Bruins

GP: 7 | W: 0 | L: 7 | OTL: 0 | P: 0
GF: 22 | GA: 54 | PP%: 44.44% | PK%: 41.86%
DG: Marc Andre Marinier | Morale : 46 | Moyenne d'Équipe : 67
Prochain matchs #84 vs Devils
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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
1Daniel SprongX100.005838856971727768546371527463657748700
2Jujhar KhairaX100.008553726489737463677057716267656352680
3Tomas NosekX100.007537876485738163706162746273683748680
4J.T. BrownX100.007444826566717364626364656277696348670
5Jordan KyrouX100.005236926369776662726461596562627652670
6Jean-Sebastien DeaX100.005739826567796664726365676269665152660
7Kalle KossilaX100.005236916067786559695860665771675152630
8Vladislav KamenevX100.006138855779645057735758625865637452610
9Andrej SustrX100.006637895799786456305453624577694652660
Rayé
MOYENNE D'ÉQUIPE100.00644085637774686263616164616966605166
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 Hutchinson100.00787775837776787776787777835552760
Rayé
MOYENNE D'ÉQUIPE100.0078777583777678777678777783555276
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Peter DeBoer79829481757075CAN5011,200,000$


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'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
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


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
Andrej SustrBruins (BOS)D261990-11-29No217 Lbs6 ft7NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Daniel SprongBruins (BOS)RW201997-03-17No180 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
J.T. BrownBruins (BOS)RW271990-07-02No166 Lbs5 ft10NoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Jean-Sebastien DeaBruins (BOS)C231994-02-08No175 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jordan KyrouBruins (BOS)C191998-05-05No175 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jujhar KhairaBruins (BOS)LW231994-08-13No212 Lbs6 ft4NoNoNo2Contrat d'EntréePro & Farm1,200,000$0$0$NoLien
Kalle KossilaBruins (BOS)C241993-04-14No185 Lbs5 ft10NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Michael HutchinsonBruins (BOS)G271990-03-02No200 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm750,000$0$0$NoLien
Tomas NosekBruins (BOS)LW251992-09-01No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm1,000,000$0$0$NoLien
Vladislav KamenevBruins (BOS)C211996-08-12No194 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1023.50191 Lbs6 ft11.30820,000$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
230122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
240122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
160122
240122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
240122
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
240122
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
, , ,
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, , ,
Tirs de Pénalité
, , , ,
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
1Crunch1010000035-2000000000001010000035-200.0003580018130234545740247883133.33%4250.00%04610742.99%419045.56%7116044.38%151901526611553
2Marlies10100000212-1010100000212-100000000000000.000246001813028454574036914154125.00%7614.29%04610742.99%419045.56%7116044.38%151901526611553
3Rocket1010000027-5000000000001010000027-500.00024600181302145457402981211200.00%6266.67%04610742.99%419045.56%7116044.38%151901526611553
4Senateurs30300000921-121010000045-120200000516-1100.0009172600181306345457406925414211545.45%161037.50%14610742.99%419045.56%7116044.38%151901526611553
5Thunderbird1010000069-31010000069-30000000000000.0006121800181302945457402162087571.43%10550.00%04610742.99%419045.56%7116044.38%151901526611553
Total707000002254-32303000001226-14404000001028-1800.00022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553
_Since Last GM Reset707000002254-32303000001226-14404000001028-1800.00022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553
_Vs Conference707000002254-32303000001226-14404000001028-1800.00022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553
_Vs Division707000002254-32303000001226-14404000001028-1800.00022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
70L722426416417955958400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
70700002254
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
30300001226
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
40400001028
Derniers 10 Matchs
WLOTWOTL SOWSOL
070000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
271244.44%432541.86%1
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
454574018130
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
4610742.99%419045.56%7116044.38%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
151901526611553


