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Moose
GP: 5 | W: 1 | L: 4
GF: 9 | GA: 23 | PP%: 15.00% | PK%: 73.68%
DG: Mika | Morale : 50 | Moyenne d’équipe : 59

Centre de jeu
Eagles
6-5-0, 12pts
4
FINAL
2 Moose
1-4-0, 2pts
Team Stats
L3SéquenceL2
4-2-0Fiche domicile1-1-0
2-3-0Fiche domicile0-3-0
5-5-0Derniers 10 matchs1-4-0
3.00Buts par match 1.80
2.09Buts contre par match 4.60
16.90%Pourcentage en avantage numérique15.00%
87.30%Pourcentage en désavantage numérique73.68%
Moose
1-4-0, 2pts
1
FINAL
6 Eagles
6-5-0, 12pts
Team Stats
L2SéquenceL3
1-1-0Fiche domicile4-2-0
0-3-0Fiche domicile2-3-0
1-4-0Derniers 10 matchs5-5-0
1.80Buts par match 3.00
4.60Buts contre par match 2.09
15.00%Pourcentage en avantage numérique16.90%
73.68%Pourcentage en désavantage numérique87.30%
Meneurs d'équipe
Buts
Aleksanteri Kaskimaki
3
Tyler PitlickPasses
Tyler Pitlick
3
Clark BishopPoints
Clark Bishop
4
Dakota MermisPlus/Moins
Dakota Mermis
2
Chris DriedgerVictoires
Chris Driedger
1
Chris DriedgerPourcentage d’arrêts
Chris Driedger
0.779

Statistiques d’équipe
Buts pour
9
1.80 GFG
Tirs pour
74
14.80 Avg
Pourcentage en avantage numérique
15.0%
3 GF
Début de zone offensive
34.6%
Buts contre
23
4.60 GAA
Tirs contre
116
23.20 Avg
Pourcentage en désavantage numérique
73.7%%
10 GA
Début de la zone défensive
38.1%
Informations de l'équipe

Directeur généralMika
EntraîneurTodd Richards
DivisionCentral Division
ConférenceWestern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance3,000
Billets de saison0


Informations de la formation

Équipe Pro19
Équipe Mineure21
Limite contact 40 / 51
Espoirs29


Historique d'équipe

Saison actuelle1-4
Historique50-25-6 (0.617%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)1 - 4 (0.200%)
Coupe Stanley0


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
1Tyler PitlickX100.007775837375737564806065666244466750640341800,000$
2Clark BishopXX100.007672866872828762785663666049506650630301775,000$
3Aleksanteri Kaskimaki (R)X100.007870956670747860755957655444446350610223870,000$
4Samu TuomaalaX100.007065816665636462506160625744446250600232863,333$
5Judd CaulfieldX100.008282826382768255505056665344446150600252837,500$
6Roby JarventieX100.008477998077363160757244684244445950590232995,000$
7Konsta Helenius (R)X100.007367876667555460755758635544446150580203975,000$
8Samuel Savoie (R)X100.007468886568798751505047614544445650570223846,666$
9Felix Unger Sorum (R)X100.007263936563717652505346604444445650560203831,667$
10Tucker RobertsonX100.007467896267565850634748614644445450540222950,000$
11Eetu LiukasX100.007877806577505050504550634844445550540233867,500$
12Uvis BalinskisX100.00765488757265956425534867255656625065N0292850,000$
13Steven SantiniX100.00827989667969755025394368415859565062N0313775,000$
14Corey SchuenemanX100.00757088667075825025434162394747555060N0302775,000$
15Dakota MermisX100.00747180697155574825403963375454525058N0323812,000$
16Michael KarowX100.007676756476535646253739613744445050560272775,000$
17Aleksi Heimosalmi (R)X100.007063866463677347253742584044445350560233805,833$
Rayé
MOYENNE D’ÉQUIPE100.00767086677165695550515064464747585059
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
1Joel Blomqvist (R)100.00595453806552696065597545456050600242925,000$
2Chris Driedger100.0044405084434250514647304444465050N0311795,000$
Rayé
MOYENNE D’ÉQUIPE100.0052475282544760565653534545535055
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Todd Richards75737168878160USA581925,000$


