Connexion

Marlies
GP: 55 | W: 33 | L: 16 | OTL: 6 | P: 72
GF: 225 | GA: 175 | PP%: 25.00% | PK%: 78.95%
DG: Eug Sorokin | Morale : 63 | Moyenne d’équipe : 62
Prochains matchs #609 vs Aces
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Centre de jeu
Marlies
33-16-6, 72pts
4
FINAL
0 Canucks
31-21-4, 66pts
Team Stats
SOL1SéquenceW1
15-9-3Fiche domicile16-10-2
18-7-3Fiche domicile15-11-2
4-4-2Derniers 10 matchs7-3-0
4.09Buts par match 3.29
3.18Buts contre par match 3.04
25.00%Pourcentage en avantage numérique26.32%
78.95%Pourcentage en désavantage numérique79.09%
Marlies
33-16-6, 72pts
2
FINAL
3 Punishers
33-17-5, 71pts
Team Stats
SOL1SéquenceSOW1
15-9-3Fiche domicile18-8-2
18-7-3Fiche domicile15-9-3
4-4-2Derniers 10 matchs7-3-0
4.09Buts par match 4.11
3.18Buts contre par match 3.62
25.00%Pourcentage en avantage numérique21.71%
78.95%Pourcentage en désavantage numérique84.62%
Aces
33-16-4, 70pts
Jour 116
Marlies
33-16-6, 72pts
Statistiques d’équipe
W3SéquenceSOL1
18-10-0Fiche domicile15-9-3
15-6-4Fiche visiteur18-7-3
9-1-010 derniers matchs4-4-2
3.66Buts par match 4.09
3.19Buts contre par match 4.09
20.17%Pourcentage en avantage numérique25.00%
83.54%Pourcentage en désavantage numérique78.95%
Marlies
33-16-6, 72pts
Jour 118
Barracuda
26-24-5, 57pts
Statistiques d’équipe
SOL1SéquenceW1
15-9-3Fiche domicile14-11-3
18-7-3Fiche visiteur12-13-2
4-4-210 derniers matchs4-4-2
4.09Buts par match 4.93
3.18Buts contre par match 4.93
25.00%Pourcentage en avantage numérique23.33%
78.95%Pourcentage en désavantage numérique71.01%
Firebirds
22-27-6, 50pts
Jour 119
Marlies
33-16-6, 72pts
Statistiques d’équipe
OTL1SéquenceSOL1
11-15-1Fiche domicile15-9-3
11-12-5Fiche visiteur18-7-3
4-5-110 derniers matchs4-4-2
4.84Buts par match 4.09
4.95Buts contre par match 4.09
18.05%Pourcentage en avantage numérique25.00%
77.85%Pourcentage en désavantage numérique78.95%
Meneurs d'équipe
Mark JankowskiButs
Mark Jankowski
29
Jesper FastPasses
Jesper Fast
40
Mark JankowskiPoints
Mark Jankowski
65
Philip TomasinoPlus/Moins
Philip Tomasino
29
Martin JonesVictoires
Martin Jones
31
Martin JonesPourcentage d’arrêts
Martin Jones
0.9

Statistiques d’équipe
Buts pour
225
4.09 GFG
Tirs pour
1861
33.84 Avg
Pourcentage en avantage numérique
25.0%
32 GF
Début de zone offensive
40.7%
Buts contre
175
3.18 GAA
Tirs contre
1728
31.42 Avg
Pourcentage en désavantage numérique
78.9%%
28 GA
Début de la zone défensive
38.9%
Informations de l'équipe

Directeur généralEug Sorokin
EntraîneurSheldon Keefe
DivisionAtlantic
ConférenceEastern Conference
CapitaineMarcus Johansson
Assistant #1Troy Stecher
Assistant #2Jesper Fast


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro27
Équipe Mineure19
Limite contact 46 / 50
Espoirs5


