Bears

GP: 76 | W: 42 | L: 24 | OTL: 10 | P: 94
GF: 202 | GA: 151 | PP%: 16.16% | PK%: 87.41%
DG: Mathieu Girard | Morale : 55 | Moyenne d'Équipe : 60
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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 SP
1Kyle CliffordX99.00955565759985727050646672557174171690
2Tanner GlassX99.00895559678179636350606064558476172640
3Jason DickinsonXX99.00635571707167676480626063555050174610
4Anton BlidhX99.00565565757871545650555660556573168590
5Anthony CamaraX100.00755565637867595550555555557274172580
6Paul ThompsonX100.00845569626866606050606060555050156580
7Rich CluneX100.00565558627568685550555556555959175570
8Dennis Yan (R)X100.00565555555657575550555555557575172550
9Brett SutterX100.00565555555758585550555555557475163550
10Reid Duke (R)X100.00565555555555555550555555555050174530
11Klas DahlbeckX100.00845575738279697225636174557272125690
12Andrei Mironov (R)X100.00725561815769576625626265556462141630
13Trevor MurphyX100.00645570655875676525616164555353171610
14Sami Niku (R)X100.00615568755677556125606260556262176610
15Kyle Wood (R)X100.00595559615959795925595959557272158590
16Simon DespresX100.00555555605555555525555555557774172560
17Michael Kapla (R)X100.00555555605555695525555555555555155550
Rayé
MOYENNE D'ÉQUIPE99.7667556266676763604158586055656516460
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Vitek Vanecek100.0064788474666670677070556867169680
2Kristers Gudlevskis100.0060788379646463666862555969152660
Rayé
MOYENNE D'ÉQUIPE100.006278847765656767696655646816167
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bob Hartley61626269885656CAN5756,300,000$


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'ÉquipePOS GP 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
1Kyle CliffordBears (Was)LW7640438323228103062163309722112.12%32195425.71151732843432021136712256.53%88800020.85350011653
2Jason DickinsonBears (Was)C/LW7618426020441021170210571508.57%25171522.57318215934000052913162.50%158400000.7013101274
3Tanner GlassBears (Was)LW64173350191180232139236611607.20%24158324.754101460261022113312152.11%45100010.6314000544
4Sami NikuBears (Was)D64153247221171511980132358011.36%61135821.2261319892641015262310.00%000000.6900101362
5Trevor MurphyBears (Was)D7610334318111151429413135847.63%82155020.405914862770004316200.00%000000.5500120234
6Paul ThompsonBears (Was)RW691818361257157052126309114.29%899114.37581335261000004345.16%6200000.7301011212
7Klas DahlbeckBears (Was)D268233111495663074284110.81%4555721.468917591170002119110.00%000001.1100001323
8Anton BlidhBears (Was)LW631020301472205992154501036.49%9124119.7028102918900001453259.09%6600010.4801004212
9Kyle WoodBears (Was)D6310192925855863856163517.86%53102816.326511351630002164210.00%000000.5600001211
10Brett SutterBears (Was)C6412142612155118677255915.58%6103016.11459202680000523056.32%109200000.5000001116
11Andrei MironovBears (Was)D4381725012010101609733698.25%5094622.016915802070220219110.00%000000.5300110024
12Rich CluneBears (Was)LW7661319915516376222569.68%981010.67145107000001591146.36%22000000.4701001122
13Simon DespresBears (Was)D6441014582069222211918.18%3679312.40022530000075000.00%000000.3500000010
14Anthony CamaraBears (Was)LW6456111332027586813507.35%1075711.8401102300052081056.40%21100000.2900000011
15Reid DukeBears (Was)C64461054820165434102111.76%46349.9201106000081050.99%55700000.3200103001
16Michael KaplaBears (Was)D6408805356031199120.00%4374811.690001130001126000.00%000000.2101001000
17Dennis YanBears (Was)LW64325720015152251413.64%33505.481015530000240051.43%7000000.2900000000
Stats d'équipe Total ou en Moyenne10801883395272151266140141612741850537125510.16%5001805316.72661191856572890347462873391456.72%520100040.585165416393739
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
1Vitek VanecekBears (Was)42241240.9131.87244344768750200.50084034421
2Juuse SarosWashington Capitals34171250.9151.97201246667770300.6679340314
3Kristers GudlevskisBears (Was)95210.9122.0250641171940201.0003851101
Stats d'équipe Total ou en Moyenne854626100.9141.924962121115918460700.650208285836


