Bruins

GP: 5 | W: 5 | L: 0 | OTL: 0 | P: 10
GF: 27 | GA: 13 | PP%: 31.82% | PK%: 85.19%
DG: Steve Gagné | Morale : 57 | Moyenne d'Équipe : N/A
Prochain matchs #69 vs Sound Tigers
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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
1Giovanni Fiore (R)XX100.0075557870727078605055615555665015500
2Pascal Pelletier (R)X100.0056555555555555555055555555505015100
3Curtis McKenzieX100.0090555975777063605061606055727215800
4Anthony Richard (R)X100.0059557262605974555055555755727315800
5Dmytro Timashov (R)X100.0065556767736469555055555555757315800
6Shawn Ouellette-St. Amant (R)X100.0076556565746665555055555555505015800
7Zac RinaldoXX100.0092555574837574685962657255757415500
8Justin FlorekX100.0059556362797272555055555555505015800
9Matej StranskyX100.0060555966797572555055555555505015800
10Louis-Marc AubryX100.0056555555555655555055555555505015800
11Ben SmithX100.0059556071776765565055565555757415800
12Yannick VeilleuxX100.0070556663787169555055555555505015800
13Liam O'BrienX100.0060555868797269605060606055505015800
14Andrej SekeraX100.0074559189857990752567608355848215800
15Chris WidemanX100.0070556480827171752574697055817715500
16Carson Soucy (R)X100.0055555560555556552555555555555515800
17Nate ProsserX100.0080558372777364692563657655817815800
Rayé
1Clarke MacArthurX100.0055555555555555555055555555737214500
2Jordan CaronX100.0056555555555655555055555555606114500
3Jack SkilleX100.0055555555555555555055555555686914500
4Brian StraitX100.0055555560555576552555555555646514500
5Loic LeducX100.0055555560555557552555555555535314500
6Maxime FortunusX100.0055555560555568552555555555535314500
MOYENNE D'ÉQUIPE100.006555626568646659435757595563621540
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
1Christopher Gibson100.006570727369696868706955686615800
2Michael Leighton100.007678778471717676797555706815300
Rayé
1Philippe Desrosiers100.005565597161616059606055565814500
2Jeremy Smith100.006274606570705956596855606314500
MOYENNE D'ÉQUIPE100.00657267736868666567685564641500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Martin Gelinas59697163687067CAN451100,000$


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
1Andrej SekeraBruins (Bos)D54610660103161925.00%413426.98112913011019000.00%000001.4800000101
2Giovanni FioreBruins (Bos)LW/RW53695601062591012.00%111723.540333140000102186.67%1500001.5300000011
3Nate ProsserBruins (Bos)D52797602410135815.38%912525.16022811000016100.00%000001.4300000110
4Zac RinaldoBruins (Bos)LW/RW5448416018132482016.67%012324.651121111012141162.77%9400001.3000000110
5Louis-Marc AubryBruins (Bos)C535872010883737.50%09118.22112114000001066.34%10100001.7600000100
6Chris WidemanBruins (Bos)D5347620116931133.33%412625.35101511011017000.00%000001.1000000111
7Ben SmithBruins (Bos)RW5347640731851116.67%29118.310223150000000100.00%400001.5300000002
8Curtis McKenzieBruins (Bos)RW521322017101421214.29%111422.871011120000220086.67%4500000.5200000000
9Justin FlorekBruins (Bos)LW5213-1002372228.57%25911.93202350000110083.33%1200001.0100000000
10Liam O'BrienBruins (Bos)LW503322038145120.00%18316.67000200000110066.67%300000.7200000000
11Anthony RichardBruins (Bos)C5022100096170.00%17515.000110120002110075.27%9300000.5300000000
12Dmytro TimashovBruins (Bos)LW51120000232233.33%0326.4100000000000050.00%200001.2500000000
13Matej StranskyBruins (Bos)RW50222000211260.00%06913.8400000000000050.00%400000.5800000000
14Shawn Ouellette-St. AmantBruins (Bos)LW5011020522040.00%07214.58011270000210091.67%1200000.2700000000
15Carson SoucyBruins (Bos)D5011560612010.00%211122.33000010000013000.00%000000.1800000000
16Yannick VeilleuxBruins (Bos)LW5000020321000.00%2306.0700012000060050.00%200000.0000000000
Stats d'équipe Total ou en Moyenne8027487552560126881734812215.61%29145918.24712193914412341775272.09%38700001.0300000545
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
1Michael LeightonBruins (Bos)54000.8692.962640013990000.000050000
2Christopher GibsonBruins (Bos)11001.0000.0039000100000.000005000
Stats d'équipe Total ou en Moyenne65000.8812.5730300131090000.000055000