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
1Mark JankowskiXX100.00555787697769597767687069517474082660303500,000$
2Tye KartyeX100.00855986717370877960636463506162081650231500,000$
3Jesper Fast (A)X100.00705689686871847550685769507775081650332500,000$
4Logan Stankoven (R)XX100.00635491715973577954697161535963064640213500,000$
5Hudson FaschingX100.00685595697570657550665661507271079630291500,000$
6Jesper BoqvistXX100.00735590696568667650646263536464079630263500,000$
7Philip TomasinoXX100.00565588736571637350716761516064080630231500,000$
8Mattias JanmarkXX100.00666282667470826655605071507575074620323500,000$
9Peyton KrebsXX100.00726076696771907366645163506263079620241500,000$
10Vasily PodkolzinX100.00775878626861546750545054505859020560231500,000$
11Troy Stecher (A)X100.00726071626473736750605476557576080650301500,000$
12Jackson LaCombeX100.00665983667575856950655271556265080650242500,000$
13Gustav LindstromX100.00756074627068676750625272566668080640261500,000$
14Calen AddisonX100.00635878716171856750645161556364078620244500,000$
15Pierre-Olivier JosephX100.00685786636668706750615069556566030620252500,000$
16John LudvigX100.00787381607760606150525467566365021600241500,000$
Rayé
1Ryan StromeXX100.006765667868789075637263595074730196703131,750,000$
2Marcus Johansson (C)XX100.00645785727378897450676360537975027660341500,000$
3Phillip Di GiuseppeX100.00776285696970697950625868507572059640312500,000$
4Linus KarlssonX100.00503589576350515050505050506060020510254750,000$
5Pierrick DubeX100.00504167575950505050505050505859020500241500,000$
6Zach BogosianX100.007864716283728066506050745580780206703411,000,000$
7Marc Del GaizoX100.00595788576652545350445054556265020530251500,000$
8Philip BrobergX100.00505099507750535050505053556063020520233500,000$
MOYENNE D’ÉQUIPE100.0067578366696770685361566352676705462
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
1Marc-Andre Fleury100.0076807871727974727364728888073730401500,000$
2Martin Jones100.0074717277727871717266508181061720351500,000$
Rayé
1Louis Domingue100.0059606377545150505150507474079570321500,000$
MOYENNE D’ÉQUIPE100.007070717566696564656057818107167
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Sheldon Keefe7585859075751CAN447500,000$


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
1Mark JankowskiMarlies (TOR)C/LW552936652620241532256116312.89%9115420.994711279701141014259.88%152300011.1313000573
2Jesper FastMarlies (TOR)RW55224062248071831615011513.66%7110920.18371023101000024045.35%8600001.1203000317
3Tye KartyeMarlies (TOR)LW5521295029260139801816112311.60%9112020.3745921990003753350.63%7900000.8903000452
4Philip TomasinoMarlies (TOR)LW/RW55222648290017551495011014.77%1087515.911234281122274140.30%6700001.1000000433
5Logan StankovenMarlies (TOR)C/RW52252247110038931965012412.76%6102219.6741519911232363148.22%39400010.9200000134
6Troy StecherMarlies (TOR)D55102636174401184566253915.15%72120821.984152490000097010%000000.6000000222
7Jesper BoqvistMarlies (TOR)C/LW5017173442405284122397813.93%981416.292248620000204147.21%100200010.8300000210
8Peyton KrebsMarlies (TOR)C/LW54112132132208611511220609.82%883015.37000010003471158.16%95600000.7700000231
9Phillip Di GiuseppeMarlies (TOR)LW44131932-62359555138351109.42%1085819.5213410571013562053.13%6400100.7500001322
10Gustav LindstromMarlies (TOR)D5532831224010150325920295.08%72112820.5105520730110102200%000000.5500101334
11Hudson FaschingMarlies (TOR)RW5517143121603636119176814.29%672813.24011230003312148.00%5000000.8500000332
12Calen AddisonMarlies (TOR)D54325281022065423613248.33%49100218.562571455000063000%000000.5600000204
13Jackson LaCombeMarlies (TOR)D55522272321562566910367.25%74116021.1014531951011104100%000000.4700000112
14Marcus JohanssonMarlies (TOR)LW/RW2151015-44029245725458.77%241119.60134946000160043.75%1600000.7300000002
15Ryan StromeMarlies (TOR)C/RW96511-160261826121623.08%018220.25112322000051048.86%21900001.2100000111
16Mattias JanmarkMarlies (TOR)LW/RW506410-220161845102913.33%113336.67101240000461066.67%2700000.6000000000
17Pierre-Olivier JosephMarlies (TOR)D331910-71803819198165.26%4455416.800000401114100100.00%100000.3600000000
18John LudvigMarlies (TOR)D170332401927220%1018711.010000200005000%000000.3200000000
19Vasily PodkolzinMarlies (TOR)RW10022160913110%0919.1600000000000033.33%600000.4400000000
20Zach BogosianMarlies (TOR)D1011220201000%22424.470000000003000%000000.8200000000
Statistiques d’équipe totales ou en moyenne83521635957521428020109210111791509118812.06%4101479917.72294776217941461023876321154.12%449000130.7819102363539
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
1Martin JonesMarlies (TOR)48311240.9003.1527262314314270110.8336478423
2Marc-Andre FleuryMarlies (TOR)82320.8913.3844441252290000.667380010
3Louis DomingueMarlies (TOR)30000.9470.87690011900000034000
Statistiques d’équipe totales ou en moyenne59331560.8993.13324064169167501195542433


