Moose
GP: 82 | W: 55 | L: 22 | OTL: 5 | P: 115
GF: 205 | GA: 141 | PP%: 13.86% | PK%: 89.14%
DG: Emmanuel Rheault | Morale : 50 | Moyenne d'Équipe : N/A
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

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
1Andrew CoglianoXX100.007843869163629061416356807286896740003311,000,000$
2Antoine RousselX100.007657718172617168456270587572736847003011,000,000$
3Brad RichardsonXX100.007844898070658058915859922580836846003511,250,000$
4Brandon SutterXX100.006355837773685665786571886378807233003111,250,001$
5Mattias JanmarkXX100.00634293827268896442695974256566675000272800,000$
6Jason SpezzaXX100.005942907079578467827370647188927015003731,950,000$
7Jujhar KhairaXX100.008666837881637960515659822561616610002511,200,000$
8Kyle TurrisX100.006141898271707676757768646676797012003011,000,000$
9Joel L'EsperanceXX100.00777581777579846278536765644545685000242722,500$
10Markus GranlundXXX100.00634187826757836344535979726566645000271900,000$
11Mason AppletonXX100.00634287807258806036576071255555645000242758,333$
12Pat MaroonXX100.008193707486628671566766622572766834003211,000,000$
13Dryden HuntXX100.00834569727156866225655570455858645000242715,000$
14Jayce HawrylukXX100.00904582676758546136726261255757661200243899,125$
15Brendan SmithXX100.008093697680568057254748772572746050003111,000,000$
16Dmitry KulikovX100.008545828074807161255248772577786350002911,000,000$
17Erik GudbransonX100.008286517686788162254949867572736350002811,062,500$
18Johnny BoychukX100.008646927482728659255148822577836450003611,006,250$
19Marc StaalX100.007845907878728358255248872581866473003312,000,000$
20Shayne GostisbehereX100.006141858666757880255253614565666348002711,000,000$
Rayé
1JC LiponX100.00646756666774785950565859554747605000264700,000$
2Daniel CarrXX100.00734388787056755325505957755959611700282750,000$
3Chase De LeoX100.00736590626573776075565865555454625000243650,000$
4Rasmus Kupari (R)X100.007569896569555653664358625544445950002031,081,667$
5Sami NikuX100.00734380756669616125634766254848615000231916,666$
6Michael StoneX100.008145857679695452255148762568696150003011,000,000$
7Scott HarringtonX100.00774487707663735925534872256061605000272675,000$
8Conor Timmins (R)X100.00716974656949475725584161394444555000213925,000$
MOYENNE D'ÉQUIPE100.0074558176736575624558577145656764420
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
1Devan Dubnyk100.005781809059555458595772727360500
2Jonathan Quick100.0071777780727065747371957681721800
Rayé
1Keith Kinkaid100.0051627879475150564848306060524400
2Eric Comrie100.0062658165626757666463304444635200
MOYENNE D'ÉQUIPE100.006071797960615764616057636562300
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/LW822222441814015137116288118.97%13140117.1049131818910142543545.93%126500000.63511000642
2Brandon SutterMoose (WPG)C/RW411622382127152476102294515.69%1078719.20410143119401141362362.50%49600000.9723012614
3Erik GudbransonMoose (WPG)D82142135161842017174118216211.86%73172321.0112921863620002335520.00%000000.4102211334
4Dmitry KulikovMoose (WPG)D82430341566067566318416.35%58174321.2741317493400000347110.00%000000.3900000023
5Kyle TurrisMoose (WPG)C301023331320125861184116.39%165021.68611171715320251621063.48%81600001.0102000432
6Markus GranlundMoose (WPG)C/LW/RW8282533133202810011728816.84%10131816.0859143332400031080046.96%23000000.5028000123
7Antoine RousselMoose (WPG)LW811714311381513070110478915.45%6143917.775491720800042664046.39%16600000.43310001433
8Jason SpezzaMoose (WPG)C/RW621316293140219088218614.77%1119219.2349132027810122243168.05%55400000.4914000322
9Johnny BoychukMoose (WPG)D8292029158951125479293911.39%61179121.845611563860221386300.00%000000.3200001033
10Dryden HuntMoose (WPG)LW/RW821216281011351137072226616.67%5105312.8525715140000092235.71%5600000.5301010216
