Bruins

GP: 49 | W: 31 | L: 15 | OTL: 3 | P: 65
GF: 124 | GA: 94 | PP%: 15.14% | PK%: 88.69%
DG: Marcel Cormier | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #543 vs Condors
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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
1Anders BjorkXX100.006942948068636660346370634557576850002311,066,667$
2Carter Verhaeghe (R)X100.00674294646854816140587061255959665000243700,000$
3Jean-Sebastien DeaXX100.00706483626478826480616264595252655000264700,000$
4Jordan KyrouXX100.00614190816557716436646652254848655000221880,000$
5John QuennevilleXXX100.00737276737260606176536564624747645000242750,000$
6Nick CousinsXXX100.007954847568659072456868596064656949002641,000,000$
7Martin KautX100.006967737367677059505954605144445950002021,350,000$
8Mathieu Joseph (R)XX100.00784387826559855934586067255758655000233910,833$
9Nicolas Aube-Kubel (R)X100.00885984676859806534677163254848705000243700,000$
10Pierre EngvallXX100.00674295747461845945627078254848705000242950,000$
11Ryan Donato (R)XX100.007343938367578566436274598058597150002411,350,000$
12Danick MartelX100.00625773625762636350576361605555625000251800,000$
13Oskar SundqvistXX100.007644858177678360576572822560627340002642,750,000$
14Peter CehlarikXX100.00787586677576796550626367604747675000252700,000$
15Trevor MooreX100.00794395666163756234606672255253685000253775,000$
16Jan RuttaX100.006743877776676561255348722557586026002912,300,000$
17Dylan McIlrathX100.00959061659065755625394783255555605000283737,500$
18Jeremy LauzonX100.00827859657567725325444877255353595000232871,666$
19Nicolas Hague (R)X100.00834676788269846625604856254747615000213863,333$
20Matt GrzelcykX100.007142858361758473255948702559616350002641,400,000$
Rayé
1Zach Senyshyn (R)X100.00777190707170745550505663534444605000232792,500$
2Ryan Fitzgerald (R)XX100.00706190656173775771515860554444615000251925,000$
3Cam Dineen (R)X100.00746692666667734725374260404444535000223910,833$
4Jakub ZborilX100.007675786675707551254541633948485450002331,288,333$
5Jeremy RoyX100.00716877616860644725394059384747515000232863,333$
6Tobias Bjornfot (R)X100.007873917473626454254648644644445850001931,083,333$
7Joey Keane (R)X100.00726782616775795925535162484444605000203925,000$
8Rob O'GaraX100.00838187638155574825364565434444555000264900,000$
9Sean Durzi (R)X100.00757185647156585125464161394444535000213925,000$
MOYENNE D'ÉQUIPE100.0075598471706574593954576541515162490
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
1Anthony Stolarz100.0063617688666555656261304545625000
2Dan Vladar100.0068587380707272767675304444704900
Rayé
1Veini Vehvilainen100.0054658169515953595655304444565000
2Filip Larsson (R)100.0044496171404250514445304444465000
MOYENNE D'ÉQUIPE100.005758737757605863605930444459500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Ken Hitchcock87808280999441CAN7031,850,000$


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
1Pierre EngvallBruins (BOS)LW/RW49241741-118046801374013617.52%683317.0113132645216000033051.92%5200010.9811000831
2Ryan DonatoBruins (BOS)C/LW49151631111952381116308012.93%492418.8728102718900031444347.06%54400000.6725001333
3Sean KuralyBruinsC/LW331119305220635962174417.74%1261618.697916191460001863058.40%35100010.9701000421
