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Connexion

Moose
GP: 78 | W: 31 | L: 40 | OTL: 7 | P: 69
GF: 243 | GA: 273 | PP%: 20.00% | PK%: 77.98%
DG: Rockey Marzano | Morale : 50 | Moyenne d’équipe : 60

Centre de jeu
Wild
30-44-4, 64pts
1
3 Moose
31-40-7, 69pts
Team Stats
L1SéquenceOTL1
19-19-1Fiche domicile20-15-4
11-25-3Fiche domicile11-25-3
3-5-2Derniers 10 matchs9-0-1
2.65Buts par match 3.12
3.35Buts contre par match 3.50
16.82%Pourcentage en avantage numérique20.00%
78.38%Pourcentage en désavantage numérique77.98%
Moose
31-40-7, 69pts
3
4 Phantoms
37-35-6, 80pts
Team Stats
OTL1SéquenceOTW1
20-15-4Fiche domicile22-13-4
11-25-3Fiche domicile15-22-2
9-0-1Derniers 10 matchs6-4-0
3.12Buts par match 3.03
3.50Buts contre par match 3.29
20.00%Pourcentage en avantage numérique21.56%
77.98%Pourcentage en désavantage numérique79.74%
Meneurs d'équipe
Buts
Nick Abruzzese
28
Calle RosenPasses
Calle Rosen
51
Points
Nick Abruzzese
67
Brendan LemieuxPlus/Moins
Brendan Lemieux
12
Victoires
Mark Sinclair
30
Pourcentage d’arrêts
Jaxon Castor
0.925

Statistiques d’équipe
Buts pour
243
3.12 GFG
Tirs pour
2314
29.67 Avg
Pourcentage en avantage numérique
20.0%
62 GF
Début de zone offensive
40.0%
Buts contre
273
3.50 GAA
Tirs contre
2359
30.24 Avg
Pourcentage en désavantage numérique
78.0%%
74 GA
Début de la zone défensive
40.0%
Informations de l'équipe

Directeur généralRockey Marzano
EntraîneurAnders Sorensen
DivisionCentral
ConférenceAmerican
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,901
Billets de saison0


Informations de la formation

Équipe Pro22
Équipe Mineure19
Limite contact 41 / 250
Espoirs59


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
1Ryan SuzukiX100.005656696972696666706660635859550506402421,200,000$
2Cameron HebigX100.00555967626268666370616366546559050630291750,000$
3Nick AbruzzeseXX100.00545969616369666455636065576257050620261800,000$
4Max McCormickXX100.00565868596462606055586063567564050610331750,000$
5Cedric PareX100.00555866607467656055595966566257047610271750,000$
6Brendan LemieuxX100.00636171587655605554555760546760050590301750,000$
7Jean-Luc FoudyXX100.00555469586363625855585663545754050590232900,000$
8Adam ErneXX100.005956725773575955555555615569610475803021,000,000$
9Ryan HoferX100.00555470557157575555545460545654050570231750,000$
10Carson GolderX100.00545470556756565455555460545654050560231750,000$
11Jon MerrillX100.006340847178628555406058845474600606603421,000,000$
12Calle RosenX100.00555769626668666140635766547062050620321750,000$
13Matt BenningX100.00594967627670645541595470557162047620311850,000$
14Nikolas MatinpaloX100.00574976647862645741595768556159050620272800,000$
15Brad HuntX100.00545868615965636040605763548168050610371800,000$
16Jarred TinordiX100.00626168588264655540575569547162050610341750,000$
17Joakim RyanX100.00515166546064615338535259516960050560321800,000$
Rayé
1Kyle McDonaldX100.005555675776646357555657625456540505902411,500,000$
2Owen PedersonX100.00545459546054545454545456545454050550242750,000$
3Connor KelleyX100.00515167516751515138515156515451050530242750,000$
MOYENNE D’ÉQUIPE100.0056556959696263575058576454645805060
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
1Mark Sinclair100.0056565756645566565961727061050590301750,000$
2Jaxon Castor100.0053535363545361536164686758050570291750,000$
Rayé
MOYENNE D’ÉQUIPE100.005555556059546455606370696005058
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Anders Sorensen7672737969611SWE502250,000$


