Connexion

Moose
GP: 10 | W: 3 | L: 5 | OTL: 2 | P: 8
GF: 21 | GA: 38 | PP%: 14.00% | PK%: 80.00%
DG: dispo | Morale : 50 | Moyenne d’équipe : N/A
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Centre de jeu
Moose
3-5-2, 8pts
2
FINAL
4 Gulls
5-4-1, 11pts
Team Stats
W1SéquenceL2
2-2-1Fiche domicile2-2-1
1-3-1Fiche domicile3-2-0
3-5-2Derniers 10 matchs5-4-1
2.10Buts par match 2.50
3.80Buts contre par match 2.80
14.00%Pourcentage en avantage numérique19.30%
80.00%Pourcentage en désavantage numérique90.20%
Barracuda
3-6-1, 7pts
2
FINAL
4 Moose
3-5-2, 8pts
Team Stats
L1SéquenceW1
2-3-0Fiche domicile2-2-1
1-3-1Fiche domicile1-3-1
3-6-1Derniers 10 matchs3-5-2
2.20Buts par match 2.10
3.20Buts contre par match 3.80
14.52%Pourcentage en avantage numérique14.00%
80.33%Pourcentage en désavantage numérique80.00%
Meneurs d'équipe
Buts
Jujhar Khaira
4
Passes
Simon Ryfors
4
Points
Jujhar Khaira
6
Plus/Moins
Matt Kiersted
2
Victoires
Eric Comrie
2
Pourcentage d’arrêts
Olle Eriksson Ek
1

Statistiques d’équipe
Buts pour
21
2.10 GFG
Tirs pour
197
19.70 Avg
Pourcentage en avantage numérique
14.0%
7 GF
Début de zone offensive
39.6%
Buts contre
38
3.80 GAA
Tirs contre
216
21.60 Avg
Pourcentage en désavantage numérique
80.0%%
14 GA
Début de la zone défensive
40.5%
Informations de l'équipe

Directeur généraldispo
EntraîneurSheldon Keefe
DivisionDivision 5
ConférenceConference 2
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro23
Équipe Mineure21
Limite contact 44 / 60
Espoirs13


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
1Justin Richards (R)93XX100.007169756369778161766256625344446250002511,425,000$
2David Cotton83X100.008075926575535450634748644644445650002611,350,000$
3Cole Smith (R)91XX100.00949776657764856025655784255454675000273750,000$
4Tim Gettinger (R)0XX100.0083838466836769625060606857444464500N0251750,000$
5Jujhar Khaira16XX100.008686827882675968696362832565666950002921,200,000$
6Kyle Olson33X100.00666472636455584750444456424444515000241950,000$
7Otto Koivula0XXX100.0080817771817376617655626759464665500N0251800,000$
8Patrick Maroon0XX100.0087995072895698613060576025788662500N03511,000,000$
9Simon Ryfors (R)0XXX100.0072658763658388658061656362444467500N0261750,000$
10Dryden Hunt29XX100.00927981727151896034505861416566625000273762,500$
11Scott Perunovich (R)48X100.006761827861535257255842594044455650002522,175,000$
12Tucker Poolman37X100.008173817873454753594545763760615150003023,500,000$
13Matt Kiersted (R)73X100.006942907167538758255148672545455950002511,350,000$
14Ben Harpur71X100.00807785658664615525504771256465585000281750,000$
15Shakir Mukhamadullin (R)0X100.007469876869494857255742624044445550002131,294,167$
16Dysin Mayo61X100.008545847868598060253947847560606150002723,250,000$
Rayé
1Felix Robert (R)0XX100.0070648564647275627856646261444464500N0241950,000$
2Bobby McMann (R)0XX100.0078758460756768665054746770444469500N0271762,500$
3Steven Lorentz0XXX100.0082459373736291627160648125626370500N02711,050,000$
4Mathieu Olivier25X100.00929967648161785729625875255758655000264750,000$
MOYENNE D’ÉQUIPE100.0079728169746272594855556943535362500
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 SPÂgeContratSalaire
1Olle Eriksson Ek (R)47100.0044486082414350524546304444465000242750,000$
Rayé
1Magnus Hellberg (R)0100.006058568365546961656075464662500N0321750,000$
2Eric Comrie1100.006051516565548061656078484862500N02822,050,000$
MOYENNE D’ÉQUIPE100.005552567757506658585561464657500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe81838485787382CAN4321,000,000$


