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Marlies
GP: 24 | W: 13 | L: 9 | OTL: 2 | P: 28
GF: 99 | GA: 100 | PP%: 21.21% | PK%: 73.12%
DG: Pascal Landry | Morale : 42 | Moyenne d’équipe : 65
Prochains matchs #321 vs Thunderbirds
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Centre de jeu
Marlies
13-9-2, 28pts
5
FINAL
4 Punishers
12-9-2, 26pts
Team Stats
L1SéquenceL3
6-4-2Fiche domicile4-7-1
7-5-0Fiche domicile8-2-1
5-4-1Derniers 10 matchs3-6-1
4.13Buts par match 4.39
4.17Buts contre par match 4.17
21.21%Pourcentage en avantage numérique23.33%
73.12%Pourcentage en désavantage numérique80.00%
Islander
13-10-3, 29pts
7
FINAL
2 Marlies
13-9-2, 28pts
Team Stats
L1SéquenceL1
5-5-1Fiche domicile6-4-2
8-5-2Fiche domicile7-5-0
5-3-2Derniers 10 matchs5-4-1
3.65Buts par match 4.13
3.62Buts contre par match 4.17
23.71%Pourcentage en avantage numérique21.21%
75.00%Pourcentage en désavantage numérique73.12%
Thunderbirds
15-9-2, 32pts
Jour 63
Marlies
13-9-2, 28pts
Statistiques d’équipe
OTL1SéquenceL1
5-6-1Fiche domicile6-4-2
10-3-1Fiche visiteur7-5-0
5-3-210 derniers matchs5-4-1
4.15Buts par match 4.13
3.69Buts contre par match 4.13
18.18%Pourcentage en avantage numérique21.21%
81.65%Pourcentage en désavantage numérique73.12%
Marlies
13-9-2, 28pts
Jour 65
Checkers
12-9-3, 27pts
Statistiques d’équipe
L1SéquenceW2
6-4-2Fiche domicile7-4-1
7-5-0Fiche visiteur5-5-2
5-4-110 derniers matchs4-5-1
4.13Buts par match 4.50
4.17Buts contre par match 4.50
21.21%Pourcentage en avantage numérique21.50%
73.12%Pourcentage en désavantage numérique86.52%
Marlies
13-9-2, 28pts
Jour 67
Phantoms
9-11-3, 21pts
Statistiques d’équipe
L1SéquenceOTW1
6-4-2Fiche domicile5-6-1
7-5-0Fiche visiteur4-5-2
5-4-110 derniers matchs5-5-0
4.13Buts par match 3.96
4.17Buts contre par match 3.96
21.21%Pourcentage en avantage numérique22.34%
73.12%Pourcentage en désavantage numérique78.65%
Meneurs d'équipe
Buts
Aleksi Saarela
24
Passes
Pierre-Olivier Joseph
27
Points
Aleksi Saarela
38
Plus/Moins
Pierre-Olivier Joseph
11
Victoires
Logan Thompson
9
Pourcentage d’arrêts
Logan Thompson
0.871

Statistiques d’équipe
Buts pour
99
4.13 GFG
Tirs pour
692
28.83 Avg
Pourcentage en avantage numérique
21.2%
21 GF
Début de zone offensive
35.4%
Buts contre
100
4.17 GAA
Tirs contre
742
30.92 Avg
Pourcentage en désavantage numérique
73.1%%
25 GA
Début de la zone défensive
37.2%
Informations de l'équipe

Directeur généralPascal Landry
EntraîneurGuy Boucher
DivisionFritz-Kraatz
ConférenceRobert-Lebel
Capitaine
Assistant #1Aleksi Saarela
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,762
Billets de saison300


