Marlies

GP: 44 | W: 4 | L: 39 | OTL: 1 | P: 9
GF: 76 | GA: 251 | PP%: 8.99% | PK%: 75.00%
DG: Sebastien Cloutier | Morale : 27 | Moyenne d'Équipe : 64
Prochain matchs #686 vs Rocket
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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
1John McCarthyX100.006236905776939056635654565582795261610
2Stefan MatteauX100.007142745584908554585352575369657661590
3Dryden HuntX100.006938925873807456525754535567645261580
4Sean MaloneX100.005935945674837755595552545167646161580
5Tom SestitoX100.008047585395736952545151595280725361580
6David Pope (R)X100.006237895378797352565153545269656061560
7Seth HelgesonX100.007644695491949553305551594977695645640
8Cameron SchillingX100.005636926077827059306054594679714458620
9Olli Juolevi (R)X100.006035946177797160306651584761638459610
10Keaton ThompsonX100.005639825571908554305351524567645661590
Rayé
1Matt HendricksXX100.008459735977645058756157755688782511620
MOYENNE D'ÉQUIPE100.00674182567982765549565358517369565560
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
1Jack Campbell100.00818684808079818079818073777461770
2Scott Darling100.00797371957877797877797879854252770
Rayé
1Chad Johnson100.00787472837776787776787782873520750
2Troy Grosenick100.00778078747675777675777678844320740
MOYENNE D'ÉQUIPE100.0079787683787779787779787883493876
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Dan Bylsma71707174726777USA484100,000$


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


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du Joueur Nom de l'ÉquipePOS Âge Date de Naissance Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat 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
Cameron SchillingMarlies (Tor)D301988-10-07No182 Lbs6 ft2NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Chad JohnsonMarlies (Tor)G331986-06-10No197 Lbs6 ft3NoNoNo2Pro & Farm1,000,000$0$0$No1,000,000$Lien
David PopeMarlies (Tor)LW241994-09-27Yes187 Lbs6 ft2NoNoNo4Pro & Farm300,000$0$0$No300,000$300,000$300,000$Lien
Dryden HuntMarlies (Tor)LW231995-11-24No191 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Jack CampbellMarlies (Tor)G271992-01-09No197 Lbs6 ft2NoNoNo3Pro & Farm1,397,349$0$0$No1,397,349$1,397,349$Lien
John McCarthyMarlies (Tor)LW321986-08-09No195 Lbs6 ft1NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Keaton ThompsonMarlies (Tor)D231995-09-14No182 Lbs6 ft0NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Matt HendricksMarlies (Tor)C/LW381981-06-17No211 Lbs6 ft0NoNoNo1Pro & Farm500,000$0$0$NoLien
Olli JuoleviMarlies (Tor)D211998-05-05Yes182 Lbs6 ft2NoNoNo4Pro & Farm900,000$0$0$No900,000$900,000$900,000$Lien
Scott DarlingMarlies (Tor)G301988-12-22No226 Lbs6 ft5NoNoNo4Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$1,000,000$Lien
Sean MaloneMarlies (Tor)C241995-04-30No197 Lbs6 ft0NoNoNo3Pro & Farm300,000$0$0$No300,000$300,000$Lien
Seth HelgesonMarlies (Tor)D281990-10-08No221 Lbs6 ft4NoNoNo3Pro & Farm500,000$0$0$No500,000$500,000$Lien
Stefan MatteauMarlies (Tor)C251994-02-23No220 Lbs6 ft2NoNoNo2Pro & Farm300,000$0$0$No300,000$Lien
Tom SestitoMarlies (Tor)LW311987-09-28No228 Lbs6 ft5NoNoNo2Pro & Farm500,000$0$0$No500,000$Lien
Troy GrosenickMarlies (Tor)G291989-08-27No185 Lbs6 ft1NoNoNo4Pro & Farm1,000,000$0$0$No1,000,000$1,000,000$1,000,000$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1527.87200 Lbs6 ft22.73619,823$



