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Bruins

GP: 79 | W: 60 | L: 15 | OTL: 4 | P: 124
GF: 367 | GA: 178 | PP%: 24.40% | PK%: 86.52%
DG: Martin Picard | Morale : 50 | Moyenne d'Équipe : 62
Prochain matchs #1232 vs Checkers
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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
1Josh LeivoXX100.00574982647976896354626659637168050640
2Kyle Clifford (C)X100.00857865638367856254616456637570050640
3Gabriel DumontXXX100.00544078626791876168625659587774050620
4Connor BrickleyXXX100.00784286617578685953615662587367050620
5John QuennevilleXXX100.00623885637676646271606362606564043620
6Francis PerronX100.00523789626892896068625756596563050610
7Adam MascherinX100.00503690596194955863585552576163050590
8Giovanni FioreXX100.00603692567590855558535457526563050590
9Maxime LajoieX100.00543889667485716430666369576362047640
10Nathan BeaulieuX100.00726173668082616430715763527367050640
11Anton LindholmX100.00783590597176695830605271466965050620
12Alex LintuniemiX100.00773691569093905530585059456764050610
13Robbie RussoX100.00593788597393905830625256477166050610
14Thomas SchemitschX100.00713787588691865730565359486563050610
15Stuart PercyX100.00593885577590855630595156467166050600
16Colton WhiteX100.00533691597486725830575456466362050590
17Connor HobbsX100.00624274567791875530565158456362050590
Rayé
1Parker WotherspoonX100.00533983566992895530565253466362050580
MOYENNE D'ÉQUIPE100.0063428460758681594460565953686504961
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
1Carter Hart100.0084888677838284838284836165050690
2Cal Petersen100.0078817974777678777678776973050660
Rayé
1Zane McIntyre100.0076807882757476757476757377050660
2Spencer Martin100.0075727085747375747375746771050650
3Dylan Wells100.0076686678757476757476756165050640
4Callum Booth100.0070666483696870696870696367050620
MOYENNE D'ÉQUIPE100.007776748076757776757776667005065
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
1Jordan OesterleBruinsD6517708759320185110171681189.94%95161124.7971320621140220167210.00%000001.0811000293
2John QuennevilleBruins (BOS)C/LW/RW743945846380531123398123311.50%10132317.8844825109000002466.93%12700011.2713000251
3Kyle CliffordBruins (BOS)LW79423779681180365902997521814.05%11153019.37527321220002656251.87%26800021.03410000948
4Gabriel DumontBruins (BOS)C/LW/RW792550756410031188263511859.51%12145018.363710321240001185060.97%186800001.0314000336
5Nathan BeaulieuBruins (BOS)D7911637460891518810011137619.91%73156619.8317830930002157110.00%000000.9400102241
6Josh LeivoBruins (BOS)LW/RW79373471526037953128022111.86%17142518.048816551450007915446.67%10500031.0024000421
7Connor BrickleyBruins (BOS)C/LW/RW79313364434602361732998522210.37%14132516.780004220000226358.31%129300000.97110003100
8Maxime LajoieBruins (BOS)D69949584640706911834737.63%101127618.5026825530110170200.00%000000.9100000014
9Francis PerronBruins (BOS)LW79263157426027111265702029.81%11130616.5400014000054162.82%7800000.8723000424
10Anton LindholmBruins (BOS)D791144555850014373101468710.89%85155419.6835824930002161020.00%000010.7100000109
11Giovanni FioreBruins (BOS)LW/RW7913324544805367182631227.14%12126215.9800001000000160.26%7800000.7100000111
12Robbie RussoBruins (BOS)D79836444660535656193414.29%60125315.8700000000070010.00%000000.7000000023
13Alex LintuniemiBruins (BOS)D796243045460160366820508.82%69110013.930001300001200.00%000000.5500000010
14Colton WhiteBruins (BOS)D7949131680261520111720.00%164485.680000100009210.00%000000.5800000100
15Adam MascherinBruins (BOS)LW798412220019488315369.64%66638.39000000003933052.90%15500000.3601000001
16Thomas SchemitschBruins (BOS)D1645998040101461328.57%2628617.93011114000030000.00%000000.6300000011
17Stuart PercyBruins (BOS)D61123207962516.67%110317.2800000000001039.68%12600000.3900000000
18Parker WotherspoonBruins (BOS)D3000-120122230.00%34615.380000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne118129256785973944915169413642709765190010.78%6221953516.54335386292906033171065412158.42%409800070.881227102324543
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
