Bruins

GP: 64 | W: 16 | L: 44 | OTL: 4 | P: 36
GF: 252 | GA: 410 | PP%: 34.90% | PK%: 45.98%
DG: Marc Andre Marinier | Morale : 31 | Moyenne d'Équipe : 66
Prochain matchs #777 vs Bears
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Timo MeierXX100.007243797976829668745472647354528666680
2Jujhar KhairaX100.007843757184808470755263707253546666670
3Daniel SprongX100.006142747970739985515560606651517447660
4Tomas NosekX100.006441817981778366745058737053524266660
5J.T. BrownX100.007442737158747263714853716562563645640
6Kalle KossilaX100.005542748463729479794756606450504266640
7Jean-Sebastien DeaX100.005346646162649962784560606150504366600
8Fredrik ClaessonX100.008443817173777968305052716454545663680
9Michal KempnyX100.006841867469776874305055746554523666680
Rayé
MOYENNE D'ÉQUIPE100.00684376747175867162505967675352536166
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 Hutchinson100.00756691837579757676757258675466730
Rayé
MOYENNE D'ÉQUIPE100.0075669183757975767675725867546673
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Peter DeBoer86878587836672CAN4921,200,000$


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
1J.T. BrownBruins (BOS)RW64162945-1232104636250871756.40%2788713.8610111000160058.97%395337001.0111011868
2Daniel SprongBruins (BOS)RW6481725-153602022186591174.30%96109.5300000000000150.00%324513000.8201000644
Stats d'équipe Total ou en Moyenne128244670-27681066584361462925.50%36149711.7010111000160154.93%719850000.9312011141012
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Daniel SprongBruins (BOS)RW201997-03-17No180 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Fredrik ClaessonBruins (BOS)D241992-11-24No200 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
J.T. BrownBruins (BOS)RW271990-07-02No169 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Jean-Sebastien DeaBruins (BOS)C231994-02-08No175 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jujhar KhairaBruins (BOS)LW231994-08-13No214 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Kalle KossilaBruins (BOS)C241993-04-14No185 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Michael HutchinsonBruins (BOS)G271990-03-02No202 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm1,300,000$0$0$NoLien
Michal KempnyBruins (BOS)D271990-09-08No194 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm2,500,000$0$0$NoLien
Timo MeierBruins (BOS)LW/RW201996-10-08No215 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm894,166$0$0$NoLien
Tomas NosekBruins (BOS)LW251992-09-01No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1024.00194 Lbs6 ft11.50994,417$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2J.T. Brown30122
3Daniel Sprong20122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2J.T. Brown40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2J.T. Brown40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
16012260122
24012240122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2J.T. Brown40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Daniel Sprong, J.T. Brown, Daniel Sprong, J.T. Brown
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , J.T. Brown, Daniel Sprong
Gardien
#1 : , #2 :