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
1Clark BishopMoose (WPG)C/LW5224020312113518.18%010320.720112150001291061.06%11300000.7700000100
2Tyler PitlickMoose (WPG)RW5134-1602270414.29%06713.53011015000000066.67%300001.1800000000
3Aleksanteri KaskimakiMoose (WPG)C5303-440511103730.00%09719.542022160000140063.00%10000000.6100000001
4Dakota MermisMoose (WPG)D50222801122010%410020.01000213000019000%000000.4000000000
5Samu TuomaalaMoose (WPG)RW5022-460168280%08016.06022015000000066.67%300000.5000000000
6Samuel SavoieMoose (WPG)LW5022-320333230%010621.320000170000210050.00%200000.3800000000
7Roby JarventieMoose (WPG)LW5202-12071540450.00%19519.161011110000170080.00%1000000.4200000000
8Corey SchuenemanMoose (WPG)D50111201031000%410521.16011114000022000%000000.1900000000
9Eetu LiukasMoose (WPG)LW5011-340653040%06713.4600001000010033.33%600000.3000000000
10Judd CaulfieldMoose (WPG)RW5101-31005654420.00%28917.9700007000090144.44%900000.2200000010
11Michael KarowMoose (WPG)D5011-480711010%38216.5000005000013000%000000.2400000000
12Aleksi HeimosalmiMoose (WPG)D5011-680231030%58016.080000400007000%000000.2500000000
13Uvis BalinskisMoose (WPG)D5000-3100474020%910921.84000314000019000%00000000000000
14Steven SantiniMoose (WPG)D5000-31151223000%311022.18000115000022000%00000000100000
15Tucker RobertsonMoose (WPG)C5000000422100%0295.9500000000000036.00%250000000000000
16Konsta HeleniusMoose (WPG)C5000-300199460%07214.4900012000060068.29%410000000000000
17Felix Unger SorumMoose (WPG)RW5000040220120%0316.3400000000000033.33%30000000000000
Statistiques d’équipe totales ou en moyenne8591524-35875859174205412.16%31143116.843581317200012051160.00%31500000.3400100111
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
1Chris DriedgerMoose (WPG)51400.7795.701790017770000050000
Statistiques d’équipe totales ou en moyenne51400.7795.70179001777000050000


