Moose

GP: 48 | W: 3 | L: 43 | OTL: 2 | P: 8
GF: 87 | GA: 266 | PP%: 8.57% | PK%: 70.00%
DG: Luc Forget | Morale : 12 | Moyenne d'Équipe : 57
Prochain matchs #766 vs Wolves
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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
1Filip Chlapik (R)X100.00685555756657576771636262557274158620
2Vinni Lettieri (R)XX100.00765581706566746561646161555050162610
3Corban KnightX100.00805567627770696050596060557571162610
4Ryan OlsenX100.00605569616866695599555559557374162580
5Garrett MitchellX100.00565558617264695550555556557450162560
6Graham BlackX100.00655567617263655550555556556950162560
7Justin Kirkland (R)X100.00655567647064695550555555555050125560
8Troy BourkeX100.00605566676360745550555556555050162560
9Antoine LaganiereX100.00565555555859595550555555557072162550
10Jeff HogganX100.00565555555557565550555555555757121530
11Travis MorinX100.00565555555555555550555555555050134530
12Yannick WeberX100.00795582838071587325636374558179162700
13Dalton ProutX100.00655560779374716425606063557873162660
14T.J. BrennanX100.00605565647965796025606058555353138600
15Chris ButlerX100.00555556605656765625565656557071162570
16Morgan Ellis (A)X100.00585555605555685525555555555353162550
17John RamageX100.00565556605656695625565656555353162550
18Jarred TinordiX100.00555555605555585525555555555353162540
19Mac BennettX100.00565555605555585525555555555353162540
Rayé
1Trent Frederic (R)X100.00565555555555555550555555555050120520
MOYENNE D'ÉQUIPE100.0062556263656165584457575855625915358
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
1Matej Machovsky (R)100.0057475974605760646060555055162580
2Matiss Kivlenieks (R)100.0053749372475550584949555055159560
Rayé
MOYENNE D'ÉQUIPE100.005561767354565561555555505516157
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Bryan Trottier57476162787363CAN5951,000,000$


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'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
1Justin KirklandMoose (Wpg)LW48161026-24695123991604611510.00%5069014.38101929000001154.17%4800000.7501001101
2T.J. BrennanMoose (Wpg)D13167-64154918116119.09%2317813.761122800002000.00%000000.7801001010
Stats d'équipe Total ou en Moyenne61171633-3011010172117171521269.94%7386914.252131137000021154.17%4800000.7602002111
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
Stats d'équipe Total ou en Moyenne0.0000.0000.000


