Bears

GP: 5 | W: 3 | L: 2 | OTL: 0 | P: 6
GF: 12 | GA: 10 | PP%: 30.00% | PK%: 80.00%
DG: Mathieu Girard | Morale : 51 | Moyenne d'Équipe : N/A
Prochain matchs #66 vs Penguins
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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
1Anton BlidhX100.0056556575787154565055566055657315200
2Anthony CamaraX100.0075556563786759555055555555727415100
3Alexander Volkov (R)X100.0073557872786269555055555555727415100
4Jason DickinsonXX100.0063557170716767648062606355505015200
5Dennis Yan (R)X100.0056555555565757555055555555757515100
6Brett SutterX100.0056555555575858555055555555747515100
7Reid Duke (R)X100.0056555555555555555055555555505015100
8Paul ThompsonX100.0084556962686660605060606055505015200
9Rich CluneX100.0056555862756868555055555655595915200
10Kyle CliffordX100.0095556575998572705064667255717415200
11Tanner GlassX100.0089555967817963635060606455847615100
12Anthony DeAngeloX100.0076558590588079802567607255757515200
13Klas DahlbeckX100.0084557573827969722563617455727215200
14Trevor MurphyX100.0064557065587567652561616455535315200
15Kyle Wood (R)X100.0059555961595979592559595955727215200
16Andrei Mironov (R)X100.0072556181576957662562626555646215100
17Sami Niku (R)X100.0061556875567755612560626055626215100
18Simon DespresX100.0055555560555555552555555555777415100
Rayé
MOYENNE D'ÉQUIPE100.006855656868686461425958615567671520
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
1Juuse Saros100.008378818388888584878255757214700
2Vitek Vanecek100.006478847466667067707055686715200
Rayé
MOYENNE D'ÉQUIPE100.00747883797777787679765572701500
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
1Anton BlidhBears (Was)LW5156212018141611136.25%010420.86044219000010033.33%600001.1500000001
2Klas DahlbeckBears (Was)D53361100115145621.43%109218.443251117000015000.00%000001.3000000101
3Kyle CliffordBears (Was)LW5235-1100231412111616.67%211923.851234180000230157.32%8200000.8400000110
4Anthony DeAngeloBears (Was)D5314-214014111941415.79%1111923.813031422000019100.00%000000.6700000000
5Kyle WoodBears (Was)D51341604380912.50%28817.72123717000011100.00%000000.9000000010
6Jason DickinsonBears (Was)C/LW5123-32028115179.09%310420.881235170000121048.78%4100000.5700000010
7Trevor MurphyBears (Was)D50220601336120.00%17314.780113400000000.00%000000.5400000000
8Rich CluneBears (Was)LW5011100116450.00%25210.49000000000120033.33%300000.3800000000
9Paul ThompsonBears (Was)RW5000-100414030.00%0346.8200000000000040.00%500000.0000000000
Stats d'équipe Total ou en Moyenne45112031-2600906096418511.46%3178817.5291322461160000963152.55%13700000.7900000232
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
1Juuse SarosBears (Was)53200.9072.1827521101080100.000050100
2Vitek VanecekBears (Was)10001.0000.002400050000.000005000
Stats d'équipe Total ou en Moyenne63200.9122.0129921101130100.000055100