11Andrew CoglianoMoose (WPG)LW/RW318162411300675255113814.55%662820.2867132315500071415050.00%5200000.7602000242
12Joel L'EsperanceMoose (WPG)C/RW82715221053574918920787.87%6119514.581341715700011242058.96%57500100.3712010224
13Brad RichardsonMoose (WPG)C/LW44911209300507860174915.00%869315.770441711911221004066.75%40600000.5823000241
14Michael StoneMoose (WPG)D7331518227006441951333.33%44104914.372135180110107100.00%000000.3400000121
15Brendan SmithMoose (WPG)LW/D74510151815115131353481314.71%30103814.0310172801101042040.00%500000.2900030021
16Mason AppletonMoose (WPG)C/RW826915-4805728524437.06%17559.21055161220000201041.86%21500000.4000000101
17Jujhar KhairaMoose (WPG)C/LW4176131038046513482220.59%23959.65022220000191250.00%16600000.6600000311
18Marc StaalMoose (WPG)D225494120301923101921.74%1550322.88325161190000103100.00%000000.3600000111
19Pat MaroonMoose (WPG)LW/RW17459431550112451816.67%025715.152351286000001041.67%1200000.7000001201
20Chase De LeoMoose (WPG)C52156-11001724276163.70%53957.610002250000330055.62%17800000.3000000000
21Jayce HawrylukMoose (WPG)C/RW37246-112405744214229.52%040510.952247940000780035.92%42600000.3000000100
22JC LiponMoose (WPG)RW28235014024142610117.69%137813.51000170001342048.84%4300000.2600000020
23Scott HarringtonMoose (WPG)D47134-1200161431333.33%84088.680000800004300100.00%100000.2000000010
24Daniel CarrMoose (WPG)LW/RW171231206612168.33%022313.15112322000060035.29%1700000.2700000100
25Sami NikuMoose (WPG)D200332401190110.00%821310.6700002000020000.00%000000.2800000000
26Conor TimminsMoose (WPG)D15022220830010.00%4805.340000000004000.00%000000.5000000000
27Rasmus KupariMoose (WPG)C33022320552220.00%11293.910110360000220052.46%6100000.3100000000
28Tyler MotteJetsLW/RW5101-12008671314.29%19519.030003210001150025.00%400000.2100000000
29Shayne GostisbehereMoose (WPG)D1000100021020.00%01414.780000000000000.00%000000.0000000000
Stats d'équipe Total ou en Moyenne142718732451121611437513621362143839599113.00%3782196215.396911618547336255611383207441654.32%574400100.471648276454345
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
1Jonathan QuickMoose (WPG)1814400.9141.22108305222560110.8005180012
2Anders NilssonJets44000.8652.502400010740000.000047000
3Devan DubnykMoose (WPG)11000.9092.0060002220000.000013000
4Eric ComrieMoose (WPG)30001.0000.0047000220000.0000053000
Stats d'équipe Total ou en Moyenne2619400.9091.43143105343740110.80052363012


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$8,065$1,000,000$8,065$0$0$NoLien
Antoine RousselMoose (WPG)LW301989-11-20No195 Lbs6 ft0NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Brad RichardsonMoose (WPG)C/LW351985-02-03No190 Lbs6 ft0NoNoNo1Pro & Farm1,250,000$10,081$1,250,000$10,081$0$0$NoLien
Brandon SutterMoose (WPG)C/RW311989-02-14No191 Lbs6 ft3NoNoNo1Pro & Farm1,250,001$10,081$1,000,000$8,065$0$0$NoLien
Brendan SmithMoose (WPG)LW/D311989-02-07No211 Lbs6 ft2NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Chase De LeoMoose (WPG)C241995-10-25No185 Lbs5 ft9NoNoNo3Pro & Farm650,000$5,242$650,000$5,242$0$0$No650,000$650,000$Lien
Conor TimminsMoose (WPG)D211998-09-18Yes184 Lbs6 ft2NoNoNo3Pro & Farm925,000$7,460$925,000$7,460$0$0$No925,000$925,000$
Daniel CarrMoose (WPG)LW/RW281991-11-01No193 Lbs6 ft0NoNoNo2Pro & Farm750,000$6,048$750,000$6,048$0$0$No750,000$Lien
Devan DubnykMoose (WPG)G341986-05-03No218 Lbs6 ft6NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Dmitry KulikovMoose (WPG)D291990-10-29No204 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Dryden HuntMoose (WPG)LW/RW241995-11-24No197 Lbs6 ft0NoNoNo2Pro & Farm715,000$5,766$715,000$5,766$0$0$No715,000$Lien
Eric ComrieMoose (WPG)G241995-07-05No175 Lbs6 ft1NoNoNo3Pro & Farm650,000$5,242$650,000$5,242$0$0$No650,000$650,000$Lien