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


Astuces sur les Filtres (Anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
LigueDomicileVisiteur
# VS Équipe GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P PCT G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT
1Americans40400000521-161010000015-430300000416-1200.000510150028272028531931733581855326651616.25%13376.92%0251100624.95%389155625.00%17971525.03%5923811589329467171
2Bruins1010000018-71010000018-70000000000000.0001230028272021131931733584612822200.00%4175.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
3Checkers4210010022193210001001192211000001110150.6252243650028272022043193173358205672413012433.33%12191.67%0251100624.95%389155625.00%17971525.03%5923811589329467171
4Comets40300010519-1430200010412-81010000017-620.25058130028272027331931733581763834561915.26%15380.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
5Crunch30300000718-1120200000411-71010000037-400.000714210028272026031931733581644420501119.09%10280.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
6Devils50500000425-2130300000214-1220200000211-900.00048120028272028731931733581896152723126.45%21766.67%0251100624.95%389155625.00%17971525.03%5923811589329467171
7Monsters60600000938-2920200000214-1240400000724-1700.000918270028272029731931733583289755943139.68%19478.95%0251100624.95%389155625.00%17971525.03%5923811589329467171
8Moose21100000853000000000002110000085320.50081624002827202903193173358861813431119.09%4250.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
9Penguins1010000018-71010000018-70000000000000.00012300282720215319317335856111218300.00%60100.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
10Phantoms1010000005-51010000005-50000000000000.000000002827202243193173358364412300.00%110.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
11Rocket50500000529-2420200000210-830300000319-1600.000510150028272029431931733582226360611800.00%19573.68%0251100624.95%389155625.00%17971525.03%5923811589329467171
12Senators70700000748-4120200000213-1150500000535-3000.0007132000282720212631931733583331066410719315.79%321165.63%0251100624.95%389155625.00%17971525.03%5923811589329467171
Total443390011076251-175211180011032117-85232210000044134-9090.1027614822400282720297531931733582081589380738178168.99%1604075.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
14Wolf Pack1010000028-61010000028-60000000000000.00024600282720293193173358551588200.00%40100.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
_Since Last GM Reset443390011076251-175211180011032117-85232210000044134-9090.1027614822400282720297531931733582081589380738178168.99%1604075.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
_Vs Conference17213001103788-51815001101836-18918000001952-3370.206377110800282720245631931733587882211443126569.23%591279.66%0251100624.95%389155625.00%17971525.03%5923811589329467171
_Vs Division20900000853003000000002060000085300.00081624002827202903193173358861813431119.09%4250.00%0251100624.95%389155625.00%17971525.03%5923811589329467171

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
449L376148224975208158938073800
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
44339011076251
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
21118011032117
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
23221000044134
Derniers 10 Matchs
WLOTWOTL SOWSOL
270010
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
178168.99%1604075.00%0
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
31931733582827202
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
251100624.95%389155625.00%17971525.03%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
5923811589329467171