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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Alexander VolkovBears (Was)RW191997-08-02Yes192 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Andrei MironovBears (Was)D221994-07-29Yes198 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Anthony CamaraBears (Was)LW231993-09-03No192 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Anthony DeAngeloBears (Was)D211995-10-24No175 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$No900,000$
Anton BlidhBears (Was)LW211995-03-14No201 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Brett SutterBears (Was)C291987-06-01No201 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Dennis YanBears (Was)LW191997-04-14Yes183 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$500,000$
Jason DickinsonBears (Was)C/LW211995-07-04No185 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm900,000$0$0$No900,000$
Juuse SarosBears (Was)G211995-04-19No180 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No500,000$
Klas DahlbeckBears (Was)D251991-07-06No207 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Kyle CliffordBears (Was)LW261991-01-13No211 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Kyle WoodBears (Was)D201996-05-04Yes210 Lbs6 ft5NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
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$0$No300,000$300,000$300,000$
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$0$No300,000$300,000$300,000$
Simon DespresBears (Was)D251991-07-26No214 Lbs6 ft4NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Tanner GlassBears (Was)LW331983-11-28No210 Lbs6 ft1NoNoNo2Sans RestrictionPro & Farm300,000$0$0$No300,000$
Trevor MurphyBears (Was)D211995-07-16No172 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Vitek VanecekBears (Was)G211996-01-09No180 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2023.20194 Lbs6 ft12.50410,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson40122
2Anton Blidh30122
3Paul ThompsonJason Dickinson20122
4Rich CluneKyle Clifford10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Anthony DeAngelo40122
2Kyle WoodKlas Dahlbeck30122
3Trevor Murphy20122
4Anthony DeAngeloKyle Wood10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJason Dickinson60122
2Anton Blidh40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Anthony DeAngelo60122
2Kyle WoodKlas Dahlbeck40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
2Jason Dickinson40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Anthony DeAngelo60122
2Kyle WoodKlas Dahlbeck40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Anthony DeAngelo60122
2Kyle Clifford40122Kyle WoodKlas Dahlbeck40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle Clifford60122
2Jason Dickinson40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Anthony DeAngelo60122
2Kyle WoodKlas Dahlbeck40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonAnthony DeAngelo
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJason DickinsonAnthony DeAngelo
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Paul Thompson, Rich Clune, Paul ThompsonRich Clune
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Trevor Murphy, Klas Dahlbeck, Trevor MurphyKlas Dahlbeck,
Tirs de Pénalité
, Kyle Clifford, , Jason Dickinson, Anton Blidh
Gardien
#1 : Juuse Saros, #2 : Vitek Vanecek


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
1Admirals1010000023-1000000000001010000023-100.00023500264013353440023316235240.00%8187.50%05314835.81%5016829.76%277336.99%10973130376029
2Crunch1010000024-21010000024-20000000000000.00024600264021353440017914225120.00%7357.14%05314835.81%5016829.76%277336.99%10973130376029
3Griffins11000000312000000000001100000031221.0003690026403535344002148187228.57%4175.00%05314835.81%5016829.76%277336.99%10973130376029
4IceHogs11000000202000000000001100000020221.00024601264025353440022610126233.33%50100.00%05314835.81%5016829.76%277336.99%10973130376029
5Sound Tigers11000000321110000003210000000000021.000358002640153534400301014187228.57%6183.33%05314835.81%5016829.76%277336.99%10973130376029
Total53200000121022110000056-13210000074360.600122234012640109353440011332629330930.00%30680.00%05314835.81%5016829.76%277336.99%10973130376029
_Since Last GM Reset53200000121022110000056-13210000074360.600122234012640109353440011332629330930.00%30680.00%05314835.81%5016829.76%277336.99%10973130376029
_Vs Conference2110000056-12110000056-10000000000020.50059140026403635344004719284012325.00%13469.23%05314835.81%5016829.76%277336.99%10973130376029
_Vs Division10100000321101000003210000000000000.000358002640153534400301014187228.57%6183.33%05314835.81%5016829.76%277336.99%10973130376029

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
56W112223410911332629301
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
53200001210
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000056
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
321000074
Derniers 10 Matchs
WLOTWOTL SOWSOL
320000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
30930.00%30680.00%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
35344002640
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
5314835.81%5016829.76%277336.99%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
10973130376029


