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Bruins

GP: 51 | W: 24 | L: 23 | OTL: 4 | P: 52
GF: 139 | GA: 165 | PP%: 13.46% | PK%: 82.00%
DG: Martin Picard | Morale : 50 | Moyenne d'Équipe : 61
Prochain matchs #765 vs Rampage
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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 SPÂgeContratSalaire
1Kyle Clifford (C)X100.008375636483798661546263566177690506402811,600,000$
2John QuennevilleXXX100.00614586637683806173606264636764050630232750,000$
3Gabriel Dumont (A)XX100.00574685626976716068595961607868050620292700,000$
4Nicholas ShoreX100.00684084587765825774535669587568050610271750,000$
5Francis PerronX100.00514588606883845861595756606764050600231715,000$
6Giovanni FioreXX100.00634387587578795651525754586764050590231701,667$
7Adam MascherinXX100.00504488576182845553585652576362050580212880,000$
8Oskar SteenX100.00515082586786885765565453586362050580213925,000$
9Jake LeschyshynX100.00514288555887885460515352556163050570203927,500$
10Jordan OesterleX100.006639896571838564307262695275680506602721,400,000$
11Maxime LajoieX100.00614289667783796330646165526563050640212780,000$
12Colton WhiteX100.00634387627481786130595758536563050610221935,833$
13Joey KeaneX100.00594885647289876330625556526164050610203925,000$
14Thomas SchemitschX100.00705186578688855630555458456764050600221715,000$
15Jeremy DaviesX100.005348836257878861305953524667640505902221,325,000$
16Parker WotherspoonX100.00535679606987855930585456456563050590221855,000$
Rayé
1Connor HobbsX100.00625280587784835630545357456563050590221798,333$
2Devante StephensX100.00634589568078775430535057486563050580221766,670$
MOYENNE D'ÉQUIPE100.0060478460728283594658565854676405061
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
1Casey DeSmith100.0079848271787779787779787783050680
2Calvin Petersen100.0076817974757476757476757175050660
Rayé
1Callum Booth100.0071565483706971706971706569050620
2Dylan Wells100.0061595778605961605961606367050570
MOYENNE D'ÉQUIPE100.007270687771707271707271697405063
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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'ÉquipePOSGP 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
1John QuennevilleBruins (BOS)C/LW/RW511331444101030142189511306.88%14121523.83268259711261463156.64%120400000.7226020322
2Nicholas ShoreBruins (BOS)C511627432200111149185461338.65%2097819.1913415820000471059.66%118000020.8801000424
3Kyle CliffordBruins (BOS)LW5117223911861025989192551338.85%10119523.45314209311221293053.53%34000100.6506011323
4Jordan OesterleBruins (BOS)D51102232-1057512710111041629.09%92125324.5827940930110115100.00%000000.5100000013
5Gabriel DumontBruins (BOS)C/RW5114142816115217115339789.15%1294018.4411228950003643157.48%12700100.6035001014
6Colton WhiteBruins (BOS)D5171926326086397720479.09%91105820.7512328850001110010.00%000000.4900000120
7Francis PerronBruins (BOS)LW51141125-14031661393610210.07%1597119.0411214651122543146.51%12900000.5101000321
8Joey KeaneBruins (BOS)D5142024428084626129516.56%70105620.7221316850000109100.00%000000.4500000000
9Thomas SchemitschBruins (BOS)D5151823-93751244350143510.00%4775614.830001200002200.00%000000.6100100011
10Maxime LajoieBruins (BOS)D5121921-634074747734562.60%6997119.0406640960003123100.00%000000.4300000000
11Adam MascherinBruins (BOS)C/LW5161218-22404767106351055.66%1084616.59000100000161148.15%8100000.4300000021
12Jeremy DaviesBruins (BOS)D5121618-78026524612244.35%5080015.6900000011155000.00%000000.4500000100
13Oskar SteenBruins (BOS)C5111718-23607110912231969.02%1085816.84000030000350050.93%97000100.4200000102
