Marlies

GP: 6 | W: 6 | L: 0 | OTL: 0 | P: 12
GF: 37 | GA: 12 | PP%: 48.39% | PK%: 80.77%
DG: Marcel Fournier | Morale : 59 | Moyenne d'Équipe : 67
Prochain matchs #83 vs Crunch
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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
1Colton Sceviour (A)X99.008142876173727361626459826078704854700
2Lawson Crouse (C)X99.009856696490739464566564796463658560700
3Brendan PerliniXX100.006439826686698165516269536465638457690
4Sean KuralyX100.008350786483758463766662746371695563690
5Luke KuninX100.007045786873817267716767696663648460680
6Zack KassianX100.008866616586779264516268666275717060680
7Charles HudonX100.008740796571726964656263706967656660670
8Tomas JurcoX100.006238856478817563656261646673677160660
9Michael McCarronX100.008342746098807459676056645867647960640
10Brendan Gaunce (A)X100.006337896184766959636158605669667760630
11Dominic TurgeonX100.005835935679847254655853645965636660610
12Mirco MuellerX98.008043856285836661307254734867648157700
13Brian LashoffX100.006236905987836858306053654577694657670
14Christian JarosX98.008344816084777458307053624765635660670
15Rinat ValievX100.007239825686918654305752584567646560650
16Anton LindholmX100.005435935771766956305453584569655460620
Rayé
MOYENNE D'ÉQUIPE99.63744382628278766153635966576966685967
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
1Charlie Lindgren99.00766664747574767574767571754760720
2Ville Husso100.00687371846766686766686767717260680
Rayé
MOYENNE D'ÉQUIPE99.5072706879717072717072716973606070
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Willie Desjardins83827684938751CAN623325,000$


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
1Brendan PerliniMarlies (TOR)LW/RW658134201131951426.32%112520.993584180000141044.44%978002.0600000120
2Colton SceviourMarlies (TOR)C46612500311155740.00%39022.694374131014131270.83%12015012.6400000201
3Sean KuralyMarlies (TOR)C6471159575174923.53%411118.60156317000060175.00%7224001.9700100020
4Lawson CrouseMarlies (TOR)LW63696100951871416.67%313121.900441180111140070.00%2075001.3700000010
5Luke KuninMarlies (TOR)C617844078152136.67%79215.3800004000011072.97%3725001.7300000000
6Tomas JurcoMarlies (TOR)LW662864066217928.57%210517.54101100000900100.00%522011.5200000100
7Mirco MuellerMarlies (TOR)D61678402311159.09%1216627.76112219000020000.00%0516000.8400000011
8Charles HudonMarlies (TOR)LW633612087651050.00%210417.481231160000120100.00%547001.1401000101
9Christian JarosMarlies (TOR)D61568008072214.29%315425.69123220000019000.00%0011000.7800000001
10Zack KassianMarlies (TOR)RW642616083151626.67%510417.38314316101120080.00%522001.1500000000
11Michael McCarronMarlies (TOR)C6224610010465633.33%310116.9401100000010073.08%2601000.7900000001
12Dominic TurgeonMarlies (TOR)C61233001120150.00%4528.680000100006100.00%101001.1500000100
13Brian LashoffMarlies (TOR)D6022500345530.00%413422.42000014011016000.00%029000.3000000000
14Brendan GaunceMarlies (TOR)C6011000514030.00%37913.2900000000000050.00%1005000.2500000000
15Anton LindholmMarlies (TOR)D6000200024020.00%47212.010000000003000.00%0010000.0000000000
16Rinat ValievMarlies (TOR)D6000640335230.00%812220.43000115000012000.00%0010000.0000000000
Stats d'équipe Total ou en Moyenne943759967055591661705110721.76%68174918.611524392217922461436371.61%31034101021.1001100665
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
1Charlie LindgrenMarlies (TOR)66000.9172.00360001214574000.000060001
Stats d'équipe Total ou en Moyenne66000.9172.00360001214574000.000060001


