Bruins

GP: 25 | W: 17 | L: 7 | OTL: 1 | P: 35
GF: 82 | GA: 51 | PP%: 16.53% | PK%: 87.50%
DG: Steve Gagné | Morale : 63 | Moyenne d'Équipe : 59
Prochain matchs #383 vs Comets
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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
1Zac RinaldoXX98.00925555748375746859626572557574166670
2Curtis McKenzieX98.00905559757770636050616060557272169630
3Giovanni Fiore (R)XX98.00755578707270786050556155556650166600
4Liam O'BrienX98.00605558687972696050606060555050172600
5Ben SmithX98.00595560717767655650555655557574169590
6Dmytro Timashov (R)X100.00655567677364695550555555557573169580
7Anthony Richard (R)X99.00595572626059745550555557557273169570
8Shawn Ouellette-St. Amant (R)X100.00765565657466655550555555555050169570
9Justin FlorekX100.00595563627972725550555555555050169570
10Matej StranskyX100.00605559667975725550555555555050172570
11Yannick VeilleuxX100.00705566637871695550555555555050169570
12Pascal Pelletier (R)X100.00565555555555555550555555555050158530
13Louis-Marc AubryX99.00565555555556555550555555555050169530
14Chris WidemanX99.00705564808271717525746970558177166700
15Nate ProsserX99.00805583727773646925636576558178169690
16Carson Soucy (R)X99.00555555605555565525555555555555169540
Rayé
1Clarke MacArthurX100.00555555555555555550555555557372125540
2Jack SkilleX100.00555555555555555550555555556869125540
3Jordan CaronX100.00565555555556555550555555556061125530
4Brian StraitX100.00555555605555765525555555556465125560
5Maxime FortunusX100.00555555605555685525555555555353125540
6Loic LeducX100.00555555605555575525555555555353125530
MOYENNE D'ÉQUIPE99.3264556164686465584457575855626115658
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 Leighton100.0076787784717176767975557068164730
2Christopher Gibson100.0065707273696968687069556866169670
Rayé
1Jeremy Smith100.0062746065707059565968556063125620
2Philippe Desrosiers100.0055655971616160596060555658125590
MOYENNE D'ÉQUIPE100.006572677368686665676855646414665
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)D25423271542075445015398.00%4061624.671673179011088210.00%000000.8800000233
2Zac RinaldoBruins (Bos)LW/RW251792612400837999335817.17%1161524.62235158320271014161.47%46200020.8401000521
3Chris WidemanBruins (Bos)D255172216340583940212512.50%2762024.832352683022193000.00%000000.7100000111
4Giovanni FioreBruins (Bos)LW/RW25812201318043368122399.88%354521.8205519840002663164.62%6500000.7301000013
5Curtis McKenzieBruins (Bos)RW256121811300643949195012.24%557523.0423588000011131064.35%23000000.6301000021
6Louis-Marc AubryBruins (Bos)C2581018146019443582822.86%143917.56235483000053056.81%43300000.8200000310
7Ben SmithBruins (Bos)RW256101610140221842133614.29%540316.13123950000031090.91%1100000.7900000102
8Liam O'BrienBruins (Bos)LW25881611295383551204015.69%750620.2631411700003652141.82%5500000.6311100022
9Anthony RichardBruins (Bos)C2537107001362871710.71%235714.312357890004480059.71%40700000.5600000100
10Carson SoucyBruins (Bos)D25088173603414113120.00%1955422.19022371000183000.00%100000.2900000010
11Dmytro TimashovBruins (Bos)LW25437-11001183581811.43%12459.8300011000000050.00%1000000.5700000010
12Shawn Ouellette-St. AmantBruins (Bos)LW2506601603616227130.00%733213.290114320000630063.79%5800000.3600000001
13Justin FlorekBruins (Bos)LW253362408102391713.04%226810.732023130000180066.67%2400000.4500000001
14Matej StranskyBruins (Bos)RW252350755193312236.06%129011.6000003000000076.92%1300000.3400100000
15David DesharnaisBoston BruinsC5314060519152820.00%212224.560113260000231070.49%12200000.6511000010
16Yannick VeilleuxBruins (Bos)LW25213180761201216.67%62339.361016260001630066.67%3600000.2600000000
17Pascal PelletierBruins (Bos)LW110000401152240.00%416214.730000150000390053.85%1300000.0000000000
Stats d'équipe Total ou en Moyenne391791332121283041052046762820143912.58%143689017.621833511508972352087617460.88%194000020.6225200131515
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)2516710.9032.07147724515240001.0004250210
2Christopher GibsonBruins (Bos)11001.0000.0039000100000.0000025000
Stats d'équipe Total ou en Moyenne2617710.9042.02151624515340001.00042525210