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 Plafond 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
Calen AddisonMarlies (TOR)D242000-04-11CANNo173 Lbs5 ft11NoNoN/ANoNo42024-08-13FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$500,000$------500,000$500,000$500,000$------NoNoNo------Lien NHL
Gustav LindstromMarlies (TOR)D261998-10-20SWENo194 Lbs6 ft2NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Hudson FaschingMarlies (TOR)RW291995-07-28USANo209 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Jackson LaCombeMarlies (TOR)D242001-01-09USANo205 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Jesper BoqvistMarlies (TOR)C/LW261998-10-30SWENo184 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Jesper FastMarlies (TOR)RW331991-12-02SWENo191 Lbs6 ft1NoNoFree AgentNoNo22024-09-11FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
John LudvigMarlies (TOR)D242000-08-02CZENo213 Lbs6 ft1NoNoFree AgentNoNo12024-09-12FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Linus KarlssonMarlies (TOR)C251999-11-16SWENo178 Lbs6 ft1NoNoFree AgentNoNo42024-09-12FalseFalsePro & Farm750,000$75,000$25,714$No750,000$750,000$750,000$------750,000$750,000$750,000$------NoNoNo------
Logan StankovenMarlies (TOR)C/RW212003-02-26CANYes171 Lbs5 ft8NoNoProspectNoNo32024-08-10FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Louis DomingueMarlies (TOR)G321992-03-06CANNo209 Lbs6 ft3NoNoFree AgentNoNo12024-11-02FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Marc Del GaizoMarlies (TOR)D251999-10-11USANo188 Lbs5 ft11NoNoFree AgentNoNo12024-09-11FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Marc-Andre FleuryMarlies (TOR)G401984-11-28CANNo185 Lbs6 ft2NoNoAssign ManuallyNoNo12024-08-26FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Marcus JohanssonMarlies (TOR)LW/RW341990-10-06SWENo203 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Mark JankowskiMarlies (TOR)C/LW301994-09-13CANNo212 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Martin JonesMarlies (TOR)G351990-01-10CANNo203 Lbs6 ft5NoNoFree AgentNoNo12024-09-09FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Mattias JanmarkMarlies (TOR)LW/RW321992-12-08SWENo205 Lbs6 ft2NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Peyton KrebsMarlies (TOR)C/LW242001-01-26CANNo186 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Philip BrobergMarlies (TOR)D232001-06-25SWENo212 Lbs6 ft4NoNoN/ANoNo3FalseFalsePro & Farm500,000$50,000$17,143$No500,000$500,000$-------500,000$500,000$-------NoNo-------Lien NHL
Philip TomasinoMarlies (TOR)LW/RW232001-07-28CANNo179 Lbs6 ft0NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Phillip Di GiuseppeMarlies (TOR)LW311993-10-09CANNo193 Lbs6 ft0NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Pierre-Olivier JosephMarlies (TOR)D251999-07-01CANNo185 Lbs6 ft2NoNoN/ANoNo2FalseFalsePro & Farm500,000$50,000$17,143$No500,000$--------500,000$--------No--------Lien NHL
Pierrick DubeMarlies (TOR)RW242001-01-07FRANo172 Lbs5 ft9NoNoFree AgentNoNo12024-09-12FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------