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
Andrej SekeraBruins (Bos)D301986-06-07No201 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm4,785,001$0$0$No4,785,001$
Anthony RichardBruins (Bos)C201996-12-20Yes163 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Ben SmithBruins (Bos)RW281988-07-10No199 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm500,000$0$0$No
Brian StraitBruins (Bos)D291988-01-03No209 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Carson SoucyBruins (Bos)D221994-07-27Yes212 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Chris WidemanBruins (Bos)D271990-01-07No180 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm500,000$0$0$No500,000$
Christopher GibsonBruins (Bos)G241992-12-27No188 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Clarke MacArthurBruins (Bos)LW311985-04-06No194 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Curtis McKenzieBruins (Bos)RW251991-02-22No192 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Dmytro TimashovBruins (Bos)LW201996-10-01Yes192 Lbs5 ft9NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No500,000$500,000$
Giovanni FioreBruins (Bos)LW/RW201996-08-13Yes194 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Jack SkilleBruins (Bos)RW291987-05-19No216 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Jeremy SmithBruins (Bos)G271989-04-13No178 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Jordan CaronBruins (Bos)RW261990-11-02No204 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Justin FlorekBruins (Bos)LW261990-05-18No199 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Liam O'BrienBruins (Bos)LW221994-07-29No205 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Loic LeducBruins (Bos)D221994-06-14No222 Lbs6 ft7NoNoNo2Contrat d'EntréePro & Farm300,000$0$0$No300,000$
Louis-Marc AubryBruins (Bos)C251991-11-11No208 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$No300,000$
Matej StranskyBruins (Bos)RW231993-07-10No210 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Maxime FortunusBruins (Bos)D331983-07-27No202 Lbs5 ft11NoNoNo4Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Michael LeightonBruins (Bos)G351981-05-18No186 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm500,000$0$0$No500,000$
Nate ProsserBruins (Bos)D301986-05-06No203 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Pascal PelletierBruins (Bos)LW331983-06-16Yes191 Lbs5 ft11NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Philippe DesrosiersBruins (Bos)G211995-08-16No195 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$No500,000$
Shawn Ouellette-St. AmantBruins (Bos)LW201996-11-18Yes198 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$
Yannick VeilleuxBruins (Bos)LW231993-02-21No206 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Zac RinaldoBruins (Bos)LW/RW261990-06-14No169 Lbs5 ft11NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No500,000$500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2725.81197 Lbs6 ft12.41592,037$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Zac RinaldoAnthony RichardCurtis McKenzie40122
2Giovanni FioreLouis-Marc AubryBen Smith30122
3Liam O'BrienZac RinaldoMatej Stransky20122
4Dmytro TimashovCurtis McKenzieGiovanni Fiore10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrej SekeraChris Wideman40122
2Nate ProsserCarson Soucy30122
3Andrej SekeraChris Wideman20122
4Nate ProsserCarson Soucy10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Zac RinaldoAnthony RichardCurtis McKenzie60122
2Giovanni FioreLouis-Marc AubryBen Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrej SekeraChris Wideman60122
2Nate ProsserCarson Soucy40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Zac RinaldoCurtis McKenzie60122
2Giovanni FioreLiam O'Brien40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrej SekeraChris Wideman60122
2Nate ProsserCarson Soucy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Zac Rinaldo60122Andrej SekeraChris Wideman60122
2Curtis McKenzie40122Nate ProsserCarson Soucy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Zac RinaldoCurtis McKenzie60122
2Giovanni FioreLiam O'Brien40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Andrej SekeraChris Wideman60122
2Nate ProsserCarson Soucy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zac RinaldoAnthony RichardCurtis McKenzieAndrej SekeraChris Wideman
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zac RinaldoAnthony RichardCurtis McKenzieAndrej SekeraChris Wideman
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Florek, Yannick Veilleux, Shawn Ouellette-St. AmantJustin Florek, Yannick VeilleuxShawn Ouellette-St. Amant
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Andrej Sekera, Chris Wideman, Nate ProsserAndrej SekeraChris Wideman, Nate Prosser
Tirs de Pénalité
Zac Rinaldo, Curtis McKenzie, Giovanni Fiore, Liam O'Brien, Ben Smith
Gardien
#1 : Michael Leighton, #2 : Christopher Gibson


