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Marlies
GP: 12 | W: 8 | L: 4 | OTL: 0 | P: 16
GF: 41 | GA: 30 | PP%: 24.14% | PK%: 88.10%
DG: Carl Fortin | Morale : 70 | Moyenne d’équipe : 65
Prochains matchs #195 vs Griffins

Centre de jeu
Griffins
10-1-0, 20pts
5
1 Marlies
8-4-0, 16pts
Team Stats
W3SéquenceW1
5-1-0Fiche domicile3-3-0
5-0-0Fiche domicile5-1-0
9-1-0Derniers 10 matchs7-3-0
3.91Buts par match 3.42
2.36Buts contre par match 2.50
18.18%Pourcentage en avantage numérique24.14%
75.00%Pourcentage en désavantage numérique88.10%
Crunch
8-4-0, 16pts
4
6 Marlies
8-4-0, 16pts
Team Stats
W1SéquenceW1
4-2-0Fiche domicile3-3-0
4-2-0Fiche domicile5-1-0
8-2-0Derniers 10 matchs7-3-0
3.67Buts par match 3.42
3.00Buts contre par match 2.50
13.11%Pourcentage en avantage numérique24.14%
78.00%Pourcentage en désavantage numérique88.10%
Marlies
8-4-0, 16pts
Jour 28
Griffins
10-1-0, 20pts
Statistiques d’équipe
W1SéquenceW3
3-3-0Fiche domicile5-1-0
5-1-0Fiche visiteur5-0-0
7-3-010 derniers matchs9-1-0
3.42Buts par match 3.91
2.50Buts contre par match 3.91
24.14%Pourcentage en avantage numérique18.18%
88.10%Pourcentage en désavantage numérique75.00%
Americans
1-9-2, 4pts
Jour 30
Marlies
8-4-0, 16pts
Statistiques d’équipe
L2SéquenceW1
0-5-1Fiche domicile3-3-0
1-4-1Fiche visiteur5-1-0
0-8-210 derniers matchs7-3-0
2.33Buts par match 3.42
3.67Buts contre par match 3.42
17.39%Pourcentage en avantage numérique24.14%
80.36%Pourcentage en désavantage numérique88.10%
Bears
7-4-0, 14pts
Jour 34
Marlies
8-4-0, 16pts
Statistiques d’équipe
W2SéquenceW1
5-1-0Fiche domicile3-3-0
2-3-0Fiche visiteur5-1-0
6-4-010 derniers matchs7-3-0
3.73Buts par match 3.42
3.73Buts contre par match 3.42
30.61%Pourcentage en avantage numérique24.14%
75.61%Pourcentage en désavantage numérique88.10%
Meneurs d'équipe
Buts
Joakim Kemell
9
Passes
Carter Yakemchuk
11
Points
Joakim Kemell
14
Plus/Moins
Konnor Smith
3
Victoires
Ken Appleby
7
Pourcentage d’arrêts
Luke Cavallin
0.926

Statistiques d’équipe
Buts pour
41
3.42 GFG
Tirs pour
358
29.83 Avg
Pourcentage en avantage numérique
24.1%
14 GF
Début de zone offensive
43.3%
Buts contre
30
2.50 GAA
Tirs contre
312
26.00 Avg
Pourcentage en désavantage numérique
88.1%%
5 GA
Début de la zone défensive
38.3%
Informations de l'équipe

Directeur généralCarl Fortin
EntraîneurJim Hiller
DivisionNorth
ConférenceConference Est
CapitaineJayson Megna
Assistant #1Laurent Dauphin
Assistant #2Turner Elson


