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Marlies
GP: 82 | W: 55 | L: 24 | OTL: 3 | P: 113
GF: 294 | GA: 180 | PP%: 18.59% | PK%: 86.35%
DG: Garrett | Morale : 50 | Moyenne d’équipe : 60

Centre de jeu
Marlies
55-24-3, 113pts
5
FINAL
2 Senators
46-29-7, 99pts
Team Stats
L1SéquenceL1
28-10-3Fiche domicile26-11-4
27-14-0Fiche domicile20-18-3
6-3-1Derniers 10 matchs2-7-1
3.59Buts par match 3.80
2.20Buts contre par match 2.67
18.59%Pourcentage en avantage numérique11.91%
86.35%Pourcentage en désavantage numérique83.37%
Marlies
55-24-3, 113pts
1
FINAL
4 Americans
61-18-3, 125pts
Team Stats
L1SéquenceW2
28-10-3Fiche domicile32-8-1
27-14-0Fiche domicile29-10-2
6-3-1Derniers 10 matchs5-4-1
3.59Buts par match 4.10
2.20Buts contre par match 1.65
18.59%Pourcentage en avantage numérique17.89%
86.35%Pourcentage en désavantage numérique90.00%
Meneurs d'équipe
Jack StudnickaButs
Jack Studnicka
36
Passes
Jacob Bernard-Docker
55
Points
Jacob Bernard-Docker
76
Plus/Moins
Ethan Cardwell
54
Victoires
Jiri Patera
39
Pourcentage d’arrêts
Jesper Vikman
0.894

Statistiques d’équipe
Buts pour
294
3.59 GFG
Tirs pour
2061
25.13 Avg
Pourcentage en avantage numérique
18.6%
71 GF
Début de zone offensive
39.7%
Buts contre
180
2.20 GAA
Tirs contre
1531
18.67 Avg
Pourcentage en désavantage numérique
86.4%%
64 GA
Début de la zone défensive
38.2%
Informations de l'équipe

Directeur généralGarrett
EntraîneurDerek Lalonde
DivisionNorth
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,946
Billets de saison0


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 51
Espoirs46


Historique d'équipe

Saison actuelle55-24-3 (113PTS)
Historique0-0-0
Coupe Stanley0


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Luke EvangelistaXX100.006341897867668569257668592561626950660241896,667$
2Rutger McGroarty (R)X100.0076748275748085625060596556444464506302231,450,000$
3Jack StudnickaXX100.007169767469818761765959625644456350620272875,000$
4Nick AbruzzeseXX100.007566956566818761765958645544446450620261775,000$
5Ethan Cardwell (R)X100.007166816866808562506457625444446450620232925,000$
6Hunter McKownX100.0076718863717883587354586455444463506002311,366,667$
7Akil Thomas (R)X100.008268907372555061445856672546466250600261775,000$
8Zayde WisdomX100.007471826471788358505358635544446250600231896,667$
9Spencer SmallmanX100.007472796572747860505956635344446250600293800,000$
10Nate Danielson (R)X100.0075718567715656607559566453444461505902131,886,667$
11Matvei Petrov (R)XX100.007167816067616452504456605344445750550232813,333$
12Jacob Bernard-DockerX100.0071568773736260602551486925595959506302511,000,000$
13Sean DayX100.008988906588707552254842694044445850630281775,000$
14Jeremy DaviesX100.007267826767818759255251624844446150620292900,000$
15Hunter McDonald (R)X100.0073786266787886482539416039444453506002331,200,000$
16John LudvigX100.007877817277575952254840643847475450600251775,000$
17Donovan Sebrango (R)X100.007481566681646754254351624844445750590241875,000$
Rayé
1William LockwoodX100.0086918269655160644554556925474761505902700$
2Martin ChromiakX100.007870956470565561505662655944446450590231820,000$
3Tanner Dickinson (R)X100.007365936265677251644751604844445650560242878,333$
4Maxim Cajkovic (R)X100.007367875967515059505658625544446050560252925,000$
5Adam RaskaX100.006466606666677250504747564544445350540241900,000$
6Ilya Nikolayev (R)X100.007670905970545649614547614544445450530242836,667$
7Joseph CecconiX100.008080806580555748254040633844445250580283800,000$
8Brinson PasichnukX100.00797491687459634825404063384444535058N0281775,000$
MOYENNE D’ÉQUIPE100.00757183677166705746525363454646595060
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
1Jiri Patera100.00444151834589454990814544446150610271775,000$
2Jesper Vikman (R)100.00444050724589454990814544446050600242858,000$
Rayé
MOYENNE D’ÉQUIPE100.0044415178458945499081454444615061
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Derek Lalonde85828887787372USA523500,000$