Informations de la formation

Équipe Pro32
Équipe Mineure18
Limite contact 50 / 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
1Aleksi Saarela (R) (A)X100.007525808472767778727377677960505648730221900,000$
2Tyler Benson (R)X100.008143757782658176637677746156466035730211900,000$
3Martin Necas (R)X100.006734817562747675849079576349446848720201950,000$
4Mathieu Olivier (R)X100.008043787881657473697574696753495338720221900,000$
5Alex Formenton (R)X100.007423866887697372697282616150447148700202950,000$
6Joel Farabee (R)X100.005737808557726587746870648843428148700191500,000$
7Kole Sherwood (R)X100.008441737372638073627373686047464748690221900,000$
8Lias Andersson (R)X100.006237837073797069637767716249476041680212750,000$
9Matthew Highmore (R)X100.007321826671717473767370567148504537670232500,000$
10Hugh McGing (R)X100.007444746980577369547467606045465941660211500,000$
11Isac Lundestrom (R)X100.006034726272637264707377586743456848650201500,000$
12Arthur Kaliyev (R)X100.006541726858636758686666526640407848610182500,000$
13Pierre-Olivier Joseph (R)X100.006028839069787891458767745857447248740202975,000$
14Lucas Carlsson (R)X100.007538887474747369506960755655475548710221900,000$
15Rasmus Dahlin (R)X100.005935828961637288438267725244427948700191500,000$
16Keaton Thompson (R)X100.006639757665647669537664755955513948690241600,000$
17Dennis Gilbert (R)X100.007438787161686757487355774348483649680231500,000$
18Dmitri Samorukov (R)X100.006524847264637452396953774843435836660202500,000$
Rayé
1Otto Koivula (R)X94.345834696173706372716172537044445135640211750,000$
2Jakob Forsbacka-Karlsson (R)X100.007141687059635958645671595846463821620231550,000$
3Samuel Fagemo (R)X100.005426756466606268545875496141427121610192500,000$
4Jonathan Davidsson (R)X100.006122736264616063617257465844484621590222650,000$
5Vasili Podkolzin (R)X100.007634556675567160565661554740407021590182500,000$
6Jan Jenik (R)X100.006533646877576659546255514941416421580191500,000$
7Jonathan Gruden (R)X100.006446595864516660456259485041416319560191500,000$
8Blake Murray (R)X100.005921585059575057524956355640406920510182500,000$
9Jacob Bernard-Docker (R)X100.005943666166665764446156654741416733610191500,000$
10Xavier Bernard (R)X100.005430636750435468326745593741416419560191500,000$
MOYENNE D’ÉQUIPE99.80673474716865696958706662594745603765
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
1Maxime Lagace100.00707069757276797573706957543754720261900,000$
2Logan Thompson100.00826077827869617372608851486054700222800,000$
Rayé
1Veini Vehvilainen100.00737476605672726158807349495428650221500,000$
2Matthew Thiessen100.00593951656447545755465341416128540191500,000$
MOYENNE D’ÉQUIPE100.0071616871686667676564715048534165
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Guy Boucher73787278387865CAN444500,000$


