Connexion

Moose
GP: 17 | W: 8 | L: 6 | OTL: 3 | P: 19
GF: 44 | GA: 39 | PP%: 15.15% | PK%: 88.18%
DG: dispo | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #195 vs Wolves
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Centre de jeu
Monarchs
7-9-2, 16pts
5
FINAL
4 Moose
8-6-3, 19pts
Team Stats
L1SéquenceL1
3-4-1Fiche domicile4-4-1
4-5-1Fiche domicile4-2-2
4-6-0Derniers 10 matchs3-4-3
2.61Buts par match 2.59
3.11Buts contre par match 2.29
15.52%Pourcentage en avantage numérique15.15%
80.33%Pourcentage en désavantage numérique88.18%
Penguins
9-7-1, 19pts
4
FINAL
3 Moose
8-6-3, 19pts
Team Stats
W1SéquenceL1
4-4-1Fiche domicile4-4-1
5-3-0Fiche domicile4-2-2
5-4-1Derniers 10 matchs3-4-3
2.41Buts par match 2.59
2.35Buts contre par match 2.29
17.24%Pourcentage en avantage numérique15.15%
91.13%Pourcentage en désavantage numérique88.18%
Moose
8-6-3, 19pts
Jour 34
Wolves
10-8-0, 20pts
Statistiques d’équipe
L1SéquenceW1
4-4-1Fiche domicile5-3-0
4-2-2Fiche visiteur5-5-0
3-4-310 derniers matchs7-3-0
2.59Buts par match 2.33
2.29Buts contre par match 2.33
15.15%Pourcentage en avantage numérique12.37%
88.18%Pourcentage en désavantage numérique86.84%
Moose
8-6-3, 19pts
Jour 36
Barracuda
10-6-1, 21pts
Statistiques d’équipe
L1SéquenceL1
4-4-1Fiche domicile5-3-0
4-2-2Fiche visiteur5-3-1
3-4-310 derniers matchs6-4-0
2.59Buts par match 2.35
2.29Buts contre par match 2.35
15.15%Pourcentage en avantage numérique11.34%
88.18%Pourcentage en désavantage numérique87.85%
Monsters
8-7-2, 18pts
Jour 37
Moose
8-6-3, 19pts
Statistiques d’équipe
L3SéquenceL1
3-4-2Fiche domicile4-4-1
5-3-0Fiche visiteur4-2-2
5-4-110 derniers matchs3-4-3
2.88Buts par match 2.59
2.47Buts contre par match 2.59
15.00%Pourcentage en avantage numérique15.15%
87.64%Pourcentage en désavantage numérique88.18%
Meneurs d'équipe
Buts
Cole Smith
7
Passes
Ben Harpur
10
Points
Cole Smith
14
Plus/Moins
Scott Harrington
8
Victoires
Eric Comrie
8
Pourcentage d’arrêts
Eric Comrie
0.875

Statistiques d’équipe
Buts pour
44
2.59 GFG
Tirs pour
327
19.24 Avg
Pourcentage en avantage numérique
15.2%
15 GF
Début de zone offensive
41.3%
Buts contre
39
2.29 GAA
Tirs contre
274
16.12 Avg
Pourcentage en désavantage numérique
88.2%%
13 GA
Début de la zone défensive
38.2%
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 Pro28
Équipe Mineure18
Limite contact 46 / 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
1Cole Smith (R)91XX100.00949776657764856025655784255454675000273750,000$
2Tim Gettinger (R)0XX100.0083838466836769625060606857444464500N0251750,000$
3Bobby McMann (R)0XX100.0078758460756768665054746770444469500N0271762,500$
4Otto Koivula0XXX100.0080817771817376617655626759464665500N0241800,000$
5Patrick Maroon0XX100.0087995072895698613060576025788662500N03511,000,000$
6Sam Gagner0XX100.0061539176726282733761706061848468500N0341750,000$
7Steven Lorentz0XXX100.0082459373736291627160648125626370500N02711,050,000$
8Mathieu Olivier25X100.00929967648161785729625875255758655000264750,000$
9Simon Ryfors (R)0XXX100.0072658763658388658061656362444467500N0261750,000$
10Zachary Sanford0XX100.0076449177786588683256647125666868500N0281850,000$
11Dryden Hunt29XX100.00927981727151896034505861416566625000273762,500$
12Tucker Poolman37X100.008173817873454753594545763760615150003023,500,000$
13Matt Kiersted (R)73X100.006942907167538758255148672545455950002511,350,000$
14Scott Harrington0X100.0076449270757071592552508025646462500N0301750,000$
15Maxence Guenette (R)0X100.0079748966747176542552416439444456500N0221813,333$
16Ben Harpur71X100.00807785658664615525504771256465585000281750,000$
17Dysin Mayo61X100.008545847868598060253947847560606150002723,250,000$
