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Toronto Marlies
GP: 14 | W: 8 | L: 5 | OTL: 1 | P: 17
GF: 46 | GA: 44 | PP%: 18.37% | PK%: 77.27%
DG: Flavio | Morale : 43 | Moyenne d’équipe : 60
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Centre de jeu
Utica Comets
9-1-4, 22pts
4
FINAL
5 Toronto Marlies
8-5-1, 17pts
Team Stats
W1SéquenceW2
6-0-1Fiche domicile5-1-1
3-1-3Fiche domicile3-4-0
7-0-3Derniers 10 matchs6-3-1
4.21Buts par match 3.29
3.64Buts contre par match 3.14
21.82%Pourcentage en avantage numérique18.37%
89.36%Pourcentage en désavantage numérique77.27%
Rochester Americans
6-6-2, 14pts
1
FINAL
4 Toronto Marlies
8-5-1, 17pts
Team Stats
L2SéquenceW2
4-3-0Fiche domicile5-1-1
2-3-2Fiche domicile3-4-0
5-3-2Derniers 10 matchs6-3-1
4.43Buts par match 3.29
4.50Buts contre par match 3.14
37.74%Pourcentage en avantage numérique18.37%
68.75%Pourcentage en désavantage numérique77.27%
Meneurs d'équipe
Dylan GambrellButs
Dylan Gambrell
7
Passes
William Lagesson
10
Points
William Lagesson
13
Plus/Moins
Easton Cowan
7
Victoires
Matt Murray
8
Pourcentage d’arrêts
Matt Murray
0.921

Statistiques d’équipe
Buts pour
46
3.29 GFG
Tirs pour
568
40.57 Avg
Pourcentage en avantage numérique
18.4%
9 GF
Début de zone offensive
41.8%
Buts contre
44
3.14 GAA
Tirs contre
541
38.64 Avg
Pourcentage en désavantage numérique
77.3%%
10 GA
Début de la zone défensive
41.2%
Informations de l'équipe

Directeur généralFlavio
EntraîneurJohn Gruden
DivisionNorth Division
ConférenceEastern Conference
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,724
Billets de saison0


Informations de la formation

Équipe Pro34
Équipe Mineure18
Limite contact 52 / 70
Espoirs11


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 moyen
1Dylan Gambrell0X100.00774086667363835871696077546158047670281775,000$
2Kieffer Bellows0XX100.00715183647360645852666166555757047640261775,000$
3Logan Shaw0X100.00555765636966646355616159587062047620321775,000$
4Alex Steeves0X100.00555866646366646155596159545855047610251775,000$
5Bobby McMann0X100.00585669627063605854586062546258047610281775,000$
6Joseph Blandisi0X100.00565764596165635970585962546760047600301775,000$
7Kyle Clifford0XX100.00616270607461655754595761547562047600331775,000$
8Fraser Minten0XXX100.006060606060606060606060606060600476002031,300,000$
9Easton Cowan (R)0XXX100.00606060606060606060606060606060047600191775,000$
10Braeden Kressler (R)0X100.00606060606060606060606060606060047600211775,000$
11Matthew Knies0XX100.005438675279675452485850575151550475602211,100,000$
12Ryan Tverberg0X100.00515165515952525152515157515149047520221775,000$
13Jake Muzzin0X100.00704076669077725740645579547765044680351775,000$
14Simon Benoit0X100.00816782577778825740695983545758045680261775,000$
15Conor Timmins0X100.00664283667670615940735675545657047660261775,000$
16William Lagesson0X100.00596272607166655840615769546258048620281775,000$
17Maxime Lajoie0X100.00555666606566646040605761546257047600271775,000$
18Noah Chadwick (R)0X100.00606060606060606060606060606060047600191775,000$
Rayé
1Josiah Slavin0XXX100.00545667576466645755565859546056026590261775,000$
2Max Ellis0XX100.00555567575660605655555761545654026570241775,000$
3Zach Solow0XX100.00565466555758585555545560546056026560261775,000$
4Dmitri Ovchinnikov0XXX100.00545468545655545455545461545352026550221775,000$
5David Farrance0X100.00555467586263615740575560555855026580251775,000$
6William Villeneuve0X100.00555462566061605744575560545453026570221775,000$
7Matteo Pietroniro0X100.00565565556261605440545460546056026570261775,000$
8Mikko Kokkonen0X100.00555462556259585544555458545553026560231775,000$
9Marshall Rifai0X100.00545257556064635438535358515853026560261775,000$
10Tommy Miller0X100.00515165536159575238525158515652026540251775,000$
11Topi Niemela0X100.00515165525452525138515157515149026530221775,000$
MOYENNE D’ÉQUIPE100.0059546859656362575059576355605703959
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 moyen
1Matt Murray0100.0076707189797381708272836868050760302775,000$
2Keith Petruzzelli0100.0067666786666567666567666369050670251775,000$
Rayé
1Joseph Woll0100.00645959727157716265575859550336402611,000,000$
2Artur Akhtyamov (R)0100.0060606060606060606060606060033600231775,000$
3Dennis Hildeby0100.0051515173615162515552625148033550231775,000$
MOYENNE D’ÉQUIPE100.006461627667616862656266606004064
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
John Gruden68756468777273USA527500,000$


