Connexion

Utica Comets
GP: 24 | W: 21 | L: 3 | OTL: 0 | P: 42
GF: 94 | GA: 20 | PP%: 17.65% | PK%: 93.18%
DG: Jonathan Brock et Marc-Andre Marinier | Morale : 50 | Moyenne d’équipe : N/A
Prochains matchs #397 vs Charlotte Checkers
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Centre de jeu
Utica Comets
21-3-0, 42pts
3
FINAL
1 Belleville Senators
8-16-0, 16pts
Team Stats
W2SéquenceL4
11-1-0Fiche domicile3-9-0
10-2-0Fiche domicile5-7-0
9-1-0Derniers 10 matchs4-6-0
3.92Buts par match 2.25
0.83Buts contre par match 4.00
17.65%Pourcentage en avantage numérique12.50%
93.18%Pourcentage en désavantage numérique77.78%
Texas Stars
19-4-2, 40pts
1
FINAL
3 Utica Comets
21-3-0, 42pts
Team Stats
L1SéquenceW2
10-1-1Fiche domicile11-1-0
9-3-1Fiche domicile10-2-0
7-2-1Derniers 10 matchs9-1-0
3.32Buts par match 3.92
0.76Buts contre par match 0.83
14.58%Pourcentage en avantage numérique17.65%
94.74%Pourcentage en désavantage numérique93.18%
Charlotte Checkers
13-10-2, 28pts
Jour 59
Utica Comets
21-3-0, 42pts
Statistiques d’équipe
L2SéquenceW2
6-6-0Fiche domicile11-1-0
7-4-2Fiche visiteur10-2-0
4-5-110 derniers matchs9-1-0
2.40Buts par match 3.92
2.20Buts contre par match 3.92
14.63%Pourcentage en avantage numérique17.65%
88.57%Pourcentage en désavantage numérique93.18%
Utica Comets
21-3-0, 42pts
Jour 61
Charlotte Checkers
13-10-2, 28pts
Statistiques d’équipe
W2SéquenceL2
11-1-0Fiche domicile6-6-0
10-2-0Fiche visiteur7-4-2
9-1-010 derniers matchs4-5-1
3.92Buts par match 2.40
0.83Buts contre par match 2.40
17.65%Pourcentage en avantage numérique14.63%
93.18%Pourcentage en désavantage numérique88.57%
Bakersfield Condors
6-17-2, 14pts
Jour 63
Utica Comets
21-3-0, 42pts
Statistiques d’équipe
L2SéquenceW2
3-8-1Fiche domicile11-1-0
3-9-1Fiche visiteur10-2-0
2-8-010 derniers matchs9-1-0
2.12Buts par match 3.92
4.60Buts contre par match 3.92
0.00%Pourcentage en avantage numérique17.65%
68.75%Pourcentage en désavantage numérique93.18%
Meneurs d'équipe
Buts
Logan Shaw
18
Passes
Logan Shaw
23
Points
Logan Shaw
41
Plus/Moins
Logan Shaw
37
Victoires
Adam Scheel
15
Pourcentage d’arrêts
Adam Scheel
0.939

Statistiques d’équipe
Buts pour
94
3.92 GFG
Tirs pour
826
34.42 Avg
Pourcentage en avantage numérique
17.6%
9 GF
Début de zone offensive
47.2%
Buts contre
20
0.83 GAA
Tirs contre
313
13.04 Avg
Pourcentage en désavantage numérique
93.2%%
6 GA
Début de la zone défensive
30.4%
Informations de l'équipe

Directeur généralJonathan Brock et Marc-Andre Marinier
DivisionATLANTIC
ConférenceConference 1
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance1,708
Billets de saison300


