Moose

GP: 8 | W: 5 | L: 3 | OTL: 0 | P: 10
GF: 19 | GA: 17 | PP%: 8.00% | PK%: 82.98%
DG: Emmanuel Rheault | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #92 vs Condors
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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
1Adam GaudetteXXX100.00655282776562836670787254255757705000
2Antoine RousselX100.00765771817261716845627058757273685000
3Mattias JanmarkXX100.00634293827268896442695974256566675000
4Joel L'EsperanceXX100.00777581777579846278536765644545685000
5Markus GranlundXXX100.00634187826757836344535979726566645000
6Zack MacEwenXX100.00899968668054725844568061254545715000
7Mason AppletonXX100.00634287807258806036576071255555645000
8Chase De LeoX100.00736590626573776075565865555454625000
9Tyler MotteXX100.00994690746564715739616289255959705300
10Dryden HuntXX100.00834569727156866225655570455858645000
11Rasmus Kupari (R)X100.00756989656955565366435862554444595000
12Brendan SmithXX100.00809369768056805725474877257274605000
13Dmitry KulikovX100.00854582807480716125524877257778635000
14Erik GudbransonX100.00828651768678816225494986757273635000
15Johnny BoychukX100.00864692748272865925514882257783645000
16Michael StoneX100.00814585767969545225514876256869615000
17Scott HarringtonX100.00774487707663735925534872256061605000
18Tyler MyersX100.00805679818983916925565079537577664700
Rayé
1JC LiponX100.00646756666774785950565859554747605000
2Sami NikuX100.00734380756669616125634766254848615000
3Conor Timmins (R)X100.00716974656949475725584161394444555000
MOYENNE D'ÉQUIPE100.0076587974736675604057567141606164500
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
1Matt Murray100.0061777474616169636461825960655000
2Ilya Samsonov100.0077636080827275768277754646755000
Rayé
1Keith Kinkaid100.0051627879475150564848306060525000
2Eric Comrie100.0062658165626757666463304444635000
MOYENNE D'ÉQUIPE100.006367737563636365656254525364500
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Alain Vigneault78767983878159CAN6133,500,000$


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
1Adam GaudetteMoose (WPG)C/LW/RW8325200313116527.27%015319.241014340000180155.56%900000.6512000100
2Antoine RousselMoose (WPG)LW8325120103931133.33%217521.951121310000321033.33%1200000.5702000011
3Brad RichardsonJetsC/LW82352401025142514.29%017922.460113351011301067.65%20400000.5612000100
4Mattias JanmarkMoose (WPG)C/LW8235220311841225.00%016720.910220340000200043.90%12300000.6012000100
5Johnny BoychukMoose (WPG)D81342407473114.29%616720.94112538011027000.00%000000.4800000001
6Tyler MyersMoose (WPG)D8134211571214497.14%519023.760111240000027000.00%000000.4200001010
7Markus GranlundMoose (WPG)C/LW/RW81232401711489.09%113817.35101232000000040.54%3700000.4311000000
8Michael StoneMoose (WPG)D8033340640000.00%311214.010000100009000.00%000000.5400000010
9Dryden HuntMoose (WPG)LW/RW8123-1315138721314.29%09812.3100001000040016.67%600000.6100010011
10Erik GudbransonMoose (WPG)D8022-121520516030.00%1016720.960001035000027000.00%000000.2401001000
11Joel L'EsperanceMoose (WPG)C/RW8022-16013115070.00%012816.05000218000000059.70%6700000.3100000000
12Zack MacEwenMoose (WPG)C/RW8202322106151240.00%0708.8500005000041133.33%900000.5600101200
13Dmitry KulikovMoose (WPG)D8011-180575230.00%817321.75000335000031000.00%000000.1100000000
14Mason AppletonMoose (WPG)C/RW8101-3200552420.00%010312.9400006000080030.23%4300000.1900000000
15Scott HarringtonMoose (WPG)D8011-160240000.00%0678.46000030000600100.00%100000.3000000000
16Brendan SmithMoose (WPG)LW/D80004235662210.00%010012.5800003000010000.00%000000.0000010000
17Sami NikuMoose (WPG)D2000000010000.00%0157.590000000000000.00%000000.0000000000
18Chase De LeoMoose (WPG)C8000000310010.00%0354.4800006000020073.91%2300000.0000000000
19Rasmus KupariMoose (WPG)C1000100330000.00%01515.7000002000020066.67%600000.0000000000
Stats d'équipe Total ou en Moyenne1391729461615030118131119358514.29%35226216.2846104236711212673254.63%54000000.41410123543
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
1Ilya SamsonovMoose (WPG)63200.9041.63332209940000.8181153010
2Matt MurrayMoose (WPG)32100.7713.10155008350000.000035000
Stats d'équipe Total ou en Moyenne95300.8682.0948820171290000.8181188010