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
1Jacob Bernard-DockerMarlies (TOR)D82215576205607484111447918.92%66173721.19141529742660111317400%000010.8700000534
2Jack StudnickaMarlies (TOR)C/RW823634701692101931932777620313.00%26163119.9010112173292123123535368.07%66700020.8614011752
3Ethan CardwellMarlies (TOR)RW82303868544801111041783912416.85%10106813.03191016740000116354.72%5300001.2702000847
4Rutger McGroartyMarlies (TOR)RW5622345696401201001935616111.40%6119521.34416203820711271635050.00%6600000.9412000451
5Jeremy DaviesMarlies (TOR)D82144155375801205389306415.73%74158619.358816451970221313300%000000.6900000253
6Sean DayMarlies (TOR)D82163450201251523057117327713.68%95172721.07101222782850112315100%000100.5800102268
7Nate DanielsonMarlies (TOR)C561928476460721171334011114.29%299017.683101323183000003163.29%105700000.9500000313
8Nick AbruzzeseMarlies (TOR)C/LW561926453130043591363110513.97%9108519.38167750213103205253.95%7600010.8311000612
9Luke EvangelistaMarlies (TOR)LW/RW4111314225120187391288412.09%173818.021111213134000112042.50%4000011.1400000510
10Hunter McKownMarlies (TOR)C5615264119535709999256815.15%592616.5567132319011241763062.50%92800000.8800001114
11John LudvigMarlies (TOR)D82831394196301315660162913.33%49137316.745914271100003188100%000000.5700510043
12Akil ThomasMarlies (TOR)C56162137375807372107347714.95%267111.9900000000023153.87%56800001.1000000034
13Martin ChromiakMarlies (TOR)RW3916193526495563493237117.20%1144011.301341456000014066.67%2700011.5900001231
14Spencer SmallmanMarlies (TOR)RW41121224214807869114358410.53%1552912.9100007000021049.32%29400010.9100000112
15Hunter McDonaldMarlies (TOR)D565182338108201282638122513.16%31124222.19437241950220254100%000000.3700112200
16Donovan SebrangoMarlies (TOR)D5631619369210110161941515.79%2480414.3601128000041000%000000.4700200011
17Zayde WisdomMarlies (TOR)C5699181924024285473216.67%32965.3000000000001258.49%21200001.2100000004
18Matvei PetrovMarlies (TOR)LW/RW41527131009122861517.86%22295.6000000000001140.00%1000000.6100000030
Statistiques d’équipe totales ou en moyenne1102277475752468106995166012521937538142414.30%4311827516.5868121189457226251116412466491360.53%399800170.8239937484749
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
1Jiri PateraMarlies (TOR)56391520.8782.013290491109010101.0007560311
2Jesper VikmanMarlies (TOR)3016910.8942.41159560646010400.50062656000
Statistiques d’équipe totales ou en moyenne86552430.8842.1448861091741502050138256311