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 Salaire restantPlafond 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
Aleksanteri KaskimakiMoose (WPG)C222004-02-06FINYes193 Lbs6 ft0NoNoAssign ManuallyNoNo32025-08-27FalseFalsePro & Farm870,000$17,755$0$0$No870,000$870,000$-------870,000$870,000$-------NoNo-------Lien
Aleksi HeimosalmiMoose (WPG)D232003-05-08FINYes170 Lbs5 ft11NoNoProspectNoNo32025-08-27FalseFalsePro & Farm805,833$16,446$0$0$No805,833$805,833$-------805,833$805,833$-------NoNo-------Lien
Chris DriedgerMoose (WPG)G311994-05-18MBNo205 Lbs6 ft4YesNoFree Agent2024-08-16NoNo12025-08-21FalseFalsePro & Farm795,000$16,224$0$0$No---------------------------Lien / Lien NHL
Clark BishopMoose (WPG)C/LW301996-03-29CANNo197 Lbs6 ft1NoNoFree AgentNoNo12024-06-16FalseFalsePro & Farm775,000$15,816$0$0$No---------------------------Lien / Lien NHL
Corey SchuenemanMoose (WPG)D301995-09-02USANo197 Lbs5 ft11YesNoFree AgentNoNo22025-08-21FalseFalsePro & Farm775,000$15,816$0$0$No775,000$--------775,000$--------Yes--------Lien
Dakota MermisMoose (WPG)D321994-01-05USANo197 Lbs6 ft0YesNoFree AgentNoNo32025-08-21FalseFalsePro & Farm812,000$16,571$0$0$No812,000$812,000$-------812,000$812,000$-------YesYes-------Lien / Lien NHL
Eetu LiukasMoose (WPG)LW232002-09-25FINNo205 Lbs6 ft3NoNoAssign ManuallyNoNo32025-08-27FalseFalsePro & Farm867,500$17,704$0$0$No867,500$867,500$-------867,500$867,500$-------NoNo-------Lien
Felix Unger SorumMoose (WPG)RW202005-09-14NORYes170 Lbs5 ft11NoNoProspectNoNo32025-08-27FalseFalsePro & Farm831,667$16,973$0$0$No831,667$831,667$-------831,667$831,667$-------NoNo-------Lien
Joel BlomqvistMoose (WPG)G242002-01-10FINYes200 Lbs6 ft3NoNoAssign ManuallyNoNo22024-06-29FalseFalsePro & Farm925,000$18,878$0$0$No925,000$--------925,000$--------No--------Lien
Judd CaulfieldMoose (WPG)RW252001-03-19USANo220 Lbs6 ft3NoNoAssign ManuallyNoNo22024-06-29FalseFalsePro & Farm837,500$17,092$0$0$No837,500$--------837,500$--------No--------Lien
Konsta HeleniusMoose (WPG)C202006-05-11FINYes189 Lbs5 ft11NoNoAssign ManuallyNoNo32025-08-27FalseFalsePro & Farm975,000$19,898$0$0$No975,000$975,000$-------975,000$975,000$-------NoNo-------Lien
Michael KarowMoose (WPG)D271998-12-18USANo209 Lbs6 ft2NoNoTrade2025-02-01NoNo22024-07-07FalseFalsePro & Farm775,000$15,816$0$0$No775,000$--------775,000$--------No--------Lien
Roby JarventieMoose (WPG)LW232002-08-08FINNo209 Lbs6 ft3NoNoFree AgentNoNo22025-08-02FalseFalsePro & Farm995,000$20,306$0$0$No995,000$--------995,000$--------No--------Lien
Samu TuomaalaMoose (WPG)RW232003-01-08FINNo180 Lbs5 ft10NoNoAssign ManuallyNoNo22024-06-29FalseFalsePro & Farm863,333$17,619$0$0$No863,333$--------863,333$--------No--------Lien
Samuel SavoieMoose (WPG)LW222004-03-25CANYes190 Lbs5 ft10NoNoProspectNoNo32025-08-27FalseFalsePro & Farm846,666$17,279$0$0$No846,666$846,666$-------846,666$846,666$-------NoNo-------Lien
Steven SantiniMoose (WPG)D311995-03-07USANo214 Lbs6 ft3YesNoFree AgentNoNo32025-08-21FalseFalsePro & Farm775,000$15,816$0$0$No775,000$775,000$-------775,000$775,000$-------YesYes-------Lien / Lien NHL
Tucker RobertsonMoose (WPG)C222003-06-22CANNo189 Lbs5 ft11NoNoAssign ManuallyNoNo22024-06-29FalseFalsePro & Farm950,000$19,388$0$0$No950,000$--------950,000$--------No--------Lien
Tyler PitlickMoose (WPG)RW341991-11-01USANo201 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm800,000$16,327$0$0$No---------------------------Lien / Lien NHL
Uvis BalinskisMoose (WPG)D291996-08-01LATNo196 Lbs6 ft0YesNoFree AgentNoNo22025-08-21FalseFalsePro & Farm850,000$17,347$0$0$No850,000$--------850,000$--------Yes--------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1925.84196 Lbs6 ft12.26848,658$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Roby JarventieClark BishopTyler Pitlick40122
2Samuel SavoieAleksanteri KaskimakiSamu Tuomaala30122
3Eetu LiukasKonsta HeleniusJudd Caulfield20122
4Roby JarventieTucker RobertsonFelix Unger Sorum10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Uvis BalinskisSteven Santini40122
2Corey SchuenemanDakota Mermis30122
3Michael KarowAleksi Heimosalmi20122
4Uvis BalinskisSteven Santini10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Roby JarventieClark BishopTyler Pitlick60122
2Samuel SavoieAleksanteri KaskimakiSamu Tuomaala40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Uvis BalinskisSteven Santini60122
2Corey SchuenemanDakota Mermis40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Clark BishopRoby Jarventie60122
2Aleksanteri KaskimakiSamuel Savoie40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Uvis BalinskisSteven Santini60122
2Corey SchuenemanDakota Mermis40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Clark Bishop60122Uvis BalinskisSteven Santini60122
2Aleksanteri Kaskimaki40122Corey SchuenemanDakota Mermis40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Clark BishopRoby Jarventie60122
2Aleksanteri KaskimakiSamuel Savoie40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Uvis BalinskisSteven Santini60122
2Corey SchuenemanDakota Mermis40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Roby JarventieClark BishopTyler PitlickUvis BalinskisSteven Santini
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Roby JarventieClark BishopTyler PitlickUvis BalinskisSteven Santini
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Judd Caulfield, Roby Jarventie, Konsta HeleniusJudd Caulfield, Roby JarventieJudd Caulfield
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dakota Mermis, Michael Karow, Aleksi HeimosalmiDakota MermisDakota Mermis, Michael Karow
Tirs de pénalité
Tyler Pitlick, Clark Bishop, Aleksanteri Kaskimaki, Samu Tuomaala, Judd Caulfield
Gardien
#1 : Chris Driedger, #2 :
Lignes d’attaque personnalisées en prolongation
Tyler Pitlick, Clark Bishop, Aleksanteri Kaskimaki, Samu Tuomaala, Judd Caulfield, Roby Jarventie, Konsta Helenius, Samuel Savoie, Felix Unger Sorum, Eetu Liukas
Lignes de défense personnalisées en prolongation
Uvis Balinskis, Steven Santini, Corey Schueneman, Dakota Mermis, Michael Karow