Informations de l’aréna

Capacité3,000
Assistance2,996
Billets de saison300


Informations de la formation

Équipe Pro29
Équipe Mineure19
Limite Contrat48 / 99
Espoirs29


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
1Beckett Sennecke (R)0XX100.005845707166858874467671607664658270690203900,000$
2Vasili Ponomarev0XX100.0068619365717661768376736766686966706802421,536,000$
3Laurent Dauphin (A)0XX100.0030239963756769737474706870737356706703132,000,000$
4Jayson Megna (C)0XXX100.0059559962776364688761677660858640706603611,200,000$
5Joakim Kemell0X100.006964877170828565526565656163638170660222900,000$
6Sheldon Dries0XXX100.00666579647172766880597166676666607065N03231,250,000$
7Hudson Elynuik0XX100.0094835566785873646968646963706552706502931,215,000$
8Turner Elson (A)0XX100.006134866075648769755555735583813470640341635,000$
9Jared Wright (R)0XX100.00623274616171736546646768656468827063N02351,150,000$
10Wilmer Skoog0XX100.0072679766756374597647656565676761706202731,000,000$
11Brody Lamb (R)0X100.005832716257677164467068606662497770620232895,000$
12Cristiano DiGiacinto0XX100.0082716268715772575760606561777345706203011,055,000$
13Griffin Mendel0X100.0098977762836673533058566860727146706602811,307,000$
14Carter Yakemchuk (R)0X100.006640706667707466457658715760597870650213900,000$
15Ryan Mast (R)0X100.006838736367778159456951745164637270650232900,000$
16Jacob Macdonald0XX100.0075719158777690552546497549666645706503321,200,000$
17Noah Chadwick (R)0X100.006440706165727759456853705160597470630213900,000$
18Konnor Smith (R)0X100.007043705867667255455856704852597070610251415,000$
Rayé
1Arnaud Durandeau0XX100.00593490687373766550626558617070447064N02741,135,000$
2Dylan James (R)0X100.006132736461707562456867715553587470630232900,000$
3Josh Samanski0XX100.00644665586168716565746363656666827063N02441,350,000$
4Corey Andonovski0XX100.0082625765747287585155476752676352706102731,111,111$
5Ryan Sandelin0XX100.006761966972577262664952675069685170600271625,000$
6Wendel Clark Jr.0XX100.00565176687766705361535361605757837058N2223868,000$
7Griffin Luce0X100.0094927560805872573060517055716844706502811,196,000$
8Kyle Capobianco0X100.0060288961767469473047686361747354706102921,375,000$
MOYENNE D’ÉQUIPE100.00685379647169756255626167606766627064
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
1Ken Appleby098.006165708271798787877672698225707603132,800,000$
2Luke Cavallin0100.007171718073717172736968586270707002511,292,500$
Rayé
1Ryan Bednard0100.0064778782787675747372717882377075N02942,215,000$
MOYENNE D’ÉQUIPE99.3365717681747578787872706875447074
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Jim Hiller81808882848372CAN572600,000$


