Moose

GP: 50 | W: 30 | L: 15 | OTL: 5 | P: 65
GF: 118 | GA: 91 | PP%: 12.72% | PK%: 89.68%
DG: Emmanuel Rheault | Morale : 50 | Moyenne d'Équipe : N/A
Prochain matchs #548 vs Flames
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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 SPÂgeContratSalaire
1Antoine RousselX100.007657718172617168456270587572736847003011,000,000$
2Brad RichardsonXX100.007844898070658058915859922580836846003511,250,000$
3Brandon SutterXX100.006355837773685665786571886378807233003111,250,001$
4Mattias JanmarkXX100.00634293827268896442695974256566675000272800,000$
5Jason SpezzaXX100.005942907079578467827370647188927015003731,950,000$
6Jujhar KhairaXX100.008666837881637960515659822561616610002511,200,000$
7Joel L'EsperanceXX100.00777581777579846278536765644545685000242722,500$
8Markus GranlundXXX100.00634187826757836344535979726566645000271900,000$
9Zack MacEwenXX100.008999686680547258445680612545457150002331,995,833$
10Mason AppletonXX100.00634287807258806036576071255555645000242758,333$
11Chase De LeoX100.00736590626573776075565865555454625000243650,000$
12Dryden HuntXX100.00834569727156866225655570455858645000242715,000$
13Brendan SmithXX100.008093697680568057254748772572746050003111,000,000$
14Dmitry KulikovX100.008545828074807161255248772577786350002911,000,000$
15Erik GudbransonX100.008286517686788162254949867572736350002811,062,500$
16Sami NikuX100.00734380756669616125634766254848615000231916,666$
17Johnny BoychukX100.008646927482728659255148822577836450003611,006,250$
18Michael StoneX100.008145857679695452255148762568696150003011,000,000$
19Tyler MyersX100.008056798189839169255650795375776646003011,000,000$
Rayé
1Andrew CoglianoXXHO7843869163629061416356807286896740003311,000,000$
2JC LiponX100.00646756666774785950565859554747605000264700,000$
3Daniel CarrXX100.00734388787056755325505957755959611700282750,000$
4Rasmus Kupari (R)X100.007569896569555653664358625544445950002031,081,667$
5Scott HarringtonX100.00774487707663735925534872256061605000272675,000$
6Conor Timmins (R)X100.00716974656949475725584161394444555000213925,000$
MOYENNE D'ÉQUIPE100.0075578075746575604457577246646564440
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
2Eric Comrie100.0062658165626757666463304444635000
Rayé
1Keith Kinkaid100.0051627879475150564848306060525000
MOYENNE D'ÉQUIPE100.005868787357605962595747545560500
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
1Mattias JanmarkMoose (WPG)C/LW50181735151001110376235823.68%11106321.2649131718410142252546.86%102000000.66511000432
2Antoine RousselMoose (WPG)LW491592411555964880275318.75%3104021.235491619700042262042.45%13900000.46310001323
3Erik GudbransonMoose (WPG)D501111226127151084476143814.47%43102720.549514522060002207420.00%000000.4302201312
4Johnny BoychukMoose (WPG)D50614208580513849212112.24%39106421.29347362190110240100.00%000000.3800000023
5Dryden HuntMoose (WPG)LW/RW50911206895794852184617.31%374414.8825715140000092235.00%4000000.5401010215
6Dmitry KulikovMoose (WPG)D502171974404140409215.00%36103220.64257301820000208100.00%000000.3700000011
7Markus GranlundMoose (WPG)C/LW/RW5021719918018627516462.67%783716.761672016700031080048.26%20100000.4528000011
8Tyler MyersMoose (WPG)D4951217651588635224459.62%33117123.91336382260001252010.00%000000.2900001133
9Jason SpezzaMoose (WPG)C/RW30610162806455194711.76%161120.392571012510111311067.95%23400000.5203000120
10Joel L'EsperanceMoose (WPG)C/RW5031215537550736418654.69%491118.231341514700011191059.89%55100100.3312010102