1Carter HartBruins (BOS)65521120.9272.133897141013818980200.821396514915
2Cal PetersenBruins (BOS)20000.9681.1353001310000.0000064000
Stats d'équipe Total ou en Moyenne67521120.9282.113950141013919290200.821396578915


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)LW201998-06-06No200 Lbs5 ft1NoNoNo3Pro & Farm880,000$0$0$No880,000$880,000$Lien / Lien NHL
Alex LintuniemiBruins (BOS)D231995-09-23No231 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Anton LindholmBruins (BOS)D231994-11-29No191 Lbs5 ft11NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Cal PetersenBruins (BOS)G231994-10-19No185 Lbs6 ft1NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Callum BoothBruins (BOS)G211997-05-21No184 Lbs6 ft4NoNoNo2Pro & Farm758,333$0$0$No758,333$Lien / Lien NHL
Carter HartBruins (BOS)G201998-08-13No181 Lbs6 ft2NoNoNo3Pro & Farm863,333$0$0$No863,333$863,333$Lien / Lien NHL
Colton WhiteBruins (BOS)D211997-05-03No185 Lbs6 ft1NoNoNo2Pro & Farm935,833$0$0$No935,833$Lien / Lien NHL
Connor BrickleyBruins (BOS)C/LW/RW261992-02-25No203 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Connor HobbsBruins (BOS)D211997-01-04No197 Lbs6 ft1NoNoNo2Pro & Farm798,333$0$0$No798,333$Lien / Lien NHL
Dylan WellsBruins (BOS)G201998-01-03No190 Lbs6 ft2NoNoNo3Pro & Farm910,833$0$0$No910,833$910,833$Lien / Lien NHL
Francis PerronBruins (BOS)LW221996-04-18No166 Lbs6 ft0NoNoNo1Pro & Farm783,333$0$0$NoLien / Lien NHL
Gabriel DumontBruins (BOS)C/LW/RW281990-10-06No190 Lbs5 ft10NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Giovanni FioreBruins (BOS)LW/RW221996-08-13No188 Lbs6 ft1NoNoNo2Pro & Farm701,667$0$0$No701,667$Lien / Lien NHL
John QuennevilleBruins (BOS)C/LW/RW221996-04-16No195 Lbs6 ft1NoNoNo1Pro & Farm894,167$0$0$NoLien / Lien NHL
Josh LeivoBruins (BOS)LW/RW251993-05-26No192 Lbs6 ft2NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Kyle CliffordBruins (BOS)LW271991-01-13No211 Lbs6 ft2NoNoNo2Pro & Farm1,600,000$0$0$No1,600,000$Lien / Lien NHL
Maxime LajoieBruins (BOS)D201997-11-05No183 Lbs6 ft1NoNoNo3Pro & Farm780,000$0$0$No780,000$780,000$Lien / Lien NHL
Nathan BeaulieuBruins (BOS)D251992-12-05No200 Lbs6 ft2NoNoNo1Pro & Farm2,400,000$0$0$NoLien / Lien NHL
Parker WotherspoonBruins (BOS)D211997-08-24No171 Lbs6 ft0NoNoNo2Pro & Farm855,000$0$0$No855,000$Lien / Lien NHL
Robbie RussoBruins (BOS)D251993-02-15No191 Lbs6 ft0NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Spencer MartinBruins (BOS)G231995-06-08No210 Lbs6 ft3NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Stuart PercyBruins (BOS)D251993-05-18No187 Lbs6 ft1NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Thomas SchemitschBruins (BOS)D211996-10-26No200 Lbs6 ft4NoNoNo1Pro & Farm925,000$0$0$NoLien / Lien NHL
Zane McIntyreBruins (BOS)G261992-08-20No206 Lbs6 ft2NoNoNo1Pro & Farm650,000$0$0$NoLien / Lien NHL
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2422.92193 Lbs6 ft11.58892,118$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Kyle CliffordGabriel DumontJosh Leivo30113
2Francis PerronStuart PercyConnor Brickley30113
3John QuennevilleGiovanni Fiore25122
4Kyle CliffordGabriel DumontJosh Leivo15122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Nathan BeaulieuMaxime Lajoie30113
2Robbie RussoAnton Lindholm30131
3Thomas Schemitsch25131
4Nathan BeaulieuMaxime Lajoie15131
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Josh Leivo60014
2Kyle CliffordGabriel Dumont40014
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160023
2Nathan BeaulieuAnton Lindholm40023
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160131
2Kyle CliffordJosh Leivo40131
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Maxime Lajoie60140
2Nathan BeaulieuAnton Lindholm40140
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160050Maxime Lajoie60050
240050Nathan BeaulieuAnton Lindholm40050
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160023
2Kyle CliffordJosh Leivo40023
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Maxime Lajoie60023
2Nathan BeaulieuAnton Lindholm40023
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Josh LeivoNathan Beaulieu
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Josh LeivoNathan Beaulieu
