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Moose
GP: 80 | W: 38 | L: 39 | OTL: 3 | P: 79
GF: 329 | GA: 360 | PP%: 22.60% | PK%: 76.52%
DG: Pascal Verret | Morale : 39 | Moyenne d’équipe : 64

Centre de jeu
Icehogs
39-34-7, 85pts
5
FINAL
8 Moose
38-39-3, 79pts
Team Stats
L1SéquenceL1
21-15-4Fiche domicile24-15-1
18-19-3Fiche domicile14-24-2
3-5-2Derniers 10 matchs7-3-0
4.29Buts par match 4.11
4.16Buts contre par match 4.50
27.18%Pourcentage en avantage numérique22.60%
79.55%Pourcentage en désavantage numérique76.52%
Moose
38-39-3, 79pts
2
FINAL
5 Wolfpack
44-29-7, 95pts
Team Stats
L1SéquenceW1
24-15-1Fiche domicile25-13-2
14-24-2Fiche domicile19-16-5
7-3-0Derniers 10 matchs5-4-1
4.11Buts par match 4.08
4.50Buts contre par match 3.85
22.60%Pourcentage en avantage numérique20.74%
76.52%Pourcentage en désavantage numérique78.35%
Meneurs d'équipe
Buts
Eetu Luostarinen
35
Passes
Juuso Valimaki
50
Points
Eetu Luostarinen
84
Plus/Moins
Joey Keane
12
Victoires
Filip Gustavsson
37
Pourcentage d’arrêts
Filip Gustavsson
0.87

Statistiques d’équipe
Buts pour
329
4.11 GFG
Tirs pour
2587
32.34 Avg
Pourcentage en avantage numérique
22.6%
73 GF
Début de zone offensive
35.5%
Buts contre
360
4.50 GAA
Tirs contre
2647
33.09 Avg
Pourcentage en désavantage numérique
76.5%%
81 GA
Début de la zone défensive
37.7%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,743
Billets de saison300


Informations de la formation

Équipe Pro35
Équipe Mineure19
Limite contact 54 / 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
1Eetu Luostarinen (R)X100.006231947370857966707767746355456048710214900,000$
2Nick PaulX100.006949857176747371697576627152483634700241900,000$
3Reid BoucherX100.006929747079687368757782626657543348700261850,000$
4Morgan Geekie (R)X100.006729807769757471768069485548445782680214900,000$
5Julien Gauthier (R)X100.006729836575716373677377586648464735680221650,000$
6Morgan Barron (R)X100.007350717086488174507072595343445374660214800,000$
7Jake Leschyshyn (R)X100.007736707179678174716964585945436359660204750,000$
8Mitchell Stephens (R)X100.005031967368846854756963665144444550650222600,000$
9Axel Jonsson-Fjallby (R)X100.007340816262605572737167635946465541650212500,000$
10Lukas Rousek (R)X100.005832797758605069546060457443445622600202500,000$
11Riley Damiani (R)X100.005723735752626364706859455341416524580191500,000$
12Aliaksei Protas (R)X100.006936616769537359495958555340408450580182500,000$
13Ludwig BystromX100.007623768077768178537364796476513555740251950,000$
14Juuso Valimaki (R)X100.006229738270776981418255735452455857700212900,000$
15Caleb Jones (R)X100.007544676673724765426358754648464940670223750,000$
16Josh Mahura (R)X100.005838767764676679387258694748454962660212650,000$
17Joey Keane (R)X100.006642846667706370546951666143435236650201500,000$
18Jonny Tychonick (R)X100.005533726155446274275743624241416625580191500,000$
Rayé
1Anders Bjork (R)X100.006829778366726981637364617148474019680231800,000$
2Logan O'Connor (R)X100.007038827072646476696968577349494544670233500,000$
3Boris Katchouk (R)X100.007242786966707475706368587044475937660214750,000$
4Nathan Bastian (R)X100.005344766163756570837065536344464120640221500,000$
5Max Jones (R)X100.007146696873607765517264584943434720630211500,000$
6William Bitten (R)X100.007445656970597367536267546243444619630211500,000$
7Jonatan Berggren (R)X100.005629786358616467697157374641416020580191500,000$
8Jaret Anderson-Dolan (R)X100.006944576059446660505963514442425419570202550,000$
9John Beecher (R)X100.006737615665537465526361464440406922570182500,000$