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Andrei MironovBears (Was)D221994-07-29Yes198 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Anthony CamaraBears (Was)LW231993-09-03No192 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Anton BlidhBears (Was)LW211995-03-14No201 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Brett SutterBears (Was)C291987-06-01No201 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm300,000$0$0$No
Dennis YanBears (Was)LW191997-04-14Yes183 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Jason DickinsonBears (Was)C/LW211995-07-04No185 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$No
Klas DahlbeckBears (Was)D251991-07-06No207 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Kristers GudlevskisBears (Was)G241992-07-31No190 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Kyle CliffordBears (Was)LW261991-01-13No211 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No
Kyle WoodBears (Was)D201996-05-04Yes210 Lbs6 ft5NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Michael KaplaBears (Was)D221994-09-19Yes201 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Paul ThompsonBears (Was)RW281988-11-29No198 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Reid DukeBears (Was)C201996-01-28Yes192 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Rich CluneBears (Was)LW291987-04-24No207 Lbs5 ft10NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Sami NikuBears (Was)D201996-10-10Yes179 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Simon DespresBears (Was)D251991-07-26No214 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Tanner GlassBears (Was)LW331983-11-28No210 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No
Trevor MurphyBears (Was)D211995-07-16No172 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No
Vitek VanecekBears (Was)G211996-01-09No180 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1923.63196 Lbs6 ft12.47373,684$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason DickinsonPaul Thompson40122
2Tanner GlassBrett SutterAnton Blidh30122
3Anton BlidhReid DukeKyle Clifford20122
4Anthony CamaraTanner GlassJason Dickinson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku40122
2Trevor Murphy30122
3Simon DespresMichael Kapla20122
4Sami Niku10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason DickinsonPaul Thompson60122
2Tanner GlassBrett SutterAnton Blidh40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle CliffordTanner Glass60122
2Jason DickinsonAnton Blidh40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Clifford60122Sami Niku60122
2Tanner Glass40122Trevor Murphy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle CliffordTanner Glass60122
2Jason DickinsonAnton Blidh40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonPaul ThompsonSami Niku
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonPaul ThompsonSami Niku
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Rich Clune, Dennis Yan, Anthony CamaraRich Clune, Dennis YanAnthony Camara
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Simon Despres, Michael Kapla, Trevor MurphySimon DespresMichael Kapla, Trevor Murphy
Tirs de Pénalité
Kyle Clifford, Tanner Glass, Jason Dickinson, Anton Blidh, Anthony Camara
Gardien
#1 : Vitek Vanecek, #2 : Kristers Gudlevskis