Ryan StromeMarlies (TOR)C/RW311993-07-11CANNo191 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm1,750,000$175,000$60,000$No1,750,000$1,750,000$-------1,750,000$1,750,000$-------NoNo-------Lien NHL
Troy StecherMarlies (TOR)D301994-04-07CANNo184 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Tye KartyeMarlies (TOR)LW232001-04-30CANNo202 Lbs5 ft11NoNoFree AgentNoNo12024-09-03FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Vasily PodkolzinMarlies (TOR)RW232001-06-24RUSNo190 Lbs6 ft1NoNoN/ANoNo1FalseFalsePro & Farm500,000$50,000$17,143$No---------------------------Lien NHL
Zach BogosianMarlies (TOR)D341990-07-15USANo231 Lbs6 ft3NoNoFree AgentNoNo12024-09-12FalseFalsePro & Farm1,000,000$100,000$34,286$No---------------------------Lien NHL
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2727.81194 Lbs6 ft11.81574,074$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tye KartyeMark JankowskiJesper Fast35122
2Jesper BoqvistLogan Stankoven35122
3Philip TomasinoPeyton KrebsHudson Fasching25122
4Mattias JanmarkPeyton KrebsVasily Podkolzin5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StecherJackson LaCombe35122
2Gustav LindstromCalen Addison35122
3Pierre-Olivier JosephJohn Ludvig30122
4Troy StecherJackson LaCombe0122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Tye KartyeMark JankowskiJesper Fast60122
2Jesper BoqvistLogan Stankoven40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StecherJackson LaCombe60122
2Gustav LindstromCalen Addison40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Peyton KrebsHudson Fasching60122
2Jesper Boqvist40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StecherJackson LaCombe60122
2Gustav LindstromCalen Addison40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Mark Jankowski60122Troy StecherJackson LaCombe60122
2Logan Stankoven40122Gustav LindstromCalen Addison40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Mark JankowskiTye Kartye60122
2Logan Stankoven40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Troy StecherJackson LaCombe60122
2Gustav LindstromCalen Addison40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tye KartyeMark JankowskiLogan StankovenTroy StecherJackson LaCombe
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Tye KartyeMark JankowskiJesper FastTroy StecherJackson LaCombe
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
, Philip Tomasino, Hudson Fasching, Philip Tomasino
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Calen Addison, Pierre-Olivier Joseph, John LudvigCalen AddisonCalen Addison, Pierre-Olivier Joseph
Tirs de pénalité
Jesper Fast, Mark Jankowski, Tye Kartye, Logan Stankoven,
Gardien
#1 : Marc-Andre Fleury, #2 : Martin Jones
Lignes d’attaque personnalisées en prolongation
Jesper Fast, Mark Jankowski, Tye Kartye, Logan Stankoven, , Philip Tomasino, Philip Tomasino, Hudson Fasching, Mattias Janmark, Jesper Boqvist, Peyton Krebs
Lignes de défense personnalisées en prolongation
Troy Stecher, Jackson LaCombe, Gustav Lindstrom, Calen Addison, Pierre-Olivier Joseph


