Bruins

GP: 26 | W: 17 | L: 8 | OTL: 1 | P: 35
GF: 80 | GA: 43 | PP%: 13.14% | PK%: 85.11%
DG: Steve Gagné | Morale : 61 | Moyenne d'Équipe : 62
Prochain matchs #393 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
1Chris WagnerXXX100.009458776374768962746163786175695167660
2Tim SchallerXXX100.008142836481687063736162786277693667650
3Tom KuhnhacklXX100.008336916180705959536258815773675267640
4Frederick GaudreauXX100.005635946372646862706364666271674367620
5Connor Bunnaman (R)X100.006536925979928858605558605861636467610
6Sam MileticX100.006236916174898360686356595863626367610
7Michael CarconeX100.005038856163928860655959546065636267600
8Giovanni FioreXX100.006036925675908555585354575265635467590
9Anthony RichardXXX100.005435935863787257615956545865636167580
10Shawn O'Donnell (R)X100.006140805476908553525152545379715467580
11Slater KoekkoekX100.007339846579815063306462715369658367650
12William Borgen (R)X100.006836905883897257305453594565636263620
13Luke Green (R)X100.006039825575716854305452544561636470570
Rayé
1Curtis McKenzieX100.006743726181949260686157605975685724630
2Kevin RooneyX100.006843905978796658735657715971775149620
3Carter CamperX100.005036906165939160706256555879715438610
4Liam O'BrienX100.006843715980949556585453565569656024600
5Zac RinaldoXX100.009452696069605058535459625777704039590
6Jack Kopacka (R)X100.006535945980827458615654575561636424590
7Steven LorentzX100.007138845788797356585552595465636224590
8Cameron HughesX100.005337875954908458615756525765636220580
9Spencer Smallman (R)X100.006340805977726858696252575465636224580
10Yannick VeilleuxXXX100.006441765479898353545152555371665924570
11Carson SoucyX100.007540795592939054305552594569655524630
12Brian StraitX100.006344645279778052305857605580675124600
13Gustav Bouramman (R)X100.005936925473787253305251555263626624570
MOYENNE D'ÉQUIPE100.00664084597682775855575661556966574761
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 Gibson100.00786866827776787776787773776367740
2Callum Booth (R)100.00706664836968706968706963677367680
Rayé
1Jeremy Smith100.00747876707372747372747378844324720
MOYENNE D'ÉQUIPE100.0074716978737274737274737176605371
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/RW2614112516240716892326315.22%1362424.01437241100224813059.41%74400020.8012000414
2Tom KuhnhacklBruins (Bos)LW/RW26131124102204734118336611.02%950919.59448241131121356050.00%4200000.9411000402
3Antoine RousselBoston BruinsLW/RW245152014351543385617498.93%1053622.37257161001014780048.98%4900000.7401111130
4Tim SchallerBruins (Bos)C/LW/RW269101912120244276194111.84%1250019.25347201121121431156.67%6000000.7602000131
5Frederick GaudreauBruins (Bos)C/LW26613198606556929548.70%346918.0714515109000040158.54%48000000.8100000030
6Slater KoekkoekBruins (Bos)D30514197360652450203310.00%2873924.6424629121000096000.00%000000.5100000214
7Connor BunnamanBruins (Bos)C2668147180202956102710.71%1244116.990224370110162150.99%25300000.6300000111
8Sam MileticBruins (Bos)LW26481278024194212339.52%845717.611121063101160033.33%1800000.5200000000
9William BorgenBruins (Bos)D25011111236103418287160.00%1365626.270001697000064000.00%000000.3300001020
10Giovanni FioreBruins (Bos)LW/RW26551054012194451911.36%541515.97022471000051172.41%2900000.4800000001
11Luke GreenBruins (Bos)D2618910135348156106.67%1063224.341341196000063000.00%000000.2800100001
12Michael CarconeBruins (Bos)LW2616712405293413232.94%339515.230001140000211053.45%5800000.3500000010
13Nate ProsserBoston BruinsD14246912010121551613.33%1736025.76000655000040100.00%000000.3300000002
14Anthony RichardBruins (Bos)C/LW/RW253258605212431612.50%329811.941015150001260045.65%9200000.3400000011
15Shawn O'DonnellBruins (Bos)RW26134860161113997.69%426210.110000160000120063.33%3000000.3000000000
16Carter CamperBruins (Bos)C7033-30031016280.00%413519.290004160000140057.14%7000000.4400000000
17Zac RinaldoBruins (Bos)LW/RW6303100121112627.27%0437.19000000000000100.00%100001.3900000011
Stats d'équipe Total ou en Moyenne391781322101432423043143875922448910.28%154748019.1319325118911524591261115456.65%192600020.5626212131718
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)2617810.9141.64156925435010201.0006260112
Stats d'équipe Total ou en Moyenne2617810.9141.64156925435010201.0006260112