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 - 2019-10-0613Bruins2Rocket7LSommaire du Match
4 - 2019-10-0722Bruins2Senateurs8LSommaire du Match
5 - 2019-10-0824Senateurs5Bruins4LSommaire du Match
9 - 2019-10-1244Bruins3Crunch5LSommaire du Match
10 - 2019-10-1348Thunderbird9Bruins6LSommaire du Match
12 - 2019-10-1562Bruins3Senateurs8LSommaire du Match
14 - 2019-10-1772Marlies12Bruins2LSommaire du Match
16 - 2019-10-1984Bruins-Devils-
17 - 2019-10-2095Rocket-Bruins-
20 - 2019-10-23113Crunch-Bruins-
21 - 2019-10-24118Bruins-Thunderbird-
22 - 2019-10-25122Bruins-Marlies-
25 - 2019-10-28143Bears-Bruins-
29 - 2019-11-01159Senateurs-Bruins-
31 - 2019-11-03173Bruins-Penguins-
33 - 2019-11-05180Phantoms-Bruins-
36 - 2019-11-08194Bruins-Rocket-
38 - 2019-11-10207Monsters-Bruins-
41 - 2019-11-13224Bruins-Reigh-
43 - 2019-11-15230Bruins-Bears-
45 - 2019-11-17238Bruins-Heat-
46 - 2019-11-18244Wolves-Bruins-
49 - 2019-11-21261Condors-Bruins-
51 - 2019-11-23276Phantoms-Bruins-
55 - 2019-11-27298Thunderbird-Bruins-
57 - 2019-11-29311Bruins-Wolves-
60 - 2019-12-02322Devils-Bruins-
62 - 2019-12-04334Bruins-Sound Tigers-
64 - 2019-12-06343Reigh-Bruins-
66 - 2019-12-08359Bruins-Gulls-
68 - 2019-12-10368Bruins-Admirals-
70 - 2019-12-12377Admirals-Bruins-
72 - 2019-12-14386Bruins-Rocket-
75 - 2019-12-17399Devils-Bruins-
78 - 2019-12-20413Bruins-Barracuda-
79 - 2019-12-21425Stars-Bruins-
81 - 2019-12-23438Bruins-Crunch-
83 - 2019-12-25448Heat-Bruins-
85 - 2019-12-27463Bruins-Crunch-
87 - 2019-12-29473Bears-Bruins-
90 - 2020-01-01487Bruins-Rampages-
92 - 2020-01-03494Penguins-Bruins-
95 - 2020-01-06508Bruins-Stars-
97 - 2020-01-08520Thunderbird-Bruins-
100 - 2020-01-11535Bruins-Blacknight-
102 - 2020-01-13542Bruins-Penguins-
103 - 2020-01-14549Sound Tigers-Bruins-
106 - 2020-01-17565Marlies-Bruins-
108 - 2020-01-19576Bruins-Thunderbird-
110 - 2020-01-21589Monsters-Bruins-
112 - 2020-01-23599Bruins-Phantoms-
117 - 2020-01-28617Icedogs-Bruins-
119 - 2020-01-30632Bruins-Moose-
120 - 2020-01-31640Rampages-Bruins-
123 - 2020-02-03655Bruins-Bears-
124 - 2020-02-04664Blacknight-Bruins-
127 - 2020-02-07682Bruins-Senateurs-
129 - 2020-02-09689Barracuda-Bruins-
132 - 2020-02-12707Sound Tigers-Bruins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
134 - 2020-02-14714Bruins-Icedogs-
136 - 2020-02-16728Bruins-Devils-
137 - 2020-02-17735Crunch-Bruins-
142 - 2020-02-22754Crunch-Bruins-
143 - 2020-02-23760Bruins-Condors-
146 - 2020-02-26775Bruins-Devils-
147 - 2020-02-27780Rocket-Bruins-
151 - 2020-03-02803Gulls-Bruins-
154 - 2020-03-05813Bruins-Thunderbird-
156 - 2020-03-07825Senateurs-Bruins-
158 - 2020-03-09837Bruins-Phantoms-
160 - 2020-03-11842Bruins-Marlies-
162 - 2020-03-13853Penguins-Bruins-
164 - 2020-03-15862Bruins-Sound Tigers-
167 - 2020-03-18874Bruins-Senateurs-
168 - 2020-03-19883Rocket-Bruins-
169 - 2020-03-20889Bruins-Marlies-
172 - 2020-03-23904Marlies-Bruins-
176 - 2020-03-27927Senateurs-Bruins-
180 - 2020-03-31945Moose-Bruins-
183 - 2020-04-03958Bruins-Monsters-
188 - 2020-04-08973Moose-Bruins-
189 - 2020-04-09978Bruins-Monsters-



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
38 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
156,022$ 820,000$ 820,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 61,777$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 176 10,576$ 1,861,376$




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
3707000002254-32303000001226-14404000001028-18022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553
Total Saison Régulière707000002254-32303000001226-14404000001028-18022426400181301644545740179559584271244.44%432541.86%14610742.99%419045.56%7116044.38%151901526611553