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Connexion

Moose
GP: 61 | W: 27 | L: 25 | OTL: 9 | P: 63
GF: 236 | GA: 256 | PP%: 19.57% | PK%: 77.48%
DG: Pascal Verret | Morale : 32 | Moyenne d’équipe : 63
Prochains matchs #770 vs Eagles

Centre de jeu
Moose
27-25-9, 63pts
6
5 Admirals
27-25-6, 60pts
Team Stats
L1SéquenceOTL1
11-13-5Fiche domicile14-11-4
16-12-4Fiche domicile13-14-2
6-3-1Derniers 10 matchs2-7-1
3.87Buts par match 4.31
4.20Buts contre par match 4.48
19.57%Pourcentage en avantage numérique24.41%
77.48%Pourcentage en désavantage numérique77.53%
Americans
28-28-3, 59pts
3
1 Moose
27-25-9, 63pts
Team Stats
W1SéquenceL1
12-16-1Fiche domicile11-13-5
16-12-2Fiche domicile16-12-4
6-3-1Derniers 10 matchs6-3-1
4.32Buts par match 3.87
4.76Buts contre par match 4.20
21.46%Pourcentage en avantage numérique19.57%
80.58%Pourcentage en désavantage numérique77.48%
Moose
27-25-9, 63pts
Jour 122
Eagles
29-26-3, 61pts
Statistiques d’équipe
L1SéquenceL2
11-13-5Fiche domicile19-10-0
16-12-4Fiche visiteur10-16-3
6-3-110 derniers matchs5-5-0
3.87Buts par match 4.55
4.20Buts contre par match 4.55
19.57%Pourcentage en avantage numérique26.99%
77.48%Pourcentage en désavantage numérique78.28%
Rockets
24-28-5, 53pts
Jour 124
Moose
27-25-9, 63pts
Statistiques d’équipe
W2SéquenceL1
11-14-4Fiche domicile11-13-5
13-14-1Fiche visiteur16-12-4
5-5-010 derniers matchs6-3-1
4.07Buts par match 3.87
4.58Buts contre par match 3.87
22.40%Pourcentage en avantage numérique19.57%
78.03%Pourcentage en désavantage numérique77.48%
Moose
27-25-9, 63pts
Jour 125
Icehogs
31-23-4, 66pts
Statistiques d’équipe
L1SéquenceL2
11-13-5Fiche domicile18-9-2
16-12-4Fiche visiteur13-14-2
6-3-110 derniers matchs2-8-0
3.87Buts par match 4.14
4.20Buts contre par match 4.14
19.57%Pourcentage en avantage numérique26.80%
77.48%Pourcentage en désavantage numérique72.97%
Meneurs d'équipe
Buts
Morgan Geekie
36
Passes
Juuso Valimaki
51
Points
Morgan Geekie
83
Plus/Moins
Cole Perfetti
6
Victoires
Karel Vejmelka
23
Pourcentage d’arrêts
Karel Vejmelka
0.879

Statistiques d’équipe
Buts pour
236
3.87 GFG
Tirs pour
1980
32.46 Avg
Pourcentage en avantage numérique
19.6%
45 GF
Début de zone offensive
35.9%
Buts contre
256
4.20 GAA
Tirs contre
2061
33.79 Avg
Pourcentage en désavantage numérique
77.5%%
59 GA
Début de la zone défensive
37.2%
Informations de l'équipe

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


Informations de l’aréna

Capacité3,000
Assistance2,777
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
1Morgan Geekie (R)X100.006829827972777575788373525954465245700223900,000$
2Jake Leschyshyn (R)X100.007936737481708378747469616452455748700213800,000$
3Julien Gauthier (R)X100.007229856877736675707679616852484334700231850,000$
4Morgan Barron (R)X100.007550757487538276557373635748454845690223800,000$
5Boris Katchouk (R)X100.007442807269737677726770617247495448690223800,000$
6Axel Jonsson-Fjallby (R)X100.007641836468645974757471646347475045680221500,000$
7Shane Bowers (R)X100.006335797362695371675971587344475233650211500,000$
8Aliaksei Protas (R)X100.007336667173617666556464615942427448630191500,000$
9Cole Perfetti (R)X100.005429776056656159787267435040407638600182500,000$
10Alexander Holtz (R)X100.005427696659646459465779456440407637590182500,000$
11Jean-Luc Foudy (R)X100.005336656647666057737767375640407835590182500,000$
12Elliot Desnoyers (R)X99.746746665375456958496260534540407514570182500,000$
13Juuso Valimaki (R)X100.006729748473807284458458755860465337730221950,000$
14Caleb Jones (R)X100.007744716875744970426863785154484530700232800,000$