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
Adam GaudetteMoose (WPG)C/LW/RW231996-10-02No170 Lbs6 ft1NoNoNo3Pro & Farm2,491,667$2,230,444$1,491,667$1,335,283$0$0$No1,491,667$1,491,667$Lien
Antoine RousselMoose (WPG)LW301989-11-20No195 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Brendan SmithMoose (WPG)LW/D311989-02-07No211 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Chase De LeoMoose (WPG)C241995-10-25No185 Lbs5 ft9NoNoNo3Pro & Farm650,000$581,855$650,000$581,855$0$0$No650,000$650,000$Lien
Conor TimminsMoose (WPG)D211998-09-18Yes184 Lbs6 ft2NoNoNo3Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$925,000$
Dmitry KulikovMoose (WPG)D291990-10-29No204 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Dryden HuntMoose (WPG)LW/RW241995-11-24No197 Lbs6 ft0NoNoNo2Pro & Farm715,000$640,040$715,000$640,040$0$0$No715,000$Lien
Eric ComrieMoose (WPG)G241995-07-05No175 Lbs6 ft1NoNoNo3Pro & Farm650,000$581,855$650,000$581,855$0$0$No650,000$650,000$Lien
Erik GudbransonMoose (WPG)D281992-01-07No220 Lbs6 ft5NoNoNo1Pro & Farm1,062,500$951,109$1,000,000$895,161$0$0$NoLien
Ilya SamsonovMoose (WPG)G231997-02-21No200 Lbs6 ft3NoNoNo2Pro & Farm1,475,000$1,320,363$1,475,000$1,320,363$0$0$No1,475,000$Lien
JC LiponMoose (WPG)RW261993-07-10No183 Lbs6 ft0NoNoNo4Pro & Farm700,000$626,613$700,000$626,613$0$0$No700,000$700,000$700,000$Lien
Joel L'EsperanceMoose (WPG)C/RW241995-08-18No201 Lbs6 ft2NoNoNo2Pro & Farm722,500$646,754$722,500$646,754$0$0$No722,500$Lien
Johnny BoychukMoose (WPG)D361984-01-19No227 Lbs6 ft2NoNoNo1Pro & Farm1,006,250$900,756$1,000,000$895,161$0$0$NoLien
Keith KinkaidMoose (WPG)G301989-07-03No195 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$1,118,952$1,250,000$1,118,952$0$0$NoLien
Markus GranlundMoose (WPG)C/LW/RW271993-04-15No183 Lbs6 ft0NoNoNo1Pro & Farm900,000$805,645$900,000$805,645$0$0$NoLien
Mason AppletonMoose (WPG)C/RW241996-01-15No193 Lbs6 ft2NoNoNo2Pro & Farm758,333$678,830$758,333$678,830$0$0$No758,333$Lien
Matt MurrayMoose (WPG)G261994-05-25No178 Lbs6 ft4NoNoNo3Pro & Farm3,800,000$3,401,613$3,750,000$3,356,855$0$0$No3,750,000$3,750,000$Lien
Mattias JanmarkMoose (WPG)C/LW271992-12-08No196 Lbs6 ft1NoNoNo2Pro & Farm800,000$716,129$800,000$716,129$0$0$No800,000$Lien
Michael StoneMoose (WPG)D301990-06-06No210 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Rasmus KupariMoose (WPG)C202000-03-15Yes185 Lbs6 ft1NoNoNo3Pro & Farm1,081,667$968,266$1,081,667$968,266$0$0$No1,081,667$1,081,667$
Sami NikuMoose (WPG)D231996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm916,666$820,564$450,000$402,823$0$0$NoLien
Scott HarringtonMoose (WPG)D271993-03-10No207 Lbs6 ft2NoNoNo2Pro & Farm675,000$604,234$675,000$604,234$0$0$No675,000$Lien
Tyler MotteMoose (WPG)LW/RW251995-03-10No188 Lbs5 ft9NoNoNo2Pro & Farm925,000$828,024$925,000$828,024$0$0$No925,000$Lien
Tyler MyersMoose (WPG)D301990-01-31No229 Lbs6 ft8NoNoNo1Pro & Farm1,000,000$895,161$1,000,000$895,161$0$0$NoLien
Zack MacEwenMoose (WPG)C/RW231996-07-08No205 Lbs6 ft3NoNoNo3Pro & Farm1,995,833$1,786,592$1,329,166$1,189,818$0$0$No995,833$995,833$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2526.20196 Lbs6 ft21.961,140,017$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Antoine RousselMattias JanmarkAdam Gaudette35122
2Tyler MotteMarkus GranlundDryden Hunt30122
3Mason AppletonJoel L'EsperanceZack MacEwen25122
4Antoine RousselMason AppletonMattias Janmark10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk35122
2Erik GudbransonDmitry Kulikov30122
3Michael StoneBrendan Smith25122
4Scott HarringtonTyler Myers10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Antoine RousselMattias JanmarkAdam Gaudette60122
2Tyler MotteMarkus GranlundDryden Hunt40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Antoine RousselMattias Janmark60122
2Adam GaudetteTyler Motte40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Antoine Roussel60122Tyler MyersJohnny Boychuk60122
2Mattias Janmark40122Erik GudbransonDmitry Kulikov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Antoine RousselMattias Janmark60122
2Adam GaudetteTyler Motte40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Antoine RousselMattias JanmarkAdam GaudetteTyler MyersJohnny Boychuk
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Antoine RousselMattias JanmarkAdam GaudetteTyler MyersJohnny Boychuk
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chase De Leo, Rasmus Kupari, Joel L'EsperanceChase De Leo, Rasmus KupariJoel L'Esperance
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Michael Stone, Brendan Smith, Scott HarringtonMichael StoneBrendan Smith, Scott Harrington
Tirs de Pénalité
Antoine Roussel, Mattias Janmark, Adam Gaudette, Tyler Motte, Markus Granlund
Gardien
#1 : Ilya Samsonov, #2 : Matt Murray