11Brandon SutterMoose (WPG)C/RW986147756272771129.63%319121.253146300110430366.84%18700001.4611001411
12Mason AppletonMoose (WPG)C/RW506713-5804687118398.45%168813.78044101000000171041.09%20200000.3800000101
13Brendan SmithMoose (WPG)LW/D50191012104108028205125.00%1767413.480002160110790040.00%500000.3000020011
14Michael StoneMoose (WPG)D42191013420352943725.00%2557413.6810129011066100.00%000000.3500000011
15Brad RichardsonMoose (WPG)C/LW124484601829196821.05%024520.460224481011483067.42%22100000.6512000120
16Zack MacEwenMoose (WPG)C/RW50617410535862254113411.11%266513.3201111890000142342.16%20400000.2101313311
17Jujhar KhairaMoose (WPG)C/LW92463100152495722.22%013715.32022219000170052.53%9900000.8700000110
18Chase De LeoMoose (WPG)C50156-11001724276163.70%53927.850002240000320056.25%17600000.3100000000
19JC LiponMoose (WPG)RW28235014024142610117.69%137813.51000170001342048.84%4300000.2600000020
20Scott HarringtonMoose (WPG)D47134-1200161431333.33%84088.680000800004300100.00%100000.2000000010
21Daniel CarrMoose (WPG)LW/RW171231206612168.33%022313.15112322000060035.29%1700000.2700000100
22Conor TimminsMoose (WPG)D15022220830010.00%4805.340000000004000.00%000000.5000000000
23Rasmus KupariMoose (WPG)C33022320552220.00%11293.910110360000220052.46%6100000.3100000000
24Sami NikuMoose (WPG)D8011-100330000.00%2617.690000100006000.00%000000.3300000000
25Tyler MotteJetsLW/RW5101-12008671314.29%19519.030003210001150025.00%400000.2100000000
Stats d'équipe Total ou en Moyenne9031111882991158498587986689625560012.39%2501445016.003761982952233347202175231652.69%340500100.411341557262627
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
1Matt MurrayMoose (WPG)43271150.8971.68257946726980200.68732437224
2Eric ComrieMoose (WPG)10001.0000.0020000100000.0000033000
Stats d'équipe Total ou en Moyenne44271150.8981.66260046727080200.687324340224


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
Andrew CoglianoMoose (WPG)LW/RW331987-06-14No177 Lbs5 ft10NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Antoine RousselMoose (WPG)LW301989-11-20No195 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Brad RichardsonMoose (WPG)C/LW351985-02-03No190 Lbs6 ft0NoNoNo1Pro & Farm1,250,000$483,871$1,250,000$483,871$0$0$NoLien
Brandon SutterMoose (WPG)C/RW311989-02-14No191 Lbs6 ft3NoNoNo1Pro & Farm1,250,001$483,871$1,000,000$387,097$0$0$NoLien
Brendan SmithMoose (WPG)LW/D311989-02-07No211 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Chase De LeoMoose (WPG)C241995-10-25No185 Lbs5 ft9NoNoNo3Pro & Farm650,000$251,613$650,000$251,613$0$0$No650,000$650,000$Lien
Conor TimminsMoose (WPG)D211998-09-18Yes184 Lbs6 ft2NoNoNo3Pro & Farm925,000$358,065$925,000$358,065$0$0$No925,000$925,000$
Daniel CarrMoose (WPG)LW/RW281991-11-01No193 Lbs6 ft0NoNoNo2Pro & Farm750,000$290,323$750,000$290,323$0$0$No750,000$Lien
Dmitry KulikovMoose (WPG)D291990-10-29No204 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Dryden HuntMoose (WPG)LW/RW241995-11-24No197 Lbs6 ft0NoNoNo2Pro & Farm715,000$276,774$715,000$276,774$0$0$No715,000$Lien
Eric ComrieMoose (WPG)G241995-07-05No175 Lbs6 ft1NoNoNo3Pro & Farm650,000$251,613$650,000$251,613$0$0$No650,000$650,000$Lien
Erik GudbransonMoose (WPG)D281992-01-07No220 Lbs6 ft5NoNoNo1Pro & Farm1,062,500$411,290$1,000,000$387,097$0$0$NoLien
JC LiponMoose (WPG)RW261993-07-10No183 Lbs6 ft0NoNoNo4Pro & Farm700,000$270,968$700,000$270,968$0$0$No700,000$700,000$700,000$Lien