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
1Nick AbruzzeseMoose (Fla)C/LW7828396763401172012336015612.02%19153519.68515206225110131892145.85%148100000.8700000452
2Ryan SuzukiMoose (Fla)C78174966-28260120299247671946.88%26166721.385232850254011103132153.77%238800000.7913000123
3Calle RosenMoose (Fla)D7895160-1052017410312038887.50%104182723.4451823732610001252210%000000.6600000232
4Cameron HebigMoose (Fla)LW78263157-142601191282477415510.53%27158620.33129217225401122835057.86%15900000.7223000234
5Matt BenningMoose (Fla)D781536512780205123135569411.11%110167521.487714842421122209200%100000.6100000222
6Nikolas MatinpaloMoose (Fla)D7893645-44601199812049907.50%91161720.7451217602320002231020%100000.5600000002
7Max McCormickMoose (Fla)LW/RW78202444-10360154901827113510.99%17146618.81710174925100021202043.33%12000000.6000000031
8Cedric PareMoose (Fla)C782022423420861691784211511.24%10117815.111016260000753249.15%117800000.7100000521
9Jean-Luc FoudyMoose (Fla)C/RW78152237-18240120121163351159.20%9153619.70167301870001173048.04%40800000.4800000201
10Jarred TinordiMoose (Fla)D7853136-9900198875521349.09%80127416.3311210590000830350.00%200000.5700000230
11Kyle McDonaldMoose (Fla)RW70191736-1034010264131539014.50%10120717.26761343227000022347.96%9800000.6000000003
12Brad HuntMoose (Fla)D7842832-4595109876917405.80%71129416.6013412500000109100%000000.4900000111
13Brendan LemieuxMoose (Fla)LW781212241236012166113278910.62%7107313.7600027000061060.87%6900000.4500000105
14Ryan HoferMoose (Fla)RW78913220200775282245310.98%1298312.6000000000000145.69%11600000.4500000102
15Jon MerrillMoose (Fla)D2981220-10160575866245412.12%4366122.8345941104000086110%000000.6000000011
16Carson GolderMoose (Fla)RW7810616-9220563748162820.83%136898.8400007000011058.82%3400000.4600000001
17Adam ErneMoose (Fla)LW/RW61437-660342136142711.11%13635.9600028000000054.55%2200000.3900000020
18Joakim RyanMoose (Fla)D26325-3100367186816.67%2341716.0400005000127000%000000.2400000010
Statistiques d’équipe totales ou en moyenne1278233434667-1126575200418112243694156510.39%6732205717.26611151765962432235242012271550.30%607700000.6036000232831
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
1Mark SinclairMoose (Fla)78303970.8823.5342960525321430320.7147780512
2Jaxon CastorMoose (Fla)141100.9252.35409201621300100078000
Statistiques d’équipe totales ou en moyenne92314070.8863.43470625269235603377878512