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
1Admirals20100100915-61000010034-110100000611-510.25091726004210010845946960859214953126265240.00%13746.15%0428107139.96%433110539.19%516139337.04%135782814635901031472
2Barracuda211000006601010000024-21100000042220.5006121800421001084554696085921437781711218.18%4250.00%0428107139.96%433110539.19%516139337.04%135782814635901031472
3Blacknight220000001082110000006511100000043141.0001017270042100108449469608592144211222510440.00%11281.82%1428107139.96%433110539.19%516139337.04%135782814635901031472
4Condors20200000314-1120200000314-110000000000000.00036900421001084634696085921467302029800.00%10640.00%1428107139.96%433110539.19%516139337.04%135782814635901031472
5Crunch5220100028244220000001688302010001216-460.6002854820042100108413346960859214110424462261350.00%231439.13%2428107139.96%433110539.19%516139337.04%135782814635901031472
6Devils404000001838-20202000001019-920200000819-1100.00018335100421001084964696085921419473625313646.15%262023.08%2428107139.96%433110539.19%516139337.04%135782814635901031472
7Gulls20200000613-71010000017-61010000056-100.00061117004210010844146960859214601822287114.29%11463.64%0428107139.96%433110539.19%516139337.04%135782814635901031472
8Heat10100000210-80000000000010100000210-800.000235004210010842146960859214327181822100.00%9544.44%0428107139.96%433110539.19%516139337.04%135782814635901031472
9Icedogs21100000660110000003211010000034-120.50061218004210010843446960859214441514234250.00%7271.43%0428107139.96%433110539.19%516139337.04%135782814635901031472
10Marlies413000001320-720200000714-72110000066020.250132538004210010841324696085921415138334520630.00%14471.43%0428107139.96%433110539.19%516139337.04%135782814635901031472
11Monsters302001001018-81000010034-120200000714-710.1671020300042100108474469608592146415344112325.00%16475.00%0428107139.96%433110539.19%516139337.04%135782814635901031472
12Moose202000001317-41010000079-21010000068-200.000132538004210010846046960859214792338158450.00%11645.45%1428107139.96%433110539.19%516139337.04%135782814635901031472
13Penguins40400000933-2420200000415-1120200000518-1300.00091827004210010841134696085921414850534818316.67%241537.50%1428107139.96%433110539.19%516139337.04%135782814635901031472
14Phantoms404000001532-1720200000815-720200000717-1000.00015294400421001084974696085921416064325617741.18%161412.50%0428107139.96%433110539.19%516139337.04%135782814635901031472
15Rampages30300000830-221010000029-720200000621-1500.000816240042100108470469608592141244042286116.67%211338.10%0428107139.96%433110539.19%516139337.04%135782814635901031472
16Reigh211000001064110000009451010000012-120.500101929004210010844346960859214641120326466.67%10280.00%0428107139.96%433110539.19%516139337.04%135782814635901031472
17Rocket733010002932-34300100019109303000001022-1280.571295584004210010841814696085921420977488826830.77%24866.67%0428107139.96%433110539.19%516139337.04%135782814635901031472
18Senateurs30300000822-1420200000616-101010000026-400.0008162400421001084754696085921412338364015426.67%181233.33%0428107139.96%433110539.19%516139337.04%135782814635901031472
19Sound Tigers201000011317-400000000000201000011317-410.2501326390042100108459469608592147436242310660.00%13127.69%0428107139.96%433110539.19%516139337.04%135782814635901031472
20Stars10100000210-810100000210-80000000000000.00023500421001084314696085921452101011300.00%550.00%1428107139.96%433110539.19%516139337.04%135782814635901031472
21Thunderbird632001003132-13210000017152311001001417-370.5833157880042100108416946960859214178714068251040.00%20955.00%1428107139.96%433110539.19%516139337.04%135782814635901031472
Total64144402301252410-15832101901200131191-603242501101121219-98360.2812524807320042100108416784696085921421397176587932558934.90%31116845.98%10428107139.96%433110539.19%516139337.04%135782814635901031472
23Wolves1010000037-41010000037-40000000000000.000369004210010842346960859214321012173133.33%5260.00%0428107139.96%433110539.19%516139337.04%135782814635901031472
_Since Last GM Reset64144402301252410-15832101901200131191-603242501101121219-98360.2812524807320042100108416784696085921421397176587932558934.90%31116845.98%10428107139.96%433110539.19%516139337.04%135782814635901031472
_Vs Conference4292802201174268-94207110110090116-26222170110184152-68250.2981743335070042100108411294696085921414115044065241826636.26%19411242.27%6428107139.96%433110539.19%516139337.04%135782814635901031472
_Vs Division2591302100109130-21137501000656321228011004467-23230.46010920731600421001084690469608592147712662013031124136.61%994752.53%3428107139.96%433110539.19%516139337.04%135782814635901031472

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
6436L12524807321678213971765879300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6414442301252410
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3210191200131191
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
324251101121219
Derniers 10 Matchs
WLOTWOTL SOWSOL
280000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2558934.90%31116845.98%10
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
46960859214421001084
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
428107139.96%433110539.19%516139337.04%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
135782814635901031472


