Marlies

GP: 6 | W: 0 | L: 6 | OTL: 0 | P: 0
GF: 5 | GA: 34 | PP%: 2.86% | PK%: 77.78%
DG: Sebastien Cloutier | Morale : 46 | Moyenne d'Équipe : 64
Prochain matchs #83 vs Wolf Pack
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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 McCarthyX100.006236905776939056635654565582795252610
2Stefan MatteauX100.007142745584908554585352575369657652590
3Dryden HuntX100.006938925873807456525754535567645252580
4Tom SestitoX100.008047585395736952545151595280725352580
5Sean MaloneX100.005935945674837755595552545167646152570
6David Pope (R)X100.006237895378797352565153545269656052560
7Cameron SchillingX100.005636926077827059306054594679714448620
8Olli Juolevi (R)X100.006035946177797160306651584761638450610
9Keaton ThompsonX100.005639825571908554305351524567645652590
Rayé
1Seth HelgesonX100.007644695491949553305551594977695637640
MOYENNE D'ÉQUIPE100.00653983568084795546565256517268595060
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 Campbell100.00818684808079818079818073777452770
Rayé
1Scott Darling100.00797371957877797877797879854244770
2Chad Johnson100.00787472837776787776787782873544760
3Troy Grosenick100.00778078747675777675777678844344740
MOYENNE D'ÉQUIPE100.0079787683787779787779787883494676
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'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
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 StatusType Salaire Actuel Cap Salariale Cap Salariale Restant Exclus du Cap Salarial Link
Cameron SchillingMarlies (Tor)D301988-10-07No182 Lbs6 ft2NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Chad JohnsonMarlies (Tor)G331986-06-10No197 Lbs6 ft3NoNoNo2Sans RestrictionPro & Farm1,000,000$0$0$NoLien
David PopeMarlies (Tor)LW241994-09-27Yes187 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$NoLien
Dryden HuntMarlies (Tor)LW231995-11-24No191 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Jack CampbellMarlies (Tor)G271992-01-09No197 Lbs6 ft2NoNoNo3Avec RestrictionPro & Farm1,397,349$0$0$NoLien
John McCarthyMarlies (Tor)LW321986-08-09No195 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$NoLien
Keaton ThompsonMarlies (Tor)D231995-09-14No182 Lbs6 ft0NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Olli JuoleviMarlies (Tor)D211998-05-05Yes182 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm900,000$0$0$NoLien
Scott DarlingMarlies (Tor)G301988-12-22No226 Lbs6 ft5NoNoNo4Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Sean MaloneMarlies (Tor)C241995-04-30No197 Lbs6 ft0NoNoNo3Avec RestrictionPro & Farm300,000$0$0$NoLien
Seth HelgesonMarlies (Tor)D281990-10-08No221 Lbs6 ft4NoNoNo3Sans RestrictionPro & Farm500,000$0$0$NoLien
Stefan MatteauMarlies (Tor)C251994-02-23No220 Lbs6 ft2NoNoNo2Avec RestrictionPro & Farm300,000$0$0$NoLien
Tom SestitoMarlies (Tor)LW311987-09-28No228 Lbs6 ft5NoNoNo2Sans RestrictionPro & Farm500,000$0$0$NoLien
Troy GrosenickMarlies (Tor)G291989-08-27No185 Lbs6 ft1NoNoNo4Sans RestrictionPro & Farm1,000,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1427.14199 Lbs6 ft22.86628,382$



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
1Americans1010000014-3000000000001010000014-300.0001230030202638374204612616300.00%3166.67%02614118.44%5320625.73%239823.47%8051213486523
2Comets30300000217-1520200000110-91010000017-600.0002460030205438374201363120461800.00%10280.00%02614118.44%5320625.73%239823.47%8051213486523
3Devils1010000006-6000000000001010000006-600.0000000030201938374204611210500.00%10100.00%02614118.44%5320625.73%239823.47%8051213486523
4Monsters1010000027-51010000027-50000000000000.0002460030201838374204658179111.11%4175.00%02614118.44%5320625.73%239823.47%8051213486523
Total60600000534-2930300000317-1430300000217-1500.0005101500302011738374202745936893512.86%18477.78%02614118.44%5320625.73%239823.47%8051213486523
_Since Last GM Reset60600000534-2930300000317-1430300000217-1500.0005101500302011738374202745936893512.86%18477.78%02614118.44%5320625.73%239823.47%8051213486523
_Vs Conference40400000321-1820200000110-920200000211-900.0003690030208038374201824326622100.00%13376.92%02614118.44%5320625.73%239823.47%8051213486523

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
60L65101511727459368900
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
6060000534
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3030000317
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3030000217
Derniers 10 Matchs
WLOTWOTL SOWSOL
060000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
3512.86%18477.78%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
38374203020
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
2614118.44%5320625.73%239823.47%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
8051213486523


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 Pack-Marlies-
21 - 2019-09-22100Rocket-Marlies-
24 - 2019-09-25107Crunch-Marlies-
31 - 2019-10-02141Marlies-Monsters-
38 - 2019-10-09183Marlies-Senators-
39 - 2019-10-10196Marlies-Senators-
42 - 2019-10-13212Marlies-Rocket-
45 - 2019-10-16225Marlies-Senators-
46 - 2019-10-17240Devils-Marlies-
47 - 2019-10-18250Devils-Marlies-
52 - 2019-10-23266Marlies-Monsters-
54 - 2019-10-25293Monsters-Marlies-
57 - 2019-10-28301Marlies-Monsters-
60 - 2019-10-31320Penguins-Marlies-
61 - 2019-11-01334Phantoms-Marlies-
64 - 2019-11-04341Bruins-Marlies-
67 - 2019-11-07363Rocket-Marlies-
68 - 2019-11-08378Senators-Marlies-
71 - 2019-11-11384Crunch-Marlies-
73 - 2019-11-13397Marlies-Moose-
74 - 2019-11-14405Marlies-Moose-
78 - 2019-11-18425Devils-Marlies-
80 - 2019-11-20441Marlies-Rocket-
81 - 2019-11-21450Marlies-Rocket-
85 - 2019-11-25464Senators-Marlies-
87 - 2019-11-27481Marlies-Americans-
90 - 2019-11-30504Checkers-Marlies-
94 - 2019-12-04521Marlies-Devils-
95 - 2019-12-05535Marlies-Crunch-
96 - 2019-12-06548Checkers-Marlies-
99 - 2019-12-09552Comets-Marlies-
101 - 2019-12-11568Marlies-Americans-
102 - 2019-12-12574Americans-Marlies-
109 - 2019-12-19618Marlies-Checkers-
110 - 2019-12-20631Marlies-Checkers-
113 - 2019-12-23647Marlies-Monsters-
115 - 2019-12-25656Marlies-Senators-
116 - 2019-12-26674Marlies-Senators-
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
35 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
17,987$ 87,973$ 3,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 9,217$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 177 969$ 171,513$




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
1460600000534-2930300000317-1430300000217-1505101500302011738374202745936893512.86%18477.78%02614118.44%5320625.73%239823.47%8051213486523
Total Saison Régulière60600000534-2930300000317-1430300000217-1505101500302011738374202745936893512.86%18477.78%02614118.44%5320625.73%239823.47%8051213486523