14Giovanni FioreBruins (BOS)LW/RW5188162140644610025768.00%692318.101011084000010038.89%5400000.3500000102
15Jake LeschyshynBruins (BOS)C51369-3216036435224395.77%883516.3900011000030144.24%32100000.2200000000
16Josh LeivoBruinsLW/RW10246-621515185914243.39%421421.4300010210002241044.58%8300000.5601010010
17Parker WotherspoonBruins (BOS)D51112-580301996911.11%133276.4200000000014000.00%000000.1200000000
Stats d'équipe Total ou en Moyenne826135257392-793904012361190172751212007.82%5411520318.4114284224990935820105620654.22%448900320.52520142171623
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
1Casey DeSmithBruins (BOS)51242140.9103.12288715515016700000.89519510543
2Calvin PetersenBruins (BOS)60200.9213.5522000131640000.0000051000
Stats d'équipe Total ou en Moyenne57242340.9113.15310715516318340000.895195151543


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 Type Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam MascherinBruins (BOS)C/LW211998-06-06No200 Lbs5 ft1NoNoNo2Pro & Farm880,000$0$0$No880,000$Lien / Lien NHL
Callum BoothBruins (BOS)G221997-05-21No184 Lbs6 ft4NoNoNo1Pro & Farm758,333$0$0$NoLien / Lien NHL
Calvin PetersenBruins (BOS)G241994-10-19No185 Lbs6 ft1NoNoNo3Pro & Farm858,333$0$0$No858,333$858,333$Lien
Casey DeSmithBruins (BOS)G281991-08-13No181 Lbs6 ft0NoNoNo3Pro & Farm1,250,000$0$0$No1,250,000$1,250,000$Lien / Lien NHL
Colton WhiteBruins (BOS)D221997-05-03No185 Lbs6 ft1NoNoNo1Pro & Farm935,833$0$0$NoLien / Lien NHL
Connor HobbsBruins (BOS)D221997-01-04No197 Lbs6 ft1NoNoNo1Pro & Farm798,333$0$0$NoLien / Lien NHL
Devante StephensBruins (BOS)D221997-01-02No185 Lbs6 ft3NoNoNo1Pro & Farm766,670$0$0$NoLien
Dylan WellsBruins (BOS)G211998-01-03No190 Lbs6 ft2NoNoNo2Pro & Farm910,833$0$0$No910,833$Lien / Lien NHL
Francis PerronBruins (BOS)LW231996-04-18No166 Lbs6 ft0NoNoNo1Pro & Farm715,000$0$0$NoLien / Lien NHL
Gabriel DumontBruins (BOS)C/RW291990-10-06No191 Lbs5 ft10NoNoNo2Pro & Farm700,000$0$0$No700,000$Lien / Lien NHL
Giovanni FioreBruins (BOS)LW/RW231996-08-13No188 Lbs6 ft1NoNoNo1Pro & Farm701,667$0$0$NoLien / Lien NHL
Jake LeschyshynBruins (BOS)C201999-03-10No185 Lbs5 ft1NoNoNo3Pro & Farm927,500$0$0$No927,500$927,500$Lien
Jeremy DaviesBruins (BOS)D221996-12-04No180 Lbs5 ft1NoNoNo2Pro & Farm1,325,000$0$0$No1,325,000$Lien
Joey KeaneBruins (BOS)D201999-07-02No187 Lbs6 ft0NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
John QuennevilleBruins (BOS)C/LW/RW231996-04-16No195 Lbs6 ft1NoNoNo2Pro & Farm750,000$0$0$No750,000$Lien / Lien NHL
Jordan OesterleBruins (BOS)D271992-06-25No182 Lbs6 ft0NoNoNo2Pro & Farm1,400,000$0$0$No1,400,000$Lien / Lien NHL
Kyle CliffordBruins (BOS)LW281991-01-13No211 Lbs6 ft2NoNoNo1Pro & Farm1,600,000$0$0$NoLien / Lien NHL
Maxime LajoieBruins (BOS)D211997-11-05No196 Lbs6 ft1NoNoNo2Pro & Farm780,000$0$0$No780,000$Lien / Lien NHL
Nicholas ShoreBruins (BOS)C271992-09-26No198 Lbs6 ft1NoNoNo1Pro & Farm750,000$0$0$No
Oskar SteenBruins (BOS)C211998-03-09No188 Lbs5 ft9NoNoNo3Pro & Farm925,000$0$0$No925,000$925,000$Lien
Parker WotherspoonBruins (BOS)D221997-08-24No171 Lbs6 ft0NoNoNo1Pro & Farm855,000$0$0$NoLien / Lien NHL
Thomas SchemitschBruins (BOS)D221996-10-26No200 Lbs6 ft4NoNoNo1Pro & Farm715,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2223.18188 Lbs5 ft111.77919,432$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJohn QuennevilleGabriel Dumont30122
2Francis PerronNicholas ShoreGiovanni Fiore30122
3Adam MascherinOskar SteenJake Leschyshyn25122
4Kyle CliffordJake LeschyshynJohn Quenneville15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMaxime Lajoie30122
2Joey KeaneColton White30122
3Thomas SchemitschJeremy Davies25122