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 RaskaMarlies (TOR)RW242001-09-25CZENo185 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm900,000$0$0$No---------------------------Lien
Akil ThomasMarlies (TOR)C262000-01-02CANYes195 Lbs6 ft0NoNoTrade2025-08-17NoYes1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Brinson PasichnukMarlies (TOR)D281997-11-23ABNo205 Lbs6 ft0YesNoFree AgentNoYes12025-09-05FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Donovan SebrangoMarlies (TOR)D242002-01-12CANYes221 Lbs6 ft2NoNoTrade2025-08-12NoNo12024-06-24FalseFalsePro & Farm875,000$0$0$No---------------------------Lien
Ethan CardwellMarlies (TOR)RW232002-08-30CANYes180 Lbs5 ft11NoNoAssign ManuallyNoNo22024-06-30FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien
Hunter McDonaldMarlies (TOR)D232002-05-11USAYes205 Lbs6 ft4NoNoAssign ManuallyNoNo32025-08-03FalseFalsePro & Farm1,200,000$0$0$No1,200,000$1,200,000$-------1,200,000$1,200,000$-------NoNo-------Lien
Hunter McKownMarlies (TOR)C232002-08-18USANo192 Lbs6 ft1NoNoTrade2025-08-17NoNo1FalseFalsePro & Farm1,366,667$0$0$No---------------------------Lien
Ilya NikolayevMarlies (TOR)C242001-06-26RUSYes190 Lbs6 ft0NoNoAssign ManuallyNoNo22024-06-30FalseFalsePro & Farm836,667$0$0$No836,667$--------836,667$--------No--------Lien
Jack StudnickaMarlies (TOR)C/RW271999-02-18CANNo187 Lbs6 ft1NoNoFree AgentNoYes22024-06-24FalseFalsePro & Farm875,000$0$0$No875,000$--------875,000$--------No--------Lien / Lien NHL
Jacob Bernard-DockerMarlies (TOR)D252000-06-30CANNo198 Lbs6 ft1NoNoFree AgentNoYes12025-06-15FalseFalsePro & Farm1,000,000$0$0$No---------------------------Lien
Jeremy DaviesMarlies (TOR)D291996-12-04CANNo185 Lbs5 ft11NoNoFree AgentNoYes22024-06-24FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------Lien / Lien NHL
Jesper VikmanMarlies (TOR)G242002-03-11SWEYes179 Lbs6 ft3NoNoAssign ManuallyNoNo22024-07-16FalseFalsePro & Farm858,000$0$0$No858,000$--------858,000$--------No--------Lien
Jiri PateraMarlies (TOR)G271999-02-24CZENo212 Lbs6 ft3NoNoN/ANoYes1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
John LudvigMarlies (TOR)D252000-08-02CZENo210 Lbs6 ft1NoNoN/ANoYes1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Joseph CecconiMarlies (TOR)D281997-05-23USANo216 Lbs6 ft3NoNoFree AgentNoYes32025-06-15FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien / Lien NHL
Luke EvangelistaMarlies (TOR)LW/RW242002-02-21CANNo183 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm896,667$0$0$No---------------------------Lien
Martin ChromiakMarlies (TOR)RW232002-08-20SVKNo190 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm820,000$0$0$No---------------------------Lien
Matvei PetrovMarlies (TOR)LW/RW232003-03-12RUSYes179 Lbs6 ft2NoNoAssign ManuallyNoNo22024-06-30FalseFalsePro & Farm813,333$0$0$No813,333$--------813,333$--------No--------Lien
Maxim CajkovicMarlies (TOR)RW252001-01-03SLOYes185 Lbs5 ft11NoNoAssign ManuallyNoYes22024-06-30FalseFalsePro & Farm925,000$0$0$No925,000$--------925,000$--------No--------Lien
Nate DanielsonMarlies (TOR)C212004-09-27ABYes190 Lbs6 ft1NoNoAssign ManuallyNoNo32025-08-03FalseFalsePro & Farm1,886,667$0$0$No1,886,667$1,886,667$-------1,886,667$1,886,667$-------NoNo-------Lien
Nick AbruzzeseMarlies (TOR)C/LW261999-06-04USANo180 Lbs5 ft11NoNoTrade2025-08-17NoYes1FalseFalsePro & Farm775,000$0$0$No---------------------------Lien
