Bears

GP: 77 | W: 49 | L: 23 | OTL: 5 | P: 103
GF: 316 | GA: 240 | PP%: 22.73% | PK%: 78.52%
DG: David Arseneault | Morale : 50 | Moyenne d'Équipe : 57
Prochain matchs #1210 vs Cougars
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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 SPÂgeContratSalaire Moyen
1David BackesXX100.008349757482586462466657615785890506303518,000,000$
2Gemel SmithXXX100.006965797268687667685765676556560506202511,200,000$
3Nick Shore (R)X100.007343897771536759795557832551510506102751,300,000$
4Dylan SikuraXXX100.00665886615880846480616261594747050600242925,000$
5Phillip Di GiuseppeXX100.00825091797356745830595664255757050600251700,000$
6Boris KatchoukX100.00757184617180856050565964564444050590212742,500$
7Nathan BastianX100.00777574627877815850535965594444050590212742,500$
8Bob Carpenter (R)XX100.00767284667253525771565363504444050560231600,000$
9Ryan GroppX100.00797193687268705050494964464444050560231825,000$
10Shea TheodoreX100.006149908474849280256858638062640506802435,200,000$
11Dakota MermisX100.00835285676776805925484774795555050640254655,000$
12Philippe MyersX100.00815084807669825931534766255353050640223700,000$
13Josh BrownX100.00817279628763755625454663255757050610251800,000$
14Jaycob MegnaX100.00817484608671805127394271395252050610263969,006$
15Jakub ZborilX100.00767280667570754925434064394848050590221895,000$
16Evan McEnenyX100.007774806375565946253543644051510505602531,154,888$
Rayé
1Antoine Morand (R)X100.00716683676670755063494759454444050550204778,334$
2Ty RattieX100.00533592665755424949475160444742050510261900,000$
3Kirill Kaprizov (R)XX100.00323737375631313237323237343230050350221525,000$
4Jack Rathbone (R)X100.00524783696859685525594153435454050560204925,000$
5Sean DayX100.00828477538451534825394164394444050550212742,500$
6Igor Ozhiganov (R)X100.00613587626947424035374362473532050510263925,000$
MOYENNE D'ÉQUIPE100.0071598266726369554350506346505005058
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
1Dan Vladar100.0064587380666768716968304444050640
2Alex Lyon100.0062688375626555656460304545050610
Rayé
1Gilles Senn (R)100.0052546886515453585454304444050560
2Kaden Fulcher (R)100.0043454566434343434362423532050460
3Linus Soderstrom (R)100.0035403769343232323232323230050370
MOYENNE D'ÉQUIPE100.005153617551525054525533403905053
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Gemel SmithBears (Was)C/LW/RW7780341143459522224065619446112.20%52158620.6016112711622600014514448.33%18000151.443900116133
2Philippe MyersBears (Was)D7711829337820279138253981594.35%190175922.85715221122220001216110.00%000001.06000002107
3Nick ShoreBears (Was)C773945843180312893148921912.42%22126316.4041620461530003458262.36%191800011.3306000543
4Phillip Di GiuseppeBears (Was)LW/RW7724376130380651192406415910.00%11121215.7554932153000005040.59%10100001.0100000444
5Dakota MermisBears (Was)D76134255265201168614346949.09%111142518.7541014581620004171100.00%000000.7701000034
6Dylan SikuraBears (Was)C/LW/RW772133541510032168224551569.38%594012.210118250000111058.70%121800001.1511000141
7John HaydenWashingtonLW/RW75193453278715228101265661917.17%13117715.69771443150000003147.52%10100000.9013201026
8Boris KatchoukBears (Was)LW772127481526068902036317510.34%2092912.07000130002433144.78%6700011.0300000306
9Nathan BastianBears (Was)RW7711304115701011284195561315.64%1687111.3201119000001247.22%7200000.9400101201