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
1William LagessonToronto Marlies (TOR)D1431013-4312518142882210.71%2031722.691121138011133020%000000.8200014010
2Conor TimminsToronto Marlies (TOR)D1421012-4203231357275.71%2833223.731232440000033000%000000.7200000111
3Dylan GambrellToronto Marlies (TOR)C147411020445467204010.45%829521.0921310390001341054.70%45700100.7503000201
4Kieffer BellowsToronto Marlies (TOR)LW/RW142790602322549333.70%529421.0602210390002341068.18%2200000.6123000101
5Kyle CliffordToronto Marlies (TOR)LW/RW14639-44017114493013.64%023416.732131041000021246.67%1500000.7700000110
6Logan ShawToronto Marlies (TOR)C14369-32023295316355.66%527319.5203310400004350043.35%34600000.6600000100
7Maxime LajoieToronto Marlies (TOR)D1418954019221914195.26%2329220.88022839000136100%000000.6200000010
8Easton CowanToronto Marlies (TOR)C/LW/RW1445971002263981610.26%216411.7500000000000025.00%1200001.0900000102
9Alex SteevesToronto Marlies (TOR)C1435872017274313216.98%224717.7001111401012370044.09%31300000.6500000010
10Braeden KresslerToronto Marlies (TOR)C14167-41003211239204.35%223116.531341140000000031.58%1900000.6000000000
11Noah ChadwickToronto Marlies (TOR)D1407751803211288150%1828920.680111239000030000%000000.4800000001
12Bobby McMannToronto Marlies (TOR)C14325-220791951215.79%221815.5900000000031050.00%2200000.4602000001
13Simon BenoitToronto Marlies (TOR)D1423511552527244158.33%2322015.770000100002000%000000.4500001110
14Fraser MintenToronto Marlies (TOR)C/LW/RW1423574018123010316.67%417212.3200002000000042.86%2100000.5800000011
15Jake MuzzinToronto Marlies (TOR)D142241401719217139.52%1724117.2420234000113000%000000.3300000000
16Joseph BlandisiToronto Marlies (TOR)C14123-1001422256214.00%11158.2800012000000056.35%12600000.5200000000
17Matthew KniesToronto Marlies (TOR)LW/RW141010209113397.69%11128.0500000000001050.00%400000.1800000000
18Ryan TverbergToronto Marlies (TOR)C14101-1002433633.33%01117.9500000000000050.00%800000.1800000000
Statistiques d’équipe totales ou en moyenne252448312710118303713325681593857.75%161416516.5391726121411112122986448.79%136500100.6128015878
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
1Matt MurrayToronto Marlies (TOR)148510.9213.0285420435410000.8899140100
Statistiques d’équipe totales ou en moyenne148510.9213.0285420435410009140100