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Connor Brickley, Francis Perron, Adam MascherinConnor Brickley, Francis PerronAdam Mascherin
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Alex Lintuniemi, Robbie Russo, Colton WhiteAlex LintuniemiRobbie Russo, Colton White
Tirs de Pénalité
, , Kyle Clifford, Josh Leivo, Gabriel Dumont
Gardien
#1 : Carter Hart, #2 : Cal 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
1Admirals21100000642110000004131010000023-120.5006111700143114991887108010551162805521864100.00%40100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
2Americans4210001015962100001010372110000056-160.7501525400014311499181511080105511628013436401145120.00%20195.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
3Barracuda2010001089-11010000035-21000001054120.500813211014311499185710801055116280852520415120.00%8362.50%01749291959.92%1407258354.47%753129658.10%232317351536482949514
4Bears31200000121202020000059-41100000073420.333122133001431149918115108010551162801042025854125.00%9366.67%01749291959.92%1407258354.47%753129658.10%232317351536482949514
5Checkers11000000202110000002020000000000021.0002350114311499183510801055116280206011100.00%000.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
6Comets220000001721511000000725110000001001041.0001731480114311499181471080105511628035118448225.00%4175.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
7Condors22000000177101100000011381100000064241.0001732490014311499181341080105511628044106555360.00%30100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
8Crunch41200001912-32010000147-32110000055030.375916250014311499181131080105511628015851531051300.00%18383.33%01749291959.92%1407258354.47%753129658.10%232317351536482949514
9Devils330000002742311000000743220000002002061.0002750770214311499182111080105511628081162083200.00%10190.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
10Eagles21000100743110000006241000010012-130.75071421001431149918451080105511628068262847300.00%14285.71%01749291959.92%1407258354.47%753129658.10%232317351536482949514
11Griffins44000000154112200000010282200000052381.0001527420114311499181361080105511628093292097200.00%10190.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
12Gulls21000010422100000102111100000021141.0004610001431149918561080105511628073199435120.00%20100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
13Heat22000000195141100000011291100000083541.0001935540014311499181331080105511628047111441000.00%7271.43%11749291959.92%1407258354.47%753129658.10%232317351536482949514
14IceHogs201000106601010000034-11000001032120.50067130014311499186810801055116280731312479222.22%60100.00%11749291959.92%1407258354.47%753129658.10%232317351536482949514
15Marlies4120001011110201000105502110000066040.5001119300014311499181171080105511628014749301149111.11%15380.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
16Monsters32100000963211000005321100000043140.667916250014311499181171080105511628087348717114.29%40100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
17Moose22000000909110000003031100000060641.000916250214311499181081080105511628035712493133.33%60100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
18Penguins330000002451922000000163131100000082661.00024477100143114991814810801055116280982322744250.00%110100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
19Phantoms320000101284100000104312200000085361.000121830001431149918131108010551162809429207610330.00%10280.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
20Rampage1010000014-31010000014-30000000000000.0001230014311499182010801055116280325825300.00%40100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
21Reign21000010972100000105411100000043141.000916250014311499187510801055116280803112506233.33%4250.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
22Roadrunners21000010523110000002021000001032141.0005712011431149918681080105511628061124553266.67%20100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
23Rocket4200011016124210000108622100010086270.8751630460014311499181391080105511628011633228510220.00%11190.91%01749291959.92%1407258354.47%753129658.10%232317351536482949514
