Bears

GP: 44 | W: 23 | L: 18 | OTL: 3 | P: 49
GF: 107 | GA: 91 | PP%: 12.31% | PK%: 89.71%
DG: Mathieu Girard | Morale : 51 | Moyenne d'Équipe : 62
Prochain matchs #700 vs Phantoms
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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
1Jason DickinsonXX100.008243806580748064766761736267667766660
2Tom KuhnhacklXX100.008336916180705959536258815773675276640
3Paul ThompsonX100.006343726277949361645960586179815461630
4Kyle CliffordX100.008578656383678562546164566375706369630
5Brett SutterX100.006138856074939059645858575980725360620
6Christoffer Ehn (R)XX100.007037886380737262706158675665646661620
7Anton BlidhX100.007338865675867355535654655267645562600
8Cooper Marody (R)X100.005336906171766960696257595665635661600
9Timothy Gettinger (R)X100.007836925896777257545655615361635661600
10Gage QuinneyX100.005436925962939058645756545967646361590
11Dennis YanX100.006239825977908557545355565263626362590
12Reid DukeX100.005938845673857956585553545065636262580
13Jayden HalbgewachsX100.005336915860928957535854525663626361580
14Rich CluneX100.006338845673666454535152535774714823550
15Kyle WoodX100.008638855898939156306052634665636261670
16Sami NikuX100.005637896473777163306858614865635662620
17Michael KaplaX100.006136925674939054305852534669656060610
18Trevor MurphyX100.005140785866928957305853564867646156600
Rayé
MOYENNE D'ÉQUIPE100.00664085607683805853595660556866596061
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 Vanecek100.00777876747675777675777665695357730
Rayé
MOYENNE D'ÉQUIPE100.0077787674767577767577766569535773
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jay Leach73676657605786USA394100,000$


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 BlidhBears (Was)LW44271441126810103902295712511.79%26104623.775813521460002435250.00%7000010.7823110622
2Sami NikuBears (Was)D441229412094010081104295711.54%76101223.014610671590000125110.00%000000.8100000232
3Kyle CliffordBears (Was)LW44172340199935130991514913011.26%1695021.5946104014300021564043.86%38300000.8404205414
4Jason DickinsonBears (Was)C/LW44211536-57010125130251711808.37%28101323.03437481330001427158.76%78800000.7114101137
5Brett SutterBears (Was)C441323367241050128209681506.22%2286119.593101343159000001254.14%95500010.8400011420
6Tom KuhnhacklBears (Was)LW/RW37161733122405845138378111.59%1474320.105611321581121546146.88%6400100.8911000513
7Trevor MurphyBears (Was)D447233087410103539926687.07%8195221.65369581460000136300.00%000000.6300011222
8Michael KaplaBears (Was)D4411415-1364107733248194.17%5666315.0700000000074000.00%000000.4500011003
9Reid DukeBears (Was)C4411314900432224244.55%02345.3300000000000048.24%31300001.1900000000
10Dennis YanBears (Was)LW44000000001110.00%0100.230000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne433115171286695178575069112283508359.36%319748817.292845733401046112663327753.01%257300120.76412449241423
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)44231830.9291.982632688712240410.76913440862
Stats d'équipe Total ou en Moyenne44231830.9291.982632688712240410.76913440862


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 Cap 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
Anton BlidhBears (Was)LW241995-03-14No201 Lbs6 ft0NoNoNo1Pro & Farm300,000$0$0$NoLien
Brett SutterBears (Was)C321987-06-02No200 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Christoffer EhnBears (Was)C/LW231996-04-05Yes181 Lbs6 ft3NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Cooper MarodyBears (Was)C221996-12-20Yes184 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Dennis YanBears (Was)LW221997-04-14No197 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Gage QuinneyBears (Was)C231995-07-29No200 Lbs5 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Jason DickinsonBears (Was)C/LW241995-07-04No200 Lbs6 ft2NoNoNo1Pro & Farm900,000$0$0$NoLien
Jayden HalbgewachsBears (Was)LW221997-03-22No160 Lbs5 ft8NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Kyle CliffordBears (Was)LW281991-01-13No211 Lbs6 ft2NoNoNo1Pro & Farm300,000$0$0$NoLien
Kyle WoodBears (Was)D231996-05-04No235 Lbs6 ft7NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Michael KaplaBears (Was)D241994-09-19No200 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Paul ThompsonBears (Was)RW301988-11-30No200 Lbs6 ft1NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Reid DukeBears (Was)C231996-01-28No191 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Rich CluneBears (Was)LW321987-04-25No207 Lbs5 ft10NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Sami NikuBears (Was)D221996-10-10No176 Lbs6 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Timothy GettingerBears (Was)LW211998-04-14Yes220 Lbs6 ft6NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Tom KuhnhacklBears (Was)LW/RW271992-01-21No196 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Trevor MurphyBears (Was)D231995-07-17No180 Lbs5 ft10NoNoNo1Pro & Farm300,000$0$0$NoLien
Vitek VanecekBears (Was)G231996-01-09No181 Lbs6 ft1NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1924.63196 Lbs6 ft02.79405,263$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson40122
2Brett SutterAnton Blidh30122
3Anton BlidhReid DukeKyle Clifford20122
4Jason Dickinson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku40122
2Trevor Murphy30122
3Michael Kapla20122
4Sami Niku10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson60122
2Brett SutterAnton Blidh40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
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
240122Trevor Murphy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
2Jason DickinsonAnton Blidh40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Sami Niku60122
2Trevor Murphy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonSami Niku
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonSami Niku
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Dennis Yan, , Dennis Yan
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Michael Kapla, Trevor MurphyMichael Kapla, Trevor Murphy
Tirs de Pénalité
Kyle Clifford, , Jason Dickinson, Anton Blidh,
Gardien
#1 : Vitek Vanecek, #2 :