4Nicolas Aube-KubelBruins (BOS)RW4910192955951064780177012.50%477215.773111422194000004239.13%4600000.7500010146
5Dylan McIlrathBruins (BOS)D4962127816335166406124399.84%4398720.1641014402001014165200.00%000000.5500502131
6Matt GrzelcykBruins (BOS)D4961925023535656812488.82%64113923.2641115482130000239120.00%000000.4400000101
7Nick CousinsBruins (BOS)C/LW/RW3210102010360613858155417.24%163919.983251614401101212048.08%10400000.6303000322
8Jordan KyrouBruins (BOS)C/RW49415191118019403772610.81%767013.6700015000010142.74%23400000.5700000110
9Mathieu JosephBruins (BOS)LW/RW49710177515574863184111.11%656411.5200000000001137.93%2900000.6000010111
10Anders BjorkBruins (BOS)LW/RW494913618025457516495.33%456811.6000004000003150.00%2400000.4600000121
11Jan RuttaBruins (BOS)D325712-3160243950152610.00%3363619.9055104114801101301120.00%500000.3800000010
12Carter VerhaegheBruins (BOS)C4957126200293834132114.71%1862812.8400010000002042.77%31800000.3800000041
13Nicolas HagueBruins (BOS)D4921012-181510541358305.71%24109022.25257292100000207000.00%000000.2200100020
14Oskar SundqvistBruins (BOS)C/RW231910512034804613462.17%1049621.5803359500041260056.20%65300000.4023000212
15Peter CehlarikBruins (BOS)LW/RW493710336052261881516.67%144208.5800000000001133.33%600000.4800000101
16Trevor MooreBruins (BOS)LW49281063155437248228.33%2353510.920001230000251034.18%7900000.3700010101
17Joel EdmundsonBruinsD183581420423015101720.00%1740522.531121175101265100.00%000000.3900000020
18Jeremy LauzonBruins (BOS)D18088101602016179160.00%1938121.170111278011069000.00%000000.4200000001
19Jean-Sebastien DeaBruins (BOS)C/RW4942601409182772614.81%42384.860116310000160160.81%7400000.5000000012
20Tobias BjornfotBruins (BOS)D17246-4751891722.22%1235620.97022363000080000.00%000000.3400001010
21John QuennevilleBruins (BOS)C/LW/RW49235140201591522.22%01923.932137340001800055.56%3600000.5200000001
22Danick MartelBruins (BOS)LW27022000324050.00%6933.4601122300015100100.00%100000.4300000000
Stats d'équipe Total ou en Moyenne8861262273538670670994893104528982312.06%3311319314.8946841303362103235161614291350.00%255600020.54513634283326
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
1Dan VladarBruins (BOS)2719710.9091.77163005485250001.0005270521
2Anthony StolarzBruins (BOS)2212820.8942.03130105444170000.636112227113
Stats d'équipe Total ou en Moyenne49311530.9021.882931010929420000.750164927634


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 Salaire RestantSalaire MoyenSalaire Moyen RestantCap 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
Anders BjorkBruins (BOS)LW/RW231996-08-05No186 Lbs6 ft0NoNoNo1Pro & Farm1,066,667$421,506$1,066,667$421,506$0$0$NoLien
Anthony StolarzBruins (BOS)G261994-01-20No210 Lbs6 ft6NoNoNo1Pro & Farm753,333$297,688$753,333$297,688$0$0$NoLien
Cam DineenBruins (BOS)D221998-06-19Yes183 Lbs5 ft11NoNoNo3Pro & Farm910,833$359,926$910,833$359,926$0$0$No910,833$910,833$
Carter VerhaegheBruins (BOS)C241995-08-14Yes181 Lbs6 ft1NoNoNo3Pro & Farm700,000$276,613$700,000$276,613$0$0$No700,000$700,000$
Dan VladarBruins (BOS)G221997-08-20No185 Lbs6 ft5NoNoNo2Pro & Farm910,000$359,597$450,000$177,823$0$0$No910,000$Lien
Danick MartelBruins (BOS)LW251994-12-12No162 Lbs5 ft8NoNoNo1Pro & Farm800,000$316,129$800,000$316,129$0$0$NoLien