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
Anton LindholmMarlies (TOR)D221994-11-29No191 Lbs5 ft11NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Brendan GaunceMarlies (TOR)C231994-03-25No217 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Brendan PerliniMarlies (TOR)LW/RW211996-04-27No211 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm874,125$0$0$NoLien
Brian LashoffMarlies (TOR)D271990-07-16No219 Lbs6 ft3NoNoNo2Avec RestrictionPro & Farm750,000$0$0$NoLien
Charles HudonMarlies (TOR)LW231994-06-23No196 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm800,000$0$0$NoLien
Charlie LindgrenMarlies (TOR)G231993-12-18No182 Lbs6 ft1NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Christian JarosMarlies (TOR)D211996-04-02No201 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm755,000$0$0$NoLien
Colton SceviourMarlies (TOR)C281989-04-20No192 Lbs6 ft0NoNoNo2Sans RestrictionPro & Farm1,200,000$0$0$NoLien
Dominic TurgeonMarlies (TOR)C211996-02-25No200 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Lawson CrouseMarlies (TOR)LW201997-06-23No220 Lbs6 ft4NoNoNo3Contrat d'EntréePro & Farm1,533,333$0$0$NoLien
Luke KuninMarlies (TOR)C191997-12-04No195 Lbs6 ft0NoNoNo1Contrat d'EntréePro & Farm925,000$0$0$NoLien
Michael McCarronMarlies (TOR)C221995-07-04No230 Lbs6 ft6NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Mirco MuellerMarlies (TOR)D221995-03-21No210 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm1,400,000$0$0$NoLien
Rinat ValievMarlies (TOR)D221995-05-11No215 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Sean KuralyMarlies (TOR)C241993-01-20No213 Lbs6 ft2NoNoNo2Contrat d'EntréePro & Farm750,000$0$0$NoLien
Tomas JurcoMarlies (TOR)LW241992-12-28No188 Lbs6 ft2NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Ville HussoMarlies (TOR)G221995-02-06No205 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm750,000$0$0$NoLien
Zack KassianMarlies (TOR)RW261991-01-24No211 Lbs6 ft3NoNoNo1Contrat d'EntréePro & Farm1,950,000$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
1822.78205 Lbs6 ft21.39940,970$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Lawson CrouseColton SceviourBrendan Perlini40122
2Charles HudonSean KuralyZack Kassian30122
3Tomas JurcoLuke KuninMichael McCarron20122
4Colton SceviourMichael McCarronLawson Crouse10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mirco MuellerChristian Jaros40122
2Brian LashoffRinat Valiev30122
3Anton LindholmBrendan Gaunce20122
4Mirco MuellerChristian Jaros10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Lawson CrouseColton SceviourBrendan Perlini60122
2Charles HudonSean KuralyZack Kassian40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mirco MuellerChristian Jaros60122
2Brian LashoffRinat Valiev40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Colton SceviourLawson Crouse60122
2Brendan PerliniSean Kuraly40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mirco MuellerChristian Jaros60122
2Brian LashoffRinat Valiev40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Colton Sceviour60122Mirco MuellerChristian Jaros60122
2Lawson Crouse40122Brian LashoffRinat Valiev40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Colton SceviourLawson Crouse60122
2Brendan PerliniSean Kuraly40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Mirco MuellerChristian Jaros60122
2Brian LashoffRinat Valiev40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Lawson CrouseColton SceviourBrendan PerliniMirco MuellerChristian Jaros
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Lawson CrouseColton SceviourBrendan PerliniMirco MuellerChristian Jaros
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dominic Turgeon, Luke Kunin, Tomas JurcoDominic Turgeon, Luke KuninTomas Jurco
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Anton Lindholm, Brian Lashoff, Rinat ValievAnton LindholmBrian Lashoff, Rinat Valiev
Tirs de Pénalité
Colton Sceviour, Lawson Crouse, Brendan Perlini, Sean Kuraly, Zack Kassian
Gardien
#1 : Charlie Lindgren, #2 : Ville Husso


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
1Bruins110000001221000000000000110000001221021.0001220320071118136465074128108177685.71%4175.00%0669172.53%7811369.03%7810574.29%131651204510968
2Crunch11000000615000000000001100000061521.000610160071118129465074118917136116.67%6183.33%0669172.53%7811369.03%7810574.29%131651204510968
3Rocket11000000523110000005230000000000021.000561100711181324650741352581922100.00%50100.00%1669172.53%7811369.03%7810574.29%131651204510968
4Senateurs11000000422110000004220000000000021.00046100071118121465074126106105120.00%3166.67%1669172.53%7811369.03%7810574.29%131651204510968
5Thunderbird210010001055100010004311100000062441.000101727007111815346507413814163211545.45%8275.00%0669172.53%7811369.03%7810574.29%131651204510968
Total650010003712253200100013763300000024519121.000375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968
_Since Last GM Reset650010003712253200100013763300000024519121.000375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968
_Vs Conference650010003712253200100013763300000024519121.000375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968
_Vs Division650010003712253200100013763300000024519121.000375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
612W537599617114568559100
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
65010003712
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3201000137
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
3300000245
Derniers 10 Matchs
WLOTWOTL SOWSOL
501000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
311548.39%26580.77%2
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
4650741711181
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
669172.53%7811369.03%7810574.29%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
131651204510968