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
1Admirals211000005501010000023-11100000032120.5005813003738303393913983892266213945300.00%16193.75%0639132348.30%633150642.03%29559949.25%10217351142307500236
2Americans21100000312110000003031010000001-120.500347013738303353913983892266182634400.00%120100.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
3Bruins321000001064211000007431100000032140.66710152500373830371391398389229427774313215.38%24195.83%0639132348.30%633150642.03%29559949.25%10217351142307500236
4Checkers220000001331000000000000220000001331041.0001321340137383031113913983892242146456116.67%30100.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
5Crunch22000000312110000002111100000010141.00035801373830344391398389225211194011218.18%6183.33%0639132348.30%633150642.03%29559949.25%10217351142307500236
6Devils2110000045-11010000024-21100000021120.5004610003738303533913983892263161830800.00%7271.43%0639132348.30%633150642.03%29559949.25%10217351142307500236
7Griffins22000000725110000003211100000040441.000710170137383035639139838922452229319333.33%12283.33%0639132348.30%633150642.03%29559949.25%10217351142307500236
8IceHogs11000000606000000000001100000060621.0006111701373830352391398389221934136116.67%20100.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
9Monsters20100010770201000107700000000000020.500712190037383035939139838922591926439222.22%13192.31%0639132348.30%633150642.03%29559949.25%10217351142307500236
10Penguins934000021517-24210000177051300001810-280.4441523380137383032413913983892227066841395958.47%40197.50%0639132348.30%633150642.03%29559949.25%10217351142307500236
11Phantoms826000001429-1530300000312-9523000001117-640.250142438103738303193391398389222497911814135617.14%37878.38%0639132348.30%633150642.03%29559949.25%10217351142307500236
12Rocket1010000012-11010000012-10000000000000.000123003738303253913983892221712214125.00%50100.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
13Sound Tigers21000010312100000102111100000010141.000325013738303473913983892244121844200.00%9188.89%0639132348.30%633150642.03%29559949.25%10217351142307500236
14Thunderbirds430001001266210001006422200000062470.87512223401373830311339139838922973540581715.88%10190.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
Total44211800122107911622711001214953-42214700001583820490.55710717227918373830311863913983892212403625417581952412.31%2042189.71%0639132348.30%633150642.03%29559949.25%10217351142307500236
16Wolf Pack2020000046-22020000046-20000000000000.0004711003738303473913983892253122531900.00%8275.00%0639132348.30%633150642.03%29559949.25%10217351142307500236
_Since Last GM Reset44211800122107911622711001214953-42214700001583820490.55710717227918373830311863913983892212403625417581952412.31%2042189.71%0639132348.30%633150642.03%29559949.25%10217351142307500236
_Vs Conference301115000226072-121649000213442-81476000012630-4280.4676094154133738303755391398389228842423855111461711.64%1441788.19%0639132348.30%633150642.03%29559949.25%10217351142307500236
_Vs Division2754000026068-81331000012537-1214230000135314120.2226095155133738303751391398389227802182954731281410.94%1171587.18%0639132348.30%633150642.03%29559949.25%10217351142307500236

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4449L21071722791186124036254175818
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
442118012210791
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2271101214953
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2214700015838
Derniers 10 Matchs
WLOTWOTL SOWSOL
550000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1952412.31%2042189.71%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
391398389223738303
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
639132348.30%633150642.03%29559949.25%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
10217351142307500236


