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Connexion

Toronto Marlies
GP: 9 | W: 3 | L: 6 | OTL: 0 | P: 6
GF: 17 | GA: 27 | PP%: 15.38% | PK%: 57.14%
DG: Tristan Goncalves-Paulin | Morale : 40 | Moyenne d’équipe : 58
Prochains matchs #125 vs Lehigh Valley Phantoms

Centre de jeu
Toronto Marlies
3-6-0, 6pts
1
3 Wilkes-Barre/Scranton Penguins
4-4-0, 8pts
Team Stats
L4SéquenceW1
2-3-0Fiche domicile4-1-0
1-3-0Fiche domicile0-3-0
3-6-0Derniers 10 matchs4-4-0
1.89Buts par match 3.00
3.00Buts contre par match 2.88
15.38%Pourcentage en avantage numérique31.82%
57.14%Pourcentage en désavantage numérique68.18%
Laval Rocket
6-3-0, 12pts
4
1 Toronto Marlies
3-6-0, 6pts
Team Stats
W1SéquenceL4
4-1-0Fiche domicile2-3-0
2-2-0Fiche domicile1-3-0
6-3-0Derniers 10 matchs3-6-0
2.56Buts par match 1.89
1.67Buts contre par match 3.00
52.63%Pourcentage en avantage numérique15.38%
85.00%Pourcentage en désavantage numérique57.14%
Toronto Marlies
3-6-0, 6pts
Jour 23
Lehigh Valley Phantoms
2-6-1, 5pts
Statistiques d’équipe
L4SéquenceL2
2-3-0Fiche domicile1-3-0
1-3-0Fiche visiteur1-3-1
3-6-010 derniers matchs2-6-1
1.89Buts par match 1.89
3.00Buts contre par match 1.89
15.38%Pourcentage en avantage numérique10.00%
57.14%Pourcentage en désavantage numérique66.67%
Toronto Marlies
3-6-0, 6pts
Jour 25
Providence Bruins
4-5-0, 8pts
Statistiques d’équipe
L4SéquenceL3
2-3-0Fiche domicile3-2-0
1-3-0Fiche visiteur1-3-0
3-6-010 derniers matchs4-5-0
1.89Buts par match 2.89
3.00Buts contre par match 2.89
15.38%Pourcentage en avantage numérique50.00%
57.14%Pourcentage en désavantage numérique53.13%
Wilkes-Barre/Scranton Penguins
4-4-0, 8pts
Jour 26
Toronto Marlies
3-6-0, 6pts
Statistiques d’équipe
W1SéquenceL4
4-1-0Fiche domicile2-3-0
0-3-0Fiche visiteur1-3-0
4-4-010 derniers matchs3-6-0
3.00Buts par match 1.89
2.88Buts contre par match 1.89
31.82%Pourcentage en avantage numérique15.38%
68.18%Pourcentage en désavantage numérique57.14%
Meneurs d'équipe
Buts
Logan Morrison
3
Passes
Cameron Hebig
3
Points
John Farinacci
5
Plus/Moins
Jake Livingstone
3
Victoires
Drew Commesso
3
Pourcentage d’arrêts
Drew Commesso
0.889

Statistiques d’équipe
Buts pour
17
1.89 GFG
Tirs pour
253
28.11 Avg
Pourcentage en avantage numérique
15.4%
4 GF
Début de zone offensive
39.4%
Buts contre
27
3.00 GAA
Tirs contre
236
26.22 Avg
Pourcentage en désavantage numérique
57.1%%
9 GA
Début de la zone défensive
36.1%
Informations de l'équipe

Directeur généralTristan Goncalves-Paulin
EntraîneurJohn MacLean
DivisionNorth
ConférenceEastern
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,879
Billets de saison300


