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Connexion

Moose
GP: 13 | W: 7 | L: 6
GF: 52 | GA: 53 | PP%: 26.92% | PK%: 89.09%
DG: Pascal Verret | Morale : 36 | Moyenne d’équipe : 64
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Centre de jeu
Griffins
8-9-0, 16pts
7
FINAL
5 Moose
7-6-0, 14pts
Team Stats
L1SéquenceL2
4-5-0Fiche domicile3-3-0
4-4-0Fiche domicile4-3-0
4-5-1Derniers 10 matchs6-4-0
4.41Buts par match 4.00
4.06Buts contre par match 4.08
19.75%Pourcentage en avantage numérique26.92%
73.68%Pourcentage en désavantage numérique89.09%
Moose
7-6-0, 14pts
1
FINAL
4 Griffins
8-9-0, 16pts
Team Stats
L2SéquenceL1
3-3-0Fiche domicile4-5-0
4-3-0Fiche domicile4-4-0
6-4-0Derniers 10 matchs4-5-1
4.00Buts par match 4.41
4.08Buts contre par match 4.06
26.92%Pourcentage en avantage numérique19.75%
89.09%Pourcentage en désavantage numérique73.68%
Meneurs d'équipe
Buts
Michael McLeod
15
Passes
Nikolay Goldobin
9
Points
Michael McLeod
19
Plus/Moins
Adam Ginning
3
Victoires
Filip Gustavsson
7
Pourcentage d’arrêts
Daniel Vladar
0.944

Statistiques d’équipe
Buts pour
52
4.00 GFG
Tirs pour
426
32.77 Avg
Pourcentage en avantage numérique
26.9%
14 GF
Début de zone offensive
38.3%
Buts contre
53
4.08 GAA
Tirs contre
376
28.92 Avg
Pourcentage en désavantage numérique
89.1%%
6 GA
Début de la zone défensive
35.0%
Informations de l'équipe

Directeur généralPascal Verret
EntraîneurJared Bednar
DivisionThayer-Tutt
ConférenceRobert-Lebel
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,991
Billets de saison300


Informations de la formation

Équipe Pro34
Équipe Mineure18
Limite contact 52 / 250
Espoirs0


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
1Dylan Strome (R)X100.006628817171837878878373575856476084710213975,000$
2Mathieu Joseph (R)X100.007638747676687776627177736852465384710212975,000$
3Nikolay Goldobin (R)X100.006937827774726182677472717951475183710223975,000$
4Michael McLeod (R)X100.005837768567716284676773677647445883700203975,000$
5Chase De Leo (R)X100.006930837272727370727875556449465275690222900,000$
6Nick Paul (R)X100.006649847173707068677374596945454083680232800,000$
7Vinni Lettieri (R)X100.006539867379787457687860656050504535670231500,000$
8Anders Bjork (R)X100.006429758262686582617061597144454479660221650,000$
9Julien Gauthier (R)X100.006429816175686070647175546446435174650212650,000$
10Boris Katchouk (R)X100.007042766863687272676366536743456583640201500,000$
11Kieffer Bellows (R)X100.006324815676696965666473457043445962630203550,000$
12Jake Leschyshyn (R)X100.007636656677618071636560525442427083620191500,000$
13Ludwig Bystrom (R)X100.007423777978767979507361786169503861730241975,000$
14Matthew Benning (R)X100.007022817171746568497161755752514152690241850,000$
15Juuso Valimaki (R)X100.005630708062696479368151715043436534660201500,000$
16Nelson Nogier (R)X100.006641766668696463426860724845454346660221650,000$
17Caleb Jones (R)X100.007344596075704459345752703943435541630211550,000$
18Josh Mahura (R)X100.005537757458636277326956664343435484630203650,000$
19Joey Keane (R)X100.006342806063645966486546595642415841610192500,000$
Rayé
1Tomas JurcoX100.007633757183747073737772657267623338710261775,000$
2Mitchell Stephens (R)X100.004929937167826651736859634843435220620211500,000$
3Nathan Bastian (R)X100.005142746061736369816762526143454620620211500,000$
4Max Jones (R)X100.006844676671567563486962564642425419610202500,000$
5William Bitten (R)X100.007242636669557166515966516042435220600202500,000$
6Riley Damiani (R)X100.005521725547586162686757425040407420560182500,000$
7Jonatan Berggren (R)X100.005528766153566364677055364440406820560182500,000$
8Alexander Khovanov (R)X100.004121696041606052646151394640406320520182500,000$
9Adam Ginning (R)X100.006241626475694848316345564540406624590182500,000$
10Jonathan Kovacevic (R)X100.006234645758655647366240623643454420570211400,000$
11Jonny Tychonick (R)X100.005332695949395972265541604140407520550182500,000$
MOYENNE D’ÉQUIPE100.00643475686767666857696159574645545064
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
1Filip Gustavsson100.00697278686182836155826949446584680203950,000$
2Daniel Vladar100.00546848695968597266575843446154610212700,000$
Rayé
1Karel Vejmelka100.00756071817661576573497346484924660221500,000$
2Joey Daccord100.00696767505474755754705545444924620222500,000$
MOYENNE D’ÉQUIPE100.0067676667637169646265644645564764
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jared Bednar53568572375954CAN543950,000$


