Connexion

Marlies
GP: 0 | W: 0 | L: 0 | OTL: 0 | P: 0
GF: 0 | GA: 0 | PP%: 0.00% | PK%: 0.00%
DG: LedTasso | Morale : 40 | Moyenne d’équipe : 59
Prochain matchs #7 vs Rocket
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Marlies
0-0-0, 0pts
2022-09-14
Rocket
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Bears
0-0-0, 0pts
2022-09-15
Marlies
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Senators
0-0-0, 0pts
2022-09-17
Marlies
0-0-0, 0pts
Statistiques d’équipe
N/ASéquenceN/A
0-0-0Fiche domicile0-0-0
0-0-0Fiche visiteur0-0-0
0-0-010 derniers matchs0-0-0
0.00Buts par match 0.00
0.00Buts contre par match 0.00
0.00%Pourcentage en avantage numérique0.00%
0.00%Pourcentage en désavantage numérique0.00%
Meneurs d'équipe

Statistiques d’équipe
Buts pour
0
0.00 GFG
Tirs pour
0
0.00 Avg
Pourcentage en avantage numérique
0.0%
0 GF
Début de zone offensive
0.0%
Buts contre
0
0.00 GAA
Tirs contre
0
0.00 Avg
Pourcentage en désavantage numérique
0.0%
0 GA
Début de la zone défensive
0.0%
Information d’équipe

Directeur généralLedTasso
EntraîneurAdam Oates
DivisionAtlantic Division
ConférenceEastern Conference
CapitaineJayson Megna
Assistant #1Michael Sgarbossa
Assistant #2Mitchell Chaffee


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison0


Information formation

Équipe Pro29
Équipe Mineure19
Limite contact 48 / 90
Espoirs31


Historique d'équipe

Saison actuelle0-0-0 (0PTS)
Historique102-40-14 (0.654%)
Apparitions séries éliminatoires 2
Historique séries éliminatoires (W-L)12-10
Stanley Cup0


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
1Seth Griffith0XX100.007043756379605270607267566468750406202921,000,000$
2Gabriel Dumont0X100.005045756178605363606665626374790406003221,000,000$
3Jayson Megna (C)0X100.007744796083625062726761636170770406003211,000,000$
4Brendan Perlini0X100.007648775787644462466368616456670405902611,800,000$
5Michael Sgarbossa (A)0X100.00594077627960396183666460626271040590301875,000$
6Mitchell Chaffee (R) (A)0X100.00994575598460456240646658635164040590241925,000$
7Ben McCartney (R)0X100.00995174617960495946646360625164040580213850,000$
8Cole Koepke (R)0X100.00504375607860475940636362625262040570241850,000$
9Dylan McLaughlin0X100.00504275598060336260686162615363040570271800,000$
10Bobby McMann (R)0XXX100.00504675548460435840626462625363040560264812,500$
11Cole Fonstad (R)0X100.00503975597760235740636062605161040550222850,000$
12Luke Johnson0X100.00504575587960105760645862595766040540282850,000$
13Dean Kukan0X100.007143896482785872206665726356650406402911,500,000$
14Jake Christiansen0X100.00734276608060547420676664635161040610231700,000$
15Artemi Kniazev (R)0X100.00704075597860507020656263615161040590213850,000$
16Reilly Walsh (R)0X100.00504175588060557220686268615262040590231925,000$
17Yanni Kaldis (R)0X100.00504275578060317220676268615463040580272750,000$
18Nicklaus Perbix (R)0X100.00504575568660107420686368625161040570241850,000$
Rayé
1Eduards Tralmaks (R)0XXX100.00504775538860315840636262615161040550252750,000$
2Taylor Ward (R)0XXX100.00504775548660106040666062605161040550241750,000$
3Ben Tardif (R)0XXX100.00504475538160465340615762595563040540222750,000$
4Bobby Trivigno (R)0XXX100.00503575607260105340615762595060040530232890,000$
5Fedor Gordeev (R)0X100.00505575439760476320605768595161040570231750,000$
6Max Martin (R)0X100.00504075557960106420615668585161040550231850,000$
7Yan Kuznetsov (R)0X100.00504975478960106320595568585060040540203850,000$
MOYENNE D’ÉQUIPE100.0060447657826136633965626361556404057
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
1Kaapo Kahkonen100.0080817886848482858482837169040790
2Troy Grosenick100.0068666384737171737270718475040700
Rayé
1Keith Petruzzelli (R)100.0051595688555553565552546867040580
2Tommy Nappier (R)100.0049636087525351535349517068040570
MOYENNE D’ÉQUIPE100.006267648666666467666365737004066
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Adam Oates75757575757575CAN608500,000$