Informations de la formation

Équipe Pro24
Équipe Mineure19
Limite Contrat43 / 72
Espoirs38


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
1Logan Morrison0X95.42654369716465636645656166665150140600241850,000$
2Cameron Hebig0XXX97.50564369696071696664636260665950140590291812,500$
3Sean Farrell0X99.00584273716067656544645960655250140590252850,000$
4Danila Klimovich0XX99.00614663656664626443596055635150140570231850,000$
5John Farinacci0XX99.00574074656267656254595556605350140560252910,000$
6Francesco Arcuri (R)0X99.00604070656560606070605560605050140560231800,000$
7Samuel Lipkin (R)0X95.76604070656060606040605560605050140560231851,667$
8Chase Wheatcroft0XX100.00604170646362605541545256575250140540241870,000$
9Luke Tuch0X100.00645059616864625941525359575250140540241875,000$
10Joey Larson0X100.00594167626364626041545653605250140540252875,000$
11Simon Robertsson (R)0X100.00584270626361585641525254565150140530231800,000$
12Zac Jones0X99.00584176746874707040696370695954140640261812,500$
13Dennis Cholowski0X100.00564077708182726740646265667767140640281875,000$
14Ian Moore0X100.006740767178756867406263716755501406402421,150,000$
15Jake Livingstone0X100.00664369656968666240585468605550140600271800,000$
16Kirill Kudryavtsev (R)0X100.00614172656563616240615463605050140580221800,000$
17Lukas Cormier0X100.00584269696263616340625765635250140580243850,000$
18John Prokop0X100.00564068616160575440515156555250140530252875,000$
Rayé
1Blake Biondi (R)0X100.00594170606361585451505152555250140520241800,000$
2Connor Mylymok0X100.00586152586564625641525152555350140520263850,000$
3Steven Santini0X93.52634172636770685940545367586559140600311800,000$
MOYENNE D’ÉQUIPE98.8160436966656663614558566061545114057
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
1Drew Commesso098.0070646963686973697169585150140640243875,000$
2Kevin Mandolese0100.0067585768646566646563515350140610263800,000$
Rayé
1Ruslan Khazheyev (R)0100.0063555566626163606360535050140580211800,000$
MOYENNE D’ÉQUIPE99.336759606665656764666454515014061
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John MacLean6966707466611CAN6121,000,000$


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
1Jiri KulichToronto Maple LeafsC/RW733622758202831910.71%315221.730113120110101061.36%13283000.7900010110
2John FarinacciToronto Marlies (TOR)C/RW10325-34019122081215.00%118218.27101322000111060.00%1072000.5500000110
3Cameron HebigToronto Marlies (TOR)C/LW/RW91341401311306163.33%417319.270000190110100027.27%1171000.4600000000
4Logan MorrisonToronto Marlies (TOR)C9314-21352113445206.82%418120.141013201014100046.48%142114000.4400100001
5Danila KlimovichToronto Marlies (TOR)LW/RW92240001481441214.29%316017.88202317000040020.00%1023000.5000000001
6Sean FarrellToronto Marlies (TOR)C9224-22015718101411.11%013615.14011041011120140.96%8360000.5900000000
7Zac JonesToronto Marlies (TOR)D9033-32081513350%1222625.19011022011013000%057000.2600000000
8Samuel LipkinToronto Marlies (TOR)LW9123-320111012358.33%215917.77011219000030012.50%825000.3800000001
9Jake LivingstoneToronto Marlies (TOR)D9022320799110%915417.2100001200004000%014000.2600000000
10Luke TuchToronto Marlies (TOR)LW9112-3007662016.67%0788.720000300011000%200000.5100000000
11Steven SantiniToronto Marlies (TOR)D7011-200892200%811616.630110900007000%007000.1700000000
12Francesco ArcuriToronto Marlies (TOR)C8011-3207816450%010012.5500016000000068.75%4840000.2000000000
13Dennis CholowskiToronto Marlies (TOR)D9011-54041310660%1019621.89000123000113000%025000.1000000000
14Ian MooreToronto Marlies (TOR)D9011-595102112220%618720.88000021000113000%061000.1100001000
15Joey LarsonToronto Marlies (TOR)RW9101-1007611489.09%213314.8100005000041020.00%532000.1500000010
16Chase WheatcroftToronto Marlies (TOR)C/LW100001951298250%213913.9200005000000050.00%81300000001000
17John ProkopToronto Marlies (TOR)D3000000010000%0144.910000000000000%00000000000000
18Blake BiondiToronto Marlies (TOR)C1000-100010000%088.300000000000000%10000000000000
19Kirill KudryavtsevToronto Marlies (TOR)D9000-100732110%1707.810000000001000%00300000000000
20Lukas CormierToronto Marlies (TOR)D9000360492010%311412.730000000003000%01000000000000
21Simon RobertssonToronto Marlies (TOR)RW3000-100521000%03010.1100000000000050.00%20200000000000
Statistiques d’équipe totales ou en moyenne166172542-258620187193258661326.59%70271916.384591622523591183150.22%4626652000.3100112233
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
1Drew CommessoToronto Marlies (TOR)93600.8892.905380026235127110090100
Statistiques d’équipe totales ou en moyenne93600.8892.90538002623512711090100