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
LigueDomicileVisiteur
# 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
1Admirals21100000541110000003121010000023-120.50059140074735273063269662534529404911327.27%20195.00%01341237956.37%1162235149.43%613106857.40%191213291783553907461
2Americans2110000034-11010000003-31100000031220.5003580074735274163269662534481740351317.69%19478.95%01341237956.37%1162235149.43%613106857.40%191213291783553907461
3Bruins6220100114113311010007523110000176170.58314274102747352717163269662534114401191232827.14%45491.11%01341237956.37%1162235149.43%613106857.40%191213291783553907461
4Checkers440000002021822000000808220000001221081.0002036560374735271636326966253485264010113215.38%180100.00%01341237956.37%1162235149.43%613106857.40%191213291783553907461
5Comets22000000725110000004131100000031241.0007132000747352759632696625346821343213323.08%12191.67%01341237956.37%1162235149.43%613106857.40%191213291783553907461
6Crunch2010010047-31010000024-21000010023-110.250481200747352758632696625343015204116318.75%9366.67%01341237956.37%1162235149.43%613106857.40%191213291783553907461
7Devils2110000023-11010000013-21100000010120.5002460174735273663269662534431831421417.14%12283.33%01341237956.37%1162235149.43%613106857.40%191213291783553907461
8Griffins22000000624110000003121100000031241.0006121800747352756632696625343911244914428.57%10280.00%01341237956.37%1162235149.43%613106857.40%191213291783553907461
9IceHogs211000003211010000012-11100000020220.50035801747352758632696625344811222715213.33%11190.91%01341237956.37%1162235149.43%613106857.40%191213291783553907461
10Marlies22000000954110000004311100000052341.000917260074735278663269662534412246473266.67%15193.33%01341237956.37%1162235149.43%613106857.40%191213291783553907461
11Monsters41200001811-32020000006-62100000185330.37581220007473527101632696625349325577124312.50%27485.19%01341237956.37%1162235149.43%613106857.40%191213291783553907461
12Penguins1255002002427-36330000011101622002001317-4120.5002444680174735272366326966253428886234228951313.68%951287.37%11341237956.37%1162235149.43%613106857.40%191213291783553907461
13Phantoms1244002022326-3621002011012-2623000011314-1120.5002336590074735272556326966253429689227215801316.25%891187.64%11341237956.37%1162235149.43%613106857.40%191213291783553907461
14Rocket211000005411010000012-11100000042220.500581300747352758632696625343314183710220.00%8187.50%01341237956.37%1162235149.43%613106857.40%191213291783553907461
15Senators2010001047-31010000004-41000001043120.5004590074735274363269662534572341401815.56%17194.12%01341237956.37%1162235149.43%613106857.40%191213291783553907461
16Sound Tigers633000001114-3321000007703120000047-360.50011172800747352711663269662534137321319136616.67%471078.72%11341237956.37%1162235149.43%613106857.40%191213291783553907461
17Thunderbirds640011003111203300000017215310011001495110.917315687017473527215632696625341225110114821733.33%42490.48%01341237956.37%1162235149.43%613106857.40%191213291783553907461
Total763924026142021515138201401201936924381910014131098227940.61820235856001074735271969632696625341707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
19Wolf Pack6510000023914330000001431132100000963100.833234467017473527187632696625341134110512334617.65%36586.11%01341237956.37%1162235149.43%613106857.40%191213291783553907461
_Since Last GM Reset763924026142021515138201401201936924381910014131098227940.61820235856001074735271969632696625341707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
_Vs Conference52212001514113115-2261111012015254-2261090031361610550.52911319731005747352712036326966253411713699659743454813.91%3775286.21%31341237956.37%1162235149.43%613106857.40%191213291783553907461
_Vs Division465700310111921923350000051411023220031060519150.16311119330406747352710946326966253410553178258712964414.86%3244486.42%31341237956.37%1162235149.43%613106857.40%191213291783553907461

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7694W52023585601969170755113301499010
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7639242614202151
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
38201412019369
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
381910141310982
Derniers 10 Matchs
WLOTWOTL SOWSOL
711010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
4587416.16%5326787.41%3
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
632696625347473527
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
1341237956.37%1162235149.43%613106857.40%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
191213291783553907461


