TORONTO Marlies

GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: Benoit Paulin | Morale : 99 | Moyenne d'Équipe : 65
Prochain matchs #4 vs BROOKLYN Wolfpack
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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
1Casey Mittelstadt0X100.006239886677818364716362656663658799690211875,000$
2Adam Erne0X100.008947776380748762586159576368657499680253800,000$
3Henrik Borgstrom0X100.0064438664838077667361596366656281996802361,250,000$
4Brett Ritchie0X100.0084507861897375595257586059736862996702711,750,000$
5John Quenneville (R)0X100.006145866376838061736062646367647699670243750,000$
6Paul Bittner (R)0XX100.007351875990858258555756605967647399670233750,000$
7Dominic Toninato (R)0X100.006347826179807859655860625971665799670263750,000$
8Jordan Kyrou (R)0X100.005739896769777666586364656863647699670223750,000$
9Lukas Vejdemo (R)0X100.006245906279788363746158646567646299670243750,000$
10Rasmus Asplund (R)0X100.005839826670817863726461656365667799670223750,000$
11Isaac Ratcliffe (R)0X100.007452835692858755515454595361627699660213750,000$
12Nicholas Merkley (R)0X100.005842896069777362576159586265637899640233750,000$
13Matthew Phillips (R)0X100.005339876157837862586059576263616499640223750,000$
14Spencer Smallman (R)0X100.006345846077757361555952586167635299640233750,000$
15Daniel O'Regan (R)0X100.004435827658474161485858585858497999570263750,000$
16Ryan Collins (R)0X100.007749875593767856305354604567647099650243750,000$
17Martin Fehervary (R)0X100.006445876081847458305757594661637499650206800,000$
18Nick Ebert0X100.006247865774828156305554584671665999640261750,000$
19Jesper Lindgren (R)0X100.005341835867757457305652545165636699610233750,000$
20Andrew Welinski (R)0X100.004835816575474350304140564960507199520273750,000$
Rayé
MOYENNE D'ÉQUIPE100.00634485627776756054585760586563719965
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 SP
1Ville Husso (R)100.00748482847372747372747369736199680
2Marcus Hogberg (R)100.00737573917271737271737271756299670
Rayé
1Veini Vehvilainen (R)100.00718280717069717069717065696299640
2Brandon Halverson (R)100.00605856885958605958605967716799580
MOYENNE D'ÉQUIPE100.0070757384696870696870696872639964
Nom du Coach PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Darryl Sutter71717070868646CAN633300,000$


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
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


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 Nouveau Joueur Poids Taille Non-Échange Disponible pour Échange Ballotage Forcé Contrat Type Salaire Actuel Salaire RestantSalaire MoyenSalaire Moyen RestantCap Salariale Cap Salariale Restant Exclus du Cap Salarial Salaire Année 2Salaire Année 3Salaire Année 4Salaire Année 5Salaire Année 6Salaire Année 7Salaire Année 8Salaire Année 9Salaire Année 10Link
Adam ErneTORONTO Marlies (TOR)LW254/20/1995No96 Kg185 CMNoNoNo3Pro & Farm800,000$800,000$800,000$800,000$0$0$No800,000$800,000$Lien
Andrew WelinskiTORONTO Marlies (TOR)D274/27/1993Yes91 Kg188 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Brandon HalversonTORONTO Marlies (TOR)G243/29/1996Yes95 Kg193 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Brett RitchieTORONTO Marlies (TOR)RW277/1/1993No100 Kg193 CMNoNoNo1Pro & Farm1,750,000$1,750,000$1,750,000$1,750,000$0$0$NoLien
Casey MittelstadtTORONTO Marlies (TOR)C2111/22/1998No90 Kg185 CMNoNoNo1Pro & Farm875,000$875,000$750,000$750,000$0$0$NoLien
Daniel O'ReganTORONTO Marlies (TOR)C261/30/1994Yes82 Kg175 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Dominic ToninatoTORONTO Marlies (TOR)C263/9/1994Yes87 Kg188 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Henrik BorgstromTORONTO Marlies (TOR)C238/6/1997No90 Kg191 CMNoNoNo6Pro & Farm1,250,000$1,250,000$750,000$750,000$0$0$No1,250,000$1,250,000$1,250,000$1,250,000$1,250,000$Lien
Isaac RatcliffeTORONTO Marlies (TOR)LW212/15/1999Yes91 Kg198 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Jesper LindgrenTORONTO Marlies (TOR)D235/19/1997Yes75 Kg183 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
John QuennevilleTORONTO Marlies (TOR)C244/16/1996Yes89 Kg185 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Jordan KyrouTORONTO Marlies (TOR)C225/5/1998Yes80 Kg183 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Lukas VejdemoTORONTO Marlies (TOR)C241/25/1996Yes88 Kg188 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Marcus HogbergTORONTO Marlies (TOR)G2511/25/1994Yes95 Kg196 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Martin FehervaryTORONTO Marlies (TOR)D2010/6/1999Yes91 Kg188 CMNoNoNo6Pro & Farm800,000$800,000$750,000$750,000$0$0$No800,000$800,000$800,000$800,000$800,000$
Matthew PhillipsTORONTO Marlies (TOR)RW224/6/1998Yes64 Kg170 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Nicholas MerkleyTORONTO Marlies (TOR)RW235/23/1997Yes88 Kg178 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Nick EbertTORONTO Marlies (TOR)D265/11/1994No91 Kg183 CMNoNoNo1Pro & Farm750,000$750,000$750,000$750,000$0$0$NoLien
Paul BittnerTORONTO Marlies (TOR)C/LW2311/4/1996Yes93 Kg196 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Rasmus AsplundTORONTO Marlies (TOR)C2212/3/1997Yes86 Kg180 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Ryan CollinsTORONTO Marlies (TOR)D245/6/1996Yes98 Kg196 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Spencer SmallmanTORONTO Marlies (TOR)RW239/9/1996Yes90 Kg185 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Veini VehvilainenTORONTO Marlies (TOR)G232/13/1997Yes82 Kg183 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Ville HussoTORONTO Marlies (TOR)G252/6/1995Yes93 Kg191 CMNoNoNo3Pro & Farm750,000$750,000$750,000$750,000$0$0$No750,000$750,000$
Joueurs TotalÂge MoyenPoids MoyenTaille MoyenneContrat MoyenSalaire Moyen 1e Année
2423.7189 Kg188 CM3.00821,875$



