000.7900000110
11Emil BemstromBears (WAS)C/RW11145-320611126238.33%018216.57022633000060049.15%5900000.5500000001
12Nikolai KnyzhovBears (WAS)D314506015723150.00%26521.8911227000011000%000001.5200000002
13Nicolas DeslauriersBears (WAS)LW/RW54040140295130930.77%110320.651013120000151035.14%3700000.7700000100
14Brendan WarrenBears (WAS)C/LW110330201972120%1827.5000000000000044.44%5400000.7300000000
15Nick CousinsBears (WAS)C/LW/RW11213-220314102620.00%0867.8900000000000054.84%6200000.6900000010
16Josh BrownBears (WAS)D11022-760231263120%922520.53022338000027000%000000.1800000000
17Broten SaboBears (WAS)D91121206420050.00%2465.210000100002000%000000.8500000000
18Andy WelinskiBears (WAS)D81123404821350.00%09111.470000000001000%000000.4400000000
19Jonathan CastagnaBears (WAS)C/LW6011000001000%030.590111100000000%100005.6100000000
20Ryan WagnerBears (WAS)LW/RW111010005481512.50%1777.0800000000000020.00%500000.2600000000
21Ben McCartneyBears (WAS)LW/RW5000000000000%030.8000002000000050.00%20000000000000
22Nate ClurmanBears (WAS)D11000-715518125470%920118.32000330000018000%00000000010000
23Gerald MayhewBears (WAS)C/LW/RW2000000052100%0126.0500000000000043.75%160000000000000
24Axel Jonsson FjallbyBears (WAS)LW3000000000000%020.750000000000000%10000000000000
25Timothy GettingerBears (WAS)LW3000000100000%072.540000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne2203974113-3293523824931910926812.23%74316114.371526419240200052566450.95%84400000.7113010576
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
1Devin CooleyBears (WAS)117400.8653.5464400382820101.0003110000
2Clay StevensonBears (WAS)10000.7698.18220031300000011000
Statistiques d’équipe totales ou en moyenne127400.8613.69666004129501031111000


