Votre version du STHS est obsolète! Veuillez mettre à jour votre version du STHS!
Connexion

Utica
GP: 82 | W: 45 | L: 33 | OTL: 4 | P: 94
GF: 266 | GA: 295 | PP%: 16.46% | PK%: 80.48%
DG: Guillaume Fortin | Morale : 50 | Moyenne d’équipe : N/A
La résolution de votre navigateur est trop petite pour cette page. Plusieurs informations sont cachées pour garder la page lisible.

Centre de jeu
Utica
45-33-4, 94pts
5
FINAL
2 Charlotte
55-21-6, 116pts
Team Stats
W2StreakW1
22-17-2Home Record31-7-3
23-16-2Away Record24-14-3
3-5-2Last 10 Games7-3-0
3.24Buts par match 4.01
3.60Buts contre par match 2.90
16.46%Pourcentage en avantage numérique20.53%
80.48%Pourcentage en désavantage numérique84.55%
Springfield
44-33-5, 93pts
1
FINAL
4 Utica
45-33-4, 94pts
Team Stats
L3StreakW2
29-9-3Home Record22-17-2
15-24-2Away Record23-16-2
5-5-0Last 10 Games3-5-2
3.26Buts par match 3.24
2.93Buts contre par match 3.60
16.32%Pourcentage en avantage numérique16.46%
84.36%Pourcentage en désavantage numérique80.48%
Meneurs d'équipe
Buts
Jonathan Dahlen
34
Passes
Dylan Sikura
51
Points
Dylan Sikura
78
Plus/Moins
Andy Andreoff
5
Victoires
Devan Dubnyk
19
Pourcentage d’arrêts
Anders Lindback
0.919

Statistiques d’équipe
Buts pour
266
3.24 GFG
Tirs pour
2623
31.99 Avg
Pourcentage en avantage numérique
16.5%
54 GF
Début de zone offensive
40.4%
Buts contre
295
3.60 GAA
Tirs contre
2773
33.82 Avg
Pourcentage en désavantage numérique
80.5%%
65 GA
Début de la zone défensive
41.6%
Informations de l'équipe

Directeur généralGuillaume Fortin
EntraîneurDavid Quinn
DivisionAtlantique
ConférenceConference est
Capitaine
Assistant #1
Assistant #2


Informations de l’aréna

Capacité3,000
Assistance2,886
Billets de saison300


Informations de la formation

Équipe Pro18
Équipe Mineure21
Limite contact 39 / 50
Espoirs36


Historique d'équipe

Saison actuelle45-33-4 (94PTS)
Historique90-66-6 (0.556%)
Apparitions en séries éliminatoires 0
Historique en séries éliminatoires (W-L)-
Coupe Stanley0


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
1Alex PicardX100.00733473527546686474606364797368205000352720,000$
2Andy AndreoffXX100.00663481678668906898666662705546325000303600,000$
3Jayson MegnaXX100.0065279474777387656664666216561355000311800,000$
4Lauri KorpikoskiXXX100.00662986577772876675636659777763255000341900,000$
5Vladimir ZharkovXX100.00542695627780946973626860826658295000332950,000$
6Dylan Sikura (R)XXX100.00693099857772846770666771755252545000261500,000$
7John Hayden (R)XX100.00856074779074816870666868755252575000261700,000$
8Jonathan Dahlen (R)XX100.00633095808080857270697466754242735000232800,000$
9Keith AulieX100.00686367608670934925495088496762255000323750,000$
10Jan RuttaX100.008233807487828753505346877565594850003032,000,000$
11Kevin GravelX100.00723178709376865150525084775955525000294775,000$
12Brandon DavidsonX100.00693280708785885250515088776052405000294890,000$
13Fredrik ClaessonX100.00793181798584855350515084725552575000281600,000$
Rayé
1Andrew LaddX100.008441645780577668736670718075722050003511,000,000$
2Logan Shaw (R)XX100.00593098718771916786666779775959535000281500,000$
3Christian FolinX100.00693776678480734450454283705953425000301600,000$
MOYENNE D’ÉQUIPE100.0070368369837385616459607469615741500
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
1Robin Lehner100.00707587938293929490908362623950002921,500,000$
2Devan Dubnyk100.0063799297849193919284817876275000351800,000$
Rayé
MOYENNE D’ÉQUIPE100.006777909583929393918782706933500
Nom de l’entraîneur PH DF OF PD EX LD PO CNT Âge Contrat Salaire
David Quinn68797771848476USA562600,000$