15Adam Boqvist (R)X100.006327808167677784488561704851446347700204650,000$
16Josh Mahura (R)X100.006239778069706981437561735151474549700221650,000$
17Jamie Drysdale (R)X100.007037755446676465326370515840408239600182500,000$
18Jonny Tychonick (R)X100.005734746461466475295944644442425823600202550,000$
Rayé
1Logan O'Connor (R)X100.007338847275696776717267607552524123690242500,000$
2Mitchell Stephens (R)X100.005231967468857059767368675647464124670231700,000$
3Lukas Rousek (R)X100.006033817862625671576262467644454924620211500,000$
4John Beecher (R)X100.006939645867597667576564474641416023600191500,000$
5Jaret Anderson-Dolan (R)X100.007046596260476862556064544643434823580211550,000$
6Juuso Parssinen (R)X100.006835675760586561586062456141416423570191500,000$
7Marat Khusnutdinov (R)X100.004534676451554570536352426440407420550182500,000$
8Brett Berard (R)X100.006739665365536557484957414240407020530182500,000$
9Mikael Pyyhtia (R)X100.005630714261555151495471395342436720530192500,000$
10Joey Keane (R)X97.80674385687072657257715469634545489680212700,000$
11Isaak Phillips (R)X100.006844536266754251236441633940406723590182500,000$
12Daemon Hunt (R)X100.006437554961715448215841524340407419540182500,000$
13Tyrel Bauer (R)X100.004727735849565252284328584040406120510182500,000$
MOYENNE D’ÉQUIPE99.92653673666665646754676257564544603163
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
1Daniel Vladar100.00607358746673667667636449485063660232500,000$
Rayé
1Karel Vejmelka93.00786373837865626877537450514058690241650,000$
2Olle Eriksson Ek100.00615366596564576355596343434420590211500,000$
MOYENNE D’ÉQUIPE97.6766636672706762696658674747454765
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jared Bednar53568572375954CAN561950,000$


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
1Morgan GeekieMoose (Win)RW56364783-422068492308012615.65%17107319.1691726351840000173361.11%1265218001.5534000553
2Jake LeschyshynMoose (Win)C6135407517401241291986713117.68%36135822.281310233619921361902250.62%20272021011.1012000635
3Juuso ValimakiMoose (Win)D5995160-216808910818877854.79%94162827.605914322040113204110%05051000.7400000112
4Morgan BarronMoose (Win)C61203454-10395127103175498711.43%25107417.6146101216101131371245.48%6973118101.0100010520
5Adam BoqvistMoose (Win)D6053843-123608810313253463.79%67138223.0327922204011187010%02636100.6200000100
6Julien GauthierMoose (Win)RW50232043-4605846111276520.72%1175315.075510141310000131155.10%492112011.1412000102
7Shane BowersMoose (Win)C60221133-51406964119408518.49%1570911.82000002242594151.36%3682311000.9301000004
8Axel Jonsson-FjallbyMoose (Win)LW61141731-21758053118367811.86%2581013.281124681011390047.06%341114000.7700010312
9Caleb JonesMoose (Win)D5142630-370095928036435.00%72135926.66145101760000155100%01650000.4400000004
10Boris KatchoukMoose (Win)LW61121729-72209993111438110.81%31116019.033581516212341564049.00%1002417000.5000000101
11Josh MahuraMoose (Win)D6112627-5455591079936351.01%63128621.09033101621122160000%03049000.4200001000
12Aliaksei ProtasMoose (Win)RW611211230380824389246113.48%2163810.4600000000002142.11%191111000.7200000031
13Logan O'ConnorMoose (Win)RW3211718-5120432763195117.46%1044413.880112490000113152.17%23118000.8100000220
14Jean-Luc FoudyMoose (Win)C5878154160242051173613.73%54547.84101180000310151.41%177114000.6600000020
15Cole PerfettiMoose (Win)LW6166126160485145203713.33%869611.41000070000770147.83%2368000.3400000001
16Jamie DrysdaleMoose (Win)D60369632051514916156.12%34101316.89213379011096000%0520000.1800000000