Erik GudbransonMoose (WPG)D281992-01-07No220 Lbs6 ft5NoNoNo1Pro & Farm1,062,500$8,569$1,000,000$8,065$0$0$NoLien
JC LiponMoose (WPG)RW261993-07-10No183 Lbs6 ft0NoNoNo4Pro & Farm700,000$5,645$700,000$5,645$0$0$No700,000$700,000$700,000$Lien
Jason SpezzaMoose (WPG)C/RW371983-06-13No214 Lbs6 ft3NoNoNo3Pro & Farm1,950,000$15,726$700,000$5,645$0$0$No700,000$700,000$Lien
Jayce HawrylukMoose (WPG)C/RW241996-01-01No186 Lbs5 ft11NoNoNo3Pro & Farm899,125$7,251$874,125$7,049$0$0$No874,125$874,125$Lien
Joel L'EsperanceMoose (WPG)C/RW241995-08-18No201 Lbs6 ft2NoNoNo2Pro & Farm722,500$5,827$722,500$5,827$0$0$No722,500$Lien
Johnny BoychukMoose (WPG)D361984-01-19No227 Lbs6 ft2NoNoNo1Pro & Farm1,006,250$8,115$1,000,000$8,065$0$0$NoLien
Jonathan QuickMoose (WPG)G341986-01-20No218 Lbs6 ft1NoNoNo1Pro & Farm2,250,000$18,145$1,000,000$8,065$0$0$NoLien
Jujhar KhairaMoose (WPG)C/LW251994-08-13No214 Lbs6 ft4NoNoNo1Pro & Farm1,200,000$9,677$1,200,000$9,677$0$0$NoLien
Keith KinkaidMoose (WPG)G301989-07-03No195 Lbs6 ft3NoNoNo1Pro & Farm1,250,000$10,081$1,250,000$10,081$0$0$NoLien
Kyle TurrisMoose (WPG)C301989-08-14No190 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Marc StaalMoose (WPG)D331987-01-12No209 Lbs6 ft4NoNoNo1Pro & Farm2,000,000$16,129$2,000,000$16,129$0$0$NoLien
Markus GranlundMoose (WPG)C/LW/RW271993-04-15No183 Lbs6 ft0NoNoNo1Pro & Farm900,000$7,258$900,000$7,258$0$0$NoLien
Mason AppletonMoose (WPG)C/RW241996-01-15No193 Lbs6 ft2NoNoNo2Pro & Farm758,333$6,116$758,333$6,116$0$0$No758,333$Lien
Mattias JanmarkMoose (WPG)C/LW271992-12-08No196 Lbs6 ft1NoNoNo2Pro & Farm800,000$6,452$800,000$6,452$0$0$No800,000$Lien
Michael StoneMoose (WPG)D301990-06-06No210 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Pat MaroonMoose (WPG)LW/RW321988-04-22No225 Lbs6 ft3NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Rasmus KupariMoose (WPG)C202000-03-15Yes185 Lbs6 ft1NoNoNo3Pro & Farm1,081,667$8,723$1,081,667$8,723$0$0$No1,081,667$1,081,667$
Sami NikuMoose (WPG)D231996-10-10No176 Lbs6 ft1NoNoNo1Pro & Farm916,666$7,392$450,000$3,629$0$0$NoLien
Scott HarringtonMoose (WPG)D271993-03-10No207 Lbs6 ft2NoNoNo2Pro & Farm675,000$5,444$675,000$5,444$0$0$No675,000$Lien
Shayne GostisbehereMoose (WPG)D271993-04-19No180 Lbs5 ft11NoNoNo1Pro & Farm1,000,000$8,065$1,000,000$8,065$0$0$NoLien
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
3228.38198 Lbs6 ft11.661,042,564$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andrew CoglianoKyle TurrisBrandon Sutter35122
2Pat MaroonJason SpezzaMarkus Granlund30122
3Antoine RousselBrad RichardsonDryden Hunt25122
4Jujhar KhairaMattias JanmarkJoel L'Esperance10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marc StaalJohnny Boychuk35122
2Erik GudbransonDmitry Kulikov30122
3Shayne GostisbehereBrendan Smith25122
4Marc StaalJohnny Boychuk10122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Andrew CoglianoKyle TurrisBrandon Sutter60122
2Pat MaroonJason SpezzaMarkus Granlund40122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marc StaalJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
1Kyle TurrisAndrew Cogliano60122
2Jason SpezzaBrandon Sutter40122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marc StaalJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
1Kyle Turris60122Marc StaalJohnny Boychuk60122
2Andrew Cogliano40122Erik GudbransonDmitry Kulikov40122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
1Kyle TurrisAndrew Cogliano60122
2Jason SpezzaBrandon Sutter40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Marc StaalJohnny Boychuk60122
2Erik GudbransonDmitry Kulikov40122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andrew CoglianoKyle TurrisJason SpezzaMarc StaalJohnny Boychuk
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Andrew CoglianoKyle TurrisJason SpezzaMarc StaalJohnny Boychuk