Rutger McGroartyMarlies (TOR)RW222004-03-30USAYes203 Lbs6 ft1NoNoAssign ManuallyNoNo32025-08-03FalseFalsePro & Farm1,450,000$0$0$No1,450,000$1,450,000$-------1,450,000$1,450,000$-------NoNo-------Lien
Sean DayMarlies (TOR)D281998-01-09BGMNo240 Lbs6 ft3NoNoN/ANoYes12025-08-19FalseFalsePro & Farm775,000$0$0$No---------------------------Lien / Lien NHL
Spencer SmallmanMarlies (TOR)RW291996-09-09CANNo198 Lbs6 ft1NoNoFree AgentNoYes32025-06-15FalseFalsePro & Farm800,000$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------Lien / Lien NHL
Tanner DickinsonMarlies (TOR)C242002-03-05USAYes176 Lbs6 ft0NoNoAssign ManuallyNoNo22024-06-30FalseFalsePro & Farm878,333$0$0$No878,333$--------878,333$--------No--------Lien
William LockwoodMarlies (TOR)RW271998-06-20USANo172 Lbs5 ft11NoNoTrade2024-11-24NoYes0FalseFalsePro & Farm0$0$No---------------------------Lien
Zayde WisdomMarlies (TOR)C232002-07-07CANNo201 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm896,667$0$0$No---------------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2725.00195 Lbs6 ft11.63909,370$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nate DanielsonRutger McGroarty40122
2Luke EvangelistaHunter McKownJack Studnicka30122
3Nick AbruzzeseAkil ThomasEthan Cardwell20122
4Matvei PetrovZayde WisdomLuke Evangelista10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob Bernard-DockerSean Day40122
2Jeremy DaviesHunter McDonald30122
3John LudvigDonovan Sebrango20122
4Jacob Bernard-DockerSean Day10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Nate DanielsonRutger McGroarty60122
2Luke EvangelistaHunter McKownJack Studnicka40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob Bernard-DockerSean Day60122
2Jeremy DaviesHunter McDonald40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jack StudnickaNick Abruzzese60122
2Hunter McKownRutger McGroarty40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob Bernard-DockerSean Day60122
2Jeremy DaviesHunter McDonald40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jack Studnicka60122Jacob Bernard-DockerSean Day60122
2Hunter McKown40122Jeremy DaviesHunter McDonald40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Nate DanielsonRutger McGroarty60122
2Hunter McKownNick Abruzzese40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob Bernard-DockerSean Day60122
2Jeremy DaviesHunter McDonald40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nick AbruzzeseNate DanielsonRutger McGroartyJacob Bernard-DockerSean Day
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Nick AbruzzeseJack StudnickaRutger McGroartyJacob Bernard-DockerSean Day
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Luke Evangelista, Hunter McKown, Luke Evangelista
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Hunter McDonald, John Ludvig, Donovan SebrangoHunter McDonaldHunter McDonald, John Ludvig
Tirs de pénalité
Rutger McGroarty, Jack Studnicka, Ethan Cardwell, Nick Abruzzese,
Gardien
#1 : Jiri Patera, #2 : Jesper Vikman
Lignes d’attaque personnalisées en prolongation
Rutger McGroarty, Jack Studnicka, Ethan Cardwell, Nick Abruzzese, , Luke Evangelista, Hunter McKown, Akil Thomas, Zayde Wisdom, Nate Danielson
Lignes de défense personnalisées en prolongation
Jacob Bernard-Docker, Sean Day, Jeremy Davies, Hunter McDonald, John Ludvig