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 Recrue Poids Taille Non-échange Disponible pour échange Acquis Par Date de la Dernière Transaction Ballotage forcé Waiver Possible Contrat Date du Signature du Contrat Forcer UFA Rappel d'urgence Type Salaire actuel Salaire restantSalaire moyenSalaire moyen restantPlafond salarial Non Activé Plafond salarial restant Exclus du plafond salarial Salaire annuel 2Salaire annuel 3Salaire annuel 4Salaire annuel 5Salaire annuel 6Salaire annuel 7Salaire annuel 8Salaire annuel 9Salaire annuel 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
Alex SteevesToronto Marlies (TOR)C2510.12.1999No89 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Artur AkhtyamovToronto Marlies (TOR)G2331.10.2001Yes76 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Bobby McMannToronto Marlies (TOR)C2815.06.1996No95 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Braeden KresslerToronto Marlies (TOR)C2105.01.2003Yes79 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Conor TimminsToronto Marlies (TOR)D2618.09.1998No92 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
David FarranceToronto Marlies (TOR)D2523.06.1999No86 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Dennis HildebyToronto Marlies (TOR)G2319.08.2001No106 Kg198 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Dmitri OvchinnikovToronto Marlies (TOR)C/LW/RW2219.08.2002No74 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Dylan GambrellToronto Marlies (TOR)C2826.08.1996No84 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien / Lien NHL
Easton CowanToronto Marlies (TOR)C/LW/RW1920.05.2005Yes84 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Fraser MintenToronto Marlies (TOR)C/LW/RW2005.07.2004 06:31:35No87 Kg188 CMNoNoN/ANoNo3FalseFalsePro & Farm1,300,000$1,300,000$0$0$No1,300,000$1,300,000$-------NoNo-------
Jake MuzzinToronto Marlies (TOR)D3521.02.1989No103 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Joseph BlandisiToronto Marlies (TOR)C3018.07.1994No83 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Joseph WollToronto Marlies (TOR)G2612.07.1998No92 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm1,000,000$1,000,000$0$0$No------------------Lien
Josiah SlavinToronto Marlies (TOR)C/LW/RW2631.12.1998No86 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Keith PetruzzelliToronto Marlies (TOR)G2509.02.1999No84 Kg196 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Kieffer BellowsToronto Marlies (TOR)LW/RW2610.06.1998No89 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Kyle CliffordToronto Marlies (TOR)LW/RW3313.01.1991No99 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Logan ShawToronto Marlies (TOR)C3205.10.1992No94 Kg193 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Marshall RifaiToronto Marlies (TOR)D2616.03.1998No86 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Matt MurrayToronto Marlies (TOR)G3025.05.1994No92 Kg196 CMNoNoN/ANoNo2FalseFalsePro & Farm775,000$775,000$0$0$No775,000$--------No--------Lien
Matteo PietroniroToronto Marlies (TOR)D2620.10.1998No84 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Matthew KniesToronto Marlies (TOR)LW/RW2217.10.2002No95 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm1,100,000$1,100,000$0$0$No------------------Lien
Max EllisToronto Marlies (TOR)LW/RW2418.01.2000No78 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Maxime LajoieToronto Marlies (TOR)D2705.11.1997No89 Kg185 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Mikko KokkonenToronto Marlies (TOR)D2318.01.2001No91 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Noah ChadwickToronto Marlies (TOR)D1910.05.2005Yes91 Kg193 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Ryan TverbergToronto Marlies (TOR)C2230.01.2002No86 Kg183 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Simon BenoitToronto Marlies (TOR)D2619.09.1998No92 Kg191 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien / Lien NHL
Tommy MillerToronto Marlies (TOR)D2506.03.1999No88 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Topi NiemelaToronto Marlies (TOR)D2225.03.2002No77 Kg180 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
William LagessonToronto Marlies (TOR)D2822.02.1996No94 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
William VilleneuveToronto Marlies (TOR)D2220.03.2002No83 Kg188 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Zach SolowToronto Marlies (TOR)LW/RW2606.11.1998No80 Kg175 CMNoNoN/ANoNo1FalseFalsePro & Farm775,000$775,000$0$0$No------------------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
3425.3288 Kg185 CM1.09806,618$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Kieffer BellowsDylan GambrellBobby McMann33122
2Braeden KresslerLogan ShawKyle Clifford30122
3Fraser MintenAlex SteevesEaston Cowan25122
4Matthew KniesJoseph BlandisiRyan Tverberg12122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Conor TimminsWilliam Lagesson33122
2Noah ChadwickMaxime Lajoie30122
3Jake MuzzinSimon Benoit25122
4Conor TimminsWilliam Lagesson12122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Kieffer BellowsDylan GambrellAlex Steeves50122
2Braeden KresslerLogan ShawKyle Clifford50122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Dylan GambrellKieffer Bellows50122
2Alex SteevesLogan Shaw50122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Dylan Gambrell50122Conor TimminsWilliam Lagesson50122
2Kieffer Bellows50122Noah ChadwickMaxime Lajoie50122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan GambrellKieffer Bellows50122
2Alex SteevesLogan Shaw50122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Conor TimminsWilliam Lagesson50122
2Noah ChadwickMaxime Lajoie50122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Kieffer BellowsDylan GambrellLogan ShawConor TimminsWilliam Lagesson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Kieffer BellowsDylan GambrellLogan ShawConor TimminsWilliam Lagesson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Joseph Blandisi, Braeden Kressler, Alex SteevesJoseph Blandisi, Braeden KresslerAlex Steeves
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Conor Timmins, William Lagesson, Noah ChadwickConor TimminsWilliam Lagesson, Noah Chadwick
Tirs de pénalité
Dylan Gambrell, Kieffer Bellows, Bobby McMann, Logan Shaw, Alex Steeves
Gardien
#1 : Matt Murray, #2 : Keith Petruzzelli
Lignes d’attaque personnalisées en prolongation
Dylan Gambrell, Kieffer Bellows, Fraser Minten, Logan Shaw, Alex Steeves, Bobby McMann, Bobby McMann, Easton Cowan, Kyle Clifford, Joseph Blandisi, Braeden Kressler
Lignes de défense personnalisées en prolongation
Conor Timmins, William Lagesson, Noah Chadwick, Maxime Lajoie, Simon Benoit