10Byron FroeseWashingtonC/RW241018287215843214735926.80%1059824.931111230930007811060.00%5000010.9403010230
11Shea TheodoreBears (Was)D23919288100233768325713.24%4560026.127293389000175100.00%000000.9300000211
12Bob CarpenterBears (Was)C/LW7718927918079901544010411.69%214325.6200000000002257.23%51200011.2500000103
13Jakub ZborilBears (Was)D7771724114801193566183710.61%7396212.5000022000195100.00%000000.5000000100
14Josh BrownBears (Was)D776172328500172407920517.59%90143918.70336271630001171000.00%000000.3200000111
15Jaycob MegnaBears (Was)D7751419108020120496418427.81%5989111.5800061700000000.00%000000.4300102001
16Filip ChytilWashingtonC/LW/RW8134-200234288243.57%019424.350119320000270049.80%24900000.4101000000
17Evan McEnenyBears (Was)D3000000000000.00%0103.660000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne10562954617563016595517521632309990221529.52%7381629515.435482136524150500021985421358.15%446800190.93524415404541
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
1Dan VladarBears (Was)77482350.9213.06455710223229420410.82941770688
2Alex LyonBears (Was)31000.9711.12107002700000.0000077000
Stats d'équipe Total ou en Moyenne80492350.9223.01466510223430120410.829417777688


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Alex LyonBears (Was)G261992-12-08No201 Lbs6 ft1NoNoNo2Pro & Farm874,125$37,596$87,412$3,760$No874,125$Lien
Antoine MorandBears (Was)C201999-02-18Yes185 Lbs5 ft10NoNoNo4Pro & Farm778,334$33,476$77,833$3,348$No778,334$778,334$778,334$Lien
Bob CarpenterBears (Was)C/LW231996-08-16Yes201 Lbs5 ft11YesNoNo1Pro & Farm600,000$25,806$60,000$2,581$NoLien
Boris KatchoukBears (Was)LW211998-06-18No192 Lbs6 ft1NoNoNo2Pro & Farm742,500$31,935$74,250$3,194$No742,500$Lien
Dakota MermisBears (Was)D251994-01-05No188 Lbs5 ft11NoNoNo4Pro & Farm655,000$28,172$65,500$2,817$No655,000$655,000$655,000$Lien
Dan VladarBears (Was)G221997-08-20No185 Lbs6 ft5NoNoNo1Pro & Farm700,000$30,107$70,000$3,011$NoLien
David BackesBears (Was)C/RW351984-05-01No221 Lbs6 ft3NoNoNo1Pro & Farm8,000,000$344,086$800,000$34,409$NoLien
Dylan SikuraBears (Was)C/LW/RW241995-06-01No158 Lbs5 ft11NoNoNo2Pro & Farm925,000$39,784$92,500$3,978$No925,000$Lien
Evan McEnenyBears (Was)D251994-05-22No203 Lbs6 ft2NoNoNo3Pro & Farm1,154,888$49,672$115,489$4,967$No1,154,888$1,154,888$Lien
Gemel SmithBears (Was)C/LW/RW251994-04-16No190 Lbs5 ft10NoNoNo1Pro & Farm1,200,000$51,612$120,000$5,161$NoLien
Gilles SennBears (Was)G231996-03-01Yes203 Lbs6 ft5NoNoNo2Pro & Farm817,500$35,161$81,750$3,516$No817,500$Lien
Igor OzhiganovBears (Was)D261992-10-13Yes210 Lbs6 ft2NoNoNo3Pro & Farm925,000$39,784$92,500$3,978$No925,000$925,000$Lien
Jack RathboneBears (Was)D201999-05-20Yes190 Lbs5 ft11NoNoNo4Pro & Farm925,000$39,784$92,500$3,978$No925,000$925,000$925,000$Lien
Jakub ZborilBears (Was)D221997-02-21No200 Lbs6 ft2NoNoNo1Pro & Farm895,000$38,494$89,500$3,849$NoLien
Jaycob MegnaBears (Was)D261992-12-10No225 Lbs6 ft6NoNoNo3Pro & Farm969,006$41,677$96,901$4,168$No969,006$969,006$Lien
Josh BrownBears (Was)D251994-01-21No225 Lbs6 ft5NoNoNo1Pro & Farm800,000$34,408$80,000$3,441$NoLien
Kaden FulcherBears (Was)G211998-09-23Yes182 Lbs6 ft2NoNoNo2Pro & Farm1,200,000$51,612$120,000$5,161$No1,200,000$Lien
Kirill KaprizovBears (Was)LW/RW221997-04-26Yes185 Lbs5 ft9NoNoNo1Pro & Farm525,000$22,580$52,500$2,258$NoLien
Linus SoderstromBears (Was)G231996-08-23Yes187 Lbs6 ft3NoNoNo1Pro & Farm650,000$27,956$65,000$2,796$NoLien