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Mason Appleton, Jayce Hawryluk, Brad RichardsonMason Appleton, Jayce HawrylukBrad Richardson
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Shayne Gostisbehere, Brendan Smith, Erik GudbransonShayne GostisbehereBrendan Smith, Erik Gudbranson
Tirs de Pénalité
Kyle Turris, Andrew Cogliano, Jason Spezza, Brandon Sutter, Pat Maroon
Gardien
#1 : Jonathan Quick, #2 : Devan Dubnyk


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
1Admirals85200010211011412000108804400000013211120.7502136570373655818153540501474721163815514255610.91%42392.86%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
2Bruins22000000752110000004311100000032141.00071320007365581832540501474723411774410220.00%19194.74%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
3Condors85300000221394130000057-24400000017611100.62522355701736558181725405014747210435123130641421.88%55885.45%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
4Crunch320000101055220000006241000001043161.000101626007365581859540501474726223566919315.79%28292.86%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
5Flames8320002116142411000209634210000178-1110.688162238007365581813154050147472149571281594149.76%62788.71%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
6Griffins22000000404110000002021100000020241.0004812027365581849540501474722810144518316.67%70100.00%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
7IceHogs32000001945110000003032100000164250.83391625027365581849540501474723911414717741.18%17194.12%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
8Marlies21000001550110000002111000000134-130.750510150073655818545405014747238922401218.33%11372.73%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
9Monarchs85200010171344220000089-143000010945120.7501726430173655818160540501474721123711111860610.00%49491.84%21301230956.34%1167213654.63%608112753.95%2142148218206071024537
10Monsters20000020532100000102111000001032141.0005510007365581842540501474723185340900.00%11190.91%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
11Penguins2020000025-31010000013-21010000012-100.00024610736558183254050147472288224620210.00%9188.89%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
12Phantoms21000010734110000003031000001043141.0007121901736558183154050147472281630371317.69%14192.86%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
13Rampage320000011064110000004222100000164250.833101727007365581872540501474726430385616318.75%18288.89%11301230956.34%1167213654.63%608112753.95%2142148218206071024537
14Rocket22000000413110000003121100000010141.00047110173655818385405014747220626411516.67%80100.00%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
15Senators3120000078-11010000023-12110000055020.3337132000736558186354050147472511246591516.67%20575.00%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
16Sharks843000011719-24210000178-1422000001011-190.5631730470073655818131540501474721423012212932618.75%54983.33%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
17Soldiers330000001411322000000120121100000021161.00014243802736558186454050147472419435621314.29%19194.74%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
18Sound Tigers3120000079-2211000005501010000024-220.3337121900736558184654050147472621146681500.00%23291.30%11301230956.34%1167213654.63%608112753.95%2142148218206071024537
19Stars5410000015873300000010552110000053280.800152540017365581875540501474728929789924520.83%35294.29%11301230956.34%1167213654.63%608112753.95%2142148218206071024537
20Wolf Pack2020000015-41010000014-31010000001-100.0001230073655818335405014747233132439800.00%12283.33%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