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
1Rocket10001000321100010003210000000000021.000358009134128535761224920226233.33%100100.00%011816671.08%9213170.23%698680.23%16712678275734
2Thunderbirds11000000734000000000001100000073421.0007111800913413753576122768258337.50%4175.00%111816671.08%9213170.23%698680.23%16712678275734
Total54001000271314210010008443300000019910101.00027487500913411735357612109295612622731.82%27485.19%111816671.08%9213170.23%698680.23%16712678275734
4Wolf Pack3300000017891100000052322000000126661.00017324900913411085357612581428798225.00%13376.92%011816671.08%9213170.23%698680.23%16712678275734
_Since Last GM Reset54001000271314210010008443300000019910101.00027487500913411735357612109295612622731.82%27485.19%111816671.08%9213170.23%698680.23%16712678275734
_Vs Conference3300000017891100000052322000000126661.00017324900913411085357612581428798225.00%13376.92%011816671.08%9213170.23%698680.23%16712678275734

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
510W3274875173109295612600
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
54010002713
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
210100084
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3300000199
Derniers 10 Matchs
WLOTWOTL SOWSOL
401000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
22731.82%27485.19%1
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
535761291341
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
11816671.08%9213170.23%698680.23%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
16712678275734


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
3 - 2018-09-074Bruins6Wolf Pack4WSommaire du Match
4 - 2018-09-0816Rocket2Bruins3WXSommaire du Match
10 - 2018-09-1436Bruins6Wolf Pack2WSommaire du Match
11 - 2018-09-1551Wolf Pack2Bruins5WSommaire du Match
12 - 2018-09-1659Bruins7Thunderbirds3WSommaire du Match
17 - 2018-09-2169Bruins-Sound Tigers-
18 - 2018-09-2288Sound Tigers-Bruins-
25 - 2018-09-29123Bruins-Thunderbirds-
26 - 2018-09-30131Sound Tigers-Bruins-
31 - 2018-10-05139Bruins-Checkers-
32 - 2018-10-06154Bruins-Checkers-
38 - 2018-10-12184Penguins-Bruins-
39 - 2018-10-13194Bruins-Sound Tigers-
40 - 2018-10-14206Penguins-Bruins-
45 - 2018-10-19227Phantoms-Bruins-
46 - 2018-10-20245Americans-Bruins-
50 - 2018-10-24257Bruins-Wolf Pack-
53 - 2018-10-27281Bruins-Phantoms-
54 - 2018-10-28292Bruins-Penguins-
59 - 2018-11-02311Checkers-Bruins-
60 - 2018-11-03322Bruins-Sound Tigers-
61 - 2018-11-04332Checkers-Bruins-
64 - 2018-11-07341Bruins-Marlies-
66 - 2018-11-09353Bruins-Americans-
67 - 2018-11-10365Bruins-Senators-
71 - 2018-11-14383Bruins-Comets-
73 - 2018-11-16393Sound Tigers-Bruins-
74 - 2018-11-17408Bears-Bruins-
78 - 2018-11-21424Bruins-Wolf Pack-
80 - 2018-11-23438Bruins-Devils-
