Connexion

Marlies
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Patrick Pellegrino | Morale : 50 | Moyenne d’équipe : 57
Prochains matchs #7 vs Rocket
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Marlies
0-0-0, 0pts
2022-10-12
Rocket
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Bears
0-0-0, 0pts
2022-10-13
Marlies
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Senators
0-0-0, 0pts
2022-10-15
Marlies
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0Buts par match 0
0Buts contre par match 0
0%Pourcentage en avantage numérique0%
0%Pourcentage en désavantage numérique0%
Meneurs d'équipe

Statistiques d’équipe
Informations de l'équipe

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


Informations de l’aréna

Capacité6,000
Assistance
Billets de saison600


Informations de la formation

Équipe Pro22
Équipe Mineure18
Limite contact 40 / 50
Espoirs10


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
1David GustafssonX100.00797392787363646278576267594646050610211817,500$
2Jan Jenik (R)XX100.00849176746457736543586865254545050610213795,000$
3Brett LeasonX100.00634296707752765936585867254747050590221842,500$
4Riley Damiani (R)X100.00676278666272756278606060574444050590213803,333$
5Cole Schwindt (R)X100.00756990616966686150566264594444050580203870,000$
6Tim GettingerX100.00844699668355655746505565254444050570231770,000$
7Tanner FritzXX100.00726980566960606176595862554444050570302825,000$
8Tyler Madden (R)X100.00675791665755546176586060574444050560213925,000$
9Ryan Suzuki (R)X100.00706583776553535670505860554444050560203894,167$
10Justin AlmeidaX100.00756798596155505875495866524444050550223809,166$
11Shane Bowers (R)X100.00767089667054555265445662534444050540222925,002$
12Kody Clark (R)X100.00737176607158605150475160484444050530213808,333$
13Jason DemersX100.007845818272666759254644772476800506703324,250,000$
14Jon MerrillX100.00694389767472855825574885255859050670291950,000$
15Kevin Bahl (R)X100.00814683688868786025534878254646050650213795,000$
16Lucas JohansenX100.00746790696759615425474662444444050570231750,000$
17Xavier Bernard (R)X100.00817790697740394525353963374444050540213650,000$
Rayé
1Samuel Helenius (R)X100.00817985667936354556384663444444050500184828,333$
2Karl Henriksson (R)X100.00423599666058803950333838405454050460204870,000$
3Albin Eriksson (R)X100.00505098607750703453293244355050050450213825,000$
MOYENNE D’ÉQUIPE100.0072618868715763555149526342484805057
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 SPÂgeContratSalaire moyen
1Alexandar Georgiev100.00656060677258836565656859590506402511,525,000$
2Daniil Tarasov (R)100.0047435480484750534949304444050510222825,000$
Rayé
MOYENNE D’ÉQUIPE100.005652577460536759575749525205058
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
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 Salaire moyen 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
Albin ErikssonMarlies (Tor)LW212000-07-20Yes205 Lbs6 ft4NoNoNo3Pro & Farm825,000$825,000$82,500$82,500$No825,000$825,000$Lien
Alexandar GeorgievMarlies (Tor)G251996-02-10No178 Lbs6 ft1NoNoNo1Pro & Farm1,525,000$1,525,000$152,500$152,500$NoLien
Brett LeasonMarlies (Tor)RW221999-04-30No201 Lbs6 ft4NoNoNo1Pro & Farm842,500$842,500$84,250$84,250$NoLien
Cole SchwindtMarlies (Tor)RW202001-04-25Yes183 Lbs6 ft2NoNoNo3Pro & Farm870,000$870,000$87,000$87,000$No870,000$870,000$Lien
Daniil TarasovMarlies (Tor)G221999-03-27Yes185 Lbs6 ft5NoNoNo2Pro & Farm825,000$825,000$82,500$82,500$No825,000$Lien
David GustafssonMarlies (Tor)C212000-04-11No196 Lbs6 ft2NoNoNo1Pro & Farm817,500$817,500$81,750$81,750$NoLien
Jan JenikMarlies (Tor)LW/RW212000-09-15Yes161 Lbs6 ft1NoNoNo3Pro & Farm795,000$795,000$79,500$79,500$No795,000$795,000$Lien