Dylan McIlrathBruins (BOS)D281992-04-20No236 Lbs6 ft5NoNoNo3Pro & Farm737,500$291,431$700,000$276,613$0$0$No700,000$700,000$Lien
Filip LarssonBruins (BOS)G211998-08-17Yes181 Lbs6 ft2NoNoNo1Pro & Farm1,505,787$595,029$1,505,787$595,029$0$0$NoLien
Jakub ZborilBruins (BOS)D231997-02-21No200 Lbs6 ft2NoNoNo3Pro & Farm1,288,333$509,099$1,288,333$509,099$0$0$No1,288,333$1,288,333$Lien
Jan RuttaBruins (BOS)D291990-07-29No200 Lbs6 ft3NoNoNo1Pro & Farm2,300,000$908,871$2,300,000$908,871$0$0$NoLien
Jean-Sebastien DeaBruins (BOS)C/RW261994-02-08No175 Lbs5 ft11NoNoNo4Pro & Farm700,000$276,613$700,000$276,613$0$0$No700,000$700,000$700,000$Lien
Jeremy LauzonBruins (BOS)D231997-04-28No204 Lbs6 ft1NoNoNo2Pro & Farm871,666$344,449$871,666$344,449$0$0$No871,666$Lien
Jeremy RoyBruins (BOS)D231997-05-14No185 Lbs6 ft0NoNoNo2Pro & Farm863,333$341,156$863,333$341,156$0$0$No863,333$Lien
Joey KeaneBruins (BOS)D201999-07-02Yes183 Lbs6 ft0NoNoNo3Pro & Farm925,000$365,524$925,000$365,524$0$0$No925,000$925,000$
John QuennevilleBruins (BOS)C/LW/RW241996-04-16No195 Lbs6 ft1NoNoNo2Pro & Farm750,000$296,371$750,000$296,371$0$0$No750,000$Lien
Jordan KyrouBruins (BOS)C/RW221998-05-05No175 Lbs6 ft0NoNoNo1Pro & Farm880,000$347,742$880,000$347,742$0$0$NoLien
Martin KautBruins (BOS)RW201999-10-02No176 Lbs6 ft2NoNoNo2Pro & Farm1,350,000$533,468$450,000$177,823$0$0$No1,350,000$Lien
Mathieu JosephBruins (BOS)LW/RW231997-02-09Yes173 Lbs6 ft1NoNoNo3Pro & Farm910,833$359,926$910,833$359,926$0$0$No910,833$910,833$
Matt GrzelcykBruins (BOS)D261994-01-05No174 Lbs5 ft9NoNoNo4Pro & Farm1,400,000$553,226$1,400,000$553,226$0$0$No1,400,000$1,400,000$1,400,000$Lien
Nick CousinsBruins (BOS)C/LW/RW261993-07-19No185 Lbs5 ft11NoNoNo4Pro & Farm1,000,000$395,161$1,000,000$395,161$0$0$No1,000,000$1,000,000$1,000,000$Lien
Nicolas Aube-KubelBruins (BOS)RW241996-05-09Yes187 Lbs5 ft11NoNoNo3Pro & Farm700,000$276,613$700,000$276,613$0$0$No700,000$700,000$
Nicolas HagueBruins (BOS)D211998-12-05Yes214 Lbs6 ft6NoNoNo3Pro & Farm863,333$341,156$863,333$341,156$0$0$No863,333$863,333$
Oskar SundqvistBruins (BOS)C/RW261994-03-23No209 Lbs6 ft3NoNoNo4Pro & Farm2,750,000$1,086,694$2,750,000$1,086,694$0$0$No2,750,000$2,750,000$2,750,000$Lien
Peter CehlarikBruins (BOS)LW/RW251995-05-12No202 Lbs6 ft2NoNoNo2Pro & Farm700,000$276,613$700,000$276,613$0$0$No700,000$Lien
Pierre EngvallBruins (BOS)LW/RW241996-05-31No192 Lbs6 ft4NoNoNo2Pro & Farm950,000$375,403$925,000$365,524$0$0$No925,000$Lien
Rob O'GaraBruins (BOS)D261993-07-06No215 Lbs6 ft4NoNoNo4Pro & Farm900,000$355,645$900,000$355,645$0$0$No900,000$900,000$900,000$Lien
Ryan DonatoBruins (BOS)C/LW241996-04-09Yes181 Lbs6 ft0NoNoNo1Pro & Farm1,350,000$533,468$450,000$177,823$0$0$No
Ryan FitzgeraldBruins (BOS)C/LW251994-10-19Yes172 Lbs5 ft9NoNoNo1Pro & Farm925,000$365,524$925,000$365,524$0$0$No
Sean DurziBruins (BOS)D211998-10-21Yes196 Lbs6 ft0NoNoNo3Pro & Farm925,000$365,524$925,000$365,524$0$0$No925,000$925,000$
Tobias BjornfotBruins (BOS)D192001-04-06Yes203 Lbs6 ft0NoNoNo3Pro & Farm1,083,333$428,091$1,083,333$428,091$0$0$No1,083,333$1,083,333$
Trevor MooreBruins (BOS)LW251995-03-31No170 Lbs5 ft9NoNoNo3Pro & Farm775,000$306,250$775,000$306,250$0$0$No775,000$775,000$Lien
Veini VehvilainenBruins (BOS)G231997-02-13No183 Lbs6 ft1NoNoNo3Pro & Farm925,250$365,623$925,000$365,524$0$0$No925,000$925,000$Lien