10Juuso Parssinen (R)X100.006634665358546359575860445940407219550182500,000$
11Alexander Khovanov (R)X100.004423726246626254666352414741415620540191500,000$
12Matthew BenningX90.957122827375776470527363765559543728710251900,000$
13Adam Ginning (R)X77.726544646676714951326547584841415815610191500,000$
MOYENNE D’ÉQUIPE98.99653675686866676859696358574745533764
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 Gustavsson100.00727581716684856560837259475979720212950,000$
2Daniel Vladar100.00577054716270627468606146465564640221750,000$
Rayé
1Karel Vejmelka100.00766172817762596674517249504520670232650,000$
2Olle Eriksson Ek100.00585164576363536054566142425020570201500,000$
MOYENNE D’ÉQUIPE100.0066646870677065666463674946524665
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jared Bednar53568572375954CAN552950,000$


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
1Eetu LuostarinenMoose (Win)LW793549845201201312327413515.09%61172321.811014243223721392903344.19%3015433000.9834000525
2Jake LeschyshynMoose (Win)C80294978-49601311301996113514.57%29141417.68717242318310151384149.42%15583922111.1001000251
3Nick PaulMoose (Win)LW60273663-618091721873910514.44%28115319.23612182716610141353237.11%974620111.0901000315
4Juuso ValimakiMoose (Win)D7985058-224807612815265675.26%98172921.895914252090004200130%02958000.6701000011
5Logan O'ConnorMoose (Win)RW7729295852409272199619614.57%19105113.662687710002505033.78%743221011.1000000622
6Morgan GeekieMoose (Win)RW78282856-11240102642306711812.17%25127016.2955101812200082081348.96%965821010.8824000324
7Ludwig BystromMoose (Win)D76144155-20840126187187721017.49%136211627.84512173228611211259310%07781000.5201000114
8Julien GauthierMoose (Win)RW61252348-32007556162548015.43%19104917.21459161830004303139.24%792319000.9111000513
9Matthew BenningMoose (Win)D6764147-2032010813110839385.56%120186227.80279212690224238000%04067000.5000000002
10Morgan BarronMoose (Win)LW75201737-4320113651655310812.12%14102813.7101189000031210256.25%322814000.7200000214
11Axel Jonsson-FjallbyMoose (Win)LW7420143401756447145407813.79%197009.46213315000082060.00%352812000.9700100114
12Anders BjorkMoose (Win)LW30121931-2140512898305812.24%1351217.07651114800003671169.23%13227001.2100000100
13Boris KatchoukMoose (Win)LW73131629-5260856813138839.92%1384711.610224390001462047.37%382614000.6800000101
14Josh MahuraMoose (Win)D80227297375361008330412.41%81112114.02101139000266000%01229000.5200100000
15Mitchell StephensMoose (Win)C70121527300398359203720.34%1685412.211015740001340048.65%520711000.6300000111
16Reid BoucherMoose (Win)C221113242200334063133917.46%1244020.044598490001464050.32%62275001.0912000110
17Caleb JonesMoose (Win)D6932023-128610102715821325.17%80131319.03123101470000155000%0947000.3500010000
18Lukas RousekMoose (Win)RW55121022-11100251480234915.00%24518.2100001000002041.67%12214000.9700000110
19Aliaksei ProtasMoose (Win)RW795914-10380874329143017.24%127339.280002120000111037.04%2759000.3800000020
20Joey KeaneMoose (Win)D5819101222102350246144.17%3773212.6300002000054000%0321000.2700101000
21Riley DamianiMoose (Win)C40549-1018029403081516.67%341810.47000000000220048.29%20542000.4300000000
22Jaret Anderson-DolanMoose (Win)C27224-51803514136615.38%62097.75000000000140049.37%7902000.3800000001
23Nathan BastianMoose (Win)RW31231002161116.67%1248.290000000000000%000002.4100000001
24William BittenMoose (Win)RW7202-20042133415.38%2476.8000000000040020.00%510100.8400000000
25Jonny TychonickMoose (Win)D1801151004176120%619010.580000000004000%005000.1100000000
26John BeecherMoose (Win)C26011-13100211510780%32198.4300000000000037.14%10522000.0900000000