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
1Michael McLeodMoose (Win)C1315419-460241859113425.42%722417.237188311013223146.31%14953011.7000000220
2Dylan StromeMoose (Win)C138715-860193147184117.02%1029822.942355411012493051.62%432810001.0100000111
3Nikolay GoldobinMoose (Win)LW135914-78016135521429.09%729522.762249410004471148.15%2793110.9500000200
4Mathieu JosephMoose (Win)RW134913-514025154814268.33%424318.77033441000000147.62%2173001.0700000110
5Ludwig BystromMoose (Win)D91910-480171322934.55%320622.9005553100009000%063000.9700000000
6Nick PaulMoose (Win)LW133710-420221523111513.04%422717.482576310000240030.77%1356000.8800000020
7Nelson NogierMoose (Win)D13178-320191912858.33%1933425.76000133011051000%0215000.4811000000
8Anders BjorkMoose (Win)LW132572401071981610.53%215612.07000010000160040.00%5101000.8900000001
9Vinni LettieriMoose (Win)RW13066-4001414145110%220015.39033230000000057.14%705000.6000000000
10Jake LeschyshynMoose (Win)C135160401691741129.41%11138.7300000000070147.22%3611001.0600000011
11Chase De LeoMoose (Win)C1342622018152971313.79%416312.58000010000200050.00%6483000.7300000010
12Caleb JonesMoose (Win)D13055-29527227450%925219.44000014000036000%0010000.4000000000
13Juuso ValimakiMoose (Win)D13145-5180182120175.00%2131324.12112543022144000%0715000.3200000000
14Boris KatchoukMoose (Win)LW13033040410127120%31048.0800000000000033.33%330000.5700000000
15Joey KeaneMoose (Win)D13112-112091242225.00%617413.390000000009000%009000.2300000000
16Julien GauthierMoose (Win)RW1311220015914547.14%213610.510000100000000%212000.2900000000
17Josh MahuraMoose (Win)D13112-7100822168116.25%1124118.56000126000035000%074000.1700000001
18Adam GinningMoose (Win)D4011320340000%65012.740000000001000%002000.3900000000
19Kieffer BellowsMoose (Win)RW130110004108160%01037.9700000000000025.00%410000.1900000000
Statistiques d’équipe totales ou en moyenne2345283135-45111528827942614426412.21%121384216.4214233746370235103757449.28%7638095120.7011000684
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
1Filip GustavssonMoose (Win)137510.8554.0876520523581742000130000
2Daniel VladarMoose (Win)10000.9442.502400118120000013000
Statistiques d’équipe totales ou en moyenne147510.8594.0378920533761862001313000