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
1Joakim KemellMarlies (TOR)RW129514220261731121929.03%219716.484151047000004125.00%1200001.4200000311
2Carter YakemchukMarlies (TOR)D12111121180122120975.00%924520.441451545000011000%000000.9800000001
3Laurent DauphinMarlies (TOR)C/LW127411-10001533123621.21%422018.41336740000040057.14%2100001.0000000111
4Beckett SenneckeMarlies (TOR)LW/RW126511060281735122217.14%221818.213141040000001046.15%1300201.0100000111
5Sheldon DriesMarlies (TOR)C/LW/RW12471116017233042613.33%022819.0723511470001333057.14%17500000.9600000210
6Vasili PonomarevMarlies (TOR)C/LW12281012020253513295.71%222418.69033740000000056.04%27300000.8900000001
7Jayson MegnaMarlies (TOR)C/LW/RW122810100624236228.70%223819.890555460000350053.33%15000000.8400000020
8Hudson ElynuikMarlies (TOR)C/LW12347012023172581712.00%116013.41000010002260058.17%15300000.8700000000
9Ryan MastMarlies (TOR)D121451140181416596.25%726822.351231045000029000%000000.3700000000
10Cristiano DiGiacintoMarlies (TOR)LW/RW12325-1207122021015.00%012610.5800000000000064.29%1400000.7900000002
11Noah ChadwickMarlies (TOR)D120441401216125100%1425221.03011742000131000%000000.3200000000
12Jacob MacdonaldMarlies (TOR)LW/D12044-20058168110%1127022.53011542000036000%000000.3000000000
13Wilmer SkoogMarlies (TOR)C/LW221300001204100.00%02412.2500000000020050.00%400002.4500000100
14Griffin MendelMarlies (TOR)D1203301603965120%1021317.800001100002000%000000.2800000000
15Corey AndonovskiMarlies (TOR)LW/RW10022-140596170%011111.1900001000060012.50%800000.3600000000
16Konnor SmithMarlies (TOR)D1202236014124050%818815.7400000000031000%000000.2100000000
17Turner ElsonMarlies (TOR)C/LW12101120121203125.00%113411.21000000001320055.75%17400000.1500000000
18Dylan JamesMarlies (TOR)LW3000000212020%0258.4900000000000050.00%20000000000000
19Brody LambMarlies (TOR)RW5000000041140%0387.7800000000000050.00%20000000000000
20Jared WrightMarlies (TOR)LW/RW70001004311260%2547.75000000000000100.00%20000000000000
21Josh SamanskiMarlies (TOR)C/LW2000000202110%0136.72000000000000100.00%10000000000000
22Arnaud DurandeauMarlies (TOR)LW/RW7000100549260%0547.7500000000000050.00%40000000000000
Statistiques d’équipe totales ou en moyenne2164174115994024627035810726711.45%75351216.261424388844100052838155.46%100800200.6500000867
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
1Ken ApplebyMarlies (TOR)97200.9142.2952501202320000093010
2Luke CavallinMarlies (TOR)21000.9261.6274002270000012000
3Ryan BednardMarlies (TOR)20200.8494.03119008530000027000
Statistiques d’équipe totales ou en moyenne138400.9042.51718013031200001212010