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
1 Americans3210000067-1110000004312110000024-240.6676814011158786747714666670225714486917211.76%22386.36%01162220752.65%1025212248.30%598123048.62%224616581767535936484
2Admirals220000001055110000006241100000043141.0001014240011587867687146666702232830417228.57%15286.67%11162220752.65%1025212248.30%598123048.62%224616581767535936484
3Barracuda21100000550110000003211010000023-120.5005813001158786736714666670223713224817423.53%9277.78%01162220752.65%1025212248.30%598123048.62%224616581767535936484
4Bears220000001358110000006421100000071641.00013243700115878677171466667022291116545240.00%8187.50%11162220752.65%1025212248.30%598123048.62%224616581767535936484
5Bruins21001000523110000003121000100021141.000581300115878675271466667022411645347228.57%15193.33%01162220752.65%1025212248.30%598123048.62%224616581767535936484
6Canucks41300000513-8211000004402020000019-820.2505914001158786750714666670221013076811715.88%30583.33%01162220752.65%1025212248.30%598123048.62%224616581767535936484
7Checkers22000000642110000004311100000021141.000611170011587867477146666702224622411300.00%110100.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
8Comets54100000209112200000073432100000136780.800203555001158786714971466667022124354614112433.33%22290.91%11162220752.65%1025212248.30%598123048.62%224616581767535936484
9Condors22000000716110000005051100000021141.000712190111587867497146666702238630361119.09%15193.33%01162220752.65%1025212248.30%598123048.62%224616581767535936484
10Crunch40300100617-112010010027-520200000410-610.12561117001158786784714666670229329607610110.00%25676.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
11Eagles2110000046-2110000003211010000014-320.500471100115878673471466667022581334288112.50%15380.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
12Firebirds2200000014212110000006151100000081741.000142539001158786797714666670223041443300.00%7185.71%01162220752.65%1025212248.30%598123048.62%224616581767535936484
13Griffins422000001495211000008622110000063340.5001422360011587867120714666670226421425618422.22%16193.75%01162220752.65%1025212248.30%598123048.62%224616581767535936484
14Gulls220000001511411000000110111100000041341.000152843011158786783714666670221656363266.67%30100.00%11162220752.65%1025212248.30%598123048.62%224616581767535936484
15Ice Hogs2200000015114110000008081100000071641.00015284301115878678371466667022211121484250.00%80100.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
16Islanders2200000017215110000009091100000082641.0001732490111587867927146666702223518422150.00%8187.50%01162220752.65%1025212248.30%598123048.62%224616581767535936484
17Monsters413000001013-32020000058-32110000055020.250101626001158786771714666670229325499223417.39%22386.36%01162220752.65%1025212248.30%598123048.62%224616581767535936484
18Moose21100000752110000004131010000034-120.5007132000115878672671466667022461339358337.50%14285.71%01162220752.65%1025212248.30%598123048.62%224616581767535936484
19Penguins211000009541010000023-11100000072520.5009182700115878677371466667022257164511327.27%7185.71%01162220752.65%1025212248.30%598123048.62%224616581767535936484
20Phantoms22000000642110000002111100000043141.00061016001158786733714666670224314225218316.67%11190.91%01162220752.65%1025212248.30%598123048.62%224616581767535936484
21Reign431000009813210000067-11100000031260.75091625001158786763714666670227130508026311.54%17382.35%01162220752.65%1025212248.30%598123048.62%224616581767535936484
22Roadrunners2200000012111110000005051100000071641.0001223350111587867757146666702223734529222.22%160100.00%11162220752.65%1025212248.30%598123048.62%224616581767535936484
23Rocket5110101113130310010019812010001045-170.70013203300115878671087146666702210030649041512.20%31390.32%01162220752.65%1025212248.30%598123048.62%224616581767535936484
24Senators431000001385211000004402200000094560.7501320330011587867101714666670228727578517847.06%23482.61%01162220752.65%1025212248.30%598123048.62%224616581767535936484
25Silver Knights22000000523110000004221100000010141.0005101501115878673771466667022278264917423.53%120100.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
26Stars210001008621000010034-11100000052330.750814220011587867497146666702246143757400.00%15473.33%01162220752.65%1025212248.30%598123048.62%224616581767535936484
27Thunderbirds2200000017314110000008081100000093641.0001730470111587867737146666702217818587342.86%9366.67%01162220752.65%1025212248.30%598123048.62%224616581767535936484
28Wild2020000048-41010000025-31010000023-100.00047110011587867427146666702247823281119.09%9366.67%01162220752.65%1025212248.30%598123048.62%224616581767535936484
29Wolf Pack21100000642110000005141010000013-220.5006111700115878673271466667022321432431317.69%16287.50%01162220752.65%1025212248.30%598123048.62%224616581767535936484
30Wolves30001020963100000103212000101064261.0009142300115878677271466667022541646341200.00%23386.96%11162220752.65%1025212248.30%598123048.62%224616581767535936484
31Wranglers2110000045-11010000025-31100000020220.500481201115878674471466667022329623411218.18%15380.00%01162220752.65%1025212248.30%598123048.62%224616581767535936484
Total824924032312941801144126100121115389644123140202014191501130.68929451280609115878672061714666670221531457110517083827118.59%4696486.35%61162220752.65%1025212248.30%598123048.62%224616581767535936484
_Since Last GM Reset824924032312941801144126100121115389644123140202014191501130.68929451280609115878672061714666670221531457110517083827118.59%4696486.35%61162220752.65%1025212248.30%598123048.62%224616581767535936484
_Vs Conference472316031311521143823127011117355182411902020795920600.63815226141301115878671155714666670229332866119662193917.81%2683487.31%31162220752.65%1025212248.30%598123048.62%224616581767535936484
_Vs Division24121401111636031266011013432212680001029281300.625631001630111587867559714666670224661433384511232217.89%1431887.41%01162220752.65%1025212248.30%598123048.62%224616581767535936484