4Parker WotherspoonJordan Oesterle15122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordJohn QuennevilleGabriel Dumont60122
2Francis PerronNicholas ShoreGiovanni Fiore40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMaxime Lajoie60122
2Joey KeaneColton White40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle CliffordJohn Quenneville60122
2Gabriel DumontNicholas Shore40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMaxime Lajoie60122
2Joey KeaneColton White40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Clifford60122Jordan OesterleMaxime Lajoie60122
2John Quenneville40122Joey KeaneColton White40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle CliffordJohn Quenneville60122
2Gabriel DumontNicholas Shore40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Jordan OesterleMaxime Lajoie60122
2Joey KeaneColton White40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJohn QuennevilleGabriel DumontJordan OesterleMaxime Lajoie
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Kyle CliffordJohn QuennevilleGabriel DumontJordan OesterleMaxime Lajoie
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Oskar Steen, Adam Mascherin, Francis PerronOskar Steen, Adam MascherinFrancis Perron
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Thomas Schemitsch, Jeremy Davies, Parker WotherspoonThomas SchemitschJeremy Davies, Parker Wotherspoon
Tirs de Pénalité
Kyle Clifford, John Quenneville, Gabriel Dumont, Nicholas Shore, Francis Perron
Gardien
#1 : Casey DeSmith, #2 : Calvin Petersen


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
1Admirals31200000710-32110000056-11010000024-220.33371421004840439117572582531621224312755120.00%6266.67%0982176855.54%1005189253.12%44782953.92%12799011169359661336
2Americans2010100067-1100010004311010000024-220.50061218004840439425725825316273191654300.00%6266.67%0982176855.54%1005189253.12%44782953.92%12799011169359661336
3Barracuda21100000642110000003031010000034-120.500612180148404397657258253162621619485120.00%5180.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
4Bears1010000034-1000000000001010000034-100.0003580048404393257258253162337623300.00%2150.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
5Checkers32100000972110000005322110000044040.667916250148404399957258253162923016773133.33%8187.50%0982176855.54%1005189253.12%44782953.92%12799011169359661336
6Comets11000000909110000009090000000000021.0009182701484043972572582531622474272150.00%20100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
7Crunch20200000412-81010000005-51010000047-300.00047110048404395557258253162872225445120.00%8362.50%0982176855.54%1005189253.12%44782953.92%12799011169359661336
8Devils2110000079-21010000025-31100000054120.50071421004840439795725825316275231050400.00%5340.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
9Eagles320010001376210010006331100000074361.0001323360148404391225725825316284268576116.67%4175.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
10Griffins2110000048-4110000004311010000005-520.5004812004840439665725825316274161949500.00%30100.00%1982176855.54%1005189253.12%44782953.92%12799011169359661336
11Gulls11000000312000000000001100000031221.00036900484043940572582531624011419100.00%10100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
12Heat1010000012-1000000000001010000012-100.00011200484043930572582531623910626100.00%30100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
13IceHogs2020000059-41010000045-11010000014-300.000510150048404395957258253162781514475240.00%7185.71%0982176855.54%1005189253.12%44782953.92%12799011169359661336