27Adam GinningMoose (Win)D1300016010124100%1114811.460000000003000%01200000000000
28Max JonesMoose (Win)LW3000000000000%000.160000000000000%00000000000000
29Juuso ParssinenMoose (Win)LW15000-8401384120%51409.390000000003000%21100000000000
Statistiques d’équipe totales ou en moyenne1494322525847-12771630169716892677848148212.03%8712350615.73611031642562286549622218351747.87%3900575529340.72715311332239
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)79373130.8704.2442342129922941056420.58312782211
2Karel VejmelkaMoose (Win)51300.8395.53152001487440100112000
3Olle Eriksson EkMoose (Win)10000.71414.1217004146000001000
4Daniel VladarMoose (Win)150500.8405.7344000422631252000166000
Statistiques d’équipe totales ou en moyenne100383930.8654.454845213592658123163128081211


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
Adam Ginning (sur la masse salariale)Moose (Win)D192000-01-01SWEYes196 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$Yes---------------------------
Alexander KhovanovMoose (Win)C192000-01-01RUSYes192 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Aliaksei ProtasMoose (Win)RW182001-01-01BLRYes225 Lbs6 ft2NoNoTrade2024-12-09NoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Anders BjorkMoose (Win)LW231996-01-01USAYes190 Lbs6 ft0NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm800,000$0$0$No---------------------------
Axel Jonsson-FjallbyMoose (Win)LW211998-01-01SWEYes190 Lbs6 ft1NoNoTrade2024-12-29NoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Boris KatchoukMoose (Win)LW211998-01-01CANYes206 Lbs6 ft2NoNoFree AgentNoNo42024-08-21FalseFalsePro & Farm750,000$0$0$No800,000$850,000$950,000$------750,000$750,000$750,000$------NoNoNo------
Caleb JonesMoose (Win)D221997-01-01USAYes194 Lbs6 ft1NoNoFree AgentNoNo32024-08-21FalseFalsePro & Farm750,000$0$0$No800,000$850,000$-------750,000$750,000$-------NoNo-------
Daniel VladarMoose (Win)G221997-01-01CZENo185 Lbs6 ft5NoNoN/ANoNo1FalseFalsePro & Farm750,000$0$0$No---------------------------
Eetu LuostarinenMoose (Win)LW211998-01-01FINYes190 Lbs6 ft3NoNoTrade2025-01-22NoNo42024-09-07FalseFalsePro & Farm900,000$0$0$No1,250,000$2,000,000$2,500,000$------900,000$900,000$900,000$------NoNoNo------
Filip GustavssonMoose (Win)G211998-01-01SWENo183 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm950,000$0$0$No950,000$--------950,000$--------No--------
Jake LeschyshynMoose (Win)C201999-01-01USAYes192 Lbs5 ft11NoNoFree AgentNoNo42024-08-21FalseFalsePro & Farm750,000$0$0$No800,000$850,000$950,000$------750,000$750,000$750,000$------NoNoNo------
Jaret Anderson-DolanMoose (Win)C201999-01-01CANYes200 Lbs5 ft11NoNoFree AgentNoNo22024-10-11FalseFalsePro & Farm550,000$0$0$No550,000$--------550,000$--------No--------
Joey KeaneMoose (Win)D201999-01-01USAYes187 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
John BeecherMoose (Win)C182001-01-01USAYes216 Lbs6 ft3NoNoTrade2025-02-21NoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Jonatan BerggrenMoose (Win)RW192000-01-01SWEYes195 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Jonny TychonickMoose (Win)D192000-01-01CANYes187 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Josh MahuraMoose (Win)D211998-01-01CANYes185 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm650,000$0$0$No650,000$--------650,000$--------No--------
Julien GauthierMoose (Win)RW221997-01-01CANYes227 Lbs6 ft4NoNoTrade2025-02-23NoNo1FalseFalsePro & Farm650,000$0$0$No---------------------------