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 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
Blake BiondiToronto Marlies (TOR)C242002-04-24USAYes198 Lbs6 ft1NoNoProspectNoYes12026-09-04FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Cameron HebigToronto Marlies (TOR)C/LW/RW291997-01-21CANNo185 Lbs5 ft10NoNoTrade2026-10-17NoYes12026-08-20FalseFalsePro & Farm812,500$733,140$0$0$No---------------------------
Chase WheatcroftToronto Marlies (TOR)C/LW242002-05-28CANNo185 Lbs6 ft2NoNoTrade2026-10-16NoYes12024-11-19FalseFalsePro & Farm870,000$785,023$0$0$No---------------------------
Connor MylymokToronto Marlies (TOR)LW262000-03-18USANo205 Lbs6 ft1NoNoTrade2026-10-17NoYes32026-09-10FalseFalsePro & Farm850,000$766,977$0$0$No850,000$850,000$-------850,000$850,000$-------NoNo-------
Danila KlimovichToronto Marlies (TOR)LW/RW232003-01-09BELNo202 Lbs6 ft2NoNoTrade2026-10-17NoYes12026-07-01FalseFalsePro & Farm850,000$766,977$0$0$No---------------------------
Dennis CholowskiToronto Marlies (TOR)D281998-02-15CANNo210 Lbs6 ft2NoNoFree AgentNoYes12026-07-02FalseFalsePro & Farm875,000$789,535$0$0$No---------------------------
Drew CommessoToronto Marlies (TOR)G242002-07-19USANo181 Lbs6 ft2NoNoFree AgentNoYes32026-07-06FalseFalsePro & Farm875,000$789,535$0$0$No875,000$875,000$-------875,000$875,000$-------NoNo-------
Francesco ArcuriToronto Marlies (TOR)C232003-06-13CANYes201 Lbs6 ft2NoNoTrade2026-10-17NoYes12026-08-20FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Ian MooreToronto Marlies (TOR)D242002-01-04USANo205 Lbs6 ft3NoNoTrade2026-09-06NoYes22026-08-02FalseFalsePro & Farm1,150,000$1,037,674$0$0$No1,150,000$--------1,150,000$--------No--------
Jake LivingstoneToronto Marlies (TOR)D271999-04-16CANNo213 Lbs6 ft4NoNoFree AgentNoYes12024-09-03FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Joey LarsonToronto Marlies (TOR)RW252001-03-27USANo196 Lbs6 ft1NoNoTrade2026-10-16NoYes22026-07-30FalseFalsePro & Farm875,000$789,535$0$0$No875,000$--------875,000$--------No--------
John FarinacciToronto Marlies (TOR)C/RW252001-02-14USANo184 Lbs5 ft11NoNoTrade2026-10-16NoYes22025-09-25FalseFalsePro & Farm910,000$821,116$0$0$No910,000$--------910,000$--------No--------
John ProkopToronto Marlies (TOR)D252001-05-13USANo195 Lbs6 ft3NoNoTrade2026-10-16NoYes22025-10-02FalseFalsePro & Farm875,000$789,535$0$0$No875,000$--------875,000$--------No--------
Kevin MandoleseToronto Marlies (TOR)G262000-08-22CANNo207 Lbs6 ft5NoNoFree AgentNoYes32026-11-01FalseFalsePro & Farm800,000$721,860$0$0$No800,000$800,000$-------800,000$800,000$-------NoNo-------
Kirill KudryavtsevToronto Marlies (TOR)D222004-02-05RUSYes200 Lbs5 ft11NoNoProspectNoYes12026-10-11FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Logan MorrisonToronto Marlies (TOR)C242002-07-09CANNo188 Lbs6 ft1NoNoTrade2024-10-31NoYes12026-06-22FalseFalsePro & Farm850,000$766,977$0$0$No---------------------------
Lukas CormierToronto Marlies (TOR)D242002-03-27CANNo184 Lbs5 ft11NoNoN/ANoYes32026-07-06FalseFalsePro & Farm850,000$766,977$0$0$No850,000$850,000$-------850,000$850,000$-------NoNo-------