24Senators44000000359262200000020515220000001541181.0003565100001431149918249108010551162801052461138450.00%30100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
25Sound Tigers3120000069-3110000003122020000038-520.3336111700143114991811010801055116280761820629222.22%8275.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
26Stars2200000016511110000009361100000072541.0001630460014311499181251080105511628063126564125.00%3166.67%01749291959.92%1407258354.47%753129658.10%232317351536482949514
27Thunderbirds4310000024915220000001321121100000117460.7502446700114311499181991080105511628012036241079333.33%10280.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
Total79491501210236717818940238010621878899392670024018090901240.78536765710241111431149918332610801055116280238067150719721684124.40%2303186.52%21749291959.92%1407258354.47%753129658.10%232317351536482949514
29Wild220000001239110000004041100000083541.0001221330114311499187110801055116280521410338675.00%50100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
30Wolf Pack31001010954100010002112100001074361.00091221001431149918871080105511628087323069500.00%15193.33%01749291959.92%1407258354.47%753129658.10%232317351536482949514
31Wolves210000015321000000123-11100000030330.75051015011431149918741080105511628057181056700.00%40100.00%01749291959.92%1407258354.47%753129658.10%232317351536482949514
_Since Last GM Reset79491501210236717818940238010621878899392670024018090901240.78536765710241111431149918332610801055116280238067150719721684124.40%2303186.52%21749291959.92%1407258354.47%753129658.10%232317351536482949514
_Vs Conference452710011512191071122212401041106515523156001101135657680.75621939461305143114991819521080105511628013753843201142972121.65%1442086.11%01749291959.92%1407258354.47%753129658.10%232317351536482949514
_Vs Division22125010201014952116201010442420116300010572532300.6821011782790314311499189541080105511628064717814553142921.43%67986.57%01749291959.92%1407258354.47%753129658.10%232317351536482949514

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
79124W33676571024332623806715071972111
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
79491512102367178
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
40238106218788
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
39267024018090
Derniers 10 Matchs
WLOTWOTL SOWSOL
710020
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1684124.40%2303186.52%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
108010551162801431149918
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
1749291959.92%1407258354.47%753129658.10%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
232317351536482949514


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
2 - 2019-10-0310Bruins7Stars2WSommaire du Match
4 - 2019-10-0526Bruins3Roadrunners2WXXSommaire du Match
7 - 2019-10-0843Bruins3Wolves0WSommaire du Match
9 - 2019-10-1056Bruins1Eagles2LXSommaire du Match
11 - 2019-10-1265Devils4Bruins7WSommaire du Match
13 - 2019-10-1478Gulls1Bruins2WXXSommaire du Match
16 - 2019-10-1798Crunch3Bruins1LSommaire du Match
18 - 2019-10-19116Bruins3Marlies2WSommaire du Match
21 - 2019-10-22133Marlies4Bruins3LSommaire du Match
25 - 2019-10-26162Rampage4Bruins1LSommaire du Match
26 - 2019-10-27175Bruins4Wolf Pack2WSommaire du Match
28 - 2019-10-29179Barracuda5Bruins3LSommaire du Match
32 - 2019-11-02207Senators4Bruins11WSommaire du Match
34 - 2019-11-04220Penguins1Bruins9WSommaire du Match
35 - 2019-11-05224Bruins2Rocket3LXSommaire du Match
38 - 2019-11-08249Bruins2Griffins1WSommaire du Match
40 - 2019-11-10268Phantoms3Bruins4WXXSommaire du Match
42 - 2019-11-12272Thunderbirds0Bruins10WSommaire du Match
45 - 2019-11-15294Bruins3Marlies4LSommaire du Match
46 - 2019-11-16303Bears3Bruins2LSommaire du Match
49 - 2019-11-19320Bruins10Devils0WSommaire du Match
51 - 2019-11-21333Americans2Bruins3WXXSommaire du Match
53 - 2019-11-23353Wild0Bruins4WSommaire du Match
56 - 2019-11-26374Bruins6Rocket3WSommaire du Match
57 - 2019-11-27378Bruins7Senators2WSommaire du Match