17Mitchell StephensMoose (Win)C263690008274119257.32%830111.61000013000090050.91%16564000.6000000000
18Alexander HoltzMoose (Win)RW54268-12024204012275.00%73817.0700005000041066.67%6122000.4200000000
19Joey KeaneMoose (Win)D48167-108043633914212.56%5183517.400000790113104000%0528000.1700000000
20Isaak PhillipsMoose (Win)D350664160412441050%2639611.3200004000020000%008000.3000000000
21Jonny TychonickMoose (Win)D19156280111712258.33%1223612.4300000000019000%006000.5100000000
22John BeecherMoose (Win)C23314-2601813153620.00%81807.8400001000031041.77%7942000.4400000000
23Juuso ParssinenMoose (Win)LW911232011100100.00%0283.190000000000000%000001.3900000000
24Daemon HuntMoose (Win)D10011360864110%212012.070000000005000%001000.1700000000
25Elliot DesnoyersMoose (Win)LW29000-58019149560%41826.2800000000050066.67%31300000000000
26Jaret Anderson-DolanMoose (Win)C9000000000000%000.070000000000000%00000000000000
27Lukas RousekMoose (Win)RW10000-100000000%040.430000000000000%31000000000000
Statistiques d’équipe totales ou en moyenne1185231397628-6858315137713242023706115811.42%6521851015.624669115196190671118251613241549.91%3899377402220.6859021251925
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
1Karel VejmelkaMoose (Win)54232250.8794.022973001991641878530.63611536221
2Daniel VladarMoose (Win)174340.8734.4072220534172111000853000
Statistiques d’équipe totales ou en moyenne71272590.8784.093696202522058108963116159221


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 BoqvistMoose (Win)D202000-01-01SWEYes182 Lbs6 ft0NoNoTrade2026-01-18NoNo42025-08-28FalseFalsePro & Farm650,000$192,308$0$0$No950,000$2,000,000$4,000,000$------950,000$2,000,000$4,000,000$------NoNoNo------Lien
Alexander HoltzMoose (Win)RW182002-01-01SWEYes192 Lbs6 ft0NoNoTrade2025-11-18NoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Aliaksei ProtasMoose (Win)RW192001-01-01BLRYes225 Lbs6 ft2NoNoTrade2024-12-09NoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Axel Jonsson-FjallbyMoose (Win)LW221998-01-01SWEYes190 Lbs6 ft1NoNoTrade2024-12-29NoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Boris KatchoukMoose (Win)LW221998-01-01CANYes206 Lbs6 ft2NoNoFree AgentNoNo32024-08-21FalseFalsePro & Farm800,000$236,686$0$0$No850,000$950,000$-------750,000$750,000$-------NoNo-------Lien
Brett BerardMoose (Win)LW182002-01-01USAYes152 Lbs5 ft9NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Caleb JonesMoose (Win)D231997-01-01USAYes194 Lbs6 ft1NoNoFree AgentNoNo22024-08-21FalseFalsePro & Farm800,000$236,686$0$0$No850,000$--------750,000$--------No--------Lien
Cole PerfettiMoose (Win)LW182002-01-01CANYes177 Lbs5 ft11NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Daemon HuntMoose (Win)D182002-01-01CANYes198 Lbs6 ft0NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Daniel VladarMoose (Win)G231997-01-01CZENo185 Lbs6 ft5NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------Lien
Elliot DesnoyersMoose (Win)LW182002-01-01CANYes183 Lbs5 ft11NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Isaak PhillipsMoose (Win)D182002-01-01CANYes205 Lbs6 ft3NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Jake LeschyshynMoose (Win)C211999-01-01USAYes192 Lbs5 ft11NoNoFree AgentNoNo32024-08-21FalseFalsePro & Farm800,000$236,686$0$0$No850,000$950,000$-------750,000$750,000$-------NoNo-------Lien
Jamie DrysdaleMoose (Win)D182002-01-01CANYes170 Lbs5 ft11NoNoTrade2025-12-11NoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Jaret Anderson-DolanMoose (Win)C211999-01-01CANYes200 Lbs5 ft11NoNoFree AgentNoNo12024-10-11FalseFalsePro & Farm550,000$162,722$0$0$No---------------------------Lien
