Marlies

GP: 50 | W: 11 | L: 34 | OTL: 5 | P: 27
GF: 96 | GA: 148 | PP%: 12.36% | PK%: 86.81%
DG: Danick Lépine | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #558 vs Griffins
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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 SPÂgeContratSalaire
1Bobby RyanX100.008294747279656879566172546382846846003311,000,000$
2Brendan LeipsicXX100.00735292716553796438615763256363625000264700,000$
3Brett HowdenXXX100.00754387807264855875626481255959695000222863,333$
4Filip ChytilXXX100.005940948266688969726274612559597051002041,244,166$
5Kailer YamamotoX100.008243868354766468258888612548488145002131,124,166$
6Gabriel BourqueXX100.00894695757252715735585666416971635000292866,000$
7Dmytro Timashov (R)X100.00864588676952755925605970255757645000233836,111$
8Jeremy Bracco (R)X100.00746498606473776150714764454747605000233925,000$
9Steven FogartyXX100.00797783627781866379626067574545655000273708,750$
10Andrew Nielsen (R)X100.00757967627956604625353963375555505000233921,666$
11Ben ThomasX100.00756988656972795025414164395555555000242700,000$
12Ian McCoshenX100.007680666080707747253740623850505150002421,024,999$
13Nikita ZadorovX100.009258728287748460255148792565666350002533,200,000$
14Josh MorrisseyX100.006542888671867972256949692564666550002521,363,333$
15Moritz Seider (R)X100.008078836778575952255040643844445550001931,775,000$
16Travis DermottX100.00795681827872775925504972255859615000232863,333$
17Bode Wilde (R)X100.00777385607356604525353961374444515000203910,833$
Rayé
MOYENNE D'ÉQUIPE100.0078618472736675593956546635575762500
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
1Cayden Primeau (R)100.0060658173586559656362304444625000
2Pheonix Copley100.0057597483555859645959304646595000
Rayé
MOYENNE D'ÉQUIPE100.005962787857625965616130454561500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Joel Quenneville72718481908455CAN6336,000,000$


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
1Gabriel BourqueMarlies (TOR)LW/RW50131932-16700155118145491058.97%20105621.12412163419120261671044.83%5800000.6106000413
2Jeremy BraccoMarlies (TOR)RW5091827-8340957285235910.59%981116.2236918184000000248.89%4500000.6711000311
3Dmytro TimashovMarlies (TOR)LW50131326-2478012710914037969.29%1177315.464151154000001020.00%2500000.6701000232
4Moritz SeiderMarlies (TOR)D5052126-1011315864150244010.00%52103720.7631316371970000172000.00%000000.5001111001
5Travis DermottMarlies (TOR)D4091726-7500704480285911.25%4290222.565611671610110167400.00%000000.5800000131
6Brendan LeipsicMarlies (TOR)LW/RW50131023-104207588117308111.11%890118.04448251750001860241.61%14900000.5126000324
7Bode WildeMarlies (TOR)D5011314-1662085392310184.35%4198019.61167181860110180010.00%000000.2901000002
8Andrew NielsenMarlies (TOR)D504711-198610117374313349.30%5395819.18325331850002165010.00%000000.2311110001
Stats d'équipe Total ou en Moyenne39067118185-110535258105486832144929.81%236742219.03275077243133722499406641.52%27700000.50417221131015
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
1Cayden PrimeauMarlies (TOR)50113450.8772.9328664014011360400.79224500012
Stats d'équipe Total ou en Moyenne50113450.8772.9328664014011360400.79224500012