Jason DemersMarlies (Tor)D331988-06-09No195 Lbs6 ft1NoNoNo2Pro & Farm3,000,000$4,250,000$425,000$425,000$No3,000,000$Lien
Jon MerrillMarlies (Tor)D291992-02-03No195 Lbs6 ft3NoNoNo1Pro & Farm950,000$950,000$95,000$95,000$NoLien
Justin AlmeidaMarlies (Tor)C221999-02-06No165 Lbs5 ft11NoNoNo3Pro & Farm809,166$809,166$80,917$80,917$No809,166$809,166$Lien
Karl HenrikssonMarlies (Tor)C202001-02-05Yes174 Lbs5 ft9NoNoNo4Pro & Farm870,000$870,000$87,000$87,000$No870,000$870,000$870,000$Lien
Kevin BahlMarlies (Tor)D212000-06-27Yes230 Lbs6 ft6NoNoNo3Pro & Farm795,000$795,000$79,500$79,500$No795,000$795,000$Lien
Kody ClarkMarlies (Tor)RW211999-10-13Yes185 Lbs6 ft3NoNoNo3Pro & Farm808,333$808,333$80,833$80,833$No808,333$808,333$Lien
Lucas JohansenMarlies (Tor)D231997-11-16No176 Lbs6 ft2NoNoNo1Pro & Farm750,000$750,000$75,000$75,000$NoLien
Riley DamianiMarlies (Tor)C212000-03-20Yes170 Lbs5 ft10NoNoNo3Pro & Farm803,333$803,333$80,333$80,333$No803,333$803,333$Lien
Ryan SuzukiMarlies (Tor)C202001-05-28Yes176 Lbs6 ft0NoNoNo3Pro & Farm894,167$894,167$89,417$89,417$No894,167$894,167$Lien
Samuel HeleniusMarlies (Tor)C182002-11-26Yes201 Lbs6 ft6NoNoNo4Pro & Farm828,333$828,333$82,833$82,833$No828,333$828,333$828,333$Lien
Shane BowersMarlies (Tor)C221999-07-30Yes186 Lbs6 ft2NoNoNo2Pro & Farm925,002$925,002$92,500$92,500$No925,002$Lien
Tanner FritzMarlies (Tor)C/RW301991-08-20No192 Lbs5 ft11NoNoNo2Pro & Farm560,000$825,000$82,500$82,500$No560,000$Lien
Tim GettingerMarlies (Tor)LW231998-04-13No218 Lbs6 ft6NoNoNo1Pro & Farm770,000$770,000$77,000$77,000$NoLien
Tyler MaddenMarlies (Tor)C211999-11-09Yes152 Lbs5 ft11NoNoNo3Pro & Farm925,000$925,000$92,500$92,500$No925,000$925,000$Lien
Xavier BernardMarlies (Tor)D212000-01-06Yes205 Lbs6 ft3NoNoNo3Pro & Farm650,000$650,000$65,000$65,000$No650,000$650,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2222.59188 Lbs6 ft22.36947,197$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jan JenikDavid GustafssonBrett Leason40122
2Tim GettingerRiley DamianiCole Schwindt30122
3Tyler MaddenKody Clark20122
4Jan JenikRyan SuzukiBrett Leason10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jason DemersJon Merrill40122
2Kevin Bahl30122
3Lucas JohansenXavier Bernard20122
4Jason DemersJon Merrill10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jan JenikDavid GustafssonBrett Leason60122
2Tim GettingerRiley DamianiCole Schwindt40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jason DemersJon Merrill60122
2Kevin Bahl40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1David GustafssonJan Jenik60122
2Riley DamianiTim Gettinger40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jason DemersJon Merrill60122
2Kevin Bahl40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1David Gustafsson60122Jason DemersJon Merrill60122
2Riley Damiani40122Kevin Bahl40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1David GustafssonJan Jenik60122
2Riley DamianiTim Gettinger40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jason DemersJon Merrill60122
2Kevin Bahl40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jan JenikDavid GustafssonBrett LeasonJason DemersJon Merrill
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jan JenikDavid GustafssonBrett LeasonJason DemersJon Merrill
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Cole Schwindt, Tim Gettinger, Tyler MaddenCole Schwindt, Tim GettingerCole Schwindt
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kevin Bahl, Lucas Johansen, Xavier BernardKevin BahlKevin Bahl, Lucas Johansen
Tirs de pénalité
Jan Jenik, David Gustafsson, Brett Leason, Riley Damiani, Cole Schwindt
Gardien
#1 : Alexandar Georgiev, #2 : Daniil Tarasov


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 matchs
WLOTWOTL SOWSOL
000000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
000000


