Moose

GP: 25 | W: 2 | L: 22 | OTL: 1 | P: 5
GF: 50 | GA: 148 | PP%: 9.43% | PK%: 72.22%
DG: Luc Forget | Morale : 31 | Moyenne d'Équipe : 57
Prochain matchs #397 vs Marlies
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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
1Vinni Lettieri (R)XX100.00765581706566746561646161555050156610
2Corban KnightX100.00805567627770696050596060557571156610
3Ryan OlsenX100.00605569616866695599555559557374156580
4Garrett MitchellX100.00565558617264695550555556557450156560
5Graham BlackX100.00655567617263655550555556556950156560
6Justin Kirkland (R)X100.00655567647064695550555555555050138560
7Troy BourkeX100.00605566676360745550555556555050156560
8Antoine LaganiereX100.00565555555859595550555555557072156550
9Nathan Walker (R)X100.00565559555460685550555555555050156540
10Travis MorinX100.00565555555555555550555555555050135530
11Yannick WeberX100.00795582838071587325636374558179156700
12Dalton ProutX100.00655560779374716425606063557873156660
13T.J. BrennanX100.00605565647965796025606058555353133600
14Chris ButlerX100.00555556605656765625565656557071156570
15Morgan Ellis (A)X100.00585555605555685525555555555353156550
16John RamageX100.00565556605656695625565656555353156550
17Jarred TinordiX100.00555555605555585525555555555353156540
18Mac BennettX100.00565555605555585525555555555353156540
Rayé
1Jeff HogganX100.00565555555557565550555555555757119530
2Trent Frederic (R)X100.00565555555555555550555555555050125520
MOYENNE D'ÉQUIPE100.0061556262656166574357575855615815057
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)100.0057475974605760646060555055153580
2Matiss Kivlenieks (R)100.0053749372475550584949555055153560
Rayé
MOYENNE D'ÉQUIPE100.005561767354565561555555505515357
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)LW2511617-7455564677235514.29%1835214.11101415000001154.55%2200000.9601001101
2T.J. BrennanMoose (Wpg)D13167-64154918116119.09%2317813.761122800002000.00%000000.7801001010
Stats d'équipe Total ou en Moyenne38121224-1386101056488296613.64%4153113.99213624000021154.55%2200000.9002002111
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 Salaire Année 2 Salaire Année 3 Salaire Année 4 Salaire Année 5 Salaire Année 6 Salaire Année 7 Salaire Année 8 Salaire Année 9 Salaire Année 10 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$0$No500,000$500,000$
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$0$No500,000$500,000$500,000$
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$0$No300,000$300,000$300,000$
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$0$No500,000$500,000$
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$0$No300,000$300,000$300,000$
Matiss KivlenieksMoose (Wpg)G201996-08-26Yes183 Lbs6 ft2NoNoNo4Contrat d'EntréePro & Farm300,000$0$0$No300,000$300,000$300,000$
Morgan EllisMoose (Wpg)D241992-04-29No204 Lbs6 ft1NoNoNo3Avec RestrictionPro & Farm300,000$0$0$No300,000$300,000$
Nathan WalkerMoose (Wpg)LW221994-02-06Yes186 Lbs5 ft8NoNoNo1Contrat d'EntréePro & Farm500,000$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$0$No500,000$500,000$500,000$
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$0$No300,000$300,000$300,000$
Yannick WeberMoose (Wpg)D281988-09-22No200 Lbs5 ft11NoNoNo3Sans RestrictionPro & Farm500,000$0$0$No500,000$500,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2224.95194 Lbs6 ft12.18436,364$



