Bruins

GP: 30 | W: 8 | L: 20 | OTL: 2 | P: 18
GF: 109 | GA: 180 | PP%: 32.56% | PK%: 46.21%
DG: Marc Andre Marinier | Morale : 42 | Moyenne d'Équipe : 66
Prochain matchs #384 vs Rampages
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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
1Timo MeierXX100.007243797976829668745472647354528658680
2Jujhar KhairaX100.007843757184808470755263707253546658670
3Daniel SprongX100.006142747970739985515560606651517449660
4Tomas NosekX100.006441817981778366745058737053524258660
5J.T. BrownX100.007442737158747263714853716562563649650
6Kalle KossilaX100.005542748463729479794756606450504258640
7Jean-Sebastien DeaX100.005346646162649962784560606150504358600
8Fredrik ClaessonX100.008443817173777968305052716454545655680
9Michal KempnyX100.006841867469776874305055746554523658680
Rayé
MOYENNE D'ÉQUIPE100.00684376747175867162505967675352535666
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien CON SK DU EN SZ AG RB SC HS RT PH PS EX LD PO MO OV TA SP
1Michael Hutchinson100.00756691837579757676757258675458730
Rayé
MOYENNE D'ÉQUIPE100.0075669183757975767675725867545873
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Peter DeBoer86878587836672CAN4921,200,000$


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Joueur Nom de l'ÉquipePOS GP G A P +/- PIM PIM5 HIT HTT SHT OSB OSM SHT% SB MP AMG PPG PPA PPP PPS PPM PKG PKA PKP PKS PKM GW GT FO% FOT GA TA EG HT P/20 PSG PSS FW FL FT S1 S2 S3
1J.T. BrownBruins (BOS)RW30101020-4120252013547977.41%1442314.1310111000110070.59%172417000.9411000632
2Daniel SprongBruins (BOS)RW3041216-424011138628584.65%82809.3600000000000033.33%15225001.1401000222
Stats d'équipe Total ou en Moyenne60142236-83603633221751556.33%2270411.7410111000110053.13%324622001.0212000854
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du Gardien Nom de l'ÉquipeGP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA ST BG S1 S2 S3
Stats d'équipe Total ou en Moyenne0.0000.0000.000


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 Link
Daniel SprongBruins (BOS)RW201997-03-17No180 Lbs6 ft0NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$No750,000$Lien
Fredrik ClaessonBruins (BOS)D241992-11-24No200 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
J.T. BrownBruins (BOS)RW271990-07-02No169 Lbs5 ft10NoNoNo2Avec RestrictionPro & Farm750,000$0$0$No750,000$Lien
Jean-Sebastien DeaBruins (BOS)C231994-02-08No175 Lbs5 ft11NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Jujhar KhairaBruins (BOS)LW231994-08-13No214 Lbs6 ft4NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Kalle KossilaBruins (BOS)C241993-04-14No185 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Michael HutchinsonBruins (BOS)G271990-03-02No202 Lbs6 ft3NoNoNo1Avec RestrictionPro & Farm1,300,000$0$0$NoLien
Michal KempnyBruins (BOS)D271990-09-08No194 Lbs6 ft0NoNoNo4Avec RestrictionPro & Farm2,500,000$0$0$No2,500,000$2,500,000$2,500,000$Lien
Timo MeierBruins (BOS)LW/RW201996-10-08No215 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm894,166$0$0$NoLien
Tomas NosekBruins (BOS)LW251992-09-01No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1024.00194 Lbs6 ft11.50994,417$