Jason SpezzaMoose (WPG)C/RW371983-06-13No214 Lbs6 ft3NoNoNo3Pro & Farm1,950,000$754,839$700,000$270,968$0$0$No700,000$700,000$Lien
Joel L'EsperanceMoose (WPG)C/RW241995-08-18No201 Lbs6 ft2NoNoNo2Pro & Farm722,500$279,677$722,500$279,677$0$0$No722,500$Lien
Johnny BoychukMoose (WPG)D361984-01-19No227 Lbs6 ft2NoNoNo1Pro & Farm1,006,250$389,516$1,000,000$387,097$0$0$NoLien
Jujhar KhairaMoose (WPG)C/LW251994-08-13No214 Lbs6 ft4NoNoNo1Pro & Farm1,200,000$464,516$1,200,000$464,516$0$0$NoLien
Keith KinkaidMoose (WPG)G301989-07-03No195 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$483,871$1,250,000$483,871$0$0$NoLien
Markus GranlundMoose (WPG)C/LW/RW271993-04-15No183 Lbs6 ft0NoNoNo1Pro & Farm900,000$348,387$900,000$348,387$0$0$NoLien
Mason AppletonMoose (WPG)C/RW241996-01-15No193 Lbs6 ft2NoNoNo2Pro & Farm758,333$293,548$758,333$293,548$0$0$No758,333$Lien
Matt MurrayMoose (WPG)G261994-05-25No178 Lbs6 ft4NoNoNo3Pro & Farm3,800,000$1,470,968$3,750,000$1,451,613$0$0$No3,750,000$3,750,000$Lien
Mattias JanmarkMoose (WPG)C/LW271992-12-08No196 Lbs6 ft1NoNoNo2Pro & Farm800,000$309,677$800,000$309,677$0$0$No800,000$Lien
Michael StoneMoose (WPG)D301990-06-06No210 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Rasmus KupariMoose (WPG)C202000-03-15Yes185 Lbs6 ft1NoNoNo3Pro & Farm1,081,667$418,710$1,081,667$418,710$0$0$No1,081,667$1,081,667$
Sami NikuMoose (WPG)D231996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm916,666$354,838$450,000$174,194$0$0$NoLien
Scott HarringtonMoose (WPG)D271993-03-10No207 Lbs6 ft2NoNoNo2Pro & Farm675,000$261,290$675,000$261,290$0$0$No675,000$Lien
Tyler MyersMoose (WPG)D301990-01-31No229 Lbs6 ft8NoNoNo1Pro & Farm1,000,000$387,097$1,000,000$387,097$0$0$NoLien
Zack MacEwenMoose (WPG)C/RW231996-07-08No205 Lbs6 ft3NoNoNo3Pro & Farm1,995,833$772,581$1,329,166$514,516$0$0$No995,833$995,833$Lien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2827.61197 Lbs6 ft21.821,107,455$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brad RichardsonBrandon SutterJason Spezza35122
2Antoine RousselMattias JanmarkMarkus Granlund30122
3Dryden HuntJujhar KhairaJoel L'Esperance25122
4Brandon SutterZack MacEwenMason Appleton10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk35122
2Erik GudbransonDmitry Kulikov30122
3Michael StoneBrendan Smith25122
4Sami NikuTyler Myers10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Brad RichardsonBrandon SutterJason Spezza60122
2Antoine RousselMattias JanmarkMarkus Granlund40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Brandon SutterJason Spezza60122
2Brad RichardsonAntoine Roussel40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Brandon Sutter60122Tyler MyersJohnny Boychuk60122
2Jason Spezza40122Erik GudbransonDmitry Kulikov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Brandon SutterJason Spezza60122
2Brad RichardsonAntoine Roussel40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Tyler MyersJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brad RichardsonBrandon SutterJason SpezzaTyler MyersJohnny Boychuk
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Brad RichardsonBrandon SutterJason SpezzaTyler MyersJohnny Boychuk
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Chase De Leo, Jujhar Khaira, Joel L'EsperanceChase De Leo, Jujhar KhairaJoel L'Esperance
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Brendan Smith, Sami Niku, Dmitry KulikovBrendan SmithMichael Stone, Sami Niku
Tirs de Pénalité
Brandon Sutter, Jason Spezza, Brad Richardson, Antoine Roussel, Mattias Janmark
Gardien
