Bruins

GP: 6 | W: 4 | L: 2 | OTL: 0 | P: 8
GF: 17 | GA: 12 | PP%: 14.71% | PK%: 100.00%
DG: Steve Gagné | Morale : 53 | Moyenne d'Équipe : 62
Prochain matchs #88 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
1Antoine RousselXX100.008059546572757864567063726578713554660
2Chris WagnerXXX100.009458776374768962746163786175695155660
3Tim SchallerXXX100.008142836481687063736162786277693655650
4Tom KuhnhacklXX100.008336916180705959536258815773675255630
5Frederick GaudreauXX100.005635946372646862706364666271674355620
6Carter CamperX100.005036906165939160706256555879715455610
7Dmytro TimashovXX100.005438856461949365586254536566626355610
8Connor Bunnaman (R)X100.006536925979928858605558605861636455610
9Sam MileticX100.006236916174898360686356595863626355610
10Michael CarconeX100.005038856163928860655959546065636255600
11Giovanni FioreXX100.006036925675908555585354575265635455590
12Zac RinaldoXX100.009452696069605058535459625777704055590
13Anthony RichardXXX100.005435935863787257615956545865636155580
14Shawn O'Donnell (R)X100.006140805476908553525152545379715455580
15Nate ProsserX100.006636885981746358306056744982733955650
16Zach WhitecloudX100.006838855682949555305751594565636252630
17William Borgen (R)X100.006836905883897257305453594565636254620
18Luke Green (R)X100.006039825575716854305452544561636455570
Rayé
1Curtis McKenzieX100.006743726181949260686157605975685744630
2Liam O'BrienX100.006843715980949556585453565569656044600
3Jack Kopacka (R)X100.006535945980827458615654575561636444590
4Steven LorentzX100.007138845788797356585552595465636244590
5Yannick VeilleuxXXX100.006441765479898353545152555371665944580
6Spencer Smallman (R)X100.006340805977726858696252575465636244580
7Carson SoucyX100.007540795592939054305552594569655544640
8Brian StraitX100.006344645279778052305857605580675144610
9Gustav Bouramman (R)X100.005936925473787253305251555263626644580
MOYENNE D'ÉQUIPE100.00674083597682795854585661557066555161
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 Gibson100.00786866827776787776787773776355740
2Callum Booth (R)100.00706664836968706968706963677355680
Rayé
1Jeremy Smith100.00747876707372747372747378844344720
MOYENNE D'ÉQUIPE100.0074716978737274737274737176605171
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Doug Weight75717977747077USA483100,000$


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
1Chris WagnerBruins (Bos)C/LW/RW61452601212151086.67%213823.041123290000161051.50%16700000.7211000110
2Zach WhitecloudBruins (Bos)D60550155753450.00%416928.24011231000012000.00%000000.5900010000
3Frederick GaudreauBruins (Bos)C/LW6134-200113165156.25%010116.84022727000000050.57%8700000.7900000010
4Carter CamperBruins (Bos)C6033-30021014170.00%412120.320004160000130056.67%6000000.4900000000
5Antoine RousselBruins (Bos)LW/RW5303140109114327.27%011222.461015240000150037.50%800000.5301000110
6Zac RinaldoBruins (Bos)LW/RW6303100121112627.27%0437.19000000000000100.00%100001.3900000011
7Tom KuhnhacklBruins (Bos)LW/RW6213-140781741011.76%310918.20101528000081055.56%900000.5500000100
8Michael CarconeBruins (Bos)LW6033000065120.00%1528.6700000000000050.00%400001.1500000000
9Tim SchallerBruins (Bos)C/LW/RW6033100678260.00%112621.040223300000120043.75%1600000.4801000000
10Luke GreenBruins (Bos)D6112-1203341225.00%014424.04112323000015000.00%000000.2800000000
11Sam MileticBruins (Bos)LW61120202483212.50%06510.830000000001000.00%500000.6200000000
12William BorgenBruins (Bos)D5022-440585230.00%413727.47000420000015000.00%000000.2900000000
13Giovanni FioreBruins (Bos)LW/RW6101-1202260416.67%16310.6400000000000140.00%500000.3100000001
14Dmytro TimashovBruins (Bos)LW/RW6101-2001341625.00%010317.24101229000000037.50%800000.1900000000