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
2 - 2019-10-059Thunderbird3Marlies4WXSommaire du Match
5 - 2019-10-0826Rocket2Marlies5WSommaire du Match
6 - 2019-10-0929Marlies6Thunderbird2WSommaire du Match
10 - 2019-10-1350Senateurs2Marlies4WSommaire du Match
12 - 2019-10-1559Marlies6Crunch1WSommaire du Match
14 - 2019-10-1772Marlies12Bruins2WSommaire du Match
16 - 2019-10-1983Crunch-Marlies-
18 - 2019-10-2196Marlies-Senateurs-
19 - 2019-10-22106Monsters-Marlies-
22 - 2019-10-25122Bruins-Marlies-
23 - 2019-10-26126Marlies-Rocket-
26 - 2019-10-29145Thunderbird-Marlies-
28 - 2019-10-31157Marlies-Thunderbird-
31 - 2019-11-03169Marlies-Rocket-
33 - 2019-11-05178Bears-Marlies-
36 - 2019-11-08197Devils-Marlies-
38 - 2019-11-10206Marlies-Condors-
41 - 2019-11-13219Marlies-Rocket-
42 - 2019-11-14227Condors-Marlies-
45 - 2019-11-17243Sound Tigers-Marlies-
47 - 2019-11-19254Marlies-Thunderbird-
49 - 2019-11-21265Marlies-Stars-
51 - 2019-11-23271Senateurs-Marlies-
53 - 2019-11-25286Marlies-Rampages-
55 - 2019-11-27294Admirals-Marlies-
57 - 2019-11-29309Marlies-Icedogs-
59 - 2019-12-01319Bears-Marlies-
64 - 2019-12-06341Senateurs-Marlies-
66 - 2019-12-08360Marlies-Phantoms-
68 - 2019-12-10365Wolves-Marlies-
72 - 2019-12-14387Icedogs-Marlies-
77 - 2019-12-19411Blacknight-Marlies-
79 - 2019-12-21422Marlies-Admirals-
80 - 2019-12-22432Barracuda-Marlies-
82 - 2019-12-24446Marlies-Blacknight-
84 - 2019-12-26455Marlies-Monsters-
85 - 2019-12-27460Devils-Marlies-
88 - 2019-12-30479Marlies-Phantoms-
89 - 2019-12-31485Reigh-Marlies-
93 - 2020-01-04500Marlies-Gulls-
94 - 2020-01-05507Rampages-Marlies-
99 - 2020-01-10531Heat-Marlies-
102 - 2020-01-13544Marlies-Senateurs-
104 - 2020-01-15553Monsters-Marlies-
106 - 2020-01-17565Marlies-Bruins-
108 - 2020-01-19577Moose-Marlies-
110 - 2020-01-21590Marlies-Penguins-
111 - 2020-01-22597Marlies-Sound Tigers-
113 - 2020-01-24603Monsters-Marlies-
118 - 2020-01-29625Penguins-Marlies-
120 - 2020-01-31634Marlies-Penguins-
122 - 2020-02-02650Crunch-Marlies-
123 - 2020-02-03659Marlies-Barracuda-
126 - 2020-02-06674Gulls-Marlies-
127 - 2020-02-07681Marlies-Crunch-
130 - 2020-02-10693Marlies-Sound Tigers-
131 - 2020-02-11700Phantoms-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
135 - 2020-02-15721Penguins-Marlies-
137 - 2020-02-17734Marlies-Heat-
139 - 2020-02-19744Marlies-Monsters-
141 - 2020-02-21748Phantoms-Marlies-
144 - 2020-02-24762Marlies-Gulls-
146 - 2020-02-26773Sound Tigers-Marlies-
148 - 2020-02-28790Marlies-Bears-
150 - 2020-03-01796Crunch-Marlies-
152 - 2020-03-03805Marlies-Senateurs-
155 - 2020-03-06819Blacknight-Marlies-
160 - 2020-03-11842Bruins-Marlies-
165 - 2020-03-16866Stars-Marlies-
168 - 2020-03-19877Marlies-Stars-
169 - 2020-03-20889Bruins-Marlies-
170 - 2020-03-21896Marlies-Crunch-
172 - 2020-03-23904Marlies-Bruins-
173 - 2020-03-24911Marlies-Devils-
174 - 2020-03-25916Thunderbird-Marlies-
177 - 2020-03-28930Marlies-Devils-
178 - 2020-03-29938Marlies-Moose-
180 - 2020-03-31942Rocket-Marlies-
181 - 2020-04-01951Marlies-Wolves-
185 - 2020-04-05963Rocket-Marlies-
187 - 2020-04-07967Marlies-Bears-
189 - 2020-04-09975Marlies-Reigh-



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
38 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
158,535$ 1,693,745$ 1,608,537$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 133,020$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 176 10,569$ 1,860,144$




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
365001000371225320010001376330000002451912375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968
Total Saison Régulière65001000371225320010001376330000002451912375996007111811714650741145685591311548.39%26580.77%2669172.53%7811369.03%7810574.29%131651204510968
Séries
219127000001079314107300000614417954000004649-3241071612680020493717942162882864818290235310924043.48%1064260.38%726542961.77%33254461.03%23639659.60%419247434148304167
Total Séries19127000001079314107300000614417954000004649-3241071612680020493717942162882864818290235310924043.48%1064260.38%726542961.77%33254461.03%23639659.60%419247434148304167