Rayé
1Justin Richards (R)93XX100.007169756369778161766256625344446250002511,425,000$
2David Cotton83X100.008075926575535450634748644644445650002611,350,000$
3Felix Robert (R)0XX100.0070648564647275627856646261444464500N0241950,000$
4Jujhar Khaira16XX100.008686827882675968696362832565666950002921,200,000$
5Kyle Olson33X100.00666472636455584750444456424444515000241950,000$
6Scott Perunovich (R)48X100.006761827861535257255842594044455650002522,175,000$
7Ty Emberson (R)0X100.0077728763727480512546426240444456500N0231775,000$
8Shakir Mukhamadullin (R)0X100.007469876869494857255742624044445550002031,294,167$
MOYENNE D’ÉQUIPE100.0078698369746374594455556842545562500
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
1Magnus Hellberg (R)0100.006058568365546961656075464662500N0321750,000$
2Eric Comrie1100.006051516565548061656078484862500N02822,050,000$
Rayé
1Olle Eriksson Ek (R)47100.0044486082414350524546304444465000242750,000$
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
1Cole SmithMoose (WPG)LW/RW1777140381044312382730.43%333319.593697710000373125.00%5200000.8401011211
2Zachary SanfordMoose (WPG)LW/RW1757126608263152016.13%125615.102247280001251039.69%13100000.9400000002
3Ben HarpurMoose (WPG)D17110112320294143107.14%1937522.101451171000065000%000000.5900000120
4Jujhar KhairaMoose (WPG)C/LW156410-112022482881521.43%629319.572133500002471052.72%29400000.6800000002
5Sam GagnerMoose (WPG)C/RW17461010012222161618.18%034720.421235720110610037.82%11900000.5802000001
6Steven LorentzMoose (WPG)C/LW/RW17461056017273583111.43%326715.741012310001220051.43%3500000.7500000101
7Scott HarringtonMoose (WPG)D17369814020151481321.43%1934820.511231257000065010%000000.5200000001
8Simon RyforsMoose (WPG)C/LW/RW173695604392782311.11%029417.32022665000010056.46%29400000.6100000110
9Patrick MaroonMoose (WPG)LW/RW172570391543122041610.00%129217.220118500001251047.06%1700000.4801201100
10Tim GettingerMoose (WPG)LW/RW1732531351912243612.50%423613.880002350000331049.23%6500000.4200100020
11Dryden HuntMoose (WPG)LW/RW17224218027131661012.50%125114.821126381011410046.15%2600000.3202000001
12Dysin MayoMoose (WPG)D1204442202512159110%825321.110221452000032000%000000.3200000000
13Bobby McMannMoose (WPG)LW/RW1721332035154713.33%0925.451014130001101040.00%500000.6500000100
14Scott PerunovichMoose (WPG)D130330402094020%623217.88000324000036000%000000.2600000010
15Tucker PoolmanMoose (WPG)D140331220291311430%1025318.10033538000239000%000000.2400000000
16Otto KoivulaMoose (WPG)C/LW/RW13123-22038941311.11%11078.241124210000130057.78%9000000.5600000010
17Matt KierstedMoose (WPG)D17112-340131111239.09%834120.09101764000073000%000000.1200000000
18Maxence GuenetteMoose (WPG)D5022-240620100%310020.1500004000022000%000000.4000000000
19Mathieu OlivierMoose (WPG)RW13011-4606133110%0765.89000130000130028.57%700000.2600000000
20Justin RichardsMoose (WPG)C/RW5000-200130010%0326.5800004000060047.06%170000000000000
21Felix RobertMoose (WPG)C/LW5000000343110%0357.05000110000110030.00%100000000000000
22Ty EmbersonMoose (WPG)D3000060421000%55016.960000000004000%00000000000000
23Shakir MukhamadullinMoose (WPG)D4000060631000%66215.500001500005000%00000000000000
Statistiques d’équipe totales ou en moyenne3064478122262623035333432710322913.46%104493616.1315274210980811296968248.88%116200000.4906312789
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)178530.8751.9498802322560010.6676170010
2Magnus HellbergMoose (WPG)10100.7656.32380041700000017000
Statistiques d’équipe totales ou en moyenne188630.8682.101027023627300161717010


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$590,323$750,000$590,323$0$0$NoLien