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
1Aleksi SaarelaMarlies (TOR)C242414383180455197225324.74%1955423.12731010820002724049.51%824146011.3700000710
2Pierre-Olivier JosephMarlies (TOR)D23327301114033517735353.90%3063727.722571192022370000%02521000.9400000130
3Joel FarabeeMarlies (TOR)LW24111728460202781204713.58%641317.233471267000092043.48%23207001.3500000105
4Martin NecasMarlies (TOR)RW24161228-1160461574163721.62%1046819.542358760002222161.76%34148011.1900000330
5Mathieu OlivierMarlies (TOR)RW24139223100282766203819.70%643818.284267740000311045.16%3197001.0000000012
6Tyler BensonMarlies (TOR)LW2061622-2220413653173211.32%842221.110663532023621055.00%40714011.0400000121
7Rasmus DahlinMarlies (TOR)D243161908014364121277.32%1749320.5815685700035510100.00%1815000.7700000110
8Lucas CarlssonMarlies (TOR)D2411415920376225694.00%3763926.63044293000080000%0726000.4700000001
9Alex FormentonMarlies (TOR)LW24661222043183183219.35%1435614.851012350111371147.83%2348000.6700000000
10Matthew HighmoreMarlies (TOR)C223710-180272212131125.00%727912.72112224000000051.72%17441000.7100000000
11Kole SherwoodMarlies (TOR)RW243472200302326192011.54%626811.2000005011040036.36%1151000.5200000110
12Lias AnderssonMarlies (TOR)C2123502024331761411.76%528413.52000143000080141.50%14752000.3500000000
13Otto KoivulaMarlies (TOR)LW161453605263516.67%3825.1500002000000045.45%1110001.2100000000
14Isac LundestromMarlies (TOR)C24404-510018201851222.22%325010.43000020000190044.33%9763000.3200000010
15Dennis GilbertMarlies (TOR)D24044-2135162314560%2029812.430000100005000%0311000.2700001000
16Dmitri SamorukovMarlies (TOR)D17044-9206199520%1622913.4901107000011000%016000.3500000000
17Arthur KaliyevMarlies (TOR)RW24134-1100258102710.00%41887.8400001000000050.00%623000.4200000010
18Keaton ThompsonMarlies (TOR)D24033-7140293013570%3047119.65011163000049000%0417000.1300000000
19Hugh McGingMarlies (TOR)LW19202-360229177811.76%41598.3700001000041062.50%842000.2500000001
20Jakob Forsbacka-KarlssonMarlies (TOR)C6000000202120%0162.7400000000000050.00%40000000000000
21Jacob Bernard-DockerMarlies (TOR)D13000240283010%51199.220000000004000%00000000000000
22Xavier BernardMarlies (TOR)D1000100000000%055.280000000000000%00000000000000
23Jonathan DavidssonMarlies (TOR)RW5000000000000%000.170000000000000%00000000000000
24Vasili PodkolzinMarlies (TOR)LW5000000000000%010.390000000001000%00000000000000
25Samuel FagemoMarlies (TOR)LW5000000000000%071.5000000000050050.00%21000000000000
Statistiques d’équipe totales ou en moyenne461991632629193551352069223640514.31%250708915.38213556677872461455813348.82%1436144158030.7400001151410
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
1Logan ThompsonMarlies (TOR)189510.8713.82102101655042613100177000
2Maxime LagaceMarlies (TOR)94410.8574.7642900342371080000717000
Statistiques d’équipe totales ou en moyenne2713920.8664.10145001997413693102424000