Nathan BastianBears (Was)RW211997-12-06No205 Lbs6 ft4NoNoNo2Pro & Farm742,500$31,935$74,250$3,194$No742,500$Lien
Nick ShoreBears (Was)C271992-09-26Yes194 Lbs6 ft1NoNoNo5Pro & Farm1,300,000$55,913$130,000$5,591$No1,300,000$1,300,000$1,300,000$1,300,000$Lien
Philippe MyersBears (Was)D221997-01-25No196 Lbs6 ft5NoNoNo3Pro & Farm700,000$30,107$70,000$3,011$No700,000$700,000$Lien
Phillip Di GiuseppeBears (Was)LW/RW251993-10-09No201 Lbs6 ft0NoNoNo1Pro & Farm700,000$30,107$70,000$3,011$NoLien
Ryan GroppBears (Was)LW231996-09-16No190 Lbs6 ft2NoNoNo1Pro & Farm825,000$35,483$82,500$3,548$NoLien
Sean DayBears (Was)D211998-01-08No231 Lbs6 ft2NoNoNo2Pro & Farm742,500$31,935$74,250$3,194$No742,500$Lien
Shea TheodoreBears (Was)D241995-08-03No195 Lbs6 ft2NoNoNo3Pro & Farm5,200,000$223,655$520,000$22,366$No5,200,000$5,200,000$Lien
Ty RattieBears (Was)RW261993-02-05No183 Lbs6 ft0NoNoNo1Pro & Farm900,000$38,709$90,000$3,871$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2723.81197 Lbs6 ft22.111,275,791$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gemel Smith40122
2Nick ShorePhillip Di Giuseppe30122
3Boris KatchoukDylan SikuraNathan Bastian20122
4Bob Carpenter10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Philippe Myers40122
2Dakota MermisJosh Brown30122
3Jaycob MegnaJakub Zboril20122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gemel Smith60122
2Nick ShorePhillip Di Giuseppe40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Philippe Myers60122
2Dakota MermisJosh Brown40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Gemel SmithNick Shore40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Philippe Myers60122
2Dakota MermisJosh Brown40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Philippe Myers60122
240122Dakota MermisJosh Brown40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Gemel SmithNick Shore40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Philippe Myers60122
2Dakota MermisJosh Brown40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gemel SmithPhilippe Myers
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gemel SmithPhilippe Myers
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dylan Sikura, Nathan Bastian, Boris KatchoukDylan Sikura, Nathan BastianBoris Katchouk
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jaycob Megna, Jakub Zboril, Jaycob MegnaJakub Zboril,
Tirs de Pénalité
, , Gemel Smith, Nick Shore,
Gardien
#1 : Dan Vladar, #2 : Alex Lyon


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
1Admirals20100010550100000103211010000023-120.50057120013794798891171105711306578251150300.00%30100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
2Baby Hawks21100000550110000002111010000034-120.500581300137947986711711057113065641510518112.50%3166.67%01558300951.78%1329299544.37%621133246.62%186713161830554974483
3Bruins301000111112-1100000106512010000157-230.50011172800137947981261171105711306513045247010110.00%11463.64%01558300951.78%1329299544.37%621133246.62%186713161830554974483
4Cabaret Lady Mary Ann220000001486110000007341100000075241.0001423370013794798171117110571130658021859300.00%4325.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
5Caroline43100000141132110000046-222000000105560.750142337001379479816611711057113065165413694900.00%18477.78%01558300951.78%1329299544.37%621133246.62%186713161830554974483