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 - 2019-09-0511Crunch1Bears2WSommaire du Match
5 - 2019-09-0626Sound Tigers1Bears2WXXSommaire du Match
10 - 2019-09-1134Bears4Griffins0WSommaire du Match
11 - 2019-09-1248Bears3Admirals2WSommaire du Match
12 - 2019-09-1362Bears6IceHogs0WSommaire du Match
15 - 2019-09-1666Bears1Penguins2LSommaire du Match
17 - 2019-09-1870Bears7Checkers0WSommaire du Match
18 - 2019-09-1984Bears6Checkers3WSommaire du Match
24 - 2019-09-25109Bears1Penguins2LXXSommaire du Match
25 - 2019-09-26118Penguins2Bears3WSommaire du Match
26 - 2019-09-27134Phantoms3Bears1LSommaire du Match
31 - 2019-10-02145Bears0Americans1LSommaire du Match
32 - 2019-10-03156Americans0Bears3WSommaire du Match
33 - 2019-10-04168Wolf Pack3Bears2LSommaire du Match
39 - 2019-10-10195Thunderbirds0Bears3WSommaire du Match
40 - 2019-10-11209Bears1Crunch0WSommaire du Match
45 - 2019-10-16223Monsters4Bears3LSommaire du Match
46 - 2019-10-17238Monsters3Bears4WXXSommaire du Match
52 - 2019-10-23268Bears1Phantoms3LSommaire du Match
53 - 2019-10-24282Bears4Penguins2WSommaire du Match
57 - 2019-10-28300Penguins3Bears2LSommaire du Match
60 - 2019-10-31323Thunderbirds4Bears3LXSommaire du Match
61 - 2019-11-01335Devils4Bears2LSommaire du Match
66 - 2019-11-06352Bears1Phantoms5LSommaire du Match
67 - 2019-11-07364Wolf Pack3Bears2LSommaire du Match
68 - 2019-11-08379Penguins0Bears1WSommaire du Match
74 - 2019-11-14408Bears3Bruins2WSommaire du Match
75 - 2019-11-15417Bears4Thunderbirds1WSommaire du Match
78 - 2019-11-18427Bears3Phantoms2WSommaire du Match
80 - 2019-11-20434Penguins2Bears1LXXSommaire du Match
81 - 2019-11-21456Phantoms4Bears2LSommaire du Match
87 - 2019-11-27479Bears1Penguins2LSommaire du Match
88 - 2019-11-28488Bruins3Bears2LSommaire du Match
89 - 2019-11-29501Bruins1Bears5WSommaire du Match
95 - 2019-12-05536Griffins2Bears3WSommaire du Match
96 - 2019-12-06549Admirals3Bears2LSommaire du Match
101 - 2019-12-11566Bears2Thunderbirds1WSommaire du Match
102 - 2019-12-12580Bears3Phantoms2WSommaire du Match
103 - 2019-12-13590Phantoms5Bears0LSommaire du Match
106 - 2019-12-16598Bears2Devils1WSommaire du Match
109 - 2019-12-19624Bears1Penguins2LSommaire du Match
110 - 2019-12-20632Bears1Sound Tigers0WSommaire du Match
113 - 2019-12-23649Bears3Phantoms5LSommaire du Match
116 - 2019-12-26672Rocket2Bears1LSommaire du Match
123 - 2020-01-02700Phantoms-Bears-
124 - 2020-01-03711Senators-Bears-
127 - 2020-01-06718Bears-Thunderbirds-
130 - 2020-01-09737Checkers-Bears-
131 - 2020-01-10755Checkers-Bears-
134 - 2020-01-13762Penguins-Bears-
137 - 2020-01-16781Phantoms-Bears-
138 - 2020-01-17801Bears-Phantoms-
143 - 2020-01-22822Bears-Penguins-
144 - 2020-01-23833IceHogs-Bears-
145 - 2020-01-24840Bears-Sound Tigers-
148 - 2020-01-27851Bears-Wolf Pack-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29857Bears-Comets-
151 - 2020-01-30870Sound Tigers-Bears-
157 - 2020-02-05901Bears-Bruins-
158 - 2020-02-06912Bears-Bruins-
159 - 2020-02-07923Bears-Wolf Pack-
162 - 2020-02-10935Thunderbirds-Bears-
164 - 2020-02-12945Marlies-Bears-
165 - 2020-02-13956Sound Tigers-Bears-
168 - 2020-02-16972Penguins-Bears-
172 - 2020-02-20996Bears-Monsters-
173 - 2020-02-211009Bears-Monsters-
179 - 2020-02-271040Bruins-Bears-
180 - 2020-02-281054Bears-Sound Tigers-
184 - 2020-03-031072Bears-Marlies-
185 - 2020-03-041073Bears-Senators-
186 - 2020-03-051083Bears-Rocket-
189 - 2020-03-081105Phantoms-Bears-
192 - 2020-03-111122Bears-Wolf Pack-
193 - 2020-03-121129Comets-Bears-
194 - 2020-03-131146Wolf Pack-Bears-



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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
106,028$ 77,000$ 24,940$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 44,643$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 75 912$ 68,400$




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
1444211800122107911622711001214953-422147000015838204910717227918373830311863913983892212403625417581952412.31%2042189.71%0639132348.30%633150642.03%29559949.25%10217351142307500236
Total Saison Régulière44211800122107911622711001214953-422147000015838204910717227918373830311863913983892212403625417581952412.31%2042189.71%0639132348.30%633150642.03%29559949.25%10217351142307500236