Bruins

GP: 50 | W: 38 | L: 10 | OTL: 2 | P: 78
GF: 171 | GA: 94 | PP%: 15.79% | PK%: 86.27%
DG: Steve Gagné | Morale : 82 | Moyenne d'Équipe : 59
Prochain matchs #773 vs Marlies
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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
1Curtis McKenzieX97.00905559757770636050616060557272191630
2Giovanni Fiore (R)XX97.00755578707270786050556155556650189600
3Liam O'BrienX97.00605558687972696050606060555050190600
4Ben SmithX97.00595560717767655650555655557574191590
5Dmytro Timashov (R)X99.00655567677364695550555555557573188580
6Matej StranskyX100.00605559667975725550555555555050191580
7Anthony Richard (R)X100.00595572626059745550555557557273191570
8Shawn Ouellette-St. Amant (R)X100.00765565657466655550555555555050187570
9Justin FlorekX100.00595563627972725550555555555050191570
10Yannick VeilleuxX100.00705566637871695550555555555050191570
11Jack SkilleX100.00555555555555555550555555556869142540
12Nate ProsserX99.00805583727773646925636576558178188690
13Loic LeducX100.00555555605555575525555555555353143540
14Maxime FortunusX100.00555555605555685525555555555353143540
Rayé
1Zac RinaldoXX100.00925555748375746859626572557574161670
2Clarke MacArthurX100.00555555555555555550555555557372119540
3Pascal Pelletier (R)X100.00565555555555555550555555555050145530
4Louis-Marc AubryX91.73565555555556555550555555555050180530
5Jordan CaronX100.00565555555556555550555555556061119530
6Brian StraitX100.00555555605555765525555555556465114550
7Carson Soucy (R)X96.86555555605555565525555555555555178540
MOYENNE D'ÉQUIPE98.7164556163676365574456575755626116857
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
1Michael Leighton97.0076787784717176767975557068188730
2Christopher Gibson100.0065707273696968687069556866189670
Rayé
1Jeremy Smith100.0062746065707059565968556063119620
2Philippe Desrosiers100.0055655971616160596060555658121590
MOYENNE D'ÉQUIPE99.256572677368686665676855646415465
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
1Nate ProsserBruins (Bos)D471249613591515573109427411.01%70114524.3751015671600220159410.00%100001.0700100483
2Curtis McKenzieBruins (Bos)RW502026462968014679137399914.60%12115523.1055102817210122105163.34%43100000.8001000442
3Giovanni FioreBruins (Bos)LW/RW50182442373208480144419312.50%8108721.7557123817100031336158.88%21400000.7701000328
4Zac RinaldoBruins (Bos)LW/RW3821183917735118116150479014.00%2291324.0327926146202101475160.91%63700020.8501000821
5Liam O'BrienBruins (Bos)LW50151934244557768120408312.50%13101220.2637102113600031185148.98%9800000.6711100233
6Louis-Marc AubryBruins (Bos)C4915173227415447672195220.83%279216.182798132000085056.61%77900000.8100001421
7Ben SmithBruins (Bos)RW5010223229300414810430879.62%1186517.32145221390000231056.76%3700000.7400000206
8Anthony RichardBruins (Bos)C50111728294077770205515.71%274814.98369181790004781256.93%86600000.7500000230
9Matej StranskyBruins (Bos)RW50612181215516419022566.67%458811.77000210000001062.96%2700000.6100100002
10Carson SoucyBruins (Bos)D5011415296607729359262.86%38109521.92044171490001160000.00%100000.2700000020
11Shawn Ouellette-St. AmantBruins (Bos)LW5031114728065326517464.62%860712.140227540000760061.40%11400000.4600000101
12Dmytro TimashovBruins (Bos)LW505813320028255712348.77%856611.340114330000271057.14%2800000.4600000010
13Justin FlorekBruins (Bos)LW5066121180162346143013.04%950410.083038410000580060.27%7300000.4800000002
14Maxime FortunusBruins (Bos)D13257141002481331115.38%1128922.26112728000046000.00%000000.4800000010
15Loic LeducBruins (Bos)D131561418022564516.67%1125019.24011218000032000.00%000000.4800000010
16Yannick VeilleuxBruins (Bos)LW50336416025201711817.65%104188.3710184900021291053.68%9500000.2900000000
17Jack SkilleBruins (Bos)RW13235400311182811.11%11118.6100000000000050.00%800000.8900000000
18Pascal PelletierBruins (Bos)LW110000401152240.00%416214.730000150000390053.85%1300000.0000000000
Stats d'équipe Total ou en Moyenne73415125941032556925959816125536487112.03%2441231616.78316293283164032525145235758.42%342200020.6714301302929
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)50371020.9161.892982479411210001.0004500332
2Christopher GibsonBruins (Bos)11001.0000.0039000100000.0000050000
Stats d'équipe Total ou en Moyenne51381020.9171.873021479411310001.00045050332