Juuso ParssinenMoose (Win)LW182001-01-01FINYes212 Lbs6 ft3NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Juuso ValimakiMoose (Win)D211998-01-01FINYes212 Lbs6 ft2NoNoFree AgentNoNo22024-08-21FalseFalsePro & Farm900,000$0$0$No950,000$--------900,000$--------No--------
Karel VejmelkaMoose (Win)G231996-01-01CZENo224 Lbs6 ft4NoNoFree AgentNoNo22024-08-21FalseFalsePro & Farm650,000$0$0$No650,000$--------650,000$--------No--------
Logan O'ConnorMoose (Win)RW231996-01-01USAYes174 Lbs6 ft0NoNoTrade2024-12-29NoNo3FalseFalsePro & Farm500,000$0$0$No500,000$500,000$-------500,000$500,000$-------NoNo-------
Ludwig BystromMoose (Win)D251994-01-01SWENo169 Lbs6 ft0NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm950,000$0$0$No---------------------------
Lukas RousekMoose (Win)RW201999-01-01CZEYes172 Lbs5 ft11NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$0$0$No500,000$--------500,000$--------No--------Lien
Matthew Benning (sur la masse salariale)Moose (Win)D251994-01-01CANNo180 Lbs6 ft0NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm900,000$0$0$Yes---------------------------
Max JonesMoose (Win)LW211998-01-01USAYes220 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Mitchell StephensMoose (Win)C221997-01-01CANYes193 Lbs5 ft11NoNoFree AgentNoNo22024-08-21FalseFalsePro & Farm600,000$0$0$No700,000$--------600,000$--------No--------
Morgan BarronMoose (Win)LW211998-01-01CANYes220 Lbs6 ft4NoNoTrade2025-03-20NoNo42024-08-21FalseFalsePro & Farm800,000$0$0$No800,000$800,000$800,000$------800,000$800,000$800,000$------NoNoNo------
Morgan GeekieMoose (Win)RW211998-01-01CANYes192 Lbs6 ft3NoNoTrade2025-03-20NoNo42024-08-21FalseFalsePro & Farm900,000$0$0$No900,000$900,000$900,000$------900,000$900,000$900,000$------NoNoNo------
Nathan BastianMoose (Win)RW221997-01-01CANYes205 Lbs6 ft4NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm500,000$0$0$No---------------------------
Nick PaulMoose (Win)LW241995-01-01CANNo185 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------
Olle Eriksson EkMoose (Win)G201999-01-01SWENo189 Lbs6 ft3NoNoTrade2024-12-29NoNo12024-10-07FalseFalsePro & Farm500,000$0$0$No---------------------------
Reid BoucherMoose (Win)C261993-01-01USANo195 Lbs5 ft10NoNoFree AgentNoNo12025-03-20FalseFalsePro & Farm850,000$0$0$No---------------------------
Riley DamianiMoose (Win)C192000-01-01CANYes170 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
William BittenMoose (Win)RW211998-01-01CANYes179 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3521.09195 Lbs6 ft11.86655,714$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Eetu LuostarinenReid BoucherMorgan Geekie35122
2Nick PaulJake LeschyshynJulien Gauthier25122
3Morgan BarronMitchell StephensLukas Rousek20122
4Axel Jonsson-FjallbyRiley DamianiAliaksei Protas20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ludwig BystromJuuso Valimaki40122
2Caleb JonesJosh Mahura30122
3Joey KeaneJonny Tychonick20122
4Ludwig BystromJuuso Valimaki10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Eetu LuostarinenReid BoucherMorgan Geekie60122
2Nick PaulJake LeschyshynJulien Gauthier40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ludwig BystromJuuso Valimaki60122
2Caleb JonesJosh Mahura40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Reid BoucherEetu Luostarinen60122
2Jake LeschyshynNick Paul40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ludwig BystromJuuso Valimaki60122
2Caleb JonesJosh Mahura40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Reid Boucher60122Ludwig BystromJuuso Valimaki60122
2Jake Leschyshyn40122Caleb JonesJosh Mahura40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Reid BoucherEetu Luostarinen60122