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 Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Plafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adam ErneMoose (Fla)LW/RW301995-04-20USANo215 Lbs6 ft0NoNoTrade2025-11-10NoNo2FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien / Lien NHL
Brad HuntMoose (Fla)D371988-08-24CANNo176 Lbs5 ft9NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm800,000$0$0$No---------------------------Lien / Lien NHL
Brendan LemieuxMoose (Fla)LW301996-03-15USANo215 Lbs6 ft0NoNoFree Agent2025-01-01NoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien / Lien NHL
Calle RosenMoose (Fla)D321994-02-02SWENo187 Lbs6 ft0NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien / Lien NHL
Cameron HebigMoose (Fla)LW291997-01-21CANNo183 Lbs5 ft10NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien / Lien NHL
Carson GolderMoose (Fla)RW232002-10-29CANNo196 Lbs6 ft0NoNoFree AgentNoNo12024-09-22FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Cedric PareMoose (Fla)C271999-01-24CANNo211 Lbs6 ft4NoNoFree AgentNoNo12025-08-02FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Connor KelleyMoose (Fla)D242002-01-30USANo201 Lbs6 ft2NoNoFree AgentNoNo22025-10-06FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Jarred TinordiMoose (Fla)D341992-02-20USANo228 Lbs6 ft5NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien / Lien NHL
Jaxon CastorMoose (Fla)G291997-03-14USANo200 Lbs6 ft3NoNoFree AgentNoNo12025-09-21FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Jean-Luc FoudyMoose (Fla)C/RW232002-05-13CANNo176 Lbs5 ft10NoNoFree AgentNoNo22025-06-30FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien
Joakim RyanMoose (Fla)D321993-06-17USANo185 Lbs5 ft11NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Jon MerrillMoose (Fla)D341992-02-03USANo204 Lbs6 ft3NoNoFree Agent2024-08-26NoNo22025-07-19FalseFalsePro & Farm1,000,000$0$0$No1,000,000$--------1,000,000$--------No--------Lien / Lien NHL
Kyle McDonaldMoose (Fla)RW242002-02-05CANNo207 Lbs6 ft4NoNoFree AgentNoNo12024-07-27FalseFalsePro & Farm1,500,000$0$0$No---------------------------Lien
Mark SinclairMoose (Fla)G301996-03-08CANNo181 Lbs6 ft0NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Matt BenningMoose (Fla)D311994-05-25CANNo202 Lbs6 ft0NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm850,000$0$0$No---------------------------Lien / Lien NHL
Max McCormickMoose (Fla)LW/RW331992-05-01USANo187 Lbs5 ft11NoNoFree AgentNoNo12025-08-01FalseFalsePro & Farm750,000$0$0$No---------------------------Lien / Lien NHL
Nick AbruzzeseMoose (Fla)C/LW261999-06-04USANo183 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm800,000$0$0$No---------------------------Lien
Nikolas MatinpaloMoose (Fla)D271998-10-05FINNo206 Lbs6 ft3NoNoFree AgentNoNo22025-06-30FalseFalsePro & Farm800,000$0$0$No800,000$--------800,000$--------No--------Lien
Owen PedersonMoose (Fla)C242002-03-27CANNo205 Lbs6 ft4NoNoFree AgentNoNo22025-10-06FalseFalsePro & Farm750,000$0$0$No750,000$--------750,000$--------No--------Lien
Ryan HoferMoose (Fla)RW232002-05-10CANNo191 Lbs6 ft3NoNoFree AgentNoNo12024-09-22FalseFalsePro & Farm750,000$0$0$No---------------------------Lien
Ryan SuzukiMoose (Fla)C242001-05-28CANNo189 Lbs6 ft1NoNoFree AgentNoNo22025-08-02FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2228.45197 Lbs6 ft11.32847,727$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cameron HebigRyan SuzukiJean-Luc Foudy40014
2Max McCormickNick Abruzzese30014
3Brendan LemieuxCedric PareRyan Hofer20122
4Adam ErneJean-Luc FoudyCarson Golder10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calle Rosen40122
2Matt BenningNikolas Matinpalo30122
3Brad HuntJarred Tinordi20122
4Calle Rosen10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cameron HebigRyan SuzukiJean-Luc Foudy60122
2Max McCormickNick Abruzzese40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calle Rosen60122
2Matt BenningNikolas Matinpalo40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Ryan SuzukiCameron Hebig60122
2Nick AbruzzeseMax McCormick40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calle Rosen60122
2Matt BenningNikolas Matinpalo40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Ryan Suzuki60122Calle Rosen60122
2Nick Abruzzese40122Matt BenningNikolas Matinpalo40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Ryan SuzukiCameron Hebig60122
2Nick AbruzzeseMax McCormick40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Calle Rosen60122
2Matt BenningNikolas Matinpalo40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cameron HebigRyan SuzukiJean-Luc FoudyCalle Rosen
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cameron HebigRyan SuzukiJean-Luc FoudyCalle Rosen
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Cedric Pare, Jean-Luc Foudy, Cedric Pare, Jean-Luc FoudyCedric Pare
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Nikolas Matinpalo, Brad Hunt, Jarred TinordiNikolas MatinpaloNikolas Matinpalo, Brad Hunt
Tirs de pénalité
Ryan Suzuki, Cameron Hebig, Nick Abruzzese, Max McCormick, Cedric Pare
Gardien
#1 : Mark Sinclair, #2 : Jaxon Castor
Lignes d’attaque personnalisées en prolongation
Ryan Suzuki, Cameron Hebig, Nick Abruzzese, Max McCormick, Cedric Pare, Jean-Luc Foudy, , Brendan Lemieux, Adam Erne, Ryan Hofer
Lignes de défense personnalisées en prolongation
, Calle Rosen, Matt Benning, Nikolas Matinpalo, Brad Hunt