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
1Admirals20200000412-80000000000020200000412-800.00047110015171623218919918898531192815320.00%7442.86%019159132.32%26188929.36%11640029.00%384257856183264103
2Condors20200000611-50000000000020200000611-500.00061117001517162871891991889108271452600.00%7185.71%019159132.32%26188929.36%11640029.00%384257856183264103
3Griffins30300000614-820200000410-61010000024-200.000612180015171627918919918891443241611100.00%13192.31%019159132.32%26188929.36%11640029.00%384257856183264103
4Gulls20200000413-90000000000020200000413-900.0004711001517162281891991889752918211218.33%8275.00%019159132.32%26188929.36%11640029.00%384257856183264103
5Heat20200000314-110000000000020200000314-1100.00036900151716248189199188998281533800.00%5420.00%019159132.32%26188929.36%11640029.00%384257856183264103
6IceHogs10001000431000000000001000100043121.00045900151716226189199188941138164125.00%4175.00%019159132.32%26188929.36%11640029.00%384257856183264103
7Rampage30200001820-1220100001713-61010000017-610.167816240015171628618919918891634031623133.33%10460.00%119159132.32%26188929.36%11640029.00%384257856183264103
8Senators2020000038-52020000038-50000000000000.000358001517162421891991889711616311317.69%8187.50%019159132.32%26188929.36%11640029.00%384257856183264103
9Stars1010000007-7000000000001010000007-700.00000000151716224189199188936121018700.00%5340.00%019159132.32%26188929.36%11640029.00%384257856183264103
Total250220200150148-981008010012256-3415014010002892-6450.100508813800151716258118919918891150328263434106109.43%1083072.22%119159132.32%26188929.36%11640029.00%384257856183264103
11Wild403010001024-1420101000710-320200000314-1120.25010162600151716272189199188919163546117211.76%25580.00%019159132.32%26188929.36%11640029.00%384257856183264103
12Wolves30300000222-2020200000115-141010000017-600.00023500151716257189199188913837375110110.00%16475.00%019159132.32%26188929.36%11640029.00%384257856183264103
_Since Last GM Reset250220200150148-981008010012256-3415014010002892-6450.100508813800151716258118919918891150328263434106109.43%1083072.22%119159132.32%26188929.36%11640029.00%384257856183264103
_Vs Conference40400000721-142020000038-520200000413-900.000712190015171627018919918891464534522528.00%16381.25%019159132.32%26188929.36%11640029.00%384257856183264103

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
255L75088138581115032826343400
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
25022200150148
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
100810012256
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
1501410002892
Derniers 10 Matchs
WLOTWOTL SOWSOL
091000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
106109.43%1083072.22%1
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
18919918891517162
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
19159132.32%26188929.36%11640029.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
384257856183264103


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 - 2018-11-16397Marlies-Moose-
74 - 2018-11-17405Marlies-Moose-
80 - 2018-11-23442Griffins-Moose-
81 - 2018-11-24451Griffins-Moose-
89 - 2018-12-02500Eagles-Moose-
90 - 2018-12-03506Eagles-Moose-
92 - 2018-12-05515Moose-Rampage-
94 - 2018-12-07526Moose-Stars-
95 - 2018-12-08541Moose-Stars-
100 - 2018-12-13560Rocket-Moose-
102 - 2018-12-15578Rocket-Moose-
104 - 2018-12-17592Admirals-Moose-
106 - 2018-12-19600Admirals-Moose-
109 - 2018-12-22617Rampage-Moose-
110 - 2018-12-23633Rampage-Moose-
113 - 2018-12-26648Moose-Griffins-
115 - 2018-12-28663Moose-IceHogs-
116 - 2018-12-29668Moose-Admirals-
122 - 2019-01-04690Moose-Admirals-
123 - 2019-01-05707Moose-Wolves-
127 - 2019-01-09717Moose-Griffins-
130 - 2019-01-12742Stars-Moose-
131 - 2019-01-13750Stars-Moose-
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
28 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
381,029$ 96,000$ 50,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 35,664$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 127 5,649$ 717,423$




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
13250220200150148-981008010012256-3415014010002892-645508813800151716258118919918891150328263434106109.43%1083072.22%119159132.32%26188929.36%11640029.00%384257856183264103
Total Saison Régulière250220200150148-981008010012256-3415014010002892-645508813800151716258118919918891150328263434106109.43%1083072.22%119159132.32%26188929.36%11640029.00%384257856183264103