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 restantPlafond salarial 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 10Link
Artemi KniazevMarlies (TOR)D211/4/2001Yes178 Lbs5 ft11NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Ben McCartneyMarlies (TOR)LW217/13/2001Yes182 Lbs6 ft0NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Ben TardifMarlies (TOR)C/LW/RW221/24/2000Yes195 Lbs5 ft10NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Bobby McMann (contrat à 1 volet)Marlies (TOR)C/LW/RW266/15/1996Yes203 Lbs6 ft1NoNoNo4Pro & Farm812,500$803,902$812,500$803,902$0$0$No812,500$812,500$812,500$Lien
Bobby TrivignoMarlies (TOR)C/LW/RW231/19/1999Yes160 Lbs5 ft7NoNoNo2Pro & Farm890,000$880,582$890,000$880,582$0$0$No890,000$Lien
Brendan PerliniMarlies (TOR)LW264/27/1996No211 Lbs6 ft3NoNoNo1Pro & Farm1,800,000$1,780,952$1,800,000$1,780,952$0$0$NoLien
Cole FonstadMarlies (TOR)LW224/24/2000Yes176 Lbs5 ft10NoNoNo2Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$Lien
Cole KoepkeMarlies (TOR)LW245/17/1998Yes172 Lbs6 ft1NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Dean Kukan (contrat à 1 volet)Marlies (TOR)D297/8/1993No190 Lbs6 ft2NoNoNo1Pro & Farm1,500,000$1,484,127$1,500,000$1,484,127$375,000$371,032$NoLien
Dylan McLaughlinMarlies (TOR)C276/5/1995No187 Lbs5 ft11NoNoNo1Pro & Farm800,000$791,534$800,000$791,534$0$0$NoLien
Eduards TralmaksMarlies (TOR)C/LW/RW252/17/1997Yes209 Lbs6 ft4NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Fedor GordeevMarlies (TOR)D231/27/1999Yes240 Lbs6 ft7NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Gabriel DumontMarlies (TOR)C3210/6/1990No180 Lbs5 ft10NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Jake ChristiansenMarlies (TOR)D239/12/1999No186 Lbs6 ft0NoNoNo1Pro & Farm700,000$692,593$700,000$692,593$0$0$NoLien
Jayson MegnaMarlies (TOR)C322/1/1990No195 Lbs6 ft1NoNoNo1Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$NoLien
Kaapo Kahkonen (contrat à 1 volet)Marlies (TOR)G268/16/1996No216 Lbs6 ft2NoNoNo2Pro & Farm2,300,000$2,275,661$2,300,000$2,275,661$1,175,000$1,162,566$No2,300,000$Lien
Keith PetruzzelliMarlies (TOR)G237/1/1999Yes185 Lbs6 ft5NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Luke JohnsonMarlies (TOR)C289/19/1994No179 Lbs6 ft0NoNoNo2Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$Lien
Max MartinMarlies (TOR)D236/25/1999Yes181 Lbs6 ft0NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Michael SgarbossaMarlies (TOR)C307/25/1992No179 Lbs6 ft0NoNoNo1Pro & Farm875,000$865,741$875,000$865,741$0$0$NoLien
Mitchell ChaffeeMarlies (TOR)RW241/26/1998Yes201 Lbs6 ft1NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Nicklaus PerbixMarlies (TOR)D246/15/1998Yes200 Lbs6 ft4NoNoNo1Pro & Farm850,000$841,005$850,000$841,005$0$0$NoLien
Reilly WalshMarlies (TOR)D234/21/1999Yes185 Lbs6 ft0NoNoNo1Pro & Farm925,000$915,212$925,000$915,212$0$0$NoLien
Seth GriffithMarlies (TOR)C/RW291/4/1993No190 Lbs5 ft9NoNoNo2Pro & Farm1,000,000$989,418$1,000,000$989,418$0$0$No1,000,000$Lien