Informations de la formation

Équipe Pro21
Équipe Mineure19
Limite contact 40 / 250
Espoirs41


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
# Nom du joueur C L R D CON CK FG DI SK ST EN DU PH FO PA SC DF PS EX LD PO MO OV TA SPÂgeContratSalaire
1Logan ShawXX100.007640856485958663706566646372774050003131,999,999$
2Hudson FaschingX100.0074389567858381645465666263697048500N0293995,000$
3Jonah Gadjovich (R)XX100.00797753608272746153596258606668674700251832,500$
4Spencer SmallmanX100.00684177597775815754555856596870475000283975,000$
5Anthony AngelloX100.00824468589169805760565559546870465000282775,000$
6Brian PinhoX100.00663795607585835868615759586971405000291775,000$
7Corey Andonovski (R)X100.00674366617674835762605556586567425000251925,000$
8James Malatesta (R)X100.00754167656884726455616263656166585000213862,500$
9Matthew Knies (R)X100.00785482738783756950706765686267715000212925,000$
10Ryder Rolston (R)X100.00633695587281715659545753566365565000222867,500$
11Kevin ConnautonX100.0072437159817383583057535646747634500N03441,999,999$
12Cameron GaunceX100.0067427058766777543055525745747638500N03441,999,999$
13Mark PysykX100.0068388855776866543053505645727450500N0321975,000$
14Dan RenoufX100.0067426959827582573058556147707235500N03041,999,999$
15Dillon HeatheringtonX100.0076417557897283563055545847697358500N02911,999,999$
16Mark FriedmanX100.0073407565698074633064596650697152500N02831,999,999$
17Nikolas BrouillardX100.00705258616472875830645456476971365000291925,000$
Rayé
1Dalton Smith (R)X100.00736253548268695356525155507274475000331775,000$
2Guillaume Brisebois (R)X100.00403540673580904020404040306668115000272775,000$
MOYENNE D’ÉQUIPE100.0070457361767779584658565853687146500
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
1Adam Scheel100.0061957482625960606050676573425000251925,000$
2Matej Machovsky100.0040908050404040404040402525114700311700,000$
Rayé
MOYENNE D’ÉQUIPE100.005193776651505050504554454927490
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire


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
1Logan ShawUtica Comets (NJD)C/RW24182341371402255130359913.85%558324.311458451013822079.91%45800001.4101000553
2Matthew KniesUtica Comets (NJD)LW24151631292003145105207914.29%445719.051126261126474068.66%20100021.3611000431
3Hudson FaschingUtica Comets (NJD)RW241692521801336125319012.80%147819.940227420000232066.67%9900001.0401000105
4Mark FriedmanUtica Comets (NJD)D2411617241003515299163.45%847419.750221637000039100%000000.7200000101
5Jonah GadjovichUtica Comets (NJD)LW/RW244121624401059227026495.71%443118.001123340001370084.21%1900000.7401101012
6Brian PinhoUtica Comets (NJD)C2461016172054358245110.34%348820.3701111420001371080.35%39700000.6500000111
7Kevin ConnautonUtica Comets (NJD)D242131527401045101671612.50%146019.19101841000160100%000000.6500200011
8Spencer SmallmanUtica Comets (NJD)RW2469151420121335163117.14%324310.1401123000003180.00%3500001.2301000201
9James MalatestaUtica Comets (NJD)LW2169152018041317512528.00%239818.981016230001221180.00%1000000.7511000211
10Anthony AngelloUtica Comets (NJD)RW22211131810033214012365.00%130013.66000000001140076.19%2100000.8700000010
11Stefan NoesenNew Jersey DevilsRW7571212208153151416.13%113519.30022312000272060.00%1000001.7800000111
12Dan RenoufUtica Comets (NJD)D21371012803051981015.79%535116.74213932011043100%000000.5700000011
13Corey AndonovskiUtica Comets (NJD)RW233710820126315339.68%024010.471121140000181072.41%2900000.8300000020
14Dillon HeatheringtonUtica Comets (NJD)D24279211004461461114.29%1244218.45011627011059100%000000.4100000011
15Nikolas BrouillardUtica Comets (NJD)D24088181803987290%437715.74000311000029000%000000.4200000001
16Cameron GaunceUtica Comets (NJD)D1805514801944360%430516.9500019000014000%000000.3300000100
17Mark PysykUtica Comets (NJD)D23145136010584512.50%625010.88011115000016000%000000.4000000100
18Ryder RolstonUtica Comets (NJD)RW1632520011265711.54%01046.5410122000000050.00%600000.9600000010
19Dalton SmithUtica Comets (NJD)LW1000200202120%02020.780000000012000%00000000000000
20Guillaume BriseboisUtica Comets (NJD)D1000200200000%01515.370000000001000%00000000000000
Statistiques d’équipe totales ou en moyenne393931752683352182046334182523161611.27%64656116.7091827934242351755920276.81%128500020.8226301191920
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
1Adam ScheelUtica Comets (NJD)1815300.9390.841078091524600000186200
2Matej MachovskyUtica Comets (NJD)66000.9250.82365025670000.8336618000
Statistiques d’équipe totales ou en moyenne2421300.9360.8314430112031300062424200