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
1Belleville Senators21100000770110000005321010000024-220.5007132000151811289178215162218325183610220.00%9277.78%028956051.61%26055247.10%11722951.09%34623431410619499
2Calgary Wranglers2110000067-1110000005321010000014-320.50061218001518112761782151622174321060600.00%5260.00%028956051.61%26055247.10%11722951.09%34623431410619499
3Cleveland Monsters2110000046-2110000004311010000003-320.50048120015181127817821516221611834586116.67%7271.43%028956051.61%26055247.10%11722951.09%34623431410619499
4Laval Rocket2010001067-11010000024-21000001043120.50069150015181129017821516221973312526116.67%50100.00%128956051.61%26055247.10%11722951.09%34623431410619499
5Rochester Americans22000000835110000004131100000042241.000815230015181128217821516221772017528225.00%6183.33%028956051.61%26055247.10%11722951.09%34623431410619499
6Syracuse Crunch210000018711000000145-11100000042230.750814220015181126117821516221621523563266.67%9277.78%028956051.61%26055247.10%11722951.09%34623431410619499
7Utica Comets20100010770100000105411010000023-120.500712190015181129217821516221871865710110.00%3166.67%028956051.61%26055247.10%11722951.09%34623431410619499
Total146500021464427410001129236724000101721-4170.60746831290015181125681782151622154116112037149918.37%441077.27%128956051.61%26055247.10%11722951.09%34623431410619499
_Since Last GM Reset146500021464427410001129236724000101721-4170.60746831290015181125681782151622154116112037149918.37%441077.27%128956051.61%26055247.10%11722951.09%34623431410619499
_Vs Conference146500021464427410001129236724000101721-4170.60746831290015181125681782151622154116112037149918.37%441077.27%128956051.61%26055247.10%11722951.09%34623431410619499
_Vs Division865000212924544100011151324240001014113171.06329518000151811232217821516221319937019627725.93%29582.76%128956051.61%26055247.10%11722951.09%34623431410619499

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1417W2468312956854116112037100
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
146500214644
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
74100112923
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
72400101721
Derniers 10 matchs
WLOTWOTL SOWSOL
630001
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
49918.37%441077.27%1
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
178215162211518112
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
28956051.61%26055247.10%11722951.09%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
34623431410619499


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
17Toronto Marlies1Calgary Wranglers4LSommaire du match
318Calgary Wranglers3Toronto Marlies5WSommaire du match
537Cleveland Monsters3Toronto Marlies4WSommaire du match
751Toronto Marlies2Belleville Senators4LSommaire du match
865Toronto Marlies4Rochester Americans2WSommaire du match
1084Belleville Senators3Toronto Marlies5WSommaire du match
1295Toronto Marlies2Utica Comets3LSommaire du match
14116Laval Rocket4Toronto Marlies2LSommaire du match
17134Toronto Marlies4Syracuse Crunch2WSommaire du match
19153Syracuse Crunch5Toronto Marlies4LXXSommaire du match
21168Toronto Marlies4Laval Rocket3WXXSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
22176Toronto Marlies0Cleveland Monsters3LSommaire du match
24189Utica Comets4Toronto Marlies5WXXSommaire du match
28217Rochester Americans1Toronto Marlies4WSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance12,6036,465
Assistance PCT90.02%92.36%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2724 - 90.80% 76,869$538,080$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
3,242,490$ 2,742,500$ 2,742,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
91,417$ 2,742,510$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 108,083$ 0$




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