Bobby McMannMoose (WPG)LW/RW271996-06-15Yes205 Lbs6 ft1YesNoNoNo1Pro & Farm762,500$600,161$762,500$600,161$0$0$NoLien
Cole SmithMoose (WPG)LW/RW271995-10-28Yes195 Lbs6 ft3NoNoNoNo3Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$750,000$Lien
David CottonMoose (WPG)C261997-07-09No201 Lbs6 ft2NoNoNoNo1Pro & Farm1,350,000$1,062,581$1,350,000$1,062,581$0$0$NoLien
Dryden HuntMoose (WPG)LW/RW271995-11-24No193 Lbs6 ft0NoNoNoNo3Pro & Farm762,500$600,161$762,500$600,161$0$0$No762,500$762,500$Lien
Dysin MayoMoose (WPG)D271996-08-17No185 Lbs6 ft0NoNoNoNo2Pro & Farm3,250,000$2,558,065$3,250,000$2,558,065$0$0$No3,250,000$Lien
Eric ComrieMoose (WPG)G281995-07-05No175 Lbs6 ft1YesNoNoNo2Pro & Farm2,050,000$1,613,548$2,050,000$1,613,548$0$0$No2,050,000$Lien
Felix RobertMoose (WPG)C/LW241999-07-24Yes180 Lbs5 ft9YesNoNoNo1Pro & Farm950,000$747,742$950,000$747,742$0$0$NoLien
Jujhar KhairaMoose (WPG)C/LW291994-08-13No212 Lbs6 ft4NoNoNoNo2Pro & Farm1,200,000$944,516$1,200,000$944,516$0$0$No1,200,000$Lien
Justin RichardsMoose (WPG)C/RW251998-03-17Yes190 Lbs5 ft11NoNoNoNo1Pro & Farm1,425,000$1,121,613$1,425,000$1,121,613$0$0$NoLien
Kyle OlsonMoose (WPG)RW241999-03-22No179 Lbs5 ft11NoNoNoNo1Pro & Farm950,000$747,742$450,000$354,194$0$0$NoLien
Magnus HellbergMoose (WPG)G321991-04-04Yes190 Lbs6 ft5YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Mathieu OlivierMoose (WPG)RW261997-02-11No210 Lbs6 ft2NoNoNoNo4Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$750,000$750,000$Lien
Matt KierstedMoose (WPG)D251998-04-14Yes181 Lbs6 ft0NoNoNoNo1Pro & Farm1,350,000$1,062,581$1,350,000$1,062,581$0$0$NoLien
Maxence GuenetteMoose (WPG)D222001-04-28Yes196 Lbs6 ft3YesNoNoNo1Pro & Farm813,333$640,172$813,333$640,172$0$0$NoLien
Olle Eriksson EkMoose (WPG)G241999-06-22Yes208 Lbs6 ft3NoNoNoNo2Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$Lien
Otto KoivulaMoose (WPG)C/LW/RW241998-09-01No219 Lbs6 ft4YesNoNoNo1Pro & Farm800,000$629,677$800,000$629,677$0$0$NoLien
Patrick MaroonMoose (WPG)LW/RW351988-04-23No236 Lbs6 ft2YesNoNoNo1Pro & Farm1,000,000$787,097$1,000,000$787,097$0$0$NoLien
Sam GagnerMoose (WPG)C/RW341989-08-10No200 Lbs5 ft11YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Scott HarringtonMoose (WPG)D301993-03-10No204 Lbs6 ft2YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Scott PerunovichMoose (WPG)D251998-08-18Yes172 Lbs5 ft9NoNoNoNo2Pro & Farm2,175,000$1,711,935$2,175,000$1,711,935$0$0$No2,175,000$Lien
Shakir MukhamadullinMoose (WPG)D202002-10-01Yes178 Lbs6 ft4NoNoNoNo3Pro & Farm1,294,167$1,018,635$1,294,167$1,018,635$0$0$No1,294,167$1,294,167$
Simon RyforsMoose (WPG)C/LW/RW261997-08-16Yes181 Lbs5 ft10YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Steven LorentzMoose (WPG)C/LW/RW271996-04-13No192 Lbs6 ft3YesNoNoNo1Pro & Farm1,050,000$826,452$1,050,000$826,452$0$0$NoLien
Tim GettingerMoose (WPG)LW/RW251998-04-13Yes218 Lbs6 ft6YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Tucker PoolmanMoose (WPG)D301993-06-08No199 Lbs6 ft2NoNoNoNo2Pro & Farm3,500,000$2,754,839$3,500,000$2,754,839$0$0$No3,500,000$Lien
Ty EmbersonMoose (WPG)D232000-05-24Yes195 Lbs6 ft1YesNoNoNo1Pro & Farm775,000$610,000$775,000$610,000$0$0$NoLien
Zachary SanfordMoose (WPG)LW/RW281994-09-11No207 Lbs6 ft4YesNoNoNo1Pro & Farm850,000$669,032$850,000$669,032$0$0$NoLien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2826.71197 Lbs6 ft21.541,180,625$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sam GagnerCole Smith35122
2Patrick MaroonSimon RyforsSteven Lorentz30122
3Dryden HuntZachary SanfordTim Gettinger25122
4Sam GagnerCole SmithPatrick Maroon10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Maxence GuenetteBen Harpur35122