Astuces sur les filtres (anglais seulement)
PriorityTypeDescription
1| or  OR Logical "or" (Vertical bar). Filter the column for content that matches text from either side of the bar
2 &&  or  AND Logical "and". Filter the column for content that matches text from either side of the operator.
3/\d/Add any regex to the query to use in the query ("mig" flags can be included /\w/mig)
4< <= >= >Find alphabetical or numerical values less than or greater than or equal to the filtered query
5! or !=Not operator, or not exactly match. Filter the column with content that do not match the query. Include an equal (=), single (') or double quote (") to exactly not match a filter.
6" or =To exactly match the search query, add a quote, apostrophe or equal sign to the beginning and/or end of the query
7 -  or  to Find a range of values. Make sure there is a space before and after the dash (or the word "to")
8?Wildcard for a single, non-space character.
8*Wildcard for zero or more non-space characters.
9~Perform a fuzzy search (matches sequential characters) by adding a tilde to the beginning of the query
10textAny text entered in the filter will match text found within the column
Nom du joueur Nom de l’équipePOS Âge Date de naissance Pays Recrue Poids Taille Non-échange Disponible pour échange Acquis 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 restantPlafond salarial Plafond salarial restant Exclus du plafond salarial Salaire année 2Salaire année 3Salaire année 4Salaire année 5Salaire année 6Salaire année 7Salaire année 8Salaire année 9Salaire année 10Plafond salarial année 2Plafond salarial année 3Plafond salarial année 4Plafond salarial année 5Plafond salarial année 6Plafond salarial année 7Plafond salarial année 8Plafond salarial année 9Plafond salarial année 10Non-échange année 2Non-échange année 3Non-échange année 4Non-échange année 5Non-échange année 6Non-échange année 7Non-échange année 8Non-échange année 9Non-échange année 10Lien
Adam ScheelUtica Comets (NJD)G251999-05-01USANo192 Lbs6 ft3NoNoN/ANoNo1FalseFalsePro & Farm925,000$648,454$0$0$No---------------------------Lien
Anthony AngelloUtica Comets (NJD)RW281996-03-06USANo210 Lbs6 ft5NoNoN/ANoNo22024-05-19FalseFalsePro & Farm775,000$543,299$0$0$No775,000$--------775,000$--------No--------Lien
Brian PinhoUtica Comets (NJD)C291995-05-11USANo190 Lbs6 ft1NoNoN/ANoNo12024-05-19FalseFalsePro & Farm775,000$543,299$0$0$No---------------------------Lien
Cameron GaunceUtica Comets (NJD)D341990-03-19CANNo194 Lbs6 ft1YesNoAssign ManuallyNoNo42024-08-21FalseFalsePro & Farm1,999,999$1,402,061$0$0$No1,999,999$1,999,999$1,999,999$------600,000$600,000$600,000$------NoNoNo------Lien
Corey AndonovskiUtica Comets (NJD)RW251999-03-26CANYes195 Lbs6 ft1NoNoAssign ManuallyNoNo12024-08-20FalseFalsePro & Farm925,000$648,454$0$0$No---------------------------Lien
Dalton SmithUtica Comets (NJD)LW331991-09-14CANYes206 Lbs6 ft2NoNoAssign ManuallyNoNo12024-08-20FalseFalsePro & Farm775,000$543,299$0$0$No---------------------------Lien
Dan RenoufUtica Comets (NJD)D301994-06-01CANNo198 Lbs6 ft1YesNoAssign ManuallyNoNo42024-08-21FalseFalsePro & Farm1,999,999$1,402,061$0$0$No1,999,999$1,999,999$1,999,999$------600,000$600,000$600,000$------NoNoNo------Lien
Dillon HeatheringtonUtica Comets (NJD)D291995-05-09CANNo215 Lbs6 ft4YesNoAssign ManuallyNoNo12024-08-21FalseFalsePro & Farm1,999,999$1,402,061$0$0$No---------------------------Lien
Guillaume BriseboisUtica Comets (NJD)D271997-07-21CANYes175 Lbs6 ft2NoNoN/ANoNo22024-05-19FalseFalsePro & Farm775,000$543,299$0$0$No775,000$--------775,000$--------No--------Lien
Hudson FaschingUtica Comets (NJD)RW291995-07-28USANo209 Lbs6 ft3YesNoAssign ManuallyNoNo32024-08-21FalseFalsePro & Farm995,000$697,526$0$0$No995,000$995,000$-------600,000$600,000$-------NoNo-------Lien
James MalatestaUtica Comets (NJD)LW212003-05-31CANYes191 Lbs5 ft9NoNoAssign ManuallyNoNo32024-08-20FalseFalsePro & Farm862,500$604,639$0$0$No862,500$862,500$-------600,000$600,000$-------NoNo-------Lien
Jonah GadjovichUtica Comets (NJD)LW/RW251998-12-10CANYes209 Lbs6 ft2NoNoN/ANoNo1FalseFalsePro & Farm832,500$583,608$0$0$No---------------------------Lien
Kevin ConnautonUtica Comets (NJD)D341990-02-23CANNo205 Lbs6 ft2YesNoAssign ManuallyNoNo42024-08-21FalseFalsePro & Farm1,999,999$1,402,061$0$0$No1,999,999$1,999,999$1,999,999$------600,000$600,000$600,000$------NoNoNo------Lien
Logan ShawUtica Comets (NJD)C/RW311992-10-05CANNo208 Lbs6 ft3NoNoN/ANoNo3FalseFalsePro & Farm1,999,999$1,402,061$0$0$No1,999,999$1,999,999$-------600,000$600,000$-------NoNo-------Lien
Mark FriedmanUtica Comets (NJD)D281995-12-25CANNo185 Lbs5 ft11YesNoAssign ManuallyNoNo32024-08-21FalseFalsePro & Farm1,999,999$1,402,061$0$0$No1,999,999$1,999,999$-------600,000$600,000$-------NoNo-------Lien
Mark PysykUtica Comets (NJD)D321992-01-11CANNo198 Lbs6 ft1YesNoAssign Manually2024-02-19NoNo12024-08-21FalseFalsePro & Farm975,000$683,505$0$0$No---------------------------Lien
Matej MachovskyUtica Comets (NJD)G311993-07-25CZENo187 Lbs6 ft2NoNoAssign ManuallyNoNo12024-09-23FalseFalsePro & Farm700,000$490,722$0$0$No---------------------------
Matthew KniesUtica Comets (NJD)LW212002-10-17USAYes217 Lbs6 ft3NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm925,000$648,454$0$0$No925,000$--------600,000$--------No--------Lien
Nikolas BrouillardUtica Comets (NJD)D291995-02-07CANNo168 Lbs5 ft10NoNoN/ANoNo1FalseFalsePro & Farm925,000$648,454$0$0$No---------------------------Lien
Ryder RolstonUtica Comets (NJD)RW222001-10-31USAYes175 Lbs6 ft1NoNoAssign ManuallyNoNo22024-08-20FalseFalsePro & Farm867,500$608,144$0$0$No867,500$--------600,000$--------No--------Lien
Spencer SmallmanUtica Comets (NJD)RW281996-09-09CANNo198 Lbs6 ft1NoNoN/ANoNo3FalseFalsePro & Farm975,000$683,505$0$0$No975,000$975,000$-------600,000$600,000$-------NoNo-------Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
2128.14196 Lbs6 ft22.101,190,833$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jonah GadjovichLogan ShawAnthony Angello38122
2James MalatestaBrian PinhoHudson Fasching30122
3Matthew KniesCorey Andonovski22122
4Ryder RolstonSpencer SmallmanAnthony Angello10122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin ConnautonMark Pysyk38122
2Nikolas BrouillardMark Friedman30122
3Dillon Heatherington22122
4Mark FriedmanDan Renouf10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jonah GadjovichLogan ShawHudson Fasching60122
2Brian PinhoHudson Fasching40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin ConnautonMark Pysyk60122
2Nikolas BrouillardMark Friedman40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
1Logan ShawJonah Gadjovich60122
2Brian Pinho40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin ConnautonNikolas Brouillard60122
2Dillon Heatherington40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
1Logan Shaw60122Kevin ConnautonNikolas Brouillard60122
2Brian Pinho40122Dillon HeatheringtonMark Friedman40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
1Logan ShawJonah Gadjovich60122
2Brian Pinho40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Kevin ConnautonMark Pysyk60122
2Nikolas BrouillardMark Friedman40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jonah GadjovichLogan ShawHudson FaschingKevin ConnautonMark Friedman
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jonah GadjovichLogan ShawHudson FaschingKevin ConnautonMark Friedman
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Corey Andonovski, Ryder Rolston, Corey Andonovski, Ryder RolstonCorey Andonovski
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
, Mark Friedman, Nikolas Brouillard, Mark Friedman
Tirs de pénalité
Jonah Gadjovich, Logan Shaw, Matthew Knies, Hudson Fasching, Spencer Smallman
Gardien
#1 : Matej Machovsky, #2 : Adam Scheel


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 Senators11000000312000000000001100000031221.00035800581916231308270248611210153133.33%40100.00%049064076.56%29441271.36%23630577.38%886715314104243151
2Bridgeport Islanders2200000012111110000007071100000051441.0001223350158191629130827024861953335300.00%9188.89%049064076.56%29441271.36%23630577.38%886715314104243151
3Calgary Wranglers11000000606110000006060000000000021.00061016015819162463082702486761117300.00%30100.00%149064076.56%29441271.36%23630577.38%886715314104243151
4Chicago Wolves1010000012-1000000000001010000012-100.00012300581916217308270248623510213133.33%40100.00%049064076.56%29441271.36%23630577.38%886715314104243151
5Cleveland Monsters11000000321110000003210000000000021.000369005819162223082702486192138000%4175.00%049064076.56%29441271.36%23630577.38%886715314104243151
6Hartford Wolf Pack22000000707000000000002200000070741.000713200258191627530827024862110646400.00%30100.00%049064076.56%29441271.36%23630577.38%886715314104243151
7LeHigh Valley Phantoms11000000413110000004130000000000021.0004812005819162413082702486165824000%40100.00%049064076.56%29441271.36%23630577.38%886715314104243151
8Manitoba Moose11000000606000000000001100000060621.000611170158191624030827024866162111100.00%30100.00%049064076.56%29441271.36%23630577.38%886715314104243151
9Milwaukee Admirals220000001111000000000000220000001111041.0001120310158191628230827024861724424125.00%20100.00%049064076.56%29441271.36%23630577.38%886715314104243151
10Ontario Reign21000010624110000003031000001032141.00069150158191627130827024862841653400.00%7271.43%049064076.56%29441271.36%23630577.38%886715314104243151
11Providence Bruins22000000826110000005051100000032141.0008152301581916269308270248620322525120.00%10190.00%149064076.56%29441271.36%23630577.38%886715314104243151
12San Jose Barracuda1010000013-2000000000001010000013-200.000123005819162103082702486184214300.00%10100.00%049064076.56%29441271.36%23630577.38%886715314104243151
13Syracuse Crunch11000000514110000005140000000000021.00051015005819162383082702486100822000%40100.00%049064076.56%29441271.36%23630577.38%886715314104243151
14Texas Stars11000000312110000003120000000000021.00036900581916225308270248616410126116.67%5180.00%049064076.56%29441271.36%23630577.38%886715314104243151
15Toronto Marlies2200000013013110000008081100000050541.0001325380258191628630827024861822538000%100100.00%049064076.56%29441271.36%23630577.38%886715314104243151
16Wilkes-Barre/Scranton Penguins32100000532321000005320000000000040.667510150158191628230827024866412344312325.00%150100.00%049064076.56%29441271.36%23630577.38%886715314104243151
Total2420300010942074121110000049841129200010451233420.87594175269011581916282630827024863136721846351917.65%88693.18%249064076.56%29441271.36%23630577.38%886715314104243151
_Since Last GM Reset2420300010942074121110000049841129200010451233420.87594175269011581916282630827024863136721846351917.65%88693.18%249064076.56%29441271.36%23630577.38%886715314104243151
_Vs Conference161420000064115387100000345298710000030624280.8756412218608581916257030827024862084516231731722.58%66296.97%149064076.56%29441271.36%23630577.38%886715314104243151
_Vs Division67100000294253410000018117330000001138141.1672955840358191622243082702486597651278225.00%28196.43%149064076.56%29441271.36%23630577.38%886715314104243151