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
1Aces22000000963000000000002200000096341.0009152400777668459591609635355010123310330.00%5260.00%11003183654.63%961175754.70%49892154.07%150010951140353688367
2Admirals1010000034-11010000034-10000000000000.0003690077766845059160963535348822400.00%4175.00%11003183654.63%961175754.70%49892154.07%150010951140353688367
3Americiens531000102417722000000128431100010129380.80024406400777668421859160963535194461612220420.00%70100.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
4Barons2020000069-32020000069-30000000000000.0006111700777668458591609635354517840100.00%4175.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
5Broncos311000018802010000168-21100000020230.500815230177766849659160963535872123609222.22%11190.91%01003183654.63%961175754.70%49892154.07%150010951140353688367
6Bruins4210100015962200000010462010100055060.750152742007776684127591609635351142724993133.33%12375.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
7Butter Knives5320000026215321000001513221100000118360.60026517700777668419059160963535198583111914321.43%12283.33%01003183654.63%961175754.70%49892154.07%150010951140353688367
8Canucks211000004131010000001-11100000040420.500461001777668450591609635354212636500.00%20100.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
9Fighting Pandas614001001724-730200100813-531200000911-230.25017304720777668416859160963535158533612911218.18%18761.11%01003183654.63%961175754.70%49892154.07%150010951140353688367
10Firebirds211000001091110000006421010000045-120.5001017270077766846559160963535832410517228.57%5180.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
11Griffins220000001477110000009451100000053241.00014233700777668496591609635356916434100.00%2150.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
12Lions540010001961311000000734430010001239101.00019365502777668414959160963535130333610511545.45%14285.71%01003183654.63%961175754.70%49892154.07%150010951140353688367
13Lynx4210010011101220000007432010010046-250.6251121320077766849959160963535922331775120.00%10280.00%11003183654.63%961175754.70%49892154.07%150010951140353688367
14Nordiks11000000752110000007520000000000021.00071421007776684335916096353543122232150.00%10100.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
15Punishers20001001660100010004311000000123-130.75061117007776684535916096353561261051000%50100.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
16Roadrunners320001001915421000100121021100000075250.8331938570077766841315916096353510224177712758.33%4250.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
17Tomahawks11000000422000000000001100000042221.000481200777668431591609635354816824100.00%4175.00%01003183654.63%961175754.70%49892154.07%150010951140353688367
18Wombats311001001112-11010000023-12100010099030.5001116270077766849359160963535891820519111.11%10190.00%11003183654.63%961175754.70%49892154.07%150010951140353688367
19Wranglers220000001248110000005321100000071641.00012233500777668495591609635358925644300.00%3166.67%01003183654.63%961175754.70%49892154.07%150010951140353688367
Total55291603412225175502714901201119992028157022111067630720.655225408633247776684186159160963535172846930811971283225.00%1332878.95%41003183654.63%961175754.70%49892154.07%150010951140353688367
_Since Last GM Reset55291603412225175502714901201119992028157022111067630720.655225408633247776684186159160963535172846930811971283225.00%1332878.95%41003183654.63%961175754.70%49892154.07%150010951140353688367
_Vs Conference3616130141114412915191060020181711017670121063585410.5691442614052177766841237591609635351151302216807942324.47%932078.49%31003183654.63%961175754.70%49892154.07%150010951140353688367
_Vs Division241190121093811212830010052421012360111041392280.5839316926220777668480259160963535756207138546531120.75%591476.27%11003183654.63%961175754.70%49892154.07%150010951140353688367