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 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 Non Activé 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 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 GinningMoose (Win)D182000-01-01Yes196 Lbs6 ft3NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Alexander KhovanovMoose (Win)C182000-01-01Yes192 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Anders BjorkMoose (Win)LW221996-01-01Yes190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm650,000$0$0$No------------------
Boris KatchoukMoose (Win)LW201998-01-01Yes206 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Caleb JonesMoose (Win)D211997-01-01Yes194 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm550,000$0$0$No------------------
Chase De LeoMoose (Win)C221996-01-01Yes179 Lbs5 ft9NoNoN/ANoNo2FalseFalsePro & Farm900,000$0$0$No900,000$--------No--------
Daniel VladarMoose (Win)G211997-01-01No185 Lbs6 ft5NoNoN/ANoNo2FalseFalsePro & Farm700,000$0$0$No750,000$--------No--------
Dylan StromeMoose (Win)C211997-01-01Yes200 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm975,000$0$0$No1,500,000$2,250,000$-------NoNo-------
Filip GustavssonMoose (Win)G201998-01-01No183 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm950,000$0$0$No950,000$950,000$-------NoNo-------
Jake LeschyshynMoose (Win)C191999-01-01Yes192 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Joey DaccordMoose (Win)G221996-01-01No197 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------
Joey KeaneMoose (Win)D191999-01-01Yes187 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Jonatan BerggrenMoose (Win)LW182000-01-01Yes195 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Jonathan KovacevicMoose (Win)D211997-01-01Yes208 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm400,000$0$0$No------------------
Jonny TychonickMoose (Win)D182000-01-01Yes187 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Josh MahuraMoose (Win)D201998-01-01Yes185 Lbs6 ft0NoNoN/ANoNo3FalseFalsePro & Farm650,000$0$0$No650,000$650,000$-------NoNo-------
Julien GauthierMoose (Win)RW211997-01-01Yes227 Lbs6 ft4NoNoN/ANoNo2FalseFalsePro & Farm650,000$0$0$No650,000$--------No--------
Juuso ValimakiMoose (Win)D201998-01-01Yes212 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Karel VejmelkaMoose (Win)G221996-01-01No224 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Kieffer BellowsMoose (Win)RW201998-01-01Yes194 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm550,000$0$0$No550,000$550,000$-------NoNo-------
Ludwig BystromMoose (Win)D241994-01-01Yes169 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm975,000$0$0$No------------------
Mathieu JosephMoose (Win)RW211997-01-01Yes190 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm975,000$0$0$No1,000,000$--------No--------
Matthew BenningMoose (Win)D241994-01-01Yes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm850,000$0$0$No------------------
Max JonesMoose (Win)LW201998-01-01Yes220 Lbs6 ft1NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------
Michael McLeodMoose (Win)C201998-01-01Yes187 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm975,000$0$0$No975,000$975,000$-------NoNo-------
Mitchell StephensMoose (Win)C211997-01-01Yes193 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Nathan BastianMoose (Win)RW211997-01-01Yes205 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
Nelson NogierMoose (Win)D221996-01-01Yes191 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm650,000$0$0$No------------------
Nick PaulMoose (Win)LW231995-01-01Yes185 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm800,000$0$0$No900,000$--------No--------
Nikolay GoldobinMoose (Win)LW221996-01-01Yes196 Lbs5 ft11NoNoN/ANoNo3FalseFalsePro & Farm975,000$0$0$No975,000$975,000$-------NoNo-------
Riley DamianiMoose (Win)C182000-01-01Yes170 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------Lien
Tomas JurcoMoose (Win)RW261992-01-01No203 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm775,000$0$0$No------------------
Vinni LettieriMoose (Win)RW231995-01-01Yes185 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No------------------
William BittenMoose (Win)RW201998-01-01Yes179 Lbs5 ft10NoNoN/ANoNo2FalseFalsePro & Farm500,000$0$0$No500,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3420.82194 Lbs6 ft11.76645,588$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolay GoldobinDylan StromeMathieu Joseph40122
2Nick PaulMichael McLeodVinni Lettieri30122
3Anders BjorkChase De LeoJulien Gauthier20122
4Boris KatchoukJake LeschyshynKieffer Bellows10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew BenningJuuso Valimaki40122
2Nelson NogierCaleb Jones30122
3Josh MahuraJoey Keane20122
4Matthew BenningJuuso Valimaki10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nikolay GoldobinDylan StromeMathieu Joseph60122
2Nick PaulMichael McLeodVinni Lettieri40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew BenningJuuso Valimaki60122
2Nelson NogierCaleb Jones40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dylan StromeNikolay Goldobin60122
2Michael McLeodNick Paul40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew BenningJuuso Valimaki60122
2Nelson NogierCaleb Jones40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Dylan Strome60122Matthew BenningJuuso Valimaki60122
2Michael McLeod40122Nelson NogierCaleb Jones40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan StromeNikolay Goldobin60122
2Michael McLeodNick Paul40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Matthew BenningJuuso Valimaki60122
2Nelson NogierCaleb Jones40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolay GoldobinDylan StromeMathieu JosephMatthew BenningJuuso Valimaki
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nikolay GoldobinDylan StromeMathieu JosephMatthew BenningJuuso Valimaki
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Chase De Leo, Nick Paul, Vinni LettieriChase De Leo, Nick PaulChase De Leo
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Caleb Jones, Josh Mahura, Joey KeaneCaleb JonesCaleb Jones, Josh Mahura
Tirs de pénalité
Mathieu Joseph, Nikolay Goldobin, Dylan Strome, Michael McLeod, Chase De Leo
Gardien
#1 : Filip Gustavsson, #2 : Daniel Vladar
Lignes d’attaque personnalisées en prolongation
Mathieu Joseph, Nikolay Goldobin, Dylan Strome, Michael McLeod, Chase De Leo, Nick Paul, Nick Paul, Vinni Lettieri, Anders Bjork, Julien Gauthier, Boris Katchouk
Lignes de défense personnalisées en prolongation
Matthew Benning, Juuso Valimaki, Nelson Nogier, Caleb Jones, Josh Mahura