Zach SenyshynBruins (BOS)RW231997-03-30Yes192 Lbs6 ft1NoNoNo2Pro & Farm792,500$313,165$792,500$313,165$0$0$No792,500$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3323.70190 Lbs6 ft12.421,038,264$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pierre Engvall35122
2Ryan DonatoNicolas Aube-Kubel30122
3Anders BjorkCarter VerhaegheMathieu Joseph25122
4Trevor MooreJordan KyrouPeter Cehlarik10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykNicolas Hague35122
2Dylan McIlrath30122
3Trevor MooreJordan Kyrou25122
4Matt GrzelcykNicolas Hague10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Pierre Engvall60122
2Ryan DonatoNicolas Aube-Kubel40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykNicolas Hague60122
2Dylan McIlrath40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
160122
2Ryan Donato40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykNicolas Hague60122
2Dylan McIlrath40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Matt GrzelcykNicolas Hague60122
240122Dylan McIlrath40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
160122
2Ryan Donato40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Matt GrzelcykNicolas Hague60122
2Dylan McIlrath40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pierre EngvallMatt GrzelcykNicolas Hague
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Pierre EngvallMatt GrzelcykNicolas Hague
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jean-Sebastien Dea, John Quenneville, Danick MartelJean-Sebastien Dea, John QuennevilleDanick Martel
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dylan McIlrath, , Matt GrzelcykDylan McIlrath, Matt Grzelcyk
Tirs de Pénalité
, , Ryan Donato, , Pierre Engvall
Gardien
#1 : Dan Vladar, #2 : Anthony Stolarz


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
1Admirals11000000422000000000001100000042221.000471100444334622301353346232598215240.00%4175.00%0637136246.77%649135148.04%33267948.90%12098391164358592301
2Crunch853000002017343100000129342200000880100.625203959014443346188301353346231654310219153713.21%47295.74%0637136246.77%649135148.04%33267948.90%12098391164358592301
3Flames1010000034-1000000000001010000034-100.000369004443346213013533462321612187114.29%6266.67%0637136246.77%649135148.04%33267948.90%12098391164358592301
4Griffins6420000013112220000004224220000099080.66713243702444334611830135334623135406411328414.29%28389.29%0637136246.77%649135148.04%33267948.90%12098391164358592301
5IceHogs11000000532110000005320000000000021.0005101500444334627301353346232274245240.00%2150.00%0637136246.77%649135148.04%33267948.90%12098391164358592301
6Marlies5310000114131320000019722110000056-170.7001425390044433461053013533462310336578829413.79%26388.46%0637136246.77%649135148.04%33267948.90%12098391164358592301
7Monarchs11000000523110000005230000000000021.00051015004443346233013533462319816226116.67%8275.00%1637136246.77%649135148.04%33267948.90%12098391164358592301
8Monsters32100000523220000004041010000012-140.667581302444334650301353346233612446017317.65%210100.00%0637136246.77%649135148.04%33267948.90%12098391164358592301
9Moose1010000023-11010000023-10000000000000.00024600444334613301353346231663315800.00%7185.71%0637136246.77%649135148.04%33267948.90%12098391164358592301