2Jake LeschyshynNick Paul40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Ludwig BystromJuuso Valimaki60122
2Caleb JonesJosh Mahura40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Eetu LuostarinenReid BoucherMorgan GeekieLudwig BystromJuuso Valimaki
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Eetu LuostarinenReid BoucherMorgan GeekieLudwig BystromJuuso Valimaki
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Julien Gauthier, Morgan Barron, Jake LeschyshynJulien Gauthier, Morgan BarronJulien Gauthier
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Josh Mahura, Joey Keane, Jonny TychonickJosh MahuraJosh Mahura, Joey Keane
Tirs de pénalité
Eetu Luostarinen, Nick Paul, Reid Boucher, Morgan Geekie, Julien Gauthier
Gardien
#1 : Filip Gustavsson, #2 : Daniel Vladar
Lignes d’attaque personnalisées en prolongation
Eetu Luostarinen, Nick Paul, Reid Boucher, Morgan Geekie, Julien Gauthier, Morgan Barron, Jake Leschyshyn, Axel Jonsson-Fjallby, Mitchell Stephens, Lukas Rousek
Lignes de défense personnalisées en prolongation
Ludwig Bystrom, Juuso Valimaki, Caleb Jones, Josh Mahura, Joey Keane


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
1Admirals3120000058-3110000003032020000028-620.33358130110210211999082889984923773424749111.11%12375.00%0832178346.66%904189447.73%656135248.52%167793017217521434715
2Americans3110100010100100010004312110000067-140.66710162600102102119996828899849231103522649222.22%11281.82%0832178346.66%904189447.73%656135248.52%167793017217521434715
3Barracuda64200000272343210000016133321000001110180.667274673001021021199200828899849231816773116291034.48%30776.67%0832178346.66%904189447.73%656135248.52%167793017217521434715
4Bears2110000069-31010000037-41100000032120.500610160010210211995782889984923782212334250.00%7357.14%0832178346.66%904189447.73%656135248.52%167793017217521434715
5Canucks20200000911-21010000067-11010000034-100.000913220010210211996982889984923651514379333.33%7271.43%0832178346.66%904189447.73%656135248.52%167793017217521434715
6Checkers2110000012931100000010461010000025-320.500121830001021021199738288998492363146409222.22%30100.00%1832178346.66%904189447.73%656135248.52%167793017217521434715
7Comets20200000516-111010000036-310100000210-800.0005914001021021199648288998492372171245200.00%6183.33%0832178346.66%904189447.73%656135248.52%167793017217521434715
8Condors63300000323023210000017134312000001517-260.50032548610102102119918982889984923206665413533721.21%26580.77%2832178346.66%904189447.73%656135248.52%167793017217521434715
9Crunch21100000752110000005231010000023-120.500714210010210211996082889984923682914356233.33%7271.43%0832178346.66%904189447.73%656135248.52%167793017217521434715
10Eagles211000009901010000035-21100000064220.500915240010210211995982889984923643314339111.11%7357.14%0832178346.66%904189447.73%656135248.52%167793017217521434715
11Firebirds2020000048-41010000025-31010000023-100.0004711001021021199558288998492367391847300.00%9188.89%0832178346.66%904189447.73%656135248.52%167793017217521434715
12Griffins631001102721632000010189931100100912-390.75027426900102102119918782889984923176567512335617.14%35682.86%0832178346.66%904189447.73%656135248.52%167793017217521434715
13Gulls622010012630-43100100114131312000001217-570.58326457100102102119920482889984923192628413033927.27%371267.57%0832178346.66%904189447.73%656135248.52%167793017217521434715
14Icehogs413000002129-8211000001112-1202000001017-720.2502135560010210211991318288998492317048436913430.77%19952.63%0832178346.66%904189447.73%656135248.52%167793017217521434715