Attaque à 5 contre 5
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneBrett Ritchie31122
2Paul Bittner26122
3Isaac RatcliffeMatthew Phillips23122
4John Quenneville20122
Défense à 5 contre 5
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins31122
226122
3Jesper LindgrenAndrew Welinski23122
4Ryan Collins20122
Attaque en Avantage Numérique
Ligne #Ailier GaucheCentreAilier Droit% TempsPHYDFOF
1Adam ErneBrett Ritchie55122
2Paul Bittner45122
Défense en Avantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
245122
Attaque à 4 en Désavantage Numérique
Ligne #CentreAilier% TempsPHYDFOF
155122
2Adam Erne45122
Défense à 4 en Désavantage Numérique
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
245122
3 joueurs en Désavantage Numérique
Ligne #Ailier% TempsPHYDFOFDéfenseDéfense% TempsPHYDFOF
155122Ryan Collins55122
24512245122
Attaque à 4 contre 4
Ligne #CentreAilier% TempsPHYDFOF
155122
2Adam Erne45122
Défense à 4 contre 4
Ligne #DéfenseDéfense% TempsPHYDFOF
1Ryan Collins55122
245122
Attaque Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneBrett RitchieRyan Collins
Défense Dernière Minute
Ailier GaucheCentreAilier DroitDéfenseDéfense
Adam ErneBrett RitchieRyan Collins
Attaquants Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Dominic Toninato, Jordan Kyrou, Lukas VejdemoDominic Toninato, Jordan KyrouLukas Vejdemo
Défenseurs Supplémentaires
Normal Avantage NumériqueDésavantage Numérique
Jesper Lindgren, Andrew Welinski, Jesper LindgrenAndrew Welinski,
Tirs de Pénalité
, , , Adam Erne, Brett Ritchie
Gardien
#1 : , #2 : Marcus Hogberg
Lignes d'Attaque Perso. en Prol.
, , , Adam Erne, Brett Ritchie, John Quenneville, John Quenneville, Paul Bittner, Dominic Toninato, Jordan Kyrou, Lukas Vejdemo
Lignes de Défense Perso. en Prol.
, Ryan Collins, , , Jesper Lindgren