15Connor BunnamanBruins (Bos)C61010000473514.29%2528.6700000000000036.00%5000000.3800000000
16Nate ProsserBruins (Bos)D61014402772914.29%1115425.77000325000015100.00%000000.1300000001
17Shawn O'DonnellBruins (Bos)RW6011000430000.00%1406.7500005000040042.86%700000.4900000000
18Anthony RichardBruins (Bos)C/LW/RW6000100010110.00%0162.7200000000070075.00%400000.0000000000
Stats d'équipe Total ou en Moyenne106162743-443576106141469411.35%34175116.5257124129300001403148.96%43100000.4913010343
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
1Christopher GibsonBruins (Bos)64200.8991.9836420121190101.000360000
Stats d'équipe Total ou en Moyenne64200.8991.9836420121190101.000360000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Anthony RichardBruins (Bos)C/LW/RW221996-12-20No163 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$NoLien
Antoine RousselBruins (Bos)LW/RW291989-11-21No199 Lbs5 ft11NoNoNo2Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Brian StraitBruins (Bos)D311988-01-04No206 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$NoLien
Callum BoothBruins (Bos)G221997-05-21Yes184 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Carson SoucyBruins (Bos)D241994-07-27No211 Lbs6 ft5NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Carter CamperBruins (Bos)C301988-07-06No176 Lbs5 ft9NoNoNo3Sans RestrictionPro & Farm311,002$0$0$NoLien
Chris WagnerBruins (Bos)C/LW/RW281991-05-27No198 Lbs6 ft0NoNoNo3Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Christopher GibsonBruins (Bos)G261992-12-27No207 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
Connor BunnamanBruins (Bos)C211998-04-16Yes207 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Curtis McKenzieBruins (Bos)LW281991-02-22No205 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm500,000$0$0$NoLien
Dmytro TimashovBruins (Bos)LW/RW221996-10-01No195 Lbs5 ft1NoNoNo2Contrat d'EntréePro & Farm500,000$0$0$NoLien
Frederick GaudreauBruins (Bos)C/LW261993-05-01No179 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Giovanni FioreBruins (Bos)LW/RW221996-08-13No188 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$NoLien
Gustav BourammanBruins (Bos)D221997-01-24Yes194 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Jack KopackaBruins (Bos)LW211998-03-05Yes197 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Jeremy SmithBruins (Bos)G301989-04-13No177 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Liam O'BrienBruins (Bos)LW241994-07-29No215 Lbs6 ft1NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Luke GreenBruins (Bos)D211998-01-12Yes188 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Michael CarconeBruins (Bos)LW231996-05-19No170 Lbs5 ft9NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Nate ProsserBruins (Bos)D331986-05-07No201 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Sam MileticBruins (Bos)LW221997-05-04No197 Lbs6 ft0NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Shawn O'DonnellBruins (Bos)RW311988-05-28Yes192 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$NoLien
Spencer SmallmanBruins (Bos)RW221996-09-09Yes198 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Steven LorentzBruins (Bos)LW231996-04-13No206 Lbs6 ft4NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Tim SchallerBruins (Bos)C/LW/RW281990-11-16No204 Lbs6 ft2NoNoNo1Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Tom KuhnhacklBruins (Bos)LW/RW271992-01-21No196 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm500,000$0$0$NoLien
William BorgenBruins (Bos)D221996-12-19Yes196 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Yannick VeilleuxBruins (Bos)C/LW/RW261993-02-22No195 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Zac RinaldoBruins (Bos)LW/RW291990-06-15No192 Lbs5 ft10NoNoNo3Sans RestrictionPro & Farm500,000$0$0$NoLien