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
Aleksi SaarelaMarlies (TOR)C221997-01-01Yes200 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Alex FormentonMarlies (TOR)LW201999-01-01Yes195 Lbs6 ft3NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm950,000$663,119$0$0$No950,000$--------No--------
Arthur KaliyevMarlies (TOR)RW182001-01-01Yes209 Lbs6 ft2NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Blake MurrayMarlies (TOR)C182001-01-01Yes190 Lbs6 ft2NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Dennis GilbertMarlies (TOR)D231996-01-01Yes216 Lbs6 ft2NoNoFree AgentNoNo12024-09-24FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Dmitri SamorukovMarlies (TOR)D201999-01-01Yes188 Lbs6 ft3NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------
Hugh McGingMarlies (TOR)LW211998-01-01Yes176 Lbs5 ft8NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Isac LundestromMarlies (TOR)C201999-01-01Yes193 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Jacob Bernard-DockerMarlies (TOR)D192000-01-01Yes190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Jakob Forsbacka-KarlssonMarlies (TOR)C231996-01-01Yes184 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm550,000$383,911$0$0$No------------------
Jan JenikMarlies (TOR)RW192000-01-01Yes185 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Joel FarabeeMarlies (TOR)LW192000-01-01Yes180 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Jonathan DavidssonMarlies (TOR)RW221997-01-01Yes181 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm650,000$453,713$0$0$No650,000$--------No--------
Jonathan GrudenMarlies (TOR)C192000-01-01Yes172 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Keaton ThompsonMarlies (TOR)D241995-01-01Yes185 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm600,000$418,812$0$0$No------------------
Kole SherwoodMarlies (TOR)RW221997-01-01Yes212 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Lias AnderssonMarlies (TOR)C211998-01-01Yes185 Lbs6 ft1NoNoFree Agent2024-08-01NoNo22024-09-24FalseFalsePro & Farm750,000$523,515$0$0$No850,000$--------No--------
Logan ThompsonMarlies (TOR)G221997-01-01No201 Lbs6 ft4NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm800,000$558,416$0$0$No900,000$--------No--------
Lucas CarlssonMarlies (TOR)D221997-01-01Yes190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Martin NecasMarlies (TOR)RW201999-01-01Yes189 Lbs6 ft2NoNoFree AgentNoNo12024-09-24FalseFalsePro & Farm950,000$663,119$0$0$No------------------
Mathieu OlivierMarlies (TOR)RW221997-01-01Yes209 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Matthew HighmoreMarlies (TOR)C231996-01-01Yes188 Lbs5 ft11NoNoN/ANoNo2FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------
Matthew ThiessenMarlies (TOR)G192000-01-01No208 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Maxime LagaceMarlies (TOR)G261993-01-01No190 Lbs6 ft0NoNoFree AgentNoNo12024-09-24FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Otto Koivula (sur la masse salariale)Marlies (TOR)LW211998-01-01Yes220 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm750,000$523,515$0$0$Yes------------------
Pierre-Olivier JosephMarlies (TOR)D201999-01-01Yes185 Lbs6 ft2NoNoFree AgentNoNo22024-09-24FalseFalsePro & Farm975,000$680,569$0$0$No1,750,000$--------No--------
Rasmus DahlinMarlies (TOR)D192000-01-01Yes202 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Samuel FagemoMarlies (TOR)LW192000-01-01Yes201 Lbs6 ft0NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Tyler BensonMarlies (TOR)LW211998-01-01Yes190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm900,000$628,218$0$0$No------------------
Vasili PodkolzinMarlies (TOR)LW182001-01-01Yes190 Lbs6 ft1NoNoAssign ManuallyNoNo22024-07-10FalseFalsePro & Farm500,000$349,010$0$0$No500,000$--------No--------Lien
Veini VehvilainenMarlies (TOR)G221997-01-01No174 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Xavier BernardMarlies (TOR)D192000-01-01Yes200 Lbs6 ft4NoNoN/ANoNo1FalseFalsePro & Farm500,000$349,010$0$0$No------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3220.72193 Lbs6 ft11.34652,344$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tyler BensonAleksi SaarelaMartin Necas40122
2Joel FarabeeMatthew HighmoreMathieu Olivier30122
3Alex FormentonLias AnderssonKole Sherwood20122
4Hugh McGingIsac LundestromArthur Kaliyev10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Lucas CarlssonPierre-Olivier Joseph40122
2Rasmus DahlinKeaton Thompson30122
3Dennis GilbertDmitri Samorukov20122
4Pierre-Olivier JosephRasmus Dahlin10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Joel FarabeeAleksi SaarelaMartin Necas60122
2Tyler BensonLias AnderssonMathieu Olivier40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephLucas Carlsson60122
2Rasmus DahlinKeaton Thompson40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Aleksi SaarelaTyler Benson60122
2Martin NecasMathieu Olivier40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephLucas Carlsson60122
2Rasmus DahlinKeaton Thompson40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Aleksi Saarela60122Pierre-Olivier JosephLucas Carlsson60122
2Tyler Benson40122Rasmus DahlinKeaton Thompson40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Aleksi SaarelaTyler Benson60122
2Martin NecasMathieu Olivier40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Pierre-Olivier JosephLucas Carlsson60122
2Rasmus DahlinKeaton Thompson40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tyler BensonAleksi SaarelaMartin NecasPierre-Olivier JosephLucas Carlsson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tyler BensonAleksi SaarelaMartin NecasPierre-Olivier JosephLucas Carlsson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Joel Farabee, Mathieu Olivier, Aleksi SaarelaAlex Formenton, Martin NecasMathieu Olivier
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Rasmus Dahlin, Dmitri Samorukov, Pierre-Olivier JosephDennis GilbertDmitri Samorukov, Rasmus Dahlin
Tirs de pénalité
Aleksi Saarela, Tyler Benson, Martin Necas, Mathieu Olivier, Joel Farabee
Gardien
#1 : Logan Thompson, #2 : Maxime Lagace
Lignes d’attaque personnalisées en prolongation
Aleksi Saarela, Tyler Benson, Martin Necas, Mathieu Olivier, Joel Farabee, Alex Formenton, Alex Formenton, Kole Sherwood, Lias Andersson, Hugh McGing, Isac Lundestrom
Lignes de défense personnalisées en prolongation
Pierre-Olivier Joseph, Rasmus Dahlin, Lucas Carlsson, Keaton Thompson, Dmitri Samorukov