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 RestantSalaire MoyenSalaire Moyen RestantCap 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
Andrew NielsenMarlies (TOR)D231996-11-13Yes210 Lbs6 ft3NoNoNo3Pro & Farm921,666$349,341$921,666$349,341$0$0$No921,666$921,666$
Ben ThomasMarlies (TOR)D241996-05-27No187 Lbs6 ft1NoNoNo2Pro & Farm700,000$265,323$700,000$265,323$0$0$No700,000$Lien
Bobby RyanMarlies (TOR)RW331987-03-17No209 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$379,032$1,000,000$379,032$0$0$NoLien
Bode WildeMarlies (TOR)D202000-01-24Yes192 Lbs6 ft3NoNoNo3Pro & Farm910,833$345,235$910,833$345,235$0$0$No910,833$910,833$
Brendan LeipsicMarlies (TOR)LW/RW261994-05-19No180 Lbs5 ft10NoNoNo4Pro & Farm700,000$265,323$700,000$265,323$0$0$No700,000$700,000$700,000$Lien
Brett HowdenMarlies (TOR)C/LW/RW221998-03-29No193 Lbs6 ft2NoNoNo2Pro & Farm863,333$327,231$450,000$170,565$0$0$No863,333$Lien
Cayden PrimeauMarlies (TOR)G201999-08-11Yes181 Lbs6 ft3NoNoNo3Pro & Farm966,666$366,398$966,666$366,398$0$0$No966,666$966,666$
Dmytro TimashovMarlies (TOR)LW231996-09-30Yes195 Lbs5 ft10NoNoNo3Pro & Farm836,111$316,913$836,111$316,913$0$0$No836,111$836,111$
Filip ChytilMarlies (TOR)C/LW/RW201999-09-05No178 Lbs6 ft1NoNoNo4Pro & Farm1,244,166$471,579$894,166$338,918$0$0$No1,244,166$1,244,166$1,244,166$Lien
Gabriel BourqueMarlies (TOR)LW/RW291990-09-23No206 Lbs5 ft10NoNoNo2Pro & Farm866,000$328,242$866,000$328,242$0$0$No866,000$Lien
Ian McCoshenMarlies (TOR)D241995-08-05No217 Lbs6 ft3NoNoNo2Pro & Farm1,024,999$388,508$1,024,999$388,508$0$0$No1,024,999$Lien
Jeremy BraccoMarlies (TOR)RW231997-03-17Yes180 Lbs5 ft9NoNoNo3Pro & Farm925,000$350,605$925,000$350,605$0$0$No925,000$925,000$
Josh MorrisseyMarlies (TOR)D251995-03-28No195 Lbs6 ft0NoNoNo2Pro & Farm1,363,333$516,747$1,363,333$516,747$0$0$No1,363,333$Lien
Kailer YamamotoMarlies (TOR)RW211998-09-29No153 Lbs5 ft8NoNoNo3Pro & Farm1,124,166$426,095$894,166$338,918$0$0$No1,124,166$1,124,166$Lien
Moritz SeiderMarlies (TOR)D192001-04-06Yes207 Lbs6 ft4NoNoNo3Pro & Farm1,775,000$672,782$1,775,000$672,782$0$0$No1,775,000$1,775,000$
Nikita ZadorovMarlies (TOR)D251995-04-15No230 Lbs6 ft5NoNoNo3Pro & Farm3,200,000$1,212,903$3,200,000$1,212,903$0$0$No3,200,000$3,200,000$Lien
Pheonix CopleyMarlies (TOR)G281992-01-18No200 Lbs6 ft4NoNoNo2Pro & Farm650,000$246,371$650,000$246,371$0$0$No650,000$Lien
Steven FogartyMarlies (TOR)C/RW271993-04-18No206 Lbs6 ft3NoNoNo3Pro & Farm708,750$268,639$708,750$268,639$0$0$No708,750$708,750$Lien
Travis DermottMarlies (TOR)D231996-12-21No215 Lbs6 ft0NoNoNo2Pro & Farm863,333$327,231$863,333$327,231$0$0$No863,333$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1923.95197 Lbs6 ft12.631,086,492$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gabriel Bourque35122
2Brendan LeipsicJeremy Bracco30122
3Dmytro Timashov25122
4Gabriel BourqueBrendan Leipsic10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Moritz Seider35122
2Andrew NielsenBode Wilde30122
325122
4Moritz Seider10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Gabriel Bourque60122
2Brendan LeipsicJeremy Bracco40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Moritz Seider60122
2Andrew NielsenBode Wilde40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Gabriel Bourque60122
2Brendan Leipsic40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Moritz Seider60122
2Andrew NielsenBode Wilde40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
160122Moritz Seider60122
2Gabriel Bourque40122Andrew NielsenBode Wilde40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Gabriel Bourque60122
2Brendan Leipsic40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Moritz Seider60122
2Andrew NielsenBode Wilde40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gabriel BourqueMoritz Seider