15Islander21000001871110000006421000000123-130.75081422001021021199728288998492373286468450.00%3166.67%0832178346.66%904189447.73%656135248.52%167793017217521434715
16Little Stars532000002824443100000221661010000068-260.60028497710102102119918982889984923170453110121419.05%13192.31%0832178346.66%904189447.73%656135248.52%167793017217521434715
17Marlies422000001217-51010000027-5321000001010040.5001218300010210211991208288998492311534368418316.67%19478.95%0832178346.66%904189447.73%656135248.52%167793017217521434715
18Penguins211000009721010000023-11100000074320.500915240010210211996182889984923722216409222.22%8275.00%0832178346.66%904189447.73%656135248.52%167793017217521434715
19Phantoms312000001215-321100000911-21010000034-120.33312203200102102119911182889984923992730511119.09%15660.00%1832178346.66%904189447.73%656135248.52%167793017217521434715
20Punishers21100000814-610100000311-81100000053220.500816240010210211997682889984923711412495360.00%6183.33%0832178346.66%904189447.73%656135248.52%167793017217521434715
21Rockets311010001192100010005412110000065140.6671118290010210211998482889984923903322691119.09%11281.82%0832178346.66%904189447.73%656135248.52%167793017217521434715
22Senators3110001013130210000109721010000046-240.667131831001021021199948288998492310146325712325.00%16381.25%0832178346.66%904189447.73%656135248.52%167793017217521434715
23Thunderbirds21100000810-21010000036-31100000054120.500815230010210211997282889984923672318286116.67%9277.78%0832178346.66%904189447.73%656135248.52%167793017217521434715
24Wolfpack302010001116-520101000911-21010000025-320.33311193000102102119990828899849231153830749111.11%15380.00%0832178346.66%904189447.73%656135248.52%167793017217521434715
25Wranglers31200000910-1110000006332020000037-420.3339152410102102119984828899849238534286310110.00%140100.00%0832178346.66%904189447.73%656135248.52%167793017217521434715
Total80323904122329360-3140181504021191182940142400101138178-40790.494329549878311021021199258782889984923264788172616433237322.60%3458176.52%4832178346.66%904189447.73%656135248.52%167793017217521434715
_Since Last GM Reset80323904122329360-3140181504021191182940142400101138178-40790.494329549878311021021199258782889984923264788172616433237322.60%3458176.52%4832178346.66%904189447.73%656135248.52%167793017217521434715
_Vs Conference50212203121205215-1023125030211149519279170010091120-29540.540205335540211021021199159082889984923160254252310352234821.52%2455975.92%3832178346.66%904189447.73%656135248.52%167793017217521434715
_Vs Division241280111111210481272010116548171256001004756-9300.625112187299101021021199780828899849237552512865041303224.62%1283076.56%2832178346.66%904189447.73%656135248.52%167793017217521434715

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8079L132954987825872647881726164331
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8032394122329360
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4018154021191182
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4014240101138178
Derniers 10 matchs
WLOTWOTL SOWSOL
630010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3237322.60%3458176.52%4
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
828899849231021021199
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
832178346.66%904189447.73%656135248.52%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
167793017217521434715


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
413Little Stars2Moose6WSommaire du match
522Moose5Marlies3WSommaire du match
839Barracuda7Moose5LR1Sommaire du match