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
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
2625.65197 Lbs6 ft12.42430,769$



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
1Chris WidemanNate Prosser40122
2Carson SoucyLiam O'Brien30122
3Chris WidemanNate Prosser20122
4Carson SoucyBen Smith10122
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
1Chris WidemanNate Prosser60122
2Carson SoucyLiam O'Brien40122
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
1Chris WidemanNate Prosser60122
2Carson Soucy40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Zac Rinaldo60122Chris WidemanNate Prosser60122
2Curtis McKenzie40122Carson Soucy40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Zac RinaldoCurtis McKenzie60122
2Giovanni FioreLiam O'Brien40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Chris WidemanNate Prosser60122
2Carson Soucy40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zac RinaldoAnthony RichardCurtis McKenzieChris WidemanNate Prosser
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Zac RinaldoAnthony RichardCurtis McKenzieChris WidemanNate Prosser
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Shawn Ouellette-St. Amant, Justin Florek, Yannick VeilleuxShawn Ouellette-St. Amant, Justin FlorekYannick Veilleux
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chris Wideman, Nate Prosser, Carson SoucyChris WidemanNate Prosser, Carson Soucy
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
1Americans22000000404110000001011100000030341.000481202322819337215205215123813282614214.29%130100.00%043271460.50%41472157.42%24936568.22%697499521167298161
2Checkers440000002361722000000112922000000124881.000234568013228193155215205215128327429916212.50%21195.24%143271460.50%41472157.42%24936568.22%697499521167298161
3Marlies11000000211000000000001100000021121.0002460032281933121520521512175823200.00%40100.00%043271460.50%41472157.42%24936568.22%697499521167298161
4Penguins3020100068-22010100056-11010000012-120.3336111700322819354215205215125117455717317.65%18383.33%043271460.50%41472157.42%24936568.22%697499521167298161
5Phantoms2020000017-61010000003-31010000014-300.0001230032281932521520521512381333371000.00%14471.43%043271460.50%41472157.42%24936568.22%697499521167298161
6Rocket10001000321100010003210000000000021.000358003228193282152052151224920226233.33%100100.00%043271460.50%41472157.42%24936568.22%697499521167298161
7Senators10000010321000000000001000001032121.00034700322819319215205215121361026100.00%110.00%043271460.50%41472157.42%24936568.22%697499521167298161
8Sound Tigers5310010013852110000045-13200010093670.7001321340132281939521520521512121376910533515.15%30293.33%043271460.50%41472157.42%24936568.22%697499521167298161
9Thunderbirds2110000010730000000000021100000107320.50010152500322819364215205215126613284711436.36%13284.62%143271460.50%41472157.42%24936568.22%697499521167298161
Total251470211082513110530200029209159400110533122350.70082147229043228193643215205215125341613255411212016.53%1441887.50%243271460.50%41472157.42%24936568.22%697499521167298161
11Wolf Pack43100000171071100000052332100000128460.750173249003228193135215205215128321429911218.18%20575.00%043271460.50%41472157.42%24936568.22%697499521167298161
_Since Last GM Reset251470211082513110530200029209159400110533122350.70082147229043228193643215205215125341613255411212016.53%1441887.50%243271460.50%41472157.42%24936568.22%697499521167298161
_Vs Conference15660111040355623010001416-29430011026197170.56740701100132281933282152052151230694199324721013.89%831581.93%043271460.50%41472157.42%24936568.22%697499521167298161

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
2535SOW18214722964353416132554104
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
2514721108251
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
105320002920
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
159401105331
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
1212016.53%1441887.50%2
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
215205215123228193
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
43271460.50%41472157.42%24936568.22%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
697499521167298161


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 - 2018-11-14383Bruins-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
28 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
85,493$ 112,000$ 96,150$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 50,970$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 127 1,093$ 138,811$




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
132514702110825131105302000292091594001105331223582147229043228193643215205215125341613255411212016.53%1441887.50%243271460.50%41472157.42%24936568.22%697499521167298161
Total Saison Régulière2514702110825131105302000292091594001105331223582147229043228193643215205215125341613255411212016.53%1441887.50%243271460.50%41472157.42%24936568.22%697499521167298161
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