Zach WhitecloudBruins (Bos)D221996-11-28No209 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3025.23195 Lbs6 ft13.07430,367$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Antoine RousselChris WagnerTim Schaller40122
2Tom KuhnhacklFrederick GaudreauDmytro Timashov30122
3Sam MileticCarter CamperGiovanni Fiore20122
4Michael CarconeConnor BunnamanZac Rinaldo10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate ProsserZach Whitecloud40122
2William BorgenLuke Green30122
3Nate ProsserZach Whitecloud20122
4William BorgenLuke Green10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Antoine RousselChris WagnerTim Schaller60122
2Tom KuhnhacklFrederick GaudreauDmytro Timashov40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate ProsserZach Whitecloud60122
2William BorgenLuke Green40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Chris WagnerAntoine Roussel60122
2Tim SchallerTom Kuhnhackl40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate ProsserZach Whitecloud60122
2William BorgenLuke Green40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Chris Wagner60122Nate ProsserZach Whitecloud60122
2Antoine Roussel40122William BorgenLuke Green40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Chris WagnerAntoine Roussel60122
2Tim SchallerTom Kuhnhackl40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate ProsserZach Whitecloud60122
2William BorgenLuke Green40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Antoine RousselChris WagnerTim SchallerNate ProsserZach Whitecloud
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Antoine RousselChris WagnerTim SchallerNate ProsserZach Whitecloud
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Shawn O'Donnell, Anthony Richard, Carter CamperShawn O'Donnell, Anthony RichardCarter Camper
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Prosser, Zach Whitecloud, William BorgenNate ProsserZach Whitecloud, William Borgen
Tirs de Pénalité
Chris Wagner, Antoine Roussel, Tim Schaller, Tom Kuhnhackl, Frederick Gaudreau
Gardien
#1 : Christopher Gibson, #2 : Callum Booth


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
1Rocket11000000312110000003120000000000021.0003580095213152434541756127114.29%30100.00%09819749.75%8216350.31%368641.86%150104138457636
2Sound Tigers1010000023-1000000000001010000023-100.0002460095212252434542971216200.00%60100.00%09819749.75%8216350.31%368641.86%150104138457636
3Thunderbirds10000010321000000000001000001032121.000347009521215243454144611400.00%30100.00%09819749.75%8216350.31%368641.86%150104138457636
Total63200010171252200000074341200010108280.667172744009521141524345411934457734514.71%200100.00%09819749.75%8216350.31%368641.86%150104138457636
5Wolf Pack32100000963110000004312110000053240.667914230095216752434545918213821419.05%80100.00%09819749.75%8216350.31%368641.86%150104138457636
_Since Last GM Reset63200010171252200000074341200010108280.667172744009521141524345411934457734514.71%200100.00%09819749.75%8216350.31%368641.86%150104138457636
_Vs Conference422000001192110000004313120000076140.5001118290095218952434548825335423417.39%140100.00%09819749.75%8216350.31%368641.86%150104138457636

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
68L117274414111934457700
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
63200101712
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
220000074
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
4120010108
Derniers 10 Matchs
WLOTWOTL SOWSOL
320010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
34514.71%200100.00%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