14Marlies30200001311-81010000002-22010000139-610.16736900484043980572582531621003247676233.33%9277.78%0982176855.54%1005189253.12%44782953.92%12799011169359661336
15Monsters2010010069-31010000035-21000010034-110.2506121800484043950572582531626720647700.00%3233.33%0982176855.54%1005189253.12%44782953.92%12799011169359661336
16Moose1000000123-1000000000001000000123-110.5002460048404392757258253162319932200.00%2150.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
17Penguins21000010954210000109540000000000041.0009162500484043910557258253162622412475240.00%50100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
18Phantoms21100000440110000004311010000001-120.5004711004840439775725825316277211245400.00%60100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
19Rampage11000000202110000002020000000000021.00024601484043932572582531623168233133.33%40100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
20Reign1010000024-21010000024-20000000000000.000246004840439235725825316241123820100.00%7185.71%0982176855.54%1005189253.12%44782953.92%12799011169359661336
21Roadrunners10000010321000000000001000001032121.000347004840439295725825316242111427000.00%6183.33%0982176855.54%1005189253.12%44782953.92%12799011169359661336
22Senators40301000516-1120200000010-102010100056-120.250591400484043914457258253162163423086900.00%15193.33%0982176855.54%1005189253.12%44782953.92%12799011169359661336
23Sound Tigers20000020862100000104311000001043141.00081220004840439675725825316275251457300.00%7185.71%0982176855.54%1005189253.12%44782953.92%12799011169359661336
24Stars2010010049-51000010034-11010000015-410.250481200484043963572582531627924855700.00%40100.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
25Thunderbirds21001000642100010004311100000021141.000610160048404396557258253162593212535120.00%5180.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
Total51162304242139165-262499031207372127714011226693-27520.510139257396054840439172757258253162183454140512361041413.46%1502782.00%3982176855.54%1005189253.12%44782953.92%12799011169359661336
26Wild1010000007-7000000000001010000007-700.000000004840439165725825316249131021100.00%4175.00%0982176855.54%1005189253.12%44782953.92%12799011169359661336
27Wolf Pack22000000853000000000002200000085341.00081523004840439605725825316275252660300.00%13192.31%2982176855.54%1005189253.12%44782953.92%12799011169359661336
_Since Last GM Reset51162304242139165-262499031207372127714011226693-27520.510139257396054840439172757258253162183454140512361041413.46%1502782.00%3982176855.54%1005189253.12%44782953.92%12799011169359661336
_Vs Conference28912030318190-91345020204142-11557010114048-8310.554811472280248404399775725825316299530923069055814.55%911682.42%2982176855.54%1005189253.12%44782953.92%12799011169359661336
_Vs Division1673010305449573001020272439430001027252220.6885497151014840439569572582531625561751024063239.38%49981.63%2982176855.54%1005189253.12%44782953.92%12799011169359661336

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5152OTL113925739617271834541405123605
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
5116234242139165
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
249931207372
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2771411226693
Derniers 10 Matchs
WLOTWOTL SOWSOL
441100
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1041413.46%1502782.00%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
572582531624840439
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
982176855.54%1005189253.12%44782953.92%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12799011169359661336


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
1 - 2020-10-051Bruins5Wolf Pack3WSommaire du Match