Taylor WardMarlies (TOR)C/LW/RW243/31/1998Yes207 Lbs6 ft2NoNoNo1Pro & Farm750,000$742,063$750,000$742,063$0$0$NoLien
Tommy NappierMarlies (TOR)G247/1/1998Yes220 Lbs6 ft3NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Troy Grosenick (contrat à 1 volet)Marlies (TOR)G337/1/1989No185 Lbs6 ft1NoNoNo3Pro & Farm1,250,000$1,236,772$1,250,000$1,236,772$125,000$123,677$No1,250,000$1,250,000$Lien
Yan KuznetsovMarlies (TOR)D203/9/2002Yes215 Lbs6 ft4NoNoNo3Pro & Farm850,000$841,005$850,000$841,005$0$0$No850,000$850,000$Lien
Yanni KaldisMarlies (TOR)D279/30/1995Yes187 Lbs5 ft11NoNoNo2Pro & Farm750,000$742,063$750,000$742,063$0$0$No750,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2925.31193 Lbs6 ft11.76959,569$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brendan PerliniMichael SgarbossaSeth Griffith35023
2Dylan McLaughlinJayson MegnaMitchell Chaffee30023
3Ben McCartneyGabriel DumontCole Koepke30023
4Bobby McMannLuke JohnsonCole Fonstad5032
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dean KukanReilly Walsh40032
2Jake ChristiansenNicklaus Perbix35032
3Yanni KaldisArtemi Kniazev25032
4Dean KukanReilly Walsh0032
Attaque en svantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Brendan PerliniMichael SgarbossaSeth Griffith60014
2Bobby McMannJayson MegnaMitchell Chaffee40014
Défense en svantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dean KukanJake Christiansen60023
2Reilly WalshArtemi Kniazev40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Jayson MegnaDylan McLaughlin50050
2Gabriel DumontCole Koepke50050
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Dean KukanReilly Walsh60050
2Yanni KaldisNicklaus Perbix40050
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Jayson Megna60050Dean KukanReilly Walsh60050
2Gabriel Dumont40050Yanni KaldisNicklaus Perbix40050
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Dylan McLaughlinBen McCartney50032
2Luke JohnsonCole Fonstad50032
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jake ChristiansenNicklaus Perbix50032
2Yanni KaldisArtemi Kniazev50032
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Brendan PerliniMichael SgarbossaSeth GriffithDean KukanReilly Walsh
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Dylan McLaughlinJayson MegnaGabriel DumontDean KukanJake Christiansen
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Michael Sgarbossa, Jayson Megna, Ben McCartneyBrendan Perlini, Mitchell ChaffeeBobby McMann
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Dean Kukan, Jake Christiansen, Yanni KaldisNicklaus PerbixJake Christiansen, Artemi Kniazev
Tirs de pénalité
Dean Kukan, Brendan Perlini, Seth Griffith, Jake Christiansen, Nicklaus Perbix
Gardien
#1 : Kaapo Kahkonen, #2 : Troy Grosenick
Lignes d’attaque personnalisées en prolongation
Michael Sgarbossa, Brendan Perlini, Jayson Megna, Seth Griffith, Gabriel Dumont, Mitchell Chaffee, Mitchell Chaffee, , , ,
Lignes de défense personnalisées en prolongation
Dean Kukan, Reilly Walsh, Jake Christiansen, Nicklaus Perbix, Artemi Kniazev