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’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
1Jujhar KhairaMoose (WPG)C/LW104260809291641525.00%421021.012134370001470053.10%29000000.5702000100
2Mathieu OlivierMoose (WPG)RW10336-1200149164518.75%011711.78112317000000035.71%1400001.0200000110
3Simon RyforsMoose (WPG)C/LW/RW9145-420013161126.25%013414.97123337000001059.59%14600000.7400000000
4Cole SmithMoose (WPG)LW/RW1004401802013192140%117117.150118370000320031.58%3800000.4700000000
5Otto KoivulaMoose (WPG)C/LW/RW9134-37511112368.33%211612.90000010000180056.48%10800000.6900010000
6Dysin MayoMoose (WPG)D9134-3100197841012.50%1320522.81112636000046000%000000.3900000000
7Scott PerunovichMoose (WPG)D10033-21001642010%316516.5401116000016000%000000.3600000000
8Tucker PoolmanMoose (WPG)D10123-218035553620.00%818818.83112332000037010%000000.3200000001
9Matt KierstedMoose (WPG)D90332401266440%818220.26022435000042000%000000.3300000000
10Patrick MaroonMoose (WPG)LW/RW9213-4201022121051420.00%016918.800113330000310054.55%1100000.3500101001
11Tim GettingerMoose (WPG)LW/RW920204081265433.33%39710.87000140000110027.27%1100000.4100000010
12Bobby McMannMoose (WPG)LW/RW7112-4404512088.33%28211.73011412000000075.00%400000.4900000000
13Ben HarpurMoose (WPG)D9112-410015961116.67%720923.22112436000051010%000000.1900000100
14Shakir MukhamadullinMoose (WPG)D8112-2140183101100.00%613316.6500003000014100%000000.3000000010
15Dryden HuntMoose (WPG)LW/RW10022-26010510150%112512.5500009000000054.55%1100000.3200000000
16Felix RobertMoose (WPG)C/LW6011000124160%1538.9600000000070039.47%3800000.3700000000
17Steven LorentzMoose (WPG)C/LW/RW9101040312157136.67%118720.830002360000510054.55%1100000.1112000000
18Justin RichardsMoose (WPG)C/RW8000120655010%1708.8100000000080050.00%200000000000000
19David CottonMoose (WPG)C3000020000000%062.310000000000000%00000000000000
20Kyle OlsonMoose (WPG)RW2000000000000%0115.98000000000000100.00%10000000000000
21Sam GagnerJetsC/RW1000000110010%088.9200000000000033.33%60000000000000
22Scott HarringtonJetsD1000000101000%01515.850001100000000%00000000000000
23Zachary SanfordJetsLW/RW1000020010010%088.050000000000000%00000000000000
Statistiques d’équipe totales ou en moyenne169193453-28165152151641704512811.18%61267115.81713204738100014202252.33%70900000.4014111332
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
1Eric ComrieMoose (WPG)82410.7983.5943400261290001.000381000
2Olle Eriksson EkMoose (WPG)11001.000060010240000011100
3Magnus HellbergMoose (WPG)30010.8574.0759004280000.333307000
Statistiques d’équipe totales ou en moyenne123420.8343.255540130181000699100