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
5572SOL122540863318611728469308119724
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
5529163412225175
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
27149120111999
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
28157221110676
Derniers 10 matchs
WLOTWOTL SOWSOL
440101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
1283225.00%1332878.95%4
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
591609635357776684
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
1003183654.63%961175754.70%49892154.07%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
150010951140353688367


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
14Lynx1Marlies3WSommaire du match
423Marlies2Americiens4LSommaire du match
525Marlies3Lions0WSommaire du match
738Bruins2Marlies4WSommaire du match
951Americiens4Marlies5WSommaire du match
1269Fighting Pandas5Marlies3LSommaire du match
1373Marlies2Lynx3LXSommaire du match
1689Marlies3Butter Knives4LSommaire du match
1795Butter Knives6Marlies5LSommaire du match
19108Marlies3Bruins2WXSommaire du match
21116Admirals4Marlies3LSommaire du match
23130Marlies2Lions0WSommaire du match
25140Bruins2Marlies6WSommaire du match
28156Wranglers3Marlies5WSommaire du match
32172Marlies1Fighting Pandas3LSommaire du match
34180Fighting Pandas3Marlies2LXSommaire du match
36192Marlies4Wombats3WSommaire du match
39200Barons5Marlies3LSommaire du match
42219Marlies6Americiens2WSommaire du match
44225Nordiks5Marlies7WSommaire du match
47241Marlies4Lions1WSommaire du match
48247Wombats3Marlies2LSommaire du match
50261Marlies2Broncos0WSommaire du match
52271Broncos4Marlies3LXXSommaire du match
55287Punishers3Marlies4WXSommaire du match
56296Marlies4Firebirds5LSommaire du match
59309Butter Knives4Marlies5WSommaire du match
60316Marlies6Fighting Pandas5WSommaire du match
63329Marlies4Americiens3WXXSommaire du match
64336Barons4Marlies3LSommaire du match
67351Marlies5Griffins3WSommaire du match
69358Roadrunners5Marlies4LXSommaire du match
72372Marlies3Lions2WXSommaire du match
73379Butter Knives3Marlies5WSommaire du match
76396Marlies6Aces4WSommaire du match
78401Lions3Marlies7WSommaire du match
80414Marlies2Bruins3LSommaire du match
81422Roadrunners5Marlies8WSommaire du match
84433Marlies8Butter Knives4WSommaire du match
86440Marlies7Wranglers1WSommaire du match
87449Americiens4Marlies7WSommaire du match
89464Marlies2Lynx3LSommaire du match
91473Firebirds4Marlies6WSommaire du match
94488Marlies3Aces2WSommaire du match
95494Lynx3Marlies4WSommaire du match
97509Marlies4Tomahawks2WSommaire du match
99515Fighting Pandas5Marlies3LSommaire du match
100526Marlies5Wombats6LXSommaire du match
103539Griffins4Marlies9WSommaire du match
105551Marlies2Fighting Pandas3LSommaire du match
107558Canucks1Marlies0LSommaire du match
109574Broncos4Marlies3LSommaire du match
111581Marlies7Roadrunners5WSommaire du match
113590Marlies4Canucks0WSommaire du match
114601Marlies2Punishers3LXXSommaire du match
116609Aces-Marlies-
118622Marlies-Barracuda-
119629Firebirds-Marlies-
122641Marlies-Barons-
124652Wranglers-Marlies-
127666Ice Bats-Marlies-
129676Marlies-Roadrunners-
130686Marlies-Nordiks-
132695Bruins-Marlies-
136710Marlies-Broncos-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
138718Americiens-Marlies-
141734Ice Bats-Marlies-
143744Marlies-Bruins-
145754Marlies-Ice Bats-
146761Wombats-Marlies-
149775Marlies-Admirals-
151782Admirals-Marlies-
152788Marlies-Firebirds-
156805Tomahawks-Marlies-
157814Marlies-Wranglers-
159822Marlies-Admirals-
160831Lynx-Marlies-
161835Marlies-Butter Knives-
164854Admirals-Marlies-
165859Marlies-Lynx-
169877Tomahawks-Marlies-
173893Barracuda-Marlies-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
14 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,392,016$ 1,550,000$ 1,550,000$ 500,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
1,550,000$ 1,063,457$ 27 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 60 11,714$ 702,840$




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