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 ParDate de la Dernière TransactionBallotage forcé Waiver Possible Contrat Date du Signature du ContratForcer 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
Arnaud DurandeauMarlies (TOR)LW/RW271999-01-14CANNo194 Lbs6 ft0YesNoFree AgentNoNo42026-09-13FalseFalsePro & Farm1,135,000$0$0$No1,135,000$1,135,000$1,135,000$------1,135,000$1,135,000$1,135,000$------YesYesYes------
Beckett SenneckeMarlies (TOR)LW/RW202006-01-28CANYes205 Lbs6 ft3NoNoFree AgentNoNo32026-06-03FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Brody LambMarlies (TOR)RW232003-08-30USAYes185 Lbs6 ft1NoNoFree AgentNoNo22026-06-03FalseFalsePro & Farm895,000$0$0$No895,000$--------895,000$--------No--------
Carter YakemchukMarlies (TOR)D212005-09-29CANYes207 Lbs6 ft4NoNoFree AgentNoNo32026-06-03FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Corey AndonovskiMarlies (TOR)LW/RW271999-03-26CANNo197 Lbs6 ft1NoNoFree AgentNoNo32024-07-15FalseFalsePro & Farm1,111,111$0$0$No1,111,111$1,111,111$-------1,111,111$1,111,111$-------NoNo-------
Cristiano DiGiacintoMarlies (TOR)LW/RW301996-01-10CANNo188 Lbs5 ft11NoNoN/ANoNo1FalseFalsePro & Farm1,055,000$0$0$No---------------------------
Dylan JamesMarlies (TOR)LW232003-10-12CANYes192 Lbs6 ft1NoNoFree AgentNoNo22026-06-03FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Griffin LuceMarlies (TOR)D281998-03-10USANo220 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm1,196,000$0$0$No---------------------------
Griffin MendelMarlies (TOR)D281998-02-18CANNo225 Lbs6 ft6NoNoN/ANoNo1FalseFalsePro & Farm1,307,000$0$0$No---------------------------
Hudson ElynuikMarlies (TOR)C/LW291997-10-12CANNo209 Lbs6 ft5NoNoFree AgentNoNo32025-12-01FalseFalsePro & Farm1,215,000$0$0$No1,215,000$1,215,000$-------1,215,000$1,215,000$-------NoNo-------
Jacob MacdonaldMarlies (TOR)LW/D331993-02-26USANo222 Lbs6 ft0NoNoFree AgentNoNo22025-08-22FalseFalsePro & Farm1,200,000$0$0$No1,200,000$--------1,200,000$--------No--------
Jared WrightMarlies (TOR)LW/RW232002-11-22USAYes183 Lbs6 ft3YesNoFree AgentNoNo52026-08-18FalseFalsePro & Farm1,150,000$0$0$No1,150,000$1,150,000$1,150,000$1,150,000$-----1,150,000$1,150,000$1,150,000$1,150,000$-----YesYesYesYes-----
Jayson MegnaMarlies (TOR)C/LW/RW361990-02-01USANo208 Lbs6 ft0NoNoFree AgentNoNo12024-07-10FalseFalsePro & Farm1,200,000$0$0$No---------------------------
Joakim KemellMarlies (TOR)RW222004-04-27FINNo102 Lbs5 ft11NoNoFree AgentNoNo22025-05-24FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Josh SamanskiMarlies (TOR)C/LW242002-03-22GERNo190 Lbs6 ft3YesNoFree AgentNoNo42026-08-18FalseFalsePro & Farm1,350,000$0$0$No1,350,000$1,350,000$1,350,000$------1,350,000$1,350,000$1,350,000$------YesYesYes------
Ken ApplebyMarlies (TOR)G311995-04-10CANNo219 Lbs6 ft4NoNoFree AgentNoNo32025-08-22FalseFalsePro & Farm2,800,000$0$0$No2,800,000$2,800,000$-------2,800,000$2,800,000$-------NoNo-------
Konnor SmithMarlies (TOR)D252001-09-02CANYes216 Lbs6 ft6NoNoProspectNoNo12026-09-02FalseFalsePro & Farm415,000$0$0$No---------------------------
Kyle CapobiancoMarlies (TOR)D291997-08-13CANNo212 Lbs6 ft1NoNoTrade2025-03-09NoNo2FalseFalsePro & Farm1,375,000$0$0$No1,375,000$--------1,375,000$--------No--------
Laurent DauphinMarlies (TOR)C/LW311995-03-27CANNo201 Lbs6 ft0NoNoFree AgentNoNo32025-08-22FalseFalsePro & Farm2,000,000$0$0$No2,000,000$2,000,000$-------2,000,000$2,000,000$-------NoNo-------
Luke CavallinMarlies (TOR)G252001-04-29GBRNo196 Lbs6 ft2NoNoFree AgentNoNo12026-06-03FalseFalsePro & Farm1,292,500$0$0$No---------------------------
Noah ChadwickMarlies (TOR)D212005-05-10CANYes207 Lbs6 ft4NoNoFree AgentNoNo32026-06-03FalseFalsePro & Farm900,000$0$0$No900,000$900,000$-------900,000$900,000$-------NoNo-------
Ryan BednardMarlies (TOR)G291997-03-31USANo212 Lbs6 ft5YesNoFree AgentNoNo42026-09-13FalseFalsePro & Farm2,215,000$0$0$No2,215,000$2,215,000$2,215,000$------2,215,000$2,215,000$2,215,000$------YesYesYes------
Ryan MastMarlies (TOR)D232003-01-14USAYes220 Lbs6 ft5NoNoFree AgentNoNo22026-06-03FalseFalsePro & Farm900,000$0$0$No900,000$--------900,000$--------No--------
Ryan SandelinMarlies (TOR)C/RW271999-01-03USANo185 Lbs6 ft0NoNoFree AgentNoNo12024-08-06FalseFalsePro & Farm625,000$0$0$No---------------------------
Sheldon DriesMarlies (TOR)C/LW/RW321994-04-23USANo196 Lbs5 ft9YesNoFree AgentNoNo32026-08-18FalseFalsePro & Farm1,250,000$0$0$No1,250,000$1,250,000$-------1,250,000$1,250,000$-------YesYes-------
Turner ElsonMarlies (TOR)C/LW341992-09-13CANNo207 Lbs6 ft0NoNoFree AgentNoNo12024-07-20FalseFalsePro & Farm635,000$0$0$No---------------------------
Vasili PonomarevMarlies (TOR)C/LW242002-03-13RUSNo191 Lbs5 ft10NoNoN/ANoNo22025-05-25FalseFalsePro & Farm1,536,000$0$0$No1,536,000$--------1,536,000$--------No--------
Wendel Clark Jr.Marlies (TOR)C/LW222004-07-31CANNo208 Lbs6 ft3YesNoN/ANoNo32026-05-31FalseFalsePro & Farm868,000$0$0$No868,000$868,000$-------868,000$868,000$-------NoNo-------
Wilmer SkoogMarlies (TOR)C/LW271999-07-17SWENo198 Lbs6 ft2NoNoFree AgentNoNo32024-07-15FalseFalsePro & Farm1,000,000$0$0$No1,000,000$1,000,000$-------1,000,000$1,000,000$-------NoNo-------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2926.69200 Lbs6 ft22.381,180,193$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Laurent DauphinVasili PonomarevBeckett Sennecke32122
2Jayson MegnaSheldon DriesJoakim Kemell28023
3Wilmer SkoogHudson ElynuikCristiano DiGiacinto23122
4Jared WrightTurner ElsonBrody Lamb17131
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MacdonaldGriffin Mendel34131
2Carter YakemchukRyan Mast34122
3Konnor SmithNoah Chadwick25221
4Griffin MendelNoah Chadwick7122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Laurent DauphinVasili PonomarevBeckett Sennecke50005
2Sheldon DriesJayson MegnaJoakim Kemell50005
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Carter YakemchukRyan Mast50005
2Jacob MacdonaldNoah Chadwick50005
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jayson MegnaSheldon Dries51041
2Turner ElsonHudson Elynuik49041
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MacdonaldNoah Chadwick51041
2Konnor SmithRyan Mast49041
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Turner Elson51050Griffin MendelKonnor Smith51050
2Jayson Megna49050Jacob MacdonaldRyan Mast49050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Jayson MegnaTurner Elson52032
2Vasili PonomarevHudson Elynuik48032
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jacob MacdonaldKonnor Smith51131
2Noah ChadwickRyan Mast49131
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Beckett SenneckeVasili PonomarevJoakim KemellGriffin MendelCarter Yakemchuk
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Beckett SenneckeVasili PonomarevJoakim KemellGriffin MendelKonnor Smith
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Vasili Ponomarev, Laurent Dauphin, Jayson MegnaVasili Ponomarev, Joakim KemellJayson Megna
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Jacob Macdonald, Noah Chadwick, Ryan MastCarter YakemchukJacob Macdonald, Konnor Smith
Tirs de pénalité
Vasili Ponomarev, Beckett Sennecke, Laurent Dauphin, Sheldon Dries, Hudson Elynuik
Gardien
#1 : Ken Appleby, #2 : Luke Cavallin