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 Recrue Poids Taille Non-échange Disponible pour échange Ballotage forcé Waiver Possible Contrat Type Salaire actuel Salaire restantSalaire moyenSalaire moyen restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 10Lien
Ben HarpurMoose (WPG)D281995-01-11No222 Lbs6 ft6NoNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Bobby McMannMoose (WPG)LW/RW271996-06-15Yes205 Lbs6 ft1YesNoNoNo1Pro & Farm762,500$762,500$762,500$762,500$0$0$NoLien
Cole SmithMoose (WPG)LW/RW271995-10-28Yes195 Lbs6 ft3NoNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$Lien
David CottonMoose (WPG)C261997-07-09No201 Lbs6 ft2NoNoNoNo1Pro & Farm1,350,000$1,350,000$1,350,000$1,350,000$0$0$NoLien
Dryden HuntMoose (WPG)LW/RW271995-11-24No193 Lbs6 ft0NoNoNoNo3Pro & Farm762,500$762,500$762,500$762,500$0$0$No762,500$762,500$Lien
Dysin MayoMoose (WPG)D271996-08-17No185 Lbs6 ft0NoNoNoNo2Pro & Farm3,250,000$3,250,000$3,250,000$3,250,000$0$0$No3,250,000$Lien
Eric ComrieMoose (WPG)G281995-07-05No175 Lbs6 ft1YesNoNoNo2Pro & Farm2,050,000$2,050,000$2,050,000$2,050,000$0$0$No2,050,000$Lien
Felix RobertMoose (WPG)C/LW241999-07-24Yes180 Lbs5 ft9YesNoNoNo1Pro & Farm950,000$950,000$950,000$950,000$0$0$NoLien
Jujhar KhairaMoose (WPG)C/LW291994-08-13No212 Lbs6 ft4NoNoNoNo2Pro & Farm1,200,000$1,200,000$1,200,000$1,200,000$0$0$No1,200,000$Lien
Justin RichardsMoose (WPG)C/RW251998-03-17Yes190 Lbs5 ft11NoNoNoNo1Pro & Farm1,425,000$1,425,000$1,425,000$1,425,000$0$0$NoLien
Kyle OlsonMoose (WPG)RW241999-03-22No179 Lbs5 ft11NoNoNoNo1Pro & Farm950,000$950,000$450,000$450,000$0$0$NoLien
Magnus HellbergMoose (WPG)G321991-04-04Yes190 Lbs6 ft5YesNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Mathieu OlivierMoose (WPG)RW261997-02-11No210 Lbs6 ft2NoNoNoNo4Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$750,000$Lien
Matt KierstedMoose (WPG)D251998-04-14Yes181 Lbs6 ft0NoNoNoNo1Pro & Farm1,350,000$1,350,000$1,350,000$1,350,000$0$0$NoLien
Olle Eriksson EkMoose (WPG)G241999-06-22Yes208 Lbs6 ft3NoNoNoNo2Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$Lien
Otto KoivulaMoose (WPG)C/LW/RW251998-09-01No219 Lbs6 ft4YesNoNoNo1Pro & Farm800,000$800,000$800,000$800,000$0$0$NoLien
Patrick MaroonMoose (WPG)LW/RW351988-04-23No236 Lbs6 ft2YesNoNoNo1Pro & Farm1,000,000$1,000,000$1,000,000$1,000,000$0$0$NoLien
Scott PerunovichMoose (WPG)D251998-08-18Yes172 Lbs5 ft9NoNoNoNo2Pro & Farm2,175,000$2,175,000$2,175,000$2,175,000$0$0$No2,175,000$Lien
Shakir MukhamadullinMoose (WPG)D212002-10-01Yes178 Lbs6 ft4NoNoNoNo3Pro & Farm1,294,167$1,294,167$1,294,167$1,294,167$0$0$No1,294,167$1,294,167$
Simon RyforsMoose (WPG)C/LW/RW261997-08-16Yes181 Lbs5 ft10YesNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Steven LorentzMoose (WPG)C/LW/RW271996-04-13No192 Lbs6 ft3YesNoNoNo1Pro & Farm1,050,000$1,050,000$1,050,000$1,050,000$0$0$NoLien
Tim GettingerMoose (WPG)LW/RW251998-04-13Yes218 Lbs6 ft6YesNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Tucker PoolmanMoose (WPG)D301993-06-08No199 Lbs6 ft2NoNoNoNo2Pro & Farm3,500,000$3,500,000$3,500,000$3,500,000$0$0$No3,500,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2326.65197 Lbs6 ft21.651,266,051$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jujhar KhairaCole Smith35122
2Patrick MaroonSimon Ryfors30122
3Dryden HuntOtto KoivulaTim Gettinger25122
4Jujhar KhairaJustin RichardsKyle Olson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dysin MayoBen Harpur35122
2Tucker PoolmanMatt Kiersted30122
3Scott PerunovichShakir Mukhamadullin25122
4Dysin MayoBen Harpur10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jujhar KhairaCole Smith60122
2Patrick MaroonSimon Ryfors40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dysin MayoBen Harpur60122
2Tucker PoolmanMatt Kiersted40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jujhar Khaira60122
2Cole SmithPatrick Maroon40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dysin MayoBen Harpur60122
2Tucker PoolmanMatt Kiersted40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jujhar Khaira60122Dysin MayoBen Harpur60122
240122Tucker PoolmanMatt Kiersted40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jujhar Khaira60122
2Cole SmithPatrick Maroon40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dysin MayoBen Harpur60122
2Tucker PoolmanMatt Kiersted40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jujhar KhairaCole SmithDysin MayoBen Harpur
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jujhar KhairaCole SmithDysin MayoBen Harpur
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
David Cotton, Dryden Hunt, Tim GettingerDavid Cotton, Dryden HuntTim Gettinger
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Scott Perunovich, Shakir Mukhamadullin, Tucker PoolmanScott PerunovichShakir Mukhamadullin, Tucker Poolman
Tirs de pénalité
Jujhar Khaira, , Cole Smith, Patrick Maroon,
Gardien
#1 : Olle Eriksson Ek, #2 :
Lignes d’attaque personnalisées en prolongation
Jujhar Khaira, , Cole Smith, Patrick Maroon, , Dryden Hunt, Dryden Hunt, Simon Ryfors, Tim Gettinger, Otto Koivula, Justin Richards
Lignes de défense personnalisées en prolongation
Dysin Mayo, Ben Harpur, Tucker Poolman, Matt Kiersted, Scott Perunovich