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
Total00000000000000000000000000000000000.000000000000000000000000.00%000.00%0000.00%000.00%000.00%000000

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
00N/A0000000000
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
000000000
Matchs extérieurs
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 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
6 - 2022-09-147Marlies-Rocket-
7 - 2022-09-1515Bears-Marlies-
9 - 2022-09-1730Senators-Marlies-
11 - 2022-09-1940Roadrunners-Marlies-
14 - 2022-09-2261Stars-Marlies-
16 - 2022-09-2478Marlies-Moose-
18 - 2022-09-2696Marlies-Silver Knights-
21 - 2022-09-29119Marlies-Barracuda-
23 - 2022-10-01130Marlies-Reign-
24 - 2022-10-02142Marlies-Gulls-
27 - 2022-10-05159Phantoms-Marlies-
30 - 2022-10-08180Bruins-Marlies-
31 - 2022-10-09191Marlies-Wolves-
33 - 2022-10-11201Silver Knights-Marlies-
36 - 2022-10-14221Penguins-Marlies-
37 - 2022-10-15230Canucks-Marlies-
40 - 2022-10-18251Marlies-Penguins-
42 - 2022-10-20264Comets-Marlies-
44 - 2022-10-22277Americans-Marlies-
46 - 2022-10-24295Islanders-Marlies-
48 - 2022-10-26309Marlies-Comets-
50 - 2022-10-28321Marlies-Wild-
51 - 2022-10-29335Marlies-Penguins-
53 - 2022-10-31348Marlies-Griffins-
55 - 2022-11-02363Barracuda-Marlies-
58 - 2022-11-05385Marlies-Crunch-
61 - 2022-11-08409Marlies-Stars-
63 - 2022-11-10420Reign-Marlies-
65 - 2022-11-12438Heat-Marlies-
68 - 2022-11-15454Gulls-Marlies-
70 - 2022-11-17476Marlies-Wolf Pack-
72 - 2022-11-19491Marlies-Bears-
75 - 2022-11-22513Crunch-Marlies-
77 - 2022-11-24525Phantoms-Marlies-
82 - 2022-11-29553Marlies-Thunderbirds-
84 - 2022-12-01572Marlies-Roadrunners-
86 - 2022-12-03582Marlies-Eagles-
89 - 2022-12-06602Thunderbirds-Marlies-
91 - 2022-12-08615Firebirds-Marlies-
93 - 2022-12-10630Griffins-Marlies-
94 - 2022-12-11643Marlies-Phantoms-
97 - 2022-12-14658Admirals-Marlies-
98 - 2022-12-15666Marlies-Griffins-
100 - 2022-12-17683Marlies-Bruins-
103 - 2022-12-20706Checkers-Marlies-
105 - 2022-12-22723Moose-Marlies-
107 - 2022-12-24737Marlies-Rocket-
109 - 2022-12-26752Islanders-Marlies-
111 - 2022-12-28767Wolf Pack-Marlies-
113 - 2022-12-30782Senators-Marlies-
115 - 2023-01-01800Bears-Marlies-
118 - 2023-01-04806Bruins-Marlies-
127 - 2023-01-13829Marlies-Monsters-
128 - 2023-01-14840Monsters-Marlies-
132 - 2023-01-18864IceHogs-Marlies-
135 - 2023-01-21888Rocket-Marlies-
136 - 2023-01-22899Marlies-IceHogs-
138 - 2023-01-24912Marlies-Americans-
141 - 2023-01-27931Wild-Marlies-
143 - 2023-01-29952Marlies-Firebirds-
146 - 2023-02-01969Marlies-Condors-
147 - 2023-02-02979Marlies-Heat-
149 - 2023-02-04994Marlies-Canucks-
152 - 2023-02-071015Marlies-Comets-
156 - 2023-02-111043Condors-Marlies-
158 - 2023-02-131061Americans-Marlies-
160 - 2023-02-151077Eagles-Marlies-
162 - 2023-02-171092Wolves-Marlies-
163 - 2023-02-181102Marlies-Senators-
166 - 2023-02-211127Marlies-Islanders-
168 - 2023-02-231140Marlies-Checkers-
170 - 2023-02-251161Marlies-Wolves-
171 - 2023-02-261167Marlies-Admirals-
174 - 2023-03-011186Checkers-Marlies-
177 - 2023-03-041210Marlies-Senators-
178 - 2023-03-051223Griffins-Marlies-
180 - 2023-03-071230Monsters-Marlies-
182 - 2023-03-091246Marlies-Bruins-
184 - 2023-03-111263Rocket-Marlies-
186 - 2023-03-131279Marlies-Checkers-
187 - 2023-03-141289Marlies-Crunch-
189 - 2023-03-161304Marlies-Wolf Pack-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance0.00%0.00%
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
41 0 - 0.00%0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
23,244$ 2,196,500$ 2,196,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
11,622$ 23,244$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 187 11,622$ 2,173,314$




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
Saison régulière
11824520026452201734741241101122124873741219015239686101132203655852750788611317310201089104951244980229420691083431.48%1374269.34%01024187854.53%930166455.89%613105658.05%1806103215767811592759
11824520026452201734741241101122124873741219015239686101132203655852750788611317310201089104951244980229420691083431.48%1374269.34%01024187854.53%930166455.89%613105658.05%1806103215767811592759
Total Saison régulière164904004128104403469482482202244248174748242180210461921722022644073011704141001561722263462040217820981024898160458841382166831.48%2748469.34%02048375654.53%1860332855.89%1226211258.05%361220643153156231841518
Séries éliminatoires
1111650000028235642000001477523000001416-212284977134176140713912613483281174126713430.77%18572.22%014825158.96%13224553.88%7513455.97%235131216106219103
1111650000028235642000001477523000001416-212284977134176140713912613483281174126713430.77%18572.22%014825158.96%13224553.88%7513455.97%235131216106219103
Total Séries éliminatoires221210000005646101284000002814141046000002832-424569815426834122814278252268166562348253426830.77%361072.22%029650258.96%26449053.88%15026855.97%470262432213439206