Connexion

Bruins
GP: 82 | W: 62 | L: 19 | OTL: 1 | P: 125
GF: 322 | GA: 211 | PP%: 20.09% | PK%: 85.45%
DG: Patrick Doyon | Morale : 50 | Moyenne d’équipe : 56
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Centre de jeu
Bruins
62-19-1, 125pts
4
FINAL
3 Chiefs
45-32-5, 95pts
Team Stats
L1StreakL3
32-9-0Home Record25-14-2
30-10-1Away Record20-18-3
5-4-1Last 10 Games6-4-0
3.93Goals Per Game3.41
2.57Goals Against Per Game3.18
20.09%Power Play Percentage22.26%
85.45%Penalty Kill Percentage80.71%
Caroline
23-48-11, 57pts
5
FINAL
1 Bruins
62-19-1, 125pts
Team Stats
W3StreakL1
17-19-5Home Record32-9-0
6-29-6Away Record30-10-1
5-3-2Last 10 Games5-4-1
3.44Goals Per Game3.93
4.65Goals Against Per Game2.57
24.23%Power Play Percentage20.09%
71.37%Penalty Kill Percentage85.45%
Meneurs d'équipe
Buts
Brett Kulak
0
Passes
Brett Kulak
6
Points
Brett Kulak
6
Plus/Moins
Brett Kulak
0
Victoires
Callum Booth
60
Pourcentage d’arrêts
Cayden Primeau
0.932

Statistiques d’équipe
Buts pour
322
3.93 GFG
Tirs pour
3414
41.63 Avg
Pourcentage en avantage numérique
20.1%
47 GF
Début de zone offensive
42.2%
Buts contre
211
2.57 GAA
Tirs contre
3004
36.63 Avg
Pourcentage en désavantage numérique
85.5%
40 GA
Début de la zone défensive
40.1%
Information d’équipe

Directeur généralPatrick Doyon
DivisionAtlantique
ConférenceEst
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,896
Billets de saison300


Information formation

Équipe Pro28
Équipe Mineure20
Limite contact 48 / 50
Espoirs17


Historique d'équipe

Saison actuelle62-19-1 (125PTS)
Historique62-19-3 (0.738%)
Apparitions séries éliminatoires
Historique séries éliminatoires (W-L)-


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 moyen
1Connor DewarXX100.00797296656573676987647269624444050630213825,834$
2Matthew Boldy (R)XX100.00807395627355517050706769644444050610193880,833$
3Ross ColtonXX100.00774484657057726173608154254646050600241650,000$
4Akil Thomas (R)XX100.00726490606472756379596363604444050590204795,000$
5Sam AnasX100.00675596665565666580705661534444050590271792,500$
6Nathan WalkerXX100.008344916465655658385064652545460505702631,000,000$
7Sampo Ranta (R)XX100.00837699627653525750506067574444050570204925,000$
8Zach Gallant (R)X100.00585659677169885458455455585454050560213525,000$
9Luke Henman (R)X100.00484182716163725858545255555051050560204791,667$
10Jonathan AngX100.00646184596169735470535059484444050550221742,500$
11Nathan BeaulieuX100.008145778075705858254347782567680506502721,200,000$
12Josh BrookX100.00787879697174715728544566394444050610213795,000$
13Jacob MacDonaldX100.00774491677365696025584866755555050610271800,000$
14Nicolas MelocheX100.00807690687661645025463964374444050580232865,000$
15Paul LaDueX100.00627335727357585625455158485051050560282968,000$
Rayé
1Morgan KlimchukX100.00716985656858585549505563554444050550251925,000$
2Tyler Sheehy (R)X100.00786999546956575265544663444444050530243525,000$
3Ben ThomsonX100.007277615277555751504057605444440505202721,000,000$
4Matej Pekar (R)XX100.00626947656959625063494555434444050520204764,167$
5Jack KopackaX100.00757281637249504750454460424444050510221742,500$
6Henrik HaapalaXX100.00383592644644293235323153453532050410261925,000$
7Julius Nattinen (R)X100.00374545456634343745373745413230050400232866,000$
8Nelson Nogier (R)X100.00727272657255584725374159394444050540241725,000$
9Marc Del Gaizo (R)X100.00756599616546445425543962374444050540203850,833$
MOYENNE D’ÉQUIPE100.0070618064685960554951526147464605056
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
1Callum Booth (R)100.0065435477706372747171304444050640
2Cayden Primeau100.0061637880586566696666334844050630
Rayé
1Alex D'Orio (R)100.0062546880626068716465304444050620
2Peyton Jones (R)100.0046516485434550534647304444050510
MOYENNE D’ÉQUIPE100.005953668158586467626231454405060
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur Nom de l’équipePOSGP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1Connor DewarBruins (Bos)C/LW81435497353551322704411273519.75%30184922.8371320581882131325710360.47%250700011.0525001856
2Matthew BoldyBruins (Bos)LW/RW823658943740101081404031082888.93%30171420.91810186618311271827147.21%19700021.1024101664
3Ross ColtonBruins (Bos)C/LW82414384463001361933319223112.39%17159919.5010616531791014877554.82%209400011.05120007103
4Sampo RantaBruins (Bos)LW/RW8228447249335901082576919010.89%27139216.99381124990000486141.74%11500001.0300010154
5Akil ThomasBruins (Bos)C/RW822643693540073133289921999.00%24149118.182810421580110244154.72%30700100.9311000263
6Sam AnasBruins (Bos)C82214768218054195250781758.40%18129615.820114131012572258.00%135700001.0500000215
7Nathan WalkerBruins (Bos)LW/RW82303363433601491172896819710.38%25138816.9315618880001424234.85%13200000.9100000534
8Josh BrookBruins (Bos)D709465529102301858211534867.83%117161123.0231114571700111185110.00%100000.6800123322
9Jacob MacDonaldBruins (Bos)D801338514930011284123397610.57%128185923.24358411800001217310.00%000000.5511000132
10Paul LaDueBruins (Bos)D707182527695195328332488.43%83128918.42213201010001121010.00%000000.3900010112
11Nicolas MelocheBruins (Bos)D82420245010945147669729614.12%121171220.88213311760113199100.00%000000.2800414013
12Zach GallantBruins (Bos)C821212242042012570118358310.17%29132116.1100008000024054.84%21700000.3611000000
13Luke HenmanBruins (Bos)C6441519-12019758228504.88%3591514.31011110000061054.95%9100000.4200000000
14Nathan BeaulieuBruins (Bos)D21215171014051414621524.35%3649523.580222346011138000.00%000000.6900000201
15Jonathan AngBruins (Bos)C704812660262931143312.90%456609.440113120000260051.02%4900000.3600000001
16Morgan KlimchukBruins (Bos)LW453582180492129101210.34%163557.9000000000000036.36%1100000.4500000002
17Brett KulakBostonD8066020910121070.00%1319724.72011419000028000.00%000000.6100000000
18Nelson NogierBruins (Bos)D202359195464163912.50%3740120.08101735000051000.00%000000.2500001000
19Jack KopackaBruins (Bos)LW181230004241225.00%0442.47112240110120057.14%2100001.3500000000
20Matej PekarBruins (Bos)C/LW31123-9155301011679.09%72076.69000030000141035.29%1700000.2900100020
Statistiques d’équipe totales ou en moyenne123428751279945865011017401682302789621579.48%8382180317.67437511845416795712341607511856.52%711600140.738147510384542
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
1Callum BoothBruins (Bos)80601810.9312.53474512820028850120.700208021443
2Cayden PrimeauBruins (Bos)42100.9322.421980081170000.0000280000
Statistiques d’équipe totales ou en moyenne84621910.9312.53494312820830020120.7002082821443