59 - 2019-11-29391Wolf Pack1Bruins2WXSommaire du Match
61 - 2019-12-01417Rocket3Bruins4WXXSommaire du Match
63 - 2019-12-03424Checkers0Bruins2WSommaire du Match
65 - 2019-12-05438IceHogs4Bruins3LSommaire du Match
67 - 2019-12-07455Eagles2Bruins6WSommaire du Match
69 - 2019-12-09470Bruins8Senators2WSommaire du Match
71 - 2019-12-11484Bruins7Bears3WSommaire du Match
72 - 2019-12-12488Bruins3Crunch2WSommaire du Match
74 - 2019-12-14510Bruins8Thunderbirds3WSommaire du Match
77 - 2019-12-17524Reign4Bruins5WXXSommaire du Match
79 - 2019-12-19538Sound Tigers1Bruins3WSommaire du Match
81 - 2019-12-21556Admirals1Bruins4WSommaire du Match
83 - 2019-12-23571Bears6Bruins3LSommaire du Match
87 - 2019-12-27582Bruins3Americans5LSommaire du Match
89 - 2019-12-29606Americans1Bruins7WSommaire du Match
91 - 2019-12-31613Bruins10Devils0WSommaire du Match
93 - 2020-01-02627Monsters1Bruins4WSommaire du Match
95 - 2020-01-04641Condors3Bruins11WSommaire du Match
98 - 2020-01-07671Bruins2Admirals3LSommaire du Match
100 - 2020-01-09678Moose0Bruins3WSommaire du Match
102 - 2020-01-11694Bruins3Sound Tigers4LSommaire du Match
104 - 2020-01-13711Bruins3Phantoms2WSommaire du Match
105 - 2020-01-14719Bruins4Monsters3WSommaire du Match
107 - 2020-01-16727Penguins2Bruins7WSommaire du Match
110 - 2020-01-19755Bruins8Penguins2WSommaire du Match
112 - 2020-01-21761Wolves3Bruins2LXXSommaire du Match
122 - 2020-01-31789Bruins6Moose0WSommaire du Match
123 - 2020-02-01802Bruins8Wild3WSommaire du Match
126 - 2020-02-04812Comets2Bruins7WSommaire du Match
127 - 2020-02-05826Bruins3IceHogs2WXXSommaire du Match
130 - 2020-02-08844Roadrunners0Bruins2WSommaire du Match
131 - 2020-02-09855Bruins3Griffins1WSommaire du Match
134 - 2020-02-12877Rocket3Bruins4WSommaire du Match
137 - 2020-02-15895Griffins0Bruins7WSommaire du Match
138 - 2020-02-16907Bruins3Wolf Pack2WXXSommaire du Match
141 - 2020-02-19928Bruins6Condors4WSommaire du Match
143 - 2020-02-21945Bruins8Heat3WSommaire du Match
144 - 2020-02-22956Bruins10Comets0WSommaire du Match
147 - 2020-02-25968Heat2Bruins11WSommaire du Match
149 - 2020-02-27984Stars3Bruins9WSommaire du Match
151 - 2020-02-29999Bruins0Sound Tigers4LSommaire du Match
154 - 2020-03-031019Bruins2Crunch3LSommaire du Match
156 - 2020-03-051035Bruins3Thunderbirds4LSommaire du Match
158 - 2020-03-071054Crunch4Bruins3LXXSommaire du Match
161 - 2020-03-101073Bruins5Phantoms3WSommaire du Match
164 - 2020-03-131093Bruins2Americans1WSommaire du Match
165 - 2020-03-141101Marlies1Bruins2WXXSommaire du Match
167 - 2020-03-161118Monsters2Bruins1LSommaire du Match
169 - 2020-03-181136Bruins2Gulls1WSommaire du Match
170 - 2020-03-191144Bruins4Reign3WSommaire du Match
172 - 2020-03-211163Bruins5Barracuda4WXXSommaire du Match
175 - 2020-03-241176Griffins2Bruins3WSommaire du Match
177 - 2020-03-261191Senators1Bruins9WSommaire du Match
179 - 2020-03-281207Thunderbirds2Bruins3WSommaire du Match
182 - 2020-03-311232Bruins-Checkers-
184 - 2020-04-021250Bruins-Rampage-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
186 - 2020-04-041260Checkers-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
1 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
2,286,980$ 2,141,082$ 2,141,082$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,286,980$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 7 11,450$ 80,150$




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
8794915012102367178189402380106218788993926700240180909012436765710241111431149918332610801055116280238067150719721684124.40%2303186.52%21749291959.92%1407258354.47%753129658.10%232317351536482949514
Total Saison Régulière57134014401614342322321416816286180590952112116666050628516085079131110667563107062232401262444469096666077322442744672567581364163834764562313107209544721.34%237038683.71%22129022138260.34%105301854756.77%5372912058.90%156061125011888389871153751
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
Total Séries734627000002331795438261200000128903835201500000105891692233416649278175725251083576881889229767990817813476819.60%3816183.99%51523279254.55%1398267752.22%616113254.42%188613101702554953487