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
TotalDomicile Visiteur
# 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 RI
1Americans11000000321000000000001100000032121.00036900181211033122118118037916205120.00%70100.00%023643654.13%21538655.70%10818658.06%2871972749015780
2Comets22000000817110000005051100000031241.00081422011812110541221181180441420359333.33%7185.71%023643654.13%21538655.70%10818658.06%2871972749015780
3Crunch220000001064110000006421100000042241.000101828001812110661221181180729182811436.36%90100.00%023643654.13%21538655.70%10818658.06%2871972749015780
4Griffins1010000015-41010000015-40000000000000.0001120018121102412211811803098213133.33%30100.00%023643654.13%21538655.70%10818658.06%2871972749015780
5Monsters22000000734110000003121100000042241.000713200018121106112211811804118103910330.00%5180.00%023643654.13%21538655.70%10818658.06%2871972749015780
6Rockets2020000058-31010000013-21010000045-100.0005101500181211061122118118053814501000.00%7271.43%023643654.13%21538655.70%10818658.06%2871972749015780
7Senators211000007521010000034-11100000041320.5007121900181211059122118118035885310220.00%4175.00%023643654.13%21538655.70%10818658.06%2871972749015780
Total12840000041301163300000191726510000022139160.667417411501181211035812211811803127594246581424.14%42588.10%023643654.13%21538655.70%10818658.06%2871972749015780
_Since Last GM Reset12840000041301163300000191726510000022139160.667417411501181211035812211811803127594246581424.14%42588.10%023643654.13%21538655.70%10818658.06%2871972749015780
_Vs Conference12840000041301163300000191726510000022139160.667417411501181211035812211811803127594246581424.14%42588.10%023643654.13%21538655.70%10818658.06%2871972749015780