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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Link
Akil ThomasBruins (Bos)C/RW202000-01-01Yes171 Lbs6 ft0NoNoNo4Pro & Farm795,000$79,500$0$No795,000$795,000$795,000$Lien
Alex D'OrioBruins (Bos)G211999-04-27Yes209 Lbs6 ft2YesNoNo1Pro & Farm850,000$85,000$0$NoLien
Ben ThomsonBruins (Bos)LW271993-01-15No205 Lbs6 ft3NoNoNo2Pro & Farm1,000,000$100,000$0$No1,000,000$Lien
Callum BoothBruins (Bos)G231997-05-20Yes184 Lbs6 ft4YesNoNo1Pro & Farm560,000$56,000$0$NoLien
Cayden PrimeauBruins (Bos)G211999-08-11No209 Lbs6 ft2NoNoNo2Pro & Farm880,833$88,083$0$No880,833$Lien
Connor DewarBruins (Bos)C/LW211999-06-26No182 Lbs5 ft10NoNoNo3Pro & Farm825,834$82,583$0$No825,834$825,834$Lien
Henrik HaapalaBruins (Bos)LW/RW261994-02-28No165 Lbs5 ft9NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Jack KopackaBruins (Bos)LW221998-03-05No191 Lbs6 ft2NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Jacob MacDonaldBruins (Bos)D271993-02-26No204 Lbs6 ft0NoNoNo1Pro & Farm800,000$80,000$0$NoLien
Jonathan AngBruins (Bos)C221998-01-31No165 Lbs5 ft11NoNoNo1Pro & Farm742,500$74,250$0$NoLien
Josh BrookBruins (Bos)D211999-06-17No192 Lbs6 ft1NoNoNo3Pro & Farm795,000$79,500$0$No795,000$795,000$Lien
Julius NattinenBruins (Bos)C231997-01-14Yes192 Lbs6 ft2NoNoNo2Pro & Farm866,000$86,600$0$No866,000$Lien
Luke HenmanBruins (Bos)C202000-04-29Yes168 Lbs6 ft0NoNoNo4Pro & Farm791,667$79,167$0$No791,667$791,667$791,667$Lien
Marc Del GaizoBruins (Bos)D201999-10-11Yes181 Lbs5 ft10NoNoNo3Pro & Farm850,833$85,083$0$No850,833$850,833$Lien
Matej PekarBruins (Bos)C/LW202000-02-10Yes185 Lbs6 ft1NoNoNo4Pro & Farm764,167$76,417$0$No764,167$764,167$764,167$Lien
Matthew BoldyBruins (Bos)LW/RW192001-04-04Yes196 Lbs6 ft2NoNoNo3Pro & Farm880,833$88,083$0$No880,833$880,833$Lien
Morgan KlimchukBruins (Bos)LW251995-03-01No185 Lbs6 ft0NoNoNo1Pro & Farm925,000$92,500$0$NoLien
Nathan BeaulieuBruins (Bos)D271992-12-05No200 Lbs6 ft2NoNoNo2Pro & Farm1,200,000$1,200,000$0$No1,200,000$Lien
Nathan WalkerBruins (Bos)LW/RW261994-02-07No186 Lbs5 ft9NoNoNo3Pro & Farm1,000,000$100,000$0$No1,000,000$1,000,000$Lien
Nelson NogierBruins (Bos)D241996-05-26Yes191 Lbs6 ft2NoNoNo1Pro & Farm725,000$72,500$0$NoLien
Nicolas MelocheBruins (Bos)D231997-07-18No204 Lbs6 ft3NoNoNo2Pro & Farm865,000$86,500$0$No865,000$Lien
Paul LaDueBruins (Bos)D281992-09-06No197 Lbs6 ft2NoNoNo2Pro & Farm968,000$96,800$0$No968,000$Lien
Peyton JonesBruins (Bos)G241996-02-13Yes209 Lbs6 ft4NoNoNo3Pro & Farm525,000$52,500$0$No525,000$525,000$Lien
Ross ColtonBruins (Bos)C/LW241996-09-11No191 Lbs6 ft0NoNoNo1Pro & Farm650,000$65,000$0$NoLien
Sam AnasBruins (Bos)C271993-06-01No157 Lbs5 ft8NoNoNo1Pro & Farm792,500$79,250$0$NoLien
Sampo RantaBruins (Bos)LW/RW202000-05-31Yes205 Lbs6 ft2NoNoNo4Pro & Farm925,000$92,500$0$No925,000$925,000$925,000$Lien
Tyler SheehyBruins (Bos)C241995-11-20Yes190 Lbs5 ft11NoNoNo3Pro & Farm525,000$52,500$0$No525,000$525,000$Lien
Zach GallantBruins (Bos)C211999-03-06Yes193 Lbs6 ft2NoNoNo3Pro & Farm525,000$52,500$0$No525,000$525,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2823.07190 Lbs6 ft12.21810,560$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew BoldyConnor DewarAkil Thomas40122
2Sampo RantaRoss ColtonNathan Walker30122
3Luke HenmanSam AnasZach Gallant20122
4Connor DewarLuke HenmanMatthew Boldy10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nathan BeaulieuJacob MacDonald40122
2Josh BrookNicolas Meloche30122
3Paul LaDueJonathan Ang20122
4Nathan BeaulieuJacob MacDonald10122
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Matthew BoldyConnor DewarAkil Thomas60122
2Sampo RantaRoss ColtonNathan Walker40122
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nathan BeaulieuJacob MacDonald60122
2Josh BrookNicolas Meloche40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Connor DewarMatthew Boldy60122
2Ross ColtonSam Anas40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nathan BeaulieuJacob MacDonald60122
2Josh BrookNicolas Meloche40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Connor Dewar60122Nathan BeaulieuJacob MacDonald60122
2Matthew Boldy40122Josh BrookNicolas Meloche40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Connor DewarMatthew Boldy60122
2Ross ColtonSam Anas40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Nathan BeaulieuJacob MacDonald60122
2Josh BrookNicolas Meloche40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew BoldyConnor DewarAkil ThomasNathan BeaulieuJacob MacDonald
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Matthew BoldyConnor DewarAkil ThomasNathan BeaulieuJacob MacDonald
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Zach Gallant, Jonathan Ang, Akil ThomasZach Gallant, Jonathan AngAkil Thomas
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Paul LaDue, Josh Brook, Nicolas MelochePaul LaDueJosh Brook, Nicolas Meloche
Tirs de pénalité
Connor Dewar, Matthew Boldy, Ross Colton, Sam Anas, Akil Thomas
Gardien
#1 : Callum Booth, #2 : Cayden Primeau


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
TotalDomicileVisiteur
# 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
1Admirals220000001046110000004041100000064241.000101727011151089311911048116711784064218314250.00%3166.67%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
2Baby Hawks22000000954110000003211100000063341.000916250011510893118710481167117840922119536350.00%70100.00%11839320457.40%1631304453.58%753133756.32%1988136618925971068552
3Bears33000000161152200000012931100000042261.0001629450011510893111221048116711784013530266814321.43%13469.23%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
4Cabaret Lady Mary Ann44000000195142200000011562200000080881.0001934530211510893111911048116711784016152409911327.27%14192.86%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
5Caroline31200000610-42110000058-31010000012-120.33361117001151089311135104811671178408529157910110.00%4325.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
6Chiefs21000010972100000105411100000043141.00091524001151089311821048116711784082231449500.00%7185.71%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
7Chill22000000624110000004221100000020241.00061117011151089311841048116711784061181247300.00%6183.33%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
8Comets220000001174110000007431100000043141.0001120310011510893117610481167117840691820368225.00%9188.89%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
9Cougars41300000915-62020000059-42110000046-220.250915240011510893111271048116711784016140328410110.00%15286.67%11839320457.40%1631304453.58%753133756.32%1988136618925971068552
10Crunch4310000015872200000010372110000055060.75015284300115108931121410481167117840119474311412433.33%90100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
11Heat21100000770110000003121010000046-220.5007132000115108931167104811671178407023649200.00%3166.67%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
12Jayhawks22000000945110000005231100000042241.000917260011510893118510481167117840712018376233.33%9277.78%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
13Las Vegas21001000963110000003121000100065141.000915240011510893119010481167117840802225515120.00%10280.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
14Manchots320000101394210000108621100000053261.000132134001151089311116104811671178401343022848225.00%11190.91%11839320457.40%1631304453.58%753133756.32%1988136618925971068552
15Marlies4220000013112211000006512110000076140.5001323360011510893111601048116711784014542537513215.38%11372.73%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
16Minnesota210000101046110000005051000001054141.00010142401115108931110210481167117840842135457114.29%9277.78%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
17Monarchs21000001660110000005411000000112-130.750612180011510893116510481167117840471316345120.00%50100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
18Monsters3210000011742110000045-11100000072540.66711182900115108931112810481167117840992623841119.09%9188.89%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
19Monsters211000007611010000034-11100000042220.500714210011510893118410481167117840591737451000.00%10190.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
20Oceanics20200000610-41010000035-21010000035-200.000612181011510893117810481167117840992626383266.67%8187.50%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
21Oil Kings22000000945110000005411100000040441.000917260111510893119310481167117840602112547228.57%6266.67%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
22Phantoms3210000013103110000004222110000098140.667132639101151089311119104811671178401163118721100.00%9277.78%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
23Rocket4120100013130211000007612010100067-140.5001325380011510893111401048116711784017359411028225.00%17476.47%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
24Senators4310000022101222000000143112110000087160.750223658001151089311175104811671178401684636996233.33%18288.89%11839320457.40%1631304453.58%753133756.32%1988136618925971068552
25Sharks22000000523110000003121100000021141.0005914001151089311711048116711784074182047600.00%10190.00%11839320457.40%1631304453.58%753133756.32%1988136618925971068552
26Sound Tigers3210000011101110000004312110000077040.6671119300011510893111221048116711784010835227212216.67%90100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
27Spiders321000009361010000012-12200000081740.667916250111510893119410481167117840983120735240.00%90100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
28Stars22000000734110000003121100000042241.000712190011510893115710481167117840752112386350.00%60100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
29Thunder4300001017892100001072522000000106481.00017294601115108931120910481167117840127474010211218.18%110100.00%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
30Wolf Pack33000000154111100000051422000000103761.00015294400115108931115010481167117840882318859111.11%8187.50%01839320457.40%1631304453.58%753133756.32%1988136618925971068552
Total8256190204132221111141299000301641046041271002011158107511250.762322573895281151089311341410481167117840300487172919462344720.09%2754085.45%51839320457.40%1631304453.58%753133756.32%1988136618925971068552
_Since Last GM Reset8256190204132221111141299000301641046041271002011158107511250.762322573895281151089311341410481167117840300487172919462344720.09%2754085.45%51839320457.40%1631304453.58%753133756.32%1988136618925971068552
_Vs Conference43319000211731076621154000208450342216500001895732670.779173307480241151089311178410481167117840156343736010111212218.18%1401887.14%31839320457.40%1631304453.58%753133756.32%1988136618925971068552
_Vs Division2874000011087038144200000603327143200001483711150.2681081902980311510893111216104811671178401054333285675711622.54%951287.37%21839320457.40%1631304453.58%753133756.32%1988136618925971068552

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82125L132257389534143004871729194628
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8256192041322211
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
412990030164104
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4127102011158107
Derniers 10 matchs
WLOTWOTL SOWSOL
540001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2344720.09%2754085.45%5
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
104811671178401151089311
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
1839320457.40%1631304453.58%753133756.32%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1988136618925971068552


Derniers matchs joués
Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe visiteuse Score Équipe locale Score ST OT SO RI Lien
2 - 2021-10-1310Bruins4Stars2WSommaire du match
4 - 2021-10-1526Bruins4Jayhawks2WSommaire du match
7 - 2021-10-1843Bruins6Las Vegas5WXSommaire du match
9 - 2021-10-2056Bruins4Monsters2WSommaire du match
11 - 2021-10-2265Spiders2Bruins1LSommaire du match
13 - 2021-10-2478Admirals0Bruins4WSommaire du match
16 - 2021-10-2798Thunder2Bruins3WXXSommaire du match
18 - 2021-10-29116Bruins5Marlies3WSommaire du match
21 - 2021-11-01133Marlies4Bruins3LSommaire du match
25 - 2021-11-05162Chiefs4Bruins5WXXSommaire du match
26 - 2021-11-06175Bruins6Wolf Pack1WSommaire du match
28 - 2021-11-08179Sharks1Bruins3WSommaire du match
32 - 2021-11-12207Senators1Bruins8WSommaire du match
34 - 2021-11-14220Manchots4Bruins5WXXSommaire du match
35 - 2021-11-15224Bruins2Rocket4LSommaire du match
38 - 2021-11-18249Bruins0Cougars3LSommaire du match
40 - 2021-11-20268Phantoms2Bruins4WSommaire du match
42 - 2021-11-22272Cabaret Lady Mary Ann3Bruins8WSommaire du match
45 - 2021-11-25294Bruins2Marlies3LSommaire du match
46 - 2021-11-26303Bears5Bruins6WSommaire du match
49 - 2021-11-29320Bruins5Spiders0WSommaire du match
51 - 2021-12-01333Crunch1Bruins6WSommaire du match
53 - 2021-12-03353Minnesota0Bruins5WSommaire du match
56 - 2021-12-06374Bruins4Rocket3WXSommaire du match
57 - 2021-12-07378Bruins6Senators3WSommaire du match
59 - 2021-12-09391Wolf Pack1Bruins5WSommaire du match
61 - 2021-12-11417Rocket3Bruins6WSommaire du match
63 - 2021-12-13424Caroline3Bruins4WSommaire du match
65 - 2021-12-15438Baby Hawks2Bruins3WSommaire du match
67 - 2021-12-17455Monsters4Bruins3LSommaire du match
69 - 2021-12-19470Bruins2Senators4LSommaire du match
71 - 2021-12-21484Bruins4Bears2WSommaire du match
72 - 2021-12-22488Bruins3Thunder2WSommaire du match
74 - 2021-12-24510Bruins3Cabaret Lady Mary Ann0WSommaire du match
77 - 2021-12-27524Monarchs4Bruins5WSommaire du match
79 - 2021-12-29538Sound Tigers3Bruins4WSommaire du match
81 - 2021-12-31556Chill2Bruins4WSommaire du match
83 - 2022-01-02571Bears4Bruins6WSommaire du match
87 - 2022-01-06582Bruins0Crunch4LSommaire du match