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Gabriel BourqueMoritz Seider
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dmytro Timashov, Jeremy Bracco, Dmytro Timashov, Jeremy Bracco
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
, Andrew Nielsen, Bode WildeAndrew Nielsen, Bode Wilde
Tirs de Pénalité
, Gabriel Bourque, Brendan Leipsic, , Dmytro Timashov
Gardien
#1 : Cayden Primeau, #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
1Admirals3120000078-1211000006511010000013-220.333713200035273155730228229331651343421317.69%19478.95%0511132938.45%574157236.51%25167737.08%10787311371378586274
2Bruins513000101314-1211000006513020001079-240.4001322350035273151033022822933110541639626311.54%29486.21%0511132938.45%574157236.51%25167737.08%10787311371378586274
3Crunch705000111020-1040300001613-73020001047-330.2141016260035273151313022822933117459861673339.09%36586.11%0511132938.45%574157236.51%25167737.08%10787311371378586274
4Griffins623001001921-2312000001011-131100100910-150.41719365500352731596302282293311904310012626623.08%46784.78%2511132938.45%574157236.51%25167737.08%10787311371378586274
5Monsters1010000012-1000000000001010000012-100.000123003527315133022822933120614196116.67%60100.00%0511132938.45%574157236.51%25167737.08%10787311371378586274
6Moose10000010431100000104310000000000021.0004610003527315213022822933125310156233.33%50100.00%0511132938.45%574157236.51%25167737.08%10787311371378586274
7Penguins211000004401010000023-11100000021120.50046100035273153730228229331341318421417.14%80100.00%1511132938.45%574157236.51%25167737.08%10787311371378586274
8Phantoms2020000037-4000000000002020000037-400.00035800352731535302282293315021223414321.43%11190.91%0511132938.45%574157236.51%25167737.08%10787311371378586274
9Rocket61400001611-53120000035-23020000136-330.25061218003527315853022822933111130871003438.82%33390.91%0511132938.45%574157236.51%25167737.08%10787311371378586274
10Senators62400000915-62200000052340400000413-940.333915240035273151143022822933114233781173525.71%38684.21%0511132938.45%574157236.51%25167737.08%10787311371378586274
11Soldiers20200000311-81010000014-31010000027-500.0003580035273152630228229331541325359111.11%100100.00%0511132938.45%574157236.51%25167737.08%10787311371378586274
12Sound Tigers3030000029-72020000027-51010000002-200.0002350035273155930228229331762832672129.52%16381.25%0511132938.45%574157236.51%25167737.08%10787311371378586274
13Stars1000000134-11000000134-10000000000010.500369003527315153022822933133410206116.67%4175.00%0511132938.45%574157236.51%25167737.08%10787311371378586274
Total508340023396148-5225616000125573-1825218002214175-34270.270961682640035273158843022822933112053436479892673312.36%2883886.81%3511132938.45%574157236.51%25167737.08%10787311371378586274
14Wolf Pack30300000611-52020000047-31010000024-200.0006101600352731552302282293317217306716318.75%15193.33%0511132938.45%574157236.51%25167737.08%10787311371378586274
15Wolves2010010068-21010000034-11000010034-110.250611170035273154030228229331541929428112.50%12375.00%0511132938.45%574157236.51%25167737.08%10787311371378586274
_Since Last GM Reset508340023396148-5225616000125573-1825218002214175-34270.270961682640035273158843022822933112053436479892673312.36%2883886.81%3511132938.45%574157236.51%25167737.08%10787311371378586274
_Vs Conference32523000225284-321449000012635-918114000212649-23160.2505288140003527315570302282293317082203986421781910.67%1762088.64%1511132938.45%574157236.51%25167737.08%10787311371378586274
_Vs Division30416000225781-241446000013036-616010000212745-18140.23357101158003527315529302282293317222064146061541711.04%1822586.26%2511132938.45%574157236.51%25167737.08%10787311371378586274