6Chiefs21000001752110000005231000000123-130.7507111800137947989111711057113065752210489333.33%5180.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
7Chill20200000810-21010000067-11010000023-100.00081220001379479863117110571130651052620498225.00%9277.78%01558300951.78%1329299544.37%621133246.62%186713161830554974483
8Comets22000000963110000005321100000043141.0009162500137947988111711057113065691618518337.50%8187.50%01558300951.78%1329299544.37%621133246.62%186713161830554974483
9Cougars210000018801000000123-11100000065130.7508111900137947986911711057113065872516557571.43%8187.50%01558300951.78%1329299544.37%621133246.62%186713161830554974483
10Crunch22000000844110000004221100000042241.000813210013794798117117110571130657824215213323.08%7271.43%01558300951.78%1329299544.37%621133246.62%186713161830554974483
11Heat220000001257110000005231100000073441.00012233500137947989811711057113065542320439333.33%8275.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
12Jayhawks21100000972110000007431010000023-120.5009182700137947987611711057113065742020596466.67%9277.78%01558300951.78%1329299544.37%621133246.62%186713161830554974483
13Las Vegas2020000058-31010000035-21010000023-100.000581300137947988111711057113065793418627342.86%8362.50%01558300951.78%1329299544.37%621133246.62%186713161830554974483
14Manchots43000010181262100001075222000000117481.0001829470013794798178117110571130651854940909222.22%20195.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
15Marlies211000007701010000024-21100000053220.5007142110137947986411711057113065712636369111.11%16475.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
16Minnesota11000000734000000000001100000073421.000710170013794798701171105711306552126232150.00%30100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
17Monarchs211000001183110000007341010000045-120.500111728001379479896117110571130651112714698450.00%70100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
18Monsters412010001114-32020000028-62100100096340.5001114250013794798158117110571130651344638921119.09%18666.67%01558300951.78%1329299544.37%621133246.62%186713161830554974483
19Monsters21100000945110000007161010000023-120.5009162500137947989211711057113065612414464250.00%60100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
20Oceanics20100001710-31010000024-21000000156-110.25071118001379479871117110571130651122518553133.33%9188.89%01558300951.78%1329299544.37%621133246.62%186713161830554974483
21Oil Kings22000000633110000004311100000020241.0006814011379479874117110571130657519234110220.00%90100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
22Phantoms412000011415-12010000179-22110000076130.37514253900137947981651171105711306514638267915426.67%13376.92%01558300951.78%1329299544.37%621133246.62%186713161830554974483
23Rocket321000001596211000008621100000073440.66715284300137947981411171105711306514127308113215.38%14471.43%01558300951.78%1329299544.37%621133246.62%186713161830554974483
24Senators321000001293211000007701100000052340.66712213300137947981511171105711306513641285913215.38%14285.71%01558300951.78%1329299544.37%621133246.62%186713161830554974483
25Sharks22000000927110000004221100000050541.000917260113794798741171105711306584201447400.00%70100.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
26Sound Tigers440000001798220000008532200000094581.0001727440013794798170117110571130651423733105600.00%11372.73%01558300951.78%1329299544.37%621133246.62%186713161830554974483