21Wolves311010005411010000001-12100100053240.667581300736558185054050147472541744591417.14%21385.71%01301230956.34%1167213654.63%608112753.95%2142148218206071024537
Total824622010852051416441221400041976928412480104410872361150.701205341546114736558181536540501474721325420129915234986913.86%5345889.14%51301230956.34%1167213654.63%608112753.95%2142148218206071024537
_Since Last GM Reset824622010852051416441221400041976928412480104410872361150.701205341546114736558181536540501474721325420129915234986913.86%5345889.14%51301230956.34%1167213654.63%608112753.95%2142148218206071024537
_Vs Conference543414010231418754271510000116445192719401012774235770.713141237378012736558181021540501474728512578159493365416.07%3403589.71%51301230956.34%1167213654.63%608112753.95%2142148218206071024537
_Vs Division402012000219369242079000113738-12013300010563125450.563931492420573655818747540501474726231976396782523614.29%2623188.17%21301230956.34%1167213654.63%608112753.95%2142148218206071024537

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
82115W32053415461536132542012991523114
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
8246221085205141
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
41221400419769
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
41248104410872
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
4986913.86%5345889.14%5
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
5405014747273655818
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
1301230956.34%1167213654.63%608112753.95%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
2142148218206071024537


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 - 2020-12-12548Moose3Flames2WSommaire du Match
78 - 2020-12-13553Wolf Pack4Moose1LSommaire du Match
79 - 2020-12-14567Monsters1Moose2WXXSommaire du Match
81 - 2020-12-16580Moose2Griffins0WSommaire du Match
82 - 2020-12-17588Admirals1Moose2WSommaire du Match
84 - 2020-12-19602Phantoms0Moose3WSommaire du Match
86 - 2020-12-21612Moose0Senators4LSommaire du Match
87 - 2020-12-22625Moose4Admirals0WSommaire du Match
88 - 2020-12-23635Senators3Moose2LSommaire du Match
91 - 2020-12-26647Moose2Wolves1WSommaire du Match
92 - 2020-12-27657Rampage2Moose4WSommaire du Match
93 - 2020-12-28666Moose4Phantoms3WXXSommaire du Match
94 - 2020-12-29678Marlies1Moose2WSommaire du Match
96 - 2020-12-31694Moose0Wolf Pack1LSommaire du Match
97 - 2021-01-01702Monarchs2Moose1LSommaire du Match
98 - 2021-01-02716Moose3Stars0WSommaire du Match
99 - 2021-01-03723Wolves1Moose0LSommaire du Match
101 - 2021-01-05736Moose3IceHogs0WSommaire du Match
102 - 2021-01-06743Moose1Rocket0WSommaire du Match
103 - 2021-01-07751Bruins3Moose4WSommaire du Match
105 - 2021-01-09768IceHogs0Moose3WSommaire du Match
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
106 - 2021-01-10782Sound Tigers3Moose4WSommaire du Match
108 - 2021-01-12795Moose2Soldiers1WSommaire du Match
109 - 2021-01-13807Crunch1Moose3WSommaire du Match
111 - 2021-01-15820Monarchs3Moose4WSommaire du Match
113 - 2021-01-17835Moose4Sharks3WSommaire du Match
114 - 2021-01-18842Moose5Condors3WSommaire du Match
115 - 2021-01-19846Stars2Moose5WSommaire du Match
117 - 2021-01-21865Penguins3Moose1LSommaire du Match
118 - 2021-01-22873Moose4Admirals0WSommaire du Match
120 - 2021-01-24884Moose6Condors1WSommaire du Match
122 - 2021-01-26899Rocket1Moose3WSommaire du Match



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des Billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacitéPopularité de l'Équipe
0 0 - 0.00% 0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
6,330,669$ 3,336,205$ 3,005,163$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 2,858,906$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 1 55,131$ 55,131$




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