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)C201996-12-20Yes163 Lbs5 ft10NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
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$0$No
Carson SoucyBruins (Bos)D221994-07-27Yes212 Lbs6 ft4NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
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$0$No
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$0$No
Giovanni FioreBruins (Bos)LW/RW201996-08-13Yes194 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Jack SkilleBruins (Bos)RW291987-05-19No216 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Jeremy SmithBruins (Bos)G271989-04-13No178 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm500,000$0$0$No
Jordan CaronBruins (Bos)RW261990-11-02No204 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
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$0$No
Louis-Marc Aubry (Sur la Masse Salariale)Bruins (Bos)C251991-11-11No208 Lbs6 ft4NoNoNo2Avec RestrictionPro & Farm300,000$0$0$Yes
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$0$No
Michael LeightonBruins (Bos)G351981-05-18No186 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm500,000$0$0$No
Nate ProsserBruins (Bos)D301986-05-06No203 Lbs6 ft2NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
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$0$No
Shawn Ouellette-St. AmantBruins (Bos)LW201996-11-18Yes198 Lbs6 ft0NoNoNo3Contrat d'EntréePro & Farm300,000$0$0$No
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$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2525.60197 Lbs6 ft12.44428,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Giovanni FioreAnthony RichardCurtis McKenzie40122
2Liam O'BrienBen Smith30122
3Dmytro TimashovCurtis McKenzieMatej Stransky20122
4Shawn Ouellette-St. AmantGiovanni FioreJack Skille10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate Prosser40122
2Maxime FortunusLoic Leduc30122
3Nate Prosser20122
4Maxime FortunusLoic Leduc10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Giovanni FioreAnthony RichardCurtis McKenzie60122
2Liam O'BrienBen Smith40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate Prosser60122
2Maxime FortunusLoic Leduc40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Curtis McKenzieGiovanni Fiore60122
2Liam O'BrienBen Smith40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate Prosser60122
2Maxime FortunusLoic Leduc40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Curtis McKenzie60122Nate Prosser60122
2Giovanni Fiore40122Maxime FortunusLoic Leduc40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Curtis McKenzieGiovanni Fiore60122
2Liam O'BrienBen Smith40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nate Prosser60122
2Maxime FortunusLoic Leduc40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Giovanni FioreAnthony RichardCurtis McKenzieNate Prosser
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Giovanni FioreAnthony RichardCurtis McKenzieNate Prosser
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Justin Florek, Yannick Veilleux, Dmytro TimashovJustin Florek, Yannick VeilleuxDmytro Timashov
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Nate Prosser, , Maxime FortunusNate Prosser, Maxime Fortunus
Tirs de Pénalité
Curtis McKenzie, Giovanni Fiore, Liam O'Brien, Ben Smith, Dmytro Timashov
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
1Americans22000000404110000001011100000030341.000481202705840337456443462143813282614214.29%130100.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
2Bears32100000550110000002112110000034-140.66759140070584036445644346214731733502713.70%12283.33%0861147058.57%813148754.67%44671562.38%13639781064338594319
3Checkers770000004283433000000152134400000027621141.000428012203705840327345644346214159497818023313.04%38294.74%1861147058.57%813148754.67%44671562.38%13639781064338594319
4Comets11000000532000000000001100000053221.0005914007058403314564434621428716166466.67%8275.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
5Crunch11000000101110000001010000000000021.000123017058403214564434621431910245120.00%50100.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
6Devils1000010023-1000000000001000010023-110.500235007058403204564434621423512187228.57%6266.67%0861147058.57%813148754.67%44671562.38%13639781064338594319
7Marlies11000000211000000000001100000021121.0002460070584033145644346214175823200.00%40100.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
8Penguins3020100068-22010100056-11010000012-120.3336111700705840354456443462145117455717317.65%18383.33%0861147058.57%813148754.67%44671562.38%13639781064338594319
9Phantoms41300000311-82110000024-22020000017-620.2503470070584036645644346214892771752600.00%31777.42%0861147058.57%813148754.67%44671562.38%13639781064338594319
10Rocket10001000321100010003210000000000021.000358007058403284564434621424920226233.33%100100.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
11Senators10000010321000000000001000001032121.00034700705840319456443462141361026100.00%110.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
12Sound Tigers962001002418642200000911-2540001001578130.722243963017058403161456443462142156012119947714.89%54590.74%0861147058.57%813148754.67%44671562.38%13639781064338594319
13Thunderbirds8710000036171933000000124854100000241311140.8753662980070584032904564434621420958105188361027.78%44784.09%2861147058.57%813148754.67%44671562.38%13639781064338594319
Total503510022101719477221640200068353328196002101035944780.780171303474077058403137145644346214113132365610902473915.79%2843986.27%3861147058.57%813148754.67%44671562.38%13639781064338594319
15Wolf Pack8710000035161944000000185134310000017116140.87535639800705840327645644346214161419918630413.33%40880.00%0861147058.57%813148754.67%44671562.38%13639781064338594319
_Since Last GM Reset503510022101719477221640200068353328196002101035944780.780171303474077058403137145644346214113132365610902473915.79%2843986.27%3861147058.57%813148754.67%44671562.38%13639781064338594319
_Vs Conference301790121079631614940100037271016850021042366400.66779135214027058403681456443462146561824016351601811.25%1672883.23%0861147058.57%813148754.67%44671562.38%13639781064338594319