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
1Eagles51400000923-142110000055030300000418-1420.2009152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632
Total51400000923-142110000055030300000418-1420.2009152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632
_Since Last GM Reset51400000923-142110000055030300000418-1420.2009152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632
_Vs Conference51400000923-142110000055030300000418-1420.2009152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632
_Vs Division50000000923-142000000055030000000418-1400.0009152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
52L2915247411631878500
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5140000923
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
211000055
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3030000418
Derniers 10 matchs
WLOTWOTL SOWSOL
140000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
20315.00%381073.68%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
32212103240
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
6010955.05%7312060.83%568665.12%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
10568127396632


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
26Moose1Eagles6LSommaire du match
414Moose2Eagles6LSommaire du match
622Eagles1Moose3WSommaire du match
830Eagles4Moose2LSommaire du match
1038Moose1Eagles6LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets330
Assistance4,0002,000
Assistance PCT100.00%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
39 3000 - 100.00% 66,000$132,000$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
0$ 1,612,450$ 1,612,450$ 925,000$0$
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$ 1 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
1Aleksanteri Kaskimaki82446110556497315629914.72%5150918.411015255500044366.54%21.3900
2Judd Caulfield82414788621001408223017.83%11154818.8946102721385259.00%31.1413
3Clark Bishop8230447457607815222413.39%17159319.4448122222483265.68%00.9323
4Samu Tuomaala823341745148789122514.67%10138616.90810183600007162.16%01.0700
5Samuel Savoie821752696457728213013.08%9151518.48156811274067.09%00.9100

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
1Chris Driedger48291330.8652.25263825997330010.5002
2Pheonix Copley42211240.8662.28231324886570000.5006

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
Saison régulière
20258245250451231919012941271101101175948141181403411144964810731958490319120979782211701716779241391412106916633545014.12%4737584.14%91460223965.21%1104181160.96%799118667.37%245518271544511956531
Total Saison régulière8245250451231919012941271101101175948141181403411144964810731958490319120979782211701716779241391412106916633545014.12%4737584.14%91460223965.21%1104181160.96%799118667.37%245518271544511956531
Séries éliminatoires
202551400000923-142110000055030300000418-1429152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632
Total Séries éliminatoires51400000923-142110000055030300000418-1429152400324074322121011631878520315.00%381073.68%06010955.05%7312060.83%568665.12%10568127396632

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
1Tyler Pitlick5134-1622714.29%06713.53011000000066.67%01.1800
2Clark Bishop5224023121118.18%010320.72011200011061.06%00.7700
3Aleksanteri Kaskimaki5303-445111030.00%09719.54202200000063.00%00.6100
4Dakota Mermis50222811220%410020.0100020000000%00.4000
5Roby Jarventie5202-12715450.00%19519.16101100000080.00%00.4200

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
1Chris Driedger51400.7795.7017900177700000