Jean-Luc FoudyMoose (Win)C182002-01-01CANYes175 Lbs5 ft11NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Joey KeaneMoose (Win)D211999-01-01USAYes187 Lbs6 ft0NoNoFree AgentNoNo22025-09-30FalseFalsePro & Farm700,000$207,101$0$0$No700,000$--------700,000$--------No--------Lien
John BeecherMoose (Win)C192001-01-01USAYes216 Lbs6 ft3NoNoTrade2025-02-21NoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Jonny TychonickMoose (Win)D202000-01-01CANYes187 Lbs6 ft0NoNoTrade2025-12-21NoNo22025-10-23FalseFalsePro & Farm550,000$162,722$0$0$No550,000$--------550,000$--------No--------Lien
Josh MahuraMoose (Win)D221998-01-01CANYes185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm650,000$192,308$0$0$No---------------------------Lien
Julien GauthierMoose (Win)RW231997-01-01CANYes227 Lbs6 ft4NoNoFree Agent2025-02-23NoNo12025-09-30FalseFalsePro & Farm850,000$251,479$0$0$No---------------------------Lien
Juuso ParssinenMoose (Win)LW192001-01-01FINYes212 Lbs6 ft3NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Juuso ValimakiMoose (Win)D221998-01-01FINYes212 Lbs6 ft2NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm950,000$281,065$0$0$No---------------------------Lien
Karel VejmelkaMoose (Win)G241996-01-01CZENo224 Lbs6 ft4NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm650,000$192,308$0$0$No---------------------------Lien
Logan O'ConnorMoose (Win)RW241996-01-01USAYes174 Lbs6 ft0NoNoTrade2024-12-29NoNo2FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------Lien
Lukas RousekMoose (Win)RW211999-01-01CZEYes172 Lbs5 ft11NoNoAssign ManuallyNoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Marat KhusnutdinovMoose (Win)C182002-01-01RUSYes176 Lbs5 ft9NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Mikael PyyhtiaMoose (Win)LW192001-01-01FINYes176 Lbs6 ft0NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Mitchell StephensMoose (Win)C231997-01-01CANYes193 Lbs5 ft11NoNoFree AgentNoNo12024-08-21FalseFalsePro & Farm700,000$207,101$0$0$No---------------------------Lien
Morgan BarronMoose (Win)C221998-01-01CANYes220 Lbs6 ft4NoNoTrade2025-03-20NoNo32024-08-21FalseFalsePro & Farm800,000$236,686$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien
Morgan GeekieMoose (Win)RW221998-01-01CANYes192 Lbs6 ft3NoNoTrade2025-03-20NoNo32024-08-21FalseFalsePro & Farm900,000$266,272$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------Lien
Olle Eriksson EkMoose (Win)G211999-01-01SWENo189 Lbs6 ft3NoNoFree Agent2024-12-29NoNo12025-09-30FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Shane BowersMoose (Win)C211999-01-01CANYes185 Lbs6 ft2NoNoTrade2026-01-18NoNo12024-07-10FalseFalsePro & Farm500,000$147,929$0$0$No---------------------------Lien
Tyrel BauerMoose (Win)D182002-01-01CANYes208 Lbs6 ft3NoNoAssign ManuallyNoNo22025-07-16FalseFalsePro & Farm500,000$147,929$0$0$No500,000$--------500,000$--------No--------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3420.41193 Lbs6 ft11.79598,529$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Boris KatchoukJake LeschyshynMorgan Geekie40122
2Axel Jonsson-FjallbyMorgan BarronJulien Gauthier30122
3Cole PerfettiShane BowersAliaksei Protas20122
4Elliot DesnoyersJean-Luc FoudyAlexander Holtz10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCaleb Jones40122
2Adam BoqvistJosh Mahura30122
3Jamie DrysdaleJonny Tychonick20122
4Juuso ValimakiCaleb Jones10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Boris KatchoukJake LeschyshynMorgan Geekie60122
2Axel Jonsson-FjallbyMorgan BarronJulien Gauthier40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCaleb Jones60122