3 - 2020-10-0715Bruins3Monsters4LXSommaire du Match
4 - 2020-10-0830Senators4Bruins0LSommaire du Match
7 - 2020-10-1147Bruins1Marlies6LSommaire du Match
8 - 2020-10-1257Senators6Bruins0LSommaire du Match
11 - 2020-10-1577Bruins3Bears4LSommaire du Match
13 - 2020-10-1791Phantoms3Bruins4WSommaire du Match
14 - 2020-10-18102Bruins2Admirals4LSommaire du Match
17 - 2020-10-21120Crunch5Bruins0LSommaire du Match
19 - 2020-10-23135Bruins4Sound Tigers3WXXSommaire du Match
21 - 2020-10-25151Americans3Bruins4WXSommaire du Match
24 - 2020-10-28170Griffins3Bruins4WSommaire du Match
26 - 2020-10-30188Bruins5Devils4WSommaire du Match
28 - 2020-11-01202Penguins1Bruins4WSommaire du Match
30 - 2020-11-03212Bruins1Checkers0WSommaire du Match
32 - 2020-11-05233Eagles3Bruins4WXSommaire du Match
34 - 2020-11-07244Bruins4Senators3WXSommaire du Match
36 - 2020-11-09257Bruins3Roadrunners2WXXSommaire du Match
38 - 2020-11-11274Eagles0Bruins2WSommaire du Match
40 - 2020-11-13285Bruins7Eagles4WSommaire du Match
41 - 2020-11-14298Bruins2Americans4LSommaire du Match
43 - 2020-11-16309Penguins4Bruins5WXXSommaire du Match
46 - 2020-11-19327Bruins2Marlies3LXXSommaire du Match
47 - 2020-11-20341Checkers3Bruins5WSommaire du Match
50 - 2020-11-23361Bruins1Stars5LSommaire du Match
51 - 2020-11-24372Comets0Bruins9WSommaire du Match
54 - 2020-11-27390Bruins2Moose3LXXSommaire du Match
55 - 2020-11-28403IceHogs5Bruins4LSommaire du Match
58 - 2020-12-01426Monsters5Bruins3LSommaire du Match
60 - 2020-12-03441Bruins0Phantoms1LSommaire du Match
62 - 2020-12-05457Reign4Bruins2LSommaire du Match
64 - 2020-12-07466Bruins1Heat2LSommaire du Match
66 - 2020-12-09482Bruins4Crunch7LSommaire du Match
68 - 2020-12-11493Bruins3Barracuda4LSommaire du Match
69 - 2020-12-12497Sound Tigers3Bruins4WXXSommaire du Match
71 - 2020-12-14519Bruins3Checkers4LSommaire du Match
73 - 2020-12-16530Marlies2Bruins0LSommaire du Match
75 - 2020-12-18551Bruins3Wolf Pack2WSommaire du Match
77 - 2020-12-20558Devils5Bruins2LSommaire du Match
80 - 2020-12-23583Rampage0Bruins2WSommaire du Match
82 - 2020-12-25596Bruins1IceHogs4LSommaire du Match
84 - 2020-12-27613Bruins0Griffins5LSommaire du Match
85 - 2020-12-28619Admirals4Bruins1LSommaire du Match
88 - 2020-12-31644Bruins1Senators3LSommaire du Match
89 - 2021-01-01651Barracuda0Bruins3WSommaire du Match
93 - 2021-01-05678Admirals2Bruins4WSommaire du Match
95 - 2021-01-07692Bruins3Gulls1WSommaire du Match
97 - 2021-01-09706Bruins0Wild7LSommaire du Match
98 - 2021-01-10712Thunderbirds3Bruins4WXSommaire du Match
101 - 2021-01-13730Bruins2Thunderbirds1WSommaire du Match
102 - 2021-01-14742Stars4Bruins3LXSommaire du Match
105 - 2021-01-17765Bruins-Rampage-
106 - 2021-01-18773Thunderbirds-Bruins-
111 - 2021-01-23801Phantoms-Bruins-
114 - 2021-01-26827Condors-Bruins-
116 - 2021-01-28836Bruins-Comets-
119 - 2021-01-31852Bruins-Sound Tigers-
120 - 2021-02-01866Wolves-Bruins-
125 - 2021-02-06893Gulls-Bruins-
128 - 2021-02-09917Wolf Pack-Bruins-
131 - 2021-02-12938Bruins-Bears-
132 - 2021-02-13949Americans-Bruins-
134 - 2021-02-15963Bruins-Wolves-
137 - 2021-02-18980Bears-Bruins-
139 - 2021-02-201000Bruins-Reign-
140 - 2021-02-211010Griffins-Bruins-
143 - 2021-02-241033Wild-Bruins-
145 - 2021-02-261045Bruins-Monsters-
148 - 2021-03-011064Senators-Bruins-
150 - 2021-03-031076Bruins-Penguins-
152 - 2021-03-051096Moose-Bruins-
155 - 2021-03-081117Bruins-Admirals-
156 - 2021-03-091125Rocket-Bruins-
159 - 2021-03-121149Bruins-Condors-
161 - 2021-03-141158Rocket-Bruins-
163 - 2021-03-161174Bruins-Rocket-
166 - 2021-03-191188Heat-Bruins-
169 - 2021-03-221209Bruins-Condors-
171 - 2021-03-241219Crunch-Bruins-