Derniers Match 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
4 - 2018-09-0811Crunch4Bears2LSommaire du Match
5 - 2018-09-0926Sound Tigers2Bears3WSommaire du Match
10 - 2018-09-1434Bears3Griffins1WSommaire du Match
11 - 2018-09-1548Bears2Admirals3LSommaire du Match
12 - 2018-09-1662Bears2IceHogs0WSommaire du Match
15 - 2018-09-1966Bears0Penguins2LSommaire du Match
17 - 2018-09-2170Bears6Checkers2WSommaire du Match
18 - 2018-09-2284Bears6Checkers0WSommaire du Match
24 - 2018-09-28109Bears1Penguins4LSommaire du Match
25 - 2018-09-29118Penguins1Bears2WSommaire du Match
26 - 2018-09-30134Phantoms3Bears2LXXSommaire du Match
31 - 2018-10-05145Bears3Americans1WSommaire du Match
32 - 2018-10-06156Americans3Bears0LSommaire du Match
33 - 2018-10-07168Wolf Pack1Bears3WSommaire du Match
39 - 2018-10-13195Thunderbirds1Bears5WSommaire du Match
40 - 2018-10-14209Bears2Crunch3LXSommaire du Match
45 - 2018-10-19223Monsters4Bears0LSommaire du Match
46 - 2018-10-20238Monsters2Bears0LSommaire du Match
52 - 2018-10-26268Bears3Phantoms2WSommaire du Match
53 - 2018-10-27282Bears3Penguins2WSommaire du Match
57 - 2018-10-31300Penguins3Bears0LSommaire du Match
60 - 2018-11-03323Thunderbirds0Bears5WSommaire du Match
61 - 2018-11-04335Devils3Bears1LSommaire du Match
66 - 2018-11-09352Bears2Phantoms3LXXSommaire du Match
67 - 2018-11-10364Wolf Pack0Bears6WSommaire du Match
68 - 2018-11-11379Penguins1Bears4WSommaire du Match
74 - 2018-11-17408Bears1Bruins2LSommaire du Match
75 - 2018-11-18417Bears4Thunderbirds5LXSommaire du Match
78 - 2018-11-21427Bears1Phantoms2LSommaire du Match
80 - 2018-11-23434Penguins0Bears3WSommaire du Match
81 - 2018-11-24456Phantoms2Bears1LXSommaire du Match
87 - 2018-11-30479Bears5Penguins3WSommaire du Match
88 - 2018-12-01488Bruins3Bears2LSommaire du Match
89 - 2018-12-02501Bruins0Bears2WSommaire du Match
95 - 2018-12-08536Griffins1Bears3WSommaire du Match
96 - 2018-12-09549Admirals1Bears3WSommaire du Match
101 - 2018-12-14566Bears4Thunderbirds3WXSommaire du Match
102 - 2018-12-15580Bears1Phantoms3LSommaire du Match
103 - 2018-12-16590Phantoms2Bears1LXSommaire du Match
106 - 2018-12-19598Bears1Devils0WSommaire du Match
109 - 2018-12-22624Bears2Penguins3LXSommaire du Match
110 - 2018-12-23632Bears3Sound Tigers2WSommaire du Match
113 - 2018-12-26649Bears1Phantoms3LSommaire du Match
116 - 2018-12-29672Rocket2Bears1LSommaire du Match
123 - 2019-01-05700Phantoms2Bears3WSommaire du Match
124 - 2019-01-06711Senators4Bears0LSommaire du Match
127 - 2019-01-09718Bears6Thunderbirds1WSommaire du Match
130 - 2019-01-12737Checkers0Bears3WSommaire du Match
131 - 2019-01-13755Checkers0Bears5WSommaire du Match
134 - 2019-01-16762Penguins3Bears1LSommaire du Match
137 - 2019-01-19781Phantoms2Bears1LSommaire du Match
138 - 2019-01-20801Bears5Phantoms1WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25822Bears2Penguins3LXSommaire du Match
144 - 2019-01-26833IceHogs2Bears1LSommaire du Match
145 - 2019-01-27840Bears0Sound Tigers1LSommaire du Match
148 - 2019-01-30851Bears3Wolf Pack1WSommaire du Match
150 - 2019-02-01857Bears3Comets1WSommaire du Match
151 - 2019-02-02870Sound Tigers2Bears3WSommaire du Match
157 - 2019-02-08901Bears3Bruins0WSommaire du Match
158 - 2019-02-09912Bears3Bruins4LXXSommaire du Match
159 - 2019-02-10923Bears3Wolf Pack4LSommaire du Match
162 - 2019-02-13935Thunderbirds1Bears7WSommaire du Match
164 - 2019-02-15945Marlies3Bears4WSommaire du Match
165 - 2019-02-16956Sound Tigers3Bears1LSommaire du Match
168 - 2019-02-19972Penguins2Bears1LSommaire du Match
172 - 2019-02-23996Bears3Monsters4LXXSommaire du Match
173 - 2019-02-241009Bears5Monsters1WSommaire du Match
179 - 2019-03-021040Bruins2Bears3WXSommaire du Match
180 - 2019-03-031054Bears1Sound Tigers4LSommaire du Match
184 - 2019-03-071072Bears5Marlies2WSommaire du Match
185 - 2019-03-081073Bears4Senators3WXXSommaire du Match
186 - 2019-03-091083Bears4Rocket2WSommaire du Match
189 - 2019-03-121105Phantoms1Bears2WSommaire du Match
192 - 2019-03-151122Bears3Wolf Pack1WSommaire du Match
193 - 2019-03-161129Comets1Bears4WSommaire du Match
194 - 2019-03-171146Wolf Pack2Bears5WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
6,374,677$ 71,000$ 46,940$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 74,688$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 0 32,840$ 0$




LigueDomicileVisiteur
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
137639240261420215151382014012019369243819100141310982279420235856001074735271969632696625341707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
Total Saison Régulière7639240261420215151382014012019369243819100141310982279420235856001074735271969632696625341707551133014994587416.16%5326787.41%31341237956.37%1162235149.43%613106857.40%191213291783553907461
Séries
1240400000313-102020000035-22020000008-803580012004915132101112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
1240400000313-102020000035-22020000008-803580012004915132101112956852129.52%27485.19%0478952.81%6915245.39%325162.75%8860107304723
Total Séries80800000626-2040400000610-440400000016-16061016002400983026420222581121704249.52%54885.19%09417852.81%13830445.39%6410262.75%177120214619446