2Adam BoqvistJosh Mahura40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jake LeschyshynBoris Katchouk60122
2Morgan BarronAxel Jonsson-Fjallby40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCaleb Jones60122
2Adam BoqvistJosh Mahura40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jake Leschyshyn60122Juuso ValimakiCaleb Jones60122
2Morgan Barron40122Adam BoqvistJosh Mahura40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jake LeschyshynBoris Katchouk60122
2Morgan BarronAxel Jonsson-Fjallby40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Juuso ValimakiCaleb Jones60122
2Adam BoqvistJosh Mahura40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Boris KatchoukJake LeschyshynMorgan GeekieJuuso ValimakiCaleb Jones
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Boris KatchoukJake LeschyshynMorgan GeekieJuuso ValimakiCaleb Jones
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Morgan Barron, Axel Jonsson-Fjallby, Shane BowersMorgan Barron, Axel Jonsson-FjallbyMorgan Barron
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Josh Mahura, Jamie Drysdale, Jonny TychonickJosh MahuraJosh Mahura, Jamie Drysdale
Tirs de pénalité
Morgan Geekie, Julien Gauthier, Jake Leschyshyn, Boris Katchouk, Morgan Barron
Gardien
#1 : , #2 : Daniel Vladar
Lignes d’attaque personnalisées en prolongation
Morgan Geekie, Julien Gauthier, Jake Leschyshyn, Boris Katchouk, Morgan Barron, Axel Jonsson-Fjallby, Shane Bowers, Aliaksei Protas, Cole Perfetti, Alexander Holtz
Lignes de défense personnalisées en prolongation
Juuso Valimaki, Caleb Jones, Adam Boqvist, Josh Mahura, Jamie Drysdale


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
1Admirals21001000963000000000002100100096341.0009172600718474126866064863549751520401317.69%10280.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
2Americans20200000610-41010000013-21010000057-200.00061016007184741253660648635496917163210110.00%8275.00%1657132649.55%686137649.85%50599350.86%129571112995811105551
3Barracuda20000200911-21000010045-11000010056-120.5009132200718474126766064863549721322338337.50%11463.64%0657132649.55%686137649.85%50599350.86%129571112995811105551
4Bears20100100711-40000000000020100100711-410.2507132000718474127166064863549743818323133.33%9277.78%0657132649.55%686137649.85%50599350.86%129571112995811105551
5Canucks604020001420-62010100045-1403010001015-540.33314213500718474121796606486354920766461251815.56%23195.65%0657132649.55%686137649.85%50599350.86%129571112995811105551
6Checkers21000010954100000104311100000052341.0009142300718474127566064863549631914555360.00%7271.43%0657132649.55%686137649.85%50599350.86%129571112995811105551
7Comets11000000312110000003120000000000021.000369007184741226660648635491464245120.00%20100.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
8Condors2110000045-12110000045-10000000000020.50045900718474124366064863549562526518112.50%13192.31%0657132649.55%686137649.85%50599350.86%129571112995811105551
9Crunch2020000037-41010000013-21010000024-200.00036900718474125566064863549641420498337.50%10280.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
10Eagles2020000048-41010000035-21010000013-200.000481210718474125866064863549541722477114.29%11281.82%0657132649.55%686137649.85%50599350.86%129571112995811105551
11Firebirds1010000059-41010000059-40000000000000.000591400718474123166064863549431910252150.00%5260.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