2Dysin MayoMatt Kiersted30122
3Tucker PoolmanScott Harrington25122
4Scott HarringtonBen Harpur10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Sam GagnerTim GettingerCole Smith60122
2Patrick MaroonSimon RyforsDryden Hunt40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Scott HarringtonBen Harpur60122
2Dysin MayoMatt Kiersted40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Sam GagnerDryden Hunt60122
2Cole SmithPatrick Maroon40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Scott HarringtonBen Harpur60122
2Maxence GuenetteMatt Kiersted40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Patrick Maroon60122Scott HarringtonBen Harpur60122
2Cole Smith40122Tucker PoolmanMatt Kiersted40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Sam GagnerTim Gettinger60122
2Cole SmithPatrick Maroon40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Maxence GuenetteBen Harpur60122
2Scott HarringtonMatt Kiersted40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sam GagnerCole SmithScott HarringtonBen Harpur
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Sam GagnerCole SmithScott HarringtonBen Harpur
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Cole Smith, Dryden Hunt, Tim GettingerCole Smith, Dryden HuntTim Gettinger
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Scott Harrington, Ben Harpur, Matt KierstedBen HarpurBen Harpur, Matt Kiersted
Tirs de pénalité
Dryden Hunt, Sam Gagner, Cole Smith, Patrick Maroon, Tim Gettinger
Gardien
#1 : Eric Comrie, #2 : Magnus Hellberg
Lignes d’attaque personnalisées en prolongation
, Sam Gagner, Cole Smith, Patrick Maroon, Zachary Sanford, Dryden Hunt, Dryden Hunt, Simon Ryfors, Tim Gettinger, Steven Lorentz, Bobby McMann
Lignes de défense personnalisées en prolongation
Maxence Guenette, Ben Harpur, Scott Harrington, Matt Kiersted, Dysin Mayo


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
1Barracuda2020000035-21010000001-11010000034-100.000358001915100381011201048331442351417.14%15473.33%024847652.10%20744047.05%11323647.88%395261416136220107
2Bruins11000000101110000001010000000000021.000112011915100141011201048952115200.00%80100.00%024847652.10%20744047.05%11323647.88%395261416136220107
3Condors2020000047-31010000024-21010000023-100.0004711001915100251011201048461644409111.11%220100.00%024847652.10%20744047.05%11323647.88%395261416136220107
4Eagles1000000123-1000000000001000000123-110.5002350019151001910112010481313820600.00%4175.00%024847652.10%20744047.05%11323647.88%395261416136220107
5Gulls22000000633110000003211100000031241.000612180019151003810112010483613204915320.00%100100.00%024847652.10%20744047.05%11323647.88%395261416136220107
6Heat2010010025-31010000013-21000010012-110.25023510191510036101120104824622341119.09%11190.91%024847652.10%20744047.05%11323647.88%395261416136220107
7IceHogs11000000312110000003120000000000021.00035800191510026101120104815715268112.50%50100.00%024847652.10%20744047.05%11323647.88%395261416136220107
8Marlies22000000716000000000002200000071641.000713200119151004410112010482110104610330.00%5180.00%024847652.10%20744047.05%11323647.88%395261416136220107
9Monarchs210000018801000000145-11100000043130.75081422001915100421011201048541160468337.50%20575.00%124847652.10%20744047.05%11323647.88%395261416136220107
10Penguins21100000862211000008620000000000020.50081523001915100451011201048239204216212.50%10190.00%024847652.10%20744047.05%11323647.88%395261416136220107
Total1786001024439594400001222208420010122175190.55944781221219151003271011201048274104262353991515.15%1101388.18%124847652.10%20744047.05%11323647.88%395261416136220107