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


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Admirals1000010034-11000010034-10000000000010.5003580017454632821130028794314894125.00%4175.00%018853735.01%20951740.43%22161535.93%634388688285483218
2Barracuda211000006601010000024-21100000042220.5006121800174546355211300287937781711218.18%4250.00%018853735.01%20951740.43%22161535.93%634388688285483218
3Blacknight11000000431000000000001100000043121.000461000174546318211300287922812133133.33%6183.33%118853735.01%20951740.43%22161535.93%634388688285483218
4Condors1010000018-71010000018-70000000000000.00012300174546332211300287933111218300.00%6433.33%118853735.01%20951740.43%22161535.93%634388688285483218
5Crunch211000001011-1110000006421010000047-320.500101929001745463522113002879361820277457.14%10640.00%018853735.01%20951740.43%22161535.93%634388688285483218
6Devils20200000819-110000000000020200000819-1100.00081523001745463522113002879913330278337.50%151220.00%118853735.01%20951740.43%22161535.93%634388688285483218
7Icedogs11000000321110000003210000000000021.00036900174546315211300287924141211000.00%6266.67%018853735.01%20951740.43%22161535.93%634388688285483218
8Marlies303000001019-920200000714-71010000035-200.000102030001745463104211300287912229253716531.25%10460.00%018853735.01%20951740.43%22161535.93%634388688285483218
9Monsters1010000045-1000000000001010000045-100.000481200174546331211300287920510124125.00%4175.00%018853735.01%20951740.43%22161535.93%634388688285483218
10Penguins30300000624-1820200000415-111010000029-700.0006121800174546377211300287911141303813323.08%151126.67%018853735.01%20951740.43%22161535.93%634388688285483218
11Rampages1010000029-71010000029-70000000000000.00024600174546325211300287944121675120.00%8362.50%018853735.01%20951740.43%22161535.93%634388688285483218
12Reigh1010000012-1000000000001010000012-100.00012300174546319211300287928610132150.00%5180.00%018853735.01%20951740.43%22161535.93%634388688285483218
13Rocket531010002419543001000191091010000059-480.800244569001745463127211300287913352306820735.00%15286.67%018853735.01%20951740.43%22161535.93%634388688285483218
14Senateurs20200000314-111010000018-71010000026-400.0003690017454634921130028797824283412216.67%14935.71%018853735.01%20951740.43%22161535.93%634388688285483218
15Sound Tigers201000011317-400000000000201000011317-410.2501326390017454635921130028797436242310660.00%13127.69%018853735.01%20951740.43%22161535.93%634388688285483218
16Thunderbird202000001118-710100000710-31010000048-400.0001120310017454635921130028799338202011545.45%10730.00%118853735.01%20951740.43%22161535.93%634388688285483218
Total3072001101109180-711659011005588-3314211000015492-38180.30010920831700174546380221130028799893482953741294232.56%1457846.21%418853735.01%20951740.43%22161535.93%634388688285483218
_Since Last GM Reset3072001101109180-711659011005588-3314211000015492-38180.30010920831700174546380221130028799893482953741294232.56%1457846.21%418853735.01%20951740.43%22161535.93%634388688285483218
_Vs Conference224160100189146-571146010004461-1711010000014585-40110.2508917126000174546361021130028797582762172861013635.64%1066439.62%218853735.01%20951740.43%22161535.93%634388688285483218
_Vs Division1449010005881-23944010004046-6505000001835-17100.357581101680017454633912113002879462161123186662334.85%592852.54%118853735.01%20951740.43%22161535.93%634388688285483218

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
3018W110920831780298934829537400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
307201101109180
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
165911005588
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1421100015492
Derniers 10 Matchs
WLOTWOTL SOWSOL
440101
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
1294232.56%1457846.21%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
21130028791745463
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
18853735.01%20951740.43%22161535.93%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
634388688285483218