12Griffins11000000321000000000001100000032121.0003580071847412316606486354936810227228.57%5180.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
13Gulls21100000910-11010000046-21100000054120.50091625107184741265660648635497412184014214.29%9455.56%0657132649.55%686137649.85%50599350.86%129571112995811105551
14Icehogs51000211272523100010117152200001101010070.70027467300718474121646606486354918046619515533.33%28775.00%1657132649.55%686137649.85%50599350.86%129571112995811105551
15Islander303000001323-101010000057-220200000816-800.000132336007184741210166064863549110303267900.00%16756.25%1657132649.55%686137649.85%50599350.86%129571112995811105551
16Little Stars3110010012932010010047-31100000082630.500122234007184741211066064863549952229701317.69%12375.00%1657132649.55%686137649.85%50599350.86%129571112995811105551
17Marlies211000007611010000013-21100000063320.5007111810718474126266064863549633114526116.67%7185.71%0657132649.55%686137649.85%50599350.86%129571112995811105551
18Penguins211000001013-31010000027-51100000086220.50010172700718474126966064863549751918365120.00%9455.56%0657132649.55%686137649.85%50599350.86%129571112995811105551
19Punishers632000102224-2311000101013-3321000001211180.667223355007184741218966064863549210624813323313.04%24291.67%0657132649.55%686137649.85%50599350.86%129571112995811105551
20Roadrunners210001008711000010034-11100000053230.750812200071847412646606486354971171849700.00%8362.50%0657132649.55%686137649.85%50599350.86%129571112995811105551
21Rockets11000000716000000000001100000071621.00071320007184741232660648635493111223500.00%10100.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
22Senators31101000912-3210010007521010000027-540.6679182700718474121136606486354911444236710110.00%9277.78%1657132649.55%686137649.85%50599350.86%129571112995811105551
23Thunderbirds32000100141221100000043121000100109150.8331423370071847412107660648635498531105716637.50%5180.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
24Wolfpack20200000914-51010000069-31010000035-200.0009162500718474127066064863549681820473133.33%10370.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
25Wranglers220000001358110000008351100000052341.000132235007184741277660648635495819205510550.00%10190.00%0657132649.55%686137649.85%50599350.86%129571112995811105551
Total61202504831236256-202971302421100121-21321312024101361351630.5162363996353071847412198066064863549206161954113262304519.57%2625977.48%5657132649.55%686137649.85%50599350.86%129571112995811105551
_Since Last GM Reset61202504831236256-202971302421100121-21321312024101361351630.5162363996353071847412198066064863549206161954113262304519.57%2625977.48%5657132649.55%686137649.85%50599350.86%129571112995811105551
_Vs Conference39111504621145164-191856023115967-82169023108697-11410.526145243388007184741212626606486354913464133478181452114.48%1653380.00%5657132649.55%686137649.85%50599350.86%129571112995811105551
_Vs Division1956023217176-5922012113437-31034011103739-2220.5797111218300718474125966606486354966819117340263914.29%831384.34%1657132649.55%686137649.85%50599350.86%129571112995811105551

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
6163L123639963519802061619541132630
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
6120254831236256
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
297132421100121
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
3213122410136135
Derniers 10 matchs
WLOTWOTL SOWSOL
432100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
2304519.57%2625977.48%5
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
6606486354971847412
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