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
LigueDomicileVisiteur
# 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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total Pour les Joueurs
Matchs JouésPointsSéquenceButsPassesPointsTirs PourTirs ContreTirs BloquésMinutes de PénalitéMises en ÉchecButs en Filet DésertBlanchissage
00N/A0000000000
Tous les Matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs Éxtérieurs
GPWLOTWOTL SOWSOLGFGA
000000000
Derniers 10 Matchs
WLOTWOTL SOWSOL
000000
Tentatives en Avantage NumériqueButs en Avantage Numérique% en Avantage NumériqueTentatives en Désavantage NumériqueButs Contre en Désavantage Numérique% en Désavantage NumériqueButs Pour en Désavantage Numérique
000.00%000.00%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
00000000
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
000.00%000.00%000.00%
Temps Avec la Rondelle
En Zone OffensiveContrôle en Zone OffensiveEn Zone DéfensiveContrôle en Zone DéfensiveEn Zone NeutreContrôle en Zone Neutre
000000


Derniers Match 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
1 - 2021-01-164TORONTO Marlies-BROOKLYN Wolfpack-
2 - 2021-01-179TORONTO Marlies-LAVAL Rocket-
5 - 2021-01-2025SCRANTON Penguins-TORONTO Marlies-
7 - 2021-01-2241HERSEY Bears-TORONTO Marlies-
10 - 2021-01-2552TORONTO Marlies-BRIDGEPORT Sound Tigers-
13 - 2021-01-2865TORONTO Marlies-TUSCON Roadrunners-
14 - 2021-01-2974UTICA Comets-TORONTO Marlies-
19 - 2021-02-0392UTICA Comets-TORONTO Marlies-
21 - 2021-02-05103TORONTO Marlies-LAVAL Rocket-
23 - 2021-02-07108TORONTO Marlies-BROOKLYN Wolfpack-
25 - 2021-02-09122PROVIDENCE Bruins-TORONTO Marlies-
30 - 2021-02-14144MANITOBA Moose-TORONTO Marlies-
31 - 2021-02-15152TORONTO Marlies-HERSEY Bears-
34 - 2021-02-18170TUSCON Roadrunners-TORONTO Marlies-
36 - 2021-02-20177TORONTO Marlies-BRIDGEPORT Sound Tigers-
38 - 2021-02-22189TORONTO Marlies-COLORADO Eagles-
40 - 2021-02-24204PROVIDENCE Bruins-TORONTO Marlies-
42 - 2021-02-26212TORONTO Marlies-ROCKFORD IceHogs-
45 - 2021-03-01225TORONTO Marlies-CHICAGO Wolves-
46 - 2021-03-02234ONTARIO Reign-TORONTO Marlies-
50 - 2021-03-06254BINGHAMTON Devils-TORONTO Marlies-
52 - 2021-03-08266TORONTO Marlies-BROOKLYN Wolfpack-
54 - 2021-03-10276TORONTO Marlies-CAROLINA Checkers-
55 - 2021-03-11282LEHIGH VALLEY Phantoms-TORONTO Marlies-
60 - 2021-03-16305TUSCON Roadrunners-TORONTO Marlies-
63 - 2021-03-19326LAVAL Rocket-TORONTO Marlies-
65 - 2021-03-21335TORONTO Marlies-UTICA Comets-
68 - 2021-03-24354TORONTO Marlies-BINGHAMTON Devils-
69 - 2021-03-25359UTICA Comets-TORONTO Marlies-
73 - 2021-03-29380COLORADO Eagles-TORONTO Marlies-
75 - 2021-03-31390TORONTO Marlies-MILWAUKEE Admirals-
77 - 2021-04-02400TORONTO Marlies-HERSEY Bears-
78 - 2021-04-03409MANITOBA Moose-TORONTO Marlies-
83 - 2021-04-08428TORONTO Marlies-ONTARIO Reign-
84 - 2021-04-09436BELLEVILLE Senators-TORONTO Marlies-
87 - 2021-04-12453TORONTO Marlies-COLORADO Eagles-
89 - 2021-04-14458PROVIDENCE Bruins-TORONTO Marlies-
91 - 2021-04-16471TORONTO Marlies-UTICA Comets-
93 - 2021-04-18484BELLEVILLE Senators-TORONTO Marlies-
95 - 2021-04-20499TORONTO Marlies-BAKERSFIELD Condors-
97 - 2021-04-22511TORONTO Marlies-SCRANTON Penguins-
98 - 2021-04-23518BAKERSFIELD Condors-TORONTO Marlies-
101 - 2021-04-26532TORONTO Marlies-HERSEY Bears-
103 - 2021-04-28543BROOKLYN Wolfpack-TORONTO Marlies-
105 - 2021-04-30561TORONTO Marlies-BRIDGEPORT Sound Tigers-
107 - 2021-05-02569CAROLINA Checkers-TORONTO Marlies-
110 - 2021-05-05588GRAND RAPIDS Griffins-TORONTO Marlies-
112 - 2021-05-07597TORONTO Marlies-BELLEVILLE Senators-
116 - 2021-05-11615ROCKFORD IceHogs-TORONTO Marlies-
118 - 2021-05-13628TORONTO Marlies-STOCKTON Flames-
120 - 2021-05-15636TORONTO Marlies-LEHIGH VALLEY Phantoms-
121 - 2021-05-16646CHICAGO Wolves-TORONTO Marlies-
124 - 2021-05-19665TORONTO Marlies-IOWA Wild-
126 - 2021-05-21672ROCKFORD IceHogs-TORONTO Marlies-
128 - 2021-05-23684TORONTO Marlies-SAN DIEGO Gulls-
131 - 2021-05-26697ST-ANTONIO Rampage-TORONTO Marlies-
134 - 2021-05-29714TORONTO Marlies-ST-ANTONIO Rampage-
136 - 2021-05-31724SYRACUSE Crunch-TORONTO Marlies-
139 - 2021-06-03741TORONTO Marlies-PROVIDENCE Bruins-
142 - 2021-06-06750SAN DIEGO Gulls-TORONTO Marlies-
145 - 2021-06-09770TORONTO Marlies-PROVIDENCE Bruins-
146 - 2021-06-10775BROOKLYN Wolfpack-TORONTO Marlies-
151 - 2021-06-15797HERSEY Bears-TORONTO Marlies-
155 - 2021-06-19819SCRANTON Penguins-TORONTO Marlies-
157 - 2021-06-21832TORONTO Marlies-SYRACUSE Crunch-
160 - 2021-06-24848STOCKTON Flames-TORONTO Marlies-
163 - 2021-06-27861TORONTO Marlies-MANITOBA Moose-
165 - 2021-06-29873TORONTO Marlies-GRAND RAPIDS Griffins-
167 - 2021-07-01879MILWAUKEE Admirals-TORONTO Marlies-
170 - 2021-07-04898ST-ANTONIO Rampage-TORONTO Marlies-
172 - 2021-07-06904TORONTO Marlies-LAVAL Rocket-
175 - 2021-07-09922TORONTO Marlies-TUSCON Roadrunners-
177 - 2021-07-11929GRAND RAPIDS Griffins-TORONTO Marlies-
181 - 2021-07-15948TORONTO Marlies-GRAND RAPIDS Griffins-
182 - 2021-07-16958SAN DIEGO Gulls-TORONTO Marlies-
186 - 2021-07-20978IOWA Wild-TORONTO Marlies-
187 - 2021-07-21979TORONTO Marlies-TUSCON Roadrunners-
189 - 2021-07-23994TORONTO Marlies-LAVAL Rocket-
192 - 2021-07-261011MILWAUKEE Admirals-TORONTO Marlies-
Date Limite d'Échange --- Les échange ne peuvent plus se faire après la simulation de cette journée!
198 - 2021-08-011036BRIDGEPORT Sound Tigers-TORONTO Marlies-