Derniers Match Joués
Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
JourMatch Équipe Visiteuse Score Équipe Locale Score ST OT SO RI Lien
3 - 2018-10-119Rocket1Bruins5WSommaire du Match
6 - 2018-10-1421Bruins4Crunch7LSommaire du Match
11 - 2018-10-1938Marlies6Bruins5LSommaire du Match
16 - 2018-10-2453Crunch4Bruins6WSommaire du Match
18 - 2018-10-2657Bruins4Thunderbird8LSommaire du Match
20 - 2018-10-2869Bruins5Rocket9LSommaire du Match
22 - 2018-10-3079Rocket3Bruins4WXSommaire du Match
24 - 2018-11-0190Bruins3Marlies5LSommaire du Match
27 - 2018-11-04107Thunderbird10Bruins7LSommaire du Match
30 - 2018-11-07123Bruins4Monsters5LSommaire du Match
32 - 2018-11-09132Senateurs8Bruins1LSommaire du Match
34 - 2018-11-11145Bruins6Sound Tigers9LSommaire du Match
36 - 2018-11-13152Bruins2Devils9LSommaire du Match
37 - 2018-11-14158Bruins2Senateurs6LSommaire du Match
39 - 2018-11-16166Condors8Bruins1LSommaire du Match
44 - 2018-11-21185Marlies8Bruins2LSommaire du Match
48 - 2018-11-25202Rampages9Bruins2LSommaire du Match
50 - 2018-11-27211Bruins4Blacknight3WSommaire du Match
54 - 2018-12-01226Bruins2Penguins9LSommaire du Match
56 - 2018-12-03231Penguins8Bruins2LSommaire du Match
60 - 2018-12-07242Bruins7Sound Tigers8LXXSommaire du Match
62 - 2018-12-09254Barracuda4Bruins2LSommaire du Match
68 - 2018-12-15272Bruins1Reigh2LSommaire du Match
69 - 2018-12-16280Penguins7Bruins2LSommaire du Match
73 - 2018-12-20297Rocket2Bruins5WSommaire du Match
77 - 2018-12-24317Admirals4Bruins3LXSommaire du Match
80 - 2018-12-27329Bruins4Barracuda2WSommaire du Match
82 - 2018-12-29341Icedogs2Bruins3WSommaire du Match
87 - 2019-01-03360Bruins6Devils10LSommaire du Match
88 - 2019-01-04369Rocket4Bruins5WSommaire du Match
91 - 2019-01-07384Bruins-Rampages-
94 - 2019-01-10393Crunch-Bruins-
97 - 2019-01-13407Bruins-Penguins-
99 - 2019-01-15415Gulls-Bruins-
103 - 2019-01-19433Bruins-Crunch-
105 - 2019-01-21438Stars-Bruins-
107 - 2019-01-23452Bruins-Phantoms-
109 - 2019-01-25459Bruins-Thunderbird-
111 - 2019-01-27468Phantoms-Bruins-
116 - 2019-02-01488Condors-Bruins-
119 - 2019-02-04500Bruins-Rocket-
121 - 2019-02-06510Moose-Bruins-
124 - 2019-02-09515Bruins-Monsters-
128 - 2019-02-13530Bruins-Heat-
130 - 2019-02-15540Thunderbird-Bruins-
133 - 2019-02-18558Bruins-Gulls-
134 - 2019-02-19564Blacknight-Bruins-
138 - 2019-02-23584Wolves-Bruins-
140 - 2019-02-25590Bruins-Rampages-
143 - 2019-02-28601Bruins-Crunch-
145 - 2019-03-02607Bruins-Admirals-
146 - 2019-03-03615Reigh-Bruins-
149 - 2019-03-06629Bruins-Thunderbird-
150 - 2019-03-07639Monsters-Bruins-
154 - 2019-03-11657Phantoms-Bruins-
156 - 2019-03-13667Bruins-Phantoms-
161 - 2019-03-18684Devils-Bruins-
164 - 2019-03-21700Bruins-Marlies-
165 - 2019-03-22707Bruins-Moose-
166 - 2019-03-23711Devils-Bruins-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
171 - 2019-03-28730Senateurs-Bruins-
175 - 2019-04-01743Bruins-Icedogs-
178 - 2019-04-04755Thunderbird-Bruins-
180 - 2019-04-06758Bruins-Rocket-
184 - 2019-04-10777Bruins-Bears-
186 - 2019-04-12783Senateurs-Bruins-
187 - 2019-04-13793Bruins-Marlies-
191 - 2019-04-17808Sound Tigers-Bruins-
193 - 2019-04-19816Bruins-Wolves-
196 - 2019-04-22828Marlies-Bruins-
202 - 2019-04-28850Crunch-Bruins-
206 - 2019-05-02867Bruins-Bears-
207 - 2019-05-03874Monsters-Bruins-
213 - 2019-05-09893Sound Tigers-Bruins-
217 - 2019-05-13910Bruins-Senateurs-
218 - 2019-05-14915Bruins-Stars-
219 - 2019-05-15923Bears-Bruins-
220 - 2019-05-16929Bruins-Senateurs-
225 - 2019-05-21947Heat-Bruins-
231 - 2019-05-27963Bruins-Stars-
232 - 2019-05-28967Bruins-Condors-
234 - 2019-05-30977Bears-Bruins-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
25 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
822,566$ 994,417$ 994,417$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 366,862$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 147 9,259$ 1,361,073$




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
23072001101109180-711659011005588-3314211000015492-381810920831700174546380221130028799893482953741294232.56%1457846.21%418853735.01%20951740.43%22161535.93%634388688285483218
Total Saison Régulière3072001101109180-711659011005588-3314211000015492-381810920831700174546380221130028799893482953741294232.56%1457846.21%418853735.01%20951740.43%22161535.93%634388688285483218