657132649.55%686137649.85%50599350.86%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
129571112995811105551


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
18Moose5Roadrunners3WSommaire du match
317Moose1Canucks2LSommaire du match
423Canucks2Moose3WXSommaire du match
640Punishers3Moose4WXXSommaire du match
749Moose1Canucks5LSommaire du match
857Moose5Thunderbirds6LXSommaire du match
1172Little Stars4Moose2LSommaire du match
1489Moose2Punishers5LSommaire du match
16103Roadrunners4Moose3LXSommaire du match
18116Moose6Punishers4WSommaire du match
20126Icehogs5Moose4LXSommaire du match
21136Moose6Icehogs5WXXSommaire du match
23145Moose5Canucks4WXSommaire du match
25156Canucks3Moose1LSommaire du match
28177Icehogs6Moose5LXXSommaire du match
30188Moose4Bears5LXSommaire du match
33202Condors1Moose2WR1Sommaire du match
35208Moose3Islander9LSommaire du match
37225Moose8Penguins6WSommaire du match
38233Checkers3Moose4WXXSommaire du match
42254Eagles5Moose3LSommaire du match
44265Moose3Admirals1WSommaire du match
45277Moose5Thunderbirds3WSommaire du match
47285Crunch3Moose1LSommaire du match
50305Marlies3Moose1LSommaire du match
52317Moose5Checkers2WSommaire du match
54326Moose8Little Stars2WSommaire du match
55336Wranglers3Moose8WSommaire du match
58356Gulls6Moose4LR1Sommaire du match
60368Moose2Crunch4LSommaire du match
61382Penguins7Moose2LSommaire du match
64399Moose3Bears6LSommaire du match
65407Barracuda5Moose4LXR1Sommaire du match
68422Moose3Griffins2WR1Sommaire du match
69434Moose3Canucks4LSommaire du match
71442Little Stars3Moose2LXSommaire du match
73457Moose7Rockets1WSommaire du match
74466Icehogs4Moose8WSommaire du match
77478Moose1Eagles3LSommaire du match
79491Punishers2Moose3WSommaire du match
81509Moose2Senators7LSommaire du match
82516Condors4Moose2LR1Sommaire du match
85534Moose5Islander7LSommaire du match
87543Firebirds9Moose5LSommaire du match
89559Moose5Wranglers2WSommaire du match
91568Moose5Gulls4WR1Sommaire du match
92576Punishers8Moose3LSommaire du match
95595Islander7Moose5LSommaire du match
96605Moose4Punishers2WSommaire du match
99620Wolfpack9Moose6LSommaire du match
101634Moose4Icehogs5LXSommaire du match
102645Moose5Americans7LSommaire du match
103650Comets1Moose3WSommaire du match
106673Senators4Moose5WXSommaire du match
108684Moose3Wolfpack5LSommaire du match
110694Moose5Barracuda6LXR1Sommaire du match
111702Senators1Moose2WSommaire du match
114720Moose6Marlies3WSommaire du match
115727Thunderbirds3Moose4WSommaire du match
118743Moose6Admirals5WXSommaire du match
119752Americans3Moose1LSommaire du match
122770Moose-Eagles-
124780Rockets-Moose-
125791Moose-Icehogs-
127803Moose-Canucks-
128806Griffins-Moose-
131821Moose-Roadrunners-
132832Rockets-Moose-
135847Moose-Roadrunners-
136858Comets-Moose-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
140883Admirals-Moose-
145909Bears-Moose-
148930Canucks-Moose-
149937Moose-Comets-
153957Little Stars-Moose-
154964Moose-Firebirds-
157982Americans-Moose-
158989Moose-Condors-
1621010Roadrunners-Moose-
1661036Roadrunners-Moose-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance54,04526,493
Assistance PCT93.18%91.36%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
11 2777 - 92.57% 175,345$5,085,013$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,096,747$ 2,035,000$ 2,035,000$ 950,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,041$ 1,427,793$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
1,928,798$ 50 17,663$ 883,150$




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