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
6 - 2022-10-127Marlies-Rocket-
7 - 2022-10-1315Bears-Marlies-
9 - 2022-10-1530Senators-Marlies-
11 - 2022-10-1740Jayhawks-Marlies-
14 - 2022-10-2061Stars-Marlies-
16 - 2022-10-2278Marlies-Oceanics-
18 - 2022-10-2496Marlies-Las Vegas-
21 - 2022-10-27119Marlies-Sharks-
23 - 2022-10-29130Marlies-Monarchs-
24 - 2022-10-30142Marlies-Admirals-
27 - 2022-11-02159Phantoms-Marlies-
30 - 2022-11-05180Bruins-Marlies-
31 - 2022-11-06191Marlies-Caroline-
33 - 2022-11-08201Las Vegas-Marlies-
36 - 2022-11-11221Manchots-Marlies-
37 - 2022-11-12230Comets-Marlies-
40 - 2022-11-15251Marlies-Manchots-
42 - 2022-11-17264Spiders-Marlies-
44 - 2022-11-19277Crunch-Marlies-
46 - 2022-11-21295Sound Tigers-Marlies-
48 - 2022-11-23309Marlies-Spiders-
50 - 2022-11-25321Marlies-Minnesota-
51 - 2022-11-26335Marlies-Manchots-
53 - 2022-11-28348Marlies-Cougars-
55 - 2022-11-30363Sharks-Marlies-
58 - 2022-12-03385Marlies-Thunder-
61 - 2022-12-06409Marlies-Stars-
63 - 2022-12-08420Monarchs-Marlies-
65 - 2022-12-10438Heat-Marlies-
68 - 2022-12-13454Admirals-Marlies-
70 - 2022-12-15476Marlies-Wolf Pack-
72 - 2022-12-17491Marlies-Bears-
75 - 2022-12-20513Thunder-Marlies-
77 - 2022-12-22525Phantoms-Marlies-
82 - 2022-12-27553Marlies-Chiefs-
84 - 2022-12-29572Marlies-Jayhawks-
86 - 2022-12-31582Marlies-Monsters-
89 - 2023-01-03602Chiefs-Marlies-
91 - 2023-01-05615Seattle-Marlies-
93 - 2023-01-07630Cougars-Marlies-
94 - 2023-01-08643Marlies-Phantoms-
97 - 2023-01-11658Chill-Marlies-
98 - 2023-01-12666Marlies-Cougars-
100 - 2023-01-14683Marlies-Bruins-
103 - 2023-01-17706Cabaret Lady Mary Ann-Marlies-
105 - 2023-01-19723Oceanics-Marlies-
107 - 2023-01-21737Marlies-Rocket-
109 - 2023-01-23752Sound Tigers-Marlies-
111 - 2023-01-25767Wolf Pack-Marlies-
113 - 2023-01-27782Senators-Marlies-
115 - 2023-01-29800Bears-Marlies-
118 - 2023-02-01806Bruins-Marlies-
127 - 2023-02-10829Marlies-Monsters-
128 - 2023-02-11840Monsters-Marlies-
132 - 2023-02-15864Baby Hawks-Marlies-
135 - 2023-02-18888Rocket-Marlies-
136 - 2023-02-19899Marlies-Baby Hawks-
138 - 2023-02-21912Marlies-Crunch-
141 - 2023-02-24931Minnesota-Marlies-
143 - 2023-02-26952Marlies-Seattle-
146 - 2023-03-01969Marlies-Oil Kings-
147 - 2023-03-02979Marlies-Heat-
149 - 2023-03-04994Marlies-Comets-
152 - 2023-03-071015Marlies-Spiders-
156 - 2023-03-111043Oil Kings-Marlies-
158 - 2023-03-131061Crunch-Marlies-
160 - 2023-03-151077Monsters-Marlies-
162 - 2023-03-171092Caroline-Marlies-
163 - 2023-03-181102Marlies-Senators-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166 - 2023-03-211127Marlies-Sound Tigers-
168 - 2023-03-231140Marlies-Cabaret Lady Mary Ann-
170 - 2023-03-251161Marlies-Caroline-
171 - 2023-03-261167Marlies-Chill-
174 - 2023-03-291186Cabaret Lady Mary Ann-Marlies-
177 - 2023-04-011210Marlies-Senators-
178 - 2023-04-021223Cougars-Marlies-
180 - 2023-04-041230Monsters-Marlies-
182 - 2023-04-061246Marlies-Bruins-
184 - 2023-04-081263Rocket-Marlies-
186 - 2023-04-101279Marlies-Cabaret Lady Mary Ann-
187 - 2023-04-111289Marlies-Thunder-
189 - 2023-04-131304Marlies-Wolf Pack-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité40002000
Prix des billets5020
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 0 - 0.00%0$0$6000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,083,833$ 2,235,333$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,765$ 0$ 22 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 190 10,968$ 2,083,920$




Marlies Leaders statistiques (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Marlies Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Marlies Statistiques de l'Équipe de Carrière

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

Marlies Leaders statistiques (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Marlies Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA