Bruins

GP: 70 | W: 44 | L: 22 | OTL: 4 | P: 92
GF: 199 | GA: 129 | PP%: 11.31% | PK%: 86.51%
DG: Steve Gagné | Morale : 75 | Moyenne d'Équipe : 61
Prochain matchs #1075 vs Sound Tigers
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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
1Sam MileticX100.006236916174898360686356595863626384620
2Carter CamperX100.005036906165939160706256555879715449610
3Nathan GerbeXXX100.005239816260847861706356545980795383610
4Connor Bunnaman (R)X100.006536925979928858605558605861636488610
5Michael CarconeX100.005038856163928860655959546065636284600
6Liam O'BrienX100.006843715980949556585453565569656046600
7Phillip Di GiuseppeXX100.007938875973736258546057565871667252590
8Giovanni FioreXX100.006036925675908555585354575265635486590
9Zac RinaldoXX100.009452696069605058535459625777704047590
10Cameron HughesX100.005337875954908458615756525765636247580
11Anthony RichardXXX100.005435935863787257615956545865636184580
12Shawn O'Donnell (R)X100.006140805476908553525152545379715486580
13Slater KoekkoekX100.007339846579815063306462715369658384650
14Carson SoucyX100.007540795592939054305552594569655546640
15William Borgen (R)X100.006836905883897257305453594565636284620
16Gustav Bouramman (R)X100.005936925473787253305251555263626648580
17Luke Green (R)X100.006039825575716854305452544561636486580
Rayé
1Curtis McKenzieX100.006743726181949260686157605975685719630
2Frederick GaudreauXX100.005635946372646862706364666271674334620
3Jack Kopacka (R)X100.006535945980827458615654575561636419590
4Steven LorentzX100.007138845788797356585552595465636220590
5Spencer Smallman (R)X100.006340805977726858696252575465636219580
6Yannick VeilleuxXXX100.006441765479898353545152555371665920570
7Joe MorrowX100.007850806574765463307162645673676917640
8Nate ProsserX100.00663688598174635830605674498273398640
9Brian StraitX100.006344645279778052305857605580675119600
MOYENNE D'ÉQUIPE100.00643984597582765852585659557066595260
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
1Christopher Gibson100.00786866827776787776787773776381740
2Callum Booth (R)100.00706664836968706968706963677385680
Rayé
1Jeremy Smith100.00747876707372747372747378844319710
MOYENNE D'ÉQUIPE100.0074716978737274737274737176606271
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Doug Weight75717977747077USA483100,000$


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
1Slater KoekkoekBruins (Bos)D741342551082014710916343907.98%69189025.5556119128100011972125.00%400000.5800000345
2Connor BunnamanBruins (Bos)C7019294820420771211785310010.67%34146120.881893420101121294255.46%108000000.6600000634
3Sam MileticBruins (Bos)LW70133043161808893183501267.10%18147321.042684023710141071151.96%30600000.5800000241
4Michael CarconeBruins (Bos)LW701020302622102477139391047.19%7125217.89235181370001563051.61%12400000.4800100134
5William BorgenBruins (Bos)D693273017671591477831373.85%53181826.3523541257000117110100.00%100000.3300002031
6Giovanni FioreBruins (Bos)LW/RW701117289240645512531798.80%9124217.7545917210000071153.66%8200000.4500000033
7Frederick GaudreauBruins (Bos)C/LW43817251801710111644946.90%884619.68156271720002340154.78%92000000.5900000031
8Carter CamperBruins (Bos)C351014241320176196175710.42%1070620.18123241170003724059.15%63900000.6800000313
9Luke GreenBruins (Bos)D704192333561074324117239.76%46150421.49336221860000149000.00%000000.3100101001
10Phillip Di GiuseppeBruins (Bos)LW/RW3211112214295673962143917.74%247414.823251162000013156.52%2300000.9300100531
11Nathan GerbeBruins (Bos)C/LW/RW347101711155184970213710.00%153315.6811212590004361062.59%27800000.6400001211
12Anthony RichardBruins (Bos)C/LW/RW691161712160164667144316.42%883112.051127450001561053.50%44300000.4100000111
13Carson SoucyBruins (Bos)D283111423411555163061410.00%2970125.0601118104000178110.00%000000.4000102013
14Zac RinaldoBruins (Bos)LW/RW3485137455722057195114.04%435010.310115340000141060.61%3300000.7400010112
15Liam O'BrienBruins (Bos)LW28641072210352147152512.77%337113.28000290000121153.57%2800000.5400002011
16Shawn O'DonnellBruins (Bos)RW7037101619536254019297.50%970010.010221380000231059.65%5700000.2900100000
17Cameron HughesBruins (Bos)C284373004323882410.53%02759.8500001000082057.81%23700000.5100000011
18Gustav BourammanBruins (Bos)D28257612021101631612.50%2454519.48011758000058100.00%000000.2600000001
19Nate ProsserBruins (Bos)D1925791201318239248.70%1847625.080001377000051100.00%000000.2900000002
20Joe MorrowBruins (Bos)D2044340411040.00%25226.120221400004000.00%000001.5300000100
Stats d'équipe Total ou en Moyenne94314828643425653680940973157045310169.43%3541750818.57265278391230011220127329955.93%425500000.5000518253336
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
1Christopher GibsonBruins (Bos)70442240.9121.84417610912814600301.0009700424
2Callum BoothBruins (Bos)20000.9231.3345001130000.0000070000
Stats d'équipe Total ou en Moyenne72442240.9121.83422110912914730301.00097070424


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
Anthony RichardBruins (Bos)C/LW/RW221996-12-20No163 Lbs5 ft10NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Brian StraitBruins (Bos)D311988-01-04No206 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Callum BoothBruins (Bos)G221997-05-21Yes184 Lbs6 ft4NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Cameron HughesBruins (Bos)C221996-10-06No160 Lbs5 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Carson SoucyBruins (Bos)D241994-07-27No211 Lbs6 ft5NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Carter CamperBruins (Bos)C301988-07-06No176 Lbs5 ft9NoNoNo3Pro & Farm311,002$0$0$No311,002$311,002$Lien
Christopher GibsonBruins (Bos)G261992-12-27No207 Lbs6 ft2NoNoNo4Pro & Farm500,000$0$0$No500,000$500,000$500,000$Lien
Connor BunnamanBruins (Bos)C211998-04-16Yes207 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Curtis McKenzieBruins (Bos)LW281991-02-22No205 Lbs6 ft2NoNoNo1Pro & Farm500,000$0$0$NoLien
Frederick GaudreauBruins (Bos)C/LW261993-05-01No179 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Giovanni FioreBruins (Bos)LW/RW221996-08-13No188 Lbs6 ft1NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Gustav BourammanBruins (Bos)D221997-01-24Yes194 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Jack KopackaBruins (Bos)LW211998-03-05Yes197 Lbs6 ft2NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Jeremy SmithBruins (Bos)G301989-04-13No177 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Joe MorrowBruins (Bos)D261992-12-09No196 Lbs6 ft0NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Liam O'BrienBruins (Bos)LW241994-07-29No215 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Luke GreenBruins (Bos)D211998-01-12Yes188 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Michael CarconeBruins (Bos)LW231996-05-19No170 Lbs5 ft9NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Nate ProsserBruins (Bos)D331986-05-07No201 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Nathan GerbeBruins (Bos)C/LW/RW311987-07-24No176 Lbs5 ft4NoNoNo1Pro & Farm500,000$0$0$NoLien
Phillip Di GiuseppeBruins (Bos)LW/RW251993-10-09No192 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Sam MileticBruins (Bos)LW221997-05-04No197 Lbs6 ft0NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Shawn O'DonnellBruins (Bos)RW311988-05-28Yes192 Lbs6 ft1NoNoNo1Pro & Farm300,000$0$0$NoLien
Slater KoekkoekBruins (Bos)D251994-02-18No193 Lbs6 ft2NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Spencer SmallmanBruins (Bos)RW221996-09-09Yes198 Lbs6 ft1NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Steven LorentzBruins (Bos)LW231996-04-13No206 Lbs6 ft4NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
William BorgenBruins (Bos)D221996-12-19Yes196 Lbs6 ft3NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Yannick VeilleuxBruins (Bos)C/LW/RW261993-02-22No195 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Zac RinaldoBruins (Bos)LW/RW291990-06-15No192 Lbs5 ft10NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2925.17192 Lbs6 ft03.03369,345$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sam MileticConnor BunnamanNathan Gerbe40122
2Michael CarconeCarter CamperGiovanni Fiore30122
3Liam O'BrienAnthony RichardPhillip Di Giuseppe20122
4Zac RinaldoCameron HughesShawn O'Donnell10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekCarson Soucy40122
2William BorgenGustav Bouramman30122
3Luke GreenSlater Koekkoek20122
4Carson SoucyWilliam Borgen10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Sam MileticConnor BunnamanNathan Gerbe60122
2Michael CarconeCarter CamperGiovanni Fiore40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekCarson Soucy60122
2William BorgenGustav Bouramman40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Sam MileticConnor Bunnaman60122
2Nathan GerbeCarter Camper40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekCarson Soucy60122
2William BorgenGustav Bouramman40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Sam Miletic60122Slater KoekkoekCarson Soucy60122
2Connor Bunnaman40122William BorgenGustav Bouramman40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Sam MileticConnor Bunnaman60122
2Nathan GerbeCarter Camper40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Slater KoekkoekCarson Soucy60122
2William BorgenGustav Bouramman40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sam MileticConnor BunnamanNathan GerbeSlater KoekkoekCarson Soucy
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Sam MileticConnor BunnamanNathan GerbeSlater KoekkoekCarson Soucy
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Liam O'Brien, Phillip Di Giuseppe, Zac RinaldoLiam O'Brien, Phillip Di GiuseppeZac Rinaldo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Luke Green, Gustav Bouramman, Slater KoekkoekLuke GreenGustav Bouramman, Slater Koekkoek
Tirs de Pénalité
Sam Miletic, Connor Bunnaman, Nathan Gerbe, Carter Camper, Michael Carcone
Gardien
#1 : Christopher Gibson, #2 : Callum Booth


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
1Americans21100000330110000003211010000001-120.5003470083654656167560470517457233310110.00%8275.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
2Bears6420000016151321000009633210000079-280.667162844008365465185675604705171363761894324.65%21480.95%01397235659.30%1060198053.54%51697253.09%187313501506486848447
3Checkers880000004734444000000233204400000024024161.000478613306836546538867560470517110285019034617.65%220100.00%11397235659.30%1060198053.54%51697253.09%187313501506486848447
4Comets10000010321000000000001000001032121.00034700836546522675604705172676145120.00%20100.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
5Crunch2020000014-31010000012-11010000002-200.0001120083654655667560470517471325341300.00%90100.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
6Devils21100000321110000003121010000001-120.500369008365465536756047051742911331200.00%30100.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