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
1Admirals31100010871201000105501100000032140.6678142200395450434929144915984918211.11%17288.24%012921161.14%10321049.05%6612353.66%2011391856110353
2Condors11000000422000000000001100000042221.0004711003954164349291410410158225.00%5180.00%012921161.14%10321049.05%6612353.66%2011391856110353
3Flames10000010211100000102110000000000021.00022400395418434929141761018900.00%5180.00%012921161.14%10321049.05%6612353.66%2011391856110353
4Monarchs11000000321110000003210000000000021.00035800395416434929141521215700.00%6266.67%112921161.14%10321049.05%6612353.66%2011391856110353
5Sharks2020000025-3000000000002020000025-300.00024600395424434929143882831800.00%14285.71%012921161.14%10321049.05%6612353.66%2011391856110353
Total833000201917241100020108242200000990100.62519325100395412443492914129351581285048.00%47882.98%112921161.14%10321049.05%6612353.66%2011391856110353
_Since Last GM Reset833000201917241100020108242200000990100.62519325100395412443492914129351581285048.00%47882.98%112921161.14%10321049.05%6612353.66%2011391856110353
_Vs Conference7330001017161311000108714220000099080.57117304700395410643492914112291481104149.76%42783.33%112921161.14%10321049.05%6612353.66%2011391856110353
_Vs Division83300010191724110001010824220000099080.50019325100395412443492914129351581285048.00%47882.98%112921161.14%10321049.05%6612353.66%2011391856110353

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
810W11932511241293515812800
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
83300201917
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4110020108
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
422000099
Derniers 10 Matchs
WLOTWOTL SOWSOL
530000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
5048.00%47882.98%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
434929143954
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
12921161.14%10321049.05%6612353.66%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2011391856110353