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
1Griffins734000002630-4312000001214-2422000001416-260.429264268001318183220160125130112115064170341029.41%32487.50%114929251.03%14226753.18%8520441.67%276154274125238113
2Reign64200000262333210000012111321000001412280.66726416700131818320616012513011165714911818422.22%23291.30%114929251.03%14226753.18%8520441.67%276154274125238113
Total1376000005253-1633000002425-17430000028280140.538528313500131818342616012513011376121113288521426.92%55689.09%214929251.03%14226753.18%8520441.67%276154274125238113
_Since Last GM Reset1376000005253-1633000002425-17430000028280140.538528313500131818342616012513011376121113288521426.92%55689.09%214929251.03%14226753.18%8520441.67%276154274125238113
_Vs Conference1376000005253-1633000002425-17430000028280140.538528313500131818342616012513011376121113288521426.92%55689.09%214929251.03%14226753.18%8520441.67%276154274125238113
_Vs Division734000002630-4312000001214-2422000001416-260.429264268001318183220160125130112115064170341029.41%32487.50%114929251.03%14226753.18%8520441.67%276154274125238113

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1314L2528313542637612111328800
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
137600005253
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
63300002425
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
74300002828
Derniers 10 matchs
WLOTWOTL SOWSOL
343000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
521426.92%55689.09%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
160125130111318183
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
14929251.03%14226753.18%8520441.67%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
276154274125238113


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
12Moose6Reign4WSommaire du match
210Moose4Reign5LXSommaire du match
318Reign4Moose2LSommaire du match
426Reign3Moose4WXSommaire du match
534Moose4Reign3WXSommaire du match
642Reign4Moose6WSommaire du match
857Moose3Griffins2WXR1Sommaire du match
961Moose2Griffins5LSommaire du match
1065Griffins2Moose4WR1Sommaire du match
1169Griffins5Moose3LSommaire du match
1273Moose8Griffins5WR1Sommaire du match
1377Griffins7Moose5LSommaire du match
1481Moose1Griffins4LR1Sommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance11,9615,984
Assistance PCT99.68%99.73%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
34 2991 - 99.69% 188,410$1,130,462$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
0$ 2,195,000$ 2,170,000$ 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$ 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