27Spiders4120001016133211000008442010001089-140.50016254100137947981521171105711306514749421081000.00%16193.75%01558300951.78%1329299544.37%621133246.62%186713161830554974483
28Stars2020000069-31010000035-21010000034-100.00061117001379479878117110571130656828323511436.36%6350.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
29Thunder320000101275220000008441000001043161.00012183000137947981461171105711306582292257300.00%10370.00%01558300951.78%1329299544.37%621133246.62%186713161830554974483
Total7743230105531624076392212000321551213438211101023161119421030.6693165268421213794798338311711057113065301386068918582425522.73%2986478.52%01558300951.78%1329299544.37%621133246.62%186713161830554974483
30Wolf Pack4400000024121222000000126622000000126681.0002445690013794798208117110571130651282641921119.09%18761.11%01558300951.78%1329299544.37%621133246.62%186713161830554974483
_Since Last GM Reset7743230105531624076392212000321551213438211101023161119421030.6693165268421213794798338311711057113065301386068918582425522.73%2986478.52%01558300951.78%1329299544.37%621133246.62%186713161830554974483
_Vs Conference452214010531821453723118000318975142211601022937023590.6561822994811113794798191111711057113065179150940710581231915.45%1823779.67%01558300951.78%1329299544.37%621133246.62%186713161830554974483

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
77103W731652684233833013860689185812
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7743231055316240
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3922120032155121
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3821111023161119
Derniers 10 Matchs
WLOTWOTL SOWSOL
900001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2425522.73%2986478.52%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
1171105711306513794798
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
1558300951.78%1329299544.37%621133246.62%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
186713161830554974483


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
1 - 2020-10-222Bears2Chiefs3LXXSommaire du Match
3 - 2020-10-2415Bears6Sound Tigers2WSommaire du Match
4 - 2020-10-2523Caroline4Bears1LSommaire du Match
7 - 2020-10-2839Stars5Bears3LSommaire du Match
9 - 2020-10-3052Bears2Chill3LSommaire du Match
11 - 2020-11-0170Bears3Stars4LSommaire du Match
13 - 2020-11-0383Monsters1Bears7WSommaire du Match
15 - 2020-11-0593Marlies4Bears2LSommaire du Match
17 - 2020-11-07109Wolf Pack2Bears6WSommaire du Match
19 - 2020-11-09126Bears3Baby Hawks4LSommaire du Match
21 - 2020-11-11142Bears7Heat3WSommaire du Match
23 - 2020-11-13154Bears2Oil Kings0WSommaire du Match
24 - 2020-11-14160Bears4Comets3WSommaire du Match
28 - 2020-11-18180Bears5Marlies3WSommaire du Match
31 - 2020-11-21198Crunch2Bears4WSommaire du Match
33 - 2020-11-23218Heat2Bears5WSommaire du Match
37 - 2020-11-27238Bears7Cabaret Lady Mary Ann5WSommaire du Match
39 - 2020-11-29258Las Vegas5Bears3LSommaire du Match
41 - 2020-12-01270Jayhawks4Bears7WSommaire du Match
43 - 2020-12-03283Bears3Phantoms4LSommaire du Match
45 - 2020-12-05296Rocket2Bears6WSommaire du Match
46 - 2020-12-06303Bears2Bruins3LXXSommaire du Match
48 - 2020-12-08316Admirals2Bears3WXXSommaire du Match
50 - 2020-12-10332Bears6Wolf Pack4WSommaire du Match
53 - 2020-12-13348Comets3Bears5WSommaire du Match
57 - 2020-12-17383Cabaret Lady Mary Ann3Bears7WSommaire du Match