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
1Dylan SikuraUtica (NJ )C/LW/RW81275178-2180311722406920511.25%16151118.66617234824610141335348.29%117000001.03010003110
2Jonathan DahlenUtica (NJ )LW/RW78343670-310016832777919712.27%9144018.47111324752740001766349.69%16300000.9702000725
3Logan ShawUtica (NJ )C/RW742037570807153228501418.77%26150320.3269155220610162443453.87%200100000.7613000172
4John HaydenUtica (NJ )C/RW74253156-473152101072285714310.96%8126417.095914592200002605143.96%101000100.8900102717
5Brandon DavidsonUtica (NJ )D80104050-8455749311739788.55%147177222.16358431880113265110.00%000100.5600001013
6Zach Aston-ReeseNew JerseyLW/RW472123446511512952168419712.50%1198320.9339123616201171272145.45%16500000.8901111711
7Andy AndreoffUtica (NJ )C/LW8216274355315771331546913310.39%20116214.1711210710000241058.73%110500000.7401102114
8Jayson MegnaUtica (NJ )C/RW82122739-131203368148461098.11%19102012.450114440000463048.26%23000000.7600000120
9Lauri KorpikoskiUtica (NJ )C/LW/RW82172037-22605168135299312.59%19116814.250112230003645157.03%38400000.6322000232
10Kevin GravelUtica (NJ )D8210273717401325911624538.62%120159919.51325512080002170100.00%000000.4600000131
11Andrew LaddUtica (NJ )LW71171633-310820252471534710511.11%17138319.4857123323000021792049.66%14500010.4804121413
12Fredrik ClaessonUtica (NJ )D6982533-268101236711541946.96%139161923.474812632260000218110.00%000000.4100001131
13Vladimir ZharkovUtica (NJ )LW/RW82161632-5801748160529810.00%14108413.23112151150000161055.42%8300000.5913000111
14Keith AulieUtica (NJ )D8171926494201005469265410.14%117138617.1212324890111136200.00%000000.3800103005
15Josh JoorisNew JerseyC/RW22518233205396222438.06%237417.030771371000012153.94%55800001.2301000021
16Christian FolinUtica (NJ )D7811920-454074615115311.96%93119515.320227510000111000.00%000000.3300000000
17Madison BoweyNew JerseyD2341418-620041255113377.84%3156224.443253874000087110.00%000000.6400000021
18Jan RuttaUtica (NJ )D2941115045551344712218.51%5669724.0722432100000081010.00%000000.4300001111
19Alex PicardUtica (NJ )LW819514-225210662885225910.59%176938.56000020000141145.00%4000000.4000101101
Statistiques d’équipe totales ou en moyenne1298263462725-55821115148913912604753179110.10%8812242417.2854981526052608235312059421951.87%705400210.654186313384239
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
1Devan DubnykUtica (NJ )31191010.9062.99180821909610020.87583033230
2Robin LehnerUtica (NJ )2113710.8983.09124121646260111.00032118301
3Anders LindbackNew Jersey2413920.9192.89145380708610000.7508243301
Statistiques d’équipe totales ou en moyenne76452640.9082.9945031222242448013197554832