Luke TuchToronto Marlies (TOR)LW242002-03-07USANo219 Lbs6 ft2NoNoTrade2026-09-14NoYes12026-07-15FalseFalsePro & Farm875,000$789,535$0$0$No---------------------------
Ruslan KhazheyevToronto Marlies (TOR)G212004-11-20RUSYes201 Lbs6 ft4NoNoProspectNoYes12026-09-04FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Samuel LipkinToronto Marlies (TOR)LW232003-01-03USAYes192 Lbs6 ft2NoNoN/ANoYes1FalseFalsePro & Farm851,667$768,481$0$0$No---------------------------
Sean FarrellToronto Marlies (TOR)C252001-11-02USANo188 Lbs5 ft9NoNoTrade2026-09-14NoYes22026-07-30FalseFalsePro & Farm850,000$766,977$0$0$No850,000$--------850,000$--------No--------
Simon RobertssonToronto Marlies (TOR)RW232003-02-05SWEYes194 Lbs6 ft0NoNoProspectNoYes12026-10-11FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Steven SantiniToronto Marlies (TOR)D311995-03-07USANo217 Lbs6 ft3NoNoFree AgentNoYes12024-09-03FalseFalsePro & Farm800,000$721,860$0$0$No---------------------------
Zac JonesToronto Marlies (TOR)D262000-10-18USANo190 Lbs5 ft11NoNoFree AgentNoYes12024-10-15FalseFalsePro & Farm812,500$733,140$0$0$No---------------------------
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2424.83198 Lbs6 ft11.54851,319$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cameron HebigLogan MorrisonDanila Klimovich35122
2Samuel LipkinSean FarrellJohn Farinacci35122
3Chase WheatcroftFrancesco ArcuriJoey Larson20122
4Luke TuchLogan MorrisonSimon Robertsson10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac JonesIan Moore35122
2Dennis CholowskiJake Livingstone35122
3Kirill KudryavtsevLukas Cormier20122
4John ProkopZac Jones10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Cameron HebigLogan MorrisonDanila Klimovich50122
2Samuel LipkinSean FarrellJohn Farinacci50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac JonesIan Moore50122
2Dennis CholowskiJake Livingstone50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Logan MorrisonCameron Hebig50122
2Sean FarrellDanila Klimovich50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac JonesIan Moore50122
2Dennis CholowskiJake Livingstone50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Logan Morrison50122Zac JonesIan Moore50122
2Cameron Hebig50122Dennis CholowskiJake Livingstone50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Logan MorrisonCameron Hebig50122
2Sean FarrellDanila Klimovich50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Zac JonesIan Moore50122
2Dennis CholowskiJake Livingstone50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cameron HebigLogan MorrisonDanila KlimovichZac JonesIan Moore
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Cameron HebigLogan MorrisonDanila KlimovichZac JonesIan Moore
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Francesco Arcuri, Chase Wheatcroft, Luke TuchFrancesco Arcuri, Chase WheatcroftLuke Tuch
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Kirill Kudryavtsev, Lukas Cormier, John ProkopKirill KudryavtsevLukas Cormier, John Prokop
Tirs de pénalité
Logan Morrison, Cameron Hebig, Sean Farrell, Danila Klimovich, Francesco Arcuri
Gardien
#1 : Drew Commesso, #2 : Kevin Mandolese