_Since Last GM Reset1786001024439594400001222208420010122175190.55944781221219151003271011201048274104262353991515.15%1101388.18%124847652.10%20744047.05%11323647.88%395261416136220107
_Vs Conference1044000022627-1522000011213-15220000114140100.50026467200191510018810112010481977418921660915.00%761086.84%124847652.10%20744047.05%11323647.88%395261416136220107
_Vs Division1034000012328-5512000011015-5522000001313070.35023416410191510017910112010481936018820457915.79%781087.18%124847652.10%20744047.05%11323647.88%395261416136220107

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1719L1447812232727410426235312
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
178601024439
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
94400012222
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
84201012217
Derniers 10 matchs
WLOTWOTL SOWSOL
340102
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
991515.15%1101388.18%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
10112010481915100
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
24847652.10%20744047.05%11323647.88%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
395261416136220107


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
27Penguins2Moose5BWSommaire du match
313Moose3Marlies1AWSommaire du match
831Barracuda1Moose0BLSommaire du match
1049IceHogs1Moose3BWSommaire du match
1155Moose4Marlies0AWSommaire du match
1368Condors4Moose2BLSommaire du match
1576Moose3Gulls1AWSommaire du match
1790Bruins0Moose1BWSommaire du match
19100Moose1Heat2ALXSommaire du match
20109Moose3Barracuda4ALSommaire du match
21120Gulls2Moose3BWSommaire du match
22123Moose2Condors3ALSommaire du match
25141Heat3Moose1BLSommaire du match
27152Moose2Eagles3ALXXSommaire du match
28156Moose4Monarchs3AWSommaire du match
30173Monarchs5Moose4BLXXSommaire du match
32184Penguins4Moose3BLSommaire du match
34195Moose-Wolves-
36204Moose-Barracuda-
37215Monsters-Moose-
40227Moose-Eagles-
41236Phantoms-Moose-
43248Moose-67s-
44259Penguins-Moose-
46270Moose-Barracuda-
47280Barracuda-Moose-
50291Moose-Monsters-
51301Gulls-Moose-
53315Heat-Moose-
55326Moose-Heat-
56334Moose-Sound Tigers-
58346Monarchs-Moose-
61356Moose-Gulls-
63368Gulls-Moose-
65379Moose-Gulls-
67389Marlies-Moose-
69401Moose-Wolves-
70408Rocket-Moose-
71417Moose-Heat-
7443167s-Moose-
76443Moose-Stars-
77450Moose-Rocket-
78459IceHogs-Moose-
80473Thunderbird-Moose-
81477Moose-Condors-
84494Moose-IceHogs-
86504Condors-Moose-
88518Moose-Monarchs-
90528IceHogs-Moose-
92539Crunch-Moose-
93546Moose-Crunch-
95560Moose-Marlies-
96566Moose-Penguins-
97572Griffins-Moose-
100588Heat-Moose-
102601Moose-IceHogs-
103611Eagles-Moose-
105624Moose-Phantoms-
106630Moose-Condors-
108638Condors-Moose-
111654Thunderbird-Moose-
112664Moose-Griffins-
114672Moose-Bruins-
115680Bruins-Moose-
118699Wolf Pack-Moose-
119706Moose-Monsters-
120718Moose-Penguins-
121724Stars-Moose-
124738Moose-Monarchs-
125747Monarchs-Moose-
127760Moose-Stars-
129768Stars-Moose-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
132785Barracuda-Moose-
134801Moose-Marlies-
135807Moose-Wolf Pack-
136813Wolves-Moose-
140832Wolves-Moose-
144848Moose-Thunderbird-
145856Sound Tigers-Moose-
146862Moose-Thunderbird-
149878Sound Tigers-Moose-
154899Eagles-Moose-



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
27 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
865,765$ 3,305,750$ 3,255,750$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 652,873$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 122 27,779$ 3,389,038$




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