89 - 2022-01-08606Crunch2Bruins4WSommaire du match
91 - 2022-01-10613Bruins3Spiders1WSommaire du match
93 - 2022-01-12627Monsters2Bruins3WSommaire du match
95 - 2022-01-14641Oil Kings4Bruins5WSommaire du match
98 - 2022-01-17671Bruins2Chill0WSommaire du match
100 - 2022-01-19678Oceanics5Bruins3LSommaire du match
102 - 2022-01-21694Bruins3Sound Tigers4LSommaire du match
104 - 2022-01-23711Bruins3Phantoms5LSommaire du match
105 - 2022-01-24719Bruins7Monsters2WSommaire du match
107 - 2022-01-26727Manchots2Bruins3WSommaire du match
110 - 2022-01-29755Bruins5Manchots3WSommaire du match
112 - 2022-01-31761Las Vegas1Bruins3WSommaire du match
122 - 2022-02-10789Bruins3Oceanics5LSommaire du match
123 - 2022-02-11802Bruins5Minnesota4WXXSommaire du match
126 - 2022-02-14812Comets4Bruins7WSommaire du match
127 - 2022-02-15826Bruins6Baby Hawks3WSommaire du match
130 - 2022-02-18844Jayhawks2Bruins5WSommaire du match
131 - 2022-02-19855Bruins4Cougars3WSommaire du match
134 - 2022-02-22877Rocket3Bruins1LSommaire du match
137 - 2022-02-25895Cougars4Bruins3LSommaire du match
138 - 2022-02-26907Bruins4Wolf Pack2WSommaire du match
141 - 2022-03-01928Bruins4Oil Kings0WSommaire du match
143 - 2022-03-03945Bruins4Heat6LSommaire du match
144 - 2022-03-04956Bruins4Comets3WSommaire du match
147 - 2022-03-07968Heat1Bruins3WSommaire du match
149 - 2022-03-09984Stars1Bruins3WSommaire du match
151 - 2022-03-11999Bruins4Sound Tigers3WSommaire du match
154 - 2022-03-141019Bruins7Thunder4WSommaire du match
156 - 2022-03-161035Bruins5Cabaret Lady Mary Ann0WSommaire du match
158 - 2022-03-181054Thunder0Bruins4WSommaire du match
161 - 2022-03-211073Bruins6Phantoms3WSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
164 - 2022-03-241093Bruins5Crunch1WSommaire du match
165 - 2022-03-251101Marlies1Bruins3WSommaire du match
167 - 2022-03-271118Monsters3Bruins1LSommaire du match
169 - 2022-03-291136Bruins6Admirals4WSommaire du match
170 - 2022-03-301144Bruins1Monarchs2LXXSommaire du match
172 - 2022-04-011163Bruins2Sharks1WSommaire du match
175 - 2022-04-041176Cougars5Bruins2LSommaire du match
177 - 2022-04-061191Senators2Bruins6WSommaire du match
179 - 2022-04-081207Cabaret Lady Mary Ann2Bruins3WSommaire du match
182 - 2022-04-111232Bruins1Caroline2LSommaire du match
184 - 2022-04-131250Bruins4Chiefs3WSommaire du match
186 - 2022-04-151260Caroline5Bruins1LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance78,96939,760
Assistance PCT96.30%96.98%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2896 - 96.53% 81,959$3,360,315$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,733,315$ 3,349,566$ 3,349,566$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
17,912$ 2,733,315$ 28 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 17,912$ 0$




TotalDomicileVisiteur
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