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
82113L1294512806206115314571105170809
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8249243231294180
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
412610121115389
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
412314202014191
Derniers 10 matchs
WLOTWOTL SOWSOL
431110
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3827118.59%4696486.35%6
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
7146666702211587867
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
1162220752.65%1025212248.30%598123048.62%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
224616581767535936484


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
13Marlies1Comets2LSommaire du match
322Rocket3Marlies4WXSommaire du match
537Marlies5Griffins1WSommaire du match
753Griffins2Marlies5WSommaire du match
968Marlies1Crunch6LSommaire du match
1076Marlies7Comets2WSommaire du match
1393Reign2Marlies3WSommaire du match
16115Rocket3Marlies2LXXSommaire du match
19137Comets1Marlies3WSommaire du match
21153Marlies1Canucks7LSommaire du match
24170Monsters4Marlies3LSommaire du match
26185Marlies4Senators2WSommaire du match
29202Reign4Marlies1LSommaire du match
31223Marlies3Monsters4LSommaire du match
33236Senators3Marlies1LSommaire du match
35245Marlies2Rocket1WXXSommaire du match
37266Wild5Marlies2LSommaire du match
39281Marlies4Phantoms3WSommaire du match
41297Marlies9Thunderbirds3WSommaire du match
43309Reign1Marlies2WSommaire du match
46328Moose1Marlies4WSommaire du match
48347Marlies1Wolf Pack3LSommaire du match
50361Marlies8Firebirds1WSommaire du match
52374Bruins1Marlies3WSommaire du match
55395Barracuda2Marlies3WSommaire du match
57410Marlies5Comets2WSommaire du match
59425Marlies2Rocket4LSommaire du match
60436Senators1Marlies3WSommaire du match
63458Marlies2Barracuda3LSommaire du match
64467Wolf Pack1Marlies5WSommaire du match
68495Roadrunners0Marlies5WSommaire du match
71516Marlies7Bears1WSommaire du match
73527Condors0Marlies5WSommaire du match
75544Marlies1Silver Knights0WSommaire du match
77558Wranglers5Marlies2LSommaire du match
80579Marlies5Stars2WSommaire du match
82590Admirals2Marlies6WSommaire du match
83607Marlies7Penguins2WSommaire du match
86623Ice Hogs0Marlies8WSommaire du match
88638Marlies4Admirals3WSommaire du match
90650Marlies3Moose4LSommaire du match
91661Monsters4Marlies2LSommaire du match
94684Phantoms1Marlies2WSommaire du match
96699Marlies0Canucks2LSommaire du match
98717Checkers3Marlies4WSommaire du match
100728Marlies7Ice Hogs1WSommaire du match
102748Comets2Marlies4WSommaire du match
105767Marlies2Checkers1WSommaire du match
106779Marlies8Islanders2WSommaire du match
108789 Americans3Marlies4WSommaire du match
111811Thunderbirds0Marlies8WSommaire du match
114831Marlies2Condors1WSommaire du match
116844Canucks3Marlies4WSommaire du match
120871Canucks1Marlies0LSommaire du match
123894Marlies4Wolves3WXSommaire du match
124903Rocket2Marlies3WSommaire du match
129935Gulls0Marlies11WSommaire du match
131951Marlies2Monsters1WSommaire du match
133965Marlies3Crunch4LSommaire du match
134969Wolves2Marlies3WXXSommaire du match
137997Eagles2Marlies3WSommaire du match
1401017Marlies7Roadrunners1WSommaire du match
1411026Marlies1Griffins2LSommaire du match
1421032Islanders0Marlies9WSommaire du match
1471061Penguins3Marlies2LSommaire du match
1491078Marlies1 Americans0WSommaire du match
1511093Griffins4Marlies3LSommaire du match
1531109Marlies2Wild3LSommaire du match
1541118Marlies3Reign1WSommaire du match
1561130Silver Knights2Marlies4WSommaire du match
1601159Stars4Marlies3LXSommaire du match
1621172Marlies4Gulls1WSommaire du match
1641189Firebirds1Marlies6WSommaire du match
1681219Crunch2Marlies1LXSommaire du match
1701232Marlies2Wolves1WXXSommaire du match
1711243Marlies1Eagles4LSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1731251Crunch5Marlies1LSommaire du match
1741261Marlies2Wranglers0WSommaire du match
1771282Bears4Marlies6WSommaire du match
1781290Marlies2Bruins1WXSommaire du match
1801301Marlies5Senators2WSommaire du match
1811310Marlies1 Americans4LSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets350
Assistance81,51339,284
Assistance PCT99.41%95.81%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2946 - 98.21% 69,584$2,852,955$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
2,960,754$ 2,455,301$ 2,455,301$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
13,344$ 2,460,818$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 16,061$ 0$




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