1049Moose2Barracuda4LSommaire du match
1259Moose4Gulls9LR1Sommaire du match
1466Griffins2Moose7WR1Sommaire du match
1885Condors3Moose5WSommaire du match
2096Moose5Condors7LR1Sommaire du match
22112Gulls4Moose3LXXSommaire du match
25128Moose2Marlies6LSommaire du match
27135Moose2Griffins8LR1Sommaire du match
29146Little Stars6Moose3LSommaire du match
31159Moose6Condors3WR1Sommaire du match
32171Moose5Rockets2WSommaire du match
34178Phantoms5Moose7WSommaire du match
37191Moose1Griffins2LXR1Sommaire du match
39202Condors7Moose4LSommaire du match
41211Moose6Eagles4WSommaire du match
46231Barracuda2Moose3WR1Sommaire du match
48241Moose6Griffins2WR1Sommaire du match
50253Moose4Condors7LSommaire du match
51260Eagles5Moose3LSommaire du match
55281Islander4Moose6WSommaire du match
60304Bears7Moose3LSommaire du match
62315Moose6Icehogs7LSommaire du match
64324Moose2Wranglers4LSommaire du match
65332Phantoms6Moose2LSommaire du match
68351Moose3Canucks4LSommaire du match
70356Moose3Marlies1WSommaire du match
71362Canucks7Moose6LSommaire du match
74382Barracuda4Moose8WR1Sommaire du match
78401Rockets4Moose5WXSommaire du match
81418Moose3Bears2WSommaire du match
83427Moose1Wranglers3LSommaire du match
85435Crunch2Moose5WSommaire du match
88452Moose6Little Stars8LSommaire du match
90460Little Stars6Moose8WSommaire du match
92473Moose7Penguins4WSommaire du match
94484Checkers4Moose10WSommaire du match
99507Little Stars2Moose5WSommaire du match
104527Moose2Firebirds3LSommaire du match
105536Firebirds5Moose2LSommaire du match
108549Moose3Gulls6LR1Sommaire du match
110561Wolfpack7Moose4LSommaire du match
114580Moose1Americans3LSommaire du match
115590Thunderbirds6Moose3LSommaire du match
118601Moose5Gulls2WR1Sommaire du match
120614Penguins3Moose2LSommaire du match
123630Moose4Icehogs10LSommaire du match
125640Wolfpack4Moose5WXSommaire du match
127649Moose1Admirals3LSommaire du match
129664Americans3Moose4WXSommaire du match
131671Moose2Comets10LSommaire du match
133686Moose3Phantoms4LSommaire du match
134695Gulls4Moose5WXR1Sommaire du match
138717Wranglers3Moose6WSommaire du match
140727Moose1Rockets3LSommaire du match
142737Moose4Senators6LSommaire du match
143747Punishers11Moose3LSommaire du match
147767Admirals0Moose3WSommaire du match
149781Moose5Americans4WSommaire du match
151792Moose5Thunderbirds4WSommaire du match
153798Moose1Admirals5LSommaire du match
154805Griffins3Moose4WXXR1Sommaire du match
157821Moose2Crunch3LSommaire du match
159829Griffins4Moose7WR1Sommaire du match
162848Moose2Checkers5LSommaire du match
163857Condors3Moose8WR1Sommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
167876Icehogs7Moose3LSommaire du match
169884Moose2Islander3LXXSommaire du match
173905Senators4Moose5WXXSommaire du match
175915Moose5Punishers3WSommaire du match
177927Marlies7Moose2LSommaire du match
181951Senators3Moose4WSommaire du match
185970Comets6Moose3LSommaire du match
189985Moose5Barracuda3WR1Sommaire du match
191995Gulls5Moose6WSommaire du match
1941012Moose4Barracuda3WR1Sommaire du match
1961022Icehogs5Moose8WSommaire du match
2001038Moose2Wolfpack5LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance72,93336,770
Assistance PCT91.17%91.93%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2743 - 91.42% 172,623$6,904,915$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
3,142,693$ 2,245,000$ 2,245,000$ 950,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
10,668$ 2,176,120$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 15,817$ 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