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 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
Antoine LaganiereMoose (Wpg)C261990-07-04No196 Lbs6 ft4NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Chris ButlerMoose (Wpg)D301986-10-27No196 Lbs6 ft1NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Corban KnightMoose (Wpg)C261990-09-10No195 Lbs6 ft2NoNoNo1Avec RestrictionPro & Farm500,000$0$0$No
Dalton ProutMoose (Wpg)D261990-03-13No222 Lbs6 ft3NoNoNo4Avec RestrictionPro & Farm500,000$0$0$No
Filip ChlapikMoose (Wpg)C191997-06-03Yes196 Lbs6 ft1NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Garrett MitchellMoose (Wpg)RW251991-02-09No183 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Graham BlackMoose (Wpg)C241993-01-13No180 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Jarred TinordiMoose (Wpg)D241992-02-20No225 Lbs6 ft6NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Jeff HogganMoose (Wpg)LW381978-02-01No193 Lbs5 ft11NoNoYes1Sans RestrictionPro & Farm500,000$0$0$No
John RamageMoose (Wpg)D251991-02-07No200 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Justin KirklandMoose (Wpg)LW201996-08-02Yes183 Lbs6 ft1NoNoNo3Contrat d'EntréePro & Farm500,000$0$0$No
Mac BennettMoose (Wpg)D251991-03-25No182 Lbs6 ft0NoNoNo1Avec RestrictionPro & Farm300,000$0$0$No
Matej MachovskyMoose (Wpg)G231993-07-25Yes187 Lbs6 ft2NoNoNo4Avec RestrictionPro & Farm300,000$0$0$No
Matiss KivlenieksMoose (Wpg)G201996-08-26Yes183 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Morgan EllisMoose (Wpg)D241992-04-29No204 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No
Ryan OlsenMoose (Wpg)C221994-03-24No187 Lbs6 ft1NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
T.J. BrennanMoose (Wpg)D271989-04-02No216 Lbs6 ft1NoNoNo1Avec RestrictionPro & Farm900,000$0$0$No
Travis MorinMoose (Wpg)C331984-01-08No190 Lbs6 ft1NoNoNo1Sans RestrictionPro & Farm300,000$0$0$No
Trent FredericMoose (Wpg)C181998-02-11Yes216 Lbs6 ft3NoNoNo4Contrat d'EntréePro & Farm500,000$0$0$No
Troy BourkeMoose (Wpg)LW221994-03-29No170 Lbs5 ft10NoNoNo1Contrat d'EntréePro & Farm300,000$0$0$No
Vinni LettieriMoose (Wpg)C/RW211995-02-06Yes181 Lbs5 ft10NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No
Yannick WeberMoose (Wpg)D281988-09-22No200 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2224.82195 Lbs6 ft12.32436,364$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
140122
2Justin Kirkland30122
320122
410122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
140122
230122
320122
410122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
160122
2Justin Kirkland40122
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
1Admirals60600000835-2720200000210-840400000625-1900.000814220031272631153893703741622783517740512.50%17947.06%1355117130.32%491164429.87%21974329.48%7374931639355514201
2Condors20200000611-50000000000020200000611-500.000611170031272638738937037416108271452600.00%7185.71%0355117130.32%491164429.87%21974329.48%7374931639355514201
3Eagles20200000010-1020200000010-100000000000000.000000003127263263893703741686322333700.00%8537.50%0355117130.32%491164429.87%21974329.48%7374931639355514201
4Griffins707000001736-19404000001122-1130300000614-800.00017335000312726317738937037416267706113620210.00%22577.27%0355117130.32%491164429.87%21974329.48%7374931639355514201
5Gulls20200000413-90000000000020200000413-900.00047110031272632838937037416752918211218.33%8275.00%0355117130.32%491164429.87%21974329.48%7374931639355514201
6Heat20200000314-110000000000020200000314-1100.000369003127263483893703741698281533800.00%5420.00%0355117130.32%491164429.87%21974329.48%7374931639355514201
7IceHogs20101000510-50000000000020101000510-520.50057120031272635538937037416682412308112.50%6266.67%0355117130.32%491164429.87%21974329.48%7374931639355514201
8Marlies20101000990201010009900000000000020.500918270031272631083893703741693208628112.50%4325.00%0355117130.32%491164429.87%21974329.48%7374931639355514201
9Rampage604001011332-19403000011022-1220100100310-720.16713263900312726314738937037416298885911514214.29%22577.27%1355117130.32%491164429.87%21974329.48%7374931639355514201
10Rocket2020000017-62020000017-60000000000000.0001230031272633938937037416882326491417.14%12191.67%0355117130.32%491164429.87%21974329.48%7374931639355514201
11Senators2020000038-52020000038-50000000000000.0003580031272634238937037416711616311317.69%8187.50%0355117130.32%491164429.87%21974329.48%7374931639355514201
12Stars50500000628-2220200000312-930300000316-1300.000612180031272631293893703741622677431012713.70%17758.82%0355117130.32%491164429.87%21974329.48%7374931639355514201
Total480430310187266-179240210200147125-78240220110040141-10180.083871602470031272631145389370374162087627443863210188.57%1805470.00%2355117130.32%491164429.87%21974329.48%7374931639355514201
14Wild403010001024-1420101000710-320200000314-1120.250101626003127263723893703741619163546117211.76%25580.00%0355117130.32%491164429.87%21974329.48%7374931639355514201
15Wolves40400000229-2720200000115-1420200000114-1300.00023500312726372389370374161914743621616.25%19478.95%0355117130.32%491164429.87%21974329.48%7374931639355514201
_Since Last GM Reset480430310187266-179240210200147125-78240220110040141-10180.083871602470031272631145389370374162087627443863210188.57%1805470.00%2355117130.32%491164429.87%21974329.48%7374931639355514201
_Vs Conference40400000721-142020000038-520200000413-900.0007121900312726370389370374161464534522528.00%16381.25%0355117130.32%491164429.87%21974329.48%7374931639355514201

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
488L16871602471145208762744386300
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
48043310187266
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
24021200147125
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
24022110040141
Derniers 10 Matchs
WLOTWOTL SOWSOL
0100000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
210188.57%1805470.00%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
389370374163127263
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
355117130.32%491164429.87%21974329.48%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
7374931639355514201