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
1Belleville Senators41300000814-62020000026-42110000068-220.25081119003770117738892011227537617211.76%9455.56%29018050.00%8416550.91%5711250.89%182941778617992
2Laval Rocket1010000014-31010000014-30000000000000.00012300377026738892032116253133.33%3233.33%09018050.00%8416550.91%5711250.89%182941778617992
3Rochester American 11000000211110000002110000000000021.0002350037702673889202813716000%110.00%09018050.00%8416550.91%5711250.89%182941778617992
4Springfield Thunderbirds11000000422110000004220000000000021.0004610003770287388920204621100.00%3166.67%09018050.00%8416550.91%5711250.89%182941778617992
5Syracuse Crunch 1010000013-2000000000001010000013-200.0001120037702773889202074223133.33%20100.00%09018050.00%8416550.91%5711250.89%182941778617992
6Wilkes-Barre/Scranton Penguins 1010000013-2000000000001010000013-200.000123103770297388920244622200.00%3166.67%09018050.00%8416550.91%5711250.89%182941778617992
Total936000001727-1052300000913-441300000814-660.3331725421037702537388920236668218226415.38%21957.14%29018050.00%8416550.91%5711250.89%182941778617992
_Since Last GM Reset936000001727-1052300000913-441300000814-660.3331725421037702537388920236668218226415.38%21957.14%29018050.00%8416550.91%5711250.89%182941778617992
_Vs Conference936000001727-1052300000913-441300000814-660.3331725421037702537388920236668218226415.38%21957.14%29018050.00%8416550.91%5711250.89%182941778617992
_Vs Division1260000013-2013000000001130000013-242.000123103770297388920244622200.00%3166.67%09018050.00%8416550.91%5711250.89%182941778617992