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
Andy WelinskiBears (WAS)D331993-04-27USANo210 Lbs6 ft1NoNoTrade2025-06-06NoNo12024-07-15FalseFalsePro & Farm1,313,333$0$0$No---------------------------
Anton FrondellBears (WAS)C/LW192007-05-07SWEYes201 Lbs6 ft1NoNoProspectNoNo32026-09-04FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Axel Jonsson FjallbyBears (WAS)LW281998-02-10SWENo194 Lbs6 ft0NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,272,000$0$0$No1,272,000$1,272,000$-------1,272,000$1,272,000$-------NoNo-------
Ben McCartneyBears (WAS)LW/RW252001-07-13CANNo205 Lbs6 ft0NoNoTrade2026-09-30NoNo32026-05-31FalseFalsePro & Farm1,216,000$0$0$No1,216,000$1,216,000$-------1,216,000$1,216,000$-------NoNo-------
Brendan WarrenBears (WAS)C/LW291997-05-07USANo196 Lbs6 ft0NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,238,000$0$0$No1,238,000$--------1,238,000$--------No--------
Broten SaboBears (WAS)D242002-08-09USAYes207 Lbs6 ft3NoNoFree AgentNoNo22026-06-22FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Carl GrundstromBears (WAS)LW/RW281997-12-01SWENo205 Lbs6 ft0NoNoFree AgentNoNo22025-06-02FalseFalsePro & Farm1,855,000$0$0$No1,855,000$--------1,855,000$--------No--------
Clay StevensonBears (WAS)G271999-03-03CANNo195 Lbs6 ft4NoNoFree AgentNoNo32026-05-31FalseFalsePro & Farm1,699,000$0$0$No1,699,000$1,699,000$-------1,699,000$1,699,000$-------NoNo-------
Devin CooleyBears (WAS)G291997-05-25USANo199 Lbs6 ft5NoNoTrade2026-03-02NoNo1FalseFalsePro & Farm2,025,000$0$0$No---------------------------
Emil BemstromBears (WAS)C/RW271999-06-01SWENo193 Lbs5 ft10NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,525,000$0$0$No1,525,000$1,525,000$-------1,525,000$1,525,000$-------NoNo-------
Gerald MayhewBears (WAS)C/LW/RW331992-12-31USANo178 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm975,000$0$0$No---------------------------
Hudson FaschingBears (WAS)RW311995-07-28USANo236 Lbs6 ft3NoNoFree AgentNoNo12024-07-09FalseFalsePro & Farm2,000,000$0$0$No---------------------------
Jonathan CastagnaBears (WAS)C/LW212005-04-20CANYes203 Lbs6 ft2NoNoProspectNoNo32026-09-04FalseFalsePro & Farm895,000$0$0$No895,000$895,000$-------895,000$895,000$-------NoNo-------
Josh BrownBears (WAS)D321994-01-21CANNo231 Lbs6 ft5NoNoTrade2024-09-12NoNo1FalseFalsePro & Farm1,705,000$0$0$No---------------------------
Kyle KeyserBears (WAS)G271999-03-08USANo195 Lbs6 ft2NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,673,000$0$0$No1,673,000$1,673,000$-------1,673,000$1,673,000$-------NoNo-------
Mason LohreiBears (WAS)D252001-01-17USANo215 Lbs6 ft4NoNoTrade2026-03-02NoNo32026-05-31FalseFalsePro & Farm2,153,000$0$0$No2,153,000$2,153,000$-------2,153,000$2,153,000$-------NoNo-------
Nate ClurmanBears (WAS)D281998-05-06USANo211 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm1,301,000$0$0$No---------------------------
Nick CousinsBears (WAS)C/LW/RW331993-07-20CANNo182 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,384,000$0$0$No---------------------------
Nicolas DeslauriersBears (WAS)LW/RW351991-02-22CANNo207 Lbs6 ft0NoNoTrade2026-03-07NoNo1FalseFalsePro & Farm2,215,000$0$0$No---------------------------
Nikolai KnyzhovBears (WAS)D281998-03-20RUSNo214 Lbs6 ft3NoNoTrade2026-09-30NoNo1FalseFalsePro & Farm1,855,000$0$0$No---------------------------
Philippe MailletBears (WAS)C341992-07-11CANNo176 Lbs5 ft9NoNoN/ANoNo1FalseFalsePro & Farm1,135,000$0$0$No---------------------------
Pierrick DubeBears (WAS)RW252001-01-07FRANo179 Lbs5 ft9NoNoTrade2026-01-02NoNo22025-05-25FalseFalsePro & Farm1,534,000$0$0$No1,534,000$--------1,534,000$--------No--------
Riley SutterBears (WAS)RW261999-10-25CANNo219 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm961,000$0$0$No---------------------------
Rory KerinsBears (WAS)C/LW242002-04-12CANNo192 Lbs5 ft11NoNoFree AgentNoNo12025-05-23FalseFalsePro & Farm900,000$0$0$No---------------------------
Ryan JohnsonBears (WAS)D252001-07-24USANo199 Lbs6 ft1NoNoN/ANoNo32026-05-31FalseFalsePro & Farm1,551,000$0$0$No1,551,000$1,551,000$-------1,551,000$1,551,000$-------NoNo-------
Ryan WagnerBears (WAS)LW/RW301996-04-15USANo200 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm975,000$0$0$No---------------------------
Sean WalkerBears (WAS)D311994-11-13CANNo208 Lbs5 ft11YesNoFree Agent2024-12-23NoNo32026-05-26FalseFalsePro & Farm1,190,000$0$0$No1,190,000$1,190,000$-------1,190,000$1,190,000$-------YesYes-------
Sheldon RempalBears (WAS)LW/RW311995-08-07CANNo175 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm1,381,000$0$0$No---------------------------
Timothy GettingerBears (WAS)LW281998-04-14USANo234 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm615,000$0$0$No---------------------------
Tyson EmpeyBears (WAS)C/LW311995-06-29CANNo209 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm975,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3028.23202 Lbs6 ft11.801,377,211$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anton FrondellRory KerinsCarl Grundstrom34023
2Sheldon RempalPhilippe MailletHudson Fasching30023
3Nicolas DeslauriersEmil BemstromPierrick Dube24131
4Brendan WarrenNick CousinsRyan Wagner12032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mason LohreiSean Walker40023
2Nikolai KnyzhovJosh Brown32041
3Nate ClurmanRyan Johnson24131
4Andy WelinskiBroten Sabo4041
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Anton FrondellRory KerinsCarl Grundstrom60005
2Sheldon RempalPhilippe MailletHudson Fasching40005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mason LohreiSean Walker60005
2Nikolai KnyzhovRyan Johnson40005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Philippe MailletHudson Fasching55050
2Rory KerinsPierrick Dube45050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mason LohreiJosh Brown55050
2Nikolai KnyzhovSean Walker45050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Philippe Maillet65050Mason LohreiJosh Brown60050
2Rory Kerins35050Nikolai KnyzhovSean Walker40050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Rory KerinsAnton Frondell55023
2Philippe MailletCarl Grundstrom45023
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Mason LohreiSean Walker55023
2Nikolai KnyzhovJosh Brown45032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Anton FrondellRory KerinsCarl GrundstromMason LohreiSean Walker
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nicolas DeslauriersPhilippe MailletPierrick DubeMason LohreiJosh Brown
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Emil Bemstrom, Pierrick Dube, Nicolas DeslauriersEmil Bemstrom, Pierrick DubeRyan Wagner
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nate Clurman, Ryan Johnson, Andy WelinskiRyan JohnsonRyan Johnson, Andy Welinski
Tirs de pénalité
Carl Grundstrom, Anton Frondell, Rory Kerins, Hudson Fasching, Pierrick Dube
Gardien
#1 : Devin Cooley, #2 : Clay Stevenson, #3 : Kyle Keyser