Capacité de l'Aréna - Tendance du Prix des Billets - %
Niveau 1Niveau 2
Capacité de l'Aréna20001000
Prix des Billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenus
Matchs à domicile RestantsAssistance Moyenne - %Revenus Moyen par MatchRevenus Annuels à ce JourCapacité de l'ArénaPopularité de l'Équipe
40 0 - 0.00%0$0$3000100

Dépenses
Dépenses Annuelles à Ce JourSalaire Total des JoueursSalaire Total Moyen des JoueursSalaire des Coachs
0$ 1,972,500$ 1,905,000$ 0$
Cap Salarial Par JourCap salarial à ce jourJoueurs Inclut dans la Cap SalarialeJoueurs Exclut dans la Cap Salariale
0$ 0$ 0 0

Éstimation
Revenus de la Saison ÉstimésJours Restants de la SaisonDépenses Par JourDépenses de la Saison Éstimées
0$ 200 9,862$ 1,972,400$




LigueDomicileVisiteur
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
Saison Régulière
3480273702842219258-394091801741105133-2840181901101114125-1176219367586226885609241978083579437291483855014782654918.49%2475478.14%21015248540.85%1116293937.97%474118939.87%180912932106559942452
3480273702842219258-394091801741105133-2840181901101114125-1176219367586226885609241978083579437291483855014782654918.49%2475478.14%21015248540.85%1116293937.97%474118939.87%180912932106559942452
Total Saison Régulière1605474041684438516-78801836021482210266-5680363802202228250-221524387341172441361701201848381560167015887458281676110029565309818.49%49410878.14%42030497040.85%2232587837.97%948237839.87%36192587421211191885905