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
1Americans10001000431100010004310000000000021.0004711003334293252312242298297421500.00%20100.00%024050247.81%26752850.57%19438949.87%517285498221436222
2Barracuda2010010049-51000010034-11010000015-410.2504711003334293402312242298662316429111.11%8275.00%024050247.81%26752850.57%19438949.87%517285498221436222
3Comets10001000651000000000001000100065121.000611170033342932723122422984011816100.00%4250.00%024050247.81%26752850.57%19438949.87%517285498221436222
4Crunch10001000541000000000001000100054121.0005813003334293262312242298278627200.00%30100.00%024050247.81%26752850.57%19438949.87%517285498221436222
5Firebirds1010000013-2000000000001010000013-200.00011210333429323231224229835114243133.33%20100.00%024050247.81%26752850.57%19438949.87%517285498221436222
6Griffins21100000811-31010000049-51100000042220.50081523003334293572312242298542416327342.86%8275.00%024050247.81%26752850.57%19438949.87%517285498221436222
7Gulls11000000725110000007250000000000021.000711180033342933123122422983376156233.33%3166.67%024050247.81%26752850.57%19438949.87%517285498221436222
8Icehogs1010000035-21010000035-20000000000000.00035800333429333231224229837188262150.00%4175.00%124050247.81%26752850.57%19438949.87%517285498221436222
9Islander1010000027-51010000027-50000000000000.00022400333429333231224229838134263266.67%220.00%024050247.81%26752850.57%19438949.87%517285498221436222
10Little Stars1010000038-5000000000001010000038-500.00034700333429327231224229839111815000%9366.67%024050247.81%26752850.57%19438949.87%517285498221436222
11Moose21100000972211000009720000000000020.50091322003334293522312242298642326517114.29%13192.31%124050247.81%26752850.57%19438949.87%517285498221436222
12Phantoms321000001394110000005052110000089-140.6671321340133342939223122422987215227619210.53%10280.00%024050247.81%26752850.57%19438949.87%517285498221436222
13Punishers11000000541000000000001100000054121.00058130033342934223122422982268215240.00%4175.00%024050247.81%26752850.57%19438949.87%517285498221436222
14Rockets21100000963110000006241010000034-120.50091625003334293612312242298562115549111.11%5340.00%024050247.81%26752850.57%19438949.87%517285498221436222
15Senators11000000431000000000001100000043121.000471100333429332231224229831176229222.22%3166.67%024050247.81%26752850.57%19438949.87%517285498221436222
16Wranglers320001001614221000100111101100000053250.8331627430033342939123122422989935264512325.00%13469.23%024050247.81%26752850.57%19438949.87%517285498221436222
Total241090320099100-1125401200545041255020004550-5280.583991632621133342936922312242298742250193513992121.21%932573.12%224050247.81%26752850.57%19438949.87%517285498221436222
_Since Last GM Reset241090320099100-1125401200545041255020004550-5280.583991632621133342936922312242298742250193513992121.21%932573.12%224050247.81%26752850.57%19438949.87%517285498221436222
_Vs Conference1896012007769811530120052439743000002526-1220.611771292060133342935142312242298541190145384851618.82%691775.36%224050247.81%26752850.57%19438949.87%517285498221436222
_Vs Division852001003829943000100221394220000016160110.68838641020133342932442312242298227716317540615.00%28967.86%024050247.81%26752850.57%19438949.87%517285498221436222