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
TotalDomicileVisiteur
# 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
1Barracuda22000000624110000004221100000020241.00061016017851306559716391338358225.00%18194.44%015329352.22%15129950.50%8414757.14%2291512627712260
2Condors20200000210-81010000013-21010000017-600.000246007851536559716542220441218.33%10460.00%015329352.22%15129950.50%8414757.14%2291512627712260
3Gulls2010000158-31000000134-11010000024-210.25059140078513865597163818344710220.00%14471.43%015329352.22%15129950.50%8414757.14%2291512627712260
4Heat20100100410-61010000005-51000010045-110.250471100785138655971652154155900.00%13284.62%015329352.22%15129950.50%8414757.14%2291512627712260
5Monarchs2010001048-4100000103211010000016-520.5004610007851386559716339324211218.18%15380.00%015329352.22%15129950.50%8414757.14%2291512627712260
Total1025001112138-17512000111116-5513001001022-1280.40021365701785119765597162167716522350714.00%701480.00%015329352.22%15129950.50%8414757.14%2291512627712260
_Since Last GM Reset1025001112138-17512000111116-5513001001022-1280.40021365701785119765597162167716522350714.00%701480.00%015329352.22%15129950.50%8414757.14%2291512627712260
_Vs Conference824000111728-11411000111111041300000617-1170.43817294601785115965597161646212416841717.07%571278.95%015329352.22%15129950.50%8414757.14%2291512627712260
_Vs Division1024000112138-17511000111116-5513000001022-1270.35021365701785119765597162167716522350714.00%701480.00%015329352.22%15129950.50%8414757.14%2291512627712260

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
108W12136571972167716522301
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
102501112138
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
51200111116
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
51301001022
Derniers 10 matchs
WLOTWOTL SOWSOL
350101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
50714.00%701480.00%0
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
65597167851
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
15329352.22%15129950.50%8414757.14%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2291512627712260


Derniers matchs 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
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
13Moose1Condors7ALSommaire du match
217Monarchs2Moose3BWXXSommaire du match
328Moose2Barracuda0AWSommaire du match
440Condors3Moose1BLSommaire du match
654Heat5Moose0BLSommaire du match
866Moose1Monarchs6ALSommaire du match
976Gulls4Moose3BLXXSommaire du match
1085Moose4Heat5ALXSommaire du match
1192Moose2Gulls4ALSommaire du match
13105Barracuda2Moose4BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets150149
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
31 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,911,917$ 2,861,917$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 0$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 0$ 0$




Moose Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Moose Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
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

Moose Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Moose Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA