Connexion

Marlies
GP: 17 | W: 6 | L: 10 | OTL: 1 | P: 13
GF: 31 | GA: 50 | PP%: 9.41% | PK%: 88.54%
DG: Danick Lépine | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #198 vs Condors
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Centre de jeu
Marlies
6-10-1, 13pts
3
FINAL
1 Monsters
8-7-2, 18pts
Team Stats
W2SéquenceL3
4-5-0Fiche domicile3-4-2
2-5-1Fiche domicile5-3-0
4-5-1Derniers 10 matchs5-4-1
1.82Buts par match 2.88
2.94Buts contre par match 2.47
9.41%Pourcentage en avantage numérique15.00%
88.54%Pourcentage en désavantage numérique87.64%
Condors
8-7-3, 19pts
1
FINAL
2 Marlies
6-10-1, 13pts
Team Stats
OTL1SéquenceW2
4-4-0Fiche domicile4-5-0
4-3-3Fiche domicile2-5-1
3-5-2Derniers 10 matchs4-5-1
2.50Buts par match 1.82
2.78Buts contre par match 2.94
12.50%Pourcentage en avantage numérique9.41%
90.91%Pourcentage en désavantage numérique88.54%
Marlies
6-10-1, 13pts
Jour 35
Condors
8-7-3, 19pts
Statistiques d’équipe
W2SéquenceOTL1
4-5-0Fiche domicile4-4-0
2-5-1Fiche visiteur4-3-3
4-5-110 derniers matchs3-5-2
1.82Buts par match 2.50
2.94Buts contre par match 2.50
9.41%Pourcentage en avantage numérique12.50%
88.54%Pourcentage en désavantage numérique90.91%
Sound Tigers
8-5-5, 21pts
Jour 36
Marlies
6-10-1, 13pts
Statistiques d’équipe
W2SéquenceW2
4-2-2Fiche domicile4-5-0
4-3-3Fiche visiteur2-5-1
6-2-210 derniers matchs4-5-1
2.44Buts par match 1.82
2.50Buts contre par match 1.82
9.57%Pourcentage en avantage numérique9.41%
87.50%Pourcentage en désavantage numérique88.54%
Marlies
6-10-1, 13pts
Jour 38
Wolf Pack
9-7-1, 19pts
Statistiques d’équipe
W2SéquenceW2
4-5-0Fiche domicile5-4-0
2-5-1Fiche visiteur4-3-1
4-5-110 derniers matchs5-4-1
1.82Buts par match 2.29
2.94Buts contre par match 2.29
9.41%Pourcentage en avantage numérique9.73%
88.54%Pourcentage en désavantage numérique80.68%
Meneurs d'équipe
Buts
Andrew Copp
8
Passes
Andrew Cogliano
9
Points
Andrew Copp
12
Plus/Moins
Ryan Merkley
2
Victoires
Alex Nedeljkovic
6
Pourcentage d’arrêts
Alex Nedeljkovic
0.848

Statistiques d’équipe
Buts pour
31
1.82 GFG
Tirs pour
271
15.94 Avg
Pourcentage en avantage numérique
9.4%
8 GF
Début de zone offensive
39.0%
Buts contre
50
2.94 GAA
Tirs contre
315
18.53 Avg
Pourcentage en désavantage numérique
88.5%%
11 GA
Début de la zone défensive
39.5%
Informations de l'équipe

Directeur généralDanick Lépine
EntraîneurJoel Quenneville
DivisionDivision 1
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance0
Billets de saison300


Informations de la formation

Équipe Pro25
Équipe Mineure19
Limite contact 44 / 60
Espoirs16


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
1Andrew Cogliano0X100.006942838963639459436064827292936950003611,250,000$
2Arthur Kaliyev0XX100.006943927972618575257274575359607250002211,066,667$
3Cal Clutterbuck0X100.0099478277766271613061628045858969500N03511,750,000$
4Michael Eyssimont (R)0XX100.0085796869716378683765596925494966500N0261750,000$
5Adam Beckman (R)0X100.00716389686378836250526862654545665000221925,000$
6Gabriel Fortier (R)0X100.00706287666285925750545661534545625000231880,000$
7Brett Howden0XX100.00855672807565685966616075256565665000251900,000$
8Kiefer Sherwood0XX100.0097897472726688695665736625585972500N0281750,000$
9Derek Stepan0XX100.006342967871548361775858686182836350003321,350,000$
10Ryan Suzuki (R)0X100.00746789776760606278586364604444655000221894,167$
11Mackenzie MacEachern0XX100.0077728971726565665063627059585867500N0291750,000$
12Andrew Copp0XXX100.006352908376789472887960806373767150002922,280,000$
13Brendan Smith0X100.008277717676687061254747832576776250003411,100,000$
14Jan Rutta0X100.007844847775728360254948892565686350003311,300,000$
15Joel Hanley0X100.00736683727058565925474771256162585000322750,000$
16Ryan Merkley0X100.006461707661758152254840573847475350002311,163,333$
17Andrew Nielsen0X100.00828380628337374225283965375555495000263750,000$
18Emil Andrae (R)0X100.00686282656258595825495360504444585000213925,000$
Rayé
1Samuel Helenius (R)0X100.00777973667955575063494562434444545000202902,500$
2Justin Sourdif (R)0X100.00686381656365675873585460514444595000213902,500$
3Alex Vlasic0X86.49817986757956585125464065384545545000222916,667$
4Jordan Oesterle0X86.667153887767686657255248692566666050003111,350,000$
MOYENNE D’ÉQUIPE98.7376638274716473604556556944596063500
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
1Alex Nedeljkovic0100.006167657069526961656075565763500N02723,000,000$
2Collin Delia0100.006055548065547261656075494962500N0292750,000$
Rayé
1Cayden Primeau0100.0056546880596150595856304545575000243890,000$
MOYENNE D’ÉQUIPE100.005959627764566460635960505061500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
Joel Quenneville77788074948240CAN6722,500,000$


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
1Andrew CoppMarlies (TOR)C/LW/RW178412-82074930102326.67%340623.912244680113752165.54%41500000.5900000201
2Arthur KaliyevMarlies (TOR)LW/RW173710-4604162691611.54%332919.380226670001511045.00%2000000.6100000200
3Andrew CoglianoMarlies (TOR)LW17099-10001026252260%233719.840448690110820031.25%1600000.5300000011
4Cal ClutterbuckMarlies (TOR)RW17448-920036202261618.18%329617.462245680000431133.93%5600000.5400000112
5Kiefer SherwoodMarlies (TOR)LW/RW17347-325538212691611.54%028716.900009680000110047.62%2100000.4900001021
6Derek StepanMarlies (TOR)C/RW13347-420023115227.27%320515.78112254000001059.07%21500000.6800000001
7Brendan SmithMarlies (TOR)D17516-1130103017194926.32%1338522.653031064101368100%000000.3100101011
8Mackenzie MacEachernMarlies (TOR)LW/RW17145-280323186185.56%222113.010000000000000%700000.4500000000
9Michael EyssimontMarlies (TOR)C/RW17134-11402223198195.26%026915.84000170000430039.56%9100000.3000000000
10Ryan SuzukiMarlies (TOR)C17134-360713104610.00%31488.7300001000000058.33%9600000.5400000000
11Brett HowdenMarlies (TOR)C/LW17213-180738255138.00%225414.96000219000090160.31%19400000.2400000010
12Jordan OesterleMarlies (TOR)D15033-316018117350%928018.73022754000051000%000000.2100000000
13Jan RuttaMarlies (TOR)D17022-122202418108100%2039022.96000767000068000%100000.1000000000
14Adam BeckmanMarlies (TOR)LW17000-4804541100%01227.20000020000110066.67%30000000000000
15Gabriel FortierMarlies (TOR)LW17000-320103210%0583.45000216000020046.67%150000000000000
16Alex VlasicMarlies (TOR)D16000-11552431030%825916.23000017000022000%00000000100000
17Joel HanleyMarlies (TOR)D17000-3200181710230%1434620.38000663000065000%00000000000000
18Ryan MerkleyMarlies (TOR)D2000200420000%23618.240000300004000%00000000000000
19Andrew NielsenMarlies (TOR)D1000020000000%01515.950000100002000%00000000000000
20Justin SourdifMarlies (TOR)C4000-100001000%071.790001200000000%10000000000000
21Emil AndraeMarlies (TOR)D1700001401144010%627015.88000012000031000%00000000000000
Statistiques d’équipe totales ou en moyenne306314980-81220202683292718419711.44%93492816.11813217073312376476357.34%115100000.3200202567
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
1Alex NedeljkovicMarlies (TOR)166800.8483.02794214026401000160001
2Collin DeliaMarlies (TOR)70210.8042.6222900105100000116000
Statistiques d’équipe totales ou en moyenne2361010.8412.931023215031501001716001


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 Ballotage forcé Waiver Possible 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 10Lien
Adam BeckmanMarlies (TOR)LW222001-05-10Yes168 Lbs6 ft1NoNoNoNo1Pro & Farm925,000$728,065$925,000$728,065$0$0$NoLien
Alex NedeljkovicMarlies (TOR)G271996-01-07No189 Lbs6 ft0YesNoNoNo2Pro & Farm3,000,000$2,361,290$3,000,000$2,361,290$0$0$No3,000,000$Lien
Alex Vlasic (sur la masse salariale)Marlies (TOR)D222001-06-05No200 Lbs6 ft6NoNoNoNo2Pro & Farm916,667$721,506$916,667$721,506$0$0$Yes916,667$Lien
Andrew CoglianoMarlies (TOR)LW361987-06-13No175 Lbs5 ft10NoNoNoNo1Pro & Farm1,250,000$983,871$1,250,000$983,871$0$0$NoLien
Andrew CoppMarlies (TOR)C/LW/RW291994-07-07No206 Lbs6 ft1NoNoNoNo2Pro & Farm2,280,000$1,794,581$2,280,000$1,794,581$0$0$No2,280,000$Lien
Andrew NielsenMarlies (TOR)D261996-11-13No224 Lbs6 ft4NoNoNoNo3Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$750,000$Lien
Arthur KaliyevMarlies (TOR)LW/RW222001-06-25No190 Lbs6 ft2NoNoNoNo1Pro & Farm1,066,667$839,570$925,000$728,065$0$0$NoLien
Brendan SmithMarlies (TOR)D341989-02-08No200 Lbs6 ft2NoNoNoNo1Pro & Farm1,100,000$865,806$1,100,000$865,806$0$0$NoLien
Brett HowdenMarlies (TOR)C/LW251998-03-28No197 Lbs6 ft3NoNoNoNo1Pro & Farm900,000$708,387$900,000$708,387$0$0$NoLien
Cal ClutterbuckMarlies (TOR)RW351987-11-17No216 Lbs5 ft11YesNoNoNo1Pro & Farm1,750,000$1,377,419$1,750,000$1,377,419$0$0$NoLien
Cayden PrimeauMarlies (TOR)G241999-08-11No200 Lbs6 ft3NoNoNoNo3Pro & Farm890,000$700,516$890,000$700,516$0$0$No890,000$890,000$Lien
Collin DeliaMarlies (TOR)G291994-06-19No208 Lbs6 ft2YesNoNoNo2Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$Lien
Derek StepanMarlies (TOR)C/RW331990-06-18No196 Lbs6 ft0NoNoNoNo2Pro & Farm1,350,000$1,062,581$1,350,000$1,062,581$0$0$No1,350,000$Lien
Emil AndraeMarlies (TOR)D212002-02-23Yes176 Lbs5 ft9NoNoNoNo3Pro & Farm925,000$728,065$925,000$728,065$0$0$No925,000$925,000$
Gabriel FortierMarlies (TOR)LW232000-02-06Yes170 Lbs5 ft10NoNoNoNo1Pro & Farm880,000$692,645$880,000$692,645$0$0$NoLien
Jan RuttaMarlies (TOR)D331990-07-29No204 Lbs6 ft2NoNoNoNo1Pro & Farm1,300,000$1,023,226$1,300,000$1,023,226$0$0$NoLien
Joel HanleyMarlies (TOR)D321991-06-08No190 Lbs5 ft11NoNoNoNo2Pro & Farm750,000$590,323$750,000$590,323$0$0$No750,000$Lien
Jordan Oesterle (sur la masse salariale)Marlies (TOR)D311992-06-25No182 Lbs6 ft0NoNoNoNo1Pro & Farm1,350,000$1,062,581$1,350,000$1,062,581$0$0$YesLien
Justin SourdifMarlies (TOR)C212002-03-24Yes173 Lbs5 ft11NoNoNoNo3Pro & Farm902,500$710,355$902,500$710,355$0$0$No902,500$902,500$
Kiefer SherwoodMarlies (TOR)LW/RW281995-03-31No194 Lbs6 ft0YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Mackenzie MacEachernMarlies (TOR)LW/RW291994-03-08No190 Lbs6 ft2YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Michael EyssimontMarlies (TOR)C/RW261996-09-09Yes192 Lbs6 ft0YesNoNoNo1Pro & Farm750,000$590,323$750,000$590,323$0$0$NoLien
Ryan MerkleyMarlies (TOR)D232000-08-14No168 Lbs5 ft11NoNoNoNo1Pro & Farm1,163,333$915,656$1,163,333$915,656$0$0$NoLien
Ryan SuzukiMarlies (TOR)C222001-05-28Yes180 Lbs6 ft0NoNoNoNo1Pro & Farm894,167$703,796$894,167$703,796$0$0$NoLien
Samuel HeleniusMarlies (TOR)C202002-11-26Yes201 Lbs6 ft6NoNoNoNo2Pro & Farm902,500$710,355$902,500$710,355$0$0$No902,500$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2526.92192 Lbs6 ft11.601,129,833$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Andrew CoglianoAndrew CoppCal Clutterbuck35122
2Kiefer SherwoodDerek StepanArthur Kaliyev30122
3Mackenzie MacEachernBrett HowdenMichael Eyssimont25122
4Adam BeckmanRyan SuzukiAndrew Copp10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaBrendan Smith35122
2Joel HanleyEmil Andrae30122
3Ryan MerkleyAndrew Nielsen25122
4Jan RuttaBrendan Smith10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Andrew CoglianoAndrew CoppCal Clutterbuck60122
2Kiefer SherwoodDerek StepanArthur Kaliyev40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaBrendan Smith60122
2Joel HanleyEmil Andrae40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Andrew CoppAndrew Cogliano60122
2Cal ClutterbuckKiefer Sherwood40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaBrendan Smith60122
2Joel HanleyEmil Andrae40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Andrew Copp60122Jan RuttaBrendan Smith60122
2Andrew Cogliano40122Joel HanleyEmil Andrae40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Andrew CoppAndrew Cogliano60122
2Cal ClutterbuckKiefer Sherwood40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaBrendan Smith60122
2Joel HanleyEmil Andrae40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Andrew CoglianoAndrew CoppCal ClutterbuckJan RuttaBrendan Smith
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Andrew CoglianoAndrew CoppCal ClutterbuckJan RuttaBrendan Smith
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Gabriel Fortier, Brett Howden, Michael EyssimontGabriel Fortier, Brett HowdenMichael Eyssimont
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Ryan Merkley, Andrew Nielsen, Joel HanleyRyan MerkleyAndrew Nielsen, Joel Hanley
Tirs de pénalité
Andrew Copp, Andrew Cogliano, Cal Clutterbuck, Kiefer Sherwood, Arthur Kaliyev
Gardien
#1 : Alex Nedeljkovic, #2 : Collin Delia
Lignes d’attaque personnalisées en prolongation
Andrew Copp, Andrew Cogliano, Cal Clutterbuck, Kiefer Sherwood, Arthur Kaliyev, Derek Stepan, Derek Stepan, Brett Howden, Michael Eyssimont, Mackenzie MacEachern, Ryan Suzuki
Lignes de défense personnalisées en prolongation
Jan Rutta, Brendan Smith, Joel Hanley, Emil Andrae, Ryan Merkley


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
167s11000000413000000000001100000041321.000471100108121108595901191016124125.00%80100.00%026044957.91%24745454.41%15324761.94%398265410132215105
2Bruins30300000410-61010000014-32020000036-300.000461000108121568595901561326531915.26%12283.33%026044957.91%24745454.41%15324761.94%398265410132215105
3Condors10001000211100010002110000000000021.0002350010812123859590112412145120.00%6183.33%026044957.91%24745454.41%15324761.94%398265410132215105
4Crunch2110000034-1110000003211010000002-220.5003580010812133859590135820311119.09%100100.00%026044957.91%24745454.41%15324761.94%398265410132215105
5Griffins20100100610-41010000047-31000010023-110.250681400108121308595901291328239222.22%12375.00%026044957.91%24745454.41%15324761.94%398265410132215105
6Monsters11000000312000000000001100000031221.00034700108121985959012371212300.00%60100.00%026044957.91%24745454.41%15324761.94%398265410132215105
7Moose2020000017-62020000017-60000000000000.00012300108121218595901441120415120.00%10370.00%026044957.91%24745454.41%15324761.94%398265410132215105
8Penguins1010000006-61010000006-60000000000000.000000001081212485959011861719600.00%6266.67%026044957.91%24745454.41%15324761.94%398265410132215105
9Rocket32100000770220000006241010000015-440.6677121901108121548595901611850451915.26%180100.00%126044957.91%24745454.41%15324761.94%398265410132215105
10Sound Tigers1010000013-2000000000001010000013-200.000123001081211185959011832118400.00%80100.00%026044957.91%24745454.41%15324761.94%398265410132215105
Total17510011003150-19935010001729-12825001001421-7130.382314980011081212718595901315932222688589.41%961188.54%126044957.91%24745454.41%15324761.94%398265410132215105
_Since Last GM Reset17510011003150-19935010001729-12825001001421-7130.382314980011081212718595901315932222688589.41%961188.54%126044957.91%24745454.41%15324761.94%398265410132215105
_Vs Conference1156000002129-8532000001014-4624000001115-4100.455213455011081211868595901212621411726246.45%60493.33%126044957.91%24745454.41%15324761.94%398265410132215105
_Vs Division1145000002432-8531000001415-1614000001017-780.364243862011081211838595901200621401646269.68%60591.67%126044957.91%24745454.41%15324761.94%398265410132215105

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
1713W23149802713159322226801
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
1751011003150
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
93510001729
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
82501001421
Derniers 10 matchs
WLOTWOTL SOWSOL
450100
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
8589.41%961188.54%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
8595901108121
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
26044957.91%24745454.41%15324761.94%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
398265410132215105


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
313Moose3Marlies1BLSommaire du match
725Marlies467s1AWSommaire du match
833Bruins4Marlies1BLSommaire du match
941Marlies2Bruins3ALSommaire du match
1155Moose4Marlies0BLSommaire du match
1371Crunch2Marlies3BWSommaire du match
1579Marlies1Bruins3ALSommaire du match
1892Griffins7Marlies4BLSommaire du match
19104Marlies1Rocket5ALSommaire du match
21115Rocket0Marlies3BWSommaire du match
22124Marlies0Crunch2ALSommaire du match
24137Rocket2Marlies3BWSommaire du match
26146Marlies1Sound Tigers3ALSommaire du match
27154Marlies2Griffins3ALXSommaire du match
29164Penguins6Marlies0BLSommaire du match
30171Marlies3Monsters1AWSommaire du match
32186Condors1Marlies2BWXSommaire du match
35198Marlies-Condors-
36207Sound Tigers-Marlies-
38220Marlies-Wolf Pack-
40230Bruins-Marlies-
42242Wolf Pack-Marlies-
44253Marlies-Griffins-
45267Griffins-Marlies-
47275Marlies-Phantoms-
49289Crunch-Marlies-
50295Marlies-Rocket-
52311Stars-Marlies-
53318Marlies-IceHogs-
56331Marlies-67s-
5734267s-Marlies-
61355Rocket-Marlies-
63367Marlies-Eagles-
65378Monarchs-Marlies-
67389Marlies-Moose-
68397Monsters-Marlies-
71413Marlies-Stars-
72419Marlies-67s-
73429Gulls-Marlies-
76444Marlies-Thunderbird-
77451Thunderbird-Marlies-
78464Eagles-Marlies-
81476Marlies-Monarchs-
82486Crunch-Marlies-
84499Marlies-Penguins-
87510Penguins-Marlies-
89522Marlies-Wolf Pack-
91532Bruins-Marlies-
92541Marlies-Condors-
94554Marlies-Rocket-
95560Moose-Marlies-
98577Marlies-Monsters-
99582Wolf Pack-Marlies-
101594Marlies-Heat-
102603Monsters-Marlies-
104619Marlies-Griffins-
106626Heat-Marlies-
109642Griffins-Marlies-
111655Marlies-Bruins-
112665Sound Tigers-Marlies-
114670Marlies-Wolves-
116686Barracuda-Marlies-
118700Marlies-Bruins-
119708Phantoms-Marlies-
121719Marlies-Sound Tigers-
122728Marlies-Monsters-
124736Wolves-Marlies-
125750Marlies-Gulls-
12775867s-Marlies-
130774Phantoms-Marlies-
131779Marlies-Phantoms-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
132790Marlies-Penguins-
134801Moose-Marlies-
136817IceHogs-Marlies-
137818Marlies-Gulls-
140831Marlies-Crunch-
143843Marlies-Sound Tigers-
14585267s-Marlies-
147867IceHogs-Marlies-
148875Marlies-Barracuda-
149880Marlies-Crunch-
154901Gulls-Marlies-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets3515
Assistance00
Assistance PCT0.00%0.00%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
27 0 - 0.00% 0$0$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
1,126,897$ 2,597,917$ 2,583,750$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
0$ 594,640$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 122 32,890$ 4,012,580$




Marlies Leaders statistiques des joueurs (saison régulière)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Marlies Leaders des statistiques des gardiens (saison régulière)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA

Marlies Statistiques de l'Équipe de Carrière

TotalDomicileVisiteur
Année GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff GP W L T OTW OTL SOW SOL GF GA Diff P G A TP SO EG GP1 GP2 GP3 GP4 SHF SH1 SP2 SP3 SP4 SHA SHB Pim Hit PPA PPG PP% PKA PK GA PK% PK GF W OF FO T OF FO OF FO% W DF FO T DF FO DF FO% W NT FO T NT FO NT FO% PZ DF PZ OF PZ NT PC DF PC OF PC NT

Marlies Leaders statistiques des joueurs (séries éliminatoires)

# Nom du joueur GP G A P +/- PIM HIT HTT SHT SHT% SB MP AMG PPG PPA PPP PPS PKG PKA PKP PKS GW GT FO% HT P/20 PSG PSS

Marlies Leaders des statistiques des gardiens (séries éliminatoires)

# Nom du gardien GP W L OTL PCT GAA MP PIM SO GA SA SAR A EG PS % PSA