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2428L19916326269274225019351311
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
24109320099100
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
125412005450
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
125520004550
Derniers 10 matchs
WLOTWOTL SOWSOL
243100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
992121.21%932573.12%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
23122422983334293
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
24050247.81%26752850.57%19438949.87%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
517285498221436222


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
12Marlies3Little Stars8LSommaire du match
522Moose5Marlies3LSommaire du match
732Wranglers7Marlies6LXR1Sommaire du match
942Marlies4Senators3WSommaire du match
1362Rockets2Marlies6WR1Sommaire du match
1571Marlies3Rockets4LSommaire du match
1886Phantoms0Marlies5WR1Sommaire du match
1994Marlies1Barracuda5LSommaire du match
21104Marlies5Wranglers3WR1Sommaire du match
22113Marlies6Phantoms2WSommaire du match
25128Moose2Marlies6WSommaire du match
28144Wranglers4Marlies5WR1Sommaire du match
30157Marlies4Griffins2WSommaire du match
32165Marlies2Phantoms7LR1Sommaire du match
34177Icehogs5Marlies3LSommaire du match
37192Marlies5Crunch4WXSommaire du match
39203Gulls2Marlies7WSommaire du match
41209Marlies6Comets5WXSommaire du match
46229Griffins9Marlies4LSommaire du match
49247Americans3Marlies4WXSommaire du match
51257Marlies1Firebirds3LSommaire du match
54275Barracuda4Marlies3LXSommaire du match
57288Marlies5Punishers4WSommaire du match
59300Islander7Marlies2LSommaire du match
63321Thunderbirds-Marlies-
65329Marlies-Checkers-
67342Marlies-Phantoms-
70356Moose-Marlies-
72369Marlies-Bears-
73380Admirals-Marlies-
78399Wranglers-Marlies-
80413Marlies-Wolfpack-
82421Marlies-Griffins-
83430Eagles-Marlies-
86444Marlies-Icehogs-
89456Admirals-Marlies-
93479Condors-Marlies-
95488Marlies-Wranglers-
98503Penguins-Marlies-
103525Canucks-Marlies-
105533Marlies-Wranglers-
108550Checkers-Marlies-
110565Marlies-Thunderbirds-
112573Marlies-Rockets-
114581Wolfpack-Marlies-
116595Marlies-Rockets-
118603Marlies-Americans-
119613Senators-Marlies-
123628Marlies-Gulls-
125639Bears-Marlies-
129661Comets-Marlies-
131674Marlies-Islander-
132684Marlies-Condors-
134692Rockets-Marlies-
137709Marlies-Eagles-
138719Rockets-Marlies-
142739Crunch-Marlies-
143745Marlies-Little Stars-
146763Condors-Marlies-
148773Marlies-Crunch-
151791Gulls-Marlies-
153802Marlies-Penguins-
156814Icehogs-Marlies-
158825Marlies-Barracuda-
160833Marlies-Americans-
162847Punishers-Marlies-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
166869Little Stars-Marlies-
168879Marlies-Little Stars-
171893Little Stars-Marlies-
172899Marlies-Barracuda-
174908Marlies-Admirals-
175917Marlies-Canucks-
177927Marlies-Moose-
178935Thunderbirds-Marlies-
183959Firebirds-Marlies-
187977Firebirds-Marlies-
192999Phantoms-Marlies-
1931005Marlies-Senators-
1961021Phantoms-Marlies-
2001036Marlies-Senators-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets7040
Assistance22,03811,103
Assistance PCT91.83%92.53%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
28 2762 - 92.06% 173,843$2,086,120$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
769,847$ 2,087,500$ 2,072,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,963$ 613,307$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,867,613$ 141 12,809$ 1,806,069$




Marlies 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

Marlies 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

Marlies 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

Marlies 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

Marlies 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