59 - 2020-12-19398Thunder2Bears3WSommaire du Match
60 - 2020-12-20407Bears6Cougars5WSommaire du Match
63 - 2020-12-23433Bears5Sharks0WSommaire du Match
64 - 2020-12-24437Bears4Monarchs5LSommaire du Match
66 - 2020-12-26451Bears2Admirals3LSommaire du Match
69 - 2020-12-29469Monsters5Bears1LSommaire du Match
71 - 2020-12-31484Bruins5Bears6WXXSommaire du Match
74 - 2021-01-03509Bears4Thunder3WXXSommaire du Match
76 - 2021-01-05521Bears3Monsters1WSommaire du Match
80 - 2021-01-09549Bears3Spiders5LSommaire du Match
81 - 2021-01-10559Thunder2Bears5WSommaire du Match
83 - 2021-01-12571Bears3Bruins4LSommaire du Match
87 - 2021-01-16585Monsters3Bears1LSommaire du Match
88 - 2021-01-17598Bears4Caroline3WSommaire du Match
91 - 2021-01-20614Sound Tigers4Bears5WSommaire du Match
94 - 2021-01-23639Bears6Caroline2WSommaire du Match
96 - 2021-01-25653Sharks2Bears4WSommaire du Match
98 - 2021-01-27667Senators4Bears2LSommaire du Match
99 - 2021-01-28676Bears4Phantoms2WSommaire du Match
102 - 2021-01-31696Spiders1Bears6WSommaire du Match
104 - 2021-02-02712Caroline2Bears3WSommaire du Match
107 - 2021-02-05732Spiders3Bears2LSommaire du Match
109 - 2021-02-07743Bears3Sound Tigers2WSommaire du Match
118 - 2021-02-16768Bears7Rocket3WSommaire du Match
120 - 2021-02-18777Chill7Bears6LSommaire du Match
122 - 2021-02-20787Bears5Senators2WSommaire du Match
124 - 2021-02-22806Manchots1Bears2WSommaire du Match
126 - 2021-02-24817Monarchs3Bears7WSommaire du Match
130 - 2021-02-28850Phantoms6Bears5LXXSommaire du Match
132 - 2021-03-02862Sound Tigers1Bears3WSommaire du Match
135 - 2021-03-05888Bears2Monsters3LSommaire du Match
137 - 2021-03-07904Bears2Jayhawks3LSommaire du Match
139 - 2021-03-09918Bears2Las Vegas3LSommaire du Match
142 - 2021-03-12935Rocket4Bears2LSommaire du Match
144 - 2021-03-14948Bears5Spiders4WXXSommaire du Match
145 - 2021-03-15959Manchots4Bears5WXXSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
147 - 2021-03-17973Oceanics4Bears2LSommaire du Match
149 - 2021-03-19992Bears5Oceanics6LXXSommaire du Match
152 - 2021-03-221014Bears7Minnesota3WSommaire du Match
155 - 2021-03-251029Phantoms3Bears2LSommaire du Match
156 - 2021-03-261036Bears6Wolf Pack2WSommaire du Match
158 - 2021-03-281050Bears6Manchots4WSommaire du Match
160 - 2021-03-301066Bears4Crunch2WSommaire du Match
163 - 2021-04-021087Cougars3Bears2LXXSommaire du Match
165 - 2021-04-041103Baby Hawks1Bears2WSommaire du Match
167 - 2021-04-061120Oil Kings3Bears4WSommaire du Match
170 - 2021-04-091141Bears6Monsters5WXSommaire du Match
171 - 2021-04-101147Senators3Bears5WSommaire du Match
173 - 2021-04-121164Bears5Manchots3WSommaire du Match
175 - 2021-04-141181Chiefs2Bears5WSommaire du Match
177 - 2021-04-161194Wolf Pack4Bears6WSommaire du Match
179 - 2021-04-181210Bears-Cougars-
181 - 2021-04-201224Bears-Crunch-
182 - 2021-04-211231Marlies-Bears-
184 - 2021-04-231248Minnesota-Bears-
186 - 2021-04-251265Bears-Cabaret Lady Mary Ann-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets4020
Assistance60,03326,001
Assistance PCT76.97%66.67%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
2 2206 - 73.53% 74,906$2,921,340$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,422,022$ 3,444,636$ 3,444,636$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
18,520$ 3,422,022$ 27 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
149,812$ 8 18,520$ 148,160$




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