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
1Bruins210000101293110000007521000001054141.00012203200181382661291009576214164813646.15%7357.14%020238452.60%18335551.55%10319951.76%2791962448114273
2Hammers2110000078-1110000005321010000025-320.500714210018138255129100957531227498562.50%10370.00%020238452.60%18335551.55%10319951.76%2791962448114273
3Penguins1010000012-1000000000001010000012-100.0001230018138231129100957204223300.00%10100.00%020238452.60%18335551.55%10319951.76%2791962448114273
4Phantoms2110000059-4110000002111010000038-520.5005101500181382651291009574516164010220.00%7185.71%020238452.60%18335551.55%10319951.76%2791962448114273
5Rockets10001000541100010005410000000000021.000581300181382341291009572310102111100.00%5180.00%020238452.60%18335551.55%10319951.76%2791962448114273
6Thunderbirds211000007701010000024-21100000053220.5007132000181382471291009576081049500.00%5180.00%020238452.60%18335551.55%10319951.76%2791962448114273
7Wolves11000000422110000004220000000000021.00047110018138230129100957321014189111.11%6183.33%020238452.60%18335551.55%10319951.76%2791962448114273
Total115401010414106410100025196513000101622-6140.6364174115001813823281291009572957495248491530.61%411075.61%020238452.60%18335551.55%10319951.76%2791962448114273
_Since Last GM Reset115401010414106410100025196513000101622-6140.6364174115001813823281291009572957495248491530.61%411075.61%020238452.60%18335551.55%10319951.76%2791962448114273
_Vs Conference115401010414106410100025196513000101622-6140.6364174115001813823281291009572957495248491530.61%411075.61%020238452.60%18335551.55%10319951.76%2791962448114273

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1114W24174115328295749524800
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
115410104141
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
64110002519
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
51300101622
Derniers 10 matchs
WLOTWOTL SOWSOL
541000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
491530.61%411075.61%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
129100957181382
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
20238452.60%18335551.55%10319951.76%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2791962448114273


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
17Bears5Bruins4WXXSommaire du match
323Bruins5Bears7WSommaire du match
538Wolves2Bears4WSommaire du match
751Bears3Phantoms8LSommaire du match
1178Thunderbirds4Bears2LSommaire du match
1389Bears1Penguins2LSommaire du match
15107Hammers3Bears5WSommaire du match
18129Rockets4Bears5WXSommaire du match
21138Bears2Hammers5LSommaire du match
24160Bears5Thunderbirds3WSommaire du match
26177Phantoms1Bears2WSommaire du match
28192Bears-Wolf Pack-
29199Bears-Wolves-
32221Penguins-Bears-
34235Bears-Marlies-
36247Checkers-Bears-
40269Reign-Bears-
42286Bears-Wranglers-
44300Roadrunners-Bears-
46313Bears-Roadrunners-
48326Bears-Monsters-
50342Bears-Firebird-
51348Monsters-Bears-
54369Bears-Bruins-
55379Silver Knight-Bears-
60399Bears-Comets-
61411Admirals-Bears-
64435Bears-IceHogs-
65442Thunderbirds-Bears-
68460Bears-Americans-
70474Wild-Bears-
72488Bears-Reign-
74504Senators-Bears-
77515Bears-Penguins-
79529Bears-Thunderbirds-
80542Canucks-Bears-
83568Gulls-Bears-
85581Bears-Gulls-
87600Bears-Canucks-
89607Wranglers-Bears-
90624Bears-Rockets-
93639Comets-Bears-
97665Bears-Wild-
98670Griffins-Bears-
100692Bears-Hammers-
102701Barracuda-Bears-
105726Bears-Checkers-
106734Eagles-Bears-
109756Firebird-Bears-
111770Bears-Admirals-
113780Bears-Condors-
116794Penguins-Bears-
118811Bears-Barracuda-
121827Hammers-Bears-
124851Bears-Moose-
125861Americans-Bears-
128882Bears-Silver Knight-
129893Wolves-Bears-
132917Bears-Eagles-
134926Condors-Bears-
138948Stars-Bears-
141968Bears-Wolves-
143982Moose-Bears-
145997Bears-Senators-
1461006Bears-Griffins-
1481015Bears-Stars-
1491023Crunch-Bears-
1521047Bears-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1541055Phantoms-Bears-
1581078Bears-Crunch-
1591088IceHogs-Bears-
1631110Bears-Wolf Pack-
1641119Wolf Pack-Bears-
1691149Bruins-Bears-
1741181Wolf Pack-Bears-
1831209Marlies-Bears-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets10099
Assistance6,5602,584
Assistance PCT54.67%43.07%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 1524 - 50.80% 226,434$1,358,605$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,613,906$ 8,263,266$ 8,263,266$ 3,250,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 1,139,575$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
7,245,893$ 158 62,234$ 9,832,972$




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