#1 : Matt Murray, #2 : Eric Comrie


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
1Admirals5220001011923020001067-12200000052360.600111930013538381587309287280638626122863026.67%29293.10%0758138354.81%706135152.26%34168849.56%12808761143376634330
2Bruins11000000321000000000001100000032121.0003690035383815163092872806313245177114.29%80100.00%0758138354.81%706135152.26%34168849.56%12808761143376634330
3Condors6330000011924130000057-22200000062460.50011162701353838151073092872806375261059040717.50%46589.13%0758138354.81%706135152.26%34168849.56%12808761143376634330
4Crunch21000010743110000003121000001043141.00071118003538381536309287280635015483310220.00%24195.83%0758138354.81%706135152.26%34168849.56%12808761143376634330
5Flames7220002113121411000209633110000146-290.643131831003538381511530928728063133491121413438.82%54787.04%0758138354.81%706135152.26%34168849.56%12808761143376634330
6Griffins11000000202110000002020000000000021.000246013538381522309287280631042169222.22%10100.00%0758138354.81%706135152.26%34168849.56%12808761143376634330
7IceHogs1000000134-1000000000001000000134-110.5003690035383815143092872806319416195360.00%8187.50%0758138354.81%706135152.26%34168849.56%12808761143376634330
8Marlies1000000134-1000000000001000000134-110.500369003538381525309287280632131225500.00%6266.67%0758138354.81%706135152.26%34168849.56%12808761143376634330
9Monarchs6410001012842110000034-143000010945100.833121729013538381511530928728063822583994249.52%36391.67%1758138354.81%706135152.26%34168849.56%12808761143376634330
10Monsters10000010321000000000001000001032121.000336003538381519309287280631363511300.00%30100.00%0758138354.81%706135152.26%34168849.56%12808761143376634330
11Penguins1010000012-1000000000001010000012-100.0001230035383815193092872806313614211119.09%6183.33%0758138354.81%706135152.26%34168849.56%12808761143376634330
12Rampage21000001642000000000002100000164230.750610160035383815443092872806352232639900.00%12191.67%1758138354.81%706135152.26%34168849.56%12808761143376634330
13Senators11000000514000000000001100000051421.00059140035383815273092872806321516195120.00%70100.00%0758138354.81%706135152.26%34168849.56%12808761143376634330
14Sharks733000011316-34210000178-13120000068-270.5001324370035383815112309287280631122710610929413.79%47785.11%0758138354.81%706135152.26%34168849.56%12808761143376634330
15Soldiers220000001201222000000120120000000000041.00012203202353838154830928728063262254014321.43%100100.00%0758138354.81%706135152.26%34168849.56%12808761143376634330
16Sound Tigers2020000036-31010000012-11010000024-200.000369003538381525309287280634673449900.00%17194.12%1758138354.81%706135152.26%34168849.56%12808761143376634330
17Stars32100000761220000005321010000023-140.66771118003538381549309287280634919406514321.43%18288.89%0758138354.81%706135152.26%34168849.56%12808761143376634330
Total50231501065118912724119000315338152612601034655312650.6501181923100635383815896309287280638392548558912833612.72%3393589.68%3758138354.81%706135152.26%34168849.56%12808761143376634330
18Wolves10001000321000000000001000100032121.000347003538381516309287280631851412700.00%7271.43%0758138354.81%706135152.26%34168849.56%12808761143376634330
_Since Last GM Reset50231501065118912724119000315338152612601034655312650.6501181923100635383815896309287280638392548558912833612.72%3393589.68%3758138354.81%706135152.26%34168849.56%12808761143376634330
_Vs Conference3618120102383641919980001141311017940101242339450.625831372200635383815639309287280635751685736242082813.46%2312489.61%3758138354.81%706135152.26%34168849.56%12808761143376634330