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 - 2020-09-272Flames1Moose2WXXSommaire du Match
2 - 2020-09-2820Moose4Condors2WSommaire du Match
4 - 2020-09-3033Monarchs2Moose3WSommaire du Match
5 - 2020-10-0141Moose2Sharks4LSommaire du Match
6 - 2020-10-0252Admirals3Moose4WXXSommaire du Match
8 - 2020-10-0462Admirals2Moose1LSommaire du Match
10 - 2020-10-0672Moose0Sharks1LSommaire du Match
12 - 2020-10-0879Moose3Admirals2WSommaire du Match
14 - 2020-10-1092Condors-Moose-
17 - 2020-10-13107Moose-Admirals-
18 - 2020-10-14115Sharks-Moose-
20 - 2020-10-16127Moose-Monarchs-
22 - 2020-10-18144Condors-Moose-
23 - 2020-10-19147Moose-Flames-
24 - 2020-10-20160Flames-Moose-
25 - 2020-10-21171Moose-Stars-
26 - 2020-10-22179Moose-Monarchs-
28 - 2020-10-24187Soldiers-Moose-
30 - 2020-10-26199Moose-IceHogs-
32 - 2020-10-28213Condors-Moose-
34 - 2020-10-30225Moose-Sound Tigers-
36 - 2020-11-01236Moose-Marlies-
38 - 2020-11-03243Stars-Moose-
40 - 2020-11-05257Moose-Rampage-
42 - 2020-11-07264Griffins-Moose-
44 - 2020-11-09276Stars-Moose-
45 - 2020-11-10291Moose-Penguins-
46 - 2020-11-11296Moose-Wolves-
47 - 2020-11-12305Admirals-Moose-
49 - 2020-11-14321Moose-Senators-
50 - 2020-11-15328Crunch-Moose-
51 - 2020-11-16339Sound Tigers-Moose-
53 - 2020-11-18354Moose-Crunch-
54 - 2020-11-19365Moose-Sharks-
55 - 2020-11-20372Sharks-Moose-
56 - 2020-11-21382Moose-Monarchs-
57 - 2020-11-22394Flames-Moose-
58 - 2020-11-23406Flames-Moose-
60 - 2020-11-25416Moose-Flames-
61 - 2020-11-26425Moose-Condors-
63 - 2020-11-28438Monarchs-Moose-
65 - 2020-11-30452Soldiers-Moose-
66 - 2020-12-01464Moose-Monsters-
67 - 2020-12-02474Moose-Rampage-
68 - 2020-12-03481Condors-Moose-
70 - 2020-12-05496Sharks-Moose-
71 - 2020-12-06507Sharks-Moose-
73 - 2020-12-08520Moose-Bruins-
75 - 2020-12-10531Moose-Flames-
76 - 2020-12-11540Moose-Monarchs-
77 - 2020-12-12548Moose-Flames-
78 - 2020-12-13553Wolf Pack-Moose-
79 - 2020-12-14567Monsters-Moose-
81 - 2020-12-16580Moose-Griffins-
82 - 2020-12-17588Admirals-Moose-
84 - 2020-12-19602Phantoms-Moose-
86 - 2020-12-21612Moose-Senators-
87 - 2020-12-22625Moose-Admirals-
88 - 2020-12-23635Senators-Moose-
91 - 2020-12-26647Moose-Wolves-
92 - 2020-12-27657Rampage-Moose-
93 - 2020-12-28666Moose-Phantoms-
94 - 2020-12-29678Marlies-Moose-
96 - 2020-12-31694Moose-Wolf Pack-
97 - 2021-01-01702Monarchs-Moose-
98 - 2021-01-02716Moose-Stars-
99 - 2021-01-03723Wolves-Moose-
101 - 2021-01-05736Moose-IceHogs-
102 - 2021-01-06743Moose-Rocket-
103 - 2021-01-07751Bruins-Moose-
105 - 2021-01-09768IceHogs-Moose-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10782Sound Tigers-Moose-
108 - 2021-01-12795Moose-Soldiers-
109 - 2021-01-13807Crunch-Moose-
111 - 2021-01-15820Monarchs-Moose-
113 - 2021-01-17835Moose-Sharks-
114 - 2021-01-18842Moose-Condors-
115 - 2021-01-19846Stars-Moose-
117 - 2021-01-21865Penguins-Moose-
118 - 2021-01-22873Moose-Admirals-
120 - 2021-01-24884Moose-Condors-
122 - 2021-01-26899Rocket-Moose-



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
37 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
679,078$ 2,850,042$ 2,624,834$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 312,140$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 111 51,210$ 5,684,310$




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
20208330002019172411000201082422000009901019325100395412443492914129351581285048.00%47882.98%112921161.14%10321049.05%6612353.66%2011391856110353
Total Saison Régulière8330002019172411000201082422000009901019325100395412443492914129351581285048.00%47882.98%112921161.14%10321049.05%6612353.66%2011391856110353