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 Waiver Possible Contrat Type Salaire actuel Salaire 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
Alex PicardUtica (NJ )LW351985-10-09No198 Lbs6 ft2NoNoNoNo2Pro & Farm720,000$0$0$No720,000$
Andrew LaddUtica (NJ )LW351985-12-12No213 Lbs6 ft2NoNoNoNo1Pro & Farm1,000,000$0$0$No
Andy AndreoffUtica (NJ )C/LW301991-05-17No214 Lbs6 ft1NoNoNoNo3Pro & Farm600,000$0$0$No600,000$600,000$Lien
Brandon DavidsonUtica (NJ )D291991-08-21No219 Lbs6 ft2NoNoNoNo4Pro & Farm890,000$0$0$No890,000$890,000$890,000$Lien
Christian FolinUtica (NJ )D301991-02-09No219 Lbs6 ft3NoNoNoNo1Pro & Farm600,000$0$0$NoLien
Devan DubnykUtica (NJ )G351986-05-04 05:37:02No221 Lbs6 ft6NoNoNoNo1Pro & Farm800,000$0$0$No
Dylan SikuraUtica (NJ )C/LW/RW261995-06-01 21:26:40Yes170 Lbs5 ft11NoNoNoNo1Pro & Farm500,000$0$0$NoLien
Fredrik ClaessonUtica (NJ )D281992-11-24No198 Lbs6 ft1NoNoNoNo1Pro & Farm600,000$0$0$NoLien
Jan RuttaUtica (NJ )D301990-07-29No201 Lbs6 ft3NoNoNoNo3Pro & Farm2,000,000$0$0$No2,000,000$2,000,000$Lien
Jayson MegnaUtica (NJ )C/RW311990-02-01No197 Lbs6 ft1NoNoNoNo1Pro & Farm800,000$0$0$NoLien
John HaydenUtica (NJ )C/RW261995-02-14 21:29:35Yes223 Lbs6 ft3NoNoNoNo1Pro & Farm700,000$0$0$NoLien
Jonathan DahlenUtica (NJ )LW/RW231997-12-20 21:32:48Yes180 Lbs5 ft11NoNoNoNo2Pro & Farm800,000$0$0$No800,000$Lien
Keith AulieUtica (NJ )D321989-06-11No237 Lbs6 ft6NoNoNoNo3Pro & Farm750,000$0$0$No750,000$750,000$Lien
Kevin GravelUtica (NJ )D291992-03-06No214 Lbs6 ft4NoNoNoNo4Pro & Farm775,000$0$0$No775,000$775,000$775,000$Lien
Lauri KorpikoskiUtica (NJ )C/LW/RW341986-07-28No203 Lbs6 ft1NoNoNoNo1Pro & Farm900,000$0$0$No
Logan ShawUtica (NJ )C/RW281992-10-05 21:35:49Yes208 Lbs6 ft3NoNoNoNo1Pro & Farm500,000$0$0$NoLien
Robin LehnerUtica (NJ )G291991-07-24 07:23:49No250 Lbs6 ft4NoNoNoNo2Pro & Farm1,500,000$0$0$No1,500,000$Lien
Vladimir ZharkovUtica (NJ )LW/RW331988-01-10No210 Lbs6 ft1NoNoNoNo2Pro & Farm950,000$0$0$No950,000$Lien
Nombre de joueursÂge moyenPoids moyenTaille moyenneContrat moyenSalaire moyen 1e année
1830.17210 Lbs6 ft21.89854,722$



Attaque à 5 contre 5
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jonathan Dahlen32122
2Dylan SikuraJohn HaydenVladimir Zharkov32122
3Lauri KorpikoskiAndy AndreoffJayson Megna31122
4Alex Picard5122
Défense à 5 contre 5
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaFredrik Claesson40122
2Brandon DavidsonKevin Gravel30122
3Keith AulieAlex Picard20122
4Jan RuttaFredrik Claesson10122
Attaque en avantage numérique
Ligne #Ailier gaucheCentreAilier droit% tempsPHYDFOF
1Jonathan Dahlen60122
2Dylan SikuraJohn HaydenVladimir Zharkov40122
Défense en avantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaFredrik Claesson60122
2Brandon DavidsonKevin Gravel40122
Attaque à 4 en désavantage numérique
Ligne #CentreAilier% tempsPHYDFOF
160122
2Jonathan DahlenJohn Hayden40122
Défense à 4 en désavantage numérique
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaFredrik Claesson60122
2Brandon DavidsonKevin Gravel40122
3 joueurs en désavantage numérique
Ligne #Ailier% tempsPHYDFOFDéfenseDéfense% tempsPHYDFOF
160122Jan RuttaFredrik Claesson60122
240122Brandon DavidsonKevin Gravel40122
Attaque à 4 contre 4
Ligne #CentreAilier% tempsPHYDFOF
160122
2Jonathan DahlenJohn Hayden40122
Défense à 4 contre 4
Ligne #DéfenseDéfense% tempsPHYDFOF
1Jan RuttaFredrik Claesson60122
2Brandon DavidsonKevin Gravel40122
Attaque dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jonathan DahlenJan RuttaFredrik Claesson
Défense dernière minute
Ailier gaucheCentreAilier droitDéfenseDéfense
Jonathan DahlenJan RuttaFredrik Claesson
Attaquants supplémentaires
Normal Avantage numériqueDésavantage numérique
Andy Andreoff, Lauri Korpikoski, Jayson MegnaAndy Andreoff, Lauri KorpikoskiJayson Megna
Défenseurs supplémentaires
Normal Avantage numériqueDésavantage numérique
Keith Aulie, Brandon Davidson, Kevin GravelKeith AulieBrandon Davidson, Kevin Gravel
Tirs de pénalité
, , Jonathan Dahlen, John Hayden, Dylan Sikura
Gardien
#1 : Devan Dubnyk, #2 : Robin Lehner


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
1Abbotsford2110000059-4110000003211010000027-520.5005101500849781588866908829396921173710220.00%5180.00%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
2Bakersfield2110000048-41010000016-51100000032120.50046100084978154586690882939771931427114.29%13376.92%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
3Charlotte632000102019131200000511-632000010158780.66720335300849781520086690882939211101861131218.33%32778.13%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
4Cleveland514000001528-1331200000812-420200000716-920.200152439108497815160866908829391696445911915.26%14471.43%11529300550.88%1557309050.39%665133749.74%1891126419896331070529
5Grand Rapids422000001113-22110000078-12110000045-140.5001120310084978151468669088293912337267020420.00%11190.91%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
6Hartford633000001917233000000146830300000511-660.5001931500084978151688669088293917656649426519.23%27485.19%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
7Hershey6320010024240311001001112-1321000001312170.58324456901849781519586690882939216785611321314.29%27485.19%11529300550.88%1557309050.39%665133749.74%1891126419896331070529
8Iowa22000000642110000003211100000032141.00061218008497815658669088293952151639700.00%8187.50%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
9Laval422000001614220200000710-32200000094540.5001629451084978151338669088293914251409222627.27%13376.92%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
10Lehigh Valley64000011251963200001012843200000113112110.91725446900849781523486690882939227727811230620.00%28582.14%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
11Manitoba2110000089-11010000057-21100000032120.500816240084978157386690882939581918399222.22%6183.33%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
12Milwaukee2110000069-31010000059-41100000010120.500611170184978156986690882939691720409111.11%10640.00%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
13Ontario21100000511-61010000019-81100000042220.50059140084978156286690882939471016361000.00%8362.50%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
14Providence440000001495220000007432200000075281.0001422360084978151258669088293914032346524520.83%17288.24%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
15Rochester40300100613-72010010036-32020000037-410.125611171084978151008669088293913439436913215.38%150100.00%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
16Rockford31200000517-1221100000512-71010000005-520.333571200849781570866908829391374650507114.29%13469.23%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
17San Diego20100001810-21010000034-11000000156-110.250813210084978156286690882939741819275120.00%7442.86%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
18San Jose2110000067-1110000005411010000013-220.500611170084978156486690882939752314369222.22%7185.71%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
19Springfield21000010844110000004131000001043141.000814220084978155786690882939742114509333.33%6266.67%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
20Texas41300000915-61100000043130300000512-720.25091625008497815116866908829391515846721119.09%20385.00%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
21Toronto43100000131122110000067-12200000074360.750132336008497815152866908829399425248518316.67%11281.82%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
22Tucson22000000835110000004221100000041341.00081422008497815628669088293961111827700.00%7185.71%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
23Wilkes-Barre/Scranton63201000252233110100011110321000001411380.66725477200849781517786690882939197637211723417.39%28389.29%01529300550.88%1557309050.39%665133749.74%1891126419896331070529
Total82413301232266295-2941201701210134156-2241211600022132139-7940.573266468734328497815262386690882939277389684715163285416.46%3336580.48%21529300550.88%1557309050.39%665133749.74%1891126419896331070529
_Since Last GM Reset82413301232266295-2941201701210134156-2241211600022132139-7940.573266468734328497815262386690882939277389684715163285416.46%3336580.48%21529300550.88%1557309050.39%665133749.74%1891126419896331070529
_Vs Conference55282101221188189-1281311012109195-42715100001197943650.591188329517318497815179086690882939182961856810212284017.54%2233584.30%21529300550.88%1557309050.39%665133749.74%1891126419896331070529
_Vs Division2916901121108110-2158401110564971485000115261-9400.690108191299118497815934866908829399853333155271191915.97%1242083.87%21529300550.88%1557309050.39%665133749.74%1891126419896331070529

Total pour les joueurs
Matchs jouésPointsSéquenceButsPassesPointsTirs pourTirs contreTirs bloquésMinutes de pénalitésMises en échecButs en filet désertBlanchissages
8294W226646873426232773896847151632
Tous les matchs
GPWLOTWOTL SOWSOLGFGA
8241331232266295
Matchs locaux
GPWLOTWOTL SOWSOLGFGA
4120171210134156
Matchs extérieurs
GPWLOTWOTL SOWSOLGFGA
4121160022132139
Derniers 10 matchs
WLOTWOTL SOWSOL
350101
Tentatives en avantage numériqueButs en avantage numérique% en avantage numériqueTentatives en désavantage numériqueButs contre en désavantage numérique% en désavantage numériqueButs pour en désavantage numérique
3285416.46%3336580.48%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
866908829398497815
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
1529300550.88%1557309050.39%665133749.74%
Temps avec la rondelle
En zone offensiveContrôle en zone offensiveEn zone défensiveContrôle en zone défensiveEn zone neutreContrôle en zone neutre
1891126419896331070529


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
1 - 2022-11-251Utica0Texas4ALSommaire du match
4 - 2022-11-2617Utica6Lehigh Valley4AWSommaire du match
5 - 2022-11-2724Wilkes-Barre/Scranton3Utica4BWSommaire du match
9 - 2022-11-2944Charlotte1Utica2BWSommaire du match
11 - 2022-11-3054Utica5Charlotte4AWXXSommaire du match
13 - 2022-12-0163Cleveland1Utica3BWSommaire du match
16 - 2022-12-0281Hartford3Utica7BWSommaire du match
18 - 2022-12-0393Utica2Hartford3ALSommaire du match
19 - 2022-12-04103Utica7Wilkes-Barre/Scranton2AWSommaire du match
22 - 2022-12-05114Lehigh Valley3Utica4BWSommaire du match
24 - 2022-12-06129Hershey3Utica5BWSommaire du match
25 - 2022-12-07135Utica4Hershey2AWSommaire du match
28 - 2022-12-08152Grand Rapids6Utica2BLSommaire du match
32 - 2022-12-10169Utica4Lehigh Valley3AWSommaire du match
34 - 2022-12-11177Hartford1Utica4BWSommaire du match
37 - 2022-12-13196Charlotte3Utica1BLSommaire du match
39 - 2022-12-14209Utica0Rockford5ALSommaire du match
41 - 2022-12-15219Utica3Lehigh Valley4ALXXSommaire du match
42 - 2022-12-15227Cleveland5Utica3BLSommaire du match
46 - 2022-12-17244San Diego4Utica3BLSommaire du match
48 - 2022-12-18256Utica1Milwaukee0AWSommaire du match
50 - 2022-12-19270Toronto3Utica4BWSommaire du match
52 - 2022-12-20276Utica4Laval2AWSommaire du match
54 - 2022-12-21289Utica3Iowa2AWSommaire du match
55 - 2022-12-22297Ontario9Utica1BLSommaire du match
58 - 2022-12-23314Utica1San Jose3ALSommaire du match
60 - 2022-12-24323Iowa2Utica3BWSommaire du match
62 - 2022-12-25334Utica3Grand Rapids1AWSommaire du match
64 - 2022-12-26345Bakersfield6Utica1BLSommaire du match
66 - 2022-12-27358Utica4Ontario2AWSommaire du match
68 - 2022-12-28365Utica4Tucson1AWSommaire du match
70 - 2022-12-29376Lehigh Valley1Utica3BWSommaire du match
74 - 2022-12-31395Hershey4Utica2BLSommaire du match