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1216W14174115358312759424601
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
128400004130
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
63300001917
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
65100002213
Derniers 10 matchs
WLOTWOTL SOWSOL
730000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
581424.14%42588.10%0
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
12211811801812110
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
23643654.13%21538655.70%10818658.06%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
2871972749015780


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
213Senators4Marlies3LSommaire du match
428Marlies4Senators1WSommaire du match
647Marlies3Comets1WSommaire du match
856Marlies3Americans2WSommaire du match
963Rockets3Marlies1LSommaire du match
1286Monsters1Marlies3WSommaire du match
14101Marlies4Rockets5LSommaire du match
17119Comets0Marlies5WSommaire du match
20131Marlies4Crunch2WSommaire du match
22147Marlies4Monsters2WSommaire du match
23159Griffins5Marlies1LSommaire du match
26181Crunch4Marlies6WSommaire du match
28195Marlies-Griffins-
30212Americans-Marlies-
34235Bears-Marlies-
37254Marlies-Moose-
40266Marlies-Americans-
41281Eagles-Marlies-
44299Moose-Marlies-
46318Marlies-Checkers-
48330Marlies-Roadrunners-
50343Canucks-Marlies-
53361Phantoms-Marlies-
58388Checkers-Marlies-
60401Marlies-Firebird-
62415Marlies-Wild-
63431Senators-Marlies-
66448Marlies-Condors-
68459Roadrunners-Marlies-
71481Marlies-Griffins-
73493Penguins-Marlies-
75506Marlies-Thunderbirds-
78524Wolf Pack-Marlies-
80540Marlies-Penguins-
82556Marlies-Bruins-
83565Stars-Marlies-
86589Admirals-Marlies-
88606Marlies-Wolf Pack-
90620Marlies-Barracuda-
91628Reign-Marlies-
94646Marlies-Silver Knight-
97660Silver Knight-Marlies-
99682IceHogs-Marlies-
101697Marlies-Rockets-
103713Marlies-Wolves-
105723Americans-Marlies-
109750Condors-Marlies-
111768Marlies-Stars-
112778Marlies-Hammers-
115789Rockets-Marlies-
118808Marlies-Canucks-
119819Crunch-Marlies-
122838Marlies-Senators-
124849Monsters-Marlies-
125866Marlies-Crunch-
127881Wranglers-Marlies-
130902Marlies-Gulls-
131913Marlies-Phantoms-
134924Gulls-Marlies-
137945Marlies-IceHogs-
139953Wolves-Marlies-
142972Marlies-Eagles-
143984Wild-Marlies-
1471009Marlies-Monsters-
1481016Hammers-Marlies-
1511038Marlies-Comets-
1521049Comets-Marlies-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1551063Marlies-Reign-
1581081Barracuda-Marlies-
1591089Marlies-Admirals-
1631112Griffins-Marlies-
1671136Thunderbirds-Marlies-
1691150Marlies-Wranglers-
1731173Firebird-Marlies-
1781195Bruins-Marlies-
1831209Marlies-Bears-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4020
Assistance11,9786,000
Assistance PCT99.82%100.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
32 2996 - 99.88% 148,782$892,689$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
1,086,588$ 6,845,122$ 6,845,122$ 600,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 999,027$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,761,008$ 158 40,244$ 6,358,552$




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