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 - 2018-09-1966Bears-Penguins-
17 - 2018-09-2170Bears-Checkers-
18 - 2018-09-2284Bears-Checkers-
24 - 2018-09-28109Bears-Penguins-
25 - 2018-09-29118Penguins-Bears-
26 - 2018-09-30134Phantoms-Bears-
31 - 2018-10-05145Bears-Americans-
32 - 2018-10-06156Americans-Bears-
33 - 2018-10-07168Wolf Pack-Bears-
39 - 2018-10-13195Thunderbirds-Bears-
40 - 2018-10-14209Bears-Crunch-
45 - 2018-10-19223Monsters-Bears-
46 - 2018-10-20238Monsters-Bears-
52 - 2018-10-26268Bears-Phantoms-
53 - 2018-10-27282Bears-Penguins-
57 - 2018-10-31300Penguins-Bears-
60 - 2018-11-03323Thunderbirds-Bears-
61 - 2018-11-04335Devils-Bears-
66 - 2018-11-09352Bears-Phantoms-
67 - 2018-11-10364Wolf Pack-Bears-
68 - 2018-11-11379Penguins-Bears-
74 - 2018-11-17408Bears-Bruins-
75 - 2018-11-18417Bears-Thunderbirds-
78 - 2018-11-21427Bears-Phantoms-
80 - 2018-11-23434Penguins-Bears-
81 - 2018-11-24456Phantoms-Bears-
87 - 2018-11-30479Bears-Penguins-
88 - 2018-12-01488Bruins-Bears-
89 - 2018-12-02501Bruins-Bears-
95 - 2018-12-08536Griffins-Bears-
96 - 2018-12-09549Admirals-Bears-
101 - 2018-12-14566Bears-Thunderbirds-
102 - 2018-12-15580Bears-Phantoms-
103 - 2018-12-16590Phantoms-Bears-
106 - 2018-12-19598Bears-Devils-
109 - 2018-12-22624Bears-Penguins-
110 - 2018-12-23632Bears-Sound Tigers-
113 - 2018-12-26649Bears-Phantoms-
116 - 2018-12-29672Rocket-Bears-
123 - 2019-01-05700Phantoms-Bears-
124 - 2019-01-06711Senators-Bears-
127 - 2019-01-09718Bears-Thunderbirds-
130 - 2019-01-12737Checkers-Bears-
131 - 2019-01-13755Checkers-Bears-
134 - 2019-01-16762Penguins-Bears-
137 - 2019-01-19781Phantoms-Bears-
138 - 2019-01-20801Bears-Phantoms-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25822Bears-Penguins-
144 - 2019-01-26833IceHogs-Bears-
145 - 2019-01-27840Bears-Sound Tigers-
148 - 2019-01-30851Bears-Wolf Pack-
150 - 2019-02-01857Bears-Comets-
151 - 2019-02-02870Sound Tigers-Bears-
157 - 2019-02-08901Bears-Bruins-
158 - 2019-02-09912Bears-Bruins-
159 - 2019-02-10923Bears-Wolf Pack-
162 - 2019-02-13935Thunderbirds-Bears-
164 - 2019-02-15945Marlies-Bears-
165 - 2019-02-16956Sound Tigers-Bears-
168 - 2019-02-19972Penguins-Bears-
172 - 2019-02-23996Bears-Monsters-
173 - 2019-02-241009Bears-Monsters-
179 - 2019-03-021040Bruins-Bears-
180 - 2019-03-031054Bears-Sound Tigers-
184 - 2019-03-071072Bears-Marlies-
185 - 2019-03-081073Bears-Senators-
186 - 2019-03-091083Bears-Rocket-
189 - 2019-03-121105Phantoms-Bears-
192 - 2019-03-151122Bears-Wolf Pack-
193 - 2019-03-161129Comets-Bears-
194 - 2019-03-171146Wolf 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
36 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
460,558$ 82,000$ 60,440$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 5,922$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 180 32,897$ 5,921,460$




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
1353200000121022110000056-1321000007436122234012640109353440011332629330930.00%30680.00%05314835.81%5016829.76%277336.99%10973130376029
Total Saison Régulière53200000121022110000056-1321000007436122234012640109353440011332629330930.00%30680.00%05314835.81%5016829.76%277336.99%10973130376029
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