81 - 2018-11-24459Bruins-Thunderbirds-
87 - 2018-11-30478Bruins-Phantoms-
88 - 2018-12-01488Bruins-Bears-
89 - 2018-12-02501Bruins-Bears-
94 - 2018-12-07520Phantoms-Bruins-
95 - 2018-12-08537Bruins-Thunderbirds-
96 - 2018-12-09546Wolf Pack-Bruins-
101 - 2018-12-14565Wolf Pack-Bruins-
102 - 2018-12-15581Bruins-Thunderbirds-
103 - 2018-12-16588Thunderbirds-Bruins-
108 - 2018-12-21607Thunderbirds-Bruins-
109 - 2018-12-22620Bruins-Sound Tigers-
110 - 2018-12-23634Wolf Pack-Bruins-
115 - 2018-12-28658Checkers-Bruins-
116 - 2018-12-29678Thunderbirds-Bruins-
122 - 2019-01-04684Bruins-Checkers-
123 - 2019-01-05699Bruins-Checkers-
129 - 2019-01-11724Sound Tigers-Bruins-
130 - 2019-01-12736Bruins-Sound Tigers-
131 - 2019-01-13752Crunch-Bruins-
136 - 2019-01-18773Marlies-Bruins-
137 - 2019-01-19786Checkers-Bruins-
138 - 2019-01-20796Thunderbirds-Bruins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25821Sound Tigers-Bruins-
144 - 2019-01-26830Bruins-Wolf Pack-
145 - 2019-01-27842Wolf Pack-Bruins-
150 - 2019-02-01861Penguins-Bruins-
151 - 2019-02-02874Bruins-Thunderbirds-
152 - 2019-02-03882Thunderbirds-Bruins-
157 - 2019-02-08901Bears-Bruins-
158 - 2019-02-09912Bears-Bruins-
159 - 2019-02-10925Thunderbirds-Bruins-
164 - 2019-02-15949Bruins-Phantoms-
165 - 2019-02-16962Bruins-Penguins-
169 - 2019-02-20980Bruins-Rocket-
171 - 2019-02-22986Senators-Bruins-
172 - 2019-02-231000Devils-Bruins-
176 - 2019-02-271020Bruins-Penguins-
178 - 2019-03-011027Bruins-Crunch-
179 - 2019-03-021040Bruins-Bears-
185 - 2019-03-081075Sound Tigers-Bruins-
186 - 2019-03-091087Bruins-Sound Tigers-
187 - 2019-03-101101Comets-Bruins-
192 - 2019-03-151119Phantoms-Bruins-
193 - 2019-03-161135Bruins-Thunderbirds-
194 - 2019-03-171143Thunderbirds-Bruins-



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
18,746$ 159,850$ 121,150$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 11,536$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 180 1,339$ 241,020$




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
13540010002713142100100084433000000199101027487500913411735357612109295612622731.82%27485.19%111816671.08%9213170.23%698680.23%16712678275734
Total Saison Régulière540010002713142100100084433000000199101027487500913411735357612109295612622731.82%27485.19%111816671.08%9213170.23%698680.23%16712678275734
Séries
1240400000714-72020000048-42020000036-30714210022307632202401004693813339.09%35682.86%05612345.53%5113438.06%287238.89%8253109324822
1240400000714-72020000048-42020000036-30714210022307632202401004693813339.09%35682.86%05612345.53%5113438.06%287238.89%8253109324822
Total Séries808000001428-1440400000816-840400000612-601428420044601526440480200921861626669.09%701282.86%011224645.53%10226838.06%5614438.89%164106219649644