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
2442W29417526982631367218463011
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
2420300109420
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
121110000498
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
129200104512
Derniers 10 matchs
WLOTWOTL SOWSOL
810010
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
51917.65%88693.18%2
Tirs en 1e périodeTirs en 2e périodeTirs en 3e périodeTirs en 4e périodeButs en 1e périodeButs en 2e périodeButs en 3e périodeButs en 4e période
30827024865819162
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
49064076.56%29441271.36%23630577.38%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
886715314104243151


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
12Wilkes-Barre/Scranton Penguins2Utica Comets3WSommaire du match
515Utica Comets4Hartford Wolf Pack0WSommaire du match
626Utica Comets5Bridgeport Islanders1WSommaire du match
943Utica Comets1Chicago Wolves2LSommaire du match
1159Cleveland Monsters2Utica Comets3WSommaire du match
1373Utica Comets6Manitoba Moose0WSommaire du match
1590Wilkes-Barre/Scranton Penguins0Utica Comets2WSommaire du match
17107Utica Comets6Milwaukee Admirals0WSommaire du match
20120Utica Comets3Providence Bruins2WSommaire du match
21126Bridgeport Islanders0Utica Comets7WSommaire du match
24152LeHigh Valley Phantoms1Utica Comets4WSommaire du match
28179Providence Bruins0Utica Comets5WSommaire du match
30201Wilkes-Barre/Scranton Penguins1Utica Comets0LSommaire du match
31208Utica Comets5Toronto Marlies0WSommaire du match
34226Utica Comets3Hartford Wolf Pack0WSommaire du match
37243Toronto Marlies0Utica Comets8WSommaire du match
40267Calgary Wranglers0Utica Comets6WSommaire du match
42290Utica Comets3Ontario Reign2WXXSommaire du match
43300Ontario Reign0Utica Comets3WSommaire du match
46322Utica Comets5Milwaukee Admirals1WSommaire du match
47333Syracuse Crunch1Utica Comets5WSommaire du match
50355Utica Comets1San Jose Barracuda3LSommaire du match
52363Utica Comets3Belleville Senators1WSommaire du match
55374Texas Stars1Utica Comets3WSommaire du match
59397Charlotte Checkers-Utica Comets-
61411Utica Comets-Charlotte Checkers-
63427Bakersfield Condors-Utica Comets-
65442Utica Comets-Tucson Roadrunners-
68460Henderson Silver Knights-Utica Comets-
72486Utica Comets-Laval Rocket-
73496Belleville Senators-Utica Comets-
76511Utica Comets-LeHigh Valley Phantoms-
78527Laval Rocket-Utica Comets-
86555Syracuse Crunch-Utica Comets-
89574Utica Comets-Hershey Bears-
90587Chicago Wolves-Utica Comets-
92604Utica Comets-Manitoba Moose-
94617Hershey Bears-Utica Comets-
98643Grand Rapids Griffins-Utica Comets-
100661Utica Comets-Providence Bruins-
102675Coachella Valley Firebirds-Utica Comets-
103691Utica Comets-Chicago Wolves-
105705Wilkes-Barre/Scranton Penguins-Utica Comets-
108721Utica Comets-Texas Stars-
109737Rockford IceHogs-Utica Comets-
112756Utica Comets-Rochester Americans-
114770Bridgeport Islanders-Utica Comets-
116789Utica Comets-Syracuse Crunch-
118801Utica Comets-Colorado Eagles-
119808Utica Comets-Iowa Wild-
121815Abbotsford Canucks-Utica Comets-
126841San Diego Gulls-Utica Comets-
127858Utica Comets-Bridgeport Islanders-
129872Rochester Americans-Utica Comets-
145895Utica Comets-LeHigh Valley Phantoms-
146907LeHigh Valley Phantoms-Utica Comets-
149922Utica Comets-Wilkes-Barre/Scranton Penguins-
150937Utica Comets-Springfield Thunderbirds-
152950Manitoba Moose-Utica Comets-
154963Utica Comets-Hartford Wolf Pack-
156973Milwaukee Admirals-Utica Comets-
157980Utica Comets-Wilkes-Barre/Scranton Penguins-
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
1621001San Diego Gulls-Utica Comets-
1631010Utica Comets-Rochester Americans-
1681026Utica Comets-Grand Rapids Griffins-
1701039Utica Comets-Chicago Wolves-
1711041Utica Comets-Bridgeport Islanders-
1731056Providence Bruins-Utica Comets-
1751076Utica Comets-Toronto Marlies-
1771087Cleveland Monsters-Utica Comets-
1841117Hartford Wolf Pack-Utica Comets-
1931149Hartford Wolf Pack-Utica Comets-



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets5025
Assistance13,6596,832
Assistance PCT56.91%56.93%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
24 1708 - 56.92% 83,952$1,007,425$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursPlafond Salariale total des joueursSalaire des entraineurs
757,424$ 2,500,750$ 1,332,702$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
12,890$ 757,424$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
2,014,850$ 136 12,890$ 1,753,040$




Utica Comets 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

Utica Comets 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

Utica Comets 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

Utica Comets 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

Utica Comets 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