52434549521
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
9819749.75%8216350.31%368641.86%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
150104138457636


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 - 2019-09-044Bruins4Wolf Pack1WSommaire du Match
4 - 2019-09-0516Rocket1Bruins3WSommaire du Match
10 - 2019-09-1136Bruins1Wolf Pack2LSommaire du Match
11 - 2019-09-1251Wolf Pack3Bruins4WSommaire du Match
12 - 2019-09-1359Bruins3Thunderbirds2WXXSommaire du Match
17 - 2019-09-1869Bruins2Sound Tigers3LSommaire du Match
18 - 2019-09-1988Sound Tigers-Bruins-
25 - 2019-09-26123Bruins-Thunderbirds-
26 - 2019-09-27131Sound Tigers-Bruins-
31 - 2019-10-02139Bruins-Checkers-
32 - 2019-10-03154Bruins-Checkers-
38 - 2019-10-09184Penguins-Bruins-
39 - 2019-10-10194Bruins-Sound Tigers-
40 - 2019-10-11206Penguins-Bruins-
45 - 2019-10-16227Phantoms-Bruins-
46 - 2019-10-17245Americans-Bruins-
50 - 2019-10-21257Bruins-Wolf Pack-
53 - 2019-10-24281Bruins-Phantoms-
54 - 2019-10-25292Bruins-Penguins-
59 - 2019-10-30311Checkers-Bruins-
60 - 2019-10-31322Bruins-Sound Tigers-
61 - 2019-11-01332Checkers-Bruins-
64 - 2019-11-04341Bruins-Marlies-
66 - 2019-11-06353Bruins-Americans-
67 - 2019-11-07365Bruins-Senators-
71 - 2019-11-11383Bruins-Comets-
73 - 2019-11-13393Sound Tigers-Bruins-
74 - 2019-11-14408Bears-Bruins-
78 - 2019-11-18424Bruins-Wolf Pack-
80 - 2019-11-20438Bruins-Devils-
81 - 2019-11-21459Bruins-Thunderbirds-
87 - 2019-11-27478Bruins-Phantoms-
88 - 2019-11-28488Bruins-Bears-
89 - 2019-11-29501Bruins-Bears-
94 - 2019-12-04520Phantoms-Bruins-
95 - 2019-12-05537Bruins-Thunderbirds-
96 - 2019-12-06546Wolf Pack-Bruins-
101 - 2019-12-11565Wolf Pack-Bruins-
102 - 2019-12-12581Bruins-Thunderbirds-
103 - 2019-12-13588Thunderbirds-Bruins-
108 - 2019-12-18607Thunderbirds-Bruins-
109 - 2019-12-19620Bruins-Sound Tigers-
110 - 2019-12-20634Wolf Pack-Bruins-
115 - 2019-12-25658Checkers-Bruins-
116 - 2019-12-26678Thunderbirds-Bruins-
122 - 2020-01-01684Bruins-Checkers-
123 - 2020-01-02699Bruins-Checkers-
129 - 2020-01-08724Sound Tigers-Bruins-
130 - 2020-01-09736Bruins-Sound Tigers-
131 - 2020-01-10752Crunch-Bruins-
136 - 2020-01-15773Marlies-Bruins-
137 - 2020-01-16786Checkers-Bruins-
138 - 2020-01-17796Thunderbirds-Bruins-
143 - 2020-01-22821Sound Tigers-Bruins-
144 - 2020-01-23830Bruins-Wolf Pack-
145 - 2020-01-24842Wolf Pack-Bruins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29861Penguins-Bruins-
151 - 2020-01-30874Bruins-Thunderbirds-
152 - 2020-01-31882Thunderbirds-Bruins-
157 - 2020-02-05901Bears-Bruins-
158 - 2020-02-06912Bears-Bruins-
159 - 2020-02-07925Thunderbirds-Bruins-
164 - 2020-02-12949Bruins-Phantoms-
165 - 2020-02-13962Bruins-Penguins-
169 - 2020-02-17980Bruins-Rocket-
171 - 2020-02-19986Senators-Bruins-
172 - 2020-02-201000Devils-Bruins-
176 - 2020-02-241020Bruins-Penguins-
178 - 2020-02-261027Bruins-Crunch-
179 - 2020-02-271040Bruins-Bears-
185 - 2020-03-041075Sound Tigers-Bruins-
186 - 2020-03-051087Bruins-Sound Tigers-
187 - 2020-03-061101Comets-Bruins-
192 - 2020-03-111119Phantoms-Bruins-
193 - 2020-03-121135Bruins-Thunderbirds-
194 - 2020-03-131143Thunderbirds-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
20,077$ 129,110$ 24,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 11,322$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 177 1,181$ 209,037$




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
146320001017125220000007434120001010828172744009521141524345411934457734514.71%200100.00%09819749.75%8216350.31%368641.86%150104138457636
Total Saison Régulière6320001017125220000007434120001010828172744009521141524345411934457734514.71%200100.00%09819749.75%8216350.31%368641.86%150104138457636