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 - 2018-10-119Rocket1Bruins5WSommaire du Match
6 - 2018-10-1421Bruins4Crunch7LSommaire du Match
11 - 2018-10-1938Marlies6Bruins5LSommaire du Match
16 - 2018-10-2453Crunch4Bruins6WSommaire du Match
18 - 2018-10-2657Bruins4Thunderbird8LSommaire du Match
20 - 2018-10-2869Bruins5Rocket9LSommaire du Match
22 - 2018-10-3079Rocket3Bruins4WXSommaire du Match
24 - 2018-11-0190Bruins3Marlies5LSommaire du Match
27 - 2018-11-04107Thunderbird10Bruins7LSommaire du Match
30 - 2018-11-07123Bruins4Monsters5LSommaire du Match
32 - 2018-11-09132Senateurs8Bruins1LSommaire du Match
34 - 2018-11-11145Bruins6Sound Tigers9LSommaire du Match
36 - 2018-11-13152Bruins2Devils9LSommaire du Match
37 - 2018-11-14158Bruins2Senateurs6LSommaire du Match
39 - 2018-11-16166Condors8Bruins1LSommaire du Match
44 - 2018-11-21185Marlies8Bruins2LSommaire du Match
48 - 2018-11-25202Rampages9Bruins2LSommaire du Match
50 - 2018-11-27211Bruins4Blacknight3WSommaire du Match
54 - 2018-12-01226Bruins2Penguins9LSommaire du Match
56 - 2018-12-03231Penguins8Bruins2LSommaire du Match
60 - 2018-12-07242Bruins7Sound Tigers8LXXSommaire du Match
62 - 2018-12-09254Barracuda4Bruins2LSommaire du Match
68 - 2018-12-15272Bruins1Reigh2LSommaire du Match
69 - 2018-12-16280Penguins7Bruins2LSommaire du Match
73 - 2018-12-20297Rocket2Bruins5WSommaire du Match
77 - 2018-12-24317Admirals4Bruins3LXSommaire du Match
80 - 2018-12-27329Bruins4Barracuda2WSommaire du Match
82 - 2018-12-29341Icedogs2Bruins3WSommaire du Match
87 - 2019-01-03360Bruins6Devils10LSommaire du Match
88 - 2019-01-04369Rocket4Bruins5WSommaire du Match
91 - 2019-01-07384Bruins2Rampages11LSommaire du Match
94 - 2019-01-10393Crunch4Bruins10WSommaire du Match
97 - 2019-01-13407Bruins3Penguins9LSommaire du Match
99 - 2019-01-15415Gulls7Bruins1LSommaire du Match
103 - 2019-01-19433Bruins6Crunch5WXSommaire du Match
105 - 2019-01-21438Stars10Bruins2LSommaire du Match
107 - 2019-01-23452Bruins5Phantoms8LSommaire du Match
109 - 2019-01-25459Bruins6Thunderbird7LXSommaire du Match
111 - 2019-01-27468Phantoms7Bruins5LSommaire du Match
116 - 2019-02-01488Condors6Bruins2LSommaire du Match
119 - 2019-02-04500Bruins1Rocket7LSommaire du Match
121 - 2019-02-06510Moose9Bruins7LSommaire du Match
124 - 2019-02-09515Bruins3Monsters9LSommaire du Match
128 - 2019-02-13530Bruins2Heat10LSommaire du Match
130 - 2019-02-15540Thunderbird3Bruins6WSommaire du Match
133 - 2019-02-18558Bruins5Gulls6LSommaire du Match
134 - 2019-02-19564Blacknight5Bruins6WSommaire du Match
138 - 2019-02-23584Wolves7Bruins3LSommaire du Match
140 - 2019-02-25590Bruins4Rampages10LSommaire du Match
143 - 2019-02-28601Bruins2Crunch4LSommaire du Match
145 - 2019-03-02607Bruins6Admirals11LSommaire du Match
146 - 2019-03-03615Reigh4Bruins9WSommaire du Match
149 - 2019-03-06629Bruins4Thunderbird2WSommaire du Match
150 - 2019-03-07639Monsters4Bruins3LXSommaire du Match
154 - 2019-03-11657Phantoms8Bruins3LSommaire du Match
156 - 2019-03-13667Bruins2Phantoms9LSommaire du Match
161 - 2019-03-18684Devils10Bruins5LSommaire du Match
164 - 2019-03-21700Bruins3Marlies1WSommaire du Match
165 - 2019-03-22707Bruins6Moose8LSommaire du Match
166 - 2019-03-23711Devils9Bruins5LSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
171 - 2019-03-28730Senateurs8Bruins5LSommaire du Match
175 - 2019-04-01743Bruins3Icedogs4LSommaire du Match
178 - 2019-04-04755Thunderbird2Bruins4WSommaire du Match
180 - 2019-04-06758Bruins4Rocket6LSommaire du Match
184 - 2019-04-10777Bruins-Bears-
186 - 2019-04-12783Senateurs-Bruins-
187 - 2019-04-13793Bruins-Marlies-
191 - 2019-04-17808Sound Tigers-Bruins-
193 - 2019-04-19816Bruins-Wolves-
196 - 2019-04-22828Marlies-Bruins-
202 - 2019-04-28850Crunch-Bruins-
206 - 2019-05-02867Bruins-Bears-
207 - 2019-05-03874Monsters-Bruins-
213 - 2019-05-09893Sound Tigers-Bruins-
217 - 2019-05-13910Bruins-Senateurs-
218 - 2019-05-14915Bruins-Stars-
219 - 2019-05-15923Bears-Bruins-
220 - 2019-05-16929Bruins-Senateurs-
225 - 2019-05-21947Heat-Bruins-
231 - 2019-05-27963Bruins-Stars-
232 - 2019-05-28967Bruins-Condors-
234 - 2019-05-30977Bears-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
9 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
1,643,868$ 994,417$ 994,417$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 732,456$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 57 9,259$ 527,763$




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
264144402301252410-15832101901200131191-603242501101121219-98362524807320042100108416784696085921421397176587932558934.90%31116845.98%10428107139.96%433110539.19%516139337.04%135782814635901031472
Total Saison Régulière64144402301252410-15832101901200131191-603242501101121219-98362524807320042100108416784696085921421397176587932558934.90%31116845.98%10428107139.96%433110539.19%516139337.04%135782814635901031472