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5078W217130347413711131323656109007
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
503510221017194
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2216420006835
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
28196021010359
Derniers 10 Matchs
WLOTWOTL SOWSOL
910000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2473915.79%2843986.27%3
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
456443462147058403
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
861147058.57%813148754.67%44671562.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
13639781064338594319


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 - 2018-09-2169Bruins1Sound Tigers2LXSommaire du Match
18 - 2018-09-2288Sound Tigers2Bruins0LSommaire du Match
25 - 2018-09-29123Bruins3Thunderbirds4LSommaire du Match
26 - 2018-09-30131Sound Tigers3Bruins4WSommaire du Match
31 - 2018-10-05139Bruins6Checkers3WSommaire du Match
32 - 2018-10-06154Bruins6Checkers1WSommaire du Match
38 - 2018-10-12184Penguins1Bruins2WXSommaire du Match
39 - 2018-10-13194Bruins3Sound Tigers1WSommaire du Match
40 - 2018-10-14206Penguins5Bruins3LSommaire du Match
45 - 2018-10-19227Phantoms3Bruins0LSommaire du Match
46 - 2018-10-20245Americans0Bruins1WSommaire du Match
50 - 2018-10-24257Bruins0Wolf Pack2LSommaire du Match
53 - 2018-10-27281Bruins1Phantoms4LSommaire du Match
54 - 2018-10-28292Bruins1Penguins2LSommaire du Match
59 - 2018-11-02311Checkers0Bruins6WSommaire du Match
60 - 2018-11-03322Bruins5Sound Tigers0WSommaire du Match
61 - 2018-11-04332Checkers2Bruins5WSommaire du Match
64 - 2018-11-07341Bruins2Marlies1WSommaire du Match
66 - 2018-11-09353Bruins3Americans0WSommaire du Match
67 - 2018-11-10365Bruins3Senators2WXXSommaire du Match
71 - 2018-11-14383Bruins5Comets3WSommaire du Match
73 - 2018-11-16393Sound Tigers2Bruins3WSommaire du Match
74 - 2018-11-17408Bears1Bruins2WSommaire du Match
78 - 2018-11-21424Bruins5Wolf Pack3WSommaire du Match
80 - 2018-11-23438Bruins2Devils3LXSommaire du Match
81 - 2018-11-24459Bruins3Thunderbirds1WSommaire du Match
87 - 2018-11-30478Bruins0Phantoms3LSommaire du Match
88 - 2018-12-01488Bruins3Bears2WSommaire du Match
89 - 2018-12-02501Bruins0Bears2LSommaire du Match
94 - 2018-12-07520Phantoms1Bruins2WSommaire du Match
95 - 2018-12-08537Bruins4Thunderbirds2WSommaire du Match
96 - 2018-12-09546Wolf Pack1Bruins3WSommaire du Match
101 - 2018-12-14565Wolf Pack1Bruins5WSommaire du Match
102 - 2018-12-15581Bruins7Thunderbirds3WSommaire du Match
103 - 2018-12-16588Thunderbirds1Bruins3WSommaire du Match
108 - 2018-12-21607Thunderbirds2Bruins4WSommaire du Match
109 - 2018-12-22620Bruins4Sound Tigers3WSommaire du Match
110 - 2018-12-23634Wolf Pack1Bruins5WSommaire du Match
115 - 2018-12-28658Checkers0Bruins4WSommaire du Match
116 - 2018-12-29678Thunderbirds1Bruins5WSommaire du Match
122 - 2019-01-04684Bruins8Checkers2WSommaire du Match
123 - 2019-01-05699Bruins7Checkers0WSommaire du Match
129 - 2019-01-11724Sound Tigers4Bruins2LSommaire du Match
130 - 2019-01-12736Bruins2Sound Tigers1WSommaire du Match
131 - 2019-01-13752Crunch0Bruins1WSommaire du Match
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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
154,344$ 104,000$ 96,150$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 86,839$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 1,052$ 66,276$




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
1350351002210171947722164020006835332819600210103594478171303474077058403137145644346214113132365610902473915.79%2843986.27%3861147058.57%813148754.67%44671562.38%13639781064338594319
Total Saison Régulière50351002210171947722164020006835332819600210103594478171303474077058403137145644346214113132365610902473915.79%2843986.27%3861147058.57%813148754.67%44671562.38%13639781064338594319
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