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
1Aces641001002417732000100138532100000119290.75024456910828767816971681076727189405015130826.67%25388.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
2Admirals522000101917231100010141222110000055060.60019345301828767816371681076727170534013915320.00%20860.00%11333260451.19%1319260350.67%643130449.31%1809120318546171049518
3Americans1010000036-3000000000001010000036-300.0003690082876783371681076727242626400.00%30100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
4Barracuda2110000023-1110000002111010000002-220.500246008287678467168107672750151860500.00%9188.89%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
5Bears1010000025-3000000000001010000025-300.000246008287678367168107672735171435100.00%7271.43%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
6Bruins11000000615000000000001100000061521.0006111700828767830716810767272156267228.57%30100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
7Crunch1010000026-4000000000001010000026-400.00024600828767834716810767273388366116.67%4175.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
8Devils10000010321100000103210000000000021.00033600828767836716810767273458367228.57%4175.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
9Falcons11000000431110000004310000000000021.000481200828767841716810767272596326350.00%3233.33%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
10Firebirds1010000013-2000000000001010000013-200.0001230082876782571681076727217628400.00%30100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
11Griffins623010001819-131200000810-231101000109160.50018355300828767816171681076727186505015518633.33%25484.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
12Gulls2020000046-21010000023-11010000023-100.0004812008287678637168107672768161044600.00%5420.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
13Heat42101000131303200100011741010000026-460.7501323360082876781007168107672713738349516318.75%17476.47%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
14Ice Hogs514000001722-5312000001212020200000510-520.20017304700828767814871681076727120323813219315.79%19478.95%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
15Marlies30200100513-81000010034-12020000029-710.167581300828767867716810767271073341711200.00%19573.68%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
16Monsters4220000015114110000008443120000077040.50015284301828767812471681076727120383010417317.65%15380.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
17Oil Kings10001000321100010003210000000000021.00035800828767823716810767273591422700.00%7185.71%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
18Penguins11000000431110000004310000000000021.0004812008287678277168107672723310236116.67%5260.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
19Phantoms1000010034-1000000000001000010034-110.5003690082876783471681076727285826200.00%4175.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
20Rampage21100000651110000003031010000035-220.50061218018287678577168107672749261060600.00%50100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
21Reign2020000036-31010000023-11010000013-200.0003690082876784671681076727662314556116.67%7271.43%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
22Rocket1010000028-6000000000001010000028-600.00023500828767832716810767274098247114.29%4250.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
23Senators1010000024-21010000024-20000000000000.0002460082876782571681076727338625500.00%30100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
24Sound Tigers2110000056-12110000056-10000000000020.50059140082876784871681076727602822476116.67%11281.82%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
25Stars1010000035-21010000035-20000000000000.000347108287678307168107672722712362150.00%6183.33%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
26Swamp Rabbits10001000431000000000001000100043121.00047110082876783271681076727157624300.00%3166.67%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
27Thunderbirds1010000025-3000000000001010000025-300.00024600828767835716810767272984293266.67%2150.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
28Wheat Kings511002011920-1301001011015-52100010095450.50019365501828767816771681076727169524812827725.93%24579.17%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
29Wild83301100322664210100015123412001001714390.56332619300828767828671681076727219658021526726.92%40977.50%11333260451.19%1319260350.67%643130449.31%1809120318546171049518
30Wolfpack1010000056-1000000000001010000056-100.000591400828767826716810767273011626100.00%30100.00%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
31Wolves615000001223-1130300000614-83120000069-320.16712213311828767817071681076727201546214930723.33%31583.87%01333260451.19%1319260350.67%643130449.31%1809120318546171049518
Total78244005621243273-303915150332113313033992502300110143-33690.442243448691358287678231471681076727235968367520593106220.00%3367477.98%21333260451.19%1319260350.67%643130449.31%1809120318546171049518
_Since Last GM Reset78244005621243273-303915150332113313033992502300110143-33690.442243448691358287678231471681076727235968367520593106220.00%3367477.98%21333260451.19%1319260350.67%643130449.31%1809120318546171049518
_Vs Conference60203003511189201-1231121202311109105429818012008096-16540.450189351540258287678176771681076727185153552515582334820.60%2615778.16%21333260451.19%1319260350.67%643130449.31%1809120318546171049518
_Vs Division28141902411102103-11671001211615921279012004144-3390.696102189291138287678927716810767278032522387711042625.00%1193074.79%21333260451.19%1319260350.67%643130449.31%1809120318546171049518