7Marlies2200000016412110000008351100000081741.0001628440083654651026756047051733116377228.57%30100.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
8Penguins63200100121203110010067-13210000065170.5831223350083654651376756047051715336791203139.68%30680.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
9Phantoms53101000963220000003123110100065180.80091524018365465117675604705171002753822428.33%22481.82%11397235659.30%1060198053.54%51697253.09%187313501506486848447
10Rocket2110000045-1110000003121010000014-320.500461000836546547675604705174111313013215.38%6266.67%01397235659.30%1060198053.54%51697253.09%187313501506486848447
11Senators2110000045-1110000003121010000014-320.5004812008365465616756047051735151327300.00%4250.00%01397235659.30%1060198053.54%51697253.09%187313501506486848447
12Sound Tigers105400100171525320000088052200100972110.55017324901836546522767560470517214569515334411.76%39587.18%01397235659.30%1060198053.54%51697253.09%187313501506486848447
13Thunderbirds12530121032284622011001214-26310011020146160.66732578901836546530367560470517271849716647510.64%43686.05%21397235659.30%1060198053.54%51697253.09%187313501506486848447
Total70392202430199129703421901210986533361813012201016437920.657199349548098365465199267560470517147340565211643363811.31%2523486.51%41397235659.30%1060198053.54%51697253.09%187313501506486848447
15Wolf Pack105400010322575220001016160532000001697120.6003251830083654652336756047051722064102156601016.67%40392.50%01397235659.30%1060198053.54%51697253.09%187313501506486848447
_Since Last GM Reset70392202430199129703421901210986533361813012201016437920.657199349548098365465199267560470517147340565211643363811.31%2523486.51%41397235659.30%1060198053.54%51697253.09%187313501506486848447
_Vs Conference432217012109484102112700110494272210100110045423500.58194164258028365465106967560470517947257439694220219.55%1682485.71%11397235659.30%1060198053.54%51697253.09%187313501506486848447

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
7092W119934954819921473405652116409
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
7039222430199129
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3421912109865
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
361813122010164
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
3363811.31%2523486.51%4
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
675604705178365465
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
1397235659.30%1060198053.54%51697253.09%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
187313501506486848447


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 - 2019-09-044Bruins4Wolf Pack1WSommaire du Match
4 - 2019-09-0516Rocket1Bruins3WSommaire du Match
10 - 2019-09-1136Bruins1Wolf Pack2LSommaire du Match
11 - 2019-09-1251Wolf Pack3Bruins4WSommaire du Match
12 - 2019-09-1359Bruins3Thunderbirds2WXXSommaire du Match
17 - 2019-09-1869Bruins2Sound Tigers3LSommaire du Match
18 - 2019-09-1988Sound Tigers2Bruins4WSommaire du Match
25 - 2019-09-26123Bruins3Thunderbirds4LXSommaire du Match
26 - 2019-09-27131Sound Tigers4Bruins1LSommaire du Match
31 - 2019-10-02139Bruins9Checkers0WSommaire du Match
32 - 2019-10-03154Bruins4Checkers0WSommaire du Match
38 - 2019-10-09184Penguins1Bruins2WSommaire du Match
39 - 2019-10-10194Bruins0Sound Tigers1LSommaire du Match
40 - 2019-10-11206Penguins2Bruins1LSommaire du Match
45 - 2019-10-16227Phantoms0Bruins1WSommaire du Match
46 - 2019-10-17245Americans2Bruins3WSommaire du Match
50 - 2019-10-21257Bruins4Wolf Pack2WSommaire du Match
53 - 2019-10-24281Bruins3Phantoms1WSommaire du Match
54 - 2019-10-25292Bruins1Penguins3LSommaire du Match
59 - 2019-10-30311Checkers0Bruins8WSommaire du Match
60 - 2019-10-31322Bruins3Sound Tigers1WSommaire du Match