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
96L4172542253236668218210
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
93600001727
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
5230000913
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4130000814
Derniers 10 matchs
WLOTWOTL SOWSOL
360000
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
26415.38%21957.14%2
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
73889203770
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
9018050.00%8416550.91%5711250.89%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
182941778617992


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
310Belleville Senators3Toronto Marlies 1LSommaire du match
422Toronto Marlies 5Belleville Senators2WSommaire du match
733Rochester American 1Toronto Marlies 2WSommaire du match
1052Toronto Marlies 1Belleville Senators6LSommaire du match
1264Springfield Thunderbirds2Toronto Marlies 4WSommaire du match
1580Belleville Senators3Toronto Marlies 1LSommaire du match
1796Toronto Marlies 1Syracuse Crunch 3LSommaire du match
19107Toronto Marlies 1Wilkes-Barre/Scranton Penguins 3LSommaire du match
21116Laval Rocket4Toronto Marlies 1LSommaire du match
23125Toronto Marlies -Lehigh Valley Phantoms-
25138Toronto Marlies -Providence Bruins-
26147Wilkes-Barre/Scranton Penguins -Toronto Marlies -
30160Toronto Marlies -Texas Stars -
33174Toronto Marlies -Hershey Bears -
34179Hartford Wolf Pack -Toronto Marlies -
37195Chicago Wolves-Toronto Marlies -
40208Toronto Marlies -Hartford Wolf Pack -
42222Toronto Marlies -Springfield Thunderbirds-
44230San Jose Barracuda-Toronto Marlies -
47247Toronto Marlies -Rochester American -
48255Manitoba Moose-Toronto Marlies -
51270Toronto Marlies -Wilkes-Barre/Scranton Penguins -
53280Rochester American -Toronto Marlies -
55296Toronto Marlies -Rockford IceHogs -
57307Wilkes-Barre/Scranton Penguins -Toronto Marlies -
60322Toronto Marlies -Henderson Silver Knights-
62333Syracuse Crunch -Toronto Marlies -
64347Toronto Marlies -Bridgeport Islanders-
67357Providence Bruins-Toronto Marlies -
69373Toronto Marlies -Belleville Senators-
71384Rockford IceHogs -Toronto Marlies -
73395Toronto Marlies -Laval Rocket-
76409Lehigh Valley Phantoms-Toronto Marlies -
78416Toronto Marlies -Lehigh Valley Phantoms-
82434Providence Bruins-Toronto Marlies -
84449Toronto Marlies -Milwaukee Admirals -
86457Toronto Marlies -Colorado Eagles-
88466Henderson Silver Knights-Toronto Marlies -
91483Toronto Marlies -Grand Rapids Griffins -
92491Milwaukee Admirals -Toronto Marlies -
95505Toronto Marlies -Grand Rapids Griffins -
97515Syracuse Crunch -Toronto Marlies -
100533Toronto Marlies -Belleville Senators-
101542Hartford Wolf Pack -Toronto Marlies -
104561Toronto Marlies -Providence Bruins-
105567Hershey Bears -Toronto Marlies -
108580Toronto Marlies -Ontario Reign-
110593San Diego Gulls-Toronto Marlies -
113611Toronto Marlies -Rochester American -
115619Grand Rapids Griffins -Toronto Marlies -
117630Toronto Marlies -Texas Stars -
119643Laval Rocket-Toronto Marlies -
121652Toronto Marlies -Iowa Wild-
125671Grand Rapids Griffins -Toronto Marlies -
128683Toronto Marlies -Hershey Bears -
130697Laval Rocket-Toronto Marlies -
133715Toronto Marlies -Wilkes-Barre/Scranton Penguins -
134723Hershey Bears -Toronto Marlies -
138738Toronto Marlies -Chicago Wolves-
140747Toronto Marlies -Syracuse Crunch -
141753Rochester American -Toronto Marlies -
145773Texas Stars -Toronto Marlies -
148794Toronto Marlies -Chicago Wolves-
149802Toronto Marlies -Coachella Valley Firebirds-
150805Iowa Wild-Toronto Marlies -
153826Colorado Eagles-Toronto Marlies -
156844Toronto Marlies -Abbotsford Canucks-
158853Ontario Reign-Toronto Marlies -
162873Toronto Marlies -Abbotsford Canucks-
163879Texas Stars -Toronto Marlies -
166900Toronto Marlies -San Jose Barracuda-
167907Bridgeport Islanders-Toronto Marlies -
169914Toronto Marlies -Laval Rocket-
171929Toronto Marlies -Manitoba Moose-
173934Abbotsford Canucks-Toronto Marlies -
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
176952Toronto Marlies -San Diego Gulls-
178960Lehigh Valley Phantoms-Toronto Marlies -
183981Toronto Marlies -Syracuse Crunch -
184988Coachella Valley Firebirds-Toronto Marlies -
1891013Belleville Senators-Toronto Marlies -
1931026Toronto Marlies -Springfield Thunderbirds-
1951039Belleville Senators-Toronto Marlies -
1991061Chicago Wolves-Toronto Marlies -
2051085Springfield Thunderbirds-Toronto Marlies -
2071098Toronto Marlies -Hartford Wolf Pack -
2121109Springfield Thunderbirds-Toronto Marlies -



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance9,6034,793
Assistance PCT96.03%95.86%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacité de l’arénaPopularité de l’équipe
38 2879 - 95.97% 121,584$607,919$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
290,145$ 2,043,167$ 2,043,167$ 1,000,000$0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
9,503$ 192,474$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
4,620,184$ 194 14,154$ 2,745,876$




Toronto 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

Toronto 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

Toronto 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

Toronto 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

Toronto 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