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
7869OTL124344869123142359683675205935
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
7824405621243273
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
3915153321133130
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
399252300110143
Derniers 10 matchs
WLOTWOTL SOWSOL
603100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3106220.00%3367477.98%2
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
716810767278287678
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
1333260451.19%1319260350.67%643130449.31%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1809120318546171049518


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
13Wild3Moose4WSommaire du match
424Moose2Wild3LXSommaire du match
639Moose3Wild4LSommaire du match
854Admirals3Moose7WSommaire du match
1064Moose5Aces2WSommaire du match
1279Moose2Griffins3LSommaire du match
1491Ice Hogs4Moose2LSommaire du match
16105Moose2Monsters3LSommaire du match
18121Aces3Moose2LXSommaire du match
20134Moose2Wolves6LSommaire du match
22153Heat1Moose3WSommaire du match
25173Moose8Wild2WSommaire du match
27186Wild4Moose3LSommaire du match
30211Wheat Kings4Moose3LXSommaire du match
33232Wolves5Moose1LSommaire du match
35244Moose2Marlies4LSommaire du match
38264Moose2Crunch6LSommaire du match
40278Sound Tigers1Moose2WSommaire du match
42293Moose2Rocket8LSommaire du match
44305Griffins3Moose1LSommaire du match
47330Moose1Admirals5LSommaire du match
49340Gulls3Moose2LSommaire du match
52366Monsters4Moose8WSommaire du match
54376Moose2Monsters0WSommaire du match
57396Penguins3Moose4WSommaire du match
60425Sound Tigers5Moose3LSommaire du match
62438Moose1Reign3LSommaire du match
64455Marlies4Moose3LXSommaire du match
66468Moose1Firebirds3LSommaire du match
68482Moose2Thunderbirds5LSommaire du match
70493Moose0Barracuda2LSommaire du match
71502Wolves3Moose1LSommaire du match
74525Moose3Aces2WSommaire du match
75533Rampage0Moose3WSommaire du match
78556Senators4Moose2LSommaire du match
80568Moose4Admirals0WSommaire du match
82587Aces3Moose5WSommaire du match
84598Moose3Monsters4LSommaire du match
87620Moose3Rampage5LSommaire du match
88628Devils2Moose3WXXSommaire du match
91654Wheat Kings5Moose2LSommaire du match
93663Moose4Wheat Kings5LXSommaire du match
95684Ice Hogs3Moose6WSommaire du match
97693Moose3Ice Hogs6LSommaire du match
99714Wheat Kings6Moose5LXXSommaire du match
101727Moose5Wheat Kings0WSommaire du match
103745Moose2Ice Hogs4LSommaire du match
105753Ice Hogs5Moose4LSommaire du match
108772Moose6Bruins1WSommaire du match
110787Stars5Moose3LSommaire du match
112806Moose2Heat6LSommaire du match
114819Griffins2Moose1LSommaire du match
116828Moose3Americans6LSommaire du match
118846Moose1Wolves3LSommaire du match
120857Wolves6Moose4LSommaire du match
122876Moose3Wolves0WSommaire du match
123884Moose2Gulls3LSommaire du match
125893Admirals3Moose4WXXSommaire du match
128917Griffins5Moose6WSommaire du match
130928Moose5Wolfpack6LSommaire du match
132946Moose0Marlies5LSommaire du match
133956Heat3Moose4WXSommaire du match
137979Moose4Wild5LSommaire du match
138988Admirals6Moose3LSommaire du match
1411012Moose2Bears5LSommaire du match
1421020Reign3Moose2LSommaire du match
1461048Oil Kings2Moose3WXSommaire du match
1501072Moose3Aces5LSommaire du match
1511081Barracuda1Moose2WSommaire du match
1551105Aces2Moose6WSommaire du match
1581130Wild4Moose5WXSommaire du match
1591138Moose4Griffins3WXSommaire du match
1631162Moose4Griffins3WSommaire du match
1651173Heat3Moose4WSommaire du match
1681194Falcons3Moose4WSommaire du match
1701211Moose4Swamp Rabbits3WXSommaire du match
1741232Wild1Moose3WSommaire du match
1761244Moose3Phantoms4LXSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets15075
Assistance75,87937,250
Assistance PCT97.28%95.51%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2901 - 96.69% 508,868$19,845,840$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,694,048$ 2,765,000$ 2,765,000$ 250,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
15,534$ 2,444,099$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 16,938$ 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