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 - 2019-09-041Marlies1Comets7LSommaire du Match
4 - 2019-09-0517Marlies0Devils6LSommaire du Match
6 - 2019-09-0727Monsters7Marlies2LSommaire du Match
11 - 2019-09-1245Comets3Marlies0LSommaire du Match
12 - 2019-09-1360Comets7Marlies1LSommaire du Match
17 - 2019-09-1874Marlies1Americans4LSommaire du Match
18 - 2019-09-1983Wolf Pack8Marlies2LSommaire du Match
21 - 2019-09-22100Rocket6Marlies1LSommaire du Match
24 - 2019-09-25107Crunch5Marlies0LSommaire du Match
31 - 2019-10-02141Marlies1Monsters3LSommaire du Match
38 - 2019-10-09183Marlies2Senators7LSommaire du Match
39 - 2019-10-10196Marlies0Senators4LSommaire du Match
42 - 2019-10-13212Marlies1Rocket5LSommaire du Match
45 - 2019-10-16225Marlies1Senators8LSommaire du Match
46 - 2019-10-17240Devils7Marlies1LSommaire du Match
47 - 2019-10-18250Devils5Marlies0LSommaire du Match
52 - 2019-10-23266Marlies2Monsters7LSommaire du Match
54 - 2019-10-25293Monsters7Marlies0LSommaire du Match
57 - 2019-10-28301Marlies2Monsters6LSommaire du Match
60 - 2019-10-31320Penguins8Marlies1LSommaire du Match
61 - 2019-11-01334Phantoms5Marlies0LSommaire du Match
64 - 2019-11-04341Bruins8Marlies1LSommaire du Match
67 - 2019-11-07363Rocket4Marlies1LSommaire du Match
68 - 2019-11-08378Senators5Marlies1LSommaire du Match
71 - 2019-11-11384Crunch6Marlies4LSommaire du Match
73 - 2019-11-13397Marlies3Moose4LSommaire du Match
74 - 2019-11-14405Marlies5Moose1WSommaire du Match
78 - 2019-11-18425Devils2Marlies1LSommaire du Match
80 - 2019-11-20441Marlies1Rocket6LSommaire du Match
81 - 2019-11-21450Marlies1Rocket8LSommaire du Match
85 - 2019-11-25464Senators8Marlies1LSommaire du Match
87 - 2019-11-27481Marlies1Americans5LSommaire du Match
90 - 2019-11-30504Checkers6Marlies5LXSommaire du Match
94 - 2019-12-04521Marlies2Devils5LSommaire du Match
95 - 2019-12-05535Marlies3Crunch7LSommaire du Match
96 - 2019-12-06548Checkers3Marlies6WSommaire du Match
99 - 2019-12-09552Comets2Marlies3WXXSommaire du Match
101 - 2019-12-11568Marlies2Americans7LSommaire du Match
102 - 2019-12-12574Americans5Marlies1LSommaire du Match
109 - 2019-12-19618Marlies5Checkers6LSommaire du Match
110 - 2019-12-20631Marlies6Checkers4WSommaire du Match
113 - 2019-12-23647Marlies2Monsters8LSommaire du Match
115 - 2019-12-25656Marlies1Senators9LSommaire du Match
116 - 2019-12-26674Marlies1Senators7LSommaire du Match
122 - 2020-01-01686Rocket-Marlies-
123 - 2020-01-02697Rocket-Marlies-
126 - 2020-01-05714Senators-Marlies-
130 - 2020-01-09735Thunderbirds-Marlies-
131 - 2020-01-10753Senators-Marlies-
134 - 2020-01-13763Marlies-Wolf Pack-
136 - 2020-01-15773Marlies-Bruins-
137 - 2020-01-16788Marlies-Thunderbirds-
139 - 2020-01-18805Crunch-Marlies-
141 - 2020-01-20808Moose-Marlies-
143 - 2020-01-22817Marlies-Crunch-
144 - 2020-01-23832Marlies-Crunch-
148 - 2020-01-27850Moose-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
151 - 2020-01-30868Monsters-Marlies-
155 - 2020-02-03893Marlies-Rocket-
157 - 2020-02-05899Marlies-Rocket-
159 - 2020-02-07927Sound Tigers-Marlies-
160 - 2020-02-08931Senators-Marlies-
164 - 2020-02-12945Marlies-Bears-
165 - 2020-02-13963Marlies-Phantoms-
166 - 2020-02-14968Marlies-Penguins-
169 - 2020-02-17977Marlies-Sound Tigers-
172 - 2020-02-20994Americans-Marlies-
173 - 2020-02-211011Americans-Marlies-
178 - 2020-02-261029Marlies-Comets-
179 - 2020-02-271044Rocket-Marlies-
184 - 2020-03-031072Bears-Marlies-
185 - 2020-03-041074Marlies-Comets-
186 - 2020-03-051093Marlies-Devils-
190 - 2020-03-091108Marlies-Senators-
193 - 2020-03-121128Senators-Marlies-
194 - 2020-03-131145Monsters-Marlies-



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
118,207$ 92,973$ 13,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 56,807$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 75 995$ 74,625$




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
14443390011076251-175211180011032117-85232210000044134-9097614822400282720297531931733582081589380738178168.99%1604075.00%0251100624.95%389155625.00%17971525.03%5923811589329467171
Total Saison Régulière443390011076251-175211180011032117-85232210000044134-9097614822400282720297531931733582081589380738178168.99%1604075.00%0251100624.95%389155625.00%17971525.03%5923811589329467171