_Vs Division31121100021605461748000113032-214830001030228290.46860941540335383815536309287280634881535285251752011.43%2122488.68%1758138354.81%706135152.26%34168849.56%12808761143376634330

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
5065W911819231089683925485589106
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
502315106511891
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
2411900315338
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
2612610346553
Derniers 10 Matchs
WLOTWOTL SOWSOL
910000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
2833612.72%3393589.68%3
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
3092872806335383815
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
758138354.81%706135152.26%34168849.56%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
12808761143376634330


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 - 2020-10-1092Condors2Moose1LSommaire du Match
17 - 2020-10-13107Moose2Admirals0WSommaire du Match
18 - 2020-10-14115Sharks3Moose1LSommaire du Match
20 - 2020-10-16127Moose2Monarchs1WSommaire du Match
22 - 2020-10-18144Condors2Moose0LSommaire du Match
23 - 2020-10-19147Moose1Flames3LSommaire du Match
24 - 2020-10-20160Flames2Moose3WXXSommaire du Match
25 - 2020-10-21171Moose2Stars3LSommaire du Match
26 - 2020-10-22179Moose1Monarchs0WSommaire du Match
28 - 2020-10-24187Soldiers0Moose5WSommaire du Match
30 - 2020-10-26199Moose3IceHogs4LXXSommaire du Match
32 - 2020-10-28213Condors2Moose1LSommaire du Match
34 - 2020-10-30225Moose2Sound Tigers4LSommaire du Match
36 - 2020-11-01236Moose3Marlies4LXXSommaire du Match
38 - 2020-11-03243Stars1Moose2WSommaire du Match
40 - 2020-11-05257Moose1Rampage2LXXSommaire du Match
42 - 2020-11-07264Griffins0Moose2WSommaire du Match
44 - 2020-11-09276Stars2Moose3WSommaire du Match
45 - 2020-11-10291Moose1Penguins2LSommaire du Match
46 - 2020-11-11296Moose3Wolves2WXSommaire du Match
47 - 2020-11-12305Admirals2Moose1LSommaire du Match
49 - 2020-11-14321Moose5Senators1WSommaire du Match
50 - 2020-11-15328Crunch1Moose3WSommaire du Match
51 - 2020-11-16339Sound Tigers2Moose1LSommaire du Match
53 - 2020-11-18354Moose4Crunch3WXXSommaire du Match
54 - 2020-11-19365Moose4Sharks3WSommaire du Match
55 - 2020-11-20372Sharks2Moose1LXXSommaire du Match
56 - 2020-11-21382Moose2Monarchs1WXXSommaire du Match
57 - 2020-11-22394Flames2Moose1LSommaire du Match
58 - 2020-11-23406Flames1Moose3WSommaire du Match
60 - 2020-11-25416Moose1Flames2LXXSommaire du Match
61 - 2020-11-26425Moose2Condors0WSommaire du Match
63 - 2020-11-28438Monarchs2Moose0LSommaire du Match
65 - 2020-11-30452Soldiers0Moose7WSommaire du Match
66 - 2020-12-01464Moose3Monsters2WXXSommaire du Match
67 - 2020-12-02474Moose5Rampage2WSommaire du Match
68 - 2020-12-03481Condors1Moose3WSommaire du Match
70 - 2020-12-05496Sharks2Moose3WSommaire du Match
71 - 2020-12-06507Sharks1Moose2WSommaire du Match
73 - 2020-12-08520Moose3Bruins2WSommaire du Match
75 - 2020-12-10531Moose2Flames1WSommaire du Match
76 - 2020-12-11540Moose4Monarchs2WSommaire du Match
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
17 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
3,796,863$ 3,000,875$ 2,725,667$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 1,651,701$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 48 52,426$ 2,516,448$




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