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5027L396168264884120534364798900
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
50834023396148
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2561600125573
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2521802214175
Derniers 10 Matchs
WLOTWOTL SOWSOL
270001
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2673312.36%2883886.81%3
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
302282293313527315
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
511132938.45%574157236.51%25167737.08%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
10787311371378586274


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
1 - 2020-09-2710Marlies1Monsters2LSommaire du Match
2 - 2020-09-2818Crunch4Marlies3LSommaire du Match
4 - 2020-09-3028Marlies2Griffins3LXSommaire du Match
5 - 2020-10-0135Rocket2Marlies1LSommaire du Match
6 - 2020-10-0251Marlies1Senators3LSommaire du Match
8 - 2020-10-0456Griffins5Marlies2LSommaire du Match
10 - 2020-10-0671Senators1Marlies2WSommaire du Match
13 - 2020-10-0987Marlies1Crunch3LSommaire du Match
14 - 2020-10-1095Marlies0Senators2LSommaire du Match
16 - 2020-10-12101Rocket1Marlies2WSommaire du Match
18 - 2020-10-14119Griffins3Marlies1LSommaire du Match
21 - 2020-10-17130Marlies1Rocket2LSommaire du Match
22 - 2020-10-18141Crunch4Marlies0LSommaire du Match
23 - 2020-10-19151Marlies3Bruins2WXXSommaire du Match
24 - 2020-10-20161Admirals3Marlies2LSommaire du Match
25 - 2020-10-21166Marlies1Rocket2LSommaire du Match
27 - 2020-10-23184Penguins3Marlies2LSommaire du Match
28 - 2020-10-24195Marlies3Wolves4LXSommaire du Match
30 - 2020-10-26205Marlies2Penguins1WSommaire du Match
32 - 2020-10-28214Soldiers4Marlies1LSommaire du Match
34 - 2020-10-30228Marlies1Rocket2LXXSommaire du Match
36 - 2020-11-01236Moose3Marlies4WXXSommaire du Match
38 - 2020-11-03249Admirals2Marlies4WSommaire du Match
40 - 2020-11-05260Marlies2Wolf Pack4LSommaire du Match
42 - 2020-11-07269Marlies2Phantoms5LSommaire du Match
44 - 2020-11-09280Wolf Pack4Marlies2LSommaire du Match
45 - 2020-11-10285Marlies1Admirals3LSommaire du Match
46 - 2020-11-11299Rocket2Marlies0LSommaire du Match
48 - 2020-11-13315Bruins4Marlies2LSommaire du Match
50 - 2020-11-15325Marlies0Sound Tigers2LSommaire du Match
51 - 2020-11-16337Marlies2Crunch1WXXSommaire du Match
52 - 2020-11-17349Sound Tigers5Marlies1LSommaire du Match
54 - 2020-11-19363Crunch3Marlies2LXXSommaire du Match
55 - 2020-11-20374Marlies1Senators4LSommaire du Match
56 - 2020-11-21381Griffins3Marlies7WSommaire du Match
57 - 2020-11-22395Marlies2Bruins3LSommaire du Match
58 - 2020-11-23404Marlies4Griffins3WSommaire du Match
59 - 2020-11-24413Wolves4Marlies3LSommaire du Match
61 - 2020-11-26429Sound Tigers2Marlies1LSommaire du Match
63 - 2020-11-28441Marlies1Phantoms2LSommaire du Match
64 - 2020-11-29450Crunch2Marlies1LSommaire du Match
66 - 2020-12-01462Bruins1Marlies4WSommaire du Match
67 - 2020-12-02470Marlies1Crunch3LSommaire du Match
68 - 2020-12-03476Marlies2Bruins4LSommaire du Match
70 - 2020-12-05491Senators1Marlies3WSommaire du Match
71 - 2020-12-06505Marlies2Soldiers7LSommaire du Match
72 - 2020-12-07514Stars4Marlies3LXXSommaire du Match
74 - 2020-12-09529Wolf Pack3Marlies2LSommaire du Match
75 - 2020-12-10537Marlies3Griffins4LSommaire du Match
77 - 2020-12-12547Marlies2Senators4LSommaire du Match
78 - 2020-12-13558Griffins-Marlies-
79 - 2020-12-14568Marlies-Flames-
80 - 2020-12-15579Flames-Marlies-
82 - 2020-12-17592Marlies-Griffins-
84 - 2020-12-19598Marlies-Monsters-
85 - 2020-12-20610Penguins-Marlies-
86 - 2020-12-21621Marlies-Sharks-
88 - 2020-12-23632Phantoms-Marlies-
90 - 2020-12-25645Marlies-Penguins-
91 - 2020-12-26655Bruins-Marlies-
93 - 2020-12-28669Sharks-Marlies-
94 - 2020-12-29678Marlies-Moose-
95 - 2020-12-30685Marlies-Bruins-
96 - 2020-12-31696Marlies-Rampage-
97 - 2021-01-01703Rampage-Marlies-
99 - 2021-01-03718Marlies-Sound Tigers-
100 - 2021-01-04727IceHogs-Marlies-
101 - 2021-01-05741Monsters-Marlies-
103 - 2021-01-07752Marlies-Stars-
104 - 2021-01-08763Admirals-Marlies-
105 - 2021-01-09775Condors-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10785Marlies-Crunch-
108 - 2021-01-12799Monarchs-Marlies-
109 - 2021-01-13808Marlies-Monarchs-
111 - 2021-01-15817Marlies-Rocket-
112 - 2021-01-16826Bruins-Marlies-
114 - 2021-01-18841Marlies-IceHogs-
115 - 2021-01-19850Rocket-Marlies-
117 - 2021-01-21862Marlies-Condors-
118 - 2021-01-22870Senators-Marlies-
120 - 2021-01-24887Senators-Marlies-
121 - 2021-01-25890Marlies-Admirals-



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
16 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
4,940,458$ 2,064,336$ 1,965,003$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,214,600$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 47 65,035$ 3,056,645$




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