78 - 2023-01-02415Abbotsford2Utica3BWSommaire du match
80 - 2023-01-03424Utica2Texas3ALSommaire du match
82 - 2023-01-04438Laval2Utica1BLSommaire du match
84 - 2023-01-05447Utica3Manitoba2AWSommaire du match
87 - 2023-01-07463Hershey5Utica4BLXSommaire du match
90 - 2023-01-08478Utica3Cleveland5ALSommaire du match
92 - 2023-01-09486Utica4Providence3AWSommaire du match
93 - 2023-01-10492Lehigh Valley4Utica5BWXXSommaire du match
96 - 2023-01-11506Utica6Hershey10ALSommaire du match
98 - 2023-01-12517Milwaukee9Utica5BLSommaire du match
100 - 2023-01-13529Utica4Cleveland11ALSommaire du match
101 - 2023-01-14538Utica2Abbotsford7ALSommaire du match
103 - 2023-01-15546Rockford2Utica3BWSommaire du match
106 - 2023-01-16563Toronto4Utica2BLSommaire du match
108 - 2023-01-17570Utica4Springfield3AWXXSommaire du match
110 - 2023-01-18578Utica3Hershey0AWSommaire du match
111 - 2023-01-19588Cleveland6Utica2BLSommaire du match
115 - 2023-01-21602Utica3Providence2AWSommaire du match
117 - 2023-01-22611Grand Rapids2Utica5BWSommaire du match
119 - 2023-01-23618Utica3Bakersfield2AWSommaire du match
123 - 2023-01-25637Providence2Utica3BWSommaire du match
125 - 2023-01-26650Utica5Laval2AWSommaire du match
126 - 2023-01-26659Laval8Utica6BLSommaire du match
131 - 2023-01-29681Manitoba7Utica5BLSommaire du match
135 - 2023-01-31704Rockford10Utica2BLSommaire du match
137 - 2023-02-01711Utica3Toronto1AWSommaire du match
140 - 2023-02-02727Utica3Texas5ALSommaire du match
141 - 2023-02-03732Tucson2Utica4BWSommaire du match
145 - 2023-02-05751Rochester4Utica2BLSommaire du match
Date limite d’échanges --- Les échanges ne peuvent plus se faire après la simulation de cette journée!
148 - 2023-02-06771San Jose4Utica5BWSommaire du match
150 - 2023-02-07783Utica1Grand Rapids4ALSommaire du match
154 - 2023-02-09795Wilkes-Barre/Scranton4Utica5BWXSommaire du match
156 - 2023-02-10809Utica4Toronto3AWSommaire du match
158 - 2023-02-11820Texas3Utica4BWSommaire du match
160 - 2023-02-12832Utica1Hartford4ALSommaire du match
163 - 2023-02-14843Providence2Utica4BWSommaire du match
164 - 2023-02-14851Utica4Wilkes-Barre/Scranton2AWSommaire du match
167 - 2023-02-16867Hartford2Utica3BWSommaire du match
168 - 2023-02-16872Utica3Wilkes-Barre/Scranton7ALSommaire du match
170 - 2023-02-17879Utica2Hartford4ALSommaire du match
173 - 2023-02-19893Wilkes-Barre/Scranton4Utica2BLSommaire du match
175 - 2023-02-20904Utica5Charlotte2AWSommaire du match
176 - 2023-02-20907Utica1Rochester3ALSommaire du match
180 - 2023-02-22919Utica5San Diego6ALXXSommaire du match
182 - 2023-02-23925Rochester2Utica1BLXSommaire du match
185 - 2023-02-25939Utica2Rochester4ALSommaire du match
188 - 2023-02-26950Charlotte7Utica2BLSommaire du match
190 - 2023-02-27958Utica5Charlotte2AWSommaire du match
195 - 2023-03-02974Springfield1Utica4BWSommaire du match