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 - 2018-09-076Moose2Wild7LSommaire du Match
5 - 2018-09-0925Moose1Wild7LSommaire du Match
10 - 2018-09-1438Senators4Moose2LSommaire du Match
11 - 2018-09-1549Senators4Moose1LSommaire du Match
17 - 2018-09-2177Rampage7Moose2LSommaire du Match
19 - 2018-09-2397Rampage6Moose5LXXSommaire du Match
25 - 2018-09-29122Moose2Admirals7LSommaire du Match
26 - 2018-09-30135Moose4IceHogs3WXSommaire du Match
28 - 2018-10-02136Moose2Admirals5LSommaire du Match
31 - 2018-10-05148Wolves8Moose1LSommaire du Match
32 - 2018-10-06158Wolves7Moose0LSommaire du Match
37 - 2018-10-11180Griffins3Moose2LSommaire du Match
39 - 2018-10-13197Griffins7Moose2LSommaire du Match
42 - 2018-10-16211Moose1Rampage7LSommaire du Match
43 - 2018-10-17220Moose0Stars7LSommaire du Match
46 - 2018-10-20241Moose2Griffins4LSommaire du Match
47 - 2018-10-21251Moose1Wolves7LSommaire du Match
52 - 2018-10-26271Wild4Moose5WXSommaire du Match
53 - 2018-10-27277Wild6Moose2LSommaire du Match
57 - 2018-10-31306Moose3Gulls7LSommaire du Match
59 - 2018-11-02316Moose1Gulls6LSommaire du Match
60 - 2018-11-03331Moose1Condors4LSommaire du Match
64 - 2018-11-07347Moose5Condors7LSommaire du Match
66 - 2018-11-09361Moose1Heat7LSommaire du Match
67 - 2018-11-10373Moose2Heat7LSommaire du Match
73 - 2018-11-16397Marlies4Moose5WXSommaire du Match
74 - 2018-11-17405Marlies5Moose4LSommaire du Match
80 - 2018-11-23442Griffins6Moose3LSommaire du Match
81 - 2018-11-24451Griffins6Moose4LSommaire du Match
89 - 2018-12-02500Eagles5Moose0LSommaire du Match
90 - 2018-12-03506Eagles5Moose0LSommaire du Match
92 - 2018-12-05515Moose2Rampage3LXSommaire du Match
94 - 2018-12-07526Moose1Stars4LSommaire du Match
95 - 2018-12-08541Moose2Stars5LSommaire du Match
100 - 2018-12-13560Rocket4Moose0LSommaire du Match
102 - 2018-12-15578Rocket3Moose1LSommaire du Match
104 - 2018-12-17592Admirals6Moose1LSommaire du Match
106 - 2018-12-19600Admirals4Moose1LSommaire du Match
109 - 2018-12-22617Rampage4Moose3LSommaire du Match
110 - 2018-12-23633Rampage5Moose0LSommaire du Match
113 - 2018-12-26648Moose2Griffins4LSommaire du Match
115 - 2018-12-28663Moose1IceHogs7LSommaire du Match
116 - 2018-12-29668Moose1Admirals6LSommaire du Match
122 - 2019-01-04690Moose1Admirals7LSommaire du Match
123 - 2019-01-05707Moose0Wolves7LSommaire du Match
127 - 2019-01-09717Moose2Griffins6LSommaire du Match
130 - 2019-01-12742Stars9Moose3LSommaire du Match
131 - 2019-01-13750Stars3Moose0LSommaire du Match
134 - 2019-01-16766Wolves-Moose-
136 - 2019-01-18776Wolves-Moose-
138 - 2019-01-20795Admirals-Moose-
139 - 2019-01-21806Admirals-Moose-
141 - 2019-01-23808Moose-Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
143 - 2019-01-25825Moose-Rocket-
144 - 2019-01-26828Moose-Rocket-
148 - 2019-01-30850Moose-Marlies-
150 - 2019-02-01860Moose-Senators-
151 - 2019-02-02872Moose-Senators-
158 - 2019-02-09911IceHogs-Moose-
159 - 2019-02-10924IceHogs-Moose-
162 - 2019-02-13940Stars-Moose-
164 - 2019-02-15951Stars-Moose-
166 - 2019-02-17967Gulls-Moose-
168 - 2019-02-19975Gulls-Moose-
171 - 2019-02-22991Moose-Eagles-
172 - 2019-02-231005Moose-Eagles-
176 - 2019-02-271024Moose-Stars-
178 - 2019-03-011035Moose-Rampage-
179 - 2019-03-021050Moose-Rampage-
182 - 2019-03-051061Condors-Moose-
183 - 2019-03-061068Condors-Moose-
186 - 2019-03-091084Heat-Moose-
187 - 2019-03-101099Heat-Moose-
192 - 2019-03-151118Moose-Griffins-
193 - 2019-03-161137Moose-Wolves-
194 - 2019-03-171148Moose-Wolves-



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
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
743,783$ 96,000$ 50,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 68,560$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 63 5,649$ 355,887$




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
13480430310187266-179240210200147125-78240220110040141-1018871602470031272631145389370374162087627443863210188.57%1805470.00%2355117130.32%491164429.87%21974329.48%7374931639355514201
Total Saison Régulière480430310187266-179240210200147125-78240220110040141-1018871602470031272631145389370374162087627443863210188.57%1805470.00%2355117130.32%491164429.87%21974329.48%7374931639355514201