61 - 2019-11-01332Checkers0Bruins4WSommaire du Match
64 - 2019-11-04341Bruins8Marlies1WSommaire du Match
66 - 2019-11-06353Bruins0Americans1LSommaire du Match
67 - 2019-11-07365Bruins1Senators4LSommaire du Match
71 - 2019-11-11383Bruins3Comets2WXXSommaire du Match
73 - 2019-11-13393Sound Tigers1Bruins0LSommaire du Match
74 - 2019-11-14408Bears3Bruins2LSommaire du Match
78 - 2019-11-18424Bruins6Wolf Pack2WSommaire du Match
80 - 2019-11-20438Bruins0Devils1LSommaire du Match
81 - 2019-11-21459Bruins4Thunderbirds2WSommaire du Match
87 - 2019-11-27478Bruins2Phantoms1WXSommaire du Match
88 - 2019-11-28488Bruins3Bears2WSommaire du Match
89 - 2019-11-29501Bruins1Bears5LSommaire du Match
94 - 2019-12-04520Phantoms1Bruins2WSommaire du Match
95 - 2019-12-05537Bruins5Thunderbirds3WSommaire du Match
96 - 2019-12-06546Wolf Pack3Bruins1LSommaire du Match
101 - 2019-12-11565Wolf Pack4Bruins5WXXSommaire du Match
102 - 2019-12-12581Bruins1Thunderbirds2LSommaire du Match
103 - 2019-12-13588Thunderbirds1Bruins2WSommaire du Match
108 - 2019-12-18607Thunderbirds3Bruins2LXSommaire du Match
109 - 2019-12-19620Bruins0Sound Tigers1LXSommaire du Match
110 - 2019-12-20634Wolf Pack4Bruins0LSommaire du Match
115 - 2019-12-25658Checkers2Bruins3WSommaire du Match
116 - 2019-12-26678Thunderbirds1Bruins2WXSommaire du Match
122 - 2020-01-01684Bruins6Checkers0WSommaire du Match
123 - 2020-01-02699Bruins5Checkers0WSommaire du Match
129 - 2020-01-08724Sound Tigers1Bruins2WSommaire du Match
130 - 2020-01-09736Bruins4Sound Tigers1WSommaire du Match
131 - 2020-01-10752Crunch2Bruins1LSommaire du Match
136 - 2020-01-15773Marlies3Bruins8WSommaire du Match
137 - 2020-01-16786Checkers1Bruins8WSommaire du Match
138 - 2020-01-17796Thunderbirds4Bruins2LSommaire du Match
143 - 2020-01-22821Sound Tigers0Bruins1WSommaire du Match
144 - 2020-01-23830Bruins1Wolf Pack2LSommaire du Match
145 - 2020-01-24842Wolf Pack2Bruins6WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
150 - 2020-01-29861Penguins4Bruins3LXSommaire du Match
151 - 2020-01-30874Bruins4Thunderbirds1WSommaire du Match
152 - 2020-01-31882Thunderbirds5Bruins2LSommaire du Match
157 - 2020-02-05901Bears1Bruins4WSommaire du Match
158 - 2020-02-06912Bears2Bruins3WSommaire du Match
159 - 2020-02-07925Thunderbirds0Bruins2WSommaire du Match
164 - 2020-02-12949Bruins1Phantoms3LSommaire du Match
165 - 2020-02-13962Bruins2Penguins1WSommaire du Match
169 - 2020-02-17980Bruins1Rocket4LSommaire du Match
171 - 2020-02-19986Senators1Bruins3WSommaire du Match
172 - 2020-02-201000Devils1Bruins3WSommaire du Match
176 - 2020-02-241020Bruins3Penguins1WSommaire du Match
178 - 2020-02-261027Bruins0Crunch2LSommaire du Match
179 - 2020-02-271040Bruins3Bears2WSommaire du Match
185 - 2020-03-041075Sound Tigers-Bruins-
186 - 2020-03-051087Bruins-Sound Tigers-
187 - 2020-03-061101Comets-Bruins-
192 - 2020-03-111119Phantoms-Bruins-
193 - 2020-03-121135Bruins-Thunderbirds-
194 - 2020-03-131143Thunderbirds-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
4 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
201,399$ 107,110$ 21,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 107,063$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 11 1,068$ 11,748$




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
147039220243019912970342190121098653336181301220101643792199349548098365465199267560470517147340565211643363811.31%2523486.51%41397235659.30%1060198053.54%51697253.09%187313501506486848447
Total Saison Régulière7039220243019912970342190121098653336181301220101643792199349548098365465199267560470517147340565211643363811.31%2523486.51%41397235659.30%1060198053.54%51697253.09%187313501506486848447