Capacité de l’aréna - Tendance du prix des billets - %
Niveau 1Niveau 2
Capacité20001000
Prix des billets4124
Assistance78,86239,454
Assistance PCT96.17%96.23%

Revenu
Matchs à domicile restantsAssistance moyenne - %Revenu moyen par matchRevenu annuel à ce jourCapacitéPopularité de l’équipe
0 2886 - 96.19% 137,933$5,655,253$3000100

Dépenses
Dépenses annuelles à ce jourSalaire total des joueursSalaire total moyen des joueursSalaire des entraineurs
2,031,800$ 1,538,500$ 1,538,500$ 0$
Plafond salarial par jourPlafond salarial à ce jourJoueurs Inclus dans le plafond salarialJoueurs exclut du plafond Salarial
7,770$ 1,431,818$ 0 0

Estimation
Revenus de la saison estimésJours restants de la saisonDépenses par jourDépenses de la saison estimées
0$ 0 10,801$ 0$




Utica 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
1Vladislav Kamenev1125874132203610832651211.33%14242421.65142842100426128455.8321.0902
2Micheal Ferland1344680126412819013642610.80%18260019.4116264290000124054.4200.9702
3Christian Fischer1564474118-81323102264609.57%24294618.8910263610400046447.8800.8002
4Alan Quine1624866114-1040922125029.56%16295118.2214142810600028649.2100.7702
5Taylor Beck1566248110-16368813437216.67%50274417.59181432106000010450.5420.8000

Utica 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
1Ondrej Pavelec94563060.9182.67562112825030460600.75016
2Thomas Greiss52222460.9122.9930900215417420000.00%4

Utica 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
Saison régulière
2082353407303260269-941191603102133127641161804201127142-1590260456716057499807264986092183444283881484813903457120.58%3696582.38%31487305248.72%1479312147.39%655131149.96%1917128119726221072533
2082353407303260269-941191603102133127641161804201127142-1590260456716057499807264986092183444283881484813903457120.58%3696582.38%31487305248.72%1479312147.39%655131149.96%1917128119726221072533
Total Saison régulière164826602464532590-5882403402420268312-4482423200044264278-1418853293614686416819416210524617321816165878554617921694303265610816.46%66613080.48%43058601050.88%3114618050.39%1330267449.74%378225283978126621401059
Séries éliminatoires
Total Séries éliminatoires00000000000000.00%0.00%0.00%0.00%0.00%000000

Utica 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 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