10Phantoms21000001642000000000002100000164230.7506111700444334644301353346233912385011327.27%19289.47%0637136246.77%649135148.04%33267948.90%12098391164358592301
11Rocket84400000141404220000067-14220000087180.50014253902444334613930135334623145431181564449.09%46882.61%0637136246.77%649135148.04%33267948.90%12098391164358592301
12Senators740001202081232000100126642000020826130.929203252034443346144301353346231274711012145817.78%42392.86%0637136246.77%649135148.04%33267948.90%12098391164358592301
13Soldiers2110000056-1110000005321010000003-320.50059140044433464430135334623379253713323.08%9277.78%0637136246.77%649135148.04%33267948.90%12098391164358592301
14Sound Tigers11000000413110000004130000000000021.00046100044433462930135334623221113156116.67%4175.00%0637136246.77%649135148.04%33267948.90%12098391164358592301
Total49281500132124943024174001117145262511110002153494650.66312422234601044433461006301353346239532956729662844315.14%2833288.69%1637136246.77%649135148.04%33267948.90%12098391164358592301
15Wolf Pack20100010440100000103211010000012-120.500461000444334639301353346234162835700.00%14192.86%0637136246.77%649135148.04%33267948.90%12098391164358592301
_Since Last GM Reset49281500132124943024174001117145262511110002153494650.66312422234601044433461006301353346239532956729662844315.14%2833288.69%1637136246.77%649135148.04%33267948.90%12098391164358592301
_Vs Conference36191100132866620171130011146311519880002140355470.65386152238084443346730301353346236772055097192133014.08%2212190.50%0637136246.77%649135148.04%33267948.90%12098391164358592301
_Vs Division341680012181631816930010143311218750002038326380.55981145226084443346694301353346236752094516691992713.57%1891989.95%0637136246.77%649135148.04%33267948.90%12098391164358592301

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
4965W11242223461006953295672966010
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
492815013212494
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2417401117145
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
25111100215349
Derniers 10 Matchs
WLOTWOTL SOWSOL
730000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2844315.14%2833288.69%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
301353346234443346
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
637136246.77%649135148.04%33267948.90%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12098391164358592301


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 - 2020-09-274Bruins4Rocket2WSommaire du Match
3 - 2020-09-2921Griffins1Bruins2WSommaire du Match
5 - 2020-10-0134Crunch2Bruins3WSommaire du Match
6 - 2020-10-0244Bruins2Crunch0WSommaire du Match
7 - 2020-10-0353Bruins0Soldiers3LSommaire du Match
9 - 2020-10-0563Monsters0Bruins3WSommaire du Match
11 - 2020-10-0777Crunch1Bruins3WSommaire du Match
13 - 2020-10-0988Bruins2Rocket3LSommaire du Match
15 - 2020-10-1198Bruins2Phantoms3LXXSommaire du Match
17 - 2020-10-13109Bruins3Crunch4LSommaire du Match
19 - 2020-10-15120Wolf Pack2Bruins3WXXSommaire du Match
20 - 2020-10-16126Bruins1Griffins5LSommaire du Match
22 - 2020-10-18136Senators0Bruins4WSommaire du Match
23 - 2020-10-19151Marlies3Bruins2LXXSommaire du Match
24 - 2020-10-20157Bruins2Senators0WSommaire du Match