172 - 2021-03-251221Bruins-Devils-
174 - 2021-03-271233Bruins-Penguins-
179 - 2021-04-011262Roadrunners-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
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,150,108$ 2,022,749$ 821,999$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,150,108$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 80 11,114$ 889,120$




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
Saison Régulière
282303601564273291-1841141701342141144-341161900222132147-1560273462735011207868112699930866887462684774102315433557220.28%3797879.42%31411272151.86%1287265048.57%697138750.25%1931132020006141052517
38253160324430817912941287020221468363412590122216296661063085448520513791739333911131110108756208565082015113575916.53%3374786.05%51902312160.94%1587253662.58%752129158.25%2189155117275881051550
48253180105527916311641314010411567185412214000141239231106279511790071098282927989418879594922536861390191657512020.87%5928685.47%21837307059.84%1649287257.42%737122460.21%2181150617596151030541
5825123021232821821004129701013161808141221601110121102191022825137950911684786296897799198535222159765620492045125.00%2924883.56%31807292561.78%1466257556.93%778124362.59%2260164316755411019538
6826016012033752121634132700101183101824128901102192111811203756901065261591081072367312291149128024232867465320682174621.20%2835381.27%52100322965.04%1566264259.27%828134961.38%2369175815695241002543
782442007272348211137412390314119293994121110413115611838883486359831712510910018363911761198122174243271257420482195826.48%2574383.27%22096339761.70%1568268958.31%827133062.18%2349173416185311010545
88250160121033771901874123901062189939641277002411889791100377674105111114711610318343011161082120284248269754020391754224.00%2393585.36%21796301759.53%1465269654.34%786134858.31%240017921608503985532
88250160121033771901874123901062189939641277002411889791100377674105111114711610318343011161082120284248269754020391754224.00%2393585.36%21796301759.53%1465269654.34%786134858.31%240017921608503985532
951162304242139165-262499031207372127714011226693-2752139257396054840439172757258253162183454140512361041413.46%1502782.00%3982176855.54%1005189253.12%44782953.92%12799011169359661336
Total Saison Régulière7074071840211848292758178397535221278013629141430830600355195106081219151328953375834275849607718562110882475710027703917089479354514208016028660116449238150421.17%276845283.67%27157272626559.88%130582324856.17%66381134958.49%193631400014738478287984638
Séries
37340000022220413000001316-3321000009636224163009571214766363122226269116541018.52%27581.48%013226450.00%14124158.51%5711549.57%180124159569548
421165000005140111183000002622410820000025187325196147032116122660201217211316401714165151492516.78%1642584.76%146081956.17%40780350.68%16829157.73%549371485167272141
51810800000565609630000031274945000002529-420569815400171820151816815217523587188210477501020.00%961980.21%127456548.50%31266846.71%14629150.17%426287470139242117
6201460000080473310910000043212210550000037261128801382182325282617872832422611637180152489701622.86%691184.06%346080457.21%40474354.37%18632856.71%509362440143252129
773400000241410422000001541131200000910-162443670198703311079410822211786118424729.17%25196.00%019734057.94%13422260.36%5910755.14%219164147479049
813760000039381734000001921-264200000201731439711100171615146613815516674301309430835411.43%441370.45%021247544.63%22748746.61%8919046.84%3302332929016586
Total Séries8653330000027221755452916000001471113641241700000125106191062724877592888918762976973923984962727809100220893827218.85%4257482.59%51735326753.11%1625316451.36%705132253.33%2216154319956451118573