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
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
Cameron HughesBruins (Bos)C221996-10-06No160 Lbs5 ft1NoNoNo3Contrat 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
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
Kevin RooneyBruins (Bos)C261993-05-21No190 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$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
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
Slater KoekkoekBruins (Bos)D251994-02-18No193 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm500,000$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
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2924.97193 Lbs6 ft13.17403,828$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tim SchallerChris WagnerTom Kuhnhackl40122
2Sam MileticFrederick GaudreauGiovanni Fiore30122
3Michael CarconeConnor BunnamanShawn O'Donnell20122
4Chris WagnerAnthony RichardTim Schaller10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekWilliam Borgen40122
2Luke GreenConnor Bunnaman30122
3Slater KoekkoekWilliam Borgen20122
4Luke GreenTom Kuhnhackl10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Tim SchallerChris WagnerTom Kuhnhackl60122
2Sam MileticFrederick GaudreauGiovanni Fiore40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekWilliam Borgen60122
2Luke GreenConnor Bunnaman40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Chris WagnerTim Schaller60122
2Tom KuhnhacklFrederick Gaudreau40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekWilliam Borgen60122
2Luke Green40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Chris Wagner60122Slater KoekkoekWilliam Borgen60122
2Tim Schaller40122Luke Green40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Chris WagnerTim Schaller60122
2Tom KuhnhacklFrederick Gaudreau40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekWilliam Borgen60122
2Luke Green40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tim SchallerChris WagnerTom KuhnhacklSlater KoekkoekWilliam Borgen
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Tim SchallerChris WagnerTom KuhnhacklSlater KoekkoekWilliam Borgen
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Carcone, Shawn O'Donnell, Anthony RichardMichael Carcone, Shawn O'DonnellAnthony Richard
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Slater Koekkoek, William Borgen, Luke GreenSlater KoekkoekWilliam Borgen, Luke Green
Tirs de Pénalité
Chris Wagner, Tim Schaller, Tom Kuhnhackl, Frederick Gaudreau, Connor Bunnaman
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
1Americans21100000330110000003211010000001-120.500347003225212612552212809457233310110.00%8275.00%054188960.85%37470852.82%18934854.31%710510544181316167
2Checkers44000000250252200000012012220000001301381.00025467104322521219125522128095218249220525.00%100100.00%154188960.85%37470852.82%18934854.31%710510544181316167
3Comets10000010321000000000001000001032121.0003470032252122225522128092676145120.00%20100.00%054188960.85%37470852.82%18934854.31%710510544181316167
4Marlies11000000817000000000001100000081721.000814220032252124625522128091144124125.00%20100.00%054188960.85%37470852.82%18934854.31%710510544181316167
5Penguins3120000046-2211000003301010000013-220.3334812003225212632552212809842053571815.56%18383.33%054188960.85%37470852.82%18934854.31%710510544181316167
6Phantoms22000000413110000001011100000031241.0004711013225212442552212809321116301100.00%70100.00%154188960.85%37470852.82%18934854.31%710510544181316167
7Rocket11000000312110000003120000000000021.0003580032252123125522128091756127114.29%30100.00%054188960.85%37470852.82%18934854.31%710510544181316167
8Senators1010000014-3000000000001010000014-300.000123003225212302552212809185620300.00%3233.33%054188960.85%37470852.82%18934854.31%710510544181316167
9Sound Tigers523000001011-12110000056-13120000055040.400101929003225212123255221280910431497219315.79%22481.82%054188960.85%37470852.82%18934854.31%710510544181316167
10Thunderbirds20000110660000000000002000011066030.7506814003225212572552212809321110221000.00%5260.00%254188960.85%37470852.82%18934854.31%710510544181316167
Total2615800120804337108200000311516167600120492821350.6738013821805322521275925522128095011412434121371813.14%941485.11%454188960.85%37470852.82%18934854.31%710510544181316167
12Wolf Pack431000001385110000004313210000095460.7501321340032252129125522128098022464830516.67%14192.86%054188960.85%37470852.82%18934854.31%710510544181316167
_Since Last GM Reset2615800120804337108200000311516167600120492821350.6738013821805322521275925522128095011412434121371813.14%941485.11%454188960.85%37470852.82%18934854.31%710510544181316167
_Vs Conference1587000003230264200000131219450000019181160.53332578901322521235125522128093188917022781911.11%641084.38%154188960.85%37470852.82%18934854.31%710510544181316167

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2635SOW18013821875950114124341205
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2615801208043
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
108200003115
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
167601204928
Derniers 10 Matchs
WLOTWOTL SOWSOL
630010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1371813.14%941485.11%4
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
25522128093225212
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
54188960.85%37470852.82%18934854.31%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
710510544181316167


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 Tigers2Bruins4WSommaire du Match
25 - 2019-09-26123Bruins3Thunderbirds4LXSommaire du Match
26 - 2019-09-27131Sound Tigers4Bruins1LSommaire du Match
31 - 2019-10-02139Bruins9Checkers0WSommaire du Match
32 - 2019-10-03154Bruins4Checkers0WSommaire du Match
38 - 2019-10-09184Penguins1Bruins2WSommaire du Match
39 - 2019-10-10194Bruins0Sound Tigers1LSommaire du Match
40 - 2019-10-11206Penguins2Bruins1LSommaire du Match
45 - 2019-10-16227Phantoms0Bruins1WSommaire du Match
46 - 2019-10-17245Americans2Bruins3WSommaire du Match
50 - 2019-10-21257Bruins4Wolf Pack2WSommaire du Match
53 - 2019-10-24281Bruins3Phantoms1WSommaire du Match
54 - 2019-10-25292Bruins1Penguins3LSommaire du Match
59 - 2019-10-30311Checkers0Bruins8WSommaire du Match
60 - 2019-10-31322Bruins3Sound Tigers1WSommaire du Match
61 - 2019-11-01332Checkers0Bruins4WSommaire du Match
64 - 2019-11-04341Bruins8Marlies1WSommaire du Match
66 - 2019-11-06353Bruins0Americans1LSommaire du Match
67 - 2019-11-07365Bruins1Senators4LSommaire du Match
71 - 2019-11-11383Bruins3Comets2WXXSommaire du Match
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
28 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
82,997$ 117,110$ 16,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 45,901$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 122 1,119$ 136,518$




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
142615800120804337108200000311516167600120492821358013821805322521275925522128095011412434121371813.14%941485.11%454188960.85%37470852.82%18934854.31%710510544181316167
Total Saison Régulière2615800120804337108200000311516167600120492821358013821805322521275925522128095011412434121371813.14%941485.11%454188960.85%37470852.82%18934854.31%710510544181316167