26 - 2020-10-22174Rocket2Bruins0LSommaire du Match
27 - 2020-10-23186Crunch3Bruins2LSommaire du Match
29 - 2020-10-25196Bruins0Crunch2LSommaire du Match
31 - 2020-10-27207Bruins3Griffins0WSommaire du Match
33 - 2020-10-29219Crunch3Bruins4WSommaire du Match
35 - 2020-10-31229Bruins3Griffins4LSommaire du Match
37 - 2020-11-02240IceHogs3Bruins5WSommaire du Match
39 - 2020-11-04252Monarchs2Bruins5WSommaire du Match
41 - 2020-11-06262Bruins3Crunch2WSommaire du Match
43 - 2020-11-08274Bruins1Monsters2LSommaire du Match
44 - 2020-11-09281Senators2Bruins5WSommaire du Match
45 - 2020-11-10293Bruins3Flames4LSommaire du Match
47 - 2020-11-12303Soldiers3Bruins5WSommaire du Match
48 - 2020-11-13315Bruins4Marlies2WSommaire du Match
49 - 2020-11-14323Bruins1Rocket0WSommaire du Match
50 - 2020-11-15329Monsters0Bruins1WSommaire du Match
52 - 2020-11-17344Rocket0Bruins1WSommaire du Match
53 - 2020-11-18357Senators4Bruins3LXSommaire du Match
54 - 2020-11-19368Bruins2Griffins0WSommaire du Match
55 - 2020-11-20377Bruins1Wolf Pack2LSommaire du Match
56 - 2020-11-21388Bruins2Senators1WXXSommaire du Match
57 - 2020-11-22395Marlies2Bruins3WSommaire du Match
59 - 2020-11-24411Rocket4Bruins3LSommaire du Match
60 - 2020-11-25422Bruins4Admirals2WSommaire du Match
62 - 2020-11-27432Rocket1Bruins2WSommaire du Match
64 - 2020-11-29444Bruins2Senators1WXXSommaire du Match
65 - 2020-11-30455Sound Tigers1Bruins4WSommaire du Match
66 - 2020-12-01462Bruins1Marlies4LSommaire du Match
68 - 2020-12-03476Marlies2Bruins4WSommaire du Match
70 - 2020-12-05490Bruins4Phantoms1WSommaire du Match
71 - 2020-12-06499Griffins1Bruins2WSommaire du Match
72 - 2020-12-07512Bruins1Rocket2LSommaire du Match
73 - 2020-12-08520Moose3Bruins2LSommaire du Match
75 - 2020-12-10532Bruins2Senators0WSommaire du Match
76 - 2020-12-11543Bruins-Condors-
77 - 2020-12-12549Monsters-Bruins-
79 - 2020-12-14563Bruins-Sharks-
80 - 2020-12-15572Wolves-Bruins-
81 - 2020-12-16585Sound Tigers-Bruins-
83 - 2020-12-18597Condors-Bruins-
85 - 2020-12-20606Bruins-Wolves-
86 - 2020-12-21619Bruins-Monarchs-
87 - 2020-12-22629Wolf Pack-Bruins-
89 - 2020-12-24640Stars-Bruins-
91 - 2020-12-26655Bruins-Marlies-
92 - 2020-12-27660Bruins-Stars-
94 - 2020-12-29671Rampage-Bruins-
95 - 2020-12-30685Marlies-Bruins-
96 - 2020-12-31690Bruins-Monsters-
97 - 2021-01-01708Bruins-IceHogs-
98 - 2021-01-02715Soldiers-Bruins-
100 - 2021-01-04731Admirals-Bruins-
101 - 2021-01-05739Bruins-Rampage-
103 - 2021-01-07751Bruins-Moose-
104 - 2021-01-08760Senators-Bruins-
105 - 2021-01-09771Bruins-Soldiers-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10779Bruins-Rocket-
107 - 2021-01-11790Phantoms-Bruins-
109 - 2021-01-13803Penguins-Bruins-
111 - 2021-01-15819Sharks-Bruins-
112 - 2021-01-16826Bruins-Marlies-
113 - 2021-01-17833Bruins-Penguins-
115 - 2021-01-19847Flames-Bruins-
117 - 2021-01-21868Griffins-Bruins-
118 - 2021-01-22875Bruins-Penguins-
120 - 2021-01-24885Griffins-Bruins-
121 - 2021-01-25893Bruins-Sound Tigers-



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
3,102,457$